Citations

The Quantitative Imaging Biomarkers Alliance Profile for dynamic susceptibility contrast (DSC) MRI and its longitudinal claims for the precision of a DSC MRI–derived quantitative imaging biomarker to assess the relative cerebral blood volume changes in gliomas are summarized.

In this case series, we present several examples from participants (2 patients and 1 healthy control) of a 12-week pilot feasibility study to create a digital phenotype of depression (unipolar or bipolar) through active and passive data collection from a smartphone and a wearable device combined with routine clinical care for mood disorders. The selected cases represent real clinical examples that highlight the intrinsic challenges that should be expected when conducting similar studies, including appropriate health data privacy protection, clinical standardization, and interindividual differences in levels of engagement and acceptability of active and passive data collection (ie, self-reported, behavioral, cognitive, and physiological data), particularly with patient-generated data in mobile apps, digital proficiency habituation, and consistent use of wearable devices. In the context of the rapidly growing use of digital technologies in psychiatry, anticipating challenges for the integration of personal mobile devices and smartphone mental health apps as aides to track specific aspects of depressive disorders is critical for a clinically meaningful digital transformation of mood disorders care.

Abdominal aortic aneurysm (AAA) is a significant vascular condition characterized by the dilation of the abdominal aorta, presenting a substantial risk of rupture and associated high mortality rates. Current management strategies primarily rely on aneurysm diameter and growth rates to predict rupture risk and determine the timing of surgical intervention. However, this approach has limitations, as ruptures can occur in smaller AAAs below surgical thresholds, and many large AAAs remain stable without intervention. This review highlights the need for more precise and individualized assessment tools that integrate biomechanical parameters such as wall stress, wall strength, and hemodynamic factors. Advancements in imaging modalities like ultrasound elastography, computed tomography (CT) angiography, and magnetic resonance imaging (MRI), combined with artificial intelligence, offer enhanced capabilities to assess biomechanical indices and predict rupture risk more accurately. Incorporating these technologies can lead to personalized medicine approaches, improving decision-making regarding the timing of interventions. Additionally, emerging treatments focusing on targeted delivery of therapeutics to weakened areas of the aortic wall, such as nanoparticle-based drug delivery, stem cell therapy, and gene editing techniques like CRISPR-Cas9, show promise in strengthening the aortic wall and halting aneurysm progression. By validating advanced screening modalities and developing targeted treatments, the future management of AAA aims to reduce unnecessary surgeries, prevent ruptures, and significantly improve patient outcomes.

Objectives: To describe member adherence to a mail-based, health insurer-sponsored gap closure program for colorectal cancer (CRC) screening using multi-target stool DNA (mt-sDNA; Cologuard ® ) tests. Methods: Combined patient data from Exact Sciences Laboratories LLC and data from mass-mailed mt-sDNA orders placed by a large Medicare Advantage Insurance Plan were analyzed (03/01/2023-06/30/2023). Adherence and time to test return were the primary and secondary outcomes, respectively. Their association with patient characteristics was evaluated using multivariable regression. Results: Among the 3201 member-patients included (86.6% aged 65-75 years; 58.7% female), adherence rate was 49.4%, and mean time to test return was 25.5 days. After multivariable adjustment, the odds of test return were significantly higher among 65- to 75-year-olds (odds ratio [OR] = 1.59 relative to 45- to 64-year-olds), those living in small towns (OR = 1.43 relative to metropolitan-located individuals), and with digital outreach via both SMS and email (OR = 4.31 relative to no digital outreach). Time to test return was shorter in 65- to 75-year-olds than in 45- to 64-year-olds and was not associated with other patient characteristics. Conclusions: Mass-mailed mt-sDNA tests for CRC screening were associated with an overall adherence rate of about 50% in this Medicare Advantage population, with higher likelihood of test return among patients receiving digital outreach.

ABSTRACTBackgroundMany vascular anomalies harbor postzygotic somatic variants in GNAQ and GNA11; however, the phenotype of specific G‐protein variants has not been well described. We report the clinical characteristics of 17 patients with a GNA11 R183C variant.MethodsThis case series is derived from a multinational cohort of vascular anomaly patients whose pathogenic mutations were identified using high‐depth next generation sequencing. Data include vascular anomaly features, imaging reports, and extracutaneous manifestations of the GNA11 R183C variant.ResultsWe identified 17 subjects (median age 18 years [range 6–67]) with somatic GNA11 R183C variant. All patients had vascular lesions of the skin that presented as pink‐to‐red in children and deeper red in adults. Most lesions were large, poorly demarcated, and reticulated patches that were often bilaterally distributed. Nevus anemicus was observed in 53% (N = 9) and dermal melanocytosis in 13.3% (N = 2) of individuals. 82% (N = 14) of patients had limb growth discrepancies, and 1 patient had marked thoracic hypoplasia. 47% (N = 8) of patients had facial involvement, and 41% (N = 7) had forehead involvement. One patient experienced seizures due to right hemispheric leptomeningeal angiomatosis consistent with Sturge–Weber syndrome. Other findings included glaucoma (29%, N = 5) and psychomotor delay (29%, N = 5).ConclusionThese findings contribute to our understanding of the clinical spectrum of GNA11 R183C capillary malformations (CMs); patients characteristically present with extensive, bilateral, poorly demarcated, pink‐to‐red CMs associated with nevus anemicus. Glaucoma and growth discrepancies (overgrowth or undergrowth) are common. Leptomeningeal angiomatosis and developmental delay can occur, appearing potentially less prevalent and severe than GNAQ‐associated disease.

Aims: Alterations of mitochondrial bioenergetics and arginine metabolism are universally present and mechanistically linked to pulmonary arterial hypertension (PAH), but there is little knowledge of arginine metabolism and mitochondrial functions across the different pulmonary hypertension (PH) groups. We hypothesize that abnormalities in mitochondrial functions are present across all PH groups and associated with clinical phenotypes. We test the hypothesis in PH patients and healthy controls from the Pulmonary Vascular Disease Phenomics Program cohort, who had comprehensive clinical phenotyping and follow-up for at least 4 years for death or transplant status. Mitochondrial transmembrane potential, superoxide production, and mass were measured by flow cytometry in fresh platelets. Metabolomics analysis was performed on plasma samples. Global arginine bioavailability was calculated as the ratio of arginine/(ornithine+citrulline). Results: Global arginine bioavailability is consistently lower than controls in all PH groups. Although the mitochondrial mass is similar across all PH groups and controls, superoxide production and transmembrane potential vary across groups. Mitochondrial superoxide is higher in group 1 PAH and lowest in group 3 compared with other groups, while transmembrane potential is lower in group 1 PAH than controls or group 3. The alterations in mitochondrial functions of group 1 PAH are associated with changes in fatty acid metabolism. Mitochondrial transmembrane potential in group 1 PAH is associated with transplant-free survival. Conclusion: While alterations in mitochondrial function are found in all PH groups, group 1 PAH has a unique mitochondrial phenotype with greater superoxide and lower transmembrane potential linked to fatty acid metabolism, and clinically to survival. Antioxid. Redox Signal. 42, 361–377.

SummaryThe age‐associated mutational state of clonal haematopoiesis (CH) is linked to multiple adverse health outcomes. As higher risk CH can lead to progressive neoplastic or vascular disease, there is interest in developing clinical trials to mitigate risk associated with CH. Given the high prevalence of CH, data from clinical trials could have broad public health implications for screening and therapy. Thoughtful consideration is needed to design trials that are both clinically relevant and avoid overmedicalization. Here, we summarize clinical studies of CH to date and provide suggestions and guidance on how to approach designing CH‐focused therapeutic clinical trials. These recommendations are derived from discussions among clinical researchers and scientists emanating from the Inaugural Meeting on Somatic Mutations and Predisease in October 2021.

Objective To characterise the changing trends in the pharmacological management of SLE in the USA between 2007 and 2023 as new treatment options emerged. Methods In a retrospective cohort study using data from OptumLabs Data Warehouse, we characterised the annual prevalent (ie, all) and incident (ie, new) use of antimalarials, glucocorticoids and immunosuppressive medications among patients with SLE from 2007 to 2023 and assessed for changing trends over time. Results We identified 19 122 adults with SLE; they were 51.2 (SD 16.1) years of age, 89% were female, 61.3% were White, 18.5% were Black and 13.1% were Hispanic. The proportion of prevalent users of antimalarials has decreased from 79.4% in 2007 to 77.2% in 2023 (p=0.0055), while the proportion of incident users fluctuated between a lowest 5.8% in 2021 and a highest 8.1% in 2008 (p=0.008). The proportion of prevalent users of glucocorticoids increased from 64.6% in 2007 to 66.7% in 2023 (p=0.0132), as did the proportion of incident users (12.4% in 2007 to 21.7% in 2023; p<0.0001). The use of cyclophosphamide (2.0% in 2007 to 0.4% in 2023, p<0.0001) has decreased; the use of mycophenolate mofetil (7.7% in 2007 to 10.3% in 2023, p<0.0001), rituximab (1.4% in 2007 to 2.1% in 2023, p<0.0001) and belimumab (0.8% in 2011 to 6.1% in 2023, p=0.0001) has increased. Conclusions Despite increasing availability of alternative treatment options, patients with SLE in the USA increasingly rely on glucocorticoid-based therapy. Efforts to improve the use of antimalarials and steroid-sparing immunosuppressants are needed.

PURPOSE Breast density is a widely established independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast density (VBD) routinely. However, current available methods extrapolate VBD from two-dimensional (2D) images acquired using DBT and/or depend on the existence of raw DBT data, which is rarely archived by clinical centers because of storage constraints. METHODS We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using previously validated software that uses 3D reconstructed slices and raw 2D DBT data. We developed a deep learning (DL) model that segments dense and fatty breast tissue from background. We then applied this model to estimate %VBD and absolute dense volume (ADV) in cm 3 in a separate case-control sample (180 cases and 654 controls). We created two conditional logistic regression models, relating each model-derived density measurement to likelihood of contralateral breast cancer diagnosis, adjusted for age, BMI, family history, and menopausal status. RESULTS The DL model achieved unweighted and weighted Dice scores of 0.88 (standard deviation [SD] = 0.08) and 0.76 (SD = 0.15), respectively, on the held-out test set, demonstrating good agreement between the model and 3D reference segmentations. There was a significant association between the odds of breast cancer diagnosis and model-derived VBD (odds ratio [OR], 1.41 [95 % CI, 1.13 to 1.77]; P = .002), with an AUC of 0.65 (95% CI, 0.60 to 0.69). ADV was also significantly associated with breast cancer diagnosis (OR, 1.45 [95% CI, 1.22 to 1.73]; P < .001) with an AUC of 0.67 (95% CI, 0.62 to 0.71). CONCLUSION DL-derived density measures derived from 3D reconstructed DBT images are associated with breast cancer diagnosis.