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CT features with histopathological correlation in inflammatory versus benign & malignant neoplastic appendiceal mucoceles: a retrospective cross-sectional study.
BMC Gastroenterol
January 2025
Faculty of Medicine, University of Khartoum, Khartoum, 11111, Sudan.
Background & Objectives: Differentiation of histologic subtypes of appendiceal mucoceles may prove to be difficult on computed tomography (CT). The main objective of this study was to identify the CT features of mucocele of the appendix and correlate the imaging findings with histopathology in inflammatory, benign, and malignant neoplastic lesions, and whether these entities can be accurately differentiated on CT imaging.
Materials And Methods: CT scans of 31 patients with diagnosis of appendiceal mucocele were retrospectively reviewed and compared with histopathology.
Use of AI in Cardiac CT and MRI: A Scientific Statement from the ESCR, EuSoMII, NASCI, SCCT, SCMR, SIIM, and RSNA.
Radiology
January 2025
From the Department of Radiology, University of Washington, UW Medical Center-Montlake, Seattle, Wash (D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC), University of Washington, Seattle, Wash (D.M.); Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (M.v.A.); Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (M.H.); Department of Radiology, Mayo Clinic, Rochester, Minn (T.L., E.E.W.); Departments of Cardiology and Radiology, Royal Brompton Hospital, London, United Kingdom (E.D.N.); School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom (E.D.N.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (B.D.A.); Department of Radiology, University of Cagliari, Cagliari, Italy (L.S.); Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1 Postbus 30 001, 9700 RB Groningen, the Netherlands (R.V.); Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada (K.H.); and Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.H.).
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite the development of many cardiac imaging AI algorithms, AI tools are at various stages of development and face challenges for clinical implementation. This scientific statement, endorsed by several societies in the field, provides an overview of the current landscape and challenges of AI applications in cardiac CT and MRI.
View Article and Find Full Text PDFEvaluation of the Efficiency of Ultrasonography and Color Doppler in Diagnosis of Intraosseous Jaw Lesions: An Study.
J Contemp Dent Pract
October 2024
Department of Prosthodontics, Dr. D.Y. Patil Dental College and Hospital, Dr. D.Y. Patil Vidyapeeth, Pune, Maharashtra, India.
Aim: The current investigation aimed to evaluate the accuracy of ultrasonography and color Doppler performed in the diagnosis of intraosseous jaw lesions.
Materials And Methods: A total of 30 patients with intraosseous jaw lesions between the ages of 12 and 60 were selected for the present study. For every jaw lesion, a preliminary diagnosis was done using preoperative conventional radiographs.
Value of MRI-based radiomics models for predicting visual outcome in patients with MOG-optic neuritis: A preliminary study.
Eur J Ophthalmol
January 2025
Department of Radiology, 3rd Medical Center of Chinese PLA General Hospital, Beijing, China.
Purpose: To investigate the predictive value of MRI-based radiomics models for the recovery of visual acuity after 12 months in patients with acute phase MOG-optic neuritis(MOG-ON).
Materials And Methods: Clinical and MRI imaging data were collected consecutively from January 2021 to April 2022 from patients with acute stage MOG-ON, and the visual acuity of patients were followed up after 12 months. After stratified random sampling, patients were divided into training and test sets, and prediction models based on CE-T1WI, FS-T2WI, and combined CE-T1WI and FS-T2WI were developed.
Preclinical evaluation and preliminary clinical study of Ga-NODAGA-NM-01 for PET imaging of PD-L1 expression.
Cancer Imaging
January 2025
Department of Nuclear Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Hongkou District, No. 100, Haining Road, Shanghai, 200080, China.
Background: Programmed cell death 1/programmed death ligand-1 (PD-L1)-based immune checkpoint blockade is an effective treatment approach for non-small-cell lung cancer (NSCLC). However, immunohistochemistry does not accurately or dynamically reflect PD-L1 expression owing to its spatiotemporal heterogeneity. Herein, we assessed the feasibility of using a Ga-labeled anti-PD-L1 nanobody, Ga-NODAGA-NM-01, for PET imaging of PD-L1.
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