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Diagnostic Accuracy of Magnetic Resonance Imaging in the Detection of Type and Location of Meniscus Tears: Comparison with Arthroscopic Findings.

ABSTRACT: Magnetic resonance imaging (MRI) has been widely used for the diagnosis of meniscal tears, but its diagnostic accuracy, depending on the type and location, has not been well investigated. We aimed to evaluate the diagnostic accuracy of MRI by comparing MRI and arthroscopic findings. Preoperative 3.0-T MRI and arthroscopic findings from 2005 to 2018 were reviewed to determine the presence, type, and location of meniscus tears. In addition, subgroup analysis was performed according to anterior cruciate ligament (ACL) injury. The exclusion criteria were as follows: (1) Inflammatory arthritis, (2) other ligament injuries, (3) inability to classify meniscal tears due to degenerative arthritis, (4) over 90 days from MRI to surgery, and (5) incomplete data. Of the 2998 eligible patients, 544 were finally included. The sensitivity and specificity of MRI in determining medial and lateral meniscus tears were 91.8% and 79.9%, and 80.8% and 85.4%, respectively. The accuracy of MRI in the ACL-injured group was lower than that in the ACL-intact group (medial meniscus: 81.7% vs. 88.1%, p = 0.041; 72.9% vs. lateral meniscus: 88.0%, p < 0.001). MRI accuracy was low for the longitudinal tears of the posterior horn of the medial meniscus in the ACL-injured group. MRI could be a diagnostic tool for meniscus tears, but has limited accuracy in their classification of the type and location. Hence, care should be taken during arthroscopic assessment of ACL-injured patients due to low diagnostic accuracy of preoperative MRI.

SUBMITTER: Kim SH

PROVIDER: S-EPMC7914628 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Diagnostic Accuracy of Magnetic Resonance Imaging in the Detection of Type and Location of Meniscus Tears: Comparison with Arthroscopic Findings.

Kim Seong Hwan SH Lee Han-Jun HJ Jang Ye-Hoon YH Chun Kwang-Jin KJ Park Yong-Beom YB

Journal of clinical medicine 20210205 4

Magnetic resonance imaging (MRI) has been widely used for the diagnosis of meniscal tears, but its diagnostic accuracy, depending on the type and location, has not been well investigated. We aimed to evaluate the diagnostic accuracy of MRI by comparing MRI and arthroscopic findings. Preoperative 3.0-T MRI and arthroscopic findings from 2005 to 2018 were reviewed to determine the presence, type, and location of meniscus tears. In addition, subgroup analysis was performed according to anterior cru ...[more]

PMID: 33562787

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Project description:ObjectivesTo review and compare the accuracy of convolutional neural networks (CNN) for the diagnosis of meniscal tears in the current literature and analyze the decision-making processes utilized by these CNN algorithms.Materials and methodsPubMed, MEDLINE, EMBASE, and Cochrane databases up to December 2022 were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement. Risk of analysis was used for all identified articles. Predictive performance values, including sensitivity and specificity, were extracted for quantitative analysis. The meta-analysis was divided between AI prediction models identifying the presence of meniscus tears and the location of meniscus tears.ResultsEleven articles were included in the final review, with a total of 13,467 patients and 57,551 images. Heterogeneity was statistically significantly large for the sensitivity of the tear identification analysis (I2 = 79%). A higher level of accuracy was observed in identifying the presence of a meniscal tear over locating tears in specific regions of the meniscus (AUC, 0.939 vs 0.905). Pooled sensitivity and specificity were 0.87 (95% confidence interval (CI) 0.80-0.91) and 0.89 (95% CI 0.83-0.93) for meniscus tear identification and 0.88 (95% CI 0.82-0.91) and 0.84 (95% CI 0.81-0.85) for locating the tears.ConclusionsAI prediction models achieved favorable performance in the diagnosis, but not location, of meniscus tears. Further studies on the clinical utilities of deep learning should include standardized reporting, external validation, and full reports of the predictive performances of these models, with a view to localizing tears more accurately.Clinical relevance statementMeniscus tears are hard to diagnose in the knee magnetic resonance images. AI prediction models may play an important role in improving the diagnostic accuracy of clinicians and radiologists.Key points• Artificial intelligence (AI) provides great potential in improving the diagnosis of meniscus tears. • The pooled diagnostic performance for artificial intelligence (AI) in identifying meniscus tears was better (sensitivity 87%, specificity 89%) than locating the tears (sensitivity 88%, specificity 84%). • AI is good at confirming the diagnosis of meniscus tears, but future work is required to guide the management of the disease.

Project description:BackgroundQuantification of myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) by cardiovascular magnetic resonance (CMR) perfusion requires sampling of the arterial input function (AIF). While variation in the AIF sampling location is known to impact quantification by CMR and positron emission tomography (PET) perfusion, there is no evidence to support the use of a specific location based on their diagnostic accuracy in the detection of coronary artery disease (CAD). This study aimed to evaluate the accuracy of stress MBF and MPR for different AIF sampling locations for the detection of abnormal myocardial perfusion with expert visual assessment as the reference.MethodsTwenty-five patients with suspected or known CAD underwent vasodilator stress-rest perfusion with a dual-sequence technique at 3T. A low-resolution slice was acquired in 3-chamber view to allow AIF sampling at five different locations: left atrium (LA), basal left ventricle (bLV), mid left ventricle (mLV), apical left ventricle (aLV) and aortic root (AoR). MBF and MPR were estimated at the segmental level using Fermi function-constrained deconvolution. Segments were scored as having normal or abnormal perfusion by visual assessment and the diagnostic accuracy of stress MBF and MPR for each location was evaluated using receiver operating characteristic curve analysis.ResultsIn both normal (300 out of 400, 75 %) and abnormal segments, rest MBF, stress MBF and MPR were significantly different across AIF sampling locations (p < 0.001). Stress MBF for the AoR (normal: 2.42 (2.15-2.84) mL/g/min; abnormal: 1.71 (1.28-1.98) mL/g/min) had the highest diagnostic accuracy (sensitivity 80 %, specificity 85 %, area under the curve 0.90; p < 0.001 versus stress MBF for all other locations including bLV: normal: 2.78 (2.39-3.14) mL/g/min; abnormal: 2.22 (1.83-2.48) mL/g/min; sensitivity 91 %, specificity 63 %, area under the curve 0.81) and performed better than MPR for the LV locations (p < 0.01). MPR for the AoR (normal: 2.43 (1.95-3.14); abnormal: 1.58 (1.34-1.90)) was not superior to MPR for the bLV (normal: 2.59 (2.04-3.20); abnormal: 1.69 (1.36-2.14); p = 0.717).ConclusionsThe AIF sampling location has a significant impact on MBF and MPR estimates by CMR perfusion, with AoR-based stress MBF comparing favorably to that for the current clinical reference bLV.

Project description:BackgroundMyocardial perfusion cardiovascular magnetic resonance (CMR) is a well-established method for detection of ischemic heart disease. However, ECG gating problems can result in image degradation and non-diagnostic scans, particularly in patients with arrhythmias.MethodsA turboFLASH saturation recovery pulse sequence was used without any ECG triggering. One saturation pulse followed by 4-5 slices of undersampled radial k-space images was acquired rapidly, on the order of 40-50 msec per image. The acquisition of the set of 4-5 slices was continuously repeated approximately 4 times per second. An iterative constrained reconstruction method was used to reconstruct the ungated images. The ungated perfusion images were post-processed into three different sets of images (ungated, self-gated to near systole, and self-gated to near diastole). To test the ungated approach and compare the different processing methods, 8 patients scheduled for coronary angiography underwent stress and rest perfusion imaging with the ungated acquisition. Six patients had a history of atrial fibrillation (AF). Three blinded readers assessed image quality and presence/absence of disease.ResultsAll 8 subjects successfully completed the perfusion CMR protocol and 7/8 underwent coronary angiography. Three patients were in atrial fibrillation during CMR. Overall, the CMR images were of high quality as assessed by the three readers. There was little difference in image quality between patients in AF compared to those in sinus rhythm (3.6±0.7 vs. 3.3±0.5). Stress/rest perfusion imaging showed normal perfusion in 4 patients, fixed perfusion defects in 2 patients, and reversible perfusion defects in 2 patients, corresponding with angiographic results. Pooled results from the independent readers gave a sensitivity of 0.92 (CI 0.65-0.99) and specificity of 0.92 (CI 0.65-0.99) for the detection of coronary artery disease using ungated perfusion imaging. The same sensitivity, and a specificity of 1 (CI 0.76-1), was achieved when the images were self-gated after acquisition into near systole or near diastole.ConclusionsUngated radial dynamic perfusion CMR can give high quality imaging in patients in sinus rhythm and during atrial fibrillation. In this small cohort, high diagnostic accuracy was possible with this rapid perfusion imaging sequence. An ungated approach simplifies the acquisition and could expand the role of perfusion CMR to include patients with arrhythmia and those with gating problems.

Project description:Meniscus root tears are increasingly being recognized and treated because of improved awareness and diagnostics. These injuries commonly occur in combination with knee ligament injuries. Untreated posterior meniscus root teats have been demonstrated to increase contact pressure and decrease contact area, ultimately leading to unfavorable joint loading and development of early osteoarthritis. Posterior lateral meniscus root tears (PLMRTs) also have been reported to increase anterior tibial translation and pivot shift in anterior cruciate ligament–deficient knees. Therefore, it is crucial to repair meniscal root tears when possible to restore knee joint loading and kinematics. Several techniques for repair of the PLMRT have been described. In this Technical Note, we describe our preferred technique for repair of PLMRT using an all-suture anchor. This technique is reproducible, does not need a tunnel, mitigates bungee effect of transtibial technique, and the anchor can easily be inserted on the footprint without a need for a guide. Technique Video Video 1 We present our arthroscopic repair of posterior root tears of the lateral meniscus with all-suture anchor. The surgical procedure is performed with the patient under epidural anesthesia in the supine position. A padded, nonsterile tourniquet is placed high on the operative thigh, and the patient is positioned with lateral support at the level of the tourniquet and a foot post to allow the knee to be maintained at 90° of flexion when required. The operative leg is prepared and draped in standard fashion. Standard anterolateral and anteromedial portals are created for routine diagnostic arthroscopy. The torn meniscal root should be probed to assess for severity and tear pattern. First with a burr and then with a curved curette, the tibial attachment site of the torn lateral meniscus root is debrided of soft tissues and overlying cartilage down to a bleeding bone bed to improve healing of the repair. Appropriate knee flexion is key to achieve a correct anchor placement. Therefore, an accessory high anteromedial portal is created with the knee hyperflexed. A curved guide is inserted through the high anteromedial portal and the guide is placed at the prepared insertion site of the footprint. A pilot hole is created at an appropriate angle using a 1.8-mm flexible drill. Afterwards, a 1.8 mm all-suture anchor loaded with a FiberWire no. 2 is placed. We recommend to set the anchor and test its stability by pulling on the sutures. The leg is then brought into the figure-of-4 position. The sutures are retrieved through the standard anteromedial portal. A direct suture passer and retriever is loaded into the bottom jaw, and it is then introduced through the standard anteromedial portal. Once the suture passer and retriever has been positioned at the desired location on the meniscus, the top jaw is closed and the back trigger is squeezed to advance suture through the tissue bottom up. With the suture captured in the top jaw, the Knee Scorpion is retracted from the tissue. The same procedure is then repeated in the posterior part of the meniscus with the second, free-end of the suture. A simple arthroscopic knot is then tightened under direct arthroscopic visualization aiming for the correct amount of tension. Finally, with a FiberTape Cutter, the FiberWire is cut and the strength of the suture fixation is tested with a probe.

Project description:BackgroundThis study aimed to systematically evaluate the value of magnetic resonance imaging (MRI) and magnetic resonance arthrography (MRA) in the diagnosis of acetabular labral tears.MethodsDatabases including PubMed, Embase, Cochrane Library, Web of Science, CBM, CNKI, WanFang Data, and VIP were electronically searched to collect relevant studies on magnetic resonance in the diagnosis of acetabular labral tears from inception to September 1, 2021. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias in the included studies by using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. RevMan 5.3, Meta Disc 1.4, and Stata SE 15.0 were used to investigate the diagnostic value of magnetic resonance in patients with acetabular labral tears.ResultsA total of 29 articles were included, involving 1385 participants and 1367 hips. The results of the meta-analysis showed that the pooled sensitivity, pooled specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, pooled diagnostic odds ratio, area under the curve of the summary receiver operating characteristic, and Q* of MRI for diagnosing acetabular labral tears were 0.77 (95% confidence interval [CI], 0.75-0.80), 0.74 (95% CI, 0.68-0.80), 2.19 (95% CI, 1.76-2.73), 0.48 (95% CI, 0.36-0.65), 4.86 (95% CI, 3.44-6.86), 0.75, and 0.69, respectively. The pooled sensitivity, pooled specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, pooled diagnostic odds ratio, area under the curve of the summary receiver operating characteristic, and Q* of MRA for diagnosing acetabular labral tears were 0.87 (95% CI, 0.84-0.89), 0.64 (95% CI, 0.57-0.71), 2.23 (95% CI, 1.57-3.16), 0.21 (95% CI, 0.16-0.27), 10.47 (95% CI, 7.09-15.48), 0.89, and 0.82, respectively.ConclusionMRI has high diagnostic efficacy for acetabular labral tears, and MRA has even higher diagnostic efficacy. Due to the limited quality and quantity of the included studies, the above results should be further validated.

Dataset Information

Diagnostic Accuracy of Magnetic Resonance Imaging in the Detection of Type and Location of Meniscus Tears: Comparison with Arthroscopic Findings.

Publications

Diagnostic Accuracy of Magnetic Resonance Imaging in the Detection of Type and Location of Meniscus Tears: Comparison with Arthroscopic Findings.

Similar Datasets

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