Objective: The objectives of our study were to assess the evidence for the diagnostic efficacy of 3-T MRI for meniscal and anterior cruciate ligament (ACL) injuries in the knee using arthroscopy as the reference standard and to compare these results with the results of a previous meta-analysis assessing 1.5-T MRI.
Materials And Methods: The online Cochrane Library, MEDLINE, and PubMed databases were searched using the following terms: MRI AND ((3 OR three) AND (Tesla OR T)) AND knee AND arthroscopy AND (menisc* OR ligament). Patient demographics, patient characteristics, MRI scanning details, and diagnostic results were investigated. The methodologic quality of the included studies was assessed using the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. A meta-analysis of studies using 3-T MRI was performed, and the results were compared with a previous meta-analysis of studies using 1.5-T MRI.
Results: One hundred one studies were identified by the search strategy, and 13 studies were included in our review. Twelve studies were considered to have level 1b evidence, and one study was considered to have level 2b evidence. All 13 studies had high methodologic integrity and low risk of bias using the QUADAS-2 tool. The studies included 1197 patients with a mean age of 41.9 years. Ten of the 13 studies were eligible for meta-analysis. The mean sensitivity and mean specificity of 3-T MRI for knee injuries by location were as follows: medial meniscus, 0.94 (95% CI, 0.91-0.96) and 0.79 (95% CI, 0.75-0.83), respectively; lateral meniscus, 0.81 (95% CI, 0.75-0.85) and 0.87 (95% CI, 0.84-0.89); and ACL, 0.92 (95% CI, 0.83-0.96) and 0.99 (95% CI, 0.96-1.00). The specificity of 3-T MRI for injuries of the lateral meniscus was significantly lower than that of 1.5-T MRI (p = 0.0013).
Conclusion: This study does not provide evidence that 3-T scanners have superior diagnostic efficacy for meniscal damage and ACL integrity when compared with previous studies of 1.5-T machines.
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http://dx.doi.org/10.2214/AJR.15.15795 | DOI Listing |
J Bone Joint Surg Am
January 2025
Shriners Children's Northern California, Sacramento, California.
Background: Magnetic resonance imaging (MRI) has not been routinely used for infants with brachial plexus birth injury (BPBI); instead, the decision to operate is based on the trajectory of clinical recovery by 6 months of age. The aim of this study was to develop an MRI protocol that can be performed without sedation or contrast in order to identify infants who would benefit from surgery at an earlier age than the age at which that decision could be made clinically.
Methods: This prospective multicenter NAPTIME (Non-Anesthetized Plexus Technique for Infant MRI Evaluation) study included infants aged 28 to 120 days with BPBI from 3 tertiary care centers.
NMR Biomed
March 2025
Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Gliomas are highly heterogeneous and often include a nonenhancing component that is hyperintense on T weighted MRI. This can often not be distinguished from secondary gliosis and surrounding edema. We hypothesized that the extent of these T hyperintense areas can more accurately be determined on high-quality 7 T MRI scans.
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, China.
Background: Multifrequency MR elastography (mMRE) enables noninvasive quantification of renal stiffness in patients with chronic kidney disease (CKD). Manual segmentation of the kidneys on mMRE is time-consuming and prone to increased interobserver variability.
Purpose: To evaluate the performance of mMRE combined with automatic segmentation in assessing CKD severity.
Radiology
January 2025
From the Department of Radiology, Division of Musculoskeletal Radiology, NYU Grossman School of Medicine, 660 1st Ave, 3rd Fl, Rm 313, New York, NY 10016 (S.S.W., J.V., R.K., E.H.P., J.F.); Department for Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, University Hospital Tübingen, Tübingen, Germany (S.S.W.); Department of Radiology, University Hospital Basel, Basel, Switzerland (J.V.); Department of Radiology, Hospital do Coraçao, São Paulo, Brazil (T.C.R.); Academic Surgical Unit, South West London Elective Orthopaedic Centre (SWLEOC), London, United Kingdom (D.D.); Department of Radiology, Balgrist University Hospital, Zurich, Switzerland (B.F.); Department of Radiology, Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Research Institute of Clinical Medicine of Jeonbuk National University, Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Medscanlagos Radiology, Cabo Frio, Brazil (A.S.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Siemens Healthineers AG, Erlangen, Germany (I.B.); and Siemens Medical Solutions USA, Malvern, Pa (G.K.).
Background Deep learning (DL) methods can improve accelerated MRI but require validation against an independent reference standard to ensure robustness and accuracy. Purpose To validate the diagnostic performance of twofold-simultaneous-multislice (SMSx2) twofold-parallel-imaging (PIx2)-accelerated DL superresolution MRI in the knee against conventional SMSx2-PIx2-accelerated MRI using arthroscopy as the reference standard. Materials and Methods Adults with painful knee conditions were prospectively enrolled from December 2021 to October 2022.
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, Peking University Third Hospital, Beijing, China.
Background: The spinal column is a frequent site for metastases, affecting over 30% of solid tumor patients. Identifying the primary tumor is essential for guiding clinical decisions but often requires resource-intensive diagnostics.
Purpose: To develop and validate artificial intelligence (AI) models using noncontrast MRI to identify primary sites of spinal metastases, aiming to enhance diagnostic efficiency.
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