Citations

Abstract Background Radiotherapy treatment planning requires knowledge of a patient's anatomical surface for use in dose calculations, collision checks, or surface‐guided radiation therapy (SGRT). This information is usually obtained from a computed tomography (CT) scan which may encounter field‐of‐view (FOV) limitations or require additional radiation dose beyond the treatment area to capture the full patient habitus. Purpose This study demonstrates an affordable alternative solution to obtain a patient's surface information without CT or room mounted surface‐guidance imaging cameras for the purpose of detecting patient collisions and providing additional skin surface information needed for appropriate depth calculations of clipped FOV scans. Methods Three‐dimensional (3D) surface models of five patients were acquired immediately prior to CT simulation using an iPad Air 2 equipped with a Structure Sensor Pro and Monocle SS application. The 3D surfaces were manually registered to the CT images and nearest distances between CT surface and 3D surface were calculated. Nearest distance calculations were also performed with a 2 mm CT rind structure that excluded select regions not relevant to surface detection. To demonstrate the advantage of having additional scan length for clearance checks, a collision simulated plan was evaluated with a shortened CT scan length versus with additional 3D surface information. Results CT rind to 3D scan surface mean distances for each patient were 1.65 mm, 0.99 mm, −0.93 mm, −0.79 mm, and −1.53 mm with standard deviations of 6.51 mm, 6.71 mm, 3.38 mm, 2.84 mm, and 2.69 mm. Conclusion This study demonstrates the feasibility of an accessible low‐cost 3D surface scanning solution to supplement clipped field‐of‐view CT scans and reduce CT scan lengths by obtaining important patient surface data for improved calculation accuracy, treatment clearance checks, and SGRT.

Abstract High-grade glioma (HGG) continues to have a dismal prognosis owing in part to its heterogeneous and invasive nature both within and between patients. The most aggressive form of high-grade glioma, called glioblastoma, portends a median survival of around 15 months. Like many cancers, high-grade glioma rewires metabolism towards its own benefit, shifting away from the typical reliance of brain tissue on glucose towards other sources such as fatty acids and acetate. Using a cohort of image-localized high-grade glioma biopsies collected from diverse imageable regions with associated transcriptomics (58 patients, 202 biopsies), we are able to assess the spatial transcriptomic landscape of HGG. We have previously shown that the transcriptome of HGG can be characterized into a continuous transition between states, and we have shown that the cellular ecosystem follows a similar pattern, using a combination of trajectory inference and cellular deconvolution. These patterns are strongly associated with the non-enhancing and contrast-enhancing regions of the tumors, which are typically considered for treatment planning and progression assessment. Here, we applied differential expression of hallmark pathways to determine how metabolism factors into this paradigm. As expected, we find overall higher levels of metabolism-associated pathway expression in the contrast enhancing regions compared to the non-enhancing regions. Interestingly, we found metabolic expression differs between the ecologies associated with transcriptional subtypes of high-grade glioma. For example, fatty acid (p=0.003), xenobiotic (p<0.0001) and heme (p<0.0001) metabolism pathways were significantly upregulated for mesenchymal tumor samples, while significantly downregulated for proliferative tumor samples (p=0.02, p<0.0001, p<0.0001, respectively). As we continue to further understand the complex spatial and temporally heterogeneous landscape of these aggressive tumors, it is important to consider the metabolites on which they depend, to better inform prognosis and develop new treatments.

Abstract Diffuse midline glioma (DMG) is a universally fatal pediatric brainstem cancer. Outside of clinical trials, palliative radiotherapy (RT) remains the only approved treatment, with a median overall survival (OS) of <12 months. The brain-penetrant oral therapy dordaviprone (ONC201) has demonstrated early clinical efficacy by activating the overexpressed mitochondrial protease ClpP, inducing mitochondrial dysfunction. Our previous studies identified that dordaviprone triggers compensatory energy production via the PI3K/mTOR pathway to avoid cell death. To overcome this adaptation, we combined dordaviprone with the brain-penetrant pan-PI3K/mTOR inhibitor paxalisib, showing synergistic anti-tumor effects across multiple immunocompromised patient-derived xenograft models. These results led to the international Phase II clinical trial (PNOC022/NCT05009992), where >20% of patients enrolled pre-radiation achieved survival beyond 2 years. However, approximately 20% of patients experienced immune-related toxicities-mucositis, colitis, and skin reactions, likely driven by paxalisib’s pan-PI3K inhibition, as PIK3CG (p110γ) and PIK3CD (p110δ) are enriched in hematopoietic cells. In contrast, PIK3CA (p110α) is a known genetic dependency in DMG. We hypothesized that the brain-penetrant, p110α-selective inhibitor GCT-007 could maintain therapeutic efficacy while reducing immune toxicity. DMG patient-derived cell lines showed comparable sensitivity to paxalisib and GCT-007 (mean IC50: 0.659 μM vs. 0.775 μM, respectively). Unbiased proteomic profiling in two DMG lines treated with GCT-007 identified robust downregulation of PI3K/AKT/mTOR signaling, confirmed via immunoblotting. Pathway enrichment further showed upregulation of oxidative phosphorylation, reinforcing the rationale for synergistic combination with dordaviprone. In aggressive immunocompetent syngeneic models, GCT-007 significantly extended overall survival (median 53 vs. 40 days, p=0.0001). When combined with dordaviprone, enzastaurin, or immune checkpoint inhibitors (ICI), GCT-007 increased survival in immune-competent DMG models by an average of 53% to 77% compared to vehicle (p=0.001), with 25% of mice in the GCT-007 + ICI cohort achieving long-term survival. Ongoing spatial profiling of the tumor immune microenvironment and organ-toxicity screening is underway to support translation.

Abstract High-grade gliomas (HGGs) are aggressive, infiltrative brain tumors with poor survival outcomes and limited therapeutic options. Their spatial and molecular heterogeneity necessitates large, well-curated datasets integrating imaging, clinical, and genomic information to enable precision medicine and drive novel treatment development. Using the Medtronic StealthStation neuronavigation system, we collected over 1,000 spatially localized intraoperative biopsy samples from more than 250 patients undergoing resection for glioma at Mayo Clinic and partnering sites. Each biopsy site was recorded with 3D coordinates, labeled in real time, flash-frozen, and annotated with metadata including collection time, anatomical location, and surgical plan. Samples were processed and entered into a secure database along with the corresponding sampling coordinates, frozen pathology, whole-exome and RNA sequencing data, 5-ALA fluorescence status, patient demographics, and T1, T1Gd, T2, and T2-FLAIR MRI. This multimodal dataset supports radiogenomic research by enabling precise mapping of imaging features to molecular characteristics. A subset of this data, including 268 biopsies from 52 patients (25 male, 27 female) with reported intraoperative 5-ALA fluorescence, was used to develop a radiomics model predicting locoregional patterns of 5-ALA positivity based on preoperative MRI. Image features were extracted from the biopsy sample coordinates across multiple MRI sequences and paired with corresponding 5-ALA fluorescence status to train the model for regional fluorescence prediction. The final model achieved 83% accuracy on the training set and 86% on the validation set using a 70-15-15 data split; this included 208 samples for training and 42 for validation, stratified by patient to ensure no overlap of samples from the same individual across sets. These findings demonstrate the feasibility of predicting 5-ALA fluorescence using radiomic features from standard preoperative MRI, offering a promising noninvasive strategy for improving intraoperative decision-making and enabling more precise, personalized resections in patients with high-grade gliomas.

Background: Adults with congenital heart disease (CHD) face ongoing physical, emotional, and psychosocial challenges that impact long-term outcomes. Research is limited on how their health topic interests vary by levels of empowerment. The 15-item Gothenburg Empowerment Scale (GES) assesses CHD patient empowerment across five domains. Objective: Examine the association between patient empowerment levels and patient-prioritized health education topics among adults with CHD. Methods: This cross-sectional study included adults (≥18) with self-reported CHD enrolled in the Empower My Congenital Heart digital study. Participants completed the GES survey and responded to open-ended questions regarding information of interest to them in managing their healthcare. GES scores were divided into tertiles, and responses were grouped into patient-prioritized topics. Descriptive analysis examined associations between empowerment levels and topic preferences. Results: Of 292 eligible patients, mean age was 45.6 ± 14.7 years, 91.4% were Caucasian, and 66.4% were female. The median (25th, 75th) GES score was 62 (57, 68). The most frequently observed patient prioritized topic was CHD health knowledge (73%), followed by interest in building CHD community (52.7%), lifestyle management (23.6%), health care navigation (7.2%), research and representation (5.1%). Participants in the lower and middle GES tertiles more frequently expressed interest in foundational sub-topics such as understanding CHD and surgical history, finding ACHD specialists, exercise and nutrition. In contrast, participants in the highest GES tertile prioritized sub-topics related to aging with CHD, managing menopause, CHD research and legislative activities. Peer support was a common topic across all groups (Figure 1). Patient quotes were stratified by tertile and patient prioritized health topics and subtopics as summarized in table 1. Conclusion: Adults with CHD prioritized varied health education topics depending on their baseline empowerment levels. Those with lower GES scores prioritized foundational information and guidance, while those with higher scores prioritized community-oriented and research-related topics. These findings could help tailor CHD patient-centered education strategies based on individual empowerment profiles.

Background: Journal editors influence the visibility and direction of scientific research and should have adequate gender and geographic representation. Research Question: Are there disparities in gender and institutional country affiliation among editors of highly cited cardiology and cardiovascular disease journals? Methods: In May 2025, we used Scimago Journal Rankings to identify the 50 top-cited cardiology and cardiovascular disease journals worldwide from 2022 to 2024. Due to the large volume of members, general editorial board listings without defined roles were excluded. Editors’ genders and country of institutional affiliation were extracted independently and in duplicate by eight sub-investigators. An additional sub-investigator resolved any discrepancies. Gender was determined using institutional profiles and publicly available pronouns on academic or professional platforms. Country affiliation was based on the editor’s primary institution and categorized by World Bank income classification 2025, which divides countries into high-income (HIC), upper-middle income (UMIC), lower-middle income (LMIC), and low-income countries (LIC). Key journal characteristics, such as country, impact factor, and article processing charges, were also extracted in duplicate. Results: All 50 top-cited cardiology and cardiovascular disease journals identified were based in HICs. A total of 1,762 editors were included. Most editorial positions were held by men (67%), with women accounting for 28%. One editor was identified as non-binary, and the gender of 91 editors (5%) could not be determined based on publicly available information (Table 1). Pronouns were identifiable for all EIC (n=52), out of which 87% were men (n=45) and 13% were women (n=7). Ninety-five percent of editors were affiliated with institutions based in HIC, while only 5% were based in UMIC (n=71), LMIC (n=16), or LIC (n=5). The most represented countries were the US (41%), Italy (8%), and the UK (7%) (Figure 2). All EICs (100%) were affiliated with institutions based in HICs, mainly the US (52%) and the UK (10%) (Figure 3). Conclusion: Editors of top-cited cardiology journals are predominantly men affiliated with HICs. Diverse editorial leadership in academic cardiology journals is needed to reflect global perspectives in research.

Introduction: Apolipoprotein B (ApoB) and coronary artery calcium score (CAC) are well-established risk factors for coronary heart disease (CHD). However, the interaction between these risk factors on CHD risk has not been well-studied. We investigated the association between ApoB levels and CAC with CHD risk. Methods: We analyzed 4,649 participants from the Multiethnic Study of Atherosclerosis cohort (median follow-up 13.9 years) without baseline CHD or statin use. High ApoB was defined as ≥120 mg/dL. Participants were divided into 6 groups; group 1: CAC = 0 with normal ApoB, group 2: CAC = 0 with high ApoB, group 3: CAC 1-99 with normal ApoB, group 4: CAC 1-99 with high ApoB, group 5: CAC ≥100 with normal ApoB, group 6: CAC ≥100 with high ApoB. CHD was defined as myocardial infarction, resuscitated cardiac arrest, or CHD death. Survival analysis using Kaplan-Meier and multivariable Cox proportional hazard models were performed to assess the relationship between ApoB, CAC, and time to first CHD event. Results: In an adjusted model, high ApoB, CAC (1-99), and CAC (≥100) were independently associated with CHD (HR: 1.48; 95% CI: 1.04, 2.11; HR: 2.54; 95% CI: 1.78, 3.64; and HR: 4.41; 95% CI: 3.08, 6.31, respectively). Compared to group 1 (CAC 0 with normal ApoB), CAC 0 and high ApoB (group 2) was not associated with increased risk of CHD (HR: 1.15; 95% CI: 0.59, 2.23). However, a statistically significant greater risk of CHD was observed in those with CAC 1-99 and normal ApoB (group 3) (HR: 2.12; 95% CI: 1.37, 3.28), CAC 1-99 and high ApoB (group 4) (HR: 4.12; 95% CI: 2.42, 7.00), CAC ≥100 and normal ApoB (group 5) (HR: 4.20; 95% CI: 2.78, 6.34), CAC ≥100 and high ApoB (group 6) (HR: 5.72; 95% CI: 3.40, 9.63). Conclusions: In this analysis, ApoB and CAC are independently associated with CHD risk. Individuals with high ApoB and CAC ≥100 had the highest risk of CHD. In contrast, individuals with CAC = 0 and high ApoB had no significant increase in CHD risk compared to individuals with normal ApoB levels. These findings suggest that ApoB and CAC may be complementary tools for CHD risk stratification in the context of primary prevention.

Background: Digital health offers a potential solution to support adults with congenital heart disease (CHD), filling the critical gap to help maintain recommended lifelong care with adult CHD specialists. However, its design and implementation require a rigorous scientific approach to make it scalable and usable for the target population. Objective: To pilot test the acceptability and feasibility of a digital health intervention to support lifelong healthcare for adults with CHD. Methods: Using a community-based participatory research and a behavioral theory-based approach, we developed and piloted a digital tool, Empower My Congenital Heart (EmpowerMyCH), within the web—and mobile-based Eureka Digital Research platform at UCSF. Intervention components within EmpowerMyCH include exhibits (expert and peer-developed learning modules on CHD-related topics such as finding specialists or navigating visits, tests, procedures, etc.), peer support, and a digital medical passport (Figure 1). Participants receive an exhibit with study measure surveys every two months, with a two-month completion window. Participant satisfaction with the digital tool is measured at six months using the Client Satisfaction Questionnaire-8 (CSQ-8), a validated survey with scores ranging from 8 to 32; higher scores indicate higher satisfaction with the digital tool. Results: Of the 519 participants recruited, 495 were eligible adults with CHD, 445 consented, and 6 withdrew. The median age was 43 (ranging from 20 to 85) years, and 30.1% were males. Survey completion rate was the highest at 88.7% during the first two months after enrollment and 53.5% at 8 months. Of the five exhibits delivered so far, over 87% of participants rated the exhibits to be helpful (Figure 2). Participants found the exhibits readable, easily accessible, motivational, useful, and educational (Figure 3). The median (25th, 75th) CSQ-8 score was 21 (18, 25) among 144 participants who completed the survey. Conclusions: EmpowerMyCH, the digital health tool, appears to be acceptable to most adults with CHD to support and educate them in navigating their healthcare. The tool and its contents are accessible, user-friendly, and responsive to the needs of the CHD community, resulting in high satisfaction rates. The feasibility rates and satisfaction scores are similar to or higher for EmpowerMyCH than those of prior digital health studies. Future hybrid intervention trials can demonstrate EmpowerMyCH‘s effectiveness.

Background: Lipoprotein(a) [Lp(a)] and metabolic syndrome (MetS) are well-established risk factors for cardiovascular disease. Recent evidence suggests that high Lp(a) levels may increase the risk of coronary heart disease (CHD) in patients with diabetes, raising the question of whether similar interactions exist between Lp(a) and metabolic syndrome. We aimed to evaluate the joint association of Lp(a) and MetS with incident CHD risk in a large, multi-ethnic, prospective cohort. Methods: We analyzed 6,664 participants from the MESA (Multiethnic Study of Atherosclerosis) cohort (median follow-up 14.0 years) without baseline CHD. MetS was defined as ≥3 of the following criteria: waist circumference ≥102 cm (men), or ≥88 cm (women), triglycerides ≥150 mg/dL or use of a fibrate medication, HDL-C <40 (men) or <50 (women) or use of a fibrate medication, SBP ≥130 mm Hg and/or DBP ≥85 mm Hg or use of antihypertensive medication, fasting glucose ≥100 mg/dL or use of antidiabetic medication (4). Elevated Lp(a) was defined as a level ≥50 mg/dL. CHD was defined as myocardial infarction, resuscitated cardiac arrest, or CHD death. Participants were divided into four groups: group 1: Normal Lp(a) without MetS, group 2: elevated Lp(a) without MetS, group 3: normal Lp(a) with MetS, group 4: elevated Lp(a) with MetS. Survival analysis using Kaplan-Meier and multivariable Cox proportional hazard models were performed to assess the relationship between Lp(a), MetS, and time to CHD. Results: In an adjusted model, log [Lp(a)] and MetS were both independently associated with CHD (HR: 1.14; 95% CI: 1.03, 1.25) and (HR: 1.75; 95% CI: 1.35, 2.27). Compared to the reference group (normal Lp(a) without MetS), those with elevated Lp(a) without MetS (group 2) did not have increased risk of CHD (HR: 1.30; 95% CI: 0.94, 1.80). However, those with normal Lp(a) with MetS (group 3) had greater risk of CHD (HR: 1.56; 95% CI: 1.18, 2.05). The highest risk for CHD were in those with elevated Lp(a) with MetS (group 4) (HR: 2.37; 95% CI: 1.66, 3.37). Conclusions: In this analysis. elevated Lp(a) and MetS independently increase CHD risk. MetS alone significantly increases risk, whereas elevated Lp(a) without MetS does not demonstrate a significant effect. However, their combination confers the highest risk, suggesting a synergistic interaction. These results emphasize the value of assessing Lp(a) in individuals with MetS to improve cardiovascular risk stratification and guide targeted prevention.

Background: Chronic kidney disease (CKD) has been linked to elevated inflammatory biomarkers, yet few studies have evaluated these associations using iothalamate-based measures of kidney function, highlighting the need for further research. Research question: Is CKD associated with elevated inflammatory markers when defined by measured glomerular filtration rate (mGFR) and urinary albumin-to-creatinine ratio (UACR)? Methods: Participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort were included if they had data available for at least one inflammatory marker at visit 2. 17 inflammatory markers were assessed, including C-reactive protein (CRP), interleukin-6 (IL-6), IL-18, tumor necrosis factor receptors 1 and 2 (TNFR1, TNFR2), serum amyloid A, intercellular and vascular adhesion molecules (ICAM, VCAM), E-selectin, P-selectin, monocyte chemoattractant protein (MCP), myeloperoxidase (MPO), receptor for advanced glycation end products (RAGE), matrix metalloproteinases 2 and 9 (MMP-2, MMP-9), and tissue inhibitors of metalloproteinases 1 and 2 (TIMP-1, TIMP-2). Kindey function was assessed using the urinary clearance of iothalamate. CKD was defined as mGFR < 60 mL/min/1.73 m 2 or UACR ≥ 30 mg/g. To further assess whether associations persisted without albuminuria, we also defined CKD solely by mGFR < 60 mL/min/1.73 m 2 . Generalized estimating equations (GEE) were used to assess associations between CKD status and inflammatory markers, accounting for familial clustering. Exponentiated beta coefficients from GEE models were used to present geometric mean (GM) ratios of each biomarker by CKD status, adjusted for demographics, lifestyle factors, cardiovascular risk factors, and medication use. Results: Among 1,010 participants (mean age 61 ± 10 years; 67% women; 48% Black adults), 207 were classified as having CKD. After adjusting for potential confounders, individuals with CKD had significantly higher levels of hsCRP, VCAM, TNFR1, and TNFR2 compared to those without CKD (GM ratios > 1; p < 0.05), while the remaining inflammatory markers showed no significant differences ( Figure 1 ). Importantly, these elevations remained significant when CKD was defined by mGFR alone ( Figure 2 ). Conclusion: Our findings suggest that CKD, defined by mGFR, is associated with specific inflammatory biomarkers, underscoring the need for mechanistic studies to investigate these associations.