Standardized quantitative measurements of wrist cartilage in healthy humans using 3T magnetic resonance imaging

Impact of bone and cartilage segmentation from CT and MRI on both bone forearm osteotomy planning

INTRODUCTION

The use of MRI scans for pre-operative surgical planning of forearm osteotomies provides additional information of joint cartilage and soft tissue structures and reduces radiation exposure in comparison with the use of CT scans. In this study, we investigated whether using 3D information obtained from MRI with and without cartilage information leads to a different outcome of pre-operative planning.

METHODS

Bilateral CT and MRI scans of the forearms of 10 adolescent and young adult patients with a unilateral bone deformation were acquired in a prospective study. The bones were segmented from CT and MRI, and cartilage only from MRI. The deformed bones were virtually reconstructed, by registering the joint ends to the healthy contralateral side. An optimal osteotomy plane was determined that minimized the distance between the resulting fragments. This process was performed in threefold: using the CT and MRI bone segmentations, and the MRI cartilage segmentations.

RESULTS

Comparison of bone segmentation from MRI and CT scan resulted in a 0.95 ± 0.02 Dice Similarity Coefficient and 0.42 ± 0.07 mm Mean Absolute Surface Distance. All realignment parameters showed excellent reliability across the different segmentations. However, the mean differences in translational realignment between CT and MRI bone segmentations (4.5 ± 2.1 mm) and between MRI bone and MRI bone and cartilage segmentations (2.8 ± 2.1 mm) were shown to be clinically and statistically significant. A significant positive correlation was found between the translational realignment and the relative amount of cartilage.

CONCLUSION

This study indicates that although bone realignment remained largely similar when using MRI with and without cartilage information compared to using CT, the small differences in segmentation could induce statistically and clinically significant differences in the osteotomy planning. We also showed that endochondral cartilage might be a non-negligible factor when planning osteotomies for young patients.

CNN-based fully automatic wrist cartilage volume quantification in MR images: A comparative analysis between different CNN architectures

PURPOSE

Automatic measurement of wrist cartilage volume in MR images.

METHODS

We assessed the performance of four manually optimized variants of the U-Net architecture, nnU-Net and Mask R-CNN frameworks for the segmentation of wrist cartilage. The results were compared to those from a patch-based convolutional neural network (CNN) we previously designed. The segmentation quality was assessed on the basis of a comparative analysis with manual segmentation. The best networks were compared using a cross-validation approach on a dataset of 33 3D VIBE images of mostly healthy volunteers. Influence of some image parameters on the segmentation reproducibility was assessed.

RESULTS

The U-Net-based networks outperformed the patch-based CNN in terms of segmentation homogeneity and quality, while Mask R-CNN did not show an acceptable performance. The median 3D DSC value computed with the U-Net_AL (0.817) was significantly larger than DSC values computed with the other networks. In addition, the U-Net_AL provided the lowest mean volume error (17%) and the highest Pearson correlation coefficient (0.765) with respect to the ground truth values. Of interest, the reproducibility computed using U-Net_AL was larger than the reproducibility of the manual segmentation. Moreover, the results indicate that the MRI-based wrist cartilage volume is strongly affected by the image resolution.

CONCLUSIONS

U-Net CNN with attention layers provided the best wrist cartilage segmentation performance. In order to be used in clinical conditions, the trained network can be fine-tuned on a dataset representing a group of specific patients. The error of cartilage volume measurement should be assessed independently using a non-MRI method.

3D MRI of the Hand and Wrist: Technical Considerations and Clinical Applications

In the last few years, major developments have been observed in the field of magnetic resonance imaging (MRI). Advances in both scanner hardware and software technologies have witnessed great leaps, enhancing the diagnostic quality and, therefore, the value of MRI. In musculoskeletal radiology, three-dimensional (3D) MRI has become an integral component of the diagnostic pathway at our institutions. This technique is particularly relevant in patients with hand and wrist symptoms, due to the intricate nature of the anatomical structures and the wide range of differential diagnoses for most presentations. We review the benefits of 3D MRI of the hand and wrist, commonly used pulse sequences, clinical applications, limitations, and future directions. We offer guidance for enhancing the image quality and tips for image interpretation of 3D MRI of the hand and wrist.

Deep learning-based fully automatic segmentation of wrist cartilage in MR images

The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images. CNN utilized a planar architecture and patch-based (PB) training approach that ensured optimal performance in the presence of a limited amount of training data. The CNN was trained and validated in 20 multi-slice MRI datasets acquired with two different coils in 11 subjects (healthy volunteers and patients). The validation included a comparison with the alternative state-of-the-art CNN methods for the segmentation of joints from MR images and the ground-truth manual segmentation. When trained on the limited training data, the CNN outperformed significantly image-based and PB-U-Net networks. Our PB-CNN also demonstrated a good agreement with manual segmentation (Sørensen-Dice similarity coefficient [DSC] = 0.81) in the representative (central coronal) slices with a large amount of cartilage tissue. Reduced performance of the network for slices with a very limited amount of cartilage tissue suggests the need for fully 3D convolutional networks to provide uniform performance across the joint. The study also assessed inter- and intra-observer variability of the manual wrist cartilage segmentation (DSC = 0.78-0.88 and 0.9, respectively). The proposed deep learning-based segmentation of the wrist cartilage from MRI could facilitate research of novel imaging markers of wrist osteoarthritis to characterize its progression and response to therapy.

Evaluation of Cartilage in the Wrist using Magnetic Resonance Imaging

Wrist pain is a common patient complaint with a myriad of clinical conditions that can explain the underlying cause. Short of wrist arthroscopy, no technique other than formal wrist arthrotomy exists for direct examination of the hyaline cartilage coating the articular surfaces of the carpal bones. Magnetic resonance imaging (MRI) has been proven accurate in evaluating joint surfaces of large joints such as the shoulder, hip, and knee with articular cartilage surface thickness is in excess of 1 mm. However, in the carpus the thickness of the cartilage and the contours present have precluded accurate imaging. Advances in MRI technology over the last several decades are now making imaging of small joint surfaces, such as the carpus, an area worth revisiting. Herein we provide a review of these efforts with a specific focus on the evaluation of the wrist.

THE ROLE OF MAGNETIC RESONANCE IMAGING IN THE DIAGNOSIS OF DEFORMING ARTHROSIS OF PROFESSIONAL ETIOLOGY IN MINERS

The paper analyzes the effectiveness of magnetic resonance imaging with cartilage diagram in diagnosing signs of professional deforming arthrosis of knee joints in miners working in conditions of significant physical loading. Aim of the research – to determine of diagnostic efficiency of indicators of magnetic resonance imaging of the knee joint and cartilage diagram in miners of the main occupations suffering from deforming arthrosis. Methods. The research is conducted in 30 miners of basic occupations: 20 mining workers of breakage face (MWBF) and 10 machinists of shearer mining machines (МSMM) have been treated in the inpatient department of occupational pathology of the Lviv Regional Clinical Hospital in 2015-2017 due to deforming arthrosis. Damages of the main anatomical elements of the knee joint with arthrosis were analyzed, visualized initially with the help of MRI, and then - cartilage diagram. Results. According to the MRI data, in miners of the main occupations with arthrosis of the knee joint the posterior cross-shaped ligament are most commonly affected (in 75.0±9.7 % MWBF and 70.0±14.5 % МSMM), damage to the medial collateral ligament are diagnosed less frequently (in 5.0±4.9 % in the MWBF and in 10.0±9.5 % in the МSMM). On average 3.8±0.4 modified elements of the knee joint are visualized in patients, whereas 4.8±0.1 affected areas are visualized on the cartilage diagram (р<0.05). In 86.7±6.2 % patients, in the analysis of cartilage diagram, changes in all five analyzed areas are diagnosed, indicating a higher efficiency of the diagnosis of changes in the structures of the joint with DA of the professional etiology of the method of cartilage diagram compared with MRI. According to the cartilage diagram the most significant changes are noted in the hypertrophy of the femur: among all miners 62.5±0.3 ms (medial) and 62.6±0.4 ms (lateral), in the MWBF group the average time of Т2-delay is the largest in the area of the medial hypertrophy of the femur is 60.9±2.3 ms, in the МSMM group – in the area of the lateral hypertrophy of the femur: 66.7±3.3 ms, which can be linked to the peculiarities of the forced working position of miners of these professions and the kinetics of joint structures. These results can be used to diagnose the initial lesions of joint structures with DA of professional genesis, as well as the creation of prognostic models for determining the the degree of risk of development of knee joint damage, which will allow to improve the system of personified approach to diagnostic and preventive measures in working persons in conditions of considerable physical activity and forced working position.

Effect of traction on wrist joint space and cartilage visibility with and without MR arthrography

OBJECTIVE

To compare the effect of traction during non-arthrographic and arthrographic MR examination of the wrist with regard to joint space width, joint fluid dispersion and cartilage surface visibility.

METHODS

Prospective 3-T MRI study of 100 wrists in 96 patients. The first 50 wrists underwent MR arthrography first without traction and then with traction. The following 50 wrists underwent standard MR first without traction and then with traction. On these examinations, two radiologists independently measured (i) joint space width, semi-quantitatively graded (ii) joint fluid dispersion between opposing cartilage surfaces and (iii) articular cartilage surface visibility. The three parameters were compared between the two groups.

RESULTS

Traction led to an increase in joint space width at nearly all joints in all patients (p < 0.05), although more so in the arthrography (∆ = 0.08-0.79 mm, all p < 0.05) than in the non-arthrography (∆ = 0.001-0.61 mm, all p < 0.05) group. Joint fluid dispersion and cartilage surface visibility improved after traction in nearly all joints (p < 0.05) in all patients and more so in the arthographic than in the non-arthrography group.

CONCLUSION

Traction did significantly improve cartilage surface visibility for standard MRI of the wrist although the effect was not as great as that seen with MR arthography or MR arthrography with traction. Advances in knowledge: This is the first study to show the beneficial effect of traction during standard non-arthrography MRI of the wrist and compare the effect of traction between non-arthrographic and arthrographic MRI of the wrist.