Publications by Year: 2026

BACKGROUND: Complex tibial plateau fractures continue to pose a significant challenge for surgeons. In recent years, the widespread use of CT imaging has led to new insights leading to novel classifications that facilitate 360° stabilization techniques. Visualization in 3D has improved both fracture reduction and surgical outcomes. This study investigated whether preoperative planning of complex tibial plateau fracture fixation via finite element modeling (FEM) could enhance the fixation performance achieved by experienced surgeons and potentially improve outcomes for less experienced surgeons.

METHODS: In twelve left cadaveric fresh-frozen human knees with intact soft tissue reproducible Schatzker type IV fractures with lateral depression were created. The samples were paired on the basis of bone mineral density and then randomly allocated into two groups. Six senior surgeons with extensive experience in the operative treatment of tibial plateau fractures performed two procedures: one using standard preoperative planning and one using FEM-optimized fixation planning. All fractures were stabilized with a medial locking plate and supplemental single screws when needed. The operation time, radiation dose and implant usage were documented. Surgeon mental workload was measured by the NASA task load index. Finally, the samples were biomechanically tested over four quasistatic load ramps from 10 to 200 N, followed by a cyclic sinusoidal load with increasing load level until failure. Failure was defined as either ≥ 5° varus/valgus malalignment or a vertical impression of the condyles ≥ 3 mm. The initial stiffness and load to failure were assessed via a 3D motion tracking system. Statistical analysis was conducted using Student's t-tests.

RESULTS: No significant differences were observed in terms of operative time or intraoperative radiation exposure. However, the NASA-TLX mental demand test revealed a statistically significant advantage for the FEM-planned group (33 ± 12.4 vs. 49 ± 8.6 (p = 0.043)), indicating a reduced cognitive load. Additionally, the FEM group exhibited superior biomechanical performance, with a higher load to failure of 1050 ± 535 N vs. 442 ± 226 N (p = 0.041).

CONCLUSION: This biomechanical feasibility study demonstrated that FEM-based preoperative planning is feasible and easy to implement for complex tibial plateau fractures. This planning supports specialized surgeons in challenging operations and can improve the stability of osteosynthesis.

BACKGROUND AND OBJECTIVES: Alzheimer's disease and related dementias (ADRDs) are prevalent conditions that are stressful and elevate emotional distress in couples after diagnosis. Without treatment, emotional distress may become chronic and negatively affect couples' quality of life. We report results from an NIH Stage 1A open pilot of Resilient Together for Dementia (RT-ADRD), a novel, dyadic, skills-based intervention aimed at preventing chronic emotional distress in couples early after diagnosis. We describe results from our mixed-methods single arm feasibility study, including preliminary feasibility and acceptability of the intervention, and qualitative feedback from exit interviews. We also present exploratory analyses for change in outcomes and mechanisms of action.

METHODS: Six couples (N = 12 individuals) were recruited within six months of ADRD diagnosis by their diagnosing providers. Participants completed baseline assessments, participated in weekly RT-ADRD sessions together, then completed post-intervention assessments and one 60-min exit interview together.

RESULTS: RT-ADRD exceeded all a-priori feasibility and acceptability benchmarks (> 70%). Feedback from exit interviews suggested that participants had favorable impressions of the program and found the skills useful and relevant. Participants also offered perspectives on barriers and facilitators of engagement and program enhancement. In exploratory analyses, persons living with dementia exhibited significant reductions in perceived stress at post-intervention (p < .05; Cohens d > 0.8). Both persons living with dementia and their care partners exhibited statistically significant improvements in positive dyadic interactions measured by the Dyadic Relationship Scale (ps < .05); Cohens ds > 0.8).

CONCLUSIONS: RT-ADRD shows promise as a feasible and acceptable dyadic intervention delivered early after diagnosis. Results support a future NIH Stage 1B trial of RT-ADRD to establish definitive feasibility markers of both intervention and control before formal efficacy testing.

TRIAL REGISTRATION: This open pilot was registered on ClinicalTrials.gov (NCT06421545) on 05/20/2024.

OBJECTIVE: To synthesize magnetic resonance imaging (MRI) features and their reported diagnostic performance that differentiate benign from malignant soft-tissue tumors in alignment with the 2020 World Health Organization classification.

MATERIALS AND METHODS: A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed, Embase, Scopus, and the Cochrane Central Register of Controlled Trials were searched through July 2024. Eligible studies reported MRI feature frequencies or diagnostic accuracy for common soft-tissue tumor subtypes. Reviews, case reports, duplicates, non-English publications, and studies outside the scope were excluded. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2).

RESULTS: Seventy-six studies met inclusion criteria. In lipomatous tumors, homogeneous fat signal and thin septa supported lipoma, whereas thick or nodular septa and enhancement favored atypical or well-differentiated liposarcoma. Myxofibrosarcoma often demonstrated an infiltrative fascial "tail." Vascular lesions included angioleiomyoma with a reticular T2 pattern and glomus tumor with marked T2 hyperintensity and avid enhancement. In peripheral nerve sheath tumors, lower apparent diffusion coefficient values and peritumoral edema favored malignancy. Heterogeneity in imaging protocols precluded meta-analysis; results were summarized descriptively by subtype.

CONCLUSION: Consolidated MRI patterns-such as septal morphology in lipomatous tumors, the fascial tail in myxofibrosarcoma, characteristic T2 patterns in vascular lesions, and diffusion and edema cues in nerve sheath tumors-support differentiation of benign and malignant entities, enhance reader confidence, and inform biopsy and management. Standardized prospective studies are needed to validate these thresholds and improve generalizability.

Pulsed field ablation (PFA) has proven to be a safe and effective non-thermal ablation modality for the treatment of atrial fibrillation (AF), but little outcome data beyond 1 year have been reported. Here we present results from the ADVENT-LTO study, which provides extended follow-up of the ADVENT trial, the first randomized trial comparing PFA with conventional thermal ablation. In ADVENT-LTO, 364 patients with paroxysmal AF (183 PFA, 181 thermal; 237 men, 127 women) participated and were followed for 1,332 ± 147 days. For the primary endpoint of 4-year treatment success, PFA demonstrated preserved effectiveness compared to thermal ablation (72.8% PFA, 64.3% thermal; P = 0.12). Moreover, there was a trend favoring PFA as compared to thermal ablation for the prespecified outcome of freedom from hospital-based arrhythmia intervention (85.6% PFA, 78.6% thermal; hazard ratio (HR) = 0.64, 95% confidence interval (CI): 0.38-1.05), including fewer repeat ablations (10.4% PFA, 17.7% thermal; P = 0.04) as well as a trend favoring PFA as compared to thermal ablation for the prespecified outcome of progression to persistent AF (2.6% PFA, 4.6% thermal; HR = 0.55, 95% CI: 0.16-1.88). Taken together, these data demonstrate that the favorable outcomes of PFA are maintained over the course of 4 years. Coupled with the safety advantages of PFA over thermal ablation, these long-term data support widespread adoption of PFA for the treatment of AF. ClinicalTrials.gov registration: NCT06526546 .

In this issue of Cancer Discovery, Chen and colleagues demonstrate that, in preclinical models, HER2 expression level directly affects trastuzumab deruxtecan internalization and cytotoxicity, with clinical data revealing divergent target dynamics depending on whether HER2 functions as an oncogenic driver or a dispensable antigen. Together with prior preclinical and clinical evidence, these findings support a context-dependent model in which target downregulation predominates in HER2-low disease, whereas payload resistance or rare binding-site mutations may dominate resistance in HER2-addicted tumors, with important implications for antibody-drug conjugate selection and sequencing. See related article by Chen et al., p. 235.

Microvascular dysfunction plays a pivotal role in numerous diseases, often preceding clinical symptoms and structural changes. Ultrasound localization microscopy (ULM) is an emerging ultrasound imaging modality that enables in vivo visualization of microvascular structures with unprecedented resolution. This narrative review aimed to examine the recent clinical applications of ULM and its role in biomarker development. It was conducted following PRISMA 2020 guidelines and included 33 articles published up to November 2025, focusing on ULM in human studies. Inclusion criteria targeted studies evaluating ULM's clinical applications and biomarkers. Data extraction encompassed imaging protocols, biomarkers and outcomes, with study quality assessed using the Newcastle-Ottawa Scale. ULM demonstrates significant promise across various organs. In kidney applications, ULM and its novel variant, sensing ULM, identified glomeruli and microvascular density as biomarkers for kidney disease and allograft dysfunction. In the brain, transcranial ULM enabled microvascular mapping with a resolution of 25 μm, aiding the evaluation of Moyamoya disease. ULM has also shown potential in detecting inflammatory changes in the carotid artery, myocardial microcirculation and testicular vascular architecture. Oncology applications include monitoring tumor vascularity and therapy response, revealing early microvascular changes undetectable by conventional imaging. Future technical improvements, such as higher-frame-rate clinical scanners, real-time data processing and clinical 3D imaging capabilities, are necessary to overcome current limitations. To conclude, ULM is on the verge of clinical translation, offering significant potential for developing microvascular biomarkers across various tissues and diseases. The medical community must now adopt and refine ULM applications and establish their role in routine clinical practice.

Patients with multiple myeloma (MM) often use cardiovascular medications due to their increased risk of cardiovascular diseases. This study investigated the associations of baseline use of these drugs with survival and adverse events in MM patients initiating daratumumab, lenalidomide, or bortezomib combination treatments. Data from Phase III trials (CASTOR, MAIA, and POLLUX) were analysed, focusing on beta-blockers, calcium channel blockers, ACE inhibitors (ACEI), angiotensin II receptor blockers (ARBs), diuretics, and statins. Cox proportional hazard analysis and logistic regression were used to assess associations with survival and grade ≥ 3 adverse events. Among 1804 patients, ACEI/ARBs were most common (31%), followed by beta-blockers (23%), statins (21%), calcium channel blockers (17%), and diuretics (16%). ACEI/ARBs was associated with better progression-free survival (adjusted hazard ratio (aHR) [95% CI] = 0.84 [0.71-0.99], P = 0.034) but also higher odds of grade ≥ 3 adverse events (adjusted odds ratio (aOR) = 1.45 [1.06-1.97], P = 0.019). Diuretics were similarly associated with grade ≥ 3 adverse events (aOR = 1.53 [1.01-2.34], P = 0.047). Other cardiovascular drugs showed no significant associations. While ACEI/ARBs may improve progression-free survival, they pose safety concerns. It is reassuring that other cardiovascular drugs were not significantly associated with MM treatment outcomes. Further research is essential to fully understand the implications of these medications.

Rare diseases affect an estimated 300-400 million people worldwide, yet individual conditions remain underdiagnosed and poorly characterized due to low prevalence and limited clinician familiarity. Computational phenotyping offers a scalable approach to improving rare disease detection, but algorithm development is constrained by scarce high-quality labeled data. Expert-labeled datasets from chart reviews and registries are highly accurate but limited in scope, whereas labels derived from electronic health records (EHRs) provide broader coverage but are often noisy or incomplete. To efficiently leverage both sources, we propose WEST (WEakly Supervised Transformer) for rare disease diagnosis and subphenotyping from EHRs. At its core, WEST employs a weakly supervised transformer trained on a limited set of expert-validated labels and extensive probabilistic silver-standard labels-derived from structured and unstructured EHR features-that are iteratively refined across training rounds to improve model calibration. We evaluate WEST on two rare pulmonary conditions using EHR data from Boston Children's Hospital and show that it outperforms existing methods in phenotype classification, identification of clinically relevant subphenotypes, and prediction of disease progression. By reducing reliance on manual annotation, WEST enables label-efficient representation learning that supports accurate rare disease diagnosis and reveals deeper clinical insights from routine EHR data.

BACKGROUND: Congenital heart disease (CHD) affects about 1% of births and is linked to differences in thinking and learning. Understanding how birth, genetic, clinical, and environmental factors together explain cognitive variability can inform monitoring and care. This study builds a multivariate model predicting cognition across multiple domains in adolescents and young adults with CHD.

METHODS: We studied 89 adolescents and young adults (AYAs; mean age 16 years) with CHD who completed structural and diffusion MRI and fifteen neurocognitive tests across seven domains. Using an enhanced forward-inclusion and backward-elimination strategy with cross-validation, we built multivariate models incorporating biological, socioeconomic, clinical, genetic, and brain imaging features. Performance was evaluated using Pearson correlation ( r ) between observed and inferred scores, mean absolute error (MAE), and inverse inferability score (IIS).

RESULTS: Here we show that models infer scores with moderate accuracy ( r  = 0.245-0.648; MAE = 1.6-12.0 points; mean MAE = 6.3). Highest correlations include Digit Span ( r  = 0.65; p < 0.001), Verbal Comprehension Index ( r  = 0.594; p < 0.001), and Matrix Reasoning ( r  = 0.574; p < 0.001). Domain ranking by IIS shows the best (lowest) scores for general intelligence (0.0886), followed by working memory (0.7100), and a higher (worse) score for perceptual reasoning (1.9199).

CONCLUSIONS: A multivariate approach combining brain imaging with genetic, clinical, and environmental factors provides clinically meaningful inference of individual cognitive performance in AYAs with CHD. These findings suggest complementary roles of brain, genetic, and contextual factors in shaping cognitive variability and motivate validation in larger cohorts.