Literature DB >> 32374669

Comparison of Clinical and Semiquantitative Cartilage Grading Systems in Predicting Outcomes After Arthroscopic Partial Meniscectomy.

Ceylan Colak1, Joshua M Polster1, Nancy A Obuchowski2, Morgan H Jones3, Greg Strnad3, Soterios Gyftopoulos4, Kurt P Spindler3, Naveen Subhas1.   

Abstract

OBJECTIVE. Cartilage loss on preoperative knee MRI is a predictor of poor outcomes after arthroscopic partial meniscectomy. The purpose of this study was to compare the ability to predict outcomes after arthroscopic partial meniscectomy with a clinically used modified Outerbridge system versus a semiquantitative MRI Osteoarthritis Knee Score system for grading cartilage loss. MATERIALS AND METHODS. Patients who underwent preoperative knee MRI within 6 months of arthroscopic partial meniscectomy and who had outcomes available from the time of surgery and 1 year later were eligible for inclusion. Cases were evaluated by two radiologists and one radiology fellow with the use of both grading systems. The accuracy of each system in discriminating between surgical success and failure was estimated using the ROC curve (AUC) with 95% CIs. A Wald test was used to assess noninferiority of the clinical grading system. Interreader agreement regarding the accuracy of the grading systems in predicting outcomes was also compared. RESULTS. A total of 78 patients (38 women and 40 men; mean age, 56.6 years) were included in the study. A prediction model using clinical grading (AUC = 0.695; 95% CI, 0.566-0.824) was noninferior (p = 0.047) to a model using MRI Osteoarthritis Knee Score grading (AUC = 0.683; 95% CI, 0.539-0.827). Both MRI prediction models performed better than a model using demographic characteristics only (AUC = 0.667; 95% CI, 0.522-0.812). Inter-reader agreement with clinical grading (80.8%) was higher than that with MRI Osteoarthritis Knee Score grading (65.0%; p = 0.012). CONCLUSION. A clinically used system to grade cartilage loss on MRI is as effective as a semiquantitative system for predicting outcomes after arthroscopic partial meniscectomy, while also offering improved interreader agreement.

Entities:  

Keywords:  MRI Osteoarthritis Knee Score; knee MRI; meniscectomy; osteoarthritis; outcomes

Year:  2020        PMID: 32374669     DOI: 10.2214/AJR.19.22285

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  3 in total

1.  Automated knee cartilage segmentation for heterogeneous clinical MRI using generative adversarial networks with transfer learning.

Authors:  Mingrui Yang; Ceylan Colak; Kishore K Chundru; Sibaji Gaj; Andreas Nanavati; Morgan H Jones; Carl S Winalski; Naveen Subhas; Xiaojuan Li
Journal:  Quant Imaging Med Surg       Date:  2022-05

2.  Specimen specific imaging and joint mechanical testing data for next generation virtual knees.

Authors:  Snehal Chokhandre; Erica E Neumann; Tara F Nagle; Robb W Colbrunn; Chris A Flask; Ceylan Colak; Jason Halloran; Ahmet Erdemir
Journal:  Data Brief       Date:  2021-01-30

3.  Establishment of a New Qualitative Evaluation Method for Articular Cartilage by Dynamic T2w MRI Using a Novel Contrast Medium as a Water Tracer.

Authors:  Yoshiaki Hosokawa; Tomohiro Onodera; Kentaro Homan; Jun Yamaguchi; Kohsuke Kudo; Hiroyuki Kameda; Hiroyuki Sugimori; Norimasa Iwasaki
Journal:  Cartilage       Date:  2022 Jul-Sep       Impact factor: 3.117

  3 in total

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