Eosinophilic fasciitis (EF) remains a rare condition without precise diagnostic criteria due to common symptoms with other autoimmune diseases requiring broad differential diagnosis. This paper describes the use of high-resolution musculoskeletal ultrasonography and elastography in the diagnosis and follow-up of eosinophilic fasciitis through the case of a 56-year-old male patient. In addition to laboratory data, instrumental data, and biopsy, musculoskeletal ultrasonography (US) was used both in the diagnostic process and in the follow-up period for an objective assessment of the changes in the patient's condition and response to treatment. The US showed disorganization of the myofibrils adjacent to the superficial fascia, edema, and thickening of the fascia and subcutaneous edema. In addition, the use of shear-wave elastography (SWE) demonstrated significantly reduced skin elasticity. High-frequency musculoskeletal ultrasound in combination with SWE is an effective method both for the diagnosis of EF and for the follow-up of the changes occurring after therapy. Based on the fact that it can easily differentiate the substrate of involvement, such as skin, subcutaneous tissue, or muscle fascia, ultrasound can be used to distinguish EF from other skin and muscle diseases.
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http://dx.doi.org/10.1007/s00296-023-05401-7 | DOI Listing |
Sci Rep
January 2025
Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192, Japan.
Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medical images. However, current approaches were either applied only to 2D cross-sectional images, addressed few structures, or were validated on small datasets, which limit the application in large-scale databases. This study aimed to validate an improved deep learning model for volumetric MSK segmentation of the hip and thigh with uncertainty estimation from clinical computed tomography (CT) images.
View Article and Find Full Text PDFAsia Ocean J Nucl Med Biol
January 2025
Research Center for Nuclear Medicine, Shraiati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Objectives: To compare the diagnostic performance of [Ga]-Ga-FAPI-46 and [F]-FDG PET/CT imaging for the detection of lesions and disease staging in breast cancer.
Methods: Twelve female patients with breast cancer (mean age= 49.2±13.
Am J Sports Med
January 2025
University of Alabama at Birmingham, Birmingham, Alabama, USA.
Background: Benign bone lesions are a common incidental finding in athletes during workup for musculoskeletal complaints, and athletes are frequently advised to halt participation in contact sports. There are no current guidelines to assist clinicians in referring patients with these lesions to a subspecialist or in advising athletes on the safety of returning to sport.
Purpose: To assist sports medicine physicians in appropriate referral for patients with benign bone lesions through presentation of a literature review and the case of an adolescent athlete with a benign bone lesion in a location with a significant fracture risk.
Bone Joint J
January 2025
King's Foot and Ankle Unit, King's College Hospital NHS Foundation Trust, London, UK.
Hallux valgus (HV) presents as a common forefoot deformity that causes problems with pain, mobility, footwear, and quality of life. The most common open correction used in the UK is the Scarf and Akin osteotomy, which has good clinical and radiological outcomes and high levels of patient satisfaction when used to treat a varying degrees of deformity. However, there are concerns regarding recurrence rates and long-term outcomes.
View Article and Find Full Text PDFEur Radiol
December 2024
Department of Medicine, Surgery, and Dentistry, University of Salerno, Baronissi, Italy.
Objectives: To evaluate the quality of radiomics research in prostate MRI for the evaluation of prostate cancer (PCa) through the assessment of METhodological RadiomICs (METRICS) score, a new scoring tool recently introduced with the goal of fostering further improvement in radiomics and machine learning methodology.
Materials And Methods: A literature search was conducted from July 1st, 2019, to November 30th, 2023, to identify original investigations assessing MRI-based radiomics in the setting of PCa. Seven readers with varying expertise underwent a quality assessment using METRICS.
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