Suicide is a leading cause of death in the United States. Historically, scientific inquiry has focused on psychological theory. However, more recent studies have started to shed light on complex biosignatures using MRI techniques, including task-based and resting-state functional MRI, brain morphometry, and diffusion tensor imaging. Here, we review recent research across these modalities, with a focus on participants with depression and Suicidal Thoughts and Behavior (STB). A PubMed search identified 149 articles specific to our population of study, and this was further refined to rule out more diffuse pathologies such as psychotic disorders and organic brain injury and illness. This left 69 articles which are reviewed in the current study. The collated articles reviewed point to a complex impairment showing atypical functional activation in areas associated with perception of reward, social/affective stimuli, top-down control, and reward-based learning. This is broadly supported by the atypical morphometric and diffusion-weighted alterations and, most significantly, in the network-based resting-state functional connectivity data that extrapolates network functions from well validated psychological paradigms using functional MRI analysis. We see an emerging picture of cognitive dysfunction evident in task-based and resting state fMRI and network neuroscience studies, likely preceded by structural changes best demonstrated in morphometric and diffusion-weighted studies. We propose a clinically-oriented chronology of the diathesis-stress model of suicide and link other areas of research that may be useful to the practicing clinician, while helping to advance the translational study of the neurobiology of suicide. SuicideMultiple general theories have been developed in an attempt to understand the risk factors, thoughts, distortions, cognitive/behavioral differences, atypical brain structures, systems and functions that distinguish suicidal individuals from those without past attempts, or a high risk. As clearly laid out in Van Heeringen’s book “the Neuroscience of Suicidal Behavior,”  five maiOur goal is to consider the current body of neuroimaging research on STBs  among those with Major Depressive Disorder (MDD) . Our goa2.A search on functional, structural, and diffusion-weighted MRI studies of the suicidal brain was performed in the search engine ‘PubMed’ for both original and review research articles that were published before December 2021. The literature search was conducted using the following terms in the title:((BOLD[Title]) OR (fMRI[Title]) OR  OR  OR (morphometry[Title]) OR (thickness[Title]) OR (surface area[Title]) OR (volume[Title]) OR (gyrification[Title]) OR (folding[Title]) OR (MRI[Title]) OR (DTI[Title]) OR (magnetic resonance imaging[Title]) OR (diffusion tensor imaging[Title]) OR (brain connectivity[Title]) OR (connectivity[Title]) OR (brain activation[Title]) OR  OR (neuroimaging[Title]) OR (spectroscopy[Title]) OR (white-matter[Title]) OR (gray-matter[Title]) OR  OR ) AND ((suicide[Title]) OR  OR  OR (suicide risk[Title]) OR (self-harm[Title]) OR ) NOT ((Inflammation[Title]) OR (Inflammatory[Title]) OR (Plasma[Title]) OR (Tumor[Title]) OR (Immunity[Title]) OR (habenula[Title]) OR (mRNA[Title]) OR (RNA[Title]) OR (DNA[Title]) OR (Gene[Title]) OR (Genetics[Title]) OR (Glucose[Title]) OR (Brain expression[Title]) OR (Pain[Title])). The search was performed without a time limit. This resulted in a total of 149 articles. The articles were further filtered through an inspection of the abstracts. A total of 80 articles that included studies focusing on patients with clinical conditions other than MDD, studies focusing on non-suicidal self-injury, and studies relating to neuroimaging modalities other than MRI  were excluded.3.A total of 69 research articles, focusing on STBs associated with depression, were identified, and reviewed in the current study –4.3.1.3.1.1.The task-based fMRI research in STBs depends on the ability of a participant to complete a task in real time, and thus, may be a more proximally clinically important difference amongst patients. Task-based fMRI studies of the suicidal brain have focused on six primary tasks according to Dr. Van Heeringen: (1) Decision Making/Reward-Based Learning; (2) Emotional Pain and Affect Regulation; (3) Sensitivity to Social Stressors; (4) Cognitive Control/Response Inhibition; (5) Hopelessness; and (6) Impulsivity and Aggression. Unfortunately, within these 6 domains, only the first 4 have functional neuroimaging data consistent with our focused limitations.3.1.1.1.increasing impulsivity with increased connectivity between these regions (Examining the fMRI activation differences during a learning task which requires participants to maximize rewards earned through a sequence of lever pulls (the Three-Armed Bandit Task), Brown et al. found that while non-suicidal participants showed decreased impulsivity with increasing connectivity between the ventromedial prefrontal cortex (vmPFC) and parietal cortex, suicidal participants had  regions .Suicide attempts have been found to be associated with greater activation in the right lateral orbitofrontal cortex (OFC) and decreased activation in the right superior frontal gyrus (SFG) while performing decision-making tasks in response to prototypical angry versus neutral faces .In a recent meta-analyses that included work on decision making/reward-based learning, Li et al. concluded that brain activation in suicide attempters increased in the left insula but decreased in the bilateral fusiform gyrus compared to non-attempters across multiple learning-based fMRI tasks .3.1.1.2.As a proximal and distal risk factor for suicide, social exclusion is of immediate importance to the suicidal patient. This is consistent with the concepts of “thwarted belongingness” in Joiner/Van Orden’s interpersonal theory of suicide, shining light on the vital importance of social support amongst persons at high risk for suicide.Two fMRI studies , 20 haveEmotion regulation is clinically relevant to multiple conditions, from self-injurious behavior to PTSD. Supportive of the clinical impression that emotion regulation is important in STBs, Miller et al. found that adolescents with suicidal ideation (SUI) showed increased activation in the dorsolateral prefrontal cortex (dlPFC) compared to healthy controls .3.1.1.3.Many studies have tried to examine the connection between the structures involved in affective processing and regions of interest in the suicidal brain. Clinically, this may be consistent with the concept of a cognitive distortion and related to such possible risks as low self-esteem, isolation, and unwillingness to seek help, though a comparison of the neurobiological changes associated with Cognitive Therapy is beyond the scope of this review.angry trials but a decreased activation in the same areas during neutral or happy face trials.In a study by Pan et al. participants made a gender selection for images of faces with or without affective valences . ConsistAi et al. similarly utilized a gender discrimination task with individuals with past suicide attempts. Authors found that they had lower activation within the fusiform gyrus during emotional face processing across all stimulus types: happy, angry, sad, and scared .Two major studies mixed resting state data with task-based functional tasks. Alarcon et al. found that depressed participants who had attempted suicide or had high suicidal ideation showed greater functional connectivity between the amygdala, dlPFC, dorsomedial prefrontal cortex (dmPFC), and precuneus compared to controls completing an emotional self-face recognition task where they considered if the faces looked like them, with valence varying between happy, sad, and neutral . Malhi eA recent machine learning study by Just et al. supported the involvement of structures important to all these processes among participants with suicidal ideation. When presented with affectively valenced verbal stimuli, specifically the words death, cruelty, trouble, carefree, good, and praise, group differences in activation in the medial superior frontal cortex, inferior parietal, medial temporal, ACC, and inferior frontal gyrus (IFG) were found .3.1.1.4.Impairments in top-down cognitive control and response inhibition have clear clinical relevance to suicide but have been studied very little in task-based fMRI research in this population. However, Richard-Devantoy et al. used a Go-No-Go task and found that deficits in cognitive inhibition  were related to the depressive, but not specifically, STB vulnerability risk . In cont3.1.2.While performance on fMRI tasks and task-based connectivity studies can show abnormal/atypical recruitment of structures theorized to be essential in relevant cognitive tasks, resting-state fMRI (rsfMRI) studies allow a view of default self-referential thought processes while the participant is not engaged in a specific task. It, therefore, is used to analyze which relevant systems have robust or weakened ‘default’ connections or communications  within aL-FPN/CCN) = functions include executive functions, such as goal-oriented cognition, working-memory, inhibition, and task switching; (2) the Pericentral/Somatomotor Network (PN/Somatomotor) = functions include involvement in motor processes and somatosensory processing; (3) Occipital Network/Visual Network (ON/VN) = functions include visual processing; (4) Dorsal Frontoparietal Network/Attention Network (D-FPN/AN) = plays a broad role in visuospatial attention. The functions of this system are to prepare and apply top-down selection for stimuli and responses; (5) The Midcingulo-insular Network/Salience Network (M-CIN/SN) = has a broad role in identifying important, or salient, information. Salience processing involves the detection of behaviorally-relevant environmental stimuli and may include internally-generated  information; and the (6) M-FPN/DMN = functions likely involve formation, temporal binding, and dynamic reconfiguration of associative representations based on current goal-states, detecting the associative relevance of internal and external stimuli, and providing value coding and elaboration to perceived events. Other accounts suggest M-FPN function accommodates predictive coding, semantic associations, and plays a role continuously monitoring the environment.Uddin proposes the following six main networks and their primary functions: (1) the Lateral Fronto-Parietal Network/Cognitive Control Network  to whole brain (as it sounds) analysis and involving established networks or networks defined within each individual study, it may become increasingly relevant to clinical practice. One limitation may be the inherent assumption of the specific functions of each interconnected area. We present RSFC studies grouped according to main findings. The most consistent findings among suicidal participants seem to occur between the M-FPN (default network/DMN) and the M-CIN . Many studies showed decreased RSFC between M-FPN/DMN and M-CIN/SN. When we talk about connections between networks, we clearly mean connections between the regions or nodes that comprise networks. In other words, resting state or intrinsic brain networks in fMRI are best thought of as a collection of regions that show correlations in terms of their fluctuating activity.decreased functional connectivity between the right ACC (M-CIN/SN), the orbito-medial prefrontal cortex (M-FPN/DMN), and the right middle temporal pole (within the D-FPN/AN) compared to non-suicidal depressed and control groups. Yang et al. , adding to the findings of Stange, Cao and others.An RSFC analysis of treatment changes by Shu et al.  showed tAfter this, intra-network abnormalities show up in multiple studies, focusing on the M-FPN/DMN.Zhang et al.  used an Yang’s work , mentionIn a study examining trauma and suicide in adults with PTSD, increased functional connectivity between reward and control regions (primarily under the M-FPN/DMN of Uddin’s definition) was found to be positively correlated with suicidality .Lee et al.  found thSchreiner et al.  examinedUsing whole brain analysis, Kim et al.  proposedMost promising may be the recent attempts to apply machine learning to one or more MRI modalities. Gosnell et al.  distilleDai et al.  used ICASuicide attempt-related altered RSFC was also observed in a Graph Analytics analysis (machine learning) by Stumps et al.  within tThere were a variety of studies showing abnormal connections between other networks, including the D-FPN/Attention Network, PN/Somatomotor Network, and ON/Visual Network.In line with the research of Du and Kang above, Chase et al.  found thSerafini et al.  in a revAlong with abnormalities in the M-FPN/DMN above, Lee also found increased RSFC in tracks from the temporooccipital part of the right inferior temporal gyrus (within the L-FPN/CCN) to the frontal eye fields of the Dorsal Attention Network . They also found decreased RSFC between the medial frontal cortex (within the M-FPN/DMN) and the right supplementary motor cortex (within the PN/Somatomotor network).3.2.Another way to examine the suicidal brain is through morphometric analysis. Here, we try to make it more directly accessible to the clinician. This modality measures the physical makeup of brain structures by examining measures such as cortical thickness, cortical surface area, and/or cortical volume of the relevant brain areas. The implication is that the neural systems which may be hypo/hyperactive during functional processing may have altered physical attributes. Many morphometric studies have been done to find alterations in those with STBs.The current review identified such studies which reported associations between these morphometric measures and suicidal behavior.One of the earlier studies addressing the association between history of suicidal attempts in elderly, depressed individuals and both cortical and sub-cortical abnormalities was attempted by Hwang et al. . In thatWagner et al. reported cortical thinning in the left dorsolateral, ventrolateral prefrontal, and ACC in depressed adults with documented suicidal behavior, i.e., high-risk group of suicide as compared to depressed adults with a non-high risk for suicide .A study by Huber et al. specifically found white-matter volume differences in the left ACC between veterans with a history of attempting suicide relative to veterans with a history of SUI . Along wWang et al. specifically reported significant differences in GMV in the bilateral MFG across patients with mood disorders and suicidal behavior, patients with mood disorders without suicidal behavior, and healthy controls . HoweverDing et al. used a region-specific approach to study differences between suicide attempters with a past history of mood disorders and suicidal behavior, participants with a mood disorder but not suicidal behavior, and healthy controls with neither . ReducedIn a recent study by Yang et al. authors found that suicidal depressed patients had reduced GMV in the right IFG and left caudate but increased GMV in the left calcarine fissure , areas aA recent study by Kang et al. involving individuals with depression with and without a history of suicide attempts showed altered morphometry in the lateral parietal and occipital brain regions along with frontal areas. In that study, depressed patients with past suicide attempts were found to have larger surface area within the left postcentral and left lateral occipital areas and large cortical volume within the left postcentral and left lateral orbitofrontal areas, whereas smaller surface area within the left SFG was found . In anotIn a study of suicide attempters with a family history of suicide and personal history of violent suicide attempts, Jollant et al. found an association between family history of suicide and reduced volume within the bilateral temporal regions, right dlPFC, and left putamen, as well as between violent methods of attempt and increased bilateral caudate and left putamen volumes . ReducedSeveral studies also reported cortical alterations within the temporal and parietal lobes but not the frontal lobe.Reduced GMV within the right STG was observed in adolescents with MDD and a history of suicide attempts compared to adolescents with MDD but without any history of suicide attempts , whereasA recent study by the ENIGMA-MDD working group of over 18,925 participants examined morphometric differences between healthy controls, depressed participants, and participants with a history of attempted suicide and found multiple differences between the groups . RegardiMost recently, Sarkinaite et al.  publisheIn 3.3.The fourth neurobiological modality that we included in this study was Diffusion Tensor Imaging (DTI). This method analyzes the robustness of water diffusion within white-matter structures of the brain to find associated differences between patient populations and healthy controls or other cohorts. DTI also examines the physical “highways” within and between significant structures. While fMRI gives information on “in the moment” electrical communication that could conceivably indicate functional robustness of structures and pathways, DTI is a direct measure of the physical robustness of those structures and pathways. To that end, it may be considered as a more concrete/persistent measure to estimate the difference between healthy controls and the suicidal patients. Again, most of the modalities can be accomplished in a relatively short scanning session and are more potentially accessible to the working clinician.Recent advancements in imaging have allowed the scientists to study differences in white-matter integrity, compactness, or structural connectivity in clinical populations – the “quality of the highways” so to speak. These studies use parameters such as apparent diffusion coefficient (ADC-speed of water flow regardless of direction), fractional anisotropy (FA-diffusion of water molecules in a particular direction), and edge-weight  to measure connections between regions of interest , 86. EdgIn a study of young adult healthy controls and young adults with MDD with and without a history of suicide attempts conducted by Jia et al. reduced FA was found in the (a) left anterior limb of the internal capsule (ALIC) for suicide attempters compared to non-attempters and healthy controls, (b) right frontal lobe  for suicide attempters compared to healthy controls, and (c) right lentiform nucleus (putamen) for suicide attempters compared to non-attempters . In anotIn another study, lower baseline FA was found in the left ALIC, bilateral dmPFC, and right dorsal cingulum for future suicide attempters  compared to non-attempters . In thatFan et al. also found lower FA in the dorsal and ventral frontal regions that included the uncinate fasciculus for individuals with MDD and a history of suicide attempts as compared to non-suicide attempters .In terms of structural connectivity parameters, it was determined that compared to individuals with MDD without SUI, individuals with MDD and SUI had reduced structural connectivity/edge weights across cortical , subdivisions of the inferior frontal cortex , and sub-cortical  regions in the left hemisphere . In termAnother structural connectivity study showed that compared to euthymic non-attempters and healthy controls, there was significantly decreased structural connectivity in euthymic suicide attempters in the connections between the left olfactory cortex and left anterior cingulate gyrus, as well as a clear trend of decreased connectivity between the right medial orbital, SFG, and the right rectal gyrus and between the right calcarine fissure and both the left superior and middle occipital gyrus . Hwang eA 2021 study by Chen et al. evaluated white-matter integrity  and white-matter compactness  among depressive patients with and without past suicide attempts . On a voThe same researchers evaluated white matter density and integrity among depressed patients with suicidal ideation but no history of attempts . In the 4.The concept of maladaptive thinking in depression is well understood by most clinicians . The notTask based fMRI studies show abnormal activation in prefrontal, subcortical, and limbic regions. Specifically, areas important for emotional processing, reward-based learning , emotional regulation/social exclusion, relative representation/sensitivity to affective stimuli, and cognitive control/response inhibition show abnormal activation, though in some cases , they coAmong our sample, rsfMRI enriches the functional data by showing the major networks with abnormal connectivity among patients with MDD and STBs. From machine learning to strictly RSFC studies, the most relevant networks are clearly the M-FPN/DMN and M-CIN/SN and their communication within and between each other and with top-down control areas of the L-FPN/CCN. With the vast and complex roles of the M-FPN/DMN and M-CIN/SN, it is clear that even in the resting state, areas important for learning, affective and social processing, and cognitive control are affected, but this research also lends depth to the increased weight of an abnormally functioning “salience judge” at the cost of new information coming in from all sides. The mix of participants  and type of STB being studied  of course complicates these already complicated findings, but data continues to grow.Helping to enlighten a picture of abnormal communication amongst regions and networks, DTI data among our sample similarly supported differences in major tracts such as the ALIC and uncinate fasciculus (UF), important in communicating between structures of the reward-based learning network, along with differences in edge weight and FA among and between structures important for emotional processing, reward-based learning , emotional regulation/social exclusion, relative representation/sensitivity to affective stimuli, and cognitive control/response inhibition. The clear difference among our DTI sample and the other methodologies, however, is that among participants with MDD and STBs, all of these measures were found to be decreased in comparison to control groups.This is further supported in our sample by the morphometric studies generally showing that structures involved in both top-down and bottom-up emotional processing, visual and language processing, impulse control, and affective processing are atypical across the board. Decreased GMV/thickness/area were found in frontal systems such as the IFG and OFC, ventral-lateral prefrontal cortex, dlPFC and temporal regions, and in suicidal individuals, there are clear reductions in GMV in subcortical (putamen and caudate) and limbic (hippocampus-MFPN/DMN) areas as well. Intuitively, these measured differences represent more long-term changes among the relevant structures and networks that a patient would depend on as stressors and, hence, the risk of STBs accumulate.Previous literature reviews are generally consistent with our results, though many have incorporated different samples with different conditions that inhibit direct comparison. Especially relevant to our review are the work of Jollant , DesmyteIn short, we are not proposing a grand new theory that is all encompassing, for that would take many more variables into account, which have their own emerging literature, such as genetic, socioeconomic, and cultural factors. Also biochemical, MEG, SPECT, and PET scanning and incorporating the rich and ever evolving psychometric data would also need to be considered. We are simply proposing a framework to begin applying emerging neurobiological data in a clinical and chronological way in conjunction with already used measures, such as psychometrics and clinical assessments, so that as a patient encounters various diatheses and stressors, their clinician will be able to look to this framework to address a complex problem in comprehensive but clinically feasible way. With genuine and earnest collaboration in translational medicine, imaging, and neuroscience, combined with machine learning and worldwide research consortiums focusing on suicidal thoughts and behaviors, and replication of findings, especially in these diverse and complicated modalities, collaboration can shrink the time from new discoveries to clinical intervention. There are few things more urgent than attempting it.Our simple framework is this: First, morphometric changes may be more observable early on from genetic and environmental stressors but also long standing atypical cognitive processing. Second, abnormalities in diffusion-weighted projections will become apparent, implying increasingly longstanding atypical networks and relevant ROI communication, and demonstrable on scanning. Third, abnormalities in processing new information, especially negative social and affective valenced-relevant stimuli tethered to language and facial processing, will be demonstrated on rsfMRI/RSFC analysis, as evident by increased communication between networks (M-CIN/SN to L-FPN/CCN), implying maladaptive rumination of faulty negative information and decreased communication between new, contradicting affective/relevant processing areas and value estimation/strategy adjustment networks (M-CIN/SN TO M-FPN/DMN). Fourth, the gap between value and risk estimation will widen on fMRI tasks immediately prior to the STBs.Ultimately, we hope to start to construct a chronological framework of early diatheses, developing stressors, whether distal or proximal, and correlating their neurobiological fingerprint across MRI modalities and behavioral task performance. We will do this through continued task/theory-based fMRI and network studies, structural/morphometric, RSFC, and DTI research. We will continue to develop machine learning evaluations through each modality and across them first using classification and machine learning techniques to quickly determine biosignatures that directly affect suicide risk and improve our model. We will then use a regression analysis to analyze level of risk and sequence mining to predict proximal neurobiological changes. Through this comprehensive and accelerated approach, we hope to begin to capture a clinically relevant and useful point-of-care tool that can accurately and thoroughly assess risk of suicidal ideation and attempt. Then, with extensive collaboration, those in the field of neurobiological suicide research can shift into evaluating the most effective interventions at each specific time that will prevent it. Lastly, given that functional connectivity studies and diffusion tensor imaging have a particular drawback: neither are in a position to assess directed functional or effective connectivity . In otheMD conceived the presented idea, performed the literature search and wrote the initial draft. KB substantially contributed to interpreting the relevant literature and writing the manuscript. EC performed the literature search and contributed to writing of the manuscript. JB substantially contributed to the conception, interpretation, and writing of the manuscript. AD contributed to the writing of the manuscript and edited various versions of the draft. SB conceived the presented idea, performed literature search, wrote the initial draft, and supervised all aspects of the study. All authors contributed to the article and approved the submitted version.This work was funded by GRT-00092 at Boys Town National Research Hospital.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


We found that individuals are “fingerprintable”  across independent functional MRI scans throughout the lifespan. We observed a U-shape distribution in the strength of “self-identifiability” , and “others-identifiability” , with a decrease from early adulthood into middle age, before improving in older age. FC edges contributing to self-identifiability were not restricted to specific brain networks and were different between individuals across the lifespan sample. Self-identifiability was additionally associated with regional brain volume. These findings indicate that individual participant-level identification is preserved across the lifespan despite the fact that its components are changing nonlinearly.Systematic changes have been observed in the functional architecture of the human brain with advancing age. However, functional connectivity (FC) is also a powerful feature to detect unique “connectome fingerprints,” allowing identification of individuals among their peers. Although fingerprinting has been robustly observed in samples of young adults, the reliability of this approach has not been demonstrated across the lifespan. We applied the fingerprinting framework to the Cambridge Centre for Ageing and Neuroscience cohort ( Important interindividual differences are increasingly identified in functional connectivity studies. However, most of the work to date has focused on samples of younger adults, ignoring older individuals in which brains undergo significant transformation. Here, we examine individual-level patterns of functional connectivity—that is, connectome fingerprints—across the adult lifespan. Our results suggest that connectome fingerprints can reliably predict individuals from independent brain scans across the lifespan. Additionally, regions contributing to fingerprints differed from person to person, emphasizing the extent of interindividual differences in the brain. Specific patterns of brain volume, associated with normative age-related atrophy, may impact the identification of individual-specific functional connectivity patterns. Our findings highlight the importance of interindividual variability in functional connectivity, regardless of participant age, when assessing individual differences in brain function. The structural and functional organization of the brain is reliably consistent within species because of strong genetic control of this biological system . In human = 483; ages 18–89 years)  , raising9 years) . Our resAnalyses were performed on 483 individuals of the Cam-CAN cohort  aged 18 To test the stability of the fingerprint metrics of interest . We also report the Overall, prediction of self-identifiability within each age window did not generalize to any left-out samples and exhibited poor model performance across all age windows . FurtherA potential issue with using the elastic net model with our data is the massive number of predictors in the model  and the sparse nature of the FC matrices derived from partial correlations rather than product–moment correlations. This could explain the lack of generalizability in the left-out test sets, as well as the lack of nodes identified consistently as predictive. To ensure that our results were not driven by these limitations, we adapted three more methods to verify these results: a connectome predictive modeling approach, an intraclass correlation approach, and a clustering approach. The connectome predictive modeling and intraclass correlation approaches tested whether FC in individual edges in specific networks were driving self-identifiability. Alternatively, the clustering approach aimed to confirm whether patterns of individual FC were shared across the brain in each age window. Detailed discussions of these methods are found in the We additionally tested whether other markers of variability in fMRI signal differed over the lifespan . To thisFinally, we tested whether a nonlinear change in amplitude of the BOLD signal with age could be driving the nonlinear association between self-identifiability and age. Amplitude was calculated as the average of the amplitude of the BOLD signal for all nodes in a given network, for each participant. We found that there was no association between amplitude of the BOLD signal and age in the Rest modality. In the Task modality, amplitude of the BOLD signal was associated nonlinearly with age , but selOur initial results suggest that fingerprint accuracy is reliably achieved in adults over the lifespan. This is likely achieved due to the variability across people in the strongest FC patterns across the brain. We finally wanted to assess whether this identifiability was associated with age-sensitive variables, such as brain volume. To do so, we used three morphometric networks derived from an independent study as our outcome of interest : one froLower self-identifiability was associated with lower gray matter volume in the frontal structural network over and above the effect of age and other covariates . This coOthers-identifiability was not associated with brain volume . Using oWe found that connectome-based fingerprinting is reliable across the lifespan. Fingerprint identification accuracy was robust even though self-identifiability and others-identifiability show a nonlinear cross-sectional distribution across the lifespan. We also found that the highest weighted edges contributing to self-identifiability varied across individuals. This interindividual variability was observed within each decade of life. Furthermore, relative to whole-brain and within-network FC, between-network FC provided more reliable identification estimates and the number of nodes (and related edges) were more important than their localization to identify individuals using brain functional proprieties. Finally, we found that self-identifiability (but not others-identifiability) was associated with frontal brain volume, a morphometric feature known to atrophy with advancing age .Our findings indicate that fingerprinting remains robust across the lifespan, despite observed age-related changes in FC in older adulthood . We founNext, we explicated fingerprint identification accuracy into its two components: self-identifiability and others-identifiability . We founWe also found that change occurring with age in self-identifiability and others-identifiability mainly occurs in parallel in all networks, including the random networks, which likely explains why the high identification accuracy is preserved across the lifespan despite age-related changes in its two components. As long as the balance between self-identifiability and others-identifiability is preserved, healthy individuals can be identified among a large group of individuals with similar accuracy . FindingOur findings are consistent with work suggesting that fMRI connectivity is composed of distinct, unique individual-specific and shared task-specific components . Using fFinally, we aimed to determine whether individual-level FC fingerprint metrics were associated with brain volume. We compared brain volume associations with self-identifiability and others-identifiability. Whole-brain connectomes, within-network FC, and between-network FC self-identifiability were associated with brain volume in frontal areas known to be particularly affected by normal age-related atrophy . We alsoSelf-identifiability may be associated with a number of factors that differentially impact individuals over the lifespan , 2018. FAs an additional note, the findings above also expand methodological aspects in the field of fingerprinting. First, we used partial correlation to generate FC matrices, which were then used for fingerprinting. Partial correlations resulted in higher identification rates in our study compared with product–moment correlations. Partial correlations produce sparse matrices excluding, to some extent, noise inherent to fMRI . Other mThe main limitation of this study is its cross-sectional nature. As such, it is difficult to determine how fingerprint metrics change during the lifespan within individuals, limiting the interpretation of our conclusions. Future work would benefit from longitudinal studies examining identifiability across scans separated by many years. Similarly, because of quality control issues, the eldest participants in our cohort were underrepresented, and as such, the nonlinearity of our findings need to be interpreted with caution. However, supporting the nonlinearity of the findings, the nonlinearity between age and self-identifiability was still preserved when removing the oldest participants. Finally, we included only two fMRI modalities in our analyses. As other studies have shown that the choice of the task can influence the ability to fingerprint, future studies should replicate our findings using other combinations of fMRI tasks.Across our analyses, we found that FC patterns allow for precise fingerprinting between individuals and that this discrimination is reliable across the lifespan. High identification rates were observed across the Cam-CAN cohort, accompanied by age-related effects on individual-level (self-identifiability) and group-level (others-identifiability) FC patterns. Accurate fingerprinting of FC was observed across the lifespan, even though edges contributing to self-identifiability differed between individuals across networks and across the decades of life. Finally, we show that individual-level self-identifiability (instead of group-level others-identifiability) is associated with brain volume in regions vulnerable to age-related atrophy. Together, the present findings illuminate the potential utility of individual-level measures that demarcate age-related brain change. Group-level differences in FC have revealed reliable patterns attributed to the aging brain. However, individual differences in FC patterns are likely to play a key role in predicting brain health and associated functional outcomes.https://www.mrc-cbu.cam.ac.uk/datasets/camcan/). The Cam-CAN cohort is a lifespan cross-sectional population-based cohort, composed of cognitively healthy participants aged between 18 and 89 years of age residing in the United Kingdom. Full details for the study participants and recruitment can be found elsewhere  were extracted using Nilearn 0.6.2  in MATLAB version 2012a, as part of a previous study  and largest (default) networks  includedR2) and the root mean square error (RMSE).We adapted an elastic net approach to predict self-identifiability from the FC edges in our sample. Specifically, we used the sliding-window method to select subsamples of participants across the lifespan. Within each window, we first removed the diagonal and lower triangle of the functional connectivity matrices of the participants and flattened the remaining 79,800 edges. The connectivity values were then standardized, and participants were randomly split in a training and testing subset . Connectivity values across all 79,800 edges were used to predict self-identifiability. In the training set, we used a 5 k-fold cross-validation with a grid search to select the optimal L1 ratio for our elastic net model. Once the optimal L1 ratio was selected, an elastic net model was fitted on the entire training set. The model was then used to predict self-identifiability in the testing set. Performance in the testing set was reported as the variance explained  and structural age-related changes. Three morphometric networks derived in an independent study were used as our outcome of interest . BrieflyAdditionally, we also determined whether other markers of variability in fMRI signal changed during the aging process. We derived two types of measures, variability in FC and variability in BOLD temporal similarity profile.Both types of measures were calculated using custom Python scripts. Variability in FC for each individual was computed as the variance coefficient of FC coefficients at a whole-brain level and within each network of interest. To obtain between-individual variability, we first computed the average variability in FC across the sample. Then, for each individual, we computed the absolute distance between their variability and the mean variability of the group. A greater distance indicates more between-individual variability.Variability within and between individuals in BOLD signal features was computed as the variance in temporal profile similarity of BOLD signal features . To do sAs a final verification, we computed BOLD signal amplitude and related this measure to age and self-identifiability. In each of the 400 brain regions, for each participant, the amplitude of the time series were computed by subtracting the minimum from the maximum BOLD value. Then, the amplitude of the nodes within the network was averaged to obtain a single amplitude measure for each network for each participant.https://www.python.org/; NumPy 1.19.1, https://github.com/villeneuvelab/projects (sihnpy Python package (https://sihnpy.readthedocs.io/).The sliding-window, fingerprinting framework, elastic net, edge-wise intraclass correlation analyses, connectome predictive modeling, clustering, and variability in FC analyses were adapted and developed using Python 3.8.5 . We used this approach to compare network performance in fingerprint identifiability within each modality pair . A family-wise Bonferroni correction was applied to each set of comparisons to account for multiple comparisons. Finally, we used the sliding-window approach where the fingerprint identification accuracy in each age window was computed and visualized.To study the relationship between self-identifiability and age, and others-identifiability and age, we used multiple linear regression models. We used polynomial (quadratic) regressions when the linearity assumption was violated and, in that case, used Stimson’s equation to derive the peak’s coordinates . AssumptAll procedures described above were reapplied to study the relationship between fingerprint metrics and brain volume. Individual variability in FC and temporal similarity profile were also associated with age and with gray matter volume using the methodology described above. These metrics were used to determine whether other fMRI measures would also show interindividual variability across the lifespan. To test whether the association was stronger in the frontal structural network, the limbic structural network, or the visual structural network, we used Vuong’s test for non-nested models . Models The authors would like to thank Jonathan Gallego Rudolf, Yara Yakoub, Ting Qiu, and Julien Menes for useful feedback on the project, and Gabriel St-Onge for technical help in implementing the connectome predictive modeling. We would also like to thank the reviewers for providing their time to review this paper and for sharing their thoughtful insights into our results, which significantly strengthened the paper. Data collection and sharing for this project were provided by the Cambridge Centre for Ageing and Neuroscience (Cam-CAN). Computations were enabled in part by support from Calcul Québec  and the Digital Research Alliance of Canada , who provided access to the Béluga high-performance computing resource. This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund and Fonds de recherche du Québec, awarded to the Healthy Brains, Healthy Lives initiative at McGill University. The funding organizations did not have a role in writing the manuscript.https://doi.org/10.1162/netn_a_00320.Supporting information for this article is available at Frédéric St-Onge: Conceptualization; Data curation; Formal analysis; Methodology; Software; Visualization; Writing–original draft; Writing–review & editing. Mohammadali Javanray: Conceptualization; Formal analysis; Writing–review & editing. Alexa Pichet Binette: Conceptualization; Methodology; Writing–review & editing. Cherie Strikwerda-Brown: Conceptualization; Writing–review & editing. Jordana Remz: Conceptualization; Software; Writing–review & editing. R. Nathan Spreng: Methodology; Supervision; Writing–review & editing. Golia Shafiei: Methodology; Writing–review & editing. Bratislav Misic: Methodology; Supervision; Writing–review & editing. Étienne Vachon-Presseau: Methodology; Supervision; Writing–review & editing. Sylvia Villeneuve: Conceptualization; Funding acquisition; Methodology; Resources; Supervision; Visualization; Writing–original draft; Writing–review & editing.https://dx.doi.org/10.13039/501100004489), Award ID: NA. Frédéric St-Onge, Fonds de Recherche du Québec–Santé (https://dx.doi.org/10.13039/501100000156), Award ID: 316992.Cam-CAN, UK Biotechnology and Biological Sciences Research Council, Award ID: BB/H008217/1. Frédéric St-Onge, Healthy Brains, Healthy Lives through the Canada First Research Excellence Fund and the Fonds de Recherche du Québec, Award ID: NA. Frédéric St-Onge, Mitacs (Click here for additional data file.


Antimicrobial stewardship programs (ASPs) are an internationally recognized strategy for reducing antimicrobial resistance while maintaining patient safety. ASP activities include the restriction of broad-spectrum antibiotics, the establishment of hospital guidelines based on antibiograms, and the promotion of appropriate antibiotic use. This study aimed to determine whether the implementation of antimicrobial stewardship practices improved the effects of a peri-procedure antibiotic prophylaxis prescribed by urologists for patients with spinal cord injury/disease (SCI/D) undergoing minor urological procedures at a tertiary care hospital.This single-group, quasi-experiment study included adult patients with SCI/D who required minor urological procedures  and who were hospitalized between 2012 and 2020.p < 0.0001), and there was a highly significant reduction in the post- compared to the pre-implementation group in the number who received a post-procedure prophylaxis .In total, 233 patients were included in each of the pre- and post-ASP implantation groups. There was a significant reduction in antibiotic use among patients who received a pre-procedure antimicrobial prophylaxis in the post- compared to the pre-implementation group (45.9% vs. 24.46%, ASP implementation is a highly effective strategy for reducing the use of peri-procedure antimicrobial prophylaxes in patients with SCI/D injuries undergoing minor urological procedures. Antimicrobial resistance (AMR) has emerged as a worldwide health issue fueled by antibiotic misuse . AccordiPatients with spinal cord injury/disease (SCI/D) are sensitive to receiving several antibiotic courses. These patients often undergo urological procedures for determining bladder capacity and diagnosing neurogenic bladders. As part of their bladder management program, they require chromic bladder instruments, such as indwelling catheters or intermittent catheterization programs, depending on the bladder management strategy used –7.Recent guidelines for antimicrobial prophylaxis for urological procedures by the American Urological Association (AUA) recommend the use of trimethoprim/sulfamethoxazole (TMP/SMX), the first or second generation of cephalosporins, or aminopenicillins combined with beta-lactamase inhibitors and metronidazole as a single dose less than 24 h before a patient undergoes a minor urological procedure with risk factors including diabetes mellitus, cardiovascular disease, anatomic anomalies, chronic corticosteroid use, and a history of recurrent urinary tract infections (UTIs) . A full Antimicrobial stewardship program (ASPs) are a globally recognized method of reducing antimicrobial resistance while maintaining patient safety. They involve selecting the ideal antimicrobial therapy for each patient, including the dosage and duration, to deliver the best outcomes through optimal therapy . When doEffective antibiotic stewardship guidelines are being implemented in Saudi Arabia to limit inappropriate antibiotic use , 11. WitThe ASP was implemented in 2015 in the studied hospital that is specialized in providing care for patients with SCI/D. An infectious disease consultant, clinical pharmacist, infection control specialist, and clinical microbiologist were part of the ASP team, with activities including reviewing and optimizing the use of prescribed antibiotics, restricting broad-spectrum antibiotics, reviewing angiograms to develop hospital clinical guidelines, and other practices. Thus, the study’s primary objective was to evaluate the appropriateness of using a peri-procedure antibiotic prophylaxis in patients undergoing urological intervention before and after ASP implementation. The secondary objective was to identify gaps in the proper implementation of stewardship. In combination with strong infection-control practices, antibiotic stewardship is likely the best option to combat the looming threat of antibiotic resistance in the absence of a successful line of new antibiotic classes in the near future.This single-group, quasi-experiment study was conducted from 2012 to 2020 at Sultan bin Abdulaziz Humanitarian City, a rehabilitation specialist hospital in Riyadh, Saudi Arabia. The hospital provides a wide range of services, including occupational therapy, speech therapy, physiotherapy, social services, rehabilitation services for outpatient clinics, and inpatient admission. Patients with SCI/D comprise a significant number of hospital admissions, and minor urological procedures, such as cystoscopies, were the most common procedures performed.The ASP was implemented at hospital in 2015. The ASP team implemented hospital guidelines following the EAU, as well as recommended not using antibiotic prophylaxis for minor urological procedures and testing patients undergoing urological procedures for urine culture to allow treatment before the procedure, if necessary. The pre-ASP implementation period was from 2012 to 2015, the post-ASP implementation period was from 2016 to 2020, and guidelines were distributed to all hospital staff.The ASP interventions the hospital adopted included education (physicians and surgeons), audits, and feedback . Restrictive interventions mostly involved the pre-authorization of restricted antibiotics. However, the implementation of these measures was beyond the scope of this study, so we only assessed guideline concordance according to the number of patients who received a prophylactic antibiotic prescription in terms of its type, dose, and duration. In addition, the timeliness of antibiotic administration pre-surgery was also studied.All adult male and female patients who were admitted to the hospital from 2012 to 2020 with SCI/D required a minor urological procedure . Patients admitted with diagnoses other than SCI/D, pregnant women, patients having undergone pediatric urological procedures, and patients with a current UTI and receiving treatment were excluded. Meanwhile, eligible patients were initially stratified into two groups: one before ASP implementation from 2012 to 2015  and a second after ASP implementation from 2016 to 2020 . We were planning to collect 50% of the sample (250) from the pre-implementation group, with an equal representation of each year (50% / 4 years = 12.5%).Trained researchers collected data from the health information system (HIS) of the hospital using a predesigned case report form. Data concerning patients’ demographics, including age, gender, comorbidities, medication history by group, voiding methods by assessment, and number of past UTIs were collected. In addition, catheterization-related data, pre- and post-procedure antibiotic use, dose frequency, duration, and other clinical data were collected before and after ASP implementation.The primary objective of the study was to evaluate the appropriateness of prescribing a peri-interventional antibiotic prophylaxis to patients undergoing minor urological procedures pre- and post-ASP implementation. The secondary objective was to assess the gaps in the proper implementation of the ASP.The study was approved in October 2021 via Institutional Review Board (IRB) no# 55-IRB-2021 by the IRB committee in Sultan Bin Abdulaziz Humanitarian City Riyadh, Saudi Arabia (IRB registration number: H-01-R-090), and the need for informed consent was waived. The study was conducted in accordance with the Declaration of Helsinki, and before the analysis, the patients’ information was anonymized and de-identified.Descriptive statistics included counts and proportions for categorical variables and means and standard deviations (SDs) for continuous variables. The chi-square test (χ2) was used for categorical variables, while the two-tailed student’s t test was used for continuous variables. Antibiotic use practices were compared between pre- and post-ASP implementation based on the surgical prophylaxis guidelines at the hospital, and data analysis was conducted using the Statistical Package for Social Sciences (SPSS) version 21 , where a p-value of < 0.05 was considered statistically significant.In total, 3,612 eligible adult patients underwent a minor urological procedure from 2012 to 2020: 1,787 patients in the pre-ASP implementation period and 1,825 in the post-ASP implementation period. Around 13% of patients were randomly selected for each year of both the pre- and post-ASP implementation periods, and the total number of patients was 233 patients in each group , with a mean age of 33 years, and the most common comorbidity observed in these patients was neurogenic bladder, at 91.84% and 99.14% in the pre- and post-ASP implementation groups, respectively. Other comorbidities were significantly fewer in the post-ASP implementation period.P < 0.0001). Concerning the voiding method, clean intermittent catheterization (CIC) was predominant in both the pre- (51.93%) and post-implementation (54.69%) groups, while the suprapubic voiding method was statistically more predominant in the post- compared to the pre-ASP implementation group . Further, the number of patients with no previous UTI history was significantly higher in the post- compared to the pre-implementation group , while the number of patients who have had at least two past UTIs was significantly greater in the pre- compared to the post-implementation group . Further, cystoscopy was the most common minor urological procedure performed in the pre- (33.01%) and post-implementation groups (63.9%), respectively , respectively. Further, the number of patients who did not receive an antimicrobial prophylaxis pre-procedure was significantly higher in the post- compared to the pre-implementation group . Of the patients who received a surgical antimicrobial prophylaxis, 57 (53.3%) in the pre-implementation group and 55 (96.5%) in the post-implementation group received it within 60 min. Moreover, the number of patients who received an antimicrobial prophylaxis ≥ 60 min was lower in the post-ASP implementation group . All patients in both implementation groups received a single-dose antimicrobial prophylaxis , respectively. Patients in both groups received ceftriaxone as a prophylaxis and were given one dose post-procedure. Meanwhile, the number of patients who did not receive a post-procedure prophylaxis was significantly higher in the post- compared to the pre-implementation group .Another factor was the timeline of the antibiotic’s prophylaxis administration within the cut-off of 60 min, in accordance with the Infectious Disease Society of America (IDSA) surgical prophylaxis guideline . A marked difference was observed between both groups regarding the timeliness of antibiotic administration, with only two patients out of 57 (3.5%) crossing the 60-min cut-off in the post-implementation period. Ceftriaxone, third-generation cephalosporin, was still preferred over the recommended cefazolin as an intravenous agent, and concessions were made in the hospital by the stewardship committee on account of the local antibiogram. However, there was a significant shift toward not prescribing surgical prophylaxis in the post-ASP implementation period. Improvements in antibiotic consumption, that is, toward using narrow-spectrum antibiotics, must be addressed, with emphasis on not using antibiotics in low-risk patients.Ceftriaxone, whose high consumption supports the results of previous studies on using broader-spectrum antibiotics in Saudi Arabia as surgical prophylaxis , was also used in low-risk groups. We noted a lack of surveillance of the resistance patterns of prevalent strains and a reduction in antibiotic consumption in the policy dictating the prescription of these agents. In addition, surgeons preferred using third-generation cephalosporins as a routine practice, with concessions granted based on constant consideration of the risk factors involved with SCI/D patients among high-risk patients. Another factor involved was the limited hospital formulary and routine screening of urine cultures, which reported ceftriaxone sensitivity.The results demonstrate a gap in the adherence of surgeons to the implemented guideline of not prescribing peri-operative antibiotics to patients undergoing minor urological procedures. Continuous feedback and auditing, education, and quarterly reporting must be adopted to improve adherence to the implemented guideline and to reduce antibiotic misuse.Because of the limitation of our quasi-experiment study design, the findings of similar local studies on antimicrobial consumption are incomparable to our data, as they were based more on prospective ASP interventions. However, the findings of our observations support previous reports that an effective ASP improves antibiotic use and, in turn, improves patient outcomes . Some of the other limitations include our inability to identify which components of the ASP were the most effective at reducing peri-operative antibiotic use, as we did not study the interventions prospectively. Third, we did not cover any other condition together with neurogenic bladder, such as stroke or non-traumatic SCI, and the selection of patients for each year at random was a limitation, as we did not cover the total number of patients screened. Lastly, comorbidities were not studied to determine whether surgeons were prescribing peri-operative antibiotics to high-risk patients.An ASP for SCI/D patients in a rehabilitation hospital is an example of a highly needed setting, and utilizing related data will greatly improve the appropriate use of antimicrobial therapy, as well as promote prescribers’ acceptance of the guideline, thus reducing related costs and antimicrobial consumption. Future studies should examine the generalizability of these findings to other patient population groups with similar conditions as neurogenic bladder (patients with stroke and non-traumatic SCI/D). Moreover, more studies are needed to assess the long-term clinical benefits for patients of all diseases . These studies can ensure the allocation of further resources that are crucial to supporting the expansion of the ASP as it becomes increasingly accepted as a standard of care in many advanced hospital settings.


We propose rb_dplr, a novel and computationally efficient algorithm for generating high-dimensional binary random variates that effectively recapitulates AM-induced genetic architectures using the Bahadur order-2 approximation of the multivariate Bernoulli distribution. The rBahadur R library is available through the Comprehensive R Archive Network at The online version contains supplementary material available at 10.1186/s12859-023-05442-6. The simulation of realistic genotype/phenotype data is a fundamental tool in statistical genetics and is essential for the development of robust statistical methods for the analysis of genome-wide data. As such, much prior effort has focused on generating synthetic data that recapitulate salient characteristics of genetic marker data, including local linkage disequilibrium (LD) structure induced by variable recombination rates –3, relatDespite these advances, existing methods are ill-suited for generating synthetic genotype/phenotype data reflecting the consequences of recent assortative mating (AM); in contrast to the effects of recombination, which yields banded covariance structures, AM induces dense covariance structures reflecting sign-consistent dependence among all causal variants across the genome , 8. On tm-dimensional multivariate Bernoulli (MVB) distribution [m haplotypes [SNP haplotypes subject to AM-induced long-range dependencies can be represented mathematically by the ribution , which imentclass2pt{minimplotypes , 15, 16 plotypes , 11. HowO(m) operations. We then present numerical experiments demonstrating that the proposed methods outperform existing direct sampling methods and verify that they faithfully represent the effects of AM by comparing results to forward-time simulations. We provide these methods, together with a collection of utilities for characterizing the equilibrium distribution of haplotypes under AM, in rBahadur, an open-source library for the R programming language.In the current manuscript, we introduce a novel collection of efficient methods for directly sampling high-dimensional MVB random variables satisfying particular moment conditions . In parThe rBahadur library consists of three component collections: First, we provide two general-purpose MVB samplers, rb_unstr and rb_dplr, the implementation of which we discuss in the following section. Second, we provide utilities for modeling equilibrium AM, including a set of convenience functions for computing equilibrium parameters given initial conditions and for parametrizing the corresponding MVB distribution. Third, we provide a routine for end-to-end simulation that combines the first two components to efficiently construct equilibrium genotypes and phenotypes given population parameters.f in  is developed specifically for the case when the correlation matrix is diagonal-plus-low-rank  operations. Both methods sample the entries of the random vector sequentially: First, a realization of conditionally on the realization of the previously drawn variables We consider Bahadur order-2 approximations to the distribution in ; i.e., wmentclass2pt{minimr. Following Nagylaki [Here we demonstrate how the DPLR order-2 MVB distribution is used to model the consequences of assortment. Consider the equilibrium distribution of haploid causal variants Nagylaki , the equAssuming casual variants are unlinked at panmixis, the correlation matrix of causal haploid variants will be of the form r et al. , \documer. Finally, am_covariance_structure parametrizes the corresponding DPLR MVB distribution for a specified set of allele frequencies, causal effects, and initial conditions, by using . am_simulate returns genotypes, phenotypes, as well as additional architectural components, including the allele frequencies, allele-substitution effects, and the heritable component of the generated phenotype. We provide a vignette illustrating usage of am_simulate in further detail in Additional file m binary haplotypes for Figure haplosim , three mmentclass2pt{minimhaplosim . Resultshaplosim , which hFigure https://CRAN.R-project.org/package=rBahadur.Given that AM is both widespread , 11 and Our approach is limited by the requirement that the target distribution admits a second-order Bahadur approximation . For far apart causal variants, this is of little consequence as the true values of moments up to order four are expected to be smaller than their sampling variances unless practice . Howevermentclass2pt{minimAdditional file 1: Supplementary note.


Results: Confirmatory factor analysis of the TUMS indicated that a one-factor model and a correlated two-factor model had similar model fit indices, and a Chi-square difference test supported the one-factor model. Further study of the parsimonious one-factor scale provided evidence of reliability and construct validity. Known group validity was evidenced by significantly higher TUMS scores in the KiSS intervention arm receiving urge management skills training than in the control arm (p < 0.001). Concurrent validity was evidenced by TUMS’s inverse association with cigarettes smoked per day and positive associations with nonsmoking days, 7-day abstinence, and self-efficacy to control smoking behaviors (p’s < 0.05). Conclusion: The TUMS is a reliable, valid measure of smoking urge management behaviors. The measure can support theory-driven research on smoking-specific coping mechanisms, inform clinical practice by identifying coping strategies that might be under-utilized in treatment-seeking smokers, and function as a measure of treatment adherence in cessation trials that target urge management behaviors.Background: During quit attempts, smokers must overcome smoking urges triggered by environmental cues and nicotine withdrawal symptoms. This study investigates the psychometric properties of the 12-item Tobacco Urge Management Scale (TUMS), a new measure of smoking urge management behaviors. Methods: We analyzed secondary data ( Tobacco smoking remains among the top global public health threats, claiming more than eight million lives yearly . CigaretThe experience of urges to smoke during periods of abstinence is a hallmark of nicotine dependence . Urges aCBT-based interventions include skills training to help smokers anticipate urge-eliciting triggers and exert compensatory urge management strategies during a quit attempt. Behavioral and social-cognitive theory conceptualizations of cessation and relapse have guided treatment models that emphasize a transitional behavior change process during a quit attempt. For example, Marlatt’s model of relapse is guided by evidence that effective CBT-framed coping responses used for relapse prevention can enhance self-efficacy to maintain abstinence, which, in turn, reduces relapse ,14. ThisExtensive evidence ,18,19,20Our conceptualization of coping skills for urge management in the KiSS intervention ,6,7 was Much smoking cessation research does not investigate urge-specific coping. Instead, it examines how smokers’ general approach to coping with stressors affects cessation and relapse. The evidence linking general coping behaviors to successful smoking control is weaker than that linking smoking-specific coping and smoking control. For example, one study  found thWe found one measure that explicitly focused on coping with urges to smoke, the 3-item Coping with Temptation to Smoke (CTS) scale . The CTSThe TUMS measure addresses the need for a theoretically grounded, valid, and reliable measure of how smokers specifically cope with the urge to smoke. The measure could be used to evaluate treatment adherence in interventions targeting urge management behaviors and advance theoretical models of successful smoking cessation treatments. For example, O’Connell and colleagues  have notThe data for this study were collected in the context of a two-group randomized controlled trial, referred to as KiSS. The Temple University Institutional Review Board approved the trial before any data collection. The KiSS trial evaluated the efficacy of a novel multilevel intervention to reduce child tobacco smoke exposure and parental smoking in low-income and predominantly minority communities ,6,7. Tobasked the parents about their child’s exposure to tobacco smoke at home, advised them about the harm to children’s health and the benefits of protecting children from tobacco smoke, and referred smoking parents to smoking cessation services. After the AAR intervention, eligible and consented smokers were randomized into two potential treatments: additional telephone-based behavioral counseling around child secondhand smoke exposure reduction and parental cessation (AAR + counseling) or nutrition education (AAR + control). The AAR + counseling group received 3 months of telephone-based behavioral counseling that included, among other things, skills training to manage urges to smoke and reduce their child’s secondhand tobacco smoke exposure. The skills included compensatory cognitive and behavioral coping strategies to avoid smoking and child exposure. These skills were introduced as either “things you think of or tell yourself that can help you avoid smoking when you have an urge”  or “things you can do when you have an urge to help avoid smoking” . The counselors provided the participants with support and problem-solving around smokers’ efforts to use urge management skills throughout the intervention. The AAR + control group received 3 months of telephone-based nutrition education (without any smoking cessation-related skills training).The KiSS participants were smoking parents/guardians recruited from safety-net pediatric clinics. All the participants received a minimal intervention, “Ask, Advise, and Refer” (AAR), during a pediatric clinic visit with their child. Pediatric providers Structured, computer-assisted telephone interviews were used to collect self-report data at baseline (before randomization and intervention) and at 3-month end-of-treatment (EOT). Descriptive measures. The demographic and pre-intervention smoking characteristics were assessed at baseline.Tobacco Urge Management Scale (TUMS). The 12-item TUMS was administered at the EOT. The participants reported how often  in the past week they used each coping strategy to prevent smoking a cigarette during an urge (see urge see . The iteAs shown in Indicators of smoking behavior at the three-month end-of-treatment (EOT) period. The following smoking behaviors were assessed at the EOT: seven-day point prevalence abstinence from smoking, average cigarettes smoked per day in the prior week, the number of nonsmoking days from baseline to EOT, smoking cessation self-efficacy, and smoke-free home/car self-efficacy. The timeline follow-back method via structured interview [nterview  was usednterview . The parnterview . The parConfirmatory factor analysis (CFA) was used to test the factor structure of the TUMS items under two possible models: A one-factor model of coping skills (factor 1) and a correlated two-factor model of cognitive coping skills (factor 1) and behavioral coping skills (factor 2). Mplus 8.1  was usedAfter identifying the best TUMS model based on CFA, the reliability of the TUMS was estimated using McDonald’s coefficient Omega . McDonalt-test was used to test the intervention and control groups’ mean differences in urge management coping. The known group validity of the scale would be evidenced if the TUMS scores were significantly higher in the intervention group than in the control group. Spearman’s correlations were used to examine the associations between the TUMS and average daily cigarettes smoked, the number of nonsmoking days, smoke-free home/car self-efficacy, and smoking cessation self-efficacy. The concurrent validity of the scale would be evidenced by the TUMS scores being significantly and negatively correlated with the average daily cigarettes smoked, and significantly and positively associated with the number of nonsmoking days, smoke-free home/car self-efficacy, and smoking cessation self-efficacy. Concurrent validity was also assessed by testing the mean differences in urge management coping between the participants reporting any versus zero cigarettes smoked  in the prior week using an independent sample t-test. Concurrent validity would be evident if the abstainers had significantly higher TUMS scores than the non-abstainers.The TUMS validity was further examined by assessing the relationship of the TUMS scores with the intervention conditions and smoking-related outcomes using IBM SPSS software (Version 26). An independent sample n = 327) were primarily African American, female, and between the ages of 18 and 65, and most were under 35 years. The majority had below college-level education and reported living under the poverty level. For the comparison of the model fitness, 29 cases were excluded due to missing information on each of the TUMS items due to attrition at the EOT. Comparisons of the baseline demographic characteristics of the participants with and without missing data revealed no statistically significant differences.The participant characteristics are shown in The one-factor model fit indices were RMSEA = 0.075, CFI = 0.962, and TLI = 0.953. The correlated two-factor model fit indices were RMSEA = 0.074, CFI = 0.963, and TLI = 0.953. The analysis showed a difference in RMSEA values of 0.001, indicating both models have a good fit with similar scores. The CFI values indicated a good fit in the one-factor and correlated two-factor models, with a 0.001 difference between the scores. The TLI values between the models were identical, indicating a good fit for both models. The factor correlation included unity (0.905–1.001), indicating a lack of discrimination between the two traits. Furthermore, the Chi-square difference test was not significant, with a Type I error rate of 0.01, confirming that the models fit equally well. Following the parsimony criteria, preference for model selection is given to the simpler one-factor model, with the least free parameters that still meet the goodness-of-fit criteria . p < 0.001), ranging from 0.578 to 0.761. The differences in the factor loading scores suggest that certain items were more strongly associated with the general factor than others. Based on these values, item 2  had the strongest association and item 1  had the weakest association to urge coping. p < 0.001). Across both groups, the participants who used urge management skills more frequently reported significantly more nonsmoking days, lower cigarettes smoked per day, higher self-efficacy to create and maintain a smoke-free home/car, and higher self-efficacy to abstain from smoking (see p < 0.05).The 12-item measure is reliable, with high internal consistency . To further examine validity, we compared the TUMS scores of the participants in the different intervention conditions. Those in the AAR + counseling intervention condition scored significantly higher on the TUMS than those in the AAR + control condition . Measures emphasizing general coping strategies e.g.,  would beThis study also has limitations. First, while the research sample is a strength, in that low-income smokers are under-represented, it also is a limitation. The TUMS was initially developed for use in the KiSS study. Due to the target population being a younger, primarily female, low-income, minority population, this analysis represents a relatively small, homogenous subgroup of the general population. The TUMS should be tested in a more diverse population. Second, the KiSS did not include an alternate measure of urge coping to validate the construct further. Being mindful of the demands of participating in a complex trial, we tried to keep participant measurement to a minimum.Overall, this study supports a one-factor model as the best characterization of the TUMS 12-items and underlying latent factor, tobacco urge management. As a 12-item measure, the participant burden of this scale during assessments is low. Determining coping strategies as a single, overarching factor recognizes that the general application of any coping skills included in the TUMS could contribute to smoking urge management. More importantly, the one-factor model has implications for developing and implementing behavioral interventions. The TUMS can be a tool for testing treatment adherence during an intervention and measuring the change in the uptake of coping skills to manage urges during smoking cessation or relapse prevention. Overall, the findings support measuring the frequency of urge-coping strategies as a valuable assessment to understand better and promote smoking behavior change.


With the advent of tyrosine kinase inhibitors (TKIs), the treatment prospects of chronic myeloid leukemia (CML) have changed markedly. This innovation can lengthen the long-term survival of patients suffering from CML. However, long-term exposure to TKIs is accompanied by various adverse events (AEs). The latter affect the quality of life and compliance of patients with CML, and may lead to serious disease progression (and even death). Recently, increasing numbers of patients with CML have begun to pursue a dose optimization strategy. Dose optimization may be considered at all stages of the entire treatment, which includes dose reduction and discontinuation of TKIs therapy. In general, reduction of the TKI dose is considered to be an important measure to reduce AEs and improve quality of life on the premise of maintaining molecular responses. Furthermore, discontinuation of TKIs therapy has been demonstrated to be feasible and safe for about half of patients with a stable optimal response and a longer duration of TKI treatment. This review focuses mainly on the latest research of dose optimization of imatinib, dasatinib, and nilotinib in CML clinical trials and real-life settings. We consider dose reduction in newly diagnosed patients, or in optimal response, or for improving AEs, either as a prelude to treatment-free remission (TFR) or as maintenance therapy in those patients unable to discontinue TKIs therapy. In addition, we also focus on discontinuation of TKIs therapy and second attempts to achieve TFR. Chronic myeloid leukemia (CML) is a myeloproliferative tumor formed by clonal adult cases of leukemia . With thLong-term treatment with TKIs is accompanied with various adverse events (AEs) that significantly affect the quality of life and compliance of patients with CML, and have the potential to cause significant disease progression and mortality. Severe AEs associated with second-generation TKIs have also been reported. These include pleural effusion (PE) and pulmonary hypertension induced by dasatinib , 5 as weIS ≤ 0.01%) can achieve relatively long-lasting safe discontinuation of TKIs therapy .Recently, increasing numbers of patients with CML have begun to pursue a dose optimization strategy, which included dose reduction and discontinuation of TKIs therapy. Dose reduction of TKIs has been suggested to be safe and feasible, and to elicit an optimal response, in patients with CML. Also, the prevention and management of AEs must also be considered to improve patient compliance and reduce the risk of treatment interruption , 9. FassIn recent years, several clinical trials and real-life practices have indicated that treatment discontinuation has become a new therapeutic goal for patients with CML who are stable and have a DMR , 13. HowBCR::ABL1IS ≤ 0.1%), but the prevalence of MMR was similar at 1 years or 2 years between the two groups being assessed. However, an increased prevalence of severe AEs and worse compliance by patients was reported in the high-dose-imatinib arm. As a result, patients received imatinib at 800 mg/day initially which was later reduced to 400 mg/day. In addition, dose reduction was accompanied by a reduction in the prevalence of AEs and medical costs, and could improve patient compliance. Claudiani and coworkers  treatment compared with standard-dose therapy –19. High00 mg/dayoworkers  found thmin) of a TKI  after a TDM-based dose-adjustment strategy. The proportion of patients with the target Cmin increased from 38% to 64%, which suggested that a TDM-based dose-adjustment strategy may be an effective strategy to enable patients who received a TKI to achieve the target Cmin. The population pharmacokinetics of imatinib in patients with CML in Nigeria (Therapeutic drug monitoring (TDM) is gradually becoming a practical tool to achieve individualized medicine for patients receiving targeted drugs . Peng an Nigeria  showed t Nigeria . If possSeveral studies have explored the efficacy and safety of standard-dose dasatinib (100 mg/day) compared with low-dose therapy (<100 mg/day) in clinical trials and real-life settings. A retrospective analysis of the DASISION trial  revealedThe CA180-034 study  enrolledmin/D/W (dasatinib concentration adjusted by dose (g), and bodyweight (kg)) (min of dasatinib. Patients were assigned randomly to a dose-reduction strategy (TDM) group and standard-dose strategy (control) group according to Cmin ≥3 nmol/L. The cumulative prevalence of PE was reduced significantly in the TDM group , whereas the prevalence of MMR was similar. A TDM-guided dose-adjustment strategy for dasatinib was feasible and resulted in a significant reduction in the incidence of PE events without impairing the MMR rate upon long-term treatment.Dasatinib exposure may be related to the clinical response and toxicity profile. The dose-limiting toxicities (DLTs) and clinical response of dasatinib were analyzed in patients with CP-CML at 17 hospitals in South Korea . Those rht (kg)) . Therefoht (kg)) . Rousselht (kg)) . All eliThe ENESTnd study  reportedIn recent years, the experience of discontinuation of TKIs therapy in patients with CML has been reported worldwide. A research team in France reported the first key study in 2007 . They suLee and collaborators  aimed toSTOP-2G  was the A meta-analysis was conducted in patients with CML under a stable DMR to assess the prevalence of TFR and the long-term safety of discontinuation of second-generation TKIs therapy . Five siThe phase-II ENESTFreedom trial  was the LAST  was a prRecently, several retrospective studies have assessed the safety of discontinuation of TKIs therapy outside of clinical trials. One research team  enrolledThe DESTINY study  aimed toIn a retrospective analysis in 2020 , 26 patiA second attempt to achieve TFR may be considered for some patients. The details of trials focusing on a second opportunity to achieve TFR are shown in Switching TKIs are required if there are intolerable toxicities, failure to achieve treatment milestones, or a BCR::ABL1 mutation that leads to resistance to specific TKI, , 81. TheIn addition to imatinib, dasatinib and nilotinib were approved recently for pediatric CML treatment, which has expanded the therapeutic options. Moreover, allogeneic stem cell transplantation suggest to be third-line treatment for most pediatric cases . However2/day) (2/day (maximum to 600 mg). The initial dose of dasatinib is 400-100 mg/m2 qd (maximum to 100 mg) in children with CP-CML (2/dose bid for nilotinib (maximum single dose of 400 mg) (Some research teams based in European groups recommend a lower starting dose of imatinib in children with CP-CML (260–300 mg/m2/day) . However2/day) , and theh CP-CML , and 230 400 mg) . The dosLimited evidence regarding discontinuation of TKIs therapy is available for pediatric CML, mostly in small studies and case series. The Japanese Pediatric Leukemia/Lymphoma Study Group  reportedRecently, increasing numbers of patients with CML have begun to pursue a dose optimization strategy, which included dose reduction and discontinuation of TKIs therapy. In the real-life settings, we will comprehensively consider the dose optimization strategy base on the treatment goal, clinical response, tolerance, and economic situation of patients. A dose-reduction regimen could allow for broader clinical use of TKIs (even in patients with comorbidities). For example, if the elderly patient with multiple comorbidities or is previously intolerant to other TKIs, we may suggest a half-dose of dasatinib treatment (50 mg/day). If conditions permit, the dose can also be adjusted according to blood concentration monitoring. For patients with sustained optimal clinical response (MMR or DMR), reducing TKIs dose can reduce AE and improve treatment compliance. The proposal of TFR as a possible final treatment endpoint should be discussed with patients  at the diagnosis to achieve a DMR rapidly and improve long-term compliance. For patients with stable DMR and long duration of TKIs treatment, it is feasible and safe to stop TKI treatment. Patients who discontinued TKIs should follow the discontinuation standards recommended in ELN or NCCN guidelines. For patients with stable DMR who want to stop TKIs treatment but are afraid of relapse, we recommend to reduce TKIs dose before discontinuation of TKIs therapy. For patients who cannot achieve TFR, the TKIs dose must be reduced without affecting the clinical response. Importantly, patients who underwent dose optimization should be advised for more intensive molecular monitoring, especially during the first 6 months. Once the patients lose the optimal response, physicians should take measures immediately, such as resuming to standard-dose therapy, reintroducing TKIs treatment, or switching to other TKIs, etc. However, evidence for dose optimization in pediatrics CML is limited. Hence, evidence from novel, prospective clinical trials and real-life clinical practice are required to explore dose-optimization strategies, which may provide more promising options for CML treatment.FC: Writing  and data curation. QL: Validation, data curation, and writing . ZC: Data curation. MH: Revision of the original draft. WL: Conceptualization, visualization, and data curation. YZ: Project administration and funding acquisition. All authors contributed to the article and approved the submitted version.


Aspergilli worldwide is adding to the global shortage of food and is affecting its safe consumption. Aspergillus-derived mycotoxins, including aflatoxins and ochratoxin A, and fumonisins (members of the fusariotoxin group) can cause pathological damage to vital organs, including the kidney or liver. Although the kidney functions as the major excretory system in mammals, monitoring and screening for mycotoxin induced nephrotoxicity is only now a developmental area in the field of livestock feed toxicology. Currently the assessment of individual exposure to mycotoxins in man and animals is usually based on the analysis of toxin and/or metabolite contamination in the blood or urine. However, this requires selective and sensitive analytical methods , which are time consuming and expensive. The toxicokinetic of mycotoxin metabolites is becoming better understood. Several kidney biomarkers are used successfully in drug development, however cost-efficient, and reliable kidney biomarkers are urgently needed for monitoring farm animals for early signs of kidney disease. β2-microglobulin (β2-MG) and N-acetyl-β-D-glucosaminidase (NAG) are the dominant biomarkers employed routinely in environmental toxicology research, while kidney injury molecule 1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL) are also emerging as effective markers to identify mycotoxin induced nephropathy. Pigs are exposed to mycotoxins due to their cereal-based diet and are particularly susceptible to Aspergillus mycotoxins. In addition to commonly used diagnostic markers for nephrotoxicity including plasma creatinine, NAG, KIM-1 and NGAL can be used in pigs. In this review, the currently available techniques are summarized, which are used for screening mycotoxin induced nephrotoxicity in farm animals. Possible approaches are considered, which could be used to detect mycotoxin induced nephropathy.The gradual spread of  Aspergillus, Penicillium, and Fusarium . Penicillium-produced CIT and OTA occur most commonly during storage  value of 0.2 μg/kg bw  is the most challenging, exerting species-specific and target organ specific effects  is a frequently occurring kidney problem in humans, and farm animals as well . Early iVarious animal models are widely used to test the nephrotoxic effects of many pharmacologically active substances. Renal biomarkers are defined in terms of their chemical, structural, physiological characteristics. That show the progress, severity or presence of any damage within the kidney that alters its function. As an example, urinary biomarkers including NAG are suitable to estimate the incidence and size of drug-induced kidney injuries . Accordi2-MG, Cystatin-C, alpha-glutathione S-transferase, mu-glutathione S-transferase, NAG, aspartate aminotransferase and NGAL  or cisplatin (CDDP) induce glomerular and proximal tubular injuries, respectively. PAN increased urinary NGAL and albumin levels  meanwhile CDDP was detected with highest sensitivity by KIM-1 . Lactateand NGAL .2-MG, calbindin, clusterin, GST-μ, NGAL, osteopontin, TIMP-1, and VEGF have been also tested  and malondialdehyde and decreased glutathione levels. The gene expression of aryl hydrocarbon receptor (AhR) and pregnane X receptor (PXR) as well as some cytochrome genes  of the phase I xenobiotic transformation were induced by OTA exposure. Moreover, the mRNA expression of phase II enzymes such as heme oxygenase-1, NAD(P)H quinone dehydrogenase 1 (NQO1), and glutamate cysteine ligase were upregulated. The response of OTA-orally administered mice also showed marked increases in these enzymes and KIM-1. These results indicate that OTA induces phase I and II enzymes through the AhR, PXR, and Nrf2 signaling pathways in HK-2 cells, which may lead to the modulation of proximal tubule injury . OTA exp1. This leads to marked cellular disturbances, which are dependent on its molecular structure. As FBs are conformational analogs of free sphinganine, competitively inhibiting the ceramide-synthase (CerS) enzymes  are accepted as interspecific, sensitive FB1 biomarkers, e.g., for humans , leads to a wide spectrum of symptoms based on disturbances in multiple organs: liver and kidney toxicity is the main characteristic in many species  were found to be of diagnostic value in fibrotic kidneys of mice and humans , but a dose–response experiment on HK-2 kidney cells showed an increased expression of Kim-1 correlated with the mRNA level after FB1 treatment , and further possible candidate compounds need much more sensitive detection (LC-TOF or LC-qTOF). These tests are unsuitable for point of care testing but would be of value as confirmatory laboratory-based tests. So far, just limited data is available in connection with FBreatment . Anyway,As mentioned above, the most widely used biomarkers in other fields, are KIM-1, NAG, NGAL, Cystatin-C and β2-MG . There iDifferent procedures exist detecting and quantifying urinary NAG activity, either spectrofluorimetrically or spectrophotometrically using a wide-selection of substrates. There are available a pig N-acetyl-β-D-glucosaminidase (NAG) ELISA Kit, with a detection range of 0.156 –10 mU/mL . ELISA or a chemiluminescent microparticle immunoassay (CMIA) kits are also available for the measurement of NGAL. This biomarker is sensitive biomarker for renal damage to the proximal tubular segment of the nephron of man as well as animals. Pig NGAL ELISA Kits also exists with a detection range of 4–400 pg/mL .Without readily available suitable methods to measure kidney biomarkers, their utility can be limited. Moreover, a wide array of kidney parameters, including novel biomarkers should be analyzed in parallel with mycotoxin metabolites. Quantification of mycotoxins in urine could be achieved by combining with specific KIM-1 tests. This would provide a point of care test for detecting nephrotoxicity caused by mycotoxins in farm animals. Urinary NAG is the predominant enzyme assay used in screening programs and is well suited for screening in low GDP countries. KIM-1 lateral-flow strip tests can be also used for screening programs see .Rapid lateral flow tests are urgently needed for predicting AKI easily and as early as possible. For example rapid tests have been developed for human KIM-1 although the sensitivity may not be sufficient yet to predict AKI . There a1 and CIT are of particular concern and their metabolites supplemented by KIM-1 would initially be a good choice for testing for mycotoxin induced nephropathy. Parallel studies with NAG and NGAL should be carried out to determine their value as screening tests. The availability of these tests would help to alleviate the increasing problem of mycotoxin contamination, but based on those tests the particular mycotoxin cannot be identified. Mycotoxin toxicity is a growing global health problem and the decrease in the amount of animal losses caused by mycotoxin exposure would have ecological as well as economic benefits. On the other hand, urinary kidney biomarkers are specific for kidney damage, but not for mycotoxin induced nephropathy alone. As a consequence, the recommended approach could be useful as a detection method when used in combination with the biomarkers of the mycotoxin metabolism excreted into the urine or blood.Mycotoxins in animal feed is an increasing problem worldwide and their deleterious effects are currently underestimated. They cause potentially severe toxicological problems, affecting both man and animals. Pigs are slaughtered at the age of 6 months and develop kidney disease only very rarely. Feed testing is the routine way to control mycotoxin uptake. Kidney and liver are particularly sensitive to mycotoxin toxins and any problems in these organs compromise overall animal health status and as well meat production. Urinary kidney biomarkers are not generally analyzed in connection with mycotoxin exposure, however, this is recommended as it could help in treating as well as identifying affected animals. The mycotoxins OTA, AFB1, FBZR: literature search, conceptualization, critical reading and discussion, and original draft preparation, review, and writing. LC and IP: literature search, conceptualization, funding acquisition, and critical reading, and discussion. MD: editing the manuscript, with particular focus on tubule physiology and specific biomarkers. RP: revising the English throughout the manuscript and modifying the contents of some of the section. MM, AS, and IB: literature search and critical reading and discussion. All authors contributed to the article and approved the submitted version.The publication was supported in Debrecen by the GINOP-2.3.2-15-2016-00062 project (IP) co-financed by the European Union and the regional Development Fund. Project no. 2018-1.2.1-NKP-2018-00002 (IP) has been implemented with the support provided from the National Research, Development, and Innovation Fund of Hungary, financed under the 2018-1.2.1-NKP funding scheme. The work was partially funded by Hungarian Academy of Sciences (ELKH-MATE 13003) and by the Hungarian National Laboratory project RRF-2.3.1-21-2022-00007 (AS). Project no. TKP2021-EGA-18 has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the TKP2021-EGA funding scheme (ZR and LC). The publication was partially funded by The Kidney Fund (UK) core17-2022/23 (MD) and the European STEP research Programme (RP).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


An automatic method to measure SRETVwb could improve disease status assessment and provide a tool for prognostication. This study aimed to develop an artificial intelligence (AI)-based method to detect and quantify SRETVwb and total lesion somatostatin receptor expression (TLSREwb) from [68Ga]Ga-DOTA-TOC/TATE PET/CT images, where all tumours were manually segmented with a semi-automatic method. The training set consisted of 148 patients, of which 108 had PET-positive tumours. The test group consisted of 30 patients, of which 25 had PET-positive tumours. Two physicians segmented tumours in the test group for comparison with the AI model.A UNet3D convolutional neural network (CNN) was used to train an AI model with [r = 0.78 and r = 0.73, respectively, for SRETVwb and r = 0.83 and r = 0.81, respectively, for TLSREwb. The sensitivity on a lesion detection level was 80% and 79%, and the positive predictive value was 83% and 84% when comparing the AI model with the two physicians.There were good correlations between the segmented SRETVwb and TLSREwb by the AI model and the physicians, with Spearman rank correlation coefficients of It was possible to develop an AI model to segment SRETVwb and TLSREwb with high performance. A fully automated method makes quantification of tumour burden achievable and has the potential to be more widely used when assessing PET/CT images. Well-diClinical interpretation of PET/CT images is a visually subjective assessment, sometimes with manual measurements of maximum standardized uptake value (SUVmax) in PET images and manual measurements of the largest tumour diameter in the CT images. Although the interpretation of SSTR PET/CT has shown good inter-observer agreement, differences between readers still exist and can be clinically significant, particularly when selecting patients for peptide receptor radionuclide therapy (PRRT)  and total lesion somatostatin receptor expression (TLSRE) on Ga-DOTA-TATE to [68Ga]Ga-DOTA-TOC, which is why both radiotracers were included in this study. The radiotracers were prepared according to established techniques  PET/CT system. In 2019, there was a shift in production from [68Ga]Ga-DOTA-TOC and -TATE was considered significant for tumour segmentation if it did not correspond to physiological uptake. The PET/CT examination clinical report was used as a reference for segmentation. No predefined threshold for SUVmax was used. A semi-automatic method was used to delineate the tumours on the PET/CT images, where SRETV was defined as the tumour volume with uptake higher than 50% of SUVmax within a VOI, and TLSRE was defined as the product of SRETV and mean SUV (SUVmean) of the tumour volume  and an experienced nuclear medicine physician (ET) using Hermes software  and correlated with the clinical report. Uptake of Ga-DOTA-TOC and -TATE PET/CT images concerning PFS and OS after treatment with PRRT.A weakness of this study is the lack of external validation, as recently noted by Pantelis et al. in a review of AI and GEP-NEN (Pantelis et al. We do not believe that AI will make radiologists or nuclear medicine specialists obsolete in the near future, but rather increase the value of PET/CT examinations by providing validated imaging biomarkers, such as tumour volume. A future AI method will still require the physician to visually inspect the segmented tumour volume and correct obviously inaccurate lesions. We believe that automated AI models, such as in the field of imaging, could help to improve patient care with better prognostication, prediction of treatment response and for evaluation of follow-up examinations.68Ga]Ga-DOTA-TOC and -TATE PET/CT images. Our AI model showed a good correlation with ground truth with few false positive and false negative lesions per patient. Since segmenting the tumour burden is a time-intensive task, it is not feasible in clinical practice. A clinically validated AI model segmenting neuroendocrine tumour lesions could be of prognostic, as well as predictive value when selecting patients for treatment.To the best of our knowledge, this is the first fully automatic AI model to segment the whole-body somatostatin-expressing tumour volume, SRETVwb, and total lesion somatostatin receptor expression, TLSREwb, on [