Citations

Background : Metastatic lung carcinoids (MLCs) represent a rare subset of lung cancers with distinct histologic subtypes. Survival outcomes and prognostic factors have not been well-studied in the real-world setting. This study investigates the impact of various treatments, including chemotherapy, hormonal therapy, and no treatment, on the overall survival (OS) of patients with typical and atypical MLC. Methods: Patients with MLC between 2010 and 2020 were included from the National Cancer Database based on histologic codes ICD-O-3 8240/3 and 8249/3. Kaplan–Meier curves and multivariate Cox proportional hazard regression were used to compare OS and evaluate prognostic factors. Results: The median age at diagnosis was 68 and 69 years for atypical and typical MLC, respectively. The 3-year OS for the atypical MLC cohort was 22.11%, and for typical MLC was 41.94% ( P < 0.001). In the atypical MLC cohort, chemotherapy showed a nonsignificant benefit in OS (hazard ratio [HR], 0.89; 95% confidence interval [CI], 0.73–1.05; P = 0.21), whereas hormonal therapy was associated with significantly improved OS (HR, 0.72; 95% CI, 0.52–0.98; P =0.04). However, in the typical MLC cohort, chemotherapy was associated with adverse OS (HR, 2.15; 95% CI, 1.85–2.49; P < 0.0001), and hormonal treatment showed better, albeit nonsignificant OS (HR, 0.84; 95% CI, 0.67–1.05; P = 0.13). Conclusion: There is a notable difference in survival outcomes between typical and atypical MLC based on the treatment strategies. While hormonal therapy shows improvement in the OS, the effectiveness of chemotherapy varies depending on the histologic subtype. These findings emphasize the necessity for personalized therapeutic approaches based on the specific characteristics of MLC, ultimately contributing to improved patient outcomes in this challenging oncologic group. Further research is warranted to validate and expand upon these observations.

Abstract Tumor microenvironments (TMEs) are spatially complex and dynamic systems shaped by evolutionary pressures, tissue architecture, and cellular interactions. To capture this complexity, we developed the Tumor Landscape Analysis (TLA) pipeline, a computational framework applying principles from landscape ecology and spatial statistics to quantitatively characterize tumor spatial heterogeneity. TLA integrates spatially resolved pathology data, including whole-cell, point-based, and region-level formats, and computes multiscale metrics to assess cell distributions, neighborhood relationships, and tissue-level organization. The framework leverages ecological indices such as the Morisita-Horn index, Ripley’s H function, and Shannon diversity to quantify intercellular proximity, spatial clustering, and cellular diversity. It also uses the concept of local microenvironments (LMEs), data-driven ecological niches defined by local cell-type abundance and spatial uniformity, enabling unsupervised and reproducible classification of tumor regions. The use of fragmentation metrics, including patch density, shape complexity, and interspersion, provide further insight into spatial disorganization and emergent tissue architecture. TLA is agnostic to imaging modality and biological context, supporting broad applicability across tumor types and sample formats. By translating complex tissue architectures into interpretable spatial metrics, the pipeline enables integrative analyses that link spatial ecology to clinical and molecular phenotypes. This approach facilitates a deeper understanding of how spatial features contribute to tumor progression, therapeutic resistance, and clinical outcomes, offering new opportunities for precision oncology rooted in spatial systems biology.

ABSTRACT Chordomas are rare notochordal malignancies typically occurring in the axial skeleton. Less than 100 extra‐axial chordomas have been reported. We describe a unique chordoma of the anteromedial thigh. The clinical presentation of extra‐axial chordomas is highly variable; thus, recognizing this entity in the differential diagnoses of extra‐axial bone/soft tissue tumors is important.

This review examines the applications and challenges of large language models (LLMs), like OpenAI’s ChatGPT, in radiology research. ChatGPT can assist radiology researchers in generating new ideas, finding and summarizing research papers, designing studies, analyzing data, and facilitating manuscript writing. LLMs are powerful tools with numerous applications in radiology research. However, users should be mindful of potential pitfalls, such as producing incorrect or biased outputs and inconsistent responses, along with ethical and privacy concerns. We discuss approaches to optimize models and address these issues, including prompting techniques like chain-of-thought prompting, retrieval-augmented generation, and fine-tuning. For researchers, prompt engineering can be particularly effective. This review seeks to demonstrate how researchers can utilize ChatGPT for radiology research while offering strategies to mitigate associated risks. We aim to help researchers harness these potent tools to safely boost their productivity.

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as nonalcoholic fatty liver disease, is increasingly recognized as a multisystem disorder with significant cardiovascular implications, particularly in its association with atrial fibrillation (AF). As the most common sustained cardiac arrhythmia, AF contributes to substantial morbidity and mortality, making it essential to explore its links with MASLD. The relationship between these conditions is underpinned by shared pathophysiological mechanisms, including systemic inflammation, insulin resistance, oxidative stress, and activation of the renin-angiotensin-aldosterone system. These processes drive atrial remodeling and electrical instability, predisposing individuals with MASLD to AF. Epidemiological studies further support this connection, showing an independent association between MASLD and an increased risk of AF, particularly in those with metabolic comorbidities such as obesity and type 2 diabetes. Beyond increasing AF susceptibility, MASLD may also influence disease progression and response to treatment, affecting anticoagulation safety, rhythm-control strategies, and the success of catheter ablation. Given these clinical implications, therapies targeting metabolic dysfunction—such as statins, renin-angiotensin-aldosterone system inhibitors, and structured lifestyle modifications—may offer dual benefits in mitigating both MASLD and AF risk. However, significant knowledge gaps remain regarding the causal direction of this association, the impact of MASLD severity on AF burden, and the most effective management strategies for patients with both conditions. Future research should prioritize longitudinal studies, mechanistic investigations, and randomized controlled trials to deepen our understanding of this relationship, ultimately guiding more personalized and integrated treatment approaches. Incorporating MASLD screening into cardiovascular risk assessment may enhance early detection and improve outcomes for at-risk populations.

Study Design Systematic Review. Objective To assess the current literature regarding the accuracy of different imaging modalities and criteria used to assess lumbar fusion, and their correlation with surgical direct observation as the current Gold Standard. Methods Following PRISMA guidelines, we conducted a comprehensive search of PubMed, Embase, Google Scholar, and Cochrane Library, studies were included if they focused on patients with a prior history of lumbar interbody fusion and at least 1 year of radiographic follow-up. The review assessed the sensitivity, specificity, and accuracy of different imaging techniques, and their correlation with surgical findings. Results Thirteen studies (1989-2019) were reviewed, including 715 patients, common imaging modalities included plain radiographs (53.8%), Computed Tomography (CT) (69.2%), and dynamic radiographs (30.7%). CT appeared as the most utilized modality post-2006. There was substantial variability in diagnostic accuracy, with CT showing high variability in sensitivity and specificity. Descriptive criteria for fusion were widely used, but interobserver agreement was generally low. Conclusion The review highlights a lack of standardized criteria for assessing lumbar fusion. Despite advancements in imaging techniques, the variability in diagnostic parameters suggests a need for consensus and multicentric studies to stablish reliable, universal criteria for evaluating fusion success.

Purpose: Prostate-specific membrane antigen positron emission tomography (PSMA-PET) improves prostate cancer (PCa) localization, particularly in biochemical recurrence (BCR). The primary objective was to assess management patterns after PSMA-PET for BCR at 2 academic centers. Methods: This study evaluated clinical management within 6 months after first PSMA-PET for patients with BCR after local therapy. Management categories included no treatment, local therapy, systemic therapy, and metastasis-directed therapy (MDT). We also evaluated clinical management decision variation across strata of PSMA-PET results PSA levels (<2.0, 2.0-4.99, and ≥5.0 ng/mL) at time of imaging. Results: We identified 581 patients who received PSMA-PET from February 2021 to June 2023. PSMA-PET findings were negative in 142 (24%) and demonstrated localized recurrence in 86 (15%), regional nodal disease in 60 (10%), and distant metastasis in 293 (50%). Distant metastasis was identified in 105 (35%) patients with PSA < 2.0, 67 (60%) with PSA 2.0 to 4.99, and 115 (71%) with PSA ≥ 5.0. In patients with negative PSMA-PET, 63 (44%) received treatment. Conversely, 92% with detected metastases were treated (systemic therapy in 189 [64%], MDT in 75 [26%], and local therapy in 7 [2%]). Treatments differed by the PSA level within strata of PSMA-PET findings. Among 293 patients with metastases, MDT was used more commonly in patients with PSA < 2.0 (37%) than PSA 2.0 to 4.99 (30%) or PSA ≥ 5.0 (13%). Conclusions: Most patients undergoing PSMA-PET for BCR had identifiable disease and initiated therapy within 6 months. Identification of distant metastases and treatment choices differed by the PSA level at imaging. Prospective research is needed to determine whether earlier detection and treatment initiation improve clinical outcomes.