Background: Symptomatic cholelithiasis is among the most common of general surgery referrals. With an appropriate clinical presentation, definitive diagnosis requires documentation of gallstones by ultrasonography (US). The authors evaluated the accuracy of surgeon-performed US for identifying gallstones in patients with a nonacute indication for study.
Methods: Patients referred for symptomatic cholelithiasis and who provided informed consent received an US examination by one or more of the surgical investigators. Surgeon-performed US findings were correlated with radiologist US findings and pathologic diagnoses.
Results: Seventy-seven patients received a total of 128 examinations by the investigators. Surgeon-performed US examination agreed with the radiologist US findings for 112 of 122 studies (92%) with a sensitivity of 100% and a specificity of 95%. Surgeon-performed US findings correlated with the pathologic diagnoses for 83 of 86 studies (97%).
Conclusions: Surgeons can perform gallbladder US in the nonacute setting with a high degree of accuracy.
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http://dx.doi.org/10.1016/s0002-9610(99)00225-1 | DOI Listing |
Oral Radiol
January 2025
University of Pennsylvania, 1 Founders Pavilion, 3400 Spruce Street, Philadelphia, PA, 19104-4283, USA.
Objectives: This study aimed to train a 3D U-Net convolutional neural network (CNN) for mandible and lower dentition segmentation from cone-beam computed tomography (CBCT) scans.
Methods: In an ambispective cross-sectional design, CBCT scans from two hospitals (2009-2019 and 2021-2022) constituted an internal dataset and external validation set, respectively. Manual segmentation informed CNN training, and evaluations employed Dice similarity coefficient (DSC) for volumetric accuracy.
Langenbecks Arch Surg
June 2024
Department of Surgical, Medical and Molecular Pathology and Critical Area, University of Pisa, Pisa, Italy.
Purpose: Assessing vocal cord mobility is crucial for patients undergoing thyroid surgery. We aimed to evaluate the feasibility and efficacy of surgeon-performed transcutaneous laryngeal ultrasound (TLUS) compared to flexible nasolaryngoscopy.
Method: From February 2022 to December 2022, we conducted a prospective observational study on patients scheduled for total thyroidectomy at our Institution.
Eur J Orthop Surg Traumatol
July 2024
Department of Orthopaedic Surgery, University of Louisville, 550 S. Jackson St., 1st Floor ACB, Louisville, KY, 40202, USA.
Introduction: Computerized surgical navigation system guidance can improve bone tumor surgical resection accuracy. This study compared the 10-mm planned resection margin agreement between simulated pelvic-region bone tumors (SPBT) resected using either skin fiducial markers or Kirschner (K)-wires inserted directly into osseous landmarks with navigational system registration under direct observation. We hypothesized that skin fiducial markers would display similar resection margin accuracy.
View Article and Find Full Text PDFAsian J Surg
September 2024
Department of Radiology, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Dusit, Bangkok, Thailand.
Background: Differentiating between arteriovenous fistula (AVF) maturation and failure can help determine which AVF will undergo successful canulation and which ones will require immediate rescue.
Methods: A prospective observational study was conducted at Vajira Hospital in Bangkok, Thailand, between October 2020-November 2022. A single vascular surgeon performed a physical examination on patients with chronic kidney disease undergoing AVF placement, and a radiologist conducted Doppler ultrasonography during the second and sixth postoperative weeks.
Neurospine
March 2024
Department of Neurosurgery, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea.
Objective: This study aimed to develop and validate a deep learning (DL) algorithm for the quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its efficacy across varying levels of clinical expertise.
Methods: Using the pretrained Mask Region-Based Convolutional Neural Networks model, originally developed for vertebral body segmentation and fracture detection, we fine-tuned the model and added a new module for measuring fracture metrics-compression rate (CR), Cobb angle (CA), Gardner angle (GA), and sagittal index (SI)-from lumbar spine lateral radiographs. These metrics were derived from six-point labeling by 3 radiologists, forming the ground truth (GT).
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