Detection Of Cartilage Lesions Research Articles

Added Value of MRI Knee Cartigram in Assessment of Anterior Knee Pain in Comparison to Conventional Standard MRI

Background Osteoarthritis (OA) is a multi-tissue, multi-factorial disease and worldwide a major cause of disability resulting from reduced joint mobility and function. Progressive loss of hyaline cartilage is one of the hallmark features of osteoarthritis, initiated by a loss of proteoglycans and an increase in water content, followed by a loss of type II collagen and a change in collagen fiber orientation. Objective To evaluate the role of T2 mapping in detection of degenerative changes in articular cartilage of knee joint as compared to standard clinical magnetic resonance imaging (MRI) at 1.5T. Patients and Methods From April 2020 to November 2020, this prospective Study was done to use T2 mapping to visualize the articular cartilage of the knee on 1.5 T MR Scanner using special software to evaluate the efficiency Of T2 mapping to detect cartilage lesions. The material of this study included 380 patients. The study includes all of them come complaining of knee pain and 2 of them had previous minor knee trauma, each patient had a single MRI exanimation including conventional MRI routine protocol and added a single complementary T2 mapping. Results there were significant differences between T2 mapping and conventional MRI sequence in the ability to detect cartilage degeneration as T2 mapping was capable of detecting all lesions that were visible on the clinical MRI. Moreover, T2 mapping showed more cartilage lesions than clinical MRI T2 mapping showed more cartilage lesions than clinical MRI, and in T2 maps the lesions appeared generally wider. This proposes that T2 mapping is feasible in the clinical setting and may reveal cartilage lesions not seen on the standard knee MRI. Conclusion Our results suggest that T2 mapping is an interesting MRI sequence for the exploration of patients articular cartilage in and should be included in the routine protocol if cartilage pathology is suspecting as it may improve the diagnostic accuracy of MRI for focal chondral lesions, and should help decide whether and MR-arthrography or CT-arthrography is necessary.

Deep learning applications in osteoarthritis imaging.

Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will provide a review of current applications of DL in osteoarthritis (OA) imaging, including methods used for cartilage lesion detection, OA diagnosis, cartilage segmentation, and OA risk assessment. DL techniques have been shown to have similar diagnostic performance as human readers for detecting and grading cartilage lesions within the knee on MRI. A variety of DL methods have been developed for detecting and grading the severity of knee OA and various features of knee OA on X-rays using standardized classification systems with diagnostic performance similar to human readers. Multiple DL approaches have been described for fully automated segmentation of cartilage and other knee tissues and have achieved higher segmentation accuracy than currently used methods with substantial reductions in segmentation times. Various DL models analyzing baseline X-rays and MRI have been developed for OA risk assessment. These models have shown high diagnostic performance for predicting a wide variety of OA outcomes, including the incidence and progression of radiographic knee OA, the presence and progression of knee pain, and future total knee replacement. The preliminary results of DL applications in OA imaging have been encouraging. However, many DL techniques require further technical refinement to maximize diagnostic performance. Furthermore, the generalizability of DL approaches needs to be further investigated in prospective studies using large image datasets acquired at different institutions with different imaging hardware before they can be implemented in clinical practice and research studies.

Inter-Rater Reliability of Magnetic Resonance Imaging in Comparison to Computed Tomography and Wrist Arthroscopy in SLAC and SNAC Wrist.

The aim of the study was to assess the inter-rater reliability of magnetic resonance imaging (MRI) in comparison to computed tomography (CT) and wrist arthroscopy in patients with scapholunate (SLAC) or scaphoid non-union advanced collapse (SNAC) as well as to evaluate a grading score of cartilage lesions. A total of 42 patients (36 male, 6 female) at a mean age of 45 years (range: 19–65 years) with a SLAC or SNAC wrist who had a preoperative MRI and CT scan as well as underwent arthroscopy of the wrist between 2013 and 2018 were included in this study. Cartilage lesions, as assessed by MRI, CT and wrist arthroscopy, were classified by two hand surgeons in three stages. Inter-rater reliability was evaluated using the Kendall Tau-b test as well as the chi-square test to analyze for trend. The correlation between cartilage lesions, classified by arthroscopy and MRI, was low. A moderate correlation between CT and arthroscopy staging was shown. The highest inter-rater correlation was found between MRI and CT staging. An additionally performed logistic regression showed that progression of cartilage lesions as shown in MRI scans correlates with a restriction of range of motion (ROM). The level of cartilage lesion may be more severely classified in an MRI than during arthroscopy. Arthroscopy remains the gold standard in detecting cartilage lesions and thus in the decision-making process of the definitive treatment in carpal collapse.

3D MRI of Articular Cartilage.

Osteoarthritis, characterized by the breakdown of articular cartilage and other joint structures, is one of the most prevalent and disabling chronic diseases in the United States. Magnetic resonance imaging is a commonly used imaging modality to evaluate patients with joint pain. Both two-dimensional fast spin-echo sequences (2D-FSE) and three-dimensional (3D) sequences are used in clinical practice to evaluate articular cartilage. The 3D sequences have many advantages compared with 2D-FSE sequences, such as their high in-plane spatial resolution, thin continuous slices that reduce the effects of partial volume averaging, and ability to create multiplanar reformat images following a single acquisition. This article reviews the different 3D imaging techniques available for evaluating cartilage morphology, illustrates the strengths and weaknesses of 3D approaches compared with 2D-FSE approaches for cartilage imaging, and summarizes the diagnostic performance of 2D-FSE and 3D sequences for detecting cartilage lesions within the knee and hip joints.

Knee MRI Underestimates the Grade of Cartilage Lesions

Purpose: This study was conducted in order to evaluate the clinical utility of MRI in detecting cartilage lesions and its dependence on anatomical location and lesion grade. Methods: A retrospective analysis of MRI reports and arthroscopic findings was performed on 190 consecutive patients treated in one orthopaedic department. MRI protocols were prepared by 18 radiologists from 10 different MRI centers with the use of 1.5 T magnets. The image protocols were selected by reading radiologists. Four hundred and fifty-three chondral lesions in five anatomic locations were identified during this study and graded according to the ICRS classification. Sensitivity, specificity, receiver operating characteristic (ROC), and Bangdiwala’s observer agreement charts were utilized to evaluate the diagnostic performance. Results: Only approximately 30% of MRI showed an adequate cartilage status in all anatomical locations. The sensitivity ranged from 92% in healthy cartilage to 5% in grade I lesions. The specificity differed also grossly depending on the lesion grade, reaching 96.5% in grade four lesions and 38% in healthy cartilage. The medial compartment Bangdiwala’s observer agreement charts show a gross underestimation of cartilage lesions, and the area under the curve (AUC) of ROC surpasses 0.7 only in the medial femoral condyle and patella-femoral joint. Overall, the medial compartment accuracy was significantly higher than the lateral compartment. The MRI showed correspondence of its diagnostic performance with cartilage lesion severity. Conclusion: MRI underestimates the extent of cartilage injury and evaluation of cartilage defects based on MRI should be taken with caution by orthopaedic surgeons in planning surgery. Surgical planning on MRI should take cartilage lesions under consideration, even if no cartilage lesions are reported on the MRI.

Advanced compositional imaging T2 mapping sequence in detection of stages of medial knee joint compartments articular cartilage degeneration

BackgroundThe predictive value of the new imaging sequences, especially T2 mapping in assessment of articular cartilage abnormalities of the medial knee compartments in patients with medial knee pain. The purpose of this study is to evaluate the additional value of T2 mapping over using a baseline standard knee MRI to detect cartilage lesions of the medial compartments in patients representing with medial knee pain.ResultsThe study included 60 patients presented with medial knee pain, where divided into two groups ; control group (20 volunteers) with age range from 19 to 41 years old 26.80 ± 8.05 (mean ± SD) and patients (40 candidates) with age range from 13 to 57 years old with a mean age 33.00 ± 14.1 (mean ± SD).ConclusionOn adding T2 mapping sequence to the routine MRI of the knee, the sensitivity for detecting knee cartilage lesions was increased, especially in the detection of early cartilage degeneration at the medial compartment.Compositional MR imaging including T2 mapping plays an important role in the assessment of early and potentially reversible cartilage damage especially among the young population.

Value of adding a T2 mapping sequence to a routine MR imaging protocol in evaluation of articular cartilage of the knee joint

Background: Magnetic resonance imaging (MRI) allows direct visualization of all tissues of the knee joint, including the articular cartilage with direct evaluation of chondral lesions. Beyond the morphological evaluation, MRI allows to characterize the structural organization (collagen network) and the matrix content of the cartilage. Such a quantitative approach may be performed in clinical practice by T2 mapping technique which can be used as early biomarker for knee osteoarthritis. T2 relaxation time measurements reflect these pathophysiological changes. T2 mapping technique had recently shown its potentiality to evaluate the quality of the cartilage composition since the transversal relaxation time (T2) reflects the ability of proton molecule to move and to exchange energy inside the cartilaginous matrix. Each variation of matrix content (water, proteoglycan and collagen) or each modification of the organization of the collagen network can induce T2 variations. Objective: The primary purpose of this study was determine whether the addition of a T2 mapping sequence to a routine MR imaging protocol could or could not improve diagnostic performance in the detection of the articular cartilage lesions and early identification of the cartilage degeneration within the knee joint. Methods: The current study is a cross sectional study that was conducted at private radiology centres in cairo.in the period between September 2019 and December 2020. The study included 20 patients. 13 Males and7 Females with age range from 25 to 65 years (mean age 41.53 years). Complaining from knee pain after direct trauma or twisting. Routine knee MR images from all patients were assessed for gross articular lesion. Then mean T2 values are obtained and the T2 maps are generated and reviewed. Comparative data of the overall Diagnostic indices of conventional MRI and T2 mapping are taken. Results: The age of the study group ranged from 25 to 65 years (mean age 41.53 years). The male patients represented the majority of our cases. We noted that there was more affection of the left knee compared to the right one with regional differences in the T2 values were observed as higher T2 values in the medial compartments cartilage (weight-bearing) compared to lateral ones’ cartilage (non-weight-bearing). Cases can be categorized according to the site of pain which was correlated later to the T2 values as: 15% anterior 35% medial, 15% lateral and 35% global. Out of the 20 cases, 12/20 (60 %) cases presented by knee pain following direct trauma, and 8/20 (40 %) cases presented by knee pain following knee twisting. All cases underwent conventional MRI with complementary T2 mapping sequence. In this study, the sensitivity, specificity, and accuracy of the conventional MRI results are 82.3%, 100 %, and 85 %, respectively. While the sensitivity, specificity, and accuracy of the T2 mapping finding results are 100 %, 100 %, and 100 %, respectively. Conclusion: In this study The addition of a T2 mapping of the knee cartilage sequence to a routine MR knee protocol at 1.5 T improved sensitivity in the detection of cartilage lesions within the knee joint from 82.3 % to 100 %, with improvement of accuracy from 85 % to 100%. The improvement in sensitivity with use of the T2 maps was in the identification of early cartilage degeneration.

Triple Contrast CT Method Enables Simultaneous Evaluation of Articular Cartilage Composition and Segmentation

Early degenerative changes of articular cartilage are detected using contrast-enhanced computed tomography (CT) with a cationic contrast agent (CA). However, cationic CA diffusion into degenerated cartilage decreases with proteoglycan depletion and increases with elevated water content, thus hampering tissue evaluation at early diffusion time points. Furthermore, the contrast at synovial fluid-cartilage interface diminishes as a function of diffusion time hindering accurate cartilage segmentation. For the first time, we employ quantitative dual-energy CT (QDECT) imaging utilizing a mixture of three CAs (cationic CA4+ and non-ionic gadoteridol which are sensitive to proteoglycan and water contents, respectively, and bismuth nanoparticles which highlight the cartilage surface) to simultaneously segment the articulating surfaces and determine of the cartilage condition. Intact healthy, proteoglycan-depleted, and mechanically injured bovine cartilage samples (n = 27) were halved and imaged with synchrotron microCT 2-h post immersion in triple CA or in dual CA (CA4+ and gadoteridol). CA4+ and gadoteridol partitions were determined using QDECT, and pairwise evaluation of these partitions was conducted for samples immersed in dual and triple CAs. In conclusion, the triple CA method is sensitive to proteoglycan depletion while maintaining sufficient contrast at the articular surface to enable detection of cartilage lesions caused by mechanical impact.

A New Method for Cartilage Evaluation in Femoroacetabular Impingement Using Quantitative T2 Magnetic Resonance Imaging: Preliminary Validation against Arthroscopic Findings.

The outcome of arthroscopic treatment for femoroacetabular impingement (FAI) depends on the preoperative status of the hip cartilage. Quantitative T2 can detect early biochemical cartilage changes, but its routine implementation is challenging. Furthermore, intrinsic T2 variability between patients makes it difficult to define a threshold to identify cartilage lesions. To address this, we propose a normalized T2-index as a new method to evaluate cartilage in FAI. We retrospectively analyzed magnetic resonance imaging (MRI) data of 18 FAI patients with arthroscopically confirmed cartilage defects. Cartilage T2 maps were reconstructed from multi-spin-echo 3-T data using the echo-modulation-curve (EMC) model-based technique. The central femoral cartilage, assumed healthy in early-stage FAI, was used as the normalization reference to define a T2-index. We investigated the ability of the T2-index to detect surgically confirmed cartilage lesions. The average T2-index was 1.14 ± 0.1 and 1.13 ± 0.1 for 2 separated segmentations. Using T2-index >1 as the threshold for damaged cartilage, accuracy was 88% and 100% for the 2 segmentations. We found moderate intraobserver repeatability, although separate segmentations yielded comparable accuracy. Damaged cartilage could not be identified using nonnormalized average T2 values. This preliminary study confirms the importance of normalizing T2 values to account for interpatient variability and suggests that the T2-index is a promising biomarker for the detection of cartilage lesions in FAI. Future work is needed to confirm that combining T2-index with morphologic MRI and other quantitative biomarkers could improve cartilage assessment in FAI.

Detecting hip osteoarthritic degenerative changes in MRI using deep learning

Purpose: Osteoarthritis (OA) is a debilitating joint disease that involves the degeneration of the articular cartilage and affects more than 25% of the adult population. Previously, SHOMRI (Scoring Hip Osteoarthritis with MRI) has been proposed as an MR-based hip OA evaluation system, based on the presence of morphological abnormalities, such as bone marrow edema, cartilage lesions, labral abnormalities and cysts. However, manual identification of bone and cartilage abnormalities in MR images can be laborious and time consuming. Thus, the goal of this study was to develop a fully automated deep learning pipeline to identify morphological and degenerative changes in patients with OA of the hip joint that would act as a radiology assist in image interpretation. Methods: 133 subjects with radiographic or symptomatic hip OA (as graded by SHOMRI) were recruited for this study (age 42.88±12.75 years, BMI 22.94± 3.029 kg/m3, 75 males, 58 females). T2-weighted, fat-saturated coronal hip images (TR = 60 ms, TR = 2.4s, slice thickness=4 mm, matrix=288x224, FOV=14-20 cm) were acquired on a 3T Discovery 750 MR scanner (GE Healthcare, Waukesha, WI). An end-to-end automated pipeline was built to evaluate morphological degenerative changes (Fig. 1). It included an object detection deep convolutional neural network (DCNN) that generated cropped images of the hip joint and a classification DCNN that identified the presence of morphological bone and cartilage abnormalities. The object detection network was implemented in Python and TensorFlow Object Detection API (Google, Mountain View, CA) on single-shot detector with Resnet-50 feature pyramid network (RetinaNet) architecture. The model was pre-trained on ImageNet classification and COCO object detection datasets and trained with Nvidia Titan X GPU on a dataset of 70 hip MR images with bounding boxes around the femoral head (90% train / 10% validation, random flip augmentation, batch=8, 25000 iterations). The network’s output was the central slice and the bounding box over the femoral head, which was used to extract a set of 5 slices, cropped around the weight bearing region of the joint (Fig. 1). These cropped images were labeled by two trained radiologists on the presence of bone marrow edema and cartilage lesions. The classification DCNN was implemented using PyTorch framework with DenseNet-100 architecture, pretrained on grayscale CIFAR-32 dataset. The model used an SGD optimizer with initial learning rate of 0.005 reduced to 0.001 after 20 epochs, momentum=0.9, weight_decay=5e-4, and random horizontal flip augmentation. It was trained on datasets of 539 and 647 images (edema, cartilage lesions) with batch of 60, 170 epochs, 65-20-15% train-validation-test split. Saliency maps were generated using Grad-CAM algorithm. Results: The detection network showed excellent convergence, without overfitting at 25000 iterations (Fig. 2). The object detection showed a mean intersection over union of 0.92±0.04 on the validation dataset. Figure 3 shows cross-entropy loss and precision/recall plots of the bone marrow edema detection network with the corresponding confusion matrix shown in figure 4. It achieved sensitivity of 0.73 and specificity of 0.92 on the validation dataset. The cartilage lesion detection network had sensitivity of 0.67 and specificity of 0.68 after 13 epochs. An example of a saliency map generated during inference with the bone marrow edema classification network is shown in figure 5. Conclusions: Our results have demonstrated the feasibility of automated identification of OA degenerative changes. Automated cropping using deep detection network allowed to focus attention on the weight-bearing area of the joint and reduced the number of parameters. Transfer learning using pre-trained detection and classification checkpoints allowed to achieve good results in a few iterations, despite having an unbalanced dataset for edema classification, and a small number of images in the training set. Future work includes training and evaluating the pipeline with a significantly-larger set of clinical hip MRI exams. View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Deep Learning Approach for Evaluating Knee MR Images: Achieving High Diagnostic Performance for Cartilage Lesion Detection.

Purpose To determine the feasibility of using a deep learning approach to detect cartilage lesions (including cartilage softening, fibrillation, fissuring, focal defects, diffuse thinning due to cartilage degeneration, and acute cartilage injury) within the knee joint on MR images. Materials and Methods A fully automated deep learning-based cartilage lesion detection system was developed by using segmentation and classification convolutional neural networks (CNNs). Fat-suppressed T2-weighted fast spin-echo MRI data sets of the knee of 175 patients with knee pain were retrospectively analyzed by using the deep learning method. The reference standard for training the CNN classification was the interpretation provided by a fellowship-trained musculoskeletal radiologist of the presence or absence of a cartilage lesion within 17 395 small image patches placed on the articular surfaces of the femur and tibia. Receiver operating curve (ROC) analysis and the κ statistic were used to assess diagnostic performance and intraobserver agreement for detecting cartilage lesions for two individual evaluations performed by the cartilage lesion detection system. Results The sensitivity and specificity of the cartilage lesion detection system at the optimal threshold according to the Youden index were 84.1% and 85.2%, respectively, for evaluation 1 and 80.5% and 87.9%, respectively, for evaluation 2. Areas under the ROC curve were 0.917 and 0.914 for evaluations 1 and 2, respectively, indicating high overall diagnostic accuracy for detecting cartilage lesions. There was good intraobserver agreement between the two individual evaluations, with a κ of 0.76. Conclusion This study demonstrated the feasibility of using a fully automated deep learning-based cartilage lesion detection system to evaluate the articular cartilage of the knee joint with high diagnostic performance and good intraobserver agreement for detecting cartilage degeneration and acute cartilage injury. © RSNA, 2018 Online supplemental material is available for this article .

Validation of scoring hip osteoarthritis with MRI (SHOMRI) scores using hip arthroscopy as a standard of reference.

To validate SHOMRI gradings in preoperative hip magnetic resonance imaging (MRI) with intra-arthroscopic evaluation of intraarticular hip abnormalities. Preoperative non-arthrographic 3.0-T MRIs of 40 hips in 39 patients (1 patient with bilateral hip surgery) with femoroacetabular impingement (FAI) syndrome (mean age, 34.7 years ± 9.0; n = 16 females), refractory to conservative measures, that underwent hip arthroscopy were retrospectively assessed by two radiologists for chondrolabral abnormalities and compared with intra-arthroscopic findings as the standard of reference. Arthroscopically accessible regions were compared with the corresponding SHOMRI subregions and assessed for the presence and grade of cartilaginous pathologies in the acetabulum and femoral head. The acetabular labrum was assessed for the presence or absence of labral tears. For the statistical analysis sensitivity and specificity as well as intraclass correlation (ICC) for interobserver agreement were calculated. Regarding chondral abnormalities, 58.8% of the surgical cases showed chondral defects. SHOMRI scoring showed a sensitivity of 95.7% and specificity of 84.8% in detecting cartilage lesions. Moreover, all cases with full-thickness defects (n = 9) were identified correctly, and in n = 6 cases (out of n = 36 with partial-thickness defects) the defective cartilage was identified but the actual depth overestimated. Labral tears were present in all cases and the MR readers identified 92.5% correctly. ICC showed a good interobserver agreement with 86.3% (95% CI 80.0, 90.6%) CONCLUSION: Using arthroscopic correlation, SHOMRI grading of the hip proves to be a reliable and precise method to assess chondrolabral hip joint abnormalities. • Assessment of hip abnormalities using MRI with surgical correlation. • Comparing surgery and MRI by creating a hybrid anatomic map that covers both modalities. • Non-arthrographic use of 3.0-T MRI provides detailed information on cartilage and labral abnormalities in hip joints.

Clinical Feasibility of Synthetic Magnetic Resonance Imaging in the Diagnosis of Internal Derangements of the Knee.

ObjectiveTo evaluate the feasibility of synthetic magnetic resonance imaging (MRI) compared to conventional MRI for the diagnosis of internal derangements of the knee at 3T.Materials and MethodsFollowing Institutional Review Board approval, image sets of conventional and synthetic MRI in 39 patients were included. Two musculoskeletal radiologists compared the image sets and qualitatively analyzed the images. Subjective image quality was assessed using a four-grade scale. Interobserver agreement and intersequence agreement between conventional and synthetic images for cartilage lesions, tears of the cruciate ligament, and tears of the meniscus were independently assessed using Kappa statistics. In patients who underwent arthroscopy (n = 8), the sensitivity, specificity, and accuracy for evaluated internal structures were calculated using arthroscopic findings as the gold standard.ResultsThere was no statistically significant difference in image quality (p = 0.90). Interobserver agreement (κ = 0.649– 0.981) and intersequence agreement (κ = 0.794–0.938) were nearly perfect for all evaluated structures. The sensitivity, specificity, and accuracy for detecting cartilage lesions (sensitivity, 63.6% vs. 54.6–63.6%; specificity, 91.9% vs. 91.9%; accuracy, 83.3–85.4% vs. 83.3–85.4%) and tears of the cruciate ligament (sensitivity, specificity, accuracy, 100% vs. 100%) and meniscus (sensitivity, 50.0–62.5% vs. 62.5%; specificity, 100% vs. 87.5–100%; accuracy, 83.3–85.4% vs. 83.3–85.4%) were similar between the two MRI methods.ConclusionConventional and synthetic MRI showed substantial to almost perfect degree of agreement for the assessment of internal derangement of knee joints. Synthetic MRI may be feasible in the diagnosis of internal derangements of the knee.

3T MRI of the knee with optimised isotropic 3D sequences: Accurate delineation of intra-articular pathology without prolonged acquisition times.

To investigate optimised isotropic 3D turbo spin echo (TSE) and gradient echo (GRE)-based pulse sequences for visualisation of articular cartilage lesions within the knee joint. Optimisation of experimental imaging sequences was completed using healthy volunteers (n=16) with a 3-Tesla (3T) MRI scanner. Imaging of patients with knee cartilage abnormalities (n=57) was then performed. Acquired sequences included 3D proton density-weighted (PDW) TSE (SPACE) with and without fat-suppression (FS), and T2*W GRE (TrueFISP) sequences, with acquisition times of 6:51, 6:32 and 5:35 min, respectively. One hundred sixty-one confirmed cartilage lesions were detected and categorised (Grade II n=90, Grade III n=71). The highest sensitivity and specificity for detecting cartilage lesions were obtained with TrueFISP with values of 84.7% and 92%, respectively. Cartilage SNR mean for PDW SPACE-FS was the highest at 72.2. TrueFISP attained the highest CNR means for joint fluid/cartilage (101.5) and joint fluid/ligament (156.5), and the lowest CNR for cartilage/meniscus (48.5). Significant differences were identified across the three sequences for all anatomical structures with respect to SNR and CNR findings (p-value <0.05). Isotropic TrueFISP at 3T, optimised for acquisition time, accurately detects cartilage defects, although it demonstrated the lowest contrast between cartilage and meniscus. • Cartilage is better visualised with 3D TrueFISP than 3D SPACE sequences. • 3D TrueFISP is a reliable sequence for detecting low- and high-grade cartilage defects. • 3D TrueFISP at 3T provides excellent contrast between cartilage and joint fluid.

Evaluation of the Articular Cartilage of the Knee Joint Using an Isotropic Resolution 3D Fast Spin-Echo Sequence With Conventional and Radial Reformatted Images.

The purpose of this study was to determine whether the use of radial reformatted images could improve the diagnostic performance of a 3D fast spin-echo (FSE) sequence for detecting surgically confirmed cartilage lesions within the knee joint. An MRI examination consisting of five 2D FSE sequences and a sagittal 3D FSE sequence was performed at 3 T on the knee joint of 150 patients who underwent subsequent knee arthroscopy, which included grading of the articular cartilage. Conventional axial, sagittal, and coronal reformatted images and radial reformatted images were created from the 3D FSE source data. Two musculoskeletal radiologists independently used the 2D FSE sequences, the 3D FSE sequence with conventional reformatted images only, and the 3D FSE sequence with both radial and conventional reformatted images at three separate sessions to grade each articular surface of the knee joint. McNemar tests were used to compare diagnostic performance for detecting cartilage lesions using arthroscopy as the reference standard. The 3D FSE sequence with radial and conventional reformatted images had higher sensitivity (p < 0.001) and similar specificity (p = 0.73) to the 2D FSE sequences for detecting cartilage lesions and higher sensitivity (p < 0.001) and specificity (p = 0.002) than the 3D FSE sequence with conventional reformatted images for detecting cartilage lesions. The 3D FSE sequence with conventional reformatted images had similar sensitivity (p = 0.93) and lower specificity (p = 0.005) than did the 2D FSE sequences for detecting cartilage lesions. A 3D FSE sequence had improved diagnostic performance compared with 2D FSE sequences for detecting cartilage lesions within the knee joint but only when using both radial and conventional reformatted images for cartilage evaluation.

Morphological MR imaging of the articular cartilage of the knee at 3T-comparison of standard and novel 3D sequences.

ObjectivesThis study sought to compare various 3D cartilage sequences and to evaluate the usefulness of ultrashort TE (UTE) imaging, a new technique to isolate signal from the osteochondral junction.MethodsTwenty knees were examined at 3 T with 3D spoiled GRE (FLASH), double-echo steady-state (DESS), balanced SSFP, 3D turbo spin-echo (TSE), and a prototype UTE sequence. Two radiologists independently evaluated all images. Consensus readings of all sequences were the reference standard. Statistical analysis included Friedman and pairwise Wilcoxon tests. Retrospective analysis of UTE morphology of osteochondral tissue in normal and abnormal cartilage seen at conventional MR was also performed.ResultsThree-dimensional TSE was superior to other sequences for detecting cartilage lesions. FLASH and DESS performed best in the subjective quality analysis. On UTE images, normal cartilage exhibited a high-intensity linear signal near the osteochondral junction. Retrospective analysis revealed abnormal UTE morphology of the osteochondral junction in 50 % of cartilage lesions diagnosed at conventional MR.ConclusionsCartilage imaging of the knee at 3 T can be reliably performed using 3D TSE, showing high accuracy when compared to standard sequences. Although UTE depicts signal from the deep cartilage layer, further studies are needed to establish its role for assessment of cartilage.Main Messages• MRI is the best available imaging method for assessment of knee cartilage.• Cartilage imaging can be reliably performed using 3D TSE.• UTE cannot be used as a single sequence to assess cartilage.

Labral and cartilage abnormalities in young patients with hip pain: accuracy of 3-Tesla indirect MR arthrography.

Assess the diagnostic accuracy of 3-T indirect magnetic resonance arthrography (iMRA) for hip cartilage and labral pathology detection using arthroscopy as the reference standard and compare it to the published performance of direct magnetic resonance arthrography (dMRA). Between 2009 and 2011, 290 patients suspected of having femoroacetabular impingement underwent iMRA. Our study group consisted of 41 of these patients (17 males, mean age 35years; 24 females, mean age 33years) who did not have a prior history of hip surgery and who subsequently underwent arthroscopy. Two experienced musculoskeletal radiologists separately evaluated the randomized and anonymized studies for the presence and quadrant location of labral and cartilage pathology. These recorded data were compared to arthroscopic reports. Forty-one patients had labral pathology, 34 patients had acetabular and 5 patients had femoral cartilage pathology at arthroscopy. Sensitivity, specificity, accuracy, negative- and positive-predictive values for labral lesion detection were respectively 98, 99, 99, 99 and 98%; for acetabular cartilage lesion detection they were 69, 98, 89, 87 and 95%; for femoral cartilage lesion detection they were 69, 95, 93 and 39%. Sensitivities of iMRA by quadrant (anteroinferior, anterosuperior, posteroinferior, posterosuperior) for the labrum were 100.0, 95.0, NA and 85.7%, for acetabular cartilage were NA, 58.8, NA and 39.5% and for femoral cartilage were 50.0, 33.3, 75.0 and 75.0%). NA indicates results not available because of the absence of findings in those quadrants. Specificities of iMRA by quadrant (anteroinferior, anterosuperior, posteroinferior, posterosuperior) for the labrum (95.0, 100.0, 95.1, 67.5%), acetabular (100.0, 85.7, 92.6, 79.5%) and femoral cartilage (100.0, 94.7, 96.2, 85.9%). iMRA at 3T is accurate in detecting labral pathology suggesting that it is a viable alternative to dMRA.

MR T1ρ quantification of cartilage focal lesions in acutely injured knees: correlation with arthroscopic evaluation

ObjectiveQuantitative T1ρ MRI has been suggested as a promising tool to detect changes in cartilage composition that are characteristic of cartilage damage and degeneration. The objective of this study was to evaluate the capability of MR T1ρ to detect cartilage lesions as evaluated by arthroscopy in acutely ACL-injured knees and to compare with the Whole-Organ Magnetic Resonance Imaging Score (WORMS) using clinical standard MRI. MethodTen healthy controls (mean age 35) with no ACL injury or history of osteoarthritis (OA) and 10 patients with acute ACL injuries (mean age 39) were scanned at 3 Tesla (3T). ACL patients underwent ACL reconstruction, where focal lesions were graded according to an Outerbridge grading system during arthroscopic evaluation. Normalized MR T1ρ values (T1ρ z-scores normalized to control values in matched regions) in full thickness, and superficial and deep layers of cartilage were compared between defined sub-compartments with and without focal lesions. Intraclass (ICC) correlation and the root mean square coefficient of variation (RMS-CV) were performed to evaluate the inter-observer reproducibility of T1ρ quantification. Sub-compartments of cartilage were also evaluated using WORMS scoring and compared to their Outerbridge score respectively. ResultsThe inter-observer ICC and the RMS-CV of the sub-compartment T1ρ quantification were 0.961 and 3.9%, respectively. The average T1ρ z-scores were significantly increased in sub-compartments with focal lesions compared to those without focal lesions and to the control cohort (p<0.05). ConclusionOur results indicate that T1ρ provided a better diagnostic capability than clinical standard MRI grading in detecting focal cartilage abnormalities after acute injuries. Quantitative MRI may have great potential in detecting cartilage abnormalities and degeneration non-invasively, which are occult with standard morphological MRI.

MR arthrography of the shoulder: Optimizing pulse sequence protocols for the evaluation of cartilage and labrum

ObjectivesTo compare axial T1weighted fat-saturated (T1w fs) and T1w non-fs sequences, and coronal T1w-fs and T2w-fs sequences, for evaluation of cartilage and labrum using CT arthrography (CTA) as the reference. MethodsPatients had MR arthrography (MRA) and CTA of the shoulder on the same day. Cartilage was assessed for superficial and full thickness focal and diffuse damage. Labral lesions were graded for Bankart variants and SLAP lesions. CTA images were read for the same features. The diagnostic performance of MRA including area under the curve (AUC) was evaluated against CTA. ResultsWhen comparing axial sequences, the diagnostic performance for cartilage lesion detection on T1w non-fs was 61.9% (sensitivity) 93.6% (specificity) and 89.5% (accuracy) with AUC 0.782, while that for T1w fs was 61.9%, 94.0%, 89.8% and 0.783. For labral assessment, it was 89.1%, 93.0%, 91.4% and 0.919 for T1w non-fs, and 89.9%, 94.0%, 92.6% and 0.922 for T1w fs. Comparing coronal sequences, diagnostic performance for cartilage was 42.5%, 97.5%, 89.8% and 0.702 for T1w fs, and 38.4%, 98.7%, 90.2%, and 0.686 for T2w fs. For the labrum it was 85.1%, 87.5%, 86.2%, and 0.868 for T1w fs, and 75.7%, 97.5%, 80.8% and 0.816 for T2w fs. ConclusionsAxial T1w fs and T1w non-fs sequences are comparable in their ability to diagnose cartilage and labral lesions. Coronal T1w fs sequence offers slightly higher sensitivity but slightly lower specificity than T2w fs sequence for diagnosis of cartilage and labral lesions.

DIagnosis of morphological internal knee derangements associated with osteoarthritis on magnetic resonance imaging sequences for quantitative T2 and T1rho mapping of articular cartilage composition.

Purpose: Novel quantitative magnetic resonance imaging (MRI) techniques for articular cartilage composition show promise for early detection of osteoarthritis (OA). However, large-scale application of quantitative MRI techniques in clinical OA research studies or in routine clinical patient care is hampered by long scan times. Implementation of quantitative MRI techniques may become more widespread if they can be applied as a replacement of routine morphological knee MRI pulse sequences rather than an extension of the MRI protocol. This study aimed to assess the diagnostic performance of a novel 3D fast spin-echo (FSE) T2 and T1rho sequence for quantitative mapping of articular cartilage composition for the detection of internal knee derangements. We focused on cruciate ligament and meniscal tears, which are among the most common internal knee derangements on MRI and are associated with (early) OA. We also determined the performance for diagnosis of bone marrow lesions and cartilage defects, which are morphological features of established OA. Methods: 39 patients underwent routine clinical MRI of the knee on a 3T MRI scanner (Discovery MR750, GE Healthcare, Waukesha, WI) using a 16-channel flexible wrap-around coil (GEM Flex Coil, NeoCoil, Pewaukee, WI). The MRI protocol consisted of 5 routine 2D FSE clinical knee MRI pulse sequences in three orthogonal planes, and was extended with novel 3D pseudo-steady-state FSE sequences for the purpose of quantitative T2 and T1rho mapping of articular cartilage (sagittal plane, slice thickness 3mm, matrix 384x256, number of excitations 0.5, field of view 15 cm, scan time 6:49 minutes for T2 and 6:37 minutes for T1rho). Three separate de-identified MRI datasets with randomized patient order were created consisting of morphological, quantitative T2, and T1rho images. An experienced musculoskeletal radiologist evaluated all MRIs for anterior and posterior cruciate ligament (ACL and PCL) complete tears, andmedial and lateral meniscal tears. Bone marrow lesions (BMLs) and cartilage defects were also assessed according to the semi-quantitative MRI Osteoarthritis Knee Score (MOAKS). In patients who subsequently underwent knee arthroscopy, the orthopaedic surgeon systematically assessed intra-articular pathology using the International Cartilage Repair Society (ICRS) scoring system. Diagnostic performance statistics were calculated for aforementioned morphological abnormalities on the T2 mapping and T1rho mapping sequence separately, only including lesions with a frequency of 5 more in our study population. Arthroscopic findings were used as reference standard for 23 patients that underwent arthroscopy, whereas for the other 16 patients we used routine morphological MRI as the reference. Results: Only four lateral meniscal tears and no PCL tears were diagnosed. The 3D FSE T1rho sequence demonstrated good sensitivity and excellent specificity for the diagnosis for ACL tears and medial meniscal tears, and generally showed better diagnostic performance than the T2 mapping 3D FSE sequence (Table 1). For both sequences, sensitivity was poor for the detection of cartilage lesions, BMLs, and lateral meniscal tears. Illustrative examples of normal and abnormal internal knee structures are shown in Figure 1. Conclusions: A 3D FSE T1rho sequence for quantitative mapping of articular cartilage composition shows good diagnostic performance for the anatomic diagnosis of ACL tears and medial meniscal tears. In MRI studies focused on these OA associated internal knee derangements, this sequence may replace routine clinical pulse sequences, enhancing scan time efficiency and potentially accelerating largescale application in clinical OA research and routine clinical patient care. The poor diagnostic performance for BMLs and cartilage lesions may be less relevant with the availability of more sensitive indicators of OA status provided by these sequences, i.e. quantitative information on cartilage composition and quality. Examining quantitative T2 or T1rho information from these sequences along with the underlying morphologic images could enhance detection of cartilage and bone marrow lesions. We also expect that diagnostic performance would benefit from isotropic acquisition methods that enable multi-planar reconstructions.