Meniscal Surgery: Risk of Radiographic Joint Space Narrowing Progression and Subsequent Knee Replacement—Data from the Osteoarthritis Initiative

Zikria, Bashir A.; Hafezi-Nejad, Nima; Roemer, Frank W.; Guermazi, Ali; Demehri, Shadpour

doi:10.1148/radiol.2016160092

Cited by 14 publications

(6 citation statements)

References 42 publications

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“…Treatment can be divided into conservative and surgical management options, depending on a variety of factors, including the shape, size, and location of the meniscus tear, as well as the age and physical activity of the patient [7][8][9][10]. Adequate treatment may reduce sequela of meniscus tears, improve quality of life, and reduce health care costs [11][12][13][14]. Therefore, accurate diagnosis of meniscus tears is important.…”

Section: Introductionmentioning

confidence: 99%

Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference

Fritz

Marbach²,

Civardi³

et al. 2020

Skeletal Radiol

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Objective To clinically validate a fully automated deep convolutional neural network (DCNN) for detection of surgically proven meniscus tears. Materials and methods One hundred consecutive patients were retrospectively included, who underwent knee MRI and knee arthroscopy in our institution. All MRI were evaluated for medial and lateral meniscus tears by two musculoskeletal radiologists independently and by DCNN. Included patients were not part of the training set of the DCNN. Surgical reports served as the standard of reference. Statistics included sensitivity, specificity, accuracy, ROC curve analysis, and kappa statistics. Results Fifty-seven percent (57/100) of patients had a tear of the medial and 24% (24/100) of the lateral meniscus, including 12% (12/100) with a tear of both menisci. For medial meniscus tear detection, sensitivity, specificity, and accuracy were for reader 1: 93%, 91%, and 92%, for reader 2: 96%, 86%, and 92%, and for the DCNN: 84%, 88%, and 86%. For lateral meniscus tear detection, sensitivity, specificity, and accuracy were for reader 1: 71%, 95%, and 89%, for reader 2: 67%, 99%, and 91%, and for the DCNN: 58%, 92%, and 84%. Sensitivity for medial meniscus tears was significantly different between reader 2 and the DCNN (p = 0.039), and no significant differences existed for all other comparisons (all p ≥ 0.092). The AUC-ROC of the DCNN was 0.882, 0.781, and 0.961 for detection of medial, lateral, and overall meniscus tear. Inter-reader agreement was very good for the medial (kappa = 0.876) and good for the lateral meniscus (kappa = 0.741). Conclusion DCNN-based meniscus tear detection can be performed in a fully automated manner with a similar specificity but a lower sensitivity in comparison with musculoskeletal radiologists.

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Section: Introductionmentioning

confidence: 99%

Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference

Fritz

Marbach²,

Civardi³

et al. 2020

Skeletal Radiol

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“…Although more and more randomized trials including patients with symptomatic KOA and meniscal tears found no greater benefit with arthroscopic surgery followed by physical therapy, [30,33] compared with physical therapy alone, our observational study showed high rates of functional improvement, despite of serious radiologic KOA progression within patients after arthroscopic partial meniscectomy and debridement. We believe that meniscus surgery can promote radiologic KOA progression [34] ; however, patient's conscious symptoms and radiological presentations are not completely consistent and even contradictor each other, and some patients were well satisfied with surgical effect while imaging revealed a severe degree of KOA progression. The degree of joint space narrowing does not fully represent the degree of degeneration of the joint.…”

Section: Discussionmentioning

confidence: 99%

Effect of medial meniscus extrusion on arthroscopic surgery outcome in the osteoarthritic knee associated with medial meniscus tear

Wang

et al. 2019

Chinese Medical Journal

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Background:The potential benefit of arthroscopic surgery for osteoarthritic knee associated with medial meniscus tear is controversial. This study was conducted to determine the effect of pre-operative medial meniscus extrusion (MME) on arthroscopic surgery outcomes in the osteoarthritic knee associated with medial meniscus tear during a minimum 4-year follow-up.Methods:This was a retrospective review of a total of 131 patients diagnosed with osteoarthritic knee associated with medial symptomatic degenerative meniscus tear who underwent arthroscopic surgery from January 2012 to December 2014 and were observed for more than 4 years. Patients were classified into two groups: MME ≥3 mm (major MME group, n = 54) and MME <3 mm (non-major MME group, n = 77). Clinical assessments, including the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, and radiographic assessments, including the Kellgren-Lawrence (K-L) grade and medial joint space width (JSW), were evaluated pre-operatively and at final follow-up. The longitudinal changes of clinical and radiographic parameters (WOMAC and the medial JSW change, K-L grade progression) were compared between groups unadjusted and adjusted for age, sex, and body mass index. Four-year survival rates (without progression to knee replacement [KR]) were also evaluated using a log-rank test and Cox proportional hazard regression model.Results:Major MME was present in 41% of patients. After a minimum 4-year follow-up, the mean WOMAC total and pain scores improved significantly in both groups. However, the medial JSW and K-L grade worsened significantly. Patients with pre-operative major MME worsened more in WOMAC total (adjusted mean difference [MD] 3.800, 95% confidence interval [CI]: 0.900, 11.400; P = 0.037) and function (adjusted MD 3.100, 95% CI: 0.700, 6.300; P = 0.038) scores than patients with pre-operative non-major MME, and no significant difference was observed in WOMAC pain and stiffness score between groups. The group with major MME had significantly higher joint space narrowing (adjusted MD −0.630, 95% CI: −1.250, −0.100; P = 0.021) and K-L rate progression (adjusted mean relative risk [RR] 1.310, 95% CI: 1.100, 1.600; P = 0.038) than the group with non-major MME. There was a significantly more KR progression in patients with major MME compared with those with non-major MME (adjusted RR 3.100, 95% CI: 1.100, 9.200; P = 0.042 and adjusted hazard ratio 3.500, 95% CI 1.100, 9.500; P = 0.022).Conclusions:Osteoarthritic knee patients associated with medial meniscus tear with non-major MME are more responsive to arthroscopic surgery in terms of the clinical and radiologic outcomes and survival for at least 4-year follow-up; however, in terms of pain relief, arthroscopic surgery in patients with major MME is also beneficial as well as in patients with non-major MME.

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“…The fibrocartilaginous meniscus is commonly injured, can lead to accelerated cartilage wear, and is frequently managed surgically with the rise in popularity of meniscus-preserving surgeries. 34,35 MRI remains the noninvasive modality of choice for the diagnosis of meniscal tears that are characterized by abnormal meniscal morphology and/or signal intensity. 36 Diagnostic performance of MRI when interpreted by radiologists in terms of sensitivity and specificity is 93% and 88% for medial meniscus tears and 79% and 96% for the lateral meniscus.…”

Section: Meniscus Meniscus Evaluation: Mrimentioning

confidence: 99%

The Use of Artificial Intelligence in the Evaluation of Knee Pathology

Garwood

Tai

Joshi

et al. 2020

Semin Musculoskelet Radiol

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Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic evaluation of knee pathology. Experimental algorithms have already been developed that can assess the severity of knee osteoarthritis from radiographs, detect and classify cartilage lesions, meniscal tears, and ligament tears on magnetic resonance imaging, provide automatic quantitative assessment of tendon healing, detect fractures on radiographs, and predict those at highest risk for recurrent bone tumors. This article reviews and summarizes the most current literature.

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Meniscal Surgery: Risk of Radiographic Joint Space Narrowing Progression and Subsequent Knee Replacement—Data from the Osteoarthritis Initiative

Cited by 14 publications

References 42 publications

Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference

Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference

Effect of medial meniscus extrusion on arthroscopic surgery outcome in the osteoarthritic knee associated with medial meniscus tear

The Use of Artificial Intelligence in the Evaluation of Knee Pathology

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