Objectives: The Residual Lesion Score (RLS) was developed as a novel tool for assessing residual lesions after congenital heart operations based on widely available clinical and echocardiographic characteristics. The RLS ranks postoperative findings as follows: Class 1 (no/trivial residua), Class 2 (minor residua), or Class 3 (major residua or reintervention before discharge for residua). The multicenter prospective RLS study aims to analyze the influence of residual lesions on outcomes in common congenital cardiac operations. We hypothesize that RLS will predict postoperative adverse events, resource utilization, mortality, and reinterventions by 1 year postoperatively.
Methods: The study cohort consisted of infants aged ≤12 months undergoing definitive surgery for complete atrioventricular septal defect, tetralogy of Fallot, dextro-transposition of the great arteries with or without intact ventricular septum, single ventricle (Norwood procedure), and coarctation or interrupted/hypoplastic arch with ventricular septal defect. Children with major congenital or acquired extracardiac anomalies that could independently affect the primary end point, which was number of days alive and out of the hospital within 30 days of surgery (60 days for Norwood procedure), were excluded. Secondary outcomes included ≥1 early major postoperative adverse event; days of intensive care unit and hospital stay, and initial and total ventilator time; mortality/transplant after discharge; unplanned reinterventions after discharge; and cost. All analyses will be performed separately by surgical operation.
Conclusions: This is the first multicenter prospective validation of a tool for surgical outcome assessment and quality improvement specific to congenital heart surgery.
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http://dx.doi.org/10.1016/j.jtcvs.2019.10.146 | DOI Listing |
Dermatofibrosarcoma protuberans (DFSP) is a rare, low to intermediate-grade soft tissue sarcoma that presents significant diagnostic and therapeutic challenges. We report the case of a 40-year-old male patient who presented with a slow-growing, asymptomatic lesion on his forehead that had developed over two years. Clinical examination revealed a firm, non-tender multinodular mass measuring 5 x 3 cm in the supraorbital region.
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January 2025
Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
Background: Intravascular lithotripsy (IVL) has an excellent efficacy and safety profile in the treatment of calcified coronary lesions during percutaneous coronary intervention (PCI). However, data regarding its use on left main (LM) lesions are still limited.
Objective: We aimed to analyze the technical success and 1-year clinical outcomes in calcified LM lesions treated with IVL.
Med Biol Eng Comput
January 2025
Artificial Intelligence Lab, School of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500046, India.
The generalization of deep learning (DL) models is critical for accurate lesion segmentation in breast ultrasound (BUS) images. Traditional DL models often struggle to generalize well due to the high frequency and scale variations inherent in BUS images. Moreover, conventional loss functions used in these models frequently result in imbalanced optimization, either prioritizing region overlap or boundary accuracy, which leads to suboptimal segmentation performance.
View Article and Find Full Text PDFNeurosurg Focus Video
January 2025
Department of Neurosurgery, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan; and.
Surgery of lesions around Wernicke's area is challenging for several reasons. The anatomical boundaries are not clearly defined, necessitating functional identification in addition to anatomical landmarks. There are potential complications secondary to injury of the surrounding structures.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Agricultural Information Technology, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
Identification and diagnosis of tobacco diseases are prerequisites for the scientific prevention and control of these ailments. To address the limitations of traditional methods, such as weak generalization and sensitivity to noise in segmenting tobacco leaf lesions, this study focused on four tobacco diseases: angular leaf spot, brown spot, wildfire disease, and frog eye disease. Building upon the Unet architecture, we developed the Multi-scale Residual Dilated Segmentation Model (MD-Unet) by enhancing the feature extraction module and integrating attention mechanisms.
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