Magnetic resonance imaging of the knee: An overview and update of conventional and state of the art imaging

Nacey, Nicholas C.; Geeslin, Matthew G.; Miller, G. Wilson; Pierce, Jennifer L.

doi:10.1002/jmri.25620

Cited by 59 publications

(33 citation statements)

References 95 publications

(249 reference statements)

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“…11 While several studies have found similar overall diagnostic performance in comparisons of SPGR versus T2-or intermediate-weighted (IM-weighted) FSE sequences, [12][13][14] there are advantages and pitfalls to both FSE and gradient-echo sequences Three-Dimensional Gradient-Echo-Based Pulse Sequences 3D gradient-echo sequences have utility in depicting cartilage thickness, cartilage volume, and some surface pathology but can be limited by a lack of contrast between fluid and cartilage, which can obscure both internal and surface cartilage pathology, as well as longer scan times. 11,15,16 Additionally, highresolution 3D gradient-echo sequences are more vulnerable to susceptibility artifacts and other off-resonance effects in comparison to spin echo sequences, a phenomenon that worsens with increasing field strength. 11,17 Three-Dimensional FSE Pulse Sequences IM-and T2-weighted FSE sequences have been shown to allow for high sensitivity and specificity for the assessment of cartilage lesions in multiple clinical studies.…”

Section: Mr Sequences For Morphologic Cartilage Assessmentmentioning

confidence: 99%

Magnetic Resonance Imaging of Articular Cartilage within the Knee

2018

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Magnetic resonance imaging (MRI) provides an effective and noninvasive means by which to evaluate articular cartilage within the knee. Existing techniques can be utilized to detect and monitor longitudinal changes in cartilage status due to injury or progression of degenerative disease. Quantitative MRI (qMRI) techniques can provide a metric by which to evaluate the efficacy of cartilage repair techniques and offer insight into the composition of cartilage and cartilage repair tissue. In this review, we provide background on MR signal generation and decay, the utility of morphologic MRI assessment, and qMRI techniques for the biochemical assessment of cartilage (dGEMRIC, T2, T2*, T1ρ, sodium, gagCEST). Finally, the description and utility of these qMRI techniques for the evaluation of cartilage repair are discussed.

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Section: Mr Sequences For Morphologic Cartilage Assessmentmentioning

confidence: 99%

Magnetic Resonance Imaging of Articular Cartilage within the Knee

2018

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“…Magnetic resonance imaging (MRI) of the knee is the standard-of-care imaging modality to evaluate knee disorders, and more musculoskeletal (MSK) MRI examinations are performed on the knee than on any other region of the body [ 1 – 3 ]. MRI has repeatedly demonstrated high accuracy for the diagnosis of meniscal and cruciate ligament pathology [ 4 – 7 ] and is routinely used to identify those who would benefit from surgery [ 8 – 10 ].…”

Section: Introductionmentioning

confidence: 99%

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

et al. 2018

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BackgroundMagnetic resonance imaging (MRI) of the knee is the preferred method for diagnosing knee injuries. However, interpretation of knee MRI is time-intensive and subject to diagnostic error and variability. An automated system for interpreting knee MRI could prioritize high-risk patients and assist clinicians in making diagnoses. Deep learning methods, in being able to automatically learn layers of features, are well suited for modeling the complex relationships between medical images and their interpretations. In this study we developed a deep learning model for detecting general abnormalities and specific diagnoses (anterior cruciate ligament [ACL] tears and meniscal tears) on knee MRI exams. We then measured the effect of providing the model’s predictions to clinical experts during interpretation.Methods and findingsOur dataset consisted of 1,370 knee MRI exams performed at Stanford University Medical Center between January 1, 2001, and December 31, 2012 (mean age 38.0 years; 569 [41.5%] female patients). The majority vote of 3 musculoskeletal radiologists established reference standard labels on an internal validation set of 120 exams. We developed MRNet, a convolutional neural network for classifying MRI series and combined predictions from 3 series per exam using logistic regression. In detecting abnormalities, ACL tears, and meniscal tears, this model achieved area under the receiver operating characteristic curve (AUC) values of 0.937 (95% CI 0.895, 0.980), 0.965 (95% CI 0.938, 0.993), and 0.847 (95% CI 0.780, 0.914), respectively, on the internal validation set. We also obtained a public dataset of 917 exams with sagittal T1-weighted series and labels for ACL injury from Clinical Hospital Centre Rijeka, Croatia. On the external validation set of 183 exams, the MRNet trained on Stanford sagittal T2-weighted series achieved an AUC of 0.824 (95% CI 0.757, 0.892) in the detection of ACL injuries with no additional training, while an MRNet trained on the rest of the external data achieved an AUC of 0.911 (95% CI 0.864, 0.958). We additionally measured the specificity, sensitivity, and accuracy of 9 clinical experts (7 board-certified general radiologists and 2 orthopedic surgeons) on the internal validation set both with and without model assistance. Using a 2-sided Pearson’s chi-squared test with adjustment for multiple comparisons, we found no significant differences between the performance of the model and that of unassisted general radiologists in detecting abnormalities. General radiologists achieved significantly higher sensitivity in detecting ACL tears (p-value = 0.002; q-value = 0.019) and significantly higher specificity in detecting meniscal tears (p-value = 0.003; q-value = 0.019). Using a 1-tailed t test on the change in performance metrics, we found that providing model predictions significantly increased clinical experts’ specificity in identifying ACL tears (p-value < 0.001; q-value = 0.006). The primary limitations of our study include lack of surgical ground truth and the small size of ...

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“…Magnetic resonance imaging (MRI) is considered to be the most accurate method for imaging the internal knee joint structure, with sensitivities in detecting medial meniscus lesions ranging from 83% to 94% [41,42,43]. The ESSKA meniscus consensus group recommended MRI when arthroscopy is considered to identify concomitant pathologies [17].…”

Section: Discussionmentioning

confidence: 99%

Clinical practice and postoperative rehabilitation after knee arthroscopy vary according to surgeons’ expertise: a survey among Polish Arthroscopy Society members.

Bąkowski

Bąkowska-Żywicka²,

Piontek

2020

Preprint

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Background: Meniscus repair is a challenging task in knee arthroscopy. Currently, there are a variety of arthroscopic methods available for meniscus repair. The purpose of this study was to determine a consensus in meniscus tear treatment in the environment of Polish orthopaedists.Methods: A total of 205 registered orthopaedic surgeons participated in the surveys. The survey consisted of 35 questions regarding general arthroscopy and postoperative management, including physicians’ level of expertise, anaesthesia, postoperative treatment, rehabilitation and procedures performed. Comparisons were made between knee arthroscopy experts (> 100 arthroscopies performed per year) and non-experts (≤ 100 cases) on aspects of patient care.Results: The most important finding of this study was the agreement among almost all aspects of the knee arthroscopy approach. Consensus among Polish surgeons was noticed in choosing regional anaesthesia for knee arthroscopy, the lack of need for knee braces and knee medications, the of use of LMW heparin for thromboprophylaxis, 1-2 days of hospitalization, the recommendation of rehabilitation and the use of magnetic resonance as a diagnostic test for meniscus damage. Surgical expertise was significantly associated with the performance of meniscus suture procedures (p = 0.009). Experts recommended starting rehabilitation on the day of surgery (p=0.007) and were more likely to use objective physical tests (p=0.003). Non-expert surgeons recommended a longer period from meniscus suture to full-range knee motion (p=0.001) and admitted that patient age does matter for meniscus repair qualification (p=0.002).Conclusions: There is consensus among almost all issues of meniscus tear treatment in the environment of Polish orthopaedists; however, the issues of rehabilitation and the use of advanced meniscus repair techniques are associated with surgical expertise.

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Magnetic resonance imaging of the knee: An overview and update of conventional and state of the art imaging

Abstract: 5 J. MAGN. RESON. IMAGING 2017;45:1257-1275.

Cited by 59 publications

References 95 publications

Magnetic Resonance Imaging of Articular Cartilage within the Knee

Magnetic Resonance Imaging of Articular Cartilage within the Knee

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

Clinical practice and postoperative rehabilitation after knee arthroscopy vary according to surgeons’ expertise: a survey among Polish Arthroscopy Society members.

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