Citations

Abstract To enhance the prediction of traumatic brain injury (mTBI) outcomes, we propose a deep learning approach that integrates brain computed tomography (CT) scans with corresponding synthetic T1-weighted magnetic resonance imaging (T1-MRI). Our method significantly outperforms the prediction using CT scans alone. TRACK-TBI Pilot dataset, which includes imaging and clinical outcome data from patients with TBI, is studied. The hypothesis is brain CT and T1-MRI complement each other and together will improve TBI prognosis compared to using either CT or T1-MRI alone. Since CT and T1-MRI may not be available for the same individual, we employed a specialized version of a generative adversarial network (GAN), known as fixed-point GAN (FP-GAN). FP-GAN was trained using unpaired CT and T1-MRI scans to generate synthetic T1-MRIs from real CT scans. This process produced pseudo-paired CT-MRI data, which was then used to train a deep learning classifier for outcome prediction. The classifier consists of dual parallel 3D ResNet-18 models, each independently processing T1-MRI and CT scans. We used Glasgow Outcome Scale-Extended (GOSE) scores at 3 months post-TBI as the measure of patient outcomes. To avoid data leakage, the subjects used in FP-GAN and ResNet-18 model have no overlap. We further divided the paired data, allocating 69 samples for 5-fold cross-validation and 17 samples for testing. Prognostic performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score (the harmonic mean of precision and recall), sensitivity (true positive rate) and specificity (true negative rate). For binary classification, we defined good recovery as GOSE ≥ 7 (positive) and poor recovery (negative) as 3 ≤ GOSE ≤ 6. Accordingly, our training set consists of 24 subjects with poor recovery and 45 subjects with good recovery, while the testing set includes 5 subjects with poor recovery and 12 subjects with good recovery. A DeLong test on AUC confirms that the improvement from incorporating synthetic T1-MRI (AUC = 0.76 ± 0.10) is statistically significant (P < 0.05) compared to using CT alone (AUC = 0.68 ± 0.13). The significant improvement from using the combination of real CT and synthetic T1-MRI in sensitivity (SEN = 0.95 ± 0.07) and overall performance metrics, such as F1-score (F1 = 0.84 ± 0.03), suggests that the proposed approach provides a robust and effective prognostic approach compared to using CT alone (SEN = 0.83 ± 0.18 and F1 = 0.76 ± 0.07). This pilot research demonstrates the potential of a deep learning-based harmonization model to bridge the gap between CT and T1-MRI in TBI assessment. By integrating synthetic T1-MRI with CT, prediction performance is substantially enhanced.

ABSTRACT Purpose Malignant rhabdoid tumor of the kidney (MRTK) is a rare, aggressive tumor seen in young children. The optimal timing of resection for locally advanced tumors is not well‐defined. The purpose of this study is to evaluate modern oncologic outcomes and the impact of surgical timing. Methods A multicenter retrospective review was performed by institutions participating in the Pediatric Surgical Oncology Research Collaborative. Children younger than 21 years old with MRTK diagnosed between 2000 and 2022 were included. Results Sixty‐nine patients were identified with MRTK and met the inclusion criteria. Median age of diagnosis was 10.1 months. Overall survival (OS) at 1, 5, and 10 years was 49%, 32%, and 19%, respectively. Patients with local Stage III disease who underwent upfront resection ( n = 18) compared to those who had delayed resection after NAT ( n = 15) had a similar OS, median OS greater than 60 months versus 14.6 months, respectively; p = 0.396. The surgical timing groups were balanced in terms of the presence of metastasis, length of follow‐up, and tumor characteristics. There was one occurrence of primary intraoperative tumor spill and two occurrences of organ injury in the upfront resection group compared to none in the delayed resection group. Conclusion MRTK carries a poor prognosis despite multimodal treatment. Histologic diagnosis may not be confirmed at presentation, and MRTK cannot be reliably distinguished from Wilms tumor on imaging alone. As overall survival is similar, the decision regarding surgical timing in locally advanced tumors should be individualized based on perceived resectability, balancing the risk of intraoperative complications against the possibility of tumor progression during neoadjuvant therapy.

ABSTRACT Imaging mass spectrometry has made significant advancements in recent years owing to its ability to study the spatial localization and abundance of proteins, peptides, lipids, glycans, metabolites, and drugs. In this study, we employed an imaging mass spectrometry‐based workflow called MALDI‐IHC, which uses antibodies conjugated with photocleavable mass‐tags, to investigate the detection of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) along with pan‐cytokeratin in formalin‐fixed paraffin‐embedded (FFPE) sections from cases with breast cancer. The expression of ER, PR, and HER2 was consistent with the clinical diagnosis based on conventional immunohistochemistry, lacking signal in triple‐negative cases and concordant signals in the cases that were classified as ER+/PR+/HER2+, ER+/PR+/HER2−, and ER−/PR−/HER2+ groups, respectively. In addition, the potential utility of a seconday antibody‐based MALDI‐IHC approach for HER2 expression was evaluated. In agreement with immunohistochemistry results, HER2 expression co‐localized within tumor regions in a HER2+ breast cancer case, while no expression was observed in a HER2− case. Collectively, these results highlight the potential of imaging mass spectrometry‐based MALDI‐IHC workflow for multiplexed detection of proteins in clinically relevant tissue sections.

57 Background: Cardiovascular disease (CVD) is the leading non-cancer cause of death among men with prostate cancer (PC), particularly during androgen-deprivation therapy. While CVD risk-prediction models are well established in the general population, barriers to integration within oncology workflows remain poorly defined. Guided by the PRISM and RE-AIM frameworks, this study evaluated multilevel determinants influencing adoption, feasibility, and sustainability of CVD risk-assessment tools in PC care. Methods: A national, cross-sectional survey of 45 physicians (medical oncology 49%, urology 38%, radiation oncology 13%) from 18 U.S. states was conducted. Respondents represented early- (27%), mid- (36%), and late-career (38%) clinicians across academic (87%) and community (13%) settings. Quantitative items mapped to PRISM/RE-AIM domains assessed adaptability, cost/resource feasibility, effectiveness, equity, and sustainability; open-ended responses explored contextual barriers and facilitators. Descriptive statistics summarized quantitative data. Results: Physicians reported moderate-to-high readiness to adopt a CVD risk-assessment tool, emphasizing workflow alignment and EHR integration over algorithmic complexity. Table 1 summarizes domain-specific findings. Ninety-three percent of respondents favored lab-independent models that minimize workflow disruption. Conclusions: Pre-implementation analysis highlighted that structural barriers, rather than algorithmic or statistical limitations, remain the primary obstacles to adopting CVD risk-assessment tools in prostate-cancer care. Physicians emphasized the need for EHR-integrated, non-laboratory-based, and time-efficient tools that align with routine oncology workflows and minimize cross-specialty friction. Addressing these practical and organizational determinants may be pivotal to achieving equitable, scalable, and sustainable cardio-oncology implementation across diverse practice settings. PRISM and RE-AIM constructs evaluation results. Construct Likely/Very Likely (%) Interpretation Perceived Effectiveness 87% Broad confidence in clinical utility Equity in Patient Reach 75% Strong perceived equity in reach Equity in Effectiveness 73% Expected to perform consistently across populations Adaptability to Workflow 71% High compatibility with existing clinic workflows Cost/Resource Feasibility 65% Feasible for resource-constrained settings Likelihood of Adoption 60% Moderate readiness for implementation Equity in Adoption 58% Equitable uptake possible despite resource differences Reach to Target Population 57% Moderate likelihood of reaching most patients Sustainability Over Time 51% Moderate long-term feasibility Consistency of Implementation 42% Need for standardized protocols

741 Background: A significant treatment gap exists for efficacious, well-tolerated bladder-sparing options for patients with HR BCG-UR NMIBC with CIS. Cretostimogene is an oncolytic immunotherapy with dual mechanisms of action. It replicates in and lyses cancer cells with Rb-E2F pathway alterations, while simultaneously amplifying an anti-tumor immune response, further mediated by the GM-CSF transgene. BOND-003 (NCT04452591) is a phase-3 study evaluating the efficacy and safety of cretostimogene in patients with HR BCG-UR NMIBC with CIS +/- HG Ta/T1 (Cohort C) and HG Ta/T1 only (Cohort P). We report data on radical cystectomy performed post-recurrence or progression on Cohort C. Methods: 112 patients were enrolled. Participants had previously received adequate BCG and were considered BCG-UR by the FDA definition. Cretostimogene treatment consisted of a 6 weekly induction course, followed by 3 weekly maintenance cycles every 3 months at year one and every 6 months during years 2-3. Repeat induction was permitted at Month 3, if persistent HG Ta or CIS. Response assessments included serial cystoscopy, urine cytology, and mandatory mapping biopsy at 12 mo, with centralized review of all pathology. The primary endpoint was Complete Response (CR) at any time. Cystectomy-Free Survival (CFS) and Progression-Free Survival (PFS) were key secondary endpoints. Results: As of the June 23, 2025 data cutoff (median follow-up of 25.8 months), the CR rate at any time is 75.5% (83/110) (95% CI 66.3-83.2%). Kaplan-Meier estimates of 12- and 24-month DoR are 64.2% (95% CI 52.5-73.8%) and 60.1% (95% CI 48.2-70.0%), respectively, with a median DoR of 27.9 months (95% CI 14.3-NE%) and ongoing. The 12- and 24- month CR rate is 46.4% (51/110) (95% CI 36.8-56.1%) and 41.8% (46/110) (95% CI 32.5-51.6%), respectively. The 12- and 24-month CFS rates are 89.2 (95% CI 81.3-93.9) and 81.3% (71.8-87.8), respectively, with median CFS not reached. Among 18 patients who underwent radical cystectomy post-disease recurrence or progression; 15 (83.3%) had NMIBC or pT0 on final pathology. At 12- and 24- months, 96.6% are free from ≥T2 progression. Cretostimogene has a well-tolerated safety profile, with no grade ≥3 treatment-related adverse events. Conclusions: Cretostimogene offers distinct advantages with its mechanism of action, efficacy, durability and safety profile for the treatment of HR BCG-UR NMIBC. Furthermore, a significant proportion of patients receiving cretostimogene remained progression-free and avoided radical cystectomy. Most patients who underwent radical cystectomy had NMIBC or pT0 on final pathology maintaining a window of opportunity. Ongoing and future investigations of cretostimogene, as monotherapy and in rational combinations, may address the considerable unmet need for patients with bladder cancer. Clinical trial information: NCT04452591 .

PURPOSE The continuous development of new imaging approaches, molecular phenotyping, genetic subtypes, prognosis assessments, and effective therapies across a range of disease states has created a need to redefine terminology and best practices for clinical trial conduct in patients with advanced prostate cancer. Methods We convened an international expert committee of diverse working groups, the Prostate Cancer Working Group 4 (PCWG4), between 2016 and 2025. Our objective was to formulate updated criteria based on emerging evidence and clinical trial data in a biomarker context to provide guidance for clinical trial design, eligibility, and end point assessments for patients with advanced prostate cancer. RESULTS PCWG4 redefines terminology around the disease state and previous therapies in a patient-centric context and terminology focused on androgen pathway modulation. We consider imaging, with a particular focus on positron emission tomography (PET)–defined disease. New recommendations are provided for disease state terminology, defining eligibility criteria, response and delay/prevent end points, intervals for reassessments including imaging, and patient-reported outcome determination. We provide recommendations in a biomarker-based context of use for the intended indication, reflective of patient benefit for specific interventions. We emphasize the need for development of validated PET imaging and molecular and phenotypic criteria as well as trial designs to appropriately risk stratify patients, predict and assess benefit, and measure post-treatment outcomes reliably in a trial framework. CONCLUSION PCWG4 updates recommendations on patient and tumor characterization, therapy development, and imaging criteria and extends guidance into earlier androgen pathway modulator–naïve/sensitive disease states to reflect an evolving, heterogeneous, and diverse patient population to optimize treatment benefits for all patients.

Background/Objectives: Precocious puberty (PP), defined as the onset of secondary sexual characteristics before 8 years in girls and 9 years in boys, is associated with psychosocial distress, compromised adult height, and long-term metabolic risk. Early identification remains challenging, as current diagnostic approaches are largely reactive and rely on invasive or resource-intensive testing. This narrative review examines how artificial intelligence (AI) can support earlier risk prediction and detection of PP through integration of clinical, hormonal, imaging, lifestyle, and environmental data. Methods: A narrative literature review was conducted using PubMed, Scopus, Embase, Web of Science, and Google Scholar to identify relevant studies published between 2005 and 2025. Eligible studies included original research and high-quality reviews that examined AI-based approaches, such as machine learning and deep learning, in pediatric endocrinology, particularly for the prediction or diagnosis of central or peripheral precocious puberty. Studies incorporating clinical, hormonal, radiological, lifestyle, environmental, or multi-omics data relevant to AI modeling were included. Results: AI models, including XGBoost, random forest, convolutional neural networks, and regression-based approaches, have demonstrated potential utility in predicting central precocious puberty using hormonal, imaging, and growth data. Reported applications include automated bone age assessment, lifestyle and dietary risk stratification, and exploratory use of wearable-derived behavioral data. However, progress is limited by small pediatric datasets, population bias, limited interpretability, and unresolved ethical challenges related to privacy, consent, and equity. Conclusions: Artificial intelligence represents a promising decision-support approach for earlier, non-invasive, and individualized risk assessment in precocious puberty. Future progress will depend on the integration of longitudinal, multimodal data, the development of ethical models, and interdisciplinary collaboration among pediatric endocrinologists, data scientists, and public health stakeholders.

Abstract Background and Aims Women are underdiagnosed and undertreated for cardiovascular disease (CVD). Automatic quantification of breast arterial calcification (BAC) on screening mammography can identify women at risk for CVD. This study aimed to determine whether artificial intelligence–based automatic quantification of BAC from screening mammograms predicts CVD and mortality beyond PREVENT scores in a large, racially diverse, multi-institutional population. Methods This retrospective cohort study included 123 762 women from two healthcare systems who had screening mammograms. Breast arterial calcification was quantified using a transformer-based neural network for segmentation. Breast arterial calcification severity was categorized as zero (0 mm2), mild (>0–10 mm2), moderate (>10–25 mm2), and severe (>25 mm2). Kaplan–Meier analysis, Cox proportional hazards, and Fine–Gray competing event models were used to examine the association between BAC and major adverse cardiovascular events (MACE). Results Breast arterial calcification was detected in 16.1% (internal cohort) and 20.6% (external cohort) of women and provided significant prognostic value incremental to the PREVENT score. In PREVENT adjusted models, a clear dose–response was observed. Compared with zero BAC, mild [internal: hazard ratio (HR) 1.32, 95% confidence interval (CI) 1.10–1.59; external: HR 1.28, 95% CI 1.17–1.39], moderate (internal: HR 1.75, 95% CI 1.23–2.50; external: HR 1.79, 95% CI 1.55–2.06), and severe BAC (internal: HR 3.29, 95% CI 2.15–5.05; external: HR 2.80, 95% CI 2.36–3.32) were all prognostic for any MACE. Each 1 mm2 increase in BAC conferred an additional 2%–3% risk for MACE (P < .001). Conclusions Automatically quantified BAC is an independent predictor of MACE and mortality, adding prognostic value to the PREVENT score. This approach may provide an opportunistic cardiovascular risk assessment during routine mammography screening without additional radiation exposure to guide earlier and more effective preventive care for women.

ABSTRACT Background Sentinel lymph node (SLN) biopsy is a critical staging tool in skin and soft tissue cancers. Although technetium lymphoscintigraphy is the most common adjunct, indocyanine green (ICG) demonstrates a promising alternative in pediatric, adolescent, and young adult (AYA) skin and soft tissue cancers. Methods and Objectives Evaluate the safety and efficacy of ICG in SLN biopsy (SLNB) in diverse pediatric and AYA solid cancers in a multi‐institutional environment. This is a prospective, observational study conducted at 13 member institutions in the Pediatric Surgical Oncology Research Collaborative between 2019 and 2023. Eligible patients underwent SLNB for primary or recurrent solid skin and soft tissue tumors. Peritumoral ICG was administered intraoperatively. Outcomes included SLN detection rates, histopathology of excised specimens, and surgeon‐reported assessment of utility. Safety was assessed through adverse event reporting. Results Forty SLNB procedures yielded 84 specimens: 13 melanoma (32.5%), 12 squamous cell carcinoma (30%), 11 non‐rhabdomyosarcoma soft tissue sarcoma (27.5%), two rhabdomyosarcoma (5%), one Ewing sarcoma (2.5%), and one malignant peripheral nerve sheath tumor (2.5%). Histologic evaluation identified 81 lymph nodes, 75 benign (89.3%) and six malignant (7.1%); three specimens were adipose tissue (3.6%). Of 81 lymph nodes, 76% were ICG‐positive. ICG had a sensitivity of 79.5%, a specificity of 33%, and a positive predictive value of 96%. All malignant nodes were ICG‐avid. There were no adverse reactions to ICG at 30 days. Conclusions ICG is a safe and effective adjunct for SLNB in pediatric and AYA soft tissue and skin malignancies.

The fallopian tubes are critical segments of the female reproductive tract and are essential for transporting gametes and embryos. It creates a conducive environment necessary for successful fertilization, early embryo development, and embryo transport. The cellular composition and function of the fallopian tube are tightly regulated by the sex hormones estradiol and progesterone. Therefore, any pathological/ metabolic condition or exposure to exogenous agents with the potential to alter endocrine levels can have a significant impact on fallopian tube function and health. This review summarizes the effects of medications, infections, pathological conditions, lifestyle choices, and environmental factors that can significantly impact the morphology, histology, cellularity, and functionality of the fallopian tube.