Literature DB >> 33132027

The Value of Preprocedural MR Imaging in Genicular Artery Embolization for Patients with Osteoarthritic Knee Pain.

Jin Woo Choi1, Du Hyun Ro2, Hee Dong Chae3, Dong Hyun Kim4, Myungsu Lee3, Saebeom Hur3, Hyo-Cheol Kim3, Hwan Jun Jae3, Jin Wook Chung3.   

Abstract

PURPOSE: To determine the value of preprocedural MR imaging in genicular artery embolization (GAE) for patients with osteoarthritic knee pain.
MATERIALS AND METHODS: This single-center study retrospectively analyzed 28 knees in 18 patients who underwent GAE for intractable knee pain < 1 month after MR imaging. The pain experienced in each knee was evaluated on a 100-mm visual analog scale (VAS) at baseline and 1- and 3-month after GAE. "GAE responders" were defined as knees that exhibited greater than 30% reduction of VAS pain scores from baseline at both follow-up visits. Musculoskeletal radiologists evaluated MR images of the affected knee compartment regarding cartilage defects, osteophytes, subchondral cysts, bone marrow lesions (BMLs), meniscal injury, and joint effusion. The performances of Kellgren-Lawrence (KL) grading and MR findings in predicting GAE responders was estimated based on receiver operating characteristic curves.
RESULTS: The mean VAS pain score was 84.3 mm. BML (area under the curve [AUC], 0.860; P < .001), meniscal injury (AUC, 0.811; P = .003), and KL grading (AUC, 0.898; P < .001) were significantly associated with GAE outcome. To predict GAE responders, KL grade ≤ 2 yielded a sensitivity of 87.5% and a specificity of 60.9%, BML grade ≤ 1 yielded a sensitivity of 75.0% and a specificity of 69.6%, and meniscal injury grade ≤ 2 yielded a sensitivity of 83.3% and a specificity of 72.7%.
CONCLUSIONS: Large BMLs and severe meniscal injuries on MR imaging, as well as high KL grades, indicated poor responses to GAE.
Copyright © 2020 SIR. Published by Elsevier Inc. All rights reserved.

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Year:  2020        PMID: 33132027     DOI: 10.1016/j.jvir.2020.08.012

Source DB:  PubMed          Journal:  J Vasc Interv Radiol        ISSN: 1051-0443            Impact factor:   3.464


  1 in total

1.  Deconstruction of Knee Cartilage Injury in Athletes Using MR Images Based on Artificial Intelligence Segmentation Algorithm.

Authors:  Yuze Zhang; Hao Lian; Yinghai Liu
Journal:  Contrast Media Mol Imaging       Date:  2022-09-27       Impact factor: 3.009

  1 in total

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