Citations

Background: Body contouring is an increasingly common trend in aesthetic plastic surgery. In the pursuit of ideal body proportions, anterior thoracic cage deformities, especially lower rib cartilage prominence have emerged as a frequent source of dissatisfaction. To address this concern, the anterior aesthetic rib cage remodeling with osteosynthesis (ARCO) technique was developed as an innovative method to reshape the anterior rib cage. Methods: A retrospective study was conducted in Colombia on patients who underwent the ARCO procedure. Preoperative and postoperative rib cage perimeter measurements were recorded. Spirometry was performed preoperatively and during long-term follow-up to assess potential changes in respiratory volumes. Intraoperative peak pressure and pulmonary compliance values were monitored to evaluate procedural safety. Postoperative satisfaction was assessed using the BODY-Q questionnaire, and all complications were documented. Results: A total of 34 patients were included, with a mean age of 34 years. A significant reduction in the inferior rib cage perimeter at the level of the eighth rib was observed (Mann-Whitney U =190, P < 0.001), with a mean decrease of 2 cm. Intraoperative peak inspiratory pressure and pulmonary compliance remained stable across all procedural stages. Spirometric analyses revealed no restrictive changes in respiratory volumes. Conclusions: The ARCO technique offers an effective approach for reducing chest circumference and enhancing the aesthetic contour of the anterior rib margin while achieving high patient satisfaction. It involves a controlled greenstick fracture followed by osteosynthesis to create a stable and natural rib curvature, reducing the risk of malunion and eliminating the need for postoperative corsets.

Abstract Pancreatic ductal adenocarcinoma (PDAC), the most common subtype of pancreatic cancer, is a deadly disease with a complex tumor microenvironment (TME). How chemotherapy alters the TME, and whether these changes drive chemoresistance, is poorly understood. We examined matched pre- and post-treatment tissue specimens and found near-universal enrichment of axonal guidance genes in cancer-associated fibroblasts (CAFs) after treatment. These CAFs were enriched near sites of perineural invasion, coinciding with regions of increased tumor cell proliferation, and were enriched in tumor areas distant from nerves after chemotherapy. Metastatic recurrence lesions had the highest prevalence of these CAFs versus primary tumors and untreated metastasis. These CAFs showed elevated non-canonical Wnt mediators and axonal guidance genes, which complemented matching cognate binding partners in tumor epithelial cells, suggesting a role in tumor-stroma crosstalk. Our findings implicate fibroblast-derived axonal-guidance genes in promoting PDAC invasion and point to a promising target for this disease. Statement of Significance Therapeutic resistance remains a major challenge in pancreatic cancer. Our findings shed light on the changes in the complex tumor microenvironment in response to chemotherapy and identify fibroblasts high in axonal-guidance genes that may drive tumor progression and chemoresistance, thus uncovering a potential avenue for targeting pancreatic cancer.

Abstract Valvular heart disease represents a significant global health burden, with an estimated prevalence of 2.5% in high-income countries and projected increases due to population ageing. Randomized controlled trials in valvular heart disease have undergone substantial evolution, shifting from mortality-focused endpoints toward comprehensive assessments integrating imaging parameters and patient-centered outcomes. Cardiovascular imaging modalities, including echocardiography, cardiac computed tomography, and cardiac magnetic resonance, have become pivotal in trial design, patient selection, and endpoint definition. Recent landmark trials in aortic stenosis, including EARLY-TAVR and EVOLVED, have challenged traditional symptom-based intervention thresholds by incorporating imaging biomarkers of subclinical myocardial dysfunction and cardiac damage staging. In aortic regurgitation, the paucity of randomized controlled trials evidence contrasts with emerging transcatheter technologies, highlighting critical knowledge gaps. Mitral regurgitation trials have demonstrated the importance of patient phenotyping, with divergent outcomes between COAPT and MITRA-FR emphasizing the role of imaging in optimal patient selection. The recent TRILUMINATE and TRISCEND trials have transformed tricuspid regurgitation management through transcatheter interventions, prioritizing quality-of-life improvements alongside traditional clinical endpoints. Future directions include standardization of imaging protocols across modalities, development of artificial intelligence-enhanced analysis, and integration of multiparametric biomarkers for personalized risk stratification. The paradigm shift toward imaging-guided, patient-centered trial design represents a fundamental reimagining of therapeutic success in valvular heart disease, moving beyond procedural outcomes toward comprehensive assessment of clinical benefit and improved patient care.

Localized cutaneous squamous cell carcinoma (cSCC) has a favorable prognosis, unlike advanced disease, especially with clinical perineural invasion (PNI), which poses substantial management challenges due to aggressivity and higher recurrence, metastasis, and mortality risks. PNI, a high-risk staging feature, has worse outcomes, particularly when clinically evident rather than incidental. Clinical PNI (cPNI) is evident by clinical symptoms (such as pain, paresthesia, or motor deficits) or radiologic findings, whereas incidental PNI (iPNI) is identified only histologically without associated symptoms or radiologic evidence. PNI remains a novel area with varying practice patterns across institutions. Improving risk stratification and tailoring multidisciplinary approaches are critical for optimizing outcomes. Our review outlines clinical practice patterns at our institution, providing insights into managing cSCC with PNI, focusing on diagnosis, imaging, staging, and emerging immunotherapies. A structured search was conducted using the terms “perineural invasion,” “cutaneous squamous cell carcinoma,” and “immunotherapy.” cPNI has a poor prognosis and requires nuanced clinical decision-making. Surgery and radiation remain central to management. Adjuvant therapy offers substantial survival benefit in cSCC with PNI, with improved disease-free and overall survival compared with surgery alone, supporting its use in appropriately selected high-risk patients. Traditional systemic therapies, including cisplatin and cetuximab, remain foundational but have shown only moderate response rates and limited durability in advanced or neurotropic cSCC. In contrast, immunotherapy—now preferred for advanced or unresectable cases—has transformed management, with programmed cell death protein-1 (PD-1) inhibitors showing promising results (up to 69% response rate) and disease stabilization. Neoadjuvant immunotherapy may enable tumor downstaging, improve radiation planning, and reduce surgical morbidity. Imaging for squamous cell carcinoma (SCC) with PNI aids staging and surveillance, but symptoms remain key for detecting recurrence. Our multidisciplinary approach emphasizes personalized care. Larger trials are needed to define the optimal role and sequencing of immunotherapy in this high-risk patient population.

BACKGROUND: Guidelines recommend 3-hour cardiac amyloid radionuclide imaging (CARI) for transthyretin amyloid cardiomyopathy. Citing rapid blood clearance of 99m Tc-hydroxymethylene-diphosphonate (HMDP) and efficient laboratory throughput, 1-hour imaging is increasingly practiced despite limited supporting evidence. We sought to compare diagnostic performance and interpreter experience of 1-hour versus 3-hour HMDP-CARI. METHODS: Consecutive patients with suspected transthyretin amyloid cardiomyopathy (n=114) underwent both 1-hour and 3-hour HMDP single photon emission computed tomography (CT)/CT. Two cardiologist-radiologist reader teams, blinded to imaging timepoint (1 versus 3 hours), assessed overall interpretation, single photon emission CT–based Perugini grade, interpretation difficulty, interpreter confidence, and need for CT-fused images for anatomic localization. Discordant, equivocal, and difficult cases were arbitrated by a third tie-breaking team. The myocardial-to-blood-pool radiotracer uptake ratio (3-dimensional Score) was measured as a surrogate of contrast resolution. RESULTS: Interinterpreter agreement was high at both time points (κ≥0.81), with more cases requiring arbitration at 3 hours versus 1 hour (22% versus 13%; P =0.049). Overall interpretation and Perugini grades were concordant between time points in 111/114 (97%) and 106/114 (93%) patients, respectively. Three patients (3%) were negative at 1 hour but equivocal at 3 hours, all of which were clinically ruled out for transthyretin amyloid cardiomyopathy. Interpreter confidence was comparable at both timepoints (97% versus 95%; P =0.317). Compared with 3-hour imaging, contrast resolution was inferior (lower 3-dimensional score, P <0.001) and CT fusion was more frequently needed (57% versus 31%, P <0.001) at 1-hour imaging. CONCLUSIONS: In a prospective, blinded comparison of 1-hour versus 3-hour HMDP-CARI, diagnostic performance and interpreter experience were similar, with readers requesting CT fusion more frequently at 1 hour to optimize myocardial-to-blood pool discrimination.

To improve synthetic CT (sCT) generation from cone-beam CT (CBCT) in radiotherapy, we propose a multiscale segmentation-guided diffusion framework. The proposed model integrates anatomical priors across multiple spatial resolutions through a segmentation mask pyramid and introduces a scale-specific loss function to guide learning at each level. When evaluated on the SynthRAD2023 brain dataset, our model achieves a mean absolute error (MAE) of 61.82 HU, a peak signal-to-noise ratio (PSNR) of 32.05 dB, and a structural similarity index (SSIM) of 0.90, outperforming baseline models. These results suggest that multiscale anatomical guidance can improve the fidelity and anatomical consistency of sCT images, thus facilitating high-quality CBCT-to-CT translation in radiotherapy applications.

Abstract An 86-year-old woman with metastatic non-small cell lung carcinoma on Pembrolizumab presented to the Emergency Department with diabetic ketoacidosis; after appropriate treatment she was transitioned to basal/bolus insulin regimen. She had chosen to receive Immune Checkpoint Inhibitor (ICI) instead of radiotherapy, as she wished to preserve her quality of life. With the demands of management of ICI-induced irreversible insulin deficient diabetes she now has substantial worsening of quality of life with considerable anxiety and depressed mood. ICI-induced diabetes and DKA is more common in patients treated with Pembrolizumab than suggested by early trials. In addition to highlighting the importance of counseling patients on the signs and symptoms of hyperglycemia for earlier detection, our case calls for considering the psychological impact of managing a chronic illness in patient education prior to initiating ICI therapy.

Abstract Pancreatic cancer, projected to become the second-deadliest malignancy in Western societies by 2030, requires urgent innovations in early detection and risk stratification. Intraductal papillary mucinous neoplasms (IPMNs) represent critical precursor lesions, but current clinical guidelines demonstrate suboptimal accuracy in malignancy prediction, leading to either unnecessary surgeries or missed opportunities for early intervention. In this paper, we present Cyst-X, an artificial intelligence (AI) framework that accurately predicts IPMN malignant transformation using multicenter magnetic resonance imaging (MRI) data. Unlike most previous approaches that rely on computed tomography (CT), our method capitalizes on the superior soft tissue contrast of MRI, allowing for more precise identification of subtle imaging biomarkers. We developed and validated deep learning models on 723 T1-weighted and 738 T2-weighted MRI scans from 764 patients among seven international institutions, demonstrating significantly superior performance (AUC=0.82) compared to current clinical (Kyoto) guidelines (AUC=0.75) and expert radiologists. AI-based imaging features correlate strongly with clinically recognized malignancy markers, providing potential biologically relevant insights. This approach holds promise to significantly refine clinical decision-making, reduce unnecessary surgeries, and better identify high-risk IPMN patients for timely intervention. Our approach integrates a novel pancreas segmentation network with robust classification models that identify subtle imaging biomarkers associated with malignancy risk. Importantly, we demonstrate that these models retain high performance in a privacy-preserving federated learning setting, where institutions collaboratively train AI models without exchanging patient data to address key regulatory and ethical barriers. We publicly release the Cyst-X dataset--the first large-scale, multi-center pancreatic cyst MRI collection--to accelerate research in this field. This study addresses a critical clinical need while establishing technical foundations for privacy-preserving AI in radiology that could transform pancreatic cancer management through earlier intervention and reduced unnecessary procedures. The dataset can be accessed at https://osf.io/74vfs/, and the source code for our deep learning segmentation and classification models is available at https://github.com/NUBagciLab/Cyst-X.