Citations

Summary: Peripheral Artery Disease (PAD) is a significant global health concern, leading to morbidity through progressive stenosis and eventually occlusion of the lower extremity arterial vasculature. Advanced imaging modalities play a major role in diagnosing PAD, in planning endovascular as well as surgical interventions, and in monitoring post-treatment outcomes. This review highlights the current major imaging techniques, including duplex ultrasound, computed tomography angiography (CTA) and magnetic resonance angiography (MRA). It provides insights into their applications, advantages, limitations and the importance of individualized imaging strategies for optimizing patient outcomes.

Abstract Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs), pancreatic cysts requiring surgery, from low-risk lesions remains a clinical challenge, often resulting in unnecessary procedures due to limited specificity of current methods. While radiomics and deep learning (DL) have been explored for pancreatic cancer, cyst-level malignancy risk stratification of IPMNs remains untapped. We conducted a multi-institutional study (seven centers, 359 T2W MRI images) to assess the feasibility of AI for predicting IPMN dysplasia grade using cyst-level image features. We developed and compared 2D and 3D radiomics-only, deep learning (DL)-only, and radiomics-DL fusion models, using expert radiologist scoring as a baseline reference. Model performance was evaluated using held-out test data. The radiomics-DL fusion model showed the highest discriminatory ability on the test set (AUC 0.692), outperforming the radiomics-only model (AUC 0.665). Expert accuracy varied widely (37.4%-66.7%). The fusion model integrating deep learning and radiomics features from routine T2W MRI (AUC: 0.692) demonstrates potential for objective, cyst-level risk stratification of IPMNs in a multi-center cohort, outperforming both radiomics-only models and expert radiologists. While performance requires improvement for standalone clinical use, this approach offers a scalable, non-invasive method to potentially improve diagnostic accuracy and reduce unnecessary surgical interventions.

Abstract Introduction: Lung cancer is the most frequently diagnosed cancer and leading cause of cancer death worldwide. While adenocarcinoma is the most common subtype of lung cancer, invasive mucinous adenocarcinoma (IMA) only represents an estimated 2-5% of lung adenocarcinomas. IMA has an incidence of just 0.2% among primary lung cancer patients. This rare form of lung cancer provides a significant diagnostic challenge due to its varied clinical and radiological manifestations, often exhibiting features overlapping with pneumonia. We present a case of IMA with radiographic findings of numerous cavitary nodules, an uncommon morphology reported in 3.5% of cases of IMA, originally thought to represent atypical multifocal pneumonia. Description of Case: A 76-year-old man with a history of coronary artery disease status post percutaneous coronary intervention on dual antiplatelet therapy; hypertension; chronic kidney disease; and 40 pack-year smoking history presented to primary care with 6 weeks of worsening cough productive of clear sputum and shortness of breath. He denied a history of fevers, night sweats, unintentional weight loss, recent travel, or sick contacts. A chest x-ray revealed extensive nodular parenchymal opacities in the lower lobes bilaterally concerning for multifocal pneumonia. Subsequent CT chest showed numerous bilateral, poorly-defined nodules with irregular margins and cavitary lesions. He was admitted for acute hypoxic respiratory failure in the setting of presumed atypical multifocal pneumonia. He completed a course of vancomycin and piperacillin/tazobactam. Notably, bronchoscopy with bronchoalveolar lavage and cytology were negative for infection and malignancy, respectively. Additional noninvasive infectious and inflammatory workup was negative and he was ultimately discharged. He was then readmitted to the ICU for respiratory failure where he eventually underwent transbronchial biopsy. Tissue biopsy revealed moderately-differentiated adenocarcinoma with mucinous features. PD-L1 staining was 0%. Genetic testing revealed two separate TP53 mutations, a KRAS G12D mutation, and SMAD4 alteration. Chemotherapy with carboplatin and pemetrexed was initiated inpatient. He had objective and subjective improvement and was ultimately discharged to continue treatment in the outpatient setting. Discussion: This case represents an uncommon presentation of an already rare form of lung cancer underscoring the diagnostic difficulty in the setting of overlapping clinical and radiological manifestations. Clinicians must consider malignancy when a patient with presumed pneumonia is not improving despite antibiotics. Bronchoscopy with both BAL and transbronchial biopsy is often required to make the diagnosis and exclude other etiologies. Early consideration of alternative diagnoses can improve patient outcomes and help avoid progressive respiratory failure.

Objective To pool data from prospective clinical trials investigating combined stereotactic ablative radiotherapy (SABR) with immune checkpoint inhibitors (ICI) in patients with metastatic cancers. Methods and analysis PubMed, Scopus and EMBASE were queried for full-length articles of prospective clinical trials involving patients with metastatic solid tumours. Random-effects meta-analysis was performed with the Knapp-Hartung method. Multilevel regression analyses with primary cancers used as random effects and pairwise comparisons with two-tailed test adjusted with Benjamini-Hochberg method were performed. Regression coefficients (β) were calculated to assess the correlation between dose and outcomes. Results We identified 30 trials and 35 individual treatment arms with a total of 951 patients with at least one outcome metric reported. Large heterogeneity was identified for all outcomes measured (I 2 range: 75%–86%). The pooled rate of grade 3+ treatment-related adverse events was 18% (95% CI 11% to 24%). The progression-free survival (PFS) and overall survival (OS) at 6 months were 27% (95% CI 19% to 36%) and 67% (95% CI 59% to 76%), respectively. On multilevel regression, we identified improvement in 6-month PFS (β=0.6, p=0.003) and OS (β=1.6, p=0.04) with increasing BED10Gy doses. Combined-target ICI correlated with better 6-month OS when compared with αPD-1/PD-L1 alone. Conclusion We report a safety profile of combined ICI with SABR in patients with metastatic cancer that is comparable to that of ICI alone. We identified higher doses of radiotherapy and dual-target ICI to be associated with better OS at 6 months. Large heterogeneity and the lack of a control group limit the interpretation of our findings.

Abstract Introduction: Glioblastoma (GBM) tumors contain distinct cell lineages, including treatment-sensitive cells (TSCs) relying on aerobic glycolysis and treatment-resistant persister cells (TRPCs) dependent on lipid metabolism. Our systems biology-based, spatial multi-omics and multi-targeted approach decodes a critical node in GBM progression, lipid acquisition in TRPCs, and validates this through a retrospective analysis of statin-treated patients, offering clinical insights into the potential benefits of targeting lipid metabolism in high TRPC signature GBM patients. Methods: We performed spatial transcriptomics and proteomics, combined with 3D rendering of the tumor microenvironment (TME) and geospatially resolved single-cell neighborhood analysis of IHC-stained GBM tissues using our custom-developed SNAQ algorithm to investigate the immune microenvironment and lipid distribution specific to TSCs and TRPCs. To characterize lipid dynamics, we employed flow cytometry, time-lapse imaging, and holotomography to track lipid transfer from Tumor-Associated Myeloid Cells (TAMCs) to TRPCs. A critical node for GBM progression was identified through in vivo survival and tumor progression studies that assessed effects of genetic targeting of CCR2 and pharmacological targeting of CSF1R and FABP3. Retrospective analysis was conducted on 4,085 GBM patients to evaluate the effect of statin treatment on GBM outcomes based on their TRPC signature. Results: Our study establishes the skewed accumulation of TAMCs within the TRPC microenvironment through upregulation of the CCL2/7-CCR2 and CSF1-CSF1R pathways. TAMCs actively transfer lipids to TRPCs to fulfill their metabolic demands. Targeting elements responsible for lipid incorporation in TRPCs, such as CCR2, CSF1R, and FABP3 in vivo, resulted in tumor immune microenvironment remodeling, significant tumor growth reduction, and improved survival. This reinforces the critical role of metabolic communications via lipid trafficking in TRPCs as an essential node in GBM progression. Our retrospective study showed that GBM patients with elevated TRPC signatures, typically associated with shorter survival, had no significant survival differences when treated with lipid-lowering statins. This suggests statins may disrupt lipid metabolism in TRPCs, reducing TAMC lipid support and improving patient outcomes. Conclusion: Our study highlights lipid trafficking in TRPCs as a key mechanism in GBM progression, suggesting that targeting TAMC recruitment and lipid acquisition in TRPCs may offer a promising therapy. Additionally, our retrospective analysis highlights the potential of transcriptomic profiling for patient stratification based on TRPC signature expression levels, enabling the identification of patients to benefit from lipid metabolism-targeted therapies. Citation Format: Avirup Chakraborty, Changlin Yang, Diana Feier, Aryeh Silver, Nyla T. Searl, Miruna Anica, Avinash Pittu, Illena West, Olusegun O. Sobanjo, Ethan D. Hodge, Mia K. Engelbart, Srabasti Sengupta, Nagheme Thomas, Christina Von Roemeling, Maryam Rahman, Matthew Sarkisian, Jianping Huang, Jeffrey Harrison, Duane A. Mitchell, Loic P. Deleyrolle. Disrupting lipid metabolism in GBM: A systems biology approach to targeting treatment-resistant persister cells and tumor associated myeloid cell-mediated support [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB082.

Abstract Breast cancer risk assessment tools are widely used in clinical practice to guide decisions regarding screening timing and modality, lifestyle interventions, genetic testing, preventive therapy, and risk-reducing surgery. Although a number of tools designed for the general population are used in practice, they face a series of challenges including: (i) modest discriminatory ability due to lack of a unified model that flexibly incorporates a comprehensive set of risk factors; (ii) inability to produce subtype-specific risk estimates, relevant for tailoring screening and/or preventive strategies (e.g. prophylactic endocrine therapy that is effective only for hormone receptor positive tumors); (iii) lack of data from diverse populations to build models that work well for all women; and, (iv) scarcity of opportunities for comparative validation of different models. The Breast Cancer Risk Prediction Project (BCRPP), a collaboration currently including 20 prospective cohorts from the National Cancer Institute’s Cohort Consortium, is addressing these challenges by harmonizing, sharing, and analyzing data on over 1.8 million women, over 115, 000 of whom have developed breast cancer. The BCRPP is developing a comprehensive tool that will predict breast cancer risk, overall and by subtypes, across major racial and ethnic groups in the United States. This tool incorporates known and emerging risk factors (e.g. reproductive history, anthropometry, smoking, alcohol intake, medication use, mammography, family history, and measured genotypes). In parallel to model building and validation efforts, BCRPP investigators are developing privacy-preserving web and mobile interfaces to deliver the risk tools to patients and clinicians. Here we present descriptive data on participating cohorts (e.g. dates of enrollment, ages at enrollment, length of follow up, numbers of cases by subtype), summarize missing data patterns and our approach to model development and validation that accounts for heterogeneity in missingness patterns across cohorts, and describe data governance procedures and data sharing infrastructure (including pooled and federated analyses, to account for policy limitations on sharing individual data). Descriptive information and procedures for requesting and accessing data are available via the BCRPP data platform (https://epidataplatforms.cancer.gov/bcrpp/). Although originally assembled for risk model development, these data on a large and diverse sample of women with extensive harmonized risk factors and covariates can be a resource to address other outstanding questions in breast cancer epidemiology across time, the lifecourse, and diverse populations. Citation Format: Peter Kraft, Laura Beane-Freeman, Julie Palmer, Ellen O'Meara, Jeanine Genkinger, James Lacey, Thomas Rohan, Lauren Teras, Marian L. Neuhouser, Kala Visvanathan, Celine Vachon, Roger Milne, Christopher Haiman, Yu Chen, Heather Eliassen, Cari Kitahara, Katie O'Brien, Emily White, Garnet Anderson, I-Min Lee, Archie Campbell, Renee Fortner, Ylva Lagerros, Sven Sandin, Mia Gaudet, Montserrat Garcia-Closas, Nilanjan Chatterjee. The Breast Cancer Risk Prediction Project: a resource of 1.8 million women with diverse backgrounds from 20 prospective cohorts to improve breast cancer risk prediction and advance breast cancer epidemiology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3583.

Abstract Background: Although colorectal cancer survival rates are improving, the risk of incident type 2 diabetes mellitus (T2D) among Asian, Native Hawaiian, and Pacific Islander (ANHPI) ethnic groups is poorly understood. This study aims to identify high-risk groups and quantify the risk across different periods. Methods: Using the SEER–Medicare database, colorectal cancer survivors who were ANHPI were matched to non-Hispanic White (NHW) survivors at a ratio of 1:3. Multivariable Cox regression models computed HRs and 95% confidence intervals (CI) for incident T2D. Results: The study included 6,463 NHW and 2,901 ANHPI colorectal cancer survivors diagnosed between 2000 and 2017. Among them, 715 NHW and 484 ANHPI developed T2D during 39,097 and 10,769 person-years of follow-up, respectively. ANHPI colorectal cancer survivors had an elevated T2D risk compared with NHW across all follow-up periods (HRoverall: 1.84, 95% CI, 1.51–2.25; HR1–5 years: 1.83, 95% CI, 1.45–2.30). Southeast and East Asians demonstrated the highest T2D risks. Colon cancer was linked to early postdiagnosis T2D risk, whereas rectal cancer was associated with later risk. No significant association was observed for Native Hawaiians and Pacific Islanders. Conclusions: ANHPI colorectal cancer survivors face a greater risk of T2D, particularly among Southeast and East Asians. These findings highlight the need for evidence-based survivorship strategies to prevent T2D and reduce ethnic disparities. Impact: This is the first study to examine T2D risk among ANHPI colorectal cancer survivors, providing critical insights to inform tailored diabetes prevention and survivorship care.

ABSTRACTBackgroundWe investigated mental health diagnoses (MHDs) in mycosis fungoides (MF) patients compared to the general population, evaluated risk factors, and studied survival outcomes in a large population database.MethodsMF patients from the Utah Cancer Registry diagnosed from 2001 to 2014 were matched with up to five general population individuals from the Utah Population Database. MHDs were retrospectively tracked in both populations (median follow‐up = 6.67 years). Risk factors for new MHDs among MF patients were studied using the Cox proportional hazards model. Overall survival (OS) and disease‐specific survival (DSS) were assessed using Kaplan–Meier analysis.ResultsThe incidence of anxiety disorders (HR = 1.99, 95% CI [1.16, 3.42]) and delirium/dementia disorders (HR = 2.43, 95% CI [1.05, 5.63]) was higher among MF patients than the matched general population. Among MF patients, Charlson Comorbidity Index (CCI) ≥ 2 and BMI < 18 kg/m2 were risk factors for new anxiety disorders. Radiation therapy, CCI ≥ 2, and female gender were risk factors for new delirium/dementia disorders. The 15‐year OS was worse for MF patients with versus without an MHD (36% vs. 81%, HR 2.62, 95%CI [1.24, 5.65]). The 15‐year DSS also worsened for MF patients with versus without an MHD (63% vs. 97%, HR 6.55, 95%CI [1.64, 26.2]).ConclusionsMF patients developed anxiety and delirium/dementia disorders at rates above the general population, and MHDs correlated with worse DSS and OS. Careful mental health monitoring may be an actionable step towards improving health‐related quality of life in this population.

Abstract Objectives To explore patients’ use of patient portals to access lab test results, their comprehension of lab test data, and factors associated with these. Materials and Methods An online survey was administered to 276 adults 18+ years. Multivariate logistic regression was used to determine factors associated with patient portal use to view lab test results and lab test comprehension. Results The sample was predominantly White (72.5%), female (55.4%), with mean age 50.7 ± 15.5 years. Overall, participants had low numeracy (10.79 ± 2.71) and eHealth literacy skills (23.91 ± 5.29), and moderate lab test comprehension scores (18 ± 2.3). White participants with greater eHealth literacy were more likely to access lab test results via patient portals, whereas those with a college education were less likely to do so (χ2 [3]=31.23, P &lt; .001). The regression showed that older age, fewer chronic conditions, and use of patient portals were significantly related to higher lab test comprehension scores (F [22, 250]=8.73, P &lt;.001). Older adults performed better on comprehension tests but reported having difficulty understanding lab tests, expressing a preference for their doctors to explain them. Discussion The findings shed light on the experiences and needs of different user groups that must be addressed to enhance their ability to effectively use patient portals for obtaining lab test results. Conclusion More research is needed to determine patient barriers to comprehending lab test results online and to develop tailored strategies to improve patients’ self-efficacy to meaningfully use medical information in patient portals.