PURPOSE: Extranodal natural killer/T-cell lymphoma (ENKTL) is an aggressive malignancy and usually involves the nasal cavity. Although the Lugano criteria is widely used for lymphoma response assessment, its applicability in ENKTL is limited by reliance on a single pre-treatment reference and a positive reference threshold with high false-positive rate. This study proposed and evaluated the ability of a novel evaluation system derived from the Lugano criteria to predict ENKTL treatment response. METHODS: A total of 259 patients underwent baseline, interim, and end-of-treatment [18F]FDG PET/CT. Treatment responses were evaluated on PET/CT using the Lugano, IPET (with interim PET/CT as the reference time point), NPU (with nasal mucosal uptake as the positive reference), and IPN (with integration of interim PET/CT as the reference time point and nasal mucosal uptake as the positive reference) criteria. Endpoints were progression-free survival (PFS) and overall survival (OS). Cox regression analysis was used to assess prognostic factors, and model discrimination was quantified using Harrell's concordance index (C-index). RESULTS: The three novel systems reclassified patients initially evaluated by Lugano. Reclassification from partial response or stable disease to a worse response category by IPET and IPN correlated with worse outcomes, whereas reclassification to complete response by NPU or IPN predicted improved outcomes. The IPN achieved the highest C-index for prediction of PFS and OS and remained independently associated with survival after multivariable adjustment. CONCLUSION: The IPN, IPET, and NPU criteria were superior to the Lugano classification for prognostic stratification. The IPN criteria had the best prediction performance and allowed early identification of high-risk patients.

Biomarker discovery in biomedicine is often cast as feature selection, yet most methods overlook gene co-localization within regulatory interaction networks, yielding isolated biomarkers with limited biological interpretability and clinical translatability. Here, we propose CNet-Cox, a disease-agnostic, Connected Network-regularized Cox proportional hazards framework that incorporates prior network connectivity into sparse feature selection to identify connected prognostic module. Applied to breast cancer, CNet-Cox revealed the network structure of 68 prognostic biomarkers associated with survival on discovery dataset (TCGA, n = 1080) and achieved a concordance index of 0.913 on internal test dataset, outperforming conventional regularized Cox methods. From these network biomarkers, we derived a six-gene prognostic risk score (PRS) and validated its robustness across seven independent bulk transcriptomic datasets (GEO; n = 1602) and a spatial transcriptomics dataset (Visium; 4992 spots). The PRS consistently improved risk stratification (log-rank p < 0.05) and produced concordant predictions with MammaPrint in spatial prognostics (Pearson r = 0.993). Although evaluated in breast cancer, CNet-Cox is readily extensible to other diseases, molecular interaction networks and time-to-event endpoints, providing a generalizable tool for digital pathology and precision oncology. Overall, our comprehensive downstream analyses highlight that CNet-Cox offers a novel network-aware survival model for systematically discovering connected biomarkers and delivering scalable, precise and interpretable risk prediction.

OBJECTIVES: Psychiatric diagnosis and fractal studies are complex processes that extend beyond clinical evaluation and require careful methodological considerations in neuroimaging. Over the years, fractals have helped reduce these complexities in research, but they still cannot grant clinical diagnoses. Thus, the main objective was a systematic review exploring the potential applications of fractal analysis in characterizing psychiatric conditions through neuroimaging techniques-including both functional and structural MRI. MATERIALS AND METHODS: A systematic literature review was conducted on PubMed, identifying thirty-nine original studies that met the inclusion criteria. Areas showing statistical significance (p < 0.05) were reported. These studies were categorized according to DSM-V classification and examined for the description of psychiatric conditions through the fractal analysis. RESULTS: The review primarily focuses on young adults with psychiatric conditions compared to control groups. Schizophrenia and Autism Spectrum Disorder are major areas of investigation, and fractal dimension (FD) is the primary analysis method used to reflect brain patterns. Studies that calculated whole-brain FD may have underestimated local abnormalities due to the inclusion of a high percentage of tissue, potentially resulting in overlooked findings. Notably, abnormalities in the frontal cortex represent a common neurobiological feature across several psychiatric conditions. CONCLUSIONS: The findings from this systematic review shed light on the use of fractal analysis to quantify complex brain patterns in both psychiatric patients and healthy individuals. However, it is essential to recognize the need for further research to elucidate a fractal analysis protocol that allows for optimal extraction of psychiatric insights. KEY POINTS: Question Fractal analysis applied to structural and functional MRI help characterize brain alterations across psychiatric conditions. Findings This review shows consistent fractal patterns across multiple psychiatric disorders, especially in frontal regions. Despite heterogeneous methodologies, results highlight shared structural and functional abnormalities. Clinical relevance Fractal analysis may offer complementary characterization of subtle brain organization across psychiatric disorders. Its potential clinical utility-such as improving diagnostic characterization, earlier detection, among others-remains limited by the current absence of a standardized protocol.

OBJECTIVES: Heart transplantation (HTx) remains the main long-term treatment for end-stage heart failure. Due to the high risk of acute cellular rejection (ACR), HTx recipients undergo multiple endomyocardial biopsies to monitor graft tolerance. This prospective, single-center study evaluated quantitative magnetic resonance imaging (MRI), particularly T1- and T2-mapping, as noninvasive tools for rejection monitoring. MATERIALS AND METHODS: The study included 17 adult HTx recipients (men, 88%; age, 53 ± 13 years) enrolled within 1 month after transplantation and 10 controls without structural heart disease. Htx recipients underwent 5 to 6 serial cardiac MRI scans with T1- and T2-mapping, coinciding with routine endomyocardial biopsies, to correlate imaging findings with histopathological evidence of ACR. Cardiac MRI relaxation times were compared based on the biopsy evidence of ACR. RESULTS: During the 6-month follow-up, HTx recipients underwent 87 cardiac MRI scans, with 13 ACR episodes reported in 9 patients (53%). They had significantly higher T1- and T2-mapping values than controls. Cardiac biomarkers, NT-proBNP and troponin, did not differ between patients with or without ACR. Global T2-mapping and regional abnormalities, particularly in septal segments, identified rejection, with a cutoff of 51 ms showing high specificity (92%) but modest sensitivity (46%) for ACR. In contrast, T1-mapping values were elevated only in selected myocardial segments, showing a consistent inferoseptal pattern, without differences in global myocardial T1 values between ACR and non-ACR patients, limiting their usefulness for identifying ACR. CONCLUSION: Noninvasive cardiac MRI, particularly T2-mapping, may help assess the risk of cardiac graft rejection and complement biopsy-based surveillance in HTx recipients. KEY POINTS: Question Monitoring acute cellular rejection (ACR) after heart transplantation is crucial, but whether noninvasive imaging can safely reduce the number of endomyocardial biopsies is still debatable. Findings Multiparametric cardiac magnetic resonance combining T1- and T2-mapping may improve diagnostic assessment and support more targeted use of invasive endomyocardial biopsies. Clinical relevance T2-mapping appears to be a promising noninvasive biomarker for detecting ACR in heart transplant recipients within the 6 months post-surgery, whereas T1-mapping shows regional differences but lacks consistency across the myocardium, having limited diagnostic utility in detecting acute inflammatory changes.

The COVID-19 pandemic propelled the growth of virtual care, yet its longitudinal impact on care utilization remains understudied. We used multichannel sequence analysis to classify 10,671 adults with diabetes by outpatient utilization patterns with their primary and diabetes care teams, including remote and in-person visits, at two San Francisco health systems from April 2019 to March 2023. Patients who transitioned to digital care were disproportionately Black or White, Medicare beneficiaries, and had higher comorbidity burdens. Individuals who increased their combined in-person and remote healthcare utilization were disproportionately Hispanic, Spanish-preferring, and had greater disease burden. Those who decreased utilization were predominantly Asian, preferred Chinese, and had low patient portal engagement. While technology-enabled care models have the potential to enhance access, some populations may be at risk of reduced access to care. Health systems should consider targeted interventions to ensure equitable telehealth access for populations at risk of digital exclusion as remote care expands.