Objective: To determine the accuracy of interpretation of a non-contrast MRI protocol in characterizing adnexal masses.
Methods And Materials: Two hundred ninety-one patients (350 adnexal masses) who underwent gynecological MRI at our institution between the 1 of January 2008 and the 31 of December 2018 were reviewed. A random subset (102 patients with 121 masses) was chosen to evaluate the reproducibility and repeatability of readers' assessments. Readers evaluated non-contrast MRI scans retrospectively, assigned a 5-point score for the risk of malignancy and gave a specific diagnosis. The reference standard for the diagnosis was histopathology or at least one-year imaging follow-up. Diagnostic accuracy of the non-contrast MRI score was calculated. Inter- and intra-reader agreement was analyzed with Cohen's kappa statistics.
Results: There were 53/350 (15.1%) malignant lesions in the whole cohort and 20/121 (16.5%) malignant lesions in the random subset. Good agreement between readers was found for the non-contrast MRI score (к = 0.73, 95% confidence interval [CI] 0.58-0.86) whilst the intra-reader agreement was excellent (к = 0.81, 95% CI 0.70-0.88). The non-contrast MRI score value of ≥ 4 was associated with malignancy with a sensitivity of 84.9%, a specificity of 95.9%, an accuracy of 94.2% and a positive likelihood ratio of 21 (area under the receiver operating curve 0.93, 95% CI 0.90-0.96).
Conclusion: Adnexal mass characterization on MRI without the administration of contrast medium has a high accuracy and excellent inter- and intra-reader agreement. Our results suggest that non-contrast studies may offer a reasonable diagnostic alternative when the administration of intravenous contrast medium is not possible.
Key Points: • A non-contrast pelvic MRI protocol may allow the characterization of adnexal masses with high accuracy. • The non-contrast MRI score may be used in clinical practice for differentiating benign from malignant adnexal lesions when the lack of intravenous contrast medium precludes analysis with the O-RADS MRI score.
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http://dx.doi.org/10.1007/s00330-021-07737-9 | DOI Listing |
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From the Department of Radiology, Medical Physics (MML, TJC), Department of Interventional Radiology (NS, GAC), Department of Surgery and Large Animal Studies (MAN), and the Department of Statistics (MG), University of Chicago, Chicago, IL, USA; Department of Anesthesiology (SPR), University of Illinois, Chicago, IL, USA; Department of Radiology (MSS), University of Massachusetts Chan Medical School, Worcester, MA, USA; Department of Radiology, Biomedical Engineering and Imaging Institute (Current affiliation MML), Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mount Carmel Health Systems (Current affiliation GAC), Columbus, OH, USA.
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From the Department of Department of Radiology, Brain Health Imaging Institute (A.R-F, J.I, S.P, M.d, G.C.C) Weill Cornell Medicine, New York-Presbyterian Hospital, New York, New York, USA; the Department of Neurology (A.R-F), Pontificia Universidad Javeriana, Bogota, Colombia; the Department of Radiology, Division of Molecular Imaging and Therapeutics (A.R-F, J.I) Weill Cornell Medicine, New York-Presbyterian Hospital, New York, New York, USA; the Department of Neurology (D.Z, MM, L.R, A.S.N) Weill Cornell Medicine, New York-Presbyterian Hospital, New York, New York, USA.
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Center for Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark.
Magnetic resonance imaging (MRI) is an invaluable method of choice for anatomical and functional in vivo imaging of the brain. Still, accurate delineation of the brain structures remains a crucial task of MR image evaluation. This study presents a novel analytical algorithm developed in MATLAB for the automatic segmentation of cerebrospinal fluid (CSF) spaces in preclinical non-contrast MR images of the mouse brain.
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Department of Radiology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang Uygur Autonomous Region, China. Electronic address:
3D BFFE and TRANCE can provide a visualization of pulmonary vessels without injection of contrast agent. T-SLIP can observe a large area of vessels using an arterial spin labeling technique. 3D BFFE and TRANCE with two T-SLIP placement strategies were compared on pulmonary artery imaging.
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Department of Neurosurgery, The Royal Melbourne Hospital, Victoria, Australia; Department of Surgery, The University of Melbourne, Victoria, Australia. Electronic address:
Glioblastoma remains the most common and lethal primary malignant brain tumour, with high rates of recurrence and progression despite gross-total resection of the contrast-enhancing region based on T1-weighted MRI. There has been growing interest in exploring "supramaximal" resections that extend beyond contrast-enhancing borders, with initial retrospective data suggesting survival benefit, but there is currently no consensus definition. In this systematic review, we explore the evolution of supramaximal resection in glioblastoma, dissect the incongruencies in the literature regarding its definition, qualitatively appraise each definition and discuss the results of various studies that have explored its impacts on patient outcomes.
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