The 2022 Banff-Canadian Society of Transplantation Meeting in Banff, Alberta, brought together transplant professionals to review new developments across various aspects of solid organ transplantation (SOT) in Canada.Presentations included consensus recommendations from expert-led forums; experiences with new procedures and legislation; reports from public health data repositories; original clinical and laboratory research; and industry updates regarding novel technologies. Speakers referenced articles and reports published in peer-reviewed journals and online, and unpublished data and preliminary findings.All authors attended presentations in-person or virtually. Recordings of select presentations were available for later review. Summaries emphasize concepts indicated by speakers as new and clinically relevant.The COVID-19 pandemic disproportionately affected solid organ transplant recipients (SOTRs), who experience worse outcomes of COVID-19 infection than the general population. Vaccinations demonstrate an attenuated immunological response in SOTRs yet provide meaningful protection. Monoclonal antibodies are effective for both passive immunization and treatment of COVID-19 in SOTRs. Infection control protocols have driven the development of virtual methods for clinical research, such as using home blood draws and virtual follow-up to evaluate vaccine efficacy in SOTRs; and patient care delivery, such as employing telerehabilitation post transplant. Access to living kidney donation is limited by various disincentives experienced by potential donors, which may be overcome by more efficient evaluations including a One-Day Living Kidney Donor Assessment Clinic. The International Donation and Transplantation Legislative and Policy Forum provided a means of establishing consensus guidance for organ donation and transplantation (ODT) program policy to standardize delivery across jurisdictions. The implementation of a deemed consent model for organ and tissue donation in Nova Scotia may provide insight as to whether this model indeed improves access to organs. Canada’s Indigenous population experiences unique barriers to transplantation, prompting efforts for more inclusive ODT policy-making. The Pan-Canadian ODT Data and Performance Reporting System Project has defined performance quality indicators, of which iTransplant and other point-of-care software solutions may facilitate collection; however, these endeavors ultimately require information technology infrastructure that exceeds the capabilities of the existing Canadian Organ Replacement Register and Canadian Transplant Registry. Pig-to-human xenotransplantation requires genetic modification of pigs and xenoantibody testing in recipients but may yet prove viable. Serum cell-free DNA, urine biomarkers, and genetic markers offer an alternative to routine biopsy for identifying subclinical rejection. Modified perfusion temperatures and perfusion solutions with hydrogen sulfide donor compounds may improve organ preservation. Molecular compatibility tools provide another means of improving SOTR outcomes, and the Genome Canada Transplant Consortium has been examining important considerations of their implementation.We were unable to capture all presentations and topics at the meeting due to the sizable quantity and variety. Topics ultimately excluded from this summary include those in pathology including Banff Classification updates; those unique to extra-renal SOT; as well as numerous abstract and poster presentations, allied health provider forums, and business meetings. A portion of the material was presented by speakers prior to peer-review or publication.The various conference presentations summarized in this report identify methods by which individual clinicians and provincial ODT programs may improve access, delivery, and quality of SOT care in Canada, while additionally identifying gaps in the literature that investigators are encouraged to pursue. This conference brought together physicians, pharmacists, nurses, physiotherapists, transplant coordinators, laboratory scientists, social scientists, and other transplant professionals for a series of virtual and in-person events. In this report, we aim to summarize and disseminate key concepts in clinical solid organ transplantation (SOT) and kidney transplantation specifically as presented within the core program of the 2022 Banff-CST Joint Meeting.In autumn of 2022, the Canadian Society of Transplantation (CST) partnered with the Banff Foundation for Allograft Pathology to host the 2022 Banff-CST Joint Meeting in Banff, Alberta, Canada.The conference was comprised of a series of plenaries each with a particular theme. Presentations within plenaries included consensus recommendations from expert-led forums and panels; first-hand clinician experiences with conventional practices and new procedures and legislation; reports generated from public health data repositories; original clinical and laboratory research; and industry updates regarding the development and real-world implementation of novel technologies. Speakers referenced articles and reports published in peer-reviewed journals and online databases; as well as unpublished data and preliminary findings from projects for which they are contributors.All authors were participants at the conference and attended in-person and/or virtually, with recordings of presentations available via a web-based application  for later review. Summaries were composed directly from select presentations, supplemented by published works referenced within the presentations where available, emphasizing concepts indicated by speakers as new and significant. Key findings are presented in subsections that mirror to the plenaries in which the topics were presented with some modifications, including combining topics in Indigenous health into a single subsection  that was not itself a conference plenary.3 The identification of steroid therapy, interleukin (IL)-6 inhibitors, novel antivirals, and monoclonal antibodies by 2021 reduced crude mortality rates among SOTRs, but they remain unacceptably high. Vaccination revolutionized the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) risk in the general population, but SOTRs were not afforded the same benefit. Solid organ transplant recipients achieved an attenuated immunologic response to COVID-19 vaccination with neutralizing antibodies against wild-type SARS-CoV-2 present in 56.9%, against delta in 45.1%, and against omicron BA.1 in only 15.7% of SOTRs 3 months after a third vaccine dose. However, when breakthrough COVID-19 infections occurred, vaccinated SOTRs experienced lower hospitalization rates and, if hospitalized, shorter lengths of stay as compared to unvaccinated SOTR controls. These findings highlight the importance of establishing clinical, not just immunologic, COVID-19 vaccine efficacy among SOTRs.Immunosuppressed solid organ transplant recipients (SOTRs) have been disproportionately afflicted by the COVID-19 pandemic. COVID-19-attributable mortality rates amongst SOTRs early in the pandemic varied widely between jurisdictions but often exceeded 20%. Cilgavimab/tixagevimab decreased the incidence of symptomatic COVID-19 in the unvaccinated general population (pre-omicron variant) from 1% to 0.2% with minimal adverse effects. The efficacy of cilgavimab/tixagevimab in the transplant population and for the omicron variants is less established. Some studies have demonstrated relatively high breakthrough infection, hospitalization, and intensive care unit admission rates among kidney transplant recipients receiving cilgavimab/tixagevimab . Variability in efficacy, particularly during the omicron wave, has contributed to inconsistencies in recommendations regarding the use of cilgavimab/tixagevimab in SOTRs across Canada.Passive immunization may provide a means of protecting at-risk SOTRs. The PROVENT randomized controlled trial examined cilgavimab/tixagevimab (Evusheld), a preparation of long-acting monoclonal antibodies against the spike protein of SARS-CoV-2 that blocks viral entry into cells, as pre-exposure prophylaxis. The management of symptomatic COVID-19 infection in SOTRs included monoclonal antibodies with efficacy against omicron (e.g. bebtelovimab in the United States) as a first-line agent in combination with dexamethasone and early remdesivir. While emergency use authorization for bebtelovimab has since been revoked by the FDA because of lack of susceptibility of recent variants, the latter 2 therapies remain the mainstay treatment for hospitalized immunocompetent and immunocompromised patients alike with severe COVID-19 infection.The treatment of SOTRs with COVID-19 is evolving. Monoclonal antibodies have provided benefit for SOTRs with COVID-19, yet activity against omicron  and the BA.2 subvariant (sotrovimab) has waned significantly, and these agents are no longer routinely used. An early study reported donor-derived COVID-19 infection in 3 lung transplant recipients, 1 of whom died from COVID-19-related complications. The donors were nucleic antigen test (NAT) negative for SARS-CoV-2 from the upper respiratory tract, but NAT positive from the lower respiratory tract. Interestingly, no nonlung organ recipients developed COVID-19 infection, prompting the cautious utilization of donors with lower respiratory tract SARS-CoV-2 NAT positivity for liver, kidney, and heart transplantation. A large, multicenter study of SARS-CoV-2 NAT positive donors demonstrated better quality organs and no statistical difference in graft failure or patient survival at 30 days for any of kidney, liver, or heart recipients as compared to NAT negative controls, and a smaller study demonstrated similar outcomes at 6 months of follow-up. The risk of transmission from SARS-CoV-2 positive donors appears to be low, but is unknown, with no long-term data available.Among potential donors, SARS-CoV-2 positivity poses an ongoing challenge due to uncertainty, with widespread discard of organs from deceased donors with COVID-19. Investigators aiming to assess the antibody response of COVID-19 vaccination among SOTRs successfully recruited participants remotely using social media.17 Participants underwent blood draws at home using TAPII devices ; samples were delivered to laboratories using postal services; and virtual follow-up was completed to track clinical outcomes. Data for this cohort continue to be collected and have contributed substantially to the evidence base for COVID-19 vaccination among SOTRs, particularly highlighting limited immunogenicity in this population. Telerehabilitation after SOT has been widely adapted in place of in-person rehabilitation.19 Numerous barriers to delivery of telerehabilitation exist including limited patient access to technology and exercise equipment, and the need for remote monitoring. While safety and efficacy relative to conventional rehabilitation has not been established, initial studies have demonstrated generally favorable outcomes. Though born out of necessity, virtual approaches have proven effective and efficient and are likely to persist even with the ongoing easing of COVID-19-related restrictions.Infection control protocols brought on by the COVID-19 pandemic have driven the rapid development of virtual methods for research and patient care delivery.21 However, frailty improves in SOTRs after transplant, and those who are most frail pretransplant experience higher degrees of improvement in health-related quality of life post transplant. Routine assessment for frailty indicators using a novel solid organ frailty index may allow for the identification of the most at-risk patients, and a comprehensive intervention consisting of rehabilitation and shared decision-making may lead to improved long-term outcomes for SOTRs experiencing frailty.Aside from pandemic-related pressures, health care delivery has needed to adapt to an aging Canadian population. Among SOTRs, frailty  has been associated with delayed graft function, persistent disability, and mortality across organ types. Kidney care in Canada is delivered by independent regional organizations that lack unifying mandates, funding models, and leadership. Within Ontario, the Ontario Renal Network (ORN) oversees the delivery of chronic kidney disease (CKD) and dialysis care while the Trillium Gift of Life Network (TGLN) oversees deceased kidney donation and transplantation. Living kidney donation is not formally managed by either organization, leading to potentially uncoordinated and ineffective efforts to recruit nondirected anonymous donors (NDADs), standardize pretransplant and posttransplant care, and provide patient education, including strategies to identify potential living donors.Multilevel inefficiencies within the organization of kidney care impede access to living kidney donation.26 The median out-of-pocket expense incurred by Canadian living kidney donors was found to be $2217 (Canadian dollars) and exceeded $5500 for at least 25% of donors, despite most Canadian reimbursement programs offering a maximum payout of $5500. Reimbursement programs may be improved by expanding promotional efforts; simplifying paperwork required for the enrolment process; and increasing payout to better reflect financial disincentives, nonfinancial disincentives, and long-term dialysis savings related to improved recipient outcomes.In completing evaluation for eligibility and subsequently following through with donation, living kidney donors must overcome many financial and nonfinancial disincentives .25,26 Th Protracted evaluations lead to donors dropping out in response to fatigue and anxiety, among other disincentives. In Ontario, the median time between initial living donor contact and donation was 10.5 months. Multiple methods to optimize living kidney donor evaluations have been suggested  systems depend on coordination between care providers and legislation, with marked variability in practices across jurisdictions. In October 2021, the International Donation and Transplantation Legislative and Policy Forum was held in Montréal, Québec, with a goal of developing expert consensus guidance that links evidence and ethical concepts to ODT legislative and policy reform. domains . These r Under this legislation, all persons who have not registered a donation decision are viewed as having consented to donate all organs and tissues after death. Next of kin may decline donation if they believe it is not consistent with the potential donor’s last known wishes. Several groups were excluded from this legislation including persons under 19 years of age; persons who lack capacity to make a decision regarding donation; and persons who are not permanent residents of Nova Scotia. Nova Scotia had been the highest performing Canadian province with respect to deceased organ donation in the early 2000s, but with rates having stagnated in the 2010s, legislators hope this model will offer successes observed in Spain and other jurisdictions with high-performing deceased donor programs where deemed consent is in effect. After HOTDA was passed, Nova Scotia’s provincial ODT program Legacy of Life faced a major infrastructure overhaul to support its enactment including onboarding a greater number of donor physicians and transplant coordinators, creating new roles including a dedicated quality database analyst and health care provider education lead, and developing new software including a new potential donor audit tool. Outcomes from 2020 and 2021 after passing HODTA, such as the number of donors per million population, have been variable, heavily confounded by COVID-19-related issues. It is expected that markers of success  will be years in the making, and it will be challenging to distinguish whether such markers are attributable to the legislation itself or the associated infrastructure reforms within Legacy of Life.Nova Scotia, Canada became the first jurisdiction in North America to introduce a deemed consent model for organ and tissue donation. The Human Organ and Tissue Donation Act (HOTDA) was passed in April 2019 and enacted January 18, 2021.35 Contributing factors include intergenerational impacts of colonialism leading to poverty, lower education, and food and housing insecurities, further confounded by jurisdictional complexities regarding the funding and provision of health care services for FNIM patients. Métis and nonstatus and off-reserve First Nations individuals receive services directly from the provinces or territories; however, status- and on-reserve First Nations individuals and Inuit receive supplementary federal funding through Indigenous Services Canada, which also directly provides health care services to First Nations and Inuit communities. This fragmented infrastructure results in gaps in care for FNIM patients who fall outside the mandates of certain services, including provincial ODT programs.The Indigenous population of Canada comprising First Nations, Inuit, and Métis (FNIM) peoples experience poorer health outcomes than the general population with higher rates of acute and long-term illness.37 First Nations, Inuit, and Métis patients experience greater challenges adhering to medical appointments due to geographical remoteness among other factors, with such nonadherence considered a relative contraindication to transplantation. Inequities in transplantation are masked by a paucity of ODT data including the number and rationale for FNIM patients refused placement on waitlists. However, one systematic review demonstrated that FNIM patients with end-stage kidney disease (ESKD) experience longer wait times to receive a kidney transplant and have lower rates of transplant than the general population.First Nations, Inuit, and Métis patients with organ failure face excessive barriers to transplantation. Organ donation and transplantation programs are urban-centric, limiting access to FNIM patients living in rural, reserve, remote, and northern (RRRN) communities who already face inadequate access to local primary and acute care.37 Though Canadian governments do not have a legal duty to consult FNIM populations before passing healthcare legislation, as per the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), Indigenous peoples have the right to “free, prior and informed consent before adopting and implementing legislative or administrative measures that may affect them.” The opinions of FNIM individuals on deemed consent are postulated to be influenced by culture, belief systems, and mistrust in the healthcare system. Nevertheless, knowledge of ODT and deemed consent legislation is lacking among the FNIM population and opinions were not established prior to enactment. There is concern that deemed consent will increase the number of FNIM donors without addressing inequities in access to transplantation such that FNIM patients will not see benefit. Government investment in formal FNIM stakeholder representation may allow these and other concerns from FNIM individuals to be appropriately addressed in ODT policy development.In drafting and passing HOTDA, Nova Scotia moved forward without formal consultation of FNIM groups.41 After a slight increase in the early 2010s, deceased kidney donation rates have remained relatively stable across provinces, though with an increase in the proportion of donation after cardiac death (DCD) from approximately 15% to 30%. Most recent CORR reports from 2021 included data from Québec for the first time since 2015 after rectifying privacy concerns, and data from Nova Scotia is now being reported separately from the other Atlantic provinces. The CORR faces ongoing challenges owing to voluntary data collection with waning engagement, and its future role remains unclear.Within Canada, public health databases, including for kidney replacement therapy and transplantation, are managed by several entities . Summary Since inception, the Kidney Paired Donation (KPD) program has facilitated over 900 kidney transplants in Canada averaging 80 per year. In response to a sharp decline in donors at the start of the COVID-19 pandemic, KPD moved away from mandating that living donors travel to the corresponding recipient’s ODT program and instead started shipping kidneys between centers. While only 6.8% of KPD kidneys between 2009 and 2019 were shipped, that increased to 85.7% in 2021, corresponding to a record 105 KPD transplants including 37 NDADs. The Highly Sensitized Patient (HSP) program has facilitated interprovincial kidney transplantation for greater than 50% of enrolled patients, corresponding to approximately 120 transplants annually. Canadian Transplant Registry has supported quality improvement projects , but was not designed to collect outcome data.The Canadian Transplant Registry (CTR) is a web-based program developed by Canadian Blood Services (CBS) to promote interprovincial sharing of organs and is itself composed of 3 distinct registries .42 Sin The project engaged stakeholders  using a modified-Delphi approach to define and prioritize performance indicators, including both general outcomes for all SOTs  and organ-specific indicators . In parallel, the project is defining minimum standards for data sets required to adequately assess these indicators. iTransplant software  is designed to minimize the burden of point-of-care data collection and eliminate antiquated home-grown, paper-based solutions requiring repeat manual entry. A nation-wide database is required to integrate, store, and analyze such data; this falls beyond the capabilities of CORR and CTR, and unfortunately, information technology infrastructure limitations continue to impede such endeavors.The Pan-Canadian ODT Data and Performance Reporting System Project aims to realize a longstanding, overarching goal within the transplant community: to decrease the number of patients on transplant waitlists and deaths while waitlisted through organizing waitlist data and minimizing missed donation opportunities.43 Pig growth receptor genes are also deleted to ensure appropriate graft size. Xenotransplantation research and development is largely industry funded, with Revivicor, Inc. having raised more than 400 genetically modified pigs to date that have maintained normal growth, fertility, and health in a pathogen-free facility.Xenotransplantation offers to improve organ supply by recovering organs from nonhuman donors, particularly pigs. To address cross-species immunological incompatibilities and prevent rejection, pigs must be genetically modified. Specific porcine genes are deleted  while human genes are added  to overcome incompatibilities. Since about 1% of naturally occurring human antibodies are directed against α-GAL, felt to be a driving force behind xenotransplant rejection, galactosyltransferase gene knockout (GTKO) pigs lacking α-GAL expression were developed. Human leukocyte antigen (HLA) antibodies have previously been demonstrated to cross-react with swine leukocyte antigens (SLA), which may cause hyperacute or acute rejection; however, a review of more recent studies found that relatively few HSPs have HLA antibodies that cross-react with SLA. Furthermore, introducing site-specific SLA mutations may minimize or eliminate cross-reactivity. Xenotransplantation may therefore be of particular benefit for HSPs, with pre-emptive plasma exchange to lower the recipient’s antibody burden and lymphocyte and nonlymphocyte  CD crossmatching being potential strategies to further reduce the risk of xenograft rejection.Complex xenoantibody testing is required during various stages of xenotransplantation. Preformed IgG and IgM pig antibodies in recipients must be measured during the pretransplant phase.51 Recipients declared brain-dead by the clinical care team underwent transplantation consisting of the anastomosis of xenograft vessels to the femoral artery and vein, with the xenograft left outside the body on the thigh for ease of direct observation and serial biopsies. These 2 decedent kidney transplants resulted in excellent xenograft urine output and doubling of estimated glomerular filtration rate (eGFR) by the end of the study period (54 hours after reperfusion). Biopsies obtained at the end of the study period did not demonstrate evidence of hyperacute rejection, disseminated intravascular coagulation (DIC), hyperinflammation, excessive cytokine release , or complement dysregulation. Additional histological assessment demonstrated glomerulitis with less marked tubulointerstitial inflammation equivocal or suspicious for early antibody mediated rejection (AMR) and acute tubular necrosis. There remains much to be learned about the adaptive immune responses to xeno-antigens that longer-term decedent studies may elucidate, but these recent advances are promising.A decedent human model was recently utilized by investigators at New York University in conducting pig-to-human xenotransplants with kidneys (n = 2) and hearts (n = 2) from GTKO pigs. Noninvasive diagnostics using urine and blood samples may replace the need for protocol biopsies and provide earlier detection of subclinical rejection. The Q-Sant test  utilizes 6 urine biomarkers  and artificial intelligence to calculate a personalized Q-score as a measure of subclinical and clinical acute rejection. Q-scores correlate to pathological findings  and have been validated in both adults and children. However, further development is required to be able to distinguish acute rejection from other injuries such as ischemia-reperfusion injury (IRI).Smoldering immune activation in clinically stable kidney allografts can lead to fibrosis and progressive graft failure. The ADMIRAL study was a retrospective, multicenter study that monitored donor-derived cfDNA (dd-cfDNA) among 1092 kidney transplant recipients over a 3-year period. Although elevated dd-cfDNA was associated with both de novo donor-specific antibodies (DSAs) and eGFR decline, results were likely confounded by graft dysfunction at the time of assessment. To address this, a subsequent retrospective observational single-center study focused on dd-cfDNA surveillance in stable patients with normal allograft function  over a median follow-up period of 1.5 years. Although elevated dd-cfDNA was a predictor of rejection, most patients with elevated dd-cfDNA remained clinically stable. The utility of cfDNA monitoring alone in the setting of stable allograft function remains unclear.Cell-free DNA (cfDNA) is a potentially useful serum marker of subclinical rejection.5961 TruGraf is therefore another potential tool for identifying subclinical rejection, with surveillance testing corresponding well to histological findings including therapeutic response. As TruGraf appears to outperform dd-cfDNA in the diagnosis of subclinical cellular rejection, and dd-cfDNA appears to outperform TruGraf in the diagnosis of subclinical AMR, combining these 2 tools may be beneficial.63 Although such noninvasive diagnostics have been implemented in the United States and other countries, implementation in Canada has been limited due to cost and other considerations.TruGraf  testing uses DNA microarray technology to measure 120 genes previously identified to be differentially expressed among patients with and without histological evidence of rejection. The current standard of static cold storage (SCS), whereby kidneys are stored on ice between 2°C and 6°C, is associated with cold injuries that contribute to delayed graft function and graft failure. Normothermic machine perfusion  and subnormothermic machine perfusion  have therefore been postulated to offer improved graft outcomes. Hydrogen sulfide (H2S) has diverse cytoprotective effects, fuelling the development of perfusion solutions containing H2S donor compounds. AP39 is one such compound and has previously been associated with decreased IRI for kidney allografts in SCS.68 Investigators in London, Ontario combined these interventions, demonstrating that ex vivo porcine kidneys subject to SNMP with AP39-supplemented autologous blood experienced improved urine output and decreased expression of injury and pro-survival genes compared to kidneys subject to SCS or standard SNMP with blood alone. In a subsequent in vivo pilot trial, patients undergoing DCD kidney transplantation with organs subject AP39-supplemented perfusion solution experienced decreased delayed graft function, higher urine output, and lower proteinuria as compared to standard solution. Modified perfusion temperatures and AP39-supplemented perfusion solutions are inexpensive methods to potentially transform organ preservation.As the use of more marginal kidney allografts expands to match rising demand, novel methods are required to optimize allograft preservation. The GCTC has been examining the legal, ethical, societal, and economic considerations of introducing molecular compatibility tools into clinical practice. With stakeholders having expressed concern regarding the implication of molecular compatibility tools on inequities in SOT access, the Kidney Transplant Simulation model was developed by GCTC to allow comparisons between present deceased donor allocation systems and proposed future systems to further support ODT programs in decision-making regarding molecular compatibility implementation.The Genome Canada Transplant Consortium (GCTC) aims to optimize SOTR outcomes through policy-making and the development of tools for use in various aspects of SOT .71 TheWe chose to summarize presentations within the core program of the conference relevant to clinical care for SOT in general and kidney transplantation specifically, recognizing that kidney transplants represent the vast majority of SOTs in Canada. We were unable to capture all presentations and topics at the meeting due to the sizable quantity and variety. Recordings were available for only a portion of presentations, impeding retroactive inclusion of presentations. Topics ultimately excluded from this summary include those in pathology including Banff Classification updates; those unique to extra-renal SOT; as well as numerous abstract and poster presentations, allied health provider forums, and business meetings. A portion of the material was presented by speakers prior to peer-review or publication and therefore validity could not be formally assessed.Transplantation in Canada is evolving. COVID-19 continues to pose a threat to SOTRs though outcomes have improved with the development of novel treatment and prevention strategies. Infection control protocols have spawned efficient virtual methods of research and patient care. Optimizing reimbursement programs and making evaluations more efficient may overcome the many disincentives faced by potential living kidney donors. Upcoming consensus expert recommendations offer to standardize ODT programs nationally and internationally, while experiences from the implementation of deemed consent in Nova Scotia may provide further insight to guide ODT reform. In Canada, FNIM patients have been identified as a population requiring distinct consideration in ODT owing to poorer health outcomes and limited access to transplantation compared to the general population. Ongoing development of data repositories may improve patient care delivery while allowing for establishment of national benchmarks on which ODT programs can base quality improvement. Additional advancements in xenotransplantation, noninvasive diagnostics for identification of subclinical rejection, graft preservation techniques, and molecular compatibility may further contribute to improvements in both access to transplantation and long-term SOTR outcomes.


The star-shaped 48-microelectrode OctarayWe present a scar-related VT case using the new Octaray mapping catheter , highlighting advantages and limitations of this new mapping tool.We report the case of a 71-year-old female patient with dilated cardiomyopathy and severe left ventricular dysfunction, broad left bundle branch block, and a secondary-prevention cardiac resynchronization therapy defibrillator in situ. She was known to have recurrent VTs, including an electrical storm managed conservatively 2 months prior to the current episode. She presented at her local hospital with 25 appropriate ICD shocks following acceleration of the VT by antitachycardia pacing into the VF zone, with 1 shock failing to terminate the VT, and 314 pace-terminated VT episodes with ventricular cycle lengths between 360 and 440 ms. A total of 4953 nonsustained VT episodes were also documented, reducing her effective biventricular pacing percentage to 77%. No acute reversible trigger was identified. The 12-lead electrocardiogram during VT showed an irregular broad complex tachycardia with QRS width of 120 ms and morphology suggesting an inferoseptal exit. The VT remained refractory to maximal medical therapy, including trials of procainamide, amiodarone, lidocaine, nadolol, and general anesthesia as well as overdrive pacing at 100 beats per minute. Given her clinical presentation and failed response to medical management, she was transferred while ventilated to our hospital for VT ablation.TM technology employing an insulated unipolar electrode at the distal tip of the shaft in the center of the star-shaped splines  electrophysiology mapping system (Biosense Webster). Triple right femoral venous and single right femoral arterial access was gained under ultrasound guidance and a standard quadripolar catheter placed at the right ventricular apex. A long 23 cm 8F sheath was inserted for retrograde arterial access. Trans-septal puncture was performed using a Heartspan ML1 sheath, a BRK-1 extra-sharp Brockenbrough needle, and a SafeSept wire. Unfractionated heparin was administered in boluses as per our institutional protocol to keep the activated clotting time above 300 seconds. A left ventricular substrate map during right ventricular pacing was acquired via retrograde and antegrade mapping A using t splines C and 1D, splines  demonstr splines  was repeBeta-blockers were reintroduced the following day after extubation and successful weaning of the pharmacological hemodynamic support. No further ventricular arrhythmias were documented during inpatient monitoring. Three days postprocedure the patient was transferred back to her local hospital on beta-blockers only for further rehabilitation and reintroduction of her heart failure medication. At 3-month follow-up, she had had no further VT and her ICD was functioning normally. The postablation complete heart block had resolved.Identification of a critical isthmus by demonstrating diastolic potentialsFor substrate and activation mapping alike, correct detection and annotation of low-amplitude, fractionated signal close to the noise floor and overshadowed by larger far-field signals from adjacent healthier areas, with subsequent interpretation of each point in the context of its 3-dimensional neighbors as well as algorithms to account for physiological constraints, remain a challenge even for the most sophisticated mapping system. Mapping density of thousands of points make manual verification and correction in real time unfeasible, even more so if a strategy requiring multiple maps using variable wavefronts for target identification is employed.Conventional activation mapping often is a significant contributor to overall procedure time, requiring extensive, potentially proarrhythmogenic catheter manipulation and, in many cases, repeated pacing maneuvers to differentiate functionally critical areas from bystanders. Longer in-heart catheter dwell time and procedure time has been associated with higher complication rates. Prolonged pacing may cause hemodynamic instability. In turn, extensive ablation may lead to unnecessarily excessive radiofrequency delivery and risk of complications on its own.,The irrigated unidirectional (D or F curve) multispline Octaray multielectrode catheter with 48 small, tightly spaced recording electrodes comes in various configurations  and with an innovative, tightly referenced indifferent electrode at the tip of the shaft and 3 true-shaft electrodes enabling visualization of the shaft deflection and tip orientation. The catheter design aims to address 2 of the above-mentioned challenges—improving EGM signal quality, particularly in areas of heterogenous scar, and increasing speed of precise high-density map acquisition—all while still being integrated in the established CARTO 3 Version 7 3D mapping system. For atrial mapping procedures it was shown that the 48-electrode catheter has a 4 times higher acquisition rate, doubling the EGM points per map yet reducing mapping time by more than 50% as compared to the Pentaray in preclinical and first-in-human studies.Our case illustrates the impressive signal quality of novel multipolar catheter designs. In particular, the unipolar signal generated between the spline poles and the isolated indifferent electrode in the shaft showed remarkably clear signal quality with little far-field artefact in the ventricle when compared with the experience of traditional unipolar references of Wilson's Central Terminal or inferior vena cava catheters. The wide reach of the Octaray’s 2-cm splines in all directions, covering large areas of the ventricular surface, facilitates near-immediate rapid diagnosis of activation patterns based on EGM interpretation alone. This facilitates mapping of unstable or even pulseless VTs, which are traditionally considered to be unmappable, by strategic positioning of the catheter over the area of interest. A further point to highlight is the incredible speed of point acquisition and density rapidly exhausting the maximum limit allowed to be displayed on the shell. Unfortunately, the longstanding issue of correct detection and LAT annotation in scar-related arrhythmias in the most critical parts of the map with high prevalence of low-voltage, fractionated EGMs remains an unresolved issue, undermining the true potential, clinical usefulness, and diagnostic value of having such high-density maps. Multiple detection algorithms in the time and frequency domain have been suggested with, so far, none achieving a fully reliable near-field annotation, particularly not in the thicker ventricular wall. The use of a dynamic window of interest, which can be repeatedly adjusted while mapping based on presence or absence of low-amplitude near-field signals, has been proposed as a pragmatic solution to facilitate correct detection and annotation in stable rhythms, yet this is not a feasible option for hemodynamically unstable arrhythmias. In summary, the sophisticated hardware and innovative design is a step in the right direction, yet there is still work to be done.The multispline multipolar Octaray mapping catheter provides excellent signal quality with particularly noticeable sharp unipolar EGM quality using the TRUEref technology and excellent catheter maneuverability. If placed strategically in areas of interest, its wide spatial reach facilitates the rapid diagnosis of VT activation pattern along the splines, allowing for mapping of even hemodynamically unstable VT.Mapping time for ultra-high-resolution maps is short, yet a major drawback remains the failure of standard automated detection algorithms to reliably annotate near-field signals in areas of scar. This undermines the current standalone value of a high-density map for scar-related arrhythmias where manual reannotation is not feasible. Until improved and/or adjusted detection and LAT annotation approaches are integrated, judicial use of dynamic windows of interest, careful map setup, and continuous attention to LAT annotation during mapping, together with traditional EGM interpretation, remain key to guide clinical management.


N = 1931) compared to typically developing youth (N = 2823). We identified three subtypes that were robust to permutation testing and sample composition. Subtype 1 evidenced a pattern of imbalanced cortical-subcortical maturation compared to the typically developing group, with subcortical regions lagging behind prefrontal cortical thinning and myelination and greater cortical surface expansion globally. Subtype 2 displayed a pattern of delayed cortical maturation indicated by higher cortical thickness and lower cortical surface area expansion and myelination compared to the typically developing group. Subtype 3 showed evidence of atypical brain maturation involving globally lower cortical thickness and surface coupled with higher myelination and neural density. Subtype 1 had superior cognitive function in contrast to the other two subtypes that underperformed compared to the typically developing group. Higher levels of parental psychopathology, family conflict, and social adversity were common to all subtypes, with subtype 3 having the highest burden of adverse exposures. These analyses comprehensively characterize pre-adolescent mood and anxiety disorders, the biopsychosocial context in which they arise, and lay the foundation for the examination of the longitudinal evolution of the subtypes identified as the study sample transitions through adolescence.Mood and anxiety disorders typically begin in adolescence and have overlapping clinical features but marked inter-individual variation in clinical presentation. The use of multimodal neuroimaging data may offer novel insights into the underlying brain mechanisms. We applied Heterogeneity Through Discriminative Analysis (HYDRA) to measures of regional brain morphometry, neurite density, and intracortical myelination to identify subtypes of youth, aged 9–10 years, with mood and anxiety disorders ( Mood and anxiety disorders collectively account for over 65% of the disease burden attributable to mental disorders in individuals aged 10–24 years , 4. TherThe diagnostic boundaries of mood  and anxiety disorders, as currently defined , 10 are In response, research efforts have shifted towards new approaches to classification that use data-driven methods to identify subgroups of individuals with mood and anxiety disorders based on their shared biological properties. This approach has yielded promising findings in adults –19 and hhttps://abcdstudy.org/) which acquires comprehensive phenotypic information and high-quality multimodal neuroimaging data from the largest currently available sample of 9–10-year-olds at study entry ; (ii) 178 participants diagnosed only with a depressive disorder ; (iii) 307 participants diagnosed only with a bipolar disorder ; (iv) 1197 participants diagnosed only with an anxiety disorder , and (v) 249 participants with comorbid mood and anxiety disorders    and thei1-weighted, and diffusion-weighted magnetic resonance imaging scans mapped Desikan-Killiany cortical parcellations [https://github.com/Jfortin1/ComBatHarmonization) [The protocols for data acquisition, processing, and neuroimaging feature extraction , 39 are llations  and subcllations  and werellations  derived llations , 25. Allization)  before fOnly participants with complete demographic, clinical, and neuroimaging data were included. Missingness for all other non-imaging measures was low (range 0.04%–8.50%) and missing values were imputed using multivariate imputation by chained equations (implemented in R 4.0.5 using the “mice” function) .We employed Heterogeneity Through Discriminative Analysis (HYDRA), a nonlinear semi-supervised machine learning algorithm  to identhttps://github.com/evarol/HYDRA) was applied to the regional morphometric, GWC, and ND measures. The diagnostic labels of the clinical group were not included in the input features of HYDRA while age, sex, and race/ethnicity were included as covariates. We assessed solutions with 2–7 clusters and chose the optimal solution following a 5-fold cross-validation based on the Adjusted Rand Index (ARI) [P < 0.05. First, we assessed whether the solution obtained in the main analyses differed from that generated following random grouping of participants over 100 permutations. Second, we assessed whether the solution obtained in the main analyses differed from that generated if the sample did not include a clinical group; this analysis also involved 100 permutations  . StatistFDR < 0.005.After identifying clusters through HYDRA, we conducted post-hoc analyses comparing each cluster’s personal, family and social characteristics to those of the typically developing group using a series of mixed linear models implemented with the “lme4” package in R. Comparisons involved neuroimaging, personal, family, and social characteristics. The effects of age, sex, and race/ethnicity were regressed from all models and total intracranial volume (TIV) from models for cortical surface area, subcortical volume, and neurite density  and subtype 2 .The 3-cluster HYDRA solution had the highest ARI and was robust to permutation testing , which included 174,551 children, found a prevalence of anxiety disorders around 9% and depression around 4% while the corresponding rates here are 10% for anxiety disorders, and 3.5% for depression . The preThe HYDRA subtypes identified using neuroimaging-based clustering included a mixture of ABCD participants with mood and anxiety disorders that may reflect diagnostic equivocality with some youth showing diagnostic continuity while others may change diagnostic status or may recover –52. HoweRisk factors for mood and anxiety disorders have been widely researched. The literature provides robust evidence that risk factors are not diagnosis-specific but are shared across multiple disorders. These include familial predisposition –55, periPrior neuroimaging studies in mood and anxiety disorders in youth have focused exclusively on brain morphometry using diagnosis-specific case-control comparisons. Excessive cortical thinning and lower surface area have been reported in youth depression , 65 and Instead, our results suggest that different brain maturational profiles can give rise to a range of clinical symptoms. Typical brain maturational events that dominate late childhood and adolescence are cortical myelination along a posterior-to-anterior gradient  and adapIn this context, the neuroimaging profile of subtype 1 suggests a pattern of imbalanced cortical-subcortical maturation compared to the typically developing group, with subcortical regions lagging behind prefrontal cortical thinning, myelination and cortical surface expansion. This interpretation is aligned with cortical maturation being associated with better cognitive abilities –83 whichThe ABCD study includes planned follow-up assessments using the same protocols that cover a 10-year period of development and will thus enable us to assess the value of neuroimaging-based classification of mood and anxiety disorders identified here. Specifically, the availability of longitudinal data will enable the comparison of this approach to traditional diagnosis-based models for the prediction of functional outcomes of ABCD participants, with regards to cognition, psychopathology and social functioning.Compared to previous studies, the large sample size, narrow age range, and the epidemiological approach to recruitment are major strengths as they optimize the capacity to examine brain variability in mood and anxiety disorders while minimizing challenges arising from selection bias and the inclusion of participants at different developmental stages. The use of HYDRA is a methodological advance over other clustering techniques as it enables the identification of clinical subgroups that differ from the normative reference group along multiple dimensions. Analyses of data from subsequent follow-up waves of the ABCD study will enable the investigation of the longitudinal evolution of the clusters identified and their prognostic values for mental health.Taken together, the findings of this study uncovered brain structural heterogeneity in youth with mood and anxiety disorders indicating marked differences in maturational profiles but lack diagnostic specificity. Future follow-up analyses will enhance understanding of the functional consequences for cognition and psychopathology of further brain development as ABCD participants transition through adolescence.SUPPLEMENTAL MATERIAL


The Coronavirus Disease 2019 (COVID-19) pandemic has been accompanied by increased prenatal maternal distress (PMD). PMD is associated with adverse pregnancy outcomes which may be mediated by the placenta. However, the potential impact of the pandemic on in vivo placental development remains unknown. To examine the impact of the pandemic and PMD on in vivo structural placental development using advanced magnetic resonance imaging (MRI), acquired anatomic images of the placenta from 63 pregnant women without known COVID-19 exposure during the pandemic and 165 pre-pandemic controls. Measures of placental morphometry and texture were extracted. PMD was determined from validated questionnaires. Generalized estimating equations were utilized to compare differences in PMD placental features between COVID-era and pre-pandemic cohorts. Maternal stress and depression scores were significantly higher in the pandemic cohort. Placental volume, thickness, gray level kurtosis, skewness and run length non-uniformity were increased in the pandemic cohort, while placental elongation, mean gray level and long run emphasis were decreased. PMD was a mediator of the association between pandemic status and placental features. Altered in vivo placental structure during the pandemic suggests an underappreciated link between disturbances in maternal environment and perturbed placental development. The long-term impact on offspring is currently under investigation. Caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infections spread globally, and COVID-19 was characterized by the World Health Organization as a pandemic on March 11, 20202. In addition to concerns about acquiring COVID-19, pregnant women are exposed to pandemic related stressors, including social distancing, generalized anxiety, financial insecurity, and fear of mortality4. The impact of these exposures on intrauterine development remains unknown. The COVID-19 pandemic offers a novel window for a natural history investigation of profound lifestyle changes and the effects of maternal stress on placental development.Coronavirus disease 2019 (COVID-19) is a novel infectious disease first reported in a few cases of pneumonia in Wuhan, China on Dec. 31, 20195. Epidemiological studies suggest that even pre-pandemic severe maternal stress is associated with poor pregnancy and neonatal outcomes8. Periods of hardship, such as natural disasters, famine or military invasion, can cause low birth weight, preterm delivery, perinatal anxiety or depressive symptoms as well as cognitive and behavioral problems later in life14. A proposed mechanism underlying these adverse outcomes is placental dysfunction as a result of maternal stress15. The placenta is the primary interface between mother and fetus, and plays important role in nutrition, excretion of toxins, immunity, and metabolism16. It is susceptible to a hostile uterine environment leading to altered placenta function and development18.Maternal mental health concerns are considered a major public health challenge21. Specifically, the morphometric and textural analyses of placental development have been utilized to study pregnancy complications24. For example, pregnancies complicated by fetal growth restriction showed smaller placental volumes and increased heterogeneity of the placenta compared to healthy controls24. Textural analyses in biomedical imaging has been used to quantify tissue microstructure in healthy and diseased tissues28 and is a proposed method to identify regional changes related to injury or inflammation29. The placental textural features calculated from in vivo placental MR imaging represent a new era of advanced placental tissue characterization30. This suggests a potential role for antenatal MR imaging to provide novel insights to placental development in high-risk conditions.At this time, there are limited non-invasive tools to assess placental development in utero, especially prior to the onset of fetal compromise. Detailed magnetic resonance imaging (MRI) analyses of placentas, a recent innovation, can identify global and local differences in placental structure and microstructure31 in pregnant women during the COVID-19 pandemic would lead to changes in placental structure.The aim of this study was to examine the impact of the COVID-19 pandemic on in vivo structural and textural placental development using MRI. We hypothesize that increased maternal mental distressWomen with singleton pregnancies were recruited in an ongoing prospective observational study between June 2020 to April 2021, as part of Project RESCUE (Reducing Elevated Stress from COVID-19 Exposure) at Children’s National Hospital. The inclusion criteria included women older than 17 years with singleton pregnancies of greater than 8 weeks gestational age (GA). Exclusion criteria included women with pregnancies complicated by known chromosomal syndromic conditions, inability to enter the MRI scanner due to physical or psychological reasons, or high-risk pregnancy conditions such as diabetes and hypertensive disorders.This study was approved by the Children’s National Hospital Institutional Review Board (IRB). All methods were performed accordance with the relevant guidelines and regulations. Pre-pandemic pregnant women were enrolled between March 2014 and February 2020 as part of an observational cohort study examining normal brain development in low-risk pregnancies, also approved by Children’s National Hospital IRB. Recruitment methods and eligibility criteria were identical for both cohorts. Written, informed consent was obtained from each participant for both cohorts.Clinical and demographic data were collected and/or abstracted from the medical record for each participant, including maternal age, maternal weight at MRI, parity, GA at birth, birth weight, and race/ethnicity.32. The questionnaire comprises 10 questions, with scoring ranging from 0 to 40. A score greater than 15 indicates a higher-than-average level of stress32. The EPDS (range: 0 to 30) is a useful tool to identify patients at risk for developing postpartum depression33. A score greater than 10 indicates a higher risk fordepression34. The SSAI was designed to evaluate anxiety as emotional state (range: 20 to 80) and as a personality trait 35. A score higher than 40 indicates the presence of anxiety37.All pregnant women were administered four questionnaires on the day of the MRI visit, including Perceived Stress Scale (PSS), Edinburgh Postnatal Depression Scale (EPDS), Spielberger State Anxiety Inventory (SSAI), and Spielberger Trait Anxiety Inventory (STAI). The PSS is a widely used measurement of the degree of stressful feelings experienced in the past monthAxial single shot fast spin echo T2-weighted images were acquired on a 1.5 Tesla Discovery MR450 scanner  using an eight-channel surface receiver coil. Acquisition parameters were as follows: echo time = 160 ms, repetition time = 1100 ms, field of view = 420 × 420 mm, and slice thickness = 4 mm. The final in-plane resolution was 1.64 × 1.64 mm with 40–60 consecutive slices for full placental coverage. Neither sedation nor contrast was used during MRI studies. Each subject was scanned up to two time points in the fetal period.38. The segmentations were performed by two research engineers  with 3–5 years of experience in MRI placental segmentation and were reviewed by a senior neonatologist (N.A.) with more than 7 years’ experience. Intra-rater and inter-rater reliability of the placenta segmentations were determined using 30% of randomly selected scans (80 pre-pandemic and 27 pandemic) by the two trained raters . Intra- and inter-rater reliabilities using intra-class correlation coefficient were all higher than 0.97 for both pre-pandemic and pandemic cohorts. All were blinded to pandemic vs. pre-pandemic cohort.Placentas were manually segmented in the plane of acquisition and then corrected on the other planes to ensure spatial consistency using ITK-SNAP Fig. 38. The s24, and brief descriptions of the features are summarized here. The volume was calculated based on the triangular meshes of the 3-D placental model22. Thickness was defined as the maximal distance between the points of the placenta belonging to the maternal surface and their projection on the fetal surface22. Elongation was defined as the length of the longest branch of the 3-D medial axis skeleton of the shape22. All calculations were implemented in MATLAB R2019a .To characterize three-dimensional (3-D) placental shape, three shape features were used: volume, thickness, and elongation. Detailed elaborations of the determination of these three features have been provided in Dahdouh and Andescavage’s studies22. Detailed descriptions can be found in Dahdouh’s study, and here we briefly describe these features22. The first set of placental textural features included the mean, variance, kurtosis, and skewness of the GL distribution of the placenta22. These four measures were designed to determine the variation of GL intensity of the placenta and were normalized by their corresponding values on the whole image. The second set of placental textural features included energy, entropy, inverse difference moment, contrast, cluster shade and cluster prominence, which were calculated based on the GL Co-occurrence Matrix (GLCM)40. These six features were characterized by capturing the spatial dependencies between pairs of GL, and each feature was averaged over all directions. The third set of placental textural features included short run emphasis, long run emphasis, GL non-uniformity, run length non-uniformity, low GL run emphasis, high GL run emphasis, short run low GL emphasis, short run high GL emphasis, long run low GL emphasis and long run high GL emphasis. These 10 features were computed based on the run-length statistics42. The run-length matrix counted the number of “runs” of consecutive voxels in a given direction41. An image with a high number of short runs is interpreted as finer texture with more details than an image with high number of long runs41. All textural feature calculations were implemented in MATLAB R2019a .To characterize the placental gray level (GL) appearance, three sets of textural features were used. We followed the analytical pipeline proposed by Dahdouh et al. to identify these three sets of placental textural featuresUnivariate analyses were performed to explore the demographic data. The Kolmogorov–Smirnov test was first utilized to test the normality of the continuous variables, including GA; maternal age; maternal weight at MRI; and birthweight, and the results showed that all these variables were not normally distributed. The fetal and maternal demographics were therefore compared between pre-pandemic and pandemic cohorts using Wilcoxon–Mann–Whitney tests for GA, maternal age, maternal weight at MRI and birthweight and using Chi-square tests for fetal sex, number of scans, maternal parity, maternal race/ethnicity and the temporal distribution of subject recruitment.43. First, the associations between pandemic status  and maternal distress measures  were determined using GEE, adjusting for GA at MRI (weeks), given the known effects of GA on placental MRI features. Second, the associations between pandemic status and placental shape features were analyzed using GEE. The primary independent variable was the pandemic status , and all GEEs were adjusted for GA at scan (weeks). Third, the associations between pandemic status and placental textural features were analyzed using GEE, adjusting for GA at scan (weeks). In addition, we further adjusted maternal distress  in the GEEs to determine whether maternal distress is a mediator in the association between pandemic status and placental shape and textural features. High distress was defined as any one of the four distress measure summary scores being greater than their corresponding threshold 37. Furthermore, the association between placental features and birth weight (g) by pandemic status were also investigated using GEEs, adjusting for GA at MRI (weeks), maternal distress  and GA at birth (weeks). Mediation analyses were further implemented to determine whether prenatal maternal distress works as a mediator on pandemic status and placental features44. Three steps of mediation analyses were conducted using GEE: (1) the association between placental features and the pandemic status, adjusting for GA at MRI; (2) the association between maternal distress measures and the pandemic status, adjusting for GA at MRI; (3) the association between placental features and the pandemic status, adjusting for GA at MRI and the significant maternal distress measures found in the previous step. Sensitivity analyses were conducted on two additional covariates, fetal sex and maternal weight, and their effect on the placental features were examined. Lastly, the time trend was investigated by fitting two GEE models (one before the pandemic and the other during the pandemic) to explore the associations between placental features and date of evaluation, adjusting for gestational age at MRI (weeks). The time trend throughout the study period was fitted using nonlinear mixed-effects estimation with the quadratic spline function45. The critical value for statistical significance was set as 0.05. The q-values calculated by the false discovery rate method for the number of features in each set  were also reported to reflect significant parameters under multiple comparisons46. The unstructured correlation matrix was utilized in all GEE models, with the robust sandwich covariance matrix47. All analyses performed in this study were conducted using MATLAB R2019a , and all hypothesis tests were 2-sided.The generalized estimating equation (GEE) was utilized to determine the following associations for comparing the pre-pandemic and pandemic cohortsParticipant recruitment is shown in Fig. 3, p = 0.02) and placental thickness  when adjusting for GA at MRI in the GEE models  to explore the association between placental features and scan date, adjusting for gestational age at MRI (weeks). The results show that within the pre-pandemic cohort, placental volume, thickness, elongation, GL non-uniformity, low GL run emphasis and short run low GL emphasis significantly increased over time. However, within the pandemic cohort, we did not identify a significant difference of placental features over time after adjusting for multiple comparisons  in the pandemic cohort. We also found larger inhomogeneous area  and higher non-uniformity  of placental images in the pandemic cohort. Furthermore, there were no significant temporal differences in placental development within the pandemic cohort for the duration of the pandemic period studied. Lastly, we report that the relationships between placental morphometry and birthweight differed in the pandemic and pre-pandemic cohorts, with stronger associations between placental volume, elongation, run length non-uniformity and birthweight during the pandemic.48. Studies have shown that maternal mental health disorders and prenatal stress can alter fetal development, affecting the child’s health long after the original insult such as difficult temperament, dysregulated sleep and harder-to-soothe infants, and later, lower cognitive performance and worse school achievement50. Prenatal stress has been associated with increased risk of depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), conduct disorders, autism and schizophrenia54. Prior studies also have indicated the increased concerns of psychological disorders in pregnant women during the pandemic compared to non-pregnant women during the pandemic and compared to pre-pandemic pregnant women56, which may represent risks for offspring neurodevelopment including delayed cognitive, language, and motor development61. Our data showed that maternal stress and depression were elevated in the pandemic cohort, and maternal distress was a mediator of the association between pandemic status and placental morphometry and texture. In addition to detecting larger placentas in the pandemic cohort, we also found that the relationship between in vivo placental size and infant birthweight was greater when compared to pre-pandemic controls. These results build upon previous work showing that elevated maternal psychosocial stress is associated with increased placental weight at birth on evaluation of gross pathology specimen62. These findings demonstrated an important link between maternal mental health and the placental development, which may further influence neurodevelopmental outcomes65.Placental adaptations to perturbations in the maternal environment and mental health can trigger adverse fetal programming67. Secondly, cytokines are potential mediator between stress and placental volume. Psychological stress is linked to lower interleukin-10 (IL-10) during pregnancy68. Animal models with IL-10 deficiency showed an increase of up to 28% in placental size69. Epigenetic mechanisms further explain how maternal stress may affect specific placental gene expression patterns. In an animal study, an insulin-like growth factor called peroxisome proliferator-activated receptor alpha (PPARα), which binds tightly with protein 1 (IGFBP-1), hypoxia-inducible factor 3a (HIF3), and glucose transporter 4 (GLUT4), has increased expression for male offspring of pregnant mice with heightened prenatal stress70. Building on the existing data from previous pathology and molecular studies, in this study, we showed a similar pattern of accelerated in vivo placental volume during the COVID-19 pandemic. Further studies exploring these relationships are warranted.In this work, we show that the pandemic cohort had morphometric changes in the placenta that represent enlarged, globular placentas. While the mechanisms of increased placental volume and thickness are unclear, eccrinology and molecular studies suggest that epigenetic changes resulting from maternal distress may upregulate growth factors, resulting in increased placental size. Several potential mediators linking maternal stress and placental growth have been proposed. One such mechanism is that increased maternal stress could result in increased production of insulin-like growth factors, which can increase placental volume71. Khalife et al. reported significant positive associations between placental size  and mental health problems in boys at 8 and 16 years of age. Specifically, increased placental weight was linked with overall probable psychiatric disturbance, antisocial behavior and ADHD symptoms71. Abnormally enlarged placentas with altered shape also have been associated with certain medical conditions, such as maternal anemia, hypertension and diabetes74.An enlarged placenta has been identified as an important factor in altered maternal–fetal nutrient supply and resulting fetal programming81. We also showed that the ratio of the placental volume/elongation relative to birth weight was smaller in the pandemic vs. the pre-pandemic cohort  percentiles of birth-weight-to-placental-weight ratio83. The impact of altered placental morphometry during pandemic on infant neurodevelopmental outcomes merits further investigation.Our data show that placental volume and elongation was positively associated with birth weight in both cohorts, and this finding is in line with several previous studiesWe found that several textural features were significantly different in the pandemic cohort, namely features associated with asymmetry of gray scale and image heterogeneity. Specifically, we noted an increase in heterogeneity and asymmetry of image intensity of placentas in the pandemic cohort.85. Regional changes in placental texture have been observed in placenta accrete88, while global changes in placental texture have been observed in fetal growth restriction (FGR)24. In this work, we found a decrease in mean GL and SRLGL along with increased kurtosis and skewness in the pandemic cohort, the converse of findings previously reported in FGR24. We also report an increase in RLNU during the pandemic, similar to changes reported in FGR, along with previously undescribed decreases in LGLRE, HGLRE and SRHGLE. The precise mechanisms of the microstructural changes of placentas observed from textural analyses in the pandemic cohort remain largely unclear and may in fact be multi-factorial. Previous studies have collectively pointed toward maternal psychosocial stress pathways that may alter the epigenetic signature in placentas94. First, prenatal maternal stress is linked with higher levels of maternal cortisol89, and the increase in maternal cortisol alters uteroplacental metabolites such as serotonin95, which is associated with beta cell heterogeneity in tryptophan hydroxylase protein induction during pregnancy91. Second, differential expression of placental glucocorticoid receptors has been reported in the presence of elevated maternal stress93, and a study has shown that glucocorticoid treatment could lead to increased glucocorticoid receptor mRNA variants detected in the human placenta, where GR-α and GR-1C mRNA having the highest expression96. Third, placental DNA methylation changes are associated with increased exposure to maternal stress98. These DNA methylation changes could regulate placental-specific gene expression, including monoallelic expression and X-chromosome inactivation in the placenta, leading to the changes of placental context98. These alterations in placental metabolism and gene expression associated with maternal distress may result in microstructural changes that can be detected by texture analyses and deserve further clinical validation particularly for the pandemic population.Textural analyses of sonographic and MR images of the placenta have shown increased heterogeneity with advancing GA, a reflection of the increasing complexity of placental microstructure during gestation101. Genome-wide placental transcriptome studies have correlated gene modules involved in immune response, myeloid cell differentiation, and placental tissue development with newborn birth weight102. The placenta is genetically identical with the fetus104, and epidemiological studies suggest that genetic factors account for 30–80% of birth weight variance107. Interestingly, placental DNA methylation may be influenced by maternal insulin levels during pregnancy108, and increased placental DNA methylation is associated with large-for-gestational-age infants109, and methylation alternations may reflect changes to placental texture110. Nevertheless, the mechanisms underlying these observations need further interrogation.Our data show that altered GL measures, namely decreased mean GL and increased kurtosis GL, of the placenta were associated with increased birth weight in the pandemic cohort, which may reflect altered placental microstructure; while the etiology of these changes is not fully elucidated, these may be related to pandemic related physiologic, psychologic and environmental stressors. The placenta can undergo major structural and functional adaptations to shield the fetus from environmental stressors112. The benefits of MRI lead to finer 3-D placental models and better estimation of the morphometric and textural features of human placentas presented in our study.Our strengths include a novel, non-invasive approach to analyze in vivo placental morphometry and texture to detect early alterations in pregnant women affected by the COVID-19 pandemic mediated, at least in part, by maternal mental distress. We utilized the 3-D reconstructed models and computational analyses of texture based on high-resolution MR images to detect abnormalities, representing gross and microstructural changes in placental development during the pandemic113. Thus, manual segmentation is currently the best method used in the literature and has served as the ground truth when developing segmentation algorithms for the human placenta115. Second, this work was intended to explore the impact of the pandemic on placental development and included women with no known COVID-19 exposures, based on serial questionnaires. However, subclinical or unknown exposures to the COVID-19 virus cannot be fully excluded. Similarly, we investigated the role of pandemic-related maternal mental distress associated with COVID-19 on placental development; however, there may be additional stressors and lifestyle changes related to the pandemic, including environmental stressors, and changes in physical activity, that also may have contributed to disrupted placental development. Furthermore, pregnant women recruited into this study were from the Washington, DC metropolitan area and the associations observed in this study should be explored in other geographic regions before assessing the generalizability of these findings. Third, the clinical implications of altered placental morphometry and texture on child neurodevelopmental for pregnancy during pandemic remain uncertain; ongoing studies of pregnancy outcome are currently underway. These include correlating of in vivo findings with ex vivo placental pathology, as well as long-term neurodevelopmental outcomes of children born during the pandemic. Lastly, application of these analyses and results should be linked to clinical evaluation and interpretation, in order to develop novel prediction models of in vivo placental structure relative to clinically significant outcomes118.Although our study had several strengths, the study limitations need to be outlined. First, the segmentation of the placentas from MR images was performed manually. Due to the variability of the placental shape, orientation and appearance, the fully automatic segmentation of the placenta remains a challenge118. The further evaluation of these findings with placental pathology, pregnancy outcomes and long-term neurodevelopmental health is currently under investigation.Our study is the first to describe MRI-based morphometric and textural changes of in vivo placenta in women pregnant during the COVID-19 pandemic. Our approach provides a semiautomated method of standardizing placental MR evaluation in women during and prior to the pandemic. With these sophisticated techniques, we can detect in vivo changes of the placenta not only on gross-level evaluation  but also microscopic-level assessment . Moreover, we demonstrate changes in gross and microscopic placental structure in women with increased levels of prenatal stress, a potentially modifiable risk factor that, if recognized early, may allow for timely interventions to improve placental health and pregnancy outcomes. Future studies relating in vivo measures of placental development with clinical evaluations and outcomes may lead to the development of clinically relevant prediction models of placental healthSupplementary Figures.Supplementary Tables.


Drug-induced liverinjury (DILI) is an important safety concernand a major reason to remove a drug from the market. Advancementsin recent machine learning methods have led to a wide range of insilico models for DILI predictive methods based on molecule chemicalstructures (fingerprints). Existing publicly available DILI data setsused for model building are based on the interpretation of drug labelsor patient case reports, resulting in a typical binary clinical DILIannotation. We developed a novel phenotype-based annotation to processhepatotoxicity information extracted from repeated dose in vivo preclinicaltoxicology studies using INHAND annotation to provide a more informativeand reliable data set for machine learning algorithms. This work resultedin a data set of 430 unique compounds covering diverse liver pathologyfindings which were utilized to develop multiple DILI prediction modelstrained on the publicly available data (TG-GATEs) using the compound’sfingerprint. We demonstrate that the TG-GATEs compounds DILI labelscan be predicted well and how the differences between TG-GATEs andthe external test compounds (Johnson & Johnson) impact the modelgeneralization performance. DILI is the main reason for drug disapprovalor market withdrawal.4 Regulatory agencies rely on drug postmarketing monitoringand clinical trials to discover adverse long-term effects.6 There are numerous public data sets14 from preclinical to postmarketing data capturing different aspectsof drug toxicity information. These data sets often use agencies reports,drug labels, or scientific literature to annotate drug toxicity. Inthis way, information about the underlying mechanisms or dose dependency(dose dependent or intrinsic versus dose independent or idiosyncraticDILI) is lacking. The main limitation of those data sets is the generalizationof hepatotoxicity, where hepatotoxicity is an umbrella term for severalcomplex DILI phenotypes due to various mechanisms. We need to be ableto differentiate primary from secondary, while we hypothesize theunderlying mechanisms in addition to clinical risk factors.4 Furthermore, different data sets report conflictingDILI risks for similar drugs15 due to differentcriteria applied to case reports or drug labels which makes the reproducibilityof them difficult.8There are nobiomarker diagnoses that specify clinical DILI fromother liver disorders with certainty and the diagnosis of DILI remainsmainly based on ruling out other competitive causes.17 to assist early prediction of toxic drugs by in silico models. TheOpen Toxicogenomics Project-Genomics Assisted Toxicity Evaluationsystem17 (TG-GATEs) is a data set thatincludes toxicological data from both in vivo studies and in vitroassays in both rat and human hepatocytes. We extended this data setby performing a digital histopathology evaluation of liver slidesthat are publicly available on TG-GATEs data set. We carried out multiplephases to ensure that morphological diagnoses reflect the known underlyingmechanisms of DILI in animals and translate the diagnoses to Standardfor Exchange of Nonclinical Data (SEND) by applying InternationalHarmonization of Nomenclature and Diagnostic Criteria (INHAND)18 compliant terms. This study collected data setswith a primary goal of generating accurate and reliable pathologydata to be utilized as training data for machine learning (ML) algorithmswhile capturing primary pathology processes and, most likely, pathogenesis.We also used this annotation to classify TG-GATEs and proprietaryJohnson & Johnson compounds into DILI-positive/negative groupsfor prediction model development and evaluation.Few data setscollect toxicity information using subtle phenotypesbased on controlled preclinical in vivo studies26 and ML based models.31 The latter reduces the task of predicting DILI label to a classificationproblem where the objective is to categorize each compound to DILI-positive/negative.A lot of studies33 developed many DILI prediction models usingvarious shallow ML methods, including random forest (RF), decisiontree, support vector machine (SVM), and logistic regression (LR) usingvarious molecular structure representations such as extended connectivityfingerprint (ECFP).34 Chierici et al. employeddeep learning to train multiple DILI prediction models using toxicogenomicsdata to compare their performance with shallow ML methods.35 They concluded that deep learning models donot systematically perform better than shallow ML methods yet dueto the size of the data set or because their data set is not informativeenough. Similarly, Kotsampasakou et al. demonstrated that data qualityand preprocessing affect the performance significantly for shallowML methods. Furthermore, Li et al. showed better performance of theensemble of shallow ML methods  than deep models using Mold2 descriptorto predict DILI.36Several methodshave been developed to predict DILI from molecularstructure using predefined rules(1)Preparing and introducing a new DILIannotation that captures mechanistic and phenotypic DILI informationmore reliably and accurately than other data sets based on specificand standard in vivo liver histopathology nomenclature.(2)Evaluating various ML methods forpredicting DILI from compounds fingerprints.(3)Studying the generalization of trainedmodels from public data to proprietary pharmaceutical data sets.This work describesa new DILI annotation approach solely basedon in vivo studies and its prediction performance using ML models.We address previous works shortcomings by determining the compoundslabel (DILI-positive/negative) based on repeated dose-dependent invivo assessments rather than drug labels or agency reports. Usingcompound chemical fingerprint, we assess the performance of a trainedmodel using only TG-GATEs on two external test data sets, JNJ-I andJNJ-II. In this study, we focused on the prediction of preclinicalstudy outcomes in industrial settings, where validation is both possibleand feasible as a generalized model solely for preclinical data remainsa complex task. This paper sheds new light on why the model failsto generalize to external test data sets. In particular, the modelparameters and present chemical substructures influence model performanceon the external test data sets. The main contributions of this workare as follows:We collected observed phenotypesof TG-GATEs, JNJ-I, and JNJ-II compounds for different doses in the29 day study. A compound was labeled DILI-positive if any phenotypesare observed regardless of the dose. For instance, those TG-GATEscompounds that showed any of the pathological end points defined in 34 derived from their molecular structure. ECFPsare circular topological fingerprints designed to represent the presenceor absence of a particular molecular substructure circular neighboringatoms. We used a diameter of 8 with a length of 4096.Compounds are represented by ECFP37 and UMAP38 are performed on ECFP fingerprints to visualizethe compounds in two-dimensional space. We used scikit-learn39 and UMAP40 to computethe embeddings.Different dimensionality reductionalgorithms were employed to project the data set to two-dimensionalspace to visually compare TG-GATEs and Johnson & Johnson compounds.In this study, PCAx =  ∈{0, 1}4096 denote abinary ECFP fingerprint of size 4096 and y ∈{0, 1} is the corresponding binary DILI label. Given a training set, N compoundsdrawn from an unknown distribution. Let N0, N1 denote the number of DILI-positiveand DILI-negative, respectively. The goal is to train a classifierto predict the DILI label of a compound by optimizing a certain objectivefunction . The distribution of DILI-positive/negativeis uneven within our data set . Finally, it assigns the most probable label toeach subgroup. The significant benefit of using RF is providing animportance score of each feature that shows each fingerprint bit’scontribution to the prediction task. RF shape and behavior are influencedby a few parameters:T.The numberof decision trees, D.The maximum allowed tree depth, H.The choice of optimization objective function (splitfunction), RF43 is a supervisedestimator that finds the best decision boundaryrepresented by a hyperplane parametrized by θ withthe largest margin to assign toxicity class to the input compounds.The main idea behind the SVM algorithm is to transform the data tohigher dimensional data using a suitable function, ϕ(x), where the classification task is simpler such thatC > 0is the regularizationcoefficient. SVM behavior is influenced withC.The regularization coefficient The kernel function such as linear or RBF.SVML1-regularizedLR is known to avoid overfitting and have a good generalization performance.44 In the logistic model, the probability of acompound x being toxic has the form:θ ∈ R4096 are the parameters. Underthe Laplacian prior,given by p(θ) = (C/2)4096 exp(−C ∥ θ∥1), the maximum a posterior estimate of θ isC is a regularizationcoefficient and ∥.∥1 is the L1 norm.LR model is a supervised linear estimator that estimates the probabilityof a compound being toxic. 39 implementationto train RF, SVM, and L1-LR models. Weperformed a grid search overthe model’s hyperparameter, as summarized in T for RF is sampled evenly inlog space from 1 to 29 which results in a search spaceof 1, 2, 4, 8, 16, 32, 64, 128, 256, 512 for the number of trees, T. The grid search follows the procedure explained in We used scikit-learn45 to find the best hyperparameter.We report the performance of each model in predicting the DILI labelon JNJ-I and JNJ-II using AUROC, precision (PR), recall (RE), specificity(SP), and Matthews correlation coefficient (MCC). The algorithm splitsthe training data (TG-GATEs) into stratified five-fold with a nonoverlappinggroup. The group labels are acquired by running Butina clusteringalgorithm46 using Tanimoto distance. Weused such procedure to prevent predicting compounds with high groupTanimoto similarity to the training data producing more realisticscenario to assess the models prediction performance.47Each model’sprediction performance and hyperparameter search is evaluated usinga 5-fold stratified group cross-validation with 10 repeats as shownin 17 and theirgeneralization performance is evaluatedon JNJ-I and JNJ-II. We used the above annotation method in this studyto process the data. The We built multiple DILI predictionmodels trained on TG-GATEs,(1)Confirming or identifyingnew diagnosesand providing all primary morphological diagnoses present in the liversections of all animals in the study and at every time point.(2)Translating each of thediagnosesto SEND-compliant terms that align with INHAND nomenclature, usingdescriptive rather than interpretative diagnoses.(3)ischemic necrosis of centrilobular hepatocytes as a result of hepatocyte hypertrophy; or liverpathology findings considered in response to lesions occurring fromoutside the liver. Furthermore, spontaneously occurring backgroundfindings such as inflammatory infiltrates or focal single cell necrosis were excluded.Identifying possible primary pathologyprocesses and differentiating them from adaptive or secondary changes,such as (4)Providing the most likely pathogenesisand possible adverse outcome pathway for the liver pathology findingsby analyzing the chronological progression of the findings from theearliest time points to later time points.Our main goal was to prepare a largedata set accurately capturing DILI and the likely underlying mechanismsto be utilized eventually in ML methods. Therefore, we performed adigital histopathology evaluation of liver slides that are publiclyavailable on TG-GATEs data set, a database containing scanned digitalmicroscopic slides of the liver, generated from various experimentsinvolving more than 100 compounds. Our review included the evaluationof slides from studies with a total of 83 hepatotoxicants carefullyselected to reflect a wide range of pathology manifestations and possiblemechanisms of DILI. Slides were generated at multiple time points:4 h, 24 h, 4 days, 7 days, 15 days to 29 days in most of the studies.The histological evaluation involved 4 phases, which were as follows:18 or SEND compliant terms, an attempt was made to harmonize nomenclatureacross studies by capturing the main morphological diagnoses withoutincluding cumbersome modifiers that are not amenable to merging withliver pathology findings from other studies. Phase 3 was criticalin determining if the liver was indeed a target of the drug/chemicalby analyzing all associated changes in the animals, in addition tocompounds that might cause liver pathology findings secondary to othersystemic changes, such as Kupffer cell hyperplasia/activation following NSAID compounds that produce intestinal ulceration andperitonitis. Therefore, this stage included analysis of all supportingdata from clinical observations, clinical pathology and the pathologyreports. Phase 4 involved identifying the earliest changes and theearliest time point at which they occurred, by looking for very subtlechanges, capturing their zonal distribution and subanatomic localization,and mapping out the lesion progression and the likely pathogenesisof the lesions. Phases 1 and 2 involved careful consideration of themorphological diagnoses to ensure all relevant morphological changeswere captured, and the diagnoses were streamlined to reflect primarypathologies that fit into the known mechanisms of DILI in animals.Besides translating the diagnoses to INHAND7 and DILIst.12We computedthe distribution ofTanimoto similarity and hamming distance between all pairs of compoundsfrom TG-GATEs to JNJ-I and JNJ-II, as shown in L1-LR models trained on TG-GATEsusing ECFP molecular fingerprints to predict compound DILI label.Models were trained within the framework of 5-fold group cross-validationwith 10 repeats to decrease the effect of randomness on the predictionmodel performance. In addition, the generalization performance ofthe trained models was evaluated on JNJ-I and JNJ-II. We used theAUROC to measure the performance. A significant drop in generalizationperformance was observed for all models when tested against both JNJ-Iand JNJ-II external sets. L1-LR across 10 repeats, but all models performed roughly14 % worse than their CV performance.We compared the performance ofRF, SVM and L1-LR.The DILI-positive/negative compoundsratio is not equal 2, leadinWe also examinedthe chemical substructure (fingerprint bit) average importance weightgiven by the RF model trained on TG-GATEs in 48 butit is necessary to accelerate the effortto evaluate and discover new DILI biomarkers. Chen et al. assertedthat “there is no commonly adopted practice by which the researchcommunity can classify a drug’s DILI potential in humans”.Assessing DILI risk associatedwith drugs is difficult and complex,50 These factors severely hinder preclinical efforts to accuratelypredict DILI and uncover the underlying in vivo mechanisms. Furthermore,existing in vitro hepatocyte systems based on human cell lines orrodent hepatocytes are not optimal when simulating human DILI.51 As a result, preclinical toxicity models lackuniversal predictability of drug efficacy in humans52 and are largely due to metabolic differences between species,resulting in setbacks within pharmaceuticals company developing newdrugs.58 Although the detection of DILI in humans is crucial, we did notadd any data enabling us to learn the translation from in vivo studyto human DILI and focused on building early preclinical DILI model.The introduced annotation framework andcorresponding data set have been developed with the primary goal ofimproving early DILI detection models in preclinical settings. Thelimited understanding and prediction of DILI is primarily due to thediscrepancies between human and animal DILI observed during preclinicaldrug development and the complex mechanism of human DILI.7 or case reports13 from approved agencies,literature, etc. Therefore, DILI labels are partially affected bythe opinions and choices of the authors rather than evidence8 given the uncertainty of the causality assessment.Alternatively, we developed a new methodology to determine DILI labelsbased on particular in vivo studies. We could generate peer-reviewed,fit for purpose and INHAND-compliant pathology data for use in ML.Implementing INHANDS provides standardized terminology and diagnosticcriteria for preclinical studies. It facilitates data integrationand enhances the interpretation of pathological findings. Furthermore,it helps in unraveling the underlying mechanisms of pathological changes,thus enabling a deeper understanding of the physiological responsesto drugs. Classic hepatotoxicants were associated with a variety ofhepatobiliary pathology and changes in liver enzymes. Several pharmaceuticalcompounds that have been withdrawn from the market or have a blackbox warning for causing idiosyncratic DILI did not produce overt pathologyin rats. However, in most of these studies, consistently cytoplasmictinctorial or degenerative changes associated with glycogen depletionwere present in the periportal areas. These are subtle changes thatwould not be typically recorded in a regular toxicological study sincemost of them were only transiently present between hours postdoseand 4 days.There have been numerous attempts tobuild data sets where DILI risk is determined based on the existenceof specific keywords on the drug labelhepatocellular hypertrophy, periportal glycogen depletion, cytoplasmic vacuolation , apoptosis/single cell necrosis aswell as zonal necrosis, and increased mitoses . When generating pathologydata for ML, recording early changes such as increased mitoses or cytoplasmic alteration is critical. These changestend to be transient, but possibly part of the early key events inthe pathogenesis of lesions observed at later time points. These earlychanges are also likely to correlate with toxicogenomic data if collectedat similar early time points.Histopathology of preclinical species might notbe able to predict idiosyncratic and immune mediated DILI, but othertools, such as toxicogenomics might be helpful since some of the earlyunderlying mechanisms might be similar between animals and human.The majority of primary lesions and clinical chemistry changes seenwith classic toxicants were present by day 4, suggesting that screeningcompounds for hepatotoxicity can be achieved in a 4 day study. Whenprimary lesions were recorded in order of frequency of induction bythe reviewed compounds, the most commonly encountered liver pathologyfindings were 7 or DILIst12 as shown in In some instances, the propseddrug labeling in this study doesnot align by DILIrankIndependent of the models, we observeda key trend where the performance dropped significantly on the externaltest set, JNJ-I and JNJ-II, while achieving good cross-validationscores on TG-GATEs. We attribute the failure of generalization mainlydue to the intrinsic difference between Johnson & Johnson compoundsand TG-GATEs. Therefore, the external test data sets cover differentregions of chemical space, while the model shows better performancefor TG-GATEs, leading to an imperfect prediction model. For instance,we showed the RF model ignores many present chemical substructuresin JNJ-I and JNJ-II compounds for predicting the DILI label, whichsubsequently affects the generalization performance.The uncertaintyin the DILI label could also contribute to the lack of generalization.Not all compounds fit into a particular pathology end point; on thecontrary, many compounds satisfy the criteria for multiple end pointsin our case where we collected information for multiple doses. Traininga separate model for each pathology end point was impossible due tothe limited data 6. Our DIWe introduced a phenotype-basedDILI annotation that is more reliable,accurate, and reproducible in comparison with previous works despitepoor generalization to the external data set. Characterization ofDILI label by phenotypes makes it easier to hypothesize causalityand eliminates the need to define opinion-based criteria to analyzethe agencies report, drug labels, etc. As a result, it is easier toreproduce more compounds for monitoring to build a prediction modelwith better generalization. Three data sets were defined using theintroduced annotation: TG-GATEs, JNJ-I, and JNJ-II. RF, SVM, and LRmodels trained on TG-GATEs achieved a good cross-validation scorebut failed to generalize to the external test data sets JNJ-I andJNJ-II. Our investigations so far have only been on a small scaleof compounds; we have shown that the difference in the data distributionof the molecular substructure impacts model parameters. In particular,TG-GATEs and Johnson & Johnson data set cover non-overlappingregions of chemical space, causing the model to ignore informationin a subset of the present Johnson & Johnson compound’ssubstructures.We are currently studying to build a dose–responsemodelfor each phenotype to address the uncertainty in labeling approach.This will allow us to avoid mixing various mechanisms under the samelabel and predict phenotype findings instead of DILI-positive/negative.By removing the fixed time of 29 days in vivo studies, we aim to createa better model. Furthermore, we plan to explore the possibility ofusing in vitro assay to improve generalization performance. Our findingshave shown that differences in molecular substructure distributioncan affect the model’s performance, and increasing the sizeof the training set or augmenting it with side information such asin vitro assay may be a way to overcome this issue. Overall, whileacknowledging the limitations and areas for improvement, our approachhas the potential to enhance the accuracy and reliability of dose–responsemodeling, which can have important implications for drug developmentand safety evaluation.