The overall drop in StO2 was negatively correlated to RD scaling (in 7 out of 9 cases) and was higher in the irradiated regions when compared to its contralateral region. Differences in the pre-RT StO2 between ipsilateral and contralateral chest wall is a potential predictor of the severity of RD. The subclinical recovery of StO2 to its original state was longer than the visual recovery in RD grading scale, as observed from the post-RT assessment of tissue oxygenation.Over 95% of breast cancer patients treated with radiation therapy (RT) undergo an adverse skin reaction known as radiation dermatitis (RD). Assessment of severity or grading of RD is clinically visual and hence subjective. Our objective is to determine sub-clinical tissue oxygenation (oxygen saturation) changes in response to RT in breast cancer patients using near-infrared spectroscopic imaging and correlate these changes to RD grading. A 4-8 week longitudinal pilot imaging study was carried out on 10 RT-treated breast cancer patients. Non-contact near-infrared spectroscopic (NIRS) imaging was performed on the irradiated ipsilateral and the contralateral breast/chest wall, axilla and lower neck regions before RT, across the weeks of RT, and during follow-up after RT ended. Significant changes (p < 0.05) in oxygen saturation (StO Breast cancer has become one of the most prominent diseases among women in the U.S. and one of women’s leading cause of death . The AmeRadiation dermatitis is a side effect of RT whereby radiation that targets cancer cells inflicts collateral damage to nearby normal skin cells. RD manifestations can be as minor as reddening of the skin (erythema) or as severe as skin ulcerations and necrosis. Currently clinicians visually assess skin tissue health throughout patients’ RT based on the Common Terminology Criteria for Adverse Events (CTCAE) and/or Radiation Therapy Oncology Group (RTOG) grading scales. Currently there is no Level 1 evidence for any product used to treat radiation dermatitis.via in-vivo human and animal studies for various cancer types as given in Many research groups have performed different optical imaging studies to assess the physiological effect of RT on the irradiated tissues, NIR , was employed to generate static 2D tissue oxygenation maps of the tissue. The system utilizes LEDs of multiple wavelengths  within the red-NIR spectrum (650-1000 nm) to acquire diffuse reflectance images of the tissue and use them to compute tissue oxygenation measurements in terms of oxygen saturation (StO2). The device utilizes red lasers as positional indicators during imaging as well as fix the distance between the imaging plane and the device. The device contains a black box feature to correct the StO2 measurements obtained from patients with darker skin, i.e. high melanin concentrations. The NIRS device also acquires digital white light images within the field of view as the tissue oxygenation maps (i.e. 15 × 20 cm) and resolution (960 × 640 pixels). The measurements were acquired by the same team throughout the entire study to minimize operator error.A non-contact NIRS imaging system, known as SnapshotThis study was WIRB approved and was carried out at the Miami Cancer Institute (MCI). Ten (non-metastatic) breast cancer patients were recruited as they received a 4-8 week radiation therapy (RT) treatment. Prior to imaging, patients provided a written consent as well as HIPAA authorization to access their medical records related to the study.Each patient was prescribed 42.6-50.4 Gy in 16-28 fractions. Only 3 of the 10 patients  received an extra radiation boost (10 Gy) towards the end of their RT. Two of the patients were black non-Hispanic (patients 4 and 10) while the rest were white Hispanic or non-Hispanic. Four of the 10 patients (patients 6-9) had a lumpectomy surgery prior to RT while the rest (patients 1-5) had a mastectomy. Eight patients received photon therapy and two received proton therapy. Patients 3-6, 9, and 10 were below 60 years and patients 1, 2, 7, and 8 were ≥60 years of age. Details of each recruited patient and their and treatment plan is given in Imaging of patients was performed weekly over the full duration of their RT, with a follow-up imaging session 4 weeks after the completion of RT. Week-0 of imaging was performed prior to the beginning of the RT (i.e. pre-RT) on all recruited patients. Each weekly imaging session was performed immediately following the clinician’s assessment of RD but before the patient’s scheduled RT procedure. Patients were imaged at an angled sitting position. Images were attained from several regions of breast tissue and its surroundings that were possibly affected by RT .These regions included the chest wall, lower neck, and axilla (underarms). Each region was imaged 3-4 times per session, at slightly varying angles. Each repeated image represented a repeated trial for quantitative and statistical analysis. Both the ipsilateral irradiated areas and their contralateral non-irradiated tissue were imaged at all the regions . Several fiducial markers were placed to obtain an approximate spatial reference across weeks of imaging the same patient. The key fiducial markers were at the inner ends of the clavicle, and close to the nipple region of both the breast tissues. Pre-RT imaging studies were performed to determine correlation of inherent tissue oxygenation differences between the irradiated and the non-irradiated breast tissues on the severity of RD as assessed visually. A one-month post-RT images were also acquired to determine if the rate of tissue recovery from RD was visually similar to the physiological change in terms of tissue oxygenation.2) maps. A manual freehand segmentation technique combined with edge detection was performed on these StO2 maps to isolate only the region of the chest wall within the plane of focus of the device and remove the irrelevant surrounding tissues. The fiducial markers were also segmented out using this technique. Segmentation was not applied to StO2 maps of the lower neck and axilla.The diffuse reflectance signals obtained during imaging studies were automatically processed by the built-in software of the device to obtain tissue oxygenation (StO2 images (as shown in A square region of interest (ROI) was extracted from each segmented  or the non-segmented (lower neck and axilla) StOWithin the extracted ROIs, 40 sample points were randomly selected for statistical relevance. The sample points were used toward further analysis.2 measurements across the ROI were averaged for 3 trials and plotted (with error bars) across time of the RT. A contrast of the average StO2 from each week with respect to average StO2 from the baseline (week 0) was determined as the tissue oxygenation index (TOI), as given in Equation 1. The TOI values were plotted across time of treatment.Analysis of longitudinal changes in ipsilateral and contralateral tissues across chest wall, axilla, and lower neck during RT was done using the sampled ROI data points. The StO2 during RT were significant. The test was applied to each trial individually. The p-value was used to determine if the changes were significant, and the F-value was used to determine the relative extent of StO2 changes across RT when comparing across different cases.A one-way ANOVA  was carried out to determine if the extent of changes in StOThe development of RD was compared to tissue oxygenation 1) pre-RT, 2) during RT, and 3) post-RT.2 differences between the ipsilateral and contralateral chest wall has any correlation with the maximum grade of RD development by the patient during their course of the RT. This physiological information can potentially determine if patients are at risk for severe RD. The pre-RT StO2 contrast between the ipsilateral and contralateral chest wall regions were calculated based on Equation 2. The contrast was then compared to the maximum RD grading scale.The focus of this study was to determine if the baseline (pre-RT) StO2 across weeks of RT. This could provide evidence toward association between the two parameters (StO2 and RD). The changes in average StO2 of the ipsilateral (irradiated) tissues were compared to the development of RD during RT. Due to the ranked data from RD CTCAE grading scale and the discrete data from the average StO2 measurements, nonparametric correlation methods were utilized. One of the statistical methods used was Spearman’s Rho (The focus of this study was to derive correlations (if any) between the development of RD and changes in StOan’s Rho , 15, whiThe second statistical method used was Kendall’s tau , 15, whi2 and RD during RT.The combination of both methods can provide evidence toward the correlation of StO2 changes between post-RT assessment  and last week of RT correlated to the visual reduction in RD grading during the follow-up visit. This could provide clinicians additional sub-clinical information to better assess the healing of tissues affected by irradiation after RT ends. The contrast between average StO2 of the last week of RT and follow-up assessment of the irradiated chest wall was calculated, as given by Equation 5.The focus of this study was to determine if the StOThe post-RT contrast was calculated for the ipsilateral chest wall and compared to the change in RD CTCAE grading between the last week of RT and follow-up assessment. The axilla and lower neck were not graded for RD at the follow-up assessment and omitted from post-RT analysis.2) maps were obtained from all patients and across all weeks of imaging, and a sample case is shown in 2 of the ipsilateral and contralateral chest wall, axilla, and lower next region of patient 2  demonstrated a distinct decrease in the StO2 in both the contralateral and ipsilateral tissues, although it was to a greater extent in the ipsilateral tissue. This indicates that the contralateral regions were exhibiting changes in StO2 in response to RT, although not to a high extent as the ipsilateral tissue.No distinct differences in the StO2 and TOI across weeks of RT from patient 2 is shown in 2 across RT were significant across the imaging time points. The average of the p-values from the three one-way ANOVAs across each trial were further compiled across all patients and imaged regions  to determine if the changes in average StO2 across weeks of RT were significant (i.e. p<0.05).The average StO2 throughout RT. This is consistent with past work, demonstrating that there are changes in hemoglobin parameters throughout RT, especially demonstrating changes in oxyhemoglobin (HbO) during radiation exposure  expressed a significant change (p<0.05) in average StOexposure . The chaue to RT , 17. It ue to RT , 10. All2 across weeks of RT. This further indicates that radiation from RT is having an impact on the contralateral chest wall and axilla regions, apart from the irradiated ipsilateral regions. The impact can be caused by radiation spill from the proton or photon RT received by the patients  and axilla region (n=8) expressed a significant change (p<0.05) in average StOpatients , 19. Rad2 in the ipsilateral chest wall and axilla is greater than the lower neck. Additionally, a relatively high F-value were evaluated for patients 1, 2, 7, and 8 in the chest wall region, whose ages ranged between 61-77 years. This indicates the extent of change of average StO2 in response to RT is greater in older patients (≥ 60 years). This can be from thinning of the skin with age, especially in post-menopause women , although her RT continued and she developed RD. Patient 6 was the only patient that was observed to have a decrease in RD grading during their RT. This may be because her RT was spaced out due to many missed treatment days, allowing her to recover intermittently. Patient 3 was the only patient to begin with an RD grading of 1, as she paused her initial RT and imaging from her first restart week was considered as her week-0 (with RD grading 1). It was noted by several patients that their condition worsened following the conclusion of their RT but was not observed nor recorded by a radiation oncologist for the grading scale until the standard one-month follow up visit.Most patients developed radiation dermatitis (RD) during RT. The most severe cases of RD grading reached grade 2, which occurred in 6 out of 10 patients. In patients 4 and 10, there were no changes in RD grading throughout the RT. However, imaging of patient 10 was interrupted after 4 sessions of StO2 were evaluated to determine if it could be a predictor of the severity of RD that the patient may experience due to the RT. The pre-RT StO2 contrast across the patients was calculated and shown in The contrast between the ipsilateral and contralateral StO2 contrast (>5%). These relatively higher pre-RT StO2 contrast (>5%) correlated to all patients who developed RD grade 2. The difference between the contralateral tissue and the targeted ipsilateral tissue may indicate that physiologically the targeted chest wall had underlying abnormal tissue oxygenation (StO2). This is either attributed to poor vasculature or atypical perfusion. This can indicate that pre-RT tissue oxygenation in the targeted irradiated region may be an indicator of the potential severity in RD because of RT.It was apparent that a majority of patients (n=6) had a relatively higher pre-RT StO2 contrast, it was also noted that a low pre-RT StO2 contrast could be an indicator for less severe RD during RT. Four  out of the ten patients experienced a pre-RT StO2 contrast below 5%. Three out of these four patients  experienced a maximum of RD grade 1 throughout the course of their RT. This further supports the correlation between pre-RT StO2 contrast and maximum RD grade during RT.Consistent with the observation made regarding a high pre-RT StO2 contrast (>5%) and experienced a max RD grade of 2. Among the 4 patients who had received a lumpectomy, 3 had a relatively low pre-RT StO2 contrast (<5%) and 2 had experienced a max RD grade of 1. This is congruent to what has been observed in the past, that patients that undergo mastectomy tend to experience more severe RD from RT, compared to lumpectomy patients  during RT. The correlation coefficients for Spearman’s Rho and Kendall’s Tau were evaluated and plotted in Statistical correlation tests were utilized to evaluate if the changes in RD grading had a relationship with the changes in tissue oxygenation . This may indicate that at the 1-month assessment, patients may still have underlying physiological abnormalities with respect to the StO2. In the cases (n=3) where the follow-up assessment occurred 3+ months after the last week of RT, a relatively higher post-RT StO2 contrast . This could indicate that the patients’ underlying tissue oxygenation, which decreased with RT was increasing with time after completion of RT, indicating vasculature and tissue recovery of those affected regions at a slower pace than visual changes. Clinicians and patients have noted that in the weeks after RT concludes and before the follow-up assessment, patients continue to experience worsening adverse effects from RT. The adverse effects can be as severe as moist desquamation coupled with bleeding which indicates grade 3 RD. This may give evidence toward prolonged effects of RT and would indicate why high negative post-RT StO2 contrast was evaluated for patients at the 1-month follow-up assessment.It was noted that in a majority of the patients, the RD grading decreased to a 0 or 1 by the follow-up assessment, while in 2 cases it remained the same (patients 4 and 8). All the cases where the follow-up assessment was 1-month from the last week of RT (n=7) displayed a relatively high negative post-RT StOin-vivo head and neck cancers and breast cancer patients and/or via animal studies  in many cases initially increased with the onset of RT, possibly from an inflammatory response of the skin to radiation. Upon continued RT, the overall oxygen saturation decreased across weeks and this drop correlated negatively with the severity of RD. The changes in physiology from RD have an impact on tissue oxygenation and how hemoglobin travels to certain regions of tissue. Inflammation is generally an early and common adverse reaction that is induced by RT. Inflammation is the body’s response to remove any foreign pathogens and isolate any injuries to a localized region by increasing vascular permeability with vasodilation. This allows neutrophils, monocytes, and nutrients to localize to the region . This reApproximately 95% of the patients will develop skin erythema and will manifest RD of different grading scales , 24, 25.Our hypothesis was that pre-RT vasodilation and angiogenesis contributed to RD in RT treated breast cancer patients; and tissue oxygenation measurements are directly related to these two physiological parameters that can be measured using a near-infrared imaging approach. From our current studies, we proved our hypothesis that the difference in tissue oxygenation contrast between the irradiated ipsilateral and the contralateral chest wall was a potential indicator of RD severity (grade 2 or lesser). This implies that there are inherent differences in breast’s tissue oxygenation in response to surgical removal of cancer (more so in mastectomy than lumpectomy) that potentially leads to a severe skin toxicity upon RT. Early identification of differences in these oxygenation differences pre-RT is essential to determine ways to predict extent of toxicity and guide interventional therapies, when used in conjunction with other dosimetric and non-dosimetric factors that assess RD risk.Understanding the physiological changes after the completion of the RT effect was also performed in our study. While the severity of RD decreased during the one-month follow-up visit, the tissue oxygenation did not recover (or increase). In cases where we imaged during their third-month follow-up, the tissue oxygenation seems to have increased more distinctly from the last RT treated visit. This implies that the physiological recovery is slower than the visual RD grading as observed. Several patients observed an increase in RD severity after completion of their RT but were not clinically assessment until the one-month follow-up. This severity in RD could have lowered the tissue oxygenation even further and shown as a slower recovery during their follow-up visit. In future studies, the weekly imaging after completion of RT will need to be carried out to continuous monitor these oxygenation changes along with clinical assessment towards better correlations and understanding the underlying physiology.2) of the ipsilateral and contralateral chest wall and axilla during RT. These changes were evaluated to be negatively correlated to the development of radiation dermatitis (RD). It was also shown that pre-RT assessment of StO2 can potentially be part of the contributing factors toward risk assessment to determine if a patient is pre-disposed to adverse reactions during RT. Post-RT assessment of StO2 showed potential in providing additional sub-clinical information to monitor RD and tissue health after the completion of RT to assess complete extent of recovery. Future work will involve a larger focused subgroup of these RT treated breast cancer patients to develop threshold factors from pre-RT analysis that can predict the severity of RD along with non-clinical parameters and comorbidities. The effect of various clinical factors such as time between surgery and RT, chemotherapy used during surgery or RT, hormonal agents used during RT, and ointments used to tread RD severity. Our imaging approach will also be expanded to head and neck cancer patients to develop physiological and non-clinical parameter-based risk assessment in RD prediction, RD monitoring during RT, and physiological recovery rate post-RTThe objective of our studies was to derive correlations between tissue oxygenation and skin toxicity in breast cancer patients by monitoring their tissue oxygenation changes throughout their radiation therapy using a NIR-based imaging technique. The studies demonstrated significant changes in oxygen saturation (StOThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by WIRB-A WIRB Copernicus Group Company. The patients/participants provided their written informed consent to participate in this study.ER: The lead author to have performed all the imaging studies, developed study design, data analysis, and writing the manuscript. JM: Involved in data management and data analysis. RM: Was involved in complete statistical analysis along with the first author. KL: Involved in clinical visits and imaging studies along with the first author. CB: Involved as the clinical coordinator in the patient recruitment, and assistance during imaging studies. MR, MF and JP: Radiation oncologists who provided clinical assessments and feedback on each patient. JP also assisted in proposing image analysis and discussion of our results and manuscript submission. MC: Radiation oncologist who was the key investigator at Miami Cancer Institute responsible in the initial study design, IRB approvals, establishing the study, and assistance in the manuscript submission. WW: Biostatistician who assisted in all the statistical analysis and methods to implement for this study. AG: Corresponding author who led the entire study and the effort from proposing the idea, executing it, and completing this manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the Coulter Seed Grant from FIU CEC-BME.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.


Artificial intelligence (AI) has shown promising results when used on retrospective data from mammographic screening. However, few studies have explored the possible consequences of different strategies for combining AI and radiologists in screen-reading.A total of 122,969 digital screening examinations performed between 2009 and 2018 in BreastScreen Norway were retrospectively processed by an AI system, which scored the examinations from 1 to 10; 1 indicated low suspicion of malignancy and 10 high suspicion. Results were merged with information about screening outcome and used to explore consensus, recall, and cancer detection for 11 different scenarios of combining AI and radiologists.Recall was 3.2%, screen-detected cancer 0.61% and interval cancer 0.17% after independent double reading and served as reference values. In a scenario where examinations with AI scores 1–5 were considered negative and 6–10 resulted in standard independent double reading, the estimated recall was 2.6% and screen-detected cancer 0.60%. When scores 1–9 were considered negative and score 10 double read, recall was 1.2% and screen-detected cancer 0.53%. In these two scenarios, potential rates of screen-detected cancer could be up to 0.63% and 0.56%, if the interval cancers selected for consensus were detected at screening. In the former scenario, screen-reading volume would be reduced by 50%, while the latter would reduce the volume by 90%.Several theoretical scenarios with AI and radiologists have the potential to reduce the volume in screen-reading without affecting cancer detection substantially. Possible influence on recall and interval cancers must be evaluated in prospective studies.Different scenarios using artificial intelligence in combination with radiologists could reduce the screen-reading volume by 50% and result in a rate of screen-detected cancer ranging from 0.59% to 0.60%, compared to 0.61% after standard independent double reading• The use of artificial intelligence in combination with radiologists has the potential to identify negative screening examinations with high precision in mammographic screening and to reduce the rate of interval cancer•  Breast cancer is the most frequent cancer and the second most frequent cause of cancer death among women worldwide . MammogrEuropean Commission Initiative on Breast Cancer suggests using double over single reading of mammograms for early detection of breast cancer in screening programs . The oveArtificial intelligence (AI) has been introduced in numerous areas of healthcare and is unaffected by reading conditions and subjectivity. In the field of mammographic screening, retrospective studies on AI have shown promising results in the classification of cancers –11. HoweAI can be used in different ways in a screening setting, and different AI systems may be designed to be used in a specific setup. For instance, AI can be used as a standalone system to directly select examinations for consensus or recall (replacement), as a triage system where examinations are interpreted by no, one or two radiologists based on the risk score from the AI system, or as one reader in an informed or independent double reading setting. Knowledge of the ideal combination of AI and radiologist is sparse . This isReduced workload for breast radiologists is an important aspect of using AI in screen-reading. Interpreting screening mammograms is a time-consuming process and about 99.4% of the examinations are determined to have a negative outcome . FurtherIn this retrospective study, we merged screening outcomes from women attending BreastScreen Norway with AI scores and explored consensus, recall, and cancer detection for different theoretical scenarios of AI and the radiologists in screen-reading.This study was based on retrospective image data and screening information collected in BreastScreen Norway, a population-based screening program administered by the Cancer Registry of Norway . The stuIn Norway, all women aged 50–69 are offered a biennial two-view mammographic screening of each breast. The standard procedure is independent double reading by breast radiologists . The radA total of 132,195 digital mammographic examinations were performed at four different screening facilities in Central Norway Regional Health Authority during the period from 2009 to 2018. The examinations were interpreted at two breast centers. After exclusions, the final study sample included 122,969 examinations from 47,877 women, resulting in 2–3 screening examinations for each woman  and correctly marked with a high AI score, there could be a chance of detecting these cases as screen-detected. In scenario 11, we presented interval cancers that AI selected to be recalled. In the real screening setting, some of these cases were not actually recalled.Screen-detected cancers were defined as breast cancer diagnosed after a recall and within 6 months after the screening examination. Both ductal carcinoma in situ and invasive carcinoma were considered breast cancer. Interval cancers were defined as breast cancers diagnosed within 24 months after a negative screening or 6–24 months after a false-positive screening result . For thea, screen-detected cancers not among recall examinations for the different scenarios and all interval cancers were considered false negatives and in b, screen-detected cancers not among recalls and interval cancers not selected for consensus were considered false negatives.In the analysis of the sensitivity, for the real setting of independent double reading, screen-detected cancers were considered true positive and interval cancers were considered false negative. For all scenarios, we considered true positive to be (a) screen-detected cancers only and (b) screen-detected and interval cancers where prior screening examination was selected for consensus or recall for scenario 11. In Categorical variables were presented with frequencies and percentages. In the scenarios where AI was used as one reader, we could have combined AI score with radiologist 1 (R1), radiologist 2 (R2), or a random combination of the two from the independent double reading setting to estimate the different rates. Due to independent double reading, we expect similar results for the two readers, but we have presented results for AI and R1 only as the first reader are, by definition, independent. Sensitivity with a 95% confidence interval (CI) was calculated with the logit-transformed formula based on true positives and false negatives as described above. Confidence intervals for the potential rate of screen-detected and interval cancers were adjusted for non-independent observations. Stata version 17.0 for Windows (StataCorp) was used to analyze the data.Consensus was 8.8%, recall 3.2%, screen-detected cancer 6.1 per 1000 examinations, and interval cancer 1.7 per 1000 in the study sample, after independent double reading in a real screening setting  of the screen-detected cancers . Including 95% CI for the sensitivity of the different scenarios with screen-detected cancers as true positive cases, estimated sensitivity and lower CI limits were above 70% for scenarios 1–4 and 7–9 Fig. . In a prIn this study using retrospective data from two breast centers in BreastScreen Norway, we estimated consensus, recall, and cancer detection rates for different theoretical scenarios of AI and radiologists in screen-reading. In scenarios 1 and 2, AI was used as one of two readers, and in scenarios 3–10, AI score was used to select examinations to be single or double read by radiologists. We found results for scenarios 1–4 and 7–9 to be promising as the recall rate is estimated to be reduced without observing a substantial decrease in the estimated cancer detection rate.The estimated reduction in screen-reading volume was similar in a setting where AI and one radiologist read all examinations and selected cases for consensus (scenarios 1 and 2) and in a setting where examinations with an AI score of 1–5 were considered negative and 6–10 was read by two independent radiologists (scenario 3). There are pros and cons to both scenarios. From the same study sample, 23% of the screen-detected cancers were detected by only one of the two radiologists . A propoThe evidence of the potential AI has to reduce interval cancer rate at the expense of an increased (or non-inferior) screen-detected cancer rate is very limited. A research group from Sweden did an informed review of prior mammograms from 429 interval cancers. A total of 58% (83/143) of the interval cancers with an AI score of 10 were classified as a minimal sign or missed and correctly localized by the AI system . This nuIn scenarios 1 and 2, a proportion of the included screen-detected cancers were selected for consensus by the AI system and not R1. In the independent double reading setting, these cancers were detected due to the interpretation score by R2. The inclusion of these cases might overestimate the screen-detected cancer rate for scenarios 1 and 2 as it might not be reasonable to assume that all cases considered negative by a radiologist and positive by AI would be recalled after consensus. However, despite being selected for consensus by AI only, we chose to keep these cases as true positives as we expect some of these cases to be recalled due to the high AI score and the consensus with two or more radiologists. In scenario 2, a total of 9% of the 729 screen-detected cancers were selected for consensus by AI only. On the contrary, 10% were selected for consensus only by R1 and not AI. This means that 81% of the cancers were selected for consensus by both R1 and AI, and we consider the rate not to be substantially overestimated.overall recall rate, i.e., recalled cases among all examinations, might not be influenced since AI defined cases that were discussed in consensus and recalled after independent double reading to be negative, i.e., not selected for consensus. However, we expect the examinations with a high score to be more time-consuming for the radiologists to screen-read compared to those with lower AI scores. The reduction in screening volume is thus not representing all aspects of workload.The optimal threshold of the AI score for selecting cases for single or independent double reading is difficult to decide to safely reduce volume. By substantially reducing the screen-reading volume, a higher consensus rate than the average in independent double reading might be an acceptable trade-off. How this will influence the subsequent recall rate and the costs are important aspects to consider. The recall rate among cases discussed at consensus might increase. However, the If AI is used as decision support at consensus and not in the interpretation process, we expect the estimated consensus rates in this study to be about the same in a prospective setting with a similar setup. If AI scores and hotspots are made available for the radiologists during the individual interpretation process, the numbers might differ from our estimates since interpretations and conclusions are expected to be influenced differently than being presented to AI findings at consensus .The strength of our study is the large study population from a real screening setting, including screen-detected as well as interval cancers. Rates of screen-detected and interval cancers vary among breast centers in BreastScreen Norway, and AI in screen-reading might support some centers more than others. During the first 20 years of screening in Norway, 1996–2016, the screen-detected cancer rate ranged from 4.4 to 6.7 . IncludiIn conclusion, different scenarios of using AI as a support in mammographic screening have the potential to reduce screen-reading volume without reducing the rate of screen-detected cancers. Possible reduction of interval cancers and rates of false-positive results for the different scenarios have to be evaluated in prospective studies.


Extracting life history information from mineralized hard tissues of extant and extinct species is an ongoing challenge in evolutionary and conservation studies. Primary lamellar bone is a mineralized tissue with multidien periodicity that begins deposition prenatally and continues until adulthood albeit with concurrent resorption, thus maintaining a record spanning several years of an individual’s life. Here, we use field-emission scanning electron microscopy and energy-dispersive X-ray analysis to measure the relative concentrations of calcium, phosphorous, oxygen, magnesium and sodium in the femora of seven rhesus macaque with known medical and life-history information. We find that the concentration of these elements distinguishes parous from nulliparous females; that in females calcium and phosphorus are lower in bone formed during reproductive events; and that significant differences in relative magnesium concentration correlate with breastfeeding in infants. The reconstruction of demographic patterns and life-history scheduling of both extant and extinct mammalian species is an ongoing challenge in several disciplines, including evolutionary biology, conservation studies and biological anthropology. The reconstruction of life-history scheduling has been routinely addressed via the histological analysis of mineralized tissues. These tissues act as recoding structures , keepingLamellar bone is an incremental tissue formed according to a coordinated internal biological rhythm. It is the same rhythm visible in the Retzius Periodicity (RP) of enamel  and it rThe skeleton participates to whole organism physiology and reflects alterations in endogenous and exogenous conditions by undergoing changes in both growth rate  and elemElemental analysis employing laser ablation inductively coupled plasma mass spectrometry on skeletal remains associated with known ages at life-history milestones has shown that weaning is recorded in the teeth of walruses , humans In this study we use field emission (FE) SEM-EDS to measure changes in five major and minor element concentrations  in the femora of seven male (n = 3) and female (n = 4) rhesus macaques with known medical and life-history information. Given the participation of the skeleton to the metabolic demands of reproduction, we predict the following:The elemental composition across all bone of parous females will be significantly different from that of males and nulliparous females.P and Ca concentrations will be lower in the tissues formed during pregnancy and lactation.Maternal relative percent concentrations of Mg will be higher in the bone formed during pregnancy and lactation since other elements, such as P and Ca, will be transferred to a proportionally greater extent than Mg.Relative percent concentrations of Mg in infants will be lower in the tissues formed during breastfeed than after weaning is completed, since other elements, such as P and Ca, will be transferred to a proportionally greater extent than Mg.The present work did not require IACUC approval as it neither used live subjects, nor did it require sacrificing any animals. All the individuals in this study died from causes unrelated to this research. The research adhered to the American Society of Primatologists’ Principles for the Ethical Treatment of Nonhuman Primates. The skeletonized specimens were acquired from the Caribbean Primate Research Center (CPRC). Prior to their death the animals were housed at the Sabana Seca field station of the University of Puerto Rico where they were provisioned with monkey chow. Veterinarians at the Field Station monitored and recorded information on their health and reproductive history. The IDs of the seven femora used in this study, together with each individuals’ sex, parity and dates of birth and death are reported in We selected the right femora of each of the seven individuals. We removed a ~1.0 cm block from the midshaft of each femur. Each block was cleaned, dehydrated using progressively higher-concentration solutions of ethanol, and then embedded in poly methyl methacrylate (PMMA) following procedures described in detail by Goldman and colleagues . Both siEach block was imaged in reflected circularly polarized light (CPL) using a Leica DMRXE microscope fitted with an automated X, Y and Z stage. We collected a montaged micrograph of each block at a resolution of 1.3 μm / pixel. Given the high resolution with which these micrographs were acquired, the identification of contiguous patches of lamellae was unambiguous. On each block, we used the reflected CPL montages to identify two regions fulfilling our criteria of contiguity across which we collected the data, from here onwards identified as Transect 1 and Transect 2. The CPL montages were used as references for the SEM imaging, which was performed before proceeding with the EDS data collection. Once we identified on the EDS the same field of view that we had chosen with the CPL images, we verified that the patches of lamellae were indeed contiguous, and only then proceeded to acquire EDS data.To be suitable for high-vacuum SEM imaging and EDS analysis, we uniformly carbon-coated the blocks using a Denton Desk V . The thickness of the carbon coating is ~20nm. It is also worth noting that Monte Carlo simulations , 30 cleaAll data were collected using a Bruker Quantax 200 XFlash 6160 EDS detector  coupled with a Zeiss Gemini-300 FE-SEM . Before collecting the data, we confirmed by imaging in the SEM that the surface was free of any topographical relief. We acquired the data with the following SEM settings: in high vacuum mode, with an accelerating voltage of 15kV, with an electron beam aperture of 60μm, in high current mode and with a working distance of 8.5mm, which is the analytical working distance of this particular microscope and detector setup. We acquired the data in line scan mode and collected one line scan per segment. The spot size was set each time to match the radius of the interaction volume of the beam, which was consistently ~1.0μm since all the samples had similar composition and were analyzed with the same experimental conditions. The scan dwell time was set at 64μs, and the spectrometer throughput at 275Kcps. To ensure that we had at least 10,000 counts for each peak, the scan time was manually determined for each specimen since they varied in dimension (length of the segment). We used the zero kV peak to make sure that each spectrum was properly aligned. After acquisition was complete, we used the P/B-ZAF standardless analysis quantification model  in interEach transect  was acquired in several separate segments , moving from the periosteal surface towards the endosteal one. The spectra corresponding to each segment is available online as supplementary data (see the Data Availability Statement). Each segment was chosen to avoid osteocyte lacunae and dehydration cracks as best we could. Details regarding the segments collected for each transect are available in The carbon-coated side of each block was mounted on an EXAKT  plastic slide using cyanoacrylate adhesive. Using a Buehler  Isomet 1000 saw we sectioned the block so that a ~150-μm thick section remained attached to the slide. Each section was then ground to 100 ± 10 μm and polished with a 0.1-μm diamond suspension. The resulting thin sections were imaged using the same Leica DMRXE microscope but in transmitted circularly polarized light (CPL). We acquired a montaged image of each section at a resolution of 0.325 μm / pixel. Since we mounted the carbon-coated surface directly on the plastic slide, without polishing or otherwise touching the surface, these micrographs clearly show the segments that were targeted by the electron beam of the SEM.To analyze the possible correlations between the elemental data and the differing physiological states of the animals we assigned a chronological age range to each transect . First, First, we discarded the data points collected over any cracks. Then, within each data file and corresponding to each acquisition point across the femoral transect, we added the following variables: age; category and specific type of event relating to reproduction and weaning; type of individual .Illnesses and traumas were detailed in the life histories, so we were able to track in time the progression of an affliction. For gestation, we began at the point in bone corresponding to an offspring’s date of birth and counted back 5.5 months (c. 165 days) prior –37. LactIn most cases, there was only one Specific Event for a given period, but for some individuals, two Specific Events may have been experienced simultaneously. These cases were mostly related to females who experienced illness while pregnant or lactating. In these scenarios, the reproductive specific event took precedent and thus we coded it accordingly.Carbon coating our specimens artificially increased concentrations of C, rendering absolute elemental values problematic. Instead, we analyzed the data in a way that they would reveal any changes in elemental composition over time . To this end, we pre-processed our original data in two different ways, each one aimed at addressing a different question:Within each data file we scaled the data for each element, which was originally recorded as net total (NETTO) counts, such that the minimum value would be 0 and the maximum would be 1. This type of processing provides information regarding the behavior of a single element over time. We use this data to address prediction 2. This dataset is referred to as “normalized data”.1%Mg = NETTOMg / (NETTOMg + NETTONa + NETTOP + NETTOCa + NETTOO)*100. This implies that the resulting relative percent concentrations reveal how changes in the concentration of one element are correlated with changes in the concentration of the other ones. This type of data allows us to analyze of the simultaneous behavior of several elements as their numerical relationship is maintained, even if all the values are artificially increased by the absence of C. We used these data to address predictions 1, 3 and 4. This dataset is referred to as “percentage data”.Within each sample, we eliminated the values for C and then calculated the percent concentration for each element at each acquisition point. For example, at tpair.test.all, remove.ns and final) to identify individuals who were significantly different from all other individuals belonging to different groups, defined as either male, nulliparous or parous female. Additionally, we performed a principal component analysis (PCA) to visually appreciate the separation between the different types of individuals. For predictions 2, 3 and 4 we ran Bonferroni-corrected two-tailed pairwise t-tests to assess whether there were significant differences in elemental composition associated with either maternal reproductive events or infant breastfeeding. Primary lamellar bone stopped forming before M591 experienced her single reproductive event. Since the age range of primary lamellar bone for M591 (5.3 to 7.5 years) did not encompass the age at which this female gave birth (7.8 years), data from this individual was not included in the analyses for predictions 2 and 3, which test the elemental composition of bone formed during reproductive activity.All data analysis was carried out using R version 3.6.3 . For prediction 1, we used proprietary scripts  for the two parous females  in both transects of MA024  and CK85As per prediction 1, we find that there is a significant difference  in relatIn agreement with the vast body of literature documenting the physiological response to the mineral needs of the developing fetus and infant –19, 44, The combined findings of prediction 1 and prediction 2 indicate that: overall Ca concentrations are lower in parous females compared to other individuals, and that they are even significantly lower in the bone of these females formed during reproductive events as bone resorption increases . ConversIn agreement with prediction 3 and partially with prediction 4, Mg relative percent concentrations are significantly different in the maternal bone formed during gestation and lactation, and in the bone formed while an infant is breastfeeding. Since the data pre-processing that we performed returns relative percent concentration of each element at each acquisition point across the femoral transects, our results indicate that during reproduction Mg might be lost by the mother proportionally less than the other elements, while concurrently received proportionally less than other elements by the breastfeeding infant. This is in agreement with research on humans showing that serum Mg is minimally altered during reproductive activity –48, whilDue to the margin of error likely associated with the chronological age assigned to each bone transect, we did not test for elemental signatures of more punctual events, such as physical trauma.The findings regarding the elemental changes associated with reproduction are of relevance as the detection of parturitions from mineralized tissues is still a vastly unexplored area of research with significant implications for evolutionary, conservation and archaeological studies. However, given the small size of our sample and limited taxonomic breadth, further research on more animals, preferably from wild populations, is necessary to determine the scalability of these results. It would be important to use femora from wild populations as the present specimens were both provisioned and sheltered from extreme climatic events. It is therefore possible that the signal of reproductive events and weaning that we detected could be masked, in wild populations, by physiological responses to changing diets and environments. From an analytical perspective, studies on animals with lower lamellar growth rate would benefit from an increase in the temporal resolution of the data, while those on species with higher growth rate  would likely have to employ sampling methods with higher spatial resolution (e.g. laser-ablation inductively coupled mass-spectrometry). Indeed, in our sample rhesus macaque primary lamellar bone growth rate is the range of 0.75 to 1.25 μm/day, while in humans a range of 0.63 to 0.88 μm/day has been reported . Hence, S1 FigThe red lines indicate the locations of transects 1 and 2. For each transect we report the length in micrometers; the yearly growth rate; the age range covered by the transect. For a description of the method used to derive the ages, see the (TIF)Click here for additional data file.S2 FigThe red lines indicate the locations of transects 1 and 2. For each transect we report the length in micrometers; the yearly growth rate; the age range covered by the transect. For a description of the method used to derive the ages, see the (TIF)Click here for additional data file.S3 FigMontaged micrograph of the femur of M526 obtained in reflected light. The red lines indicate the locations of transects 1 and 2. For each transect we report the length in micrometers; the yearly growth rate; the age range covered by the transect. For a description of the method used to derive the ages, see the (TIF)Click here for additional data file.S4 FigThe red lines indicate the locations of transects 1 and 2. For each transect we report the length in micrometers; the yearly growth rate; the age range covered by the transect. For a description of the method used to derive the ages, see the (TIF)Click here for additional data file.S5 FigThe red lines indicate the locations of transects 1 and 2. For each transect we report the length in micrometers; the yearly growth rate; the age range covered by the transect. For a description of the method used to derive the ages, see the (TIF)Click here for additional data file.S6 FigThe red lines indicate the locations of transects 1 and 2. For each transect we report the length in micrometers; the yearly growth rate; the age range covered by the transect. For a description of the method used to derive the ages, see the (TIF)Click here for additional data file.S7 FigFor each transect we report the length in micrometers; the yearly growth rate; the age range covered by the transect. For a description of the method used to derive the ages, see the (TIF)Click here for additional data file.S8 FigAs visible by the superimposition between blue and yellow datapoints, age is not a discriminating factor.(TIF)Click here for additional data file.S9 FigThe data from both segments of the same individual are pooled together. There is clear separation between parous and nulliparous females. Dot size is proportional to age. It is clearly visible that the separation between parous and nulliparous females is independent of age (dot size).(TIF)Click here for additional data file.S10 FigCa values are significantly lower only in Transect 2 (p<0.00001).(TIF)Click here for additional data file.S11 FigP values are significantly lower only in Transect 2 (p<0.00001).(TIF)Click here for additional data file.S12 FigThere is a significant difference only in Transect 2 (p<0.001).(TIF)Click here for additional data file.S13 FigThe difference is significant in both transect 1 and transect 2 (p<0.00001).(TIF)Click here for additional data file.S14 Fig(TIF)Click here for additional data file.S1 TableAges are reported in years. The duration of each medical event was inferred from the duration of the medical treatment received by the animal, while the duration of gestation was assumed to be the same for all individuals and taken from the published literature, as reported in the Supplementary Methods section.(XLSX)Click here for additional data file.S2 TableFor each transect: five measures of lamella thickness and corresponding yearly growth rate; average (avg) value of lamella thickness and corresponding growth rate, together with the standard deviation (sd).(XLSX)Click here for additional data file.S3 TableValues reported as 0 are actually extremely small, but below the reporting threshold of the pairwise.t.test function in R.(XLSX)Click here for additional data file.S1 File(DOCX)Click here for additional data file.


Obtaining a booster dose of coronavirus disease 2019 (COVID-19) vaccine is required to maintain the protective level of neutralizing antibodies and therefore herd immunity in the community, and the success of booster dose programs depends on public acceptance. The aim of this study was to determine the acceptance of a booster dose of COVID-19 vaccine and its drivers and barriers in Indonesia. A cross-sectional survey was conducted in the provinces of Indonesia between 1 and 15 August 2022. Individuals who completed the primary series of the COVID-19 vaccine were asked about their acceptance of a booster dose. Those who refused the booster dose were questioned about their reasons. A logistic regression was used to determine the determinants associated with rejection of a booster dose of COVID-19 vaccine. A total of 2935 respondents were included in the final analysis. With no information on the efficacy and safety of the COVID-19 vaccine, 95% of respondents agreed to receive a booster dose if it were provided for free by the government. This acceptance was reduced to only 50.3% if the vaccine had a 75% efficacy with a 20% chance of side effects. The adjusted logistic regression analysis indicated that there were eight factors associated with the rejection of the booster dose: age, marital status, religion, occupation, type of the first two vaccines received, knowledge regarding the importance of the booster dose, belief that natural immunity is sufficient to prevent COVID-19 and disbelief in the effectiveness of the booster dose. In conclusion, the hesitancy toward booster doses in Indonesia is influenced by some intrinsic factors such as lack of knowledge on the benefits of the booster dose, worries regarding the unexpected side effects and concerns about the halal status of the provided vaccines and extrinsic determinants such as the effectiveness and safety of the vaccine. These findings suggest the need for more campaigns and promotions regarding the booster dose benefits to increase its acceptance. Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still a major public health problem with a significant impact globally, including in countries in Southeast Asia such as Indonesia . The evidence shows waning protection from COVID-19 vaccines against infection over time due to declining immunity and the emergence of the new variants ,5 raisinAs Indonesia is still struggling to distribute booster doses to an adequate number of people, understanding the basis to vaccine acceptability is critical for developing strategies to immediately form community health resilience . Previoun = 8), considered possible (n = 15) and probable (n = 1) [In addition, some of the uncertainties related to the COVID-19 vaccine’s safety also contribute to vaccine acceptance . Side ef (n = 1) . The cur (n = 1) ,30. A study about the acceptance of the COVID-19 vaccine booster in two provinces of Indonesia showed that the socioeconomic determinants, health beliefs, social media and trust in government information were associated with booster dose acceptance . An updaA cross-sectional survey was conducted in Indonesia covering five main islands in the country. Individuals who were Indonesian citizens, over 18 years old and had completed the primary series of COVID-19 vaccination were eligible to participate in this study. The respondents were asked about their acceptance of a booster dose. Those who were hesitant were asked about their reasons and barriers. The Ethical Committee of the School of Medicine, Universitas Syiah Kuala, examined and approved the study protocol (No. 008/EA/FK/2022 and registration number 1171012P). All respondents who participated in the study provided their informed consent. The dependent variable of the study was the acceptance of a booster dose of COVID-19 vaccine. To assess the acceptance, the respondents were asked whether they would accept a booster dose of COVID-19 vaccine if it were provided freely by the government without information about the efficacy or safety of the booster dose. Subsequently, in order to assess the role of different vaccine profiles, respondents were then asked about their acceptance of a booster dose of the vaccine with different efficacies  and different chances of side effects such as fever or local pain (5% or 20%). The plausible explanatory variables of booster dose acceptance in this study ranged from sociodemographic data ; knowledge and belief about the safety and efficacy of the COVID-19 vaccine; perceived risk of COVID-19 infection; previous COVID-19 infection; experiences surrounding previous COVID-19 vaccinations and knowledge about the vaccine benefits. The questionnaire consisted of several different sets of questions. In the first section, respondents were asked demographic information . The second section asked about knowledge of a booster dose of the COVID-19 vaccine where the respondents’ knowledge regarding the booster dose effects was asked in four questions that could be responded with “yes”, “no” or “not sure”: (1) whether a booster dose can give better immunity, (2) whether a booster dose can stimulate the production of antibodies for protection against COVID-19, (3) whether a booster dose can lower the hospitalization rate of COVID-19 infection and (4) whether a booster dose can protect unvaccinated people. The accurate answer to an item was scored as one, whereas an incorrect/uncertain response was scored as zero. The third section was about the awareness of the importance of a booster dose of the COVID-19 vaccine. The acceptance for a booster dose of the COVID-19 vaccine is assessed in Section four, including the booster doses’ country of origin. Section five evaluates the respondents’ perceptions of booster doses with four questions: (1) whether the respondent worried about the side effects or allergic reactions towards a booster dose, (2) whether there is a belief that the booster dose is crucial, (3) whether a booster dose is useful in protecting people from COVID-19 and (4) whether a booster dose is safe. The possible responses ranged from “strongly agree” to “strongly disagree”. For each “strongly agree” and “agree” response, respondents were given a score of one, while each “neither agree or disagree”, “disagree” and “strongly disagree” response received a score of zero.The next three sections asked about the perceived severity of COVID-19, the perceived benefit of the booster dose and the perceived barriers to getting the booster dose in Indonesia. Perceived severity was assessed using two questions: (1) COVID-19 may lead to a severe condition and (2) fears of unexpected side effects of a booster dose of COVID-19 vaccine in the future. Perceived barriers on getting the booster dose were assessed using two questions: (1) whether the respondents doubted the halal status about the booster dose and (2) whether it takes a lot of time and effort to get the booster dose. In addition, in the last section, to further explore the acceptance and hesitancy of a booster dose of the COVID-19 vaccine, the respondents were asked about their motivations to be vaccinated and the factors that influenced their decision to accept the booster dose. One respondent could choose more than one motivation or factor. www.surveymonkey.com). To cover all the main island groups in Indonesia, 31 local enumerators were recruited who were responsible for data collection. The electronic links were distributed to community members through the local enumerators’ social networks, including WhatsApp, Telegram, Messenger, Line, Facebook, Instagram and Twitter. Before completing the questionnaire voluntarily, each potential respondent provided informed consent by clicking the “Agree” button. The next page of the survey was opened automatically if the respondent agreed to participate. When the respondent clicked the “Agree” button, any responses provided by the respondents were recorded and collected automatically, even if the survey was not completed. To ensure anonymity and confidentiality, no identifiable details of personal information were collected. There was no compensation promised or provided to the respondents.The data collection was conducted between 1 and 15 August 2022 on the Survey Monkey platform. It is an online survey software using the web interface that allows the authors to use multiple pages and logics during the survey (p < 0.05) were included in the adjusted analysis, with the output being an adjusted odds ratio (aOR). Statistical significance was defined as p < 0.05.All analyses were conducted using SPSS version 20 . For continuous variables, descriptive statistics were reported in means and standard deviations (mean ± SD), whereas categorical variables were summarized using frequencies and percentages. In this exploratory analysis of reasons behind the booster dose vaccination acceptance, a two-step logistic regression procedure was implemented. First, the crude odds ratio (OR), along with 95% confidence interval (CI), were computed for each independent variable. All drivers or barriers that were significant in this unadjusted logistic regression analysis  were excluded due to incomplete responses. A total of 2935 (79.4%) respondents who responded to all of the questions were included in the analysis . Out of A total of 740/2935 respondents (25%) reported having a family member who was seriously ill or who died due to COVID-19, and 47.3% had been infected with COVID-19 themselves . RelativMore than 80% of the respondents believed that a booster dose could improve immunity, stimulate antibody production, and reduce the number of COVID-19 treatments . Almost In relation to vaccine decisions, 57.9% reported that their decision to get vaccinated with a booster dose was influenced by a person or family they live with. More than half of the respondents (57.5%) also admitted that their decision was influenced by their colleagues at their workplace during the pandemic. In terms of perceived benefits, 79.0% and 81.4% of the respondents believed that booster doses of the vaccines were useful for protecting themselves and others from COVID-19 infection, respectively. Although a majority of respondents (81.8%) believed that a booster dose reduced the risk of contracting and infecting others with COVID-19, 20.5% of them doubted that the benefits of the booster dose outweighed the risks.Without revealing the efficacy and safety of the COVID-19 vaccine, 93.9% of the respondents would accept the booster dose if it were freely provided by the Indonesian government, and only 6.1% of the respondents would reject the booster dose . If the The initial logistic regression analysis showed that demographic factors such as age, marital status, religion and occupation were associated with booster dose vaccine acceptance . BesidesRespondents who were vaccinated by a Pfizer vaccine had a lower acceptance odds ratio compared to those who received Sinovac for the 1st and 2nd dose . Not knowing that they have been reinfected with COVID-19 after vaccination, belief that a booster dose can provide better immunity than just a second dose and that a booster dose can stimulate antibody production, lower hospitalization, and protect other people who were not vaccinated were also associated with booster dose acceptance . ParticiThe factors associated with reduced acceptance included the belief that serious complications will arise after getting the COVID-19 booster vaccine and worry about the unexpected side effect of the COVID-19 booster dose vaccine in the future. Respondents who agree that they were worried about the halal status of the vaccine and that getting a booster dose vaccination takes a lot of time and effort were less likely to receive the vaccine . These factors were classified as inhibitors, because they reduced the rate of acceptance. All factors that were significant in the unadjusted model were included in the final logistic regression model. In the adjusted logistic regression model, only some factors were significantly associated with the acceptance of a booster dose of the COVID-19 vaccine. These included age, marital status, religion, occupation, type of vaccine received in the first and second dose by the respondents, belief in the efficacy of the booster dose in protecting the public from COVID-19, belief in the role of natural immunity and belief in the effectiveness of the vaccination against COVID-19 . p = 0.035). The participants who received a Sinovac vaccine for the first dose had a higher acceptance compared to those who received Sinopharm, while those who received AstraZeneca during the second dose had almost an eight times higher odds ratio of acceptance compared to those who received the Sinovac vaccine. Respondents who did not know if they had ever been infected with COVID-19 after getting vaccinated had lower odds of accepting a booster dose compared to those who knew that they had been infected . Compared to the respondents who did not believe that the booster dose is important to protect the public from COVID-19, those who believed were three times more likely to accept the booster dose. Respondents between 18 and 30 years old had two-to-three times higher acceptance for the booster dose compared to respondents 31–40 years old . Particip = 0.002). The participants who believed that natural immunity is sufficient to protect from COVID-19 had a lower acceptance rate compared to those who did not have this belief . Respondents who did not believe or were unsure that the vaccine is effective against COVID-19 had lower odds of booster dose acceptance compared to those who believed .Those who agreed that the booster dose for the COVID-19 vaccine is very important were almost six times more likely to accept the booster dose compared to those that disagreed , followed by protecting their family (67.7%) and protecting their co-workers (48.8%). There were some respondents (10.6%) who stated that government pressure was one of their reasons for accepting a booster dose . In the decision process to accept a booster dose, the respondents stated that some reasons included increasing the number of confirmed COVID-19 cases in their area (54.3%), vaccine effectiveness (53.0%), advice given by doctors or the Ministry of Health (46.2%), the participants’ health status (32.9%) and fatalities caused by COVID-19 (26.3%). The type of vaccine, side effects and fear of interference with the treatment of other illnesses were less important reasons, being listed by 16.1%, 10.3% and 4.7% of the respondents, respectively . In terms of vaccine type, participants also acknowledged the preferred sources of the booster dose, such as the United States (25.9%), United Kingdom (10.1%), China (7.4%) and Russia (2.7%). More than half of the participants (53.9%) did not know/did not answer for their country of choice for a booster dose .This survey was conducted across Indonesia on a backdrop of continued outbreaks of COVID-19 and a need for understanding why individuals were vaccine-hesitant. In this study, 93% of the respondents would accept a booster dose of the COVID-19 vaccine if it were provided by the government for free. This acceptance rate is above the target of the Indonesian Ministry of Health, which stated that 70% vaccine coverage is adequate to achieve herd immunity . This raOur study found that the specific vaccine received by participants in the past led to differing levels of acceptance of a booster. Sinovac was the type of vaccine that most respondents received as the first dose (85.1%), followed by AstraZeneca (7.6%), Moderna (3.1%) and Pfizer (2.6%). Our study indicated that recipients of the Sinopharm or AstraZeneca vaccine were significantly more hesitant to accept a booster dose compared to those with a Sinovac vaccine. This finding might be associated with the safety or effectiveness profile of the previously received vaccine. A study indicated that six months after two doses of Sinovac, there were low antibody concentrations ; therefoTwo inhibitors toward booster dose acceptance were identified: belief that natural immunity is sufficient in preventing COVID-19 and belief that the vaccination is not effective against COVID-19 . A previThe perceived halal status of the vaccine doses significantly contributes to the respondents’ confidence in accepting a booster dose. A previous study also found that those who refused the vaccine believed that it was not halal. Several respondents were under the impression that vaccines might contain non-halal ingredients such as porcine and fetal materials . We noteMotivations to receive the booster dose of the COVID-19 vaccine may vary. Based on a study conducted in Spain, the concern of transmitting COVID-19 to the family 49.52%) and concern of self-infection (39.45%) were the most common reasons for vaccination, followed by socializing (31.0%) and travel (30.56%) % and con. These fThe efficacy of the booster dose, as well as worries about adverse effects, have a significant impact on the reasons for the third dose of the COVID-19 vaccine. Previous research has demonstrated vaccine efficacy, safety and a lack of worry about adverse effects to be associated with increased vaccine acceptance . DespiteEven if more than half of the participants (53.9%) did not respond, the question regarding the preferred country as the source of the booster dose, the remaining participants agreed that the two most preferred countries are the United States and United Kingdom. This is in line with the perceived superiority of Pfizer and Moderna, which are from the United States, in being the most effective vaccine in terms of protection against hospitalization, admission to the ICU or death .Our study had some limitations that need to be discussed to be able to interpret the results. First, the internet-based survey method in this study may have excluded people who lacked internet access or could not read or write in the country. The active internet user base was approximately 56% of the Indonesian population in 2018 [Our study found that the experience of contracting SARS-CoV-2 infection, previously receiving a Sinopharm or AstraZeneca vaccine, and knowledge that vaccines give protection from COVID-19, reduce the length of treatment and protect unvaccinated people could relate to the levels of acceptance of a COVID-19 vaccine booster. Additionally, confidence in their existing immunity, mistrust over the effectiveness of a booster dose, worries regarding the unexpected side effects following a booster dose and concerns about its halal status might inhibit the Indonesian population in accepting the booster dose.


The experience for patients with mental health disorders may be negatively impacted by the barriers to care, such as low health care provider-to-population ratios, travel time to reach service providers, higher hospital readmission rates, and local demand for services, especially in suburban and rural areas.The project aimed to design a model in which physicians and pharmacists collaborate to provide comprehensive care to patients with depression in two northern communities and improve the patient and provider experience.Pharmacists and primary care physicians developed a model in which patients starting on new antidepressant medications received regular follow-up care and education on adjunct therapies from the community pharmacists instead of the physician. The patient and provider experiences were measured through surveys.Out of the 14 patients who completed the patient survey, 13 reported feeling more supported by receiving follow-up care from pharmacists. Out of the 5 providers who completed the provider survey, 4 reported that the physician-pharmacist collaboration and additional support were helpful to patients.Overall, the project positively impacted patient experience and providers perceived value in the shared-care model. Pharmacists are accessible health care providers who can help increase health system capacity and support continuity of care. Considering that medications such as antidepressants are a cornerstone of treatment for depression, pharmacists are well-positioned to provide follow-up care and support around the effectiveness, safety, and use of medications.,,Patient experience is an important measure of health care quality and provides useful information about how patients assess their care.Improving patient experience is a key priority for Ontario.A CQI project based on the OH quality standards for depression was designed in this project. One of the key features of the CQI project was the collaboration between primary care physicians and pharmacists to provide longitudinal care during regular follow-ups. The project was conducted in two northern communities in Ontario (Sudbury and Espanola). Patient surveys were utilized to evaluate the overall patient experience. The experience of pharmacists and physicians was also measured via provider surveys to gain their perspective on the collaborative approach.2Together with a team of two primary care physicians and six pharmacists, all practicing in the two northern communities, a CQI project was developed that aligned to the OH quality standards for Major Depression.2.11.Patient-centred: The CQI project will be modeled with the patient at the centre of the health care delivery system. A strong primary care foundation, as well as collaboration and communication within and between primary care practitioners and community pharmacists along the continuum, are essential to achieving patient-centered care.2.Practicing to optimal scope: The CQI project will encourage all professionals to work to their optimal scope of practice. Clinicians will be supported to practice in an environment that allows them to fully utilize their knowledge, skills, and expertise to benefit patients and the health care system.3.Quadruple aim: The project will take a population-based health approach, enhancing the experience and outcomes for patients, improving health system efficiency, and will seek to improve the experience of those providing the care.4.Shared Accountability: All professionals and organizations involved in the CQI project will be responsible for ensuring the best outcomes for their patients. A structured approach to sharing outcome measures will support shared accountability.5.Scalable: To spread to a wider range of patients, the model will be reproducible and portable.6.Sustainable: The model's infrastructure will be able to be supported and maintained.The team established the following six principles to underpin the CQI project:2.2•Quality Statement # 5: Adjunct Therapies and Self-Management: People with major depression are advised about adjunctive therapies and self-management strategies that complement antidepressant medication or psychotherapy.•Quality Statement #6. Monitoring for Treatment Adherence and Response: People with major depression are monitored for the onset of, or an increase in, suicidal thinking following initiation of any treatment. People with major depression have a follow-up appointment with their health care provider at least every 2 weeks for at least 6 weeks or until treatment adherence and response have been achieved. After this, they have a follow-up appointment at least every 4 weeks until they enter remission.The team reviewed all statements within the Ontario Health quality standard for Major Depression and identified the two highest impact areas for a joint physician and community pharmacist intervention2.3In the practice model developed, the primary care physicians asked patients starting on new antidepressant medication to follow up with their community pharmacist every two weeks. Patients who were newly diagnosed with depression or changed medication therapy were eligible to participate. Patients with suicidal ideation were excluded. Pharmacists supported adherence to therapy and reinforced education on adjunct therapies until the follow-up appointment with the primary care physician  approach was applied. Regular meetings were held with the participants to discuss any barriers and enhancements to the project. The meetings served as a forum to implement improvements and modifications based on timely feedback and observations. For example, an adjustment was made to enable pharmacists to identify patients and enroll them in the project to broaden recruitment. The group determined that recruitment through physicians limited patient enrollment. Due to time constraints, it was not always feasible to introduce the project during physician visits.2.4The primary outcome was patient experience, and the secondary outcome was provider experience.2.5For the primary outcome, a patient experience survey was created using the experience-based co-design (EBCD) toolkit.The patient experience survey was conducted at the 6-week follow-up appointment by the pharmacist or the primary care physician. The survey consisted of two questions and an emotional mapping questionnaire.The two questions asked were “I felt that the additional supports provided to me  were helpful to me” and “If friends and/or family were in a similar situation, I would recommend the additional supports I received to them.” The two questions were answered based on a 5-point Likert scale with responses ranging from ‘strongly agree’ to ‘strongly disagree.’when they started taking antidepressant medication and when they received additional support with their antidepressant medication. The word selection consisted of 7 ‘positive’ words and 5 ‘negative’ words. When presented to the patients, the 12 words were not stratified into positive and negative words but instead were arranged in the following assorted order: safe, supported, concerned, calm, disappointed, worried, informed, appreciated, knowledgeable, frustrated, understood, uncomfortable.For the emotional mapping question, patients were asked to select from a list of 12 words the feelings they had During the follow-ups, pharmacists assessed medication adherence and response to therapy, provided clinical activities  agreed to participate, and 5 (14.3%) declined.The 30 participants received, on average, 2 follow-ups. During the follow-ups, pharmacists assessed medication adherence and response to therapy for all 30 patients. Of the 30 patients, pharmacists identified drug-related problems in 13 (43.3%) patients and provided pharmaceutical opinion/intervention to 10 (33.3%) patients. Physicians accepted all recommendations made by pharmacists. In one case, a pharmacist recommended titrating a dose of the antidepressant more slowly to reduce side effects. Additionally, on average, pharmacists provided support on 1 adjunct therapy per patient. The type of adjunct therapies provided was determined based on individual patient factors. Of the 30 patients, 12 (40.0%) received additional support on healthy sleep habits, 8 (26.6%) on physical activity, 5 (16.6%) on nutrition and 1 (3.3%) on yoga. Of the 30 participants, 14 (46.7%) completed the patient experience survey. For the first and second questions, 13 patients (92.9%) reported that they “strongly agree/agree,” and 1 patient (7.1%) selected “neither agrees nor disagrees.” when they started taking their antidepressant. The most common negative word was “worried” (n = 3). In contrast, no patient selected a negative word when asked how they felt after receiving additional support from the pharmacist. Also, the frequency of the positive words increased after the patients obtained additional support. The most common positive words were “supported” (n = 13) and “safe” (n = 9), and the words with the largest increase in frequency were “supported” and “appreciated.” The emotional mapping was analyzed to determine any trends in negative and positive responses. On average, patients selected 3–4 words to describe their emotions. Of the 14 patients, 6 patients (42.9%) selected at least one negative word when asked how they felt collaboration between providers was beneficial to patients and would recommend the project to colleagues. There was 1 physician who “strongly agree/agree” that the support for medication adherence and adjunct therapies was helpful to patients. Of the 18 providers (7 physicians and 11 pharmacists) invited to complete the provider experience survey, 5 providers (3 physicians and 2 pharmacists) completed it. The 2 pharmacists “strongly agree/agree” to all four questions. Of the 3 physicians, 2 “strongly agree/agree” that the 4This project found that the patients' experience improved with the practice model. The patients viewed the support provided by pharmacists as valuable to their overall experience. Pharmacists contributed to patient care through various clinical activities. In addition to implementing best practices to support medication adherence (through patient follow-up) and self-management , pharmacists optimized medication therapy by identifying and addressing medication-related problems in collaboration with the physician. Additionally, the negative feelings experienced by patients at the time of starting the medication disappeared after patients received follow-ups from the pharmacist, demonstrating the benefits of continued support.The role of pharmacists in this project is similar to that reported by Haslam et al.Furthermore, the provider experience survey findings suggest that the physicians and pharmacists believed there was value in the additional support provided to patients. The pharmacists appeared to be slightly more positive than the physicians that the project was helpful to patients. During the project, pharmacists interacted more frequently with patients, which may have influenced their more positive perception of patient satisfaction.The project also demonstrated that this collaboration facilitated the implementation of best practices. This project builds upon existing literature in which pharmacists have applied CQI with primary health care teams. In a study conducted by Raiche et al.,Additionally, this project demonstrated the value of involving pharmacists as part of the broader primary health care team. Physicians and pharmacists participated in a debriefing session to synthesize learnings at the end of the project. A foundation to effective collaboration is establishing trusting relationships among providers facilitated through communication. Legacy methods, such as fax, were seen as a barrier by some physicians. While others utilized a more streamlined approach, such as using secure web-based means or electronic patient care records, to foster more effective communication. The group emphasized the value of standard tools and templates available in the project toolkit as an enabler to support implementation and consistent communication. The group also recognized the importance of change management and engaging clinical champions early in the process to leverage their expertise and influence and sustain project momentum. Physicians suggested involving other primary care professionals, such as nurses and allied health staff, in future CQI projects to facilitate greater uptake and enrollment. The pharmacists reported they could sustain this model and embed this into their practice. Lessons learned from the group may help other teams implement a pharmacist-physician collaborative CQI project to support patient experiences with conditions like COPD and diabetes.4.1This project was designed as a CQI initiative, and the results should be interpreted accordingly. As such, there was not a control group to compare the outcomes measures or establish a baseline. A future project may enrich the understanding of the impact of this work. Additionally, the PHQ-9 was an optional tool rather than a required tool. The use of validated tools may enhance the generalizability of the results.Three of the five providers who completed the provider experience survey created the practice model, potentially introducing bias and skewing towards more favourable responses. Further, patients that agreed to participate may have been more willing to accept additional support and, therefore, may positively skew patient experience. Additionally, patients with suicidal ideation were not enrolled due to the need for more close physician supervision, introducing potential recruitment bias.5Continuous quality improvement was used as a framework to establish a collaborative model between physicians and community pharmacists to implement evidence-based standards in practice and improve the experience for patients with depression. The collaborative approach to care reinforced the role of pharmacists in improving the quality of care and strengthening access to health care. Pharmacists were well-positioned to provide follow-up and monitoring in the community. A similar approach may be taken to address other local health care needs. Larger studies that build on this approach may further elucidate the impact on patient and system outcomes.No external sources of funding were used for the conduct of this study or the writing, correction, and submission of this article.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.