Quantitative MRI of cartilage and bone: degenerative changes in osteoarthritis

Highly accelerated parameter mapping using model-based alternating reconstruction coupling fitting

Objective.A model-based alternating reconstruction coupling fitting, termed Model-based Alternating Reconstruction COupling fitting (MARCO), is proposed for accurate and fast magnetic resonance parameter mapping.Approach.MARCO utilizes the signal model as a regularization by minimizing the bias between the image series and the signal produced by the suitable signal model based on iteratively updated parameter maps when reconstructing. The technique can incorporate prior knowledge of both image series and parameters by adding sparsity constraints. The optimization problem is decomposed into three subproblems and solved through three alternating steps involving reconstruction and nonlinear least-square fitting, which can produce both contrast-weighted images and parameter maps simultaneously.Main results.The algorithm is applied toT2mapping with extended phase graph algorithm integrated and validated on undersampled multi-echo spin-echo data from both phantom and in vivo sources. Compared with traditional compressed sensing and model-based methods, the proposed approach yields more accurateT2maps with more details at high acceleration factors.Significance.The proposed method provides a basic framework for quantitative MR relaxometry, theoretically applicable to all quantitative MR relaxometry. It has the potential to improve the diagnostic utility of quantitative imaging techniques.

Bone marrow lesions in osteoarthritis: biomarker or treatment target? A narrative review

Osteoarthritis (OA) is a leading cause of pain, functional impairment, and disability in older adults. However, there are no effective treatments to delay and reverse OA. Magnetic resonance imaging (MRI) can assess structural abnormalities of OA by directly visualizing damage and inflammatory reactions within the tissues and detecting abnormal signals in the subchondral bone marrow region. While some studies have shown that bone marrow lesions (BMLs) are one of the early signs of the development of OA and predict structural and symptomatic progression of OA, others claimed that BMLs are prevalent in the general population and have no role in the progression of OA. In this narrative review, we screened and summarized studies with different designs that evaluated the association of BMLs with joint symptoms and structural abnormalities of OA. We also discussed whether BMLs may serve as an imaging biomarker and a treatment target for OA based on existing clinical trials.

Joint reconstruction and segmentation in undersampled 3D knee MRI combining shape knowledge and deep learning

Objective.Task-adapted image reconstruction methods using end-to-end trainable neural networks (NNs) have been proposed to optimize reconstruction for subsequent processing tasks, such as segmentation. However, their training typically requires considerable hardware resources and thus, only relatively simple building blocks, e.g. U-Nets, are typically used, which, albeit powerful, do not integrate model-specific knowledge.Approach.In this work, we extend an end-to-end trainable task-adapted image reconstruction method for a clinically realistic reconstruction and segmentation problem of bone and cartilage in 3D knee MRI by incorporating statistical shape models (SSMs). The SSMs model the prior information and help to regularize the segmentation maps as a final post-processing step. We compare the proposed method to a simultaneous multitask learning approach for image reconstruction and segmentation (MTL) and to a complex SSMs-informed segmentation pipeline (SIS).Main results.Our experiments show that the combination of joint end-to-end training and SSMs to further regularize the segmentation maps obtained by MTL highly improves the results, especially in terms of mean and maximal surface errors. In particular, we achieve the segmentation quality of SIS and, at the same time, a substantial model reduction that yields a five-fold decimation in model parameters and a computational speedup of an order of magnitude.Significance.Remarkably, even for undersampling factors of up toR= 8, the obtained segmentation maps are of comparable quality to those obtained by SIS from ground-truth images.

Which Knee Phenotypes Exhibit the Strongest Correlation With Cartilage Degeneration?

BACKGROUND

Although articular wear has been thoroughly investigated, the effects of abnormal limb alignment on cartilage degeneration over time remain poorly understood. An exact assessment of the correlation between lower limb alignment abnormalities and MRI-observed articular degradation may be helpful for understanding the progression of osteoarthritis and planning future treatment.

QUESTION/PURPOSE

In patients with moderate to advanced osteoarthritis, (1) is there a correlation between overall alignment of the knee and the location of cartilage degradation over time, as measured by cartilage metrics on MRI? (2) Is there a correlation between tibial alignment and the location of cartilage degradation over time, as measured by cartilage metrics on MRI? (3) Is there a correlation between femoral alignment and the location of cartilage degradation over time, as measured by cartilage metrics on MRI?

METHODS

Between April 2020 and September 2022, we retrospectively evaluated 3106 patients aged 45 to 79 years who were at risk of experiencing knee osteoarthritis. Of those, we considered as potentially eligible 600 symptomatic index knees with radiographic evidence of osteoarthritis-Kellgren-Lawrence Grades 2 or 3-at the baseline visit. Of those, 22% (134 of 600) were excluded because of a lack of proper alignment measurements, leaving 466 knees with measurements of radiologic alignment angles and quantitative MRI cartilage measurements of 16 subregions of the femorotibial compartment at baseline and 12 and 24 months, and 64 knees at the 48-month visit for investigation in the current study. Data regarding cartilage measurements of the patellofemoral compartment were not available for analysis. The knees were categorized into one of the possible 25 different phenotypes of the lower extremity established by previous research, based on the neutral, valgus, or varus distal mechanical angle of the femur and proximal tibial mechanical angle on full-limb radiographs. We applied ANOVA to estimate the effect size of the overall, femoral, and tibial alignments on the location of cartilage degradation over time, as measured by cartilage metrics on MRI.

RESULTS

We found that the overall combinations of a valgus femur with valgus tibia or a valgus femur with varus tibia were associated with the highest loss of cartilage in the internal medial tibial subregion and anterior lateral tibial subregion (η 2 p = 0.39 and 0.17, respectively). For the tibia, we found that the combination of a valgus femur with valgus tibia was associated with an increase in the area of subchondral bone denuded of cartilage in the central lateral tibial subregion (η 2 p = 0.2). For the femur, we found that the combination of a valgus femur with valgus tibia was associated with loss of cartilage thickness in the central weightbearing lateral femorotibial compartment (η 2 p = 0.15).

CONCLUSION

We found that certain alignment patterns are associated with rapid deterioration of cartilage and exposure of subchondral bone, even over short time periods. In particular, the valgus femur with valgus tibia and valgus femur with varus tibia phenotypes deserve special attention, because they exhibited a strong, atypical correlation with the internal medial tibial subregion and anterior lateral tibial subregion, respectively. This is important because valgus and varus malalignment cause isolated lateral and medial compartment disease, respectively. Therefore, these findings suggest that a more individualized approach for limb axis deformities is valuable, and hint at a more meticulous radiologic and clinical investigation, perhaps using different imaging modalities, especially when assessing the exact cartilage state and planning an intervention. Future studies, ideally biomechanical, might help in assessing the long-term effects of the various phenotypes on cartilage degradation and their relevance in reconstructive surgery.

LEVEL OF EVIDENCE

Level II, prognostic study.

Imaging Biomarkers of Osteoarthritis

Currently no disease-modifying osteoarthritis drug has been approved for the treatment of osteoarthritis (OA) that can reverse, hold, or slow the progression of structural damage of OA-affected joints. The reasons for failure are manifold and include the heterogeneity of structural disease of the OA joint at trial inclusion, and the sensitivity of biomarkers used to measure a potential treatment effect.This article discusses the role and potential of different imaging biomarkers in OA research. We review the current role of radiography, as well as advances in quantitative three-dimensional morphological cartilage assessment and semiquantitative whole-organ assessment of OA. Although magnetic resonance imaging has evolved as the leading imaging method in OA research, recent developments in computed tomography are also discussed briefly. Finally, we address the experience from the Foundation for the National Institutes of Health Biomarker Consortium biomarker qualification study and the future role of artificial intelligence.

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.

Biomarkers in osteoarthritis: current status and outlook - the FNIH Biomarkers Consortium PROGRESS OA study

Currently, no disease-modifying therapies are approved for osteoarthritis (OA) use. One obstacle to trial success in this field has been our existing endpoints' limited validity and responsiveness. To overcome this impasse, the Foundation for the NIH OA Biomarkers Consortium is focused on investigating biomarkers for a prognostic context of use for subsequent qualification through regulatory agencies. This narrative review describes this activity and the work underway, focusing on the PROGRESS OA study.

Leukocyte-Poor Platelet-Rich Plasma Injections Improve Cartilage T1ρ and T2 and Patient-Reported Outcomes in Mild-to-Moderate Knee Osteoarthritis

Purpose

To use T1ρ and T2 magnetic resonance imaging to evaluate the effect of leukocyte-poor platelet-rich plasma (LP-PRP) injections on knee cartilage health and to correlate structural changes with patient-reported outcome measurements.

Methods

Ten patients with symptomatic unilateral mild-to-moderate knee osteoarthritis (Kellgren-Lawrence Grade 1-2) underwent T1ρ and T2 magnetic resonance imaging of both the symptomatic and contralateral knee before injection and 6 months after injection with LP-PRP. Patient-reported outcome questionnaires (Knee Osteoarthritis Outcome Score and International Knee Documentation Committee) that evaluate the domains of pain, symptoms, activities of daily living, sports function, and quality of life were completed at baseline, 3 months, 6 months, and 12 months after injection. T1ρ and T2 relaxation times, which are correlated with the proteoglycan and collagen concentration of cartilage, were measured in compartments with and without chondral lesions.

Results

Ten patients were prospectively enrolled (9 female, 1 male) with a mean age of 52.9 years (range, 42-68) years and mean body mass index of 23.2 ± 1.9. Significant increases in Knee Osteoarthritis Outcome Score for all subscales and International Knee Documentation Committee scores were observed 3 months after injection and the improvements were sustained at 12 months. T1ρ and T2 values of compartments with chondral lesions were observed to significantly decrease by 6.0% (P = .036) and 7.1% (P = .017) 6 months after LP-PRP injection, respectively. No significant associations between T1ρ and T2 relaxation times and improvement in patient-reported outcomes were observed.

Conclusions

Patients undergoing LP-PRP injections for the treatment of mild-to-moderate knee osteoarthritis had increased proteoglycan and collagen deposition in the cartilage of affected compartments by 6 months after injection. Patient-reported outcomes scores improved 3 months after injection and were sustained through 1 year after injection, but these improvements were not associated with the changes in proteoglycan and collagen deposition in knee cartilage.

Level of Evidence

Level II, prospective cohort study.

Are patients with preoperative synovitis suitable for unicompartmental knee arthroplasty? Magnetic resonance imaging evidence from a retrospective cohort study

BACKGROUND

The use of unicompartmental knee arthroplasty (UKA) in patients with preoperative synovitis is controversial. This study aimed to investigate the association between synovitis detected by magnetic resonance imaging (MRI) and prognosis after UKA.

METHODS

Synovitis was graded using the MRI Osteoarthritis Knee Score criteria based on preoperative MRI findings of 132 UKAs performed between June 2020 and August 2021. The Knee Society Knee Score (KS-KS) and the Knee Society Function Score were collected preoperatively and 1 year postoperatively. The relationship between synovitis and the changes in the Knee Society score was analyzed using logistic regression.

RESULTS

Univariate logistic regression showed that patients with higher preoperative synovitis scores (odds ratio (OR) = 1.925, 95% confidence interval (CI): 1.482-2.500, P < 0.001) had higher KS-KS changes. After adjusting for confounding variables, synovitis was proven to be an independent factor for KS-KS improvement after UKA in multivariate logistic regression (OR = 1.814, 95% CI: 1.354-2.430, P < 0.001). Before UKA, patients with synovitis had lower pain scores (PS) than patients without synovitis (95% CI: -17.159 - -11.160, t = -9.347, P < 0.001). There was no difference in PS between the two groups after UKA (95% CI: -6.559 - 0.345, t = -1.782, P = 0.077).

CONCLUSIONS

Patients with synovitis can achieve good improvement of pain symptoms, and the efficacy is not inferior to that of non-synovitis patients after UKA.

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.

Posterior subtotal meniscectomy revealed the worst scenario for the progression of osteocartilaginous damage in cases of juvenile discoid lateral meniscus with peripheral tear

INTRODUCTION

We compared subtotal meniscectomy and saucerization with stabilization for osteocartilaginous damage based on injured location and further examined the factors related to osteocartilaginous damage in juvenile discoid lateral meniscus (DLM) with peripheral tear after a follow-up period of at least 5 years.

MATERIALS AND METHODS

We retrospectively reviewed juvenile DLM patients with peripheral tear who underwent arthroscopic surgery with more than 5 years of follow-up. Osteocartilaginous damage, which was identified by osteochondritis dissecans (OCD) development and the whole-organ magnetic resonance imaging score (WORMS) of cartilage grade ≥ 3, was compared between subtotal meniscectomy and saucerization with stabilization. A subgroup analysis examining the location of the tear site was performed. Factors for osteocartilaginous damage were analyzed between the damaged and non-damaged groups.

RESULTS

Forty-one patients, including 29 who underwent saucerization with stabilization and 12 who underwent subtotal meniscectomy, were included in this study. Seven patients developed OCD lesions; six patients showed cartilage WORMS of more than grade 3. Overall, there was a significant difference in the total cartilage and meniscus WORMS between the two groups at the final follow-up. The subgroup analysis demonstrated more severe osteocartilaginous damage developed in posterior subtotal meniscectomy than in posterior stabilization following saucerization. The damaged group showed significant difference compared to the non-damaged group in terms of age (p = 0.003), sex (p = 0.036), and posterior subtotal meniscectomy (p < 0.001).

CONCLUSIONS

Posterior subtotal meniscectomy revealed the worst scenario for the progression of osteocartilaginous damage in cases of juvenile DLM with peripheral tear over a minimum follow-up period of 5 years.

Intra-articular Injection of Bone Marrow Concentrate for Treatment of Patellofemoral Osteoarthritis: Preliminary Results Utilizing an Ultrasound-Guided Marrow Harvesting Technique

OBJECTIVE

To assess the effectiveness of intra-articular injection of bone marrow concentrate (BMC) under ultrasound (US) guidance in the treatment of patellofemoral osteoarthritis (OA), with clinical and volumetric magnetic resonance (MR) imaging follow-up.

METHODS

This retrospective study included 96 consecutive patients referred for US-guided intra-articular injection of BMC for symptomatic patellofemoral OA for which conservative treatment had failed. A control group of 21 patients with symptomatic patellofemoral OA was included for comparison. Data on International Knee Documentation Committee (IKDC), Visual Analog Scale (VAS), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores as well as volumetric MR imaging (using T2 mapping sequence) were collected before and 12 months after injection, and the results were compared.

RESULTS

No technical adverse events were noted during bone marrow aspiration, BMC preparation, or intra-articular injection of BMC. No clinical adverse events were reported during long-term follow-up. All mean scores improved between baseline and 12 months after intra-articular injection of BMC (VAS 5.5 to 3.6, P < .0001; WOMAC 36.8 to 22.2, P < .0001; and IKDC 41.8 to 58.2, P < .0001). MR imaging at 1 year of follow-up after BMC treatment showed no statistically significant difference in hyaline cartilage volume compared with that at the baseline (P = .690), suggesting stabilization of the cartilage degradation process. In contrast, the group of untreated patients showed a significant decrease in the cartilage volume (P = .001), corresponding to a cartilage loss of 6.9%.

CONCLUSIONS

The results suggest that intra-articular injection of BMC under US guidance could be a promising option for the treatment of symptomatic patellofemoral OA and could promote the preservation of healthy residual cartilage volume.

Making the invisible visible-ultrashort echo time magnetic resonance imaging: Technical developments and applications

Magnetic resonance imaging (MRI) uses a large magnetic field and radio waves to generate images of tissues in the body. Conventional MRI techniques have been developed to image and quantify tissues and fluids with long transverse relaxation times (T2s), such as muscle, cartilage, liver, white matter, gray matter, spinal cord, and cerebrospinal fluid. However, the body also contains many tissues and tissue components such as the osteochondral junction, menisci, ligaments, tendons, bone, lung parenchyma, and myelin, which have short or ultrashort T2s. After radio frequency excitation, their transverse magnetizations typically decay to zero or near zero before the receiving mode is enabled for spatial encoding with conventional MR imaging. As a result, these tissues appear dark, and their MR properties are inaccessible. However, when ultrashort echo times (UTEs) are used, signals can be detected from these tissues before they decay to zero. This review summarizes recent technical developments in UTE MRI of tissues with short and ultrashort T2 relaxation times. A series of UTE MRI techniques for high-resolution morphological and quantitative imaging of these short-T2 tissues are discussed. Applications of UTE imaging in the musculoskeletal, nervous, respiratory, gastrointestinal, and cardiovascular systems of the body are included.

Analysing the effects of metallic biomaterial design and imaging sequences on MRI interpretation challenges due to image artefacts

Biometals cause signal loss and susceptibility artefacts in the surrounding tissue, resulting in deterioration in magnetic resonance (MR) images. This metal-artefact effect may lead to interpretation challenges for MR images. Therefore, artefact reduction is required to obtain higher-quality images. This paper aims to analyse the impact of imaging sequence and metallic biomaterial design on MR image artefacts. In this respect, implant specimens were designed in thin, thick, and pointed forms and manufactured using 316LVM, 316L, CoCr-alloy, and Ti-alloy, which are commonly utilized materials in the biomaterials field. Specimens were placed in a phantom that simulates average human anatomy separately and scanned in a 1.5 T MRI under four imaging conditions: "Axial-T₁-Gradient-Echo (GRE)", "Sagittal-T₁-GRE", "Axial-T₂-Spin-Echo (SE)" and "Sagittal-T₂-SE". Images were analysed regarding image artefact amount. The lower magnetic susceptibility of Ti-alloy specimens caused 84.76% less deterioration than 316LVM specimens in the MR images with the mean image artefact-to-specimen size ratio. Thinner implant designs provided better performance regarding the metal artefact by reducing the artefact-to-specimen size ratio. T₂SE decreased the image artefact by 44.7% for 316LVM and 54.6% for Ti-Alloy specimens and provided better image quality than T₁GRE for clinical interpretation. This study reveals that image artefacts directly depend on material content, implant volume, geometry, and imaging sequence selection. The minor artefact effect of T₂SE provides more accurate MR images than T₁GRE regarding the interpretation of the images of the patients with biometals. The higher magnetic susceptibility of biometals causes more deterioration of the images.

Association of Postoperative Lateral Meniscal Extrusion With Cartilage Degeneration on Magnetic Resonance Imaging After Discoid Lateral Meniscus Reshaping Surgery

Background:

Although arthroscopic reshaping surgery for a discoid lateral meniscus (DLM) has good clinical results, it cannot completely prevent degeneration. The degree of DLM extrusion associated with degenerative changes is unclear.

Purpose/Hypothesis:

To measure meniscal extrusion preoperatively and postoperatively in patients who underwent DLM-reshaping surgery and examine factors associated with knee articular cartilage degeneration. It was hypothesized that meniscal extrusion existed preoperatively, progressed postoperatively, and was related to knee joint degeneration.

Study Design:

Case-control study; Level of evidence, 3.

Methods:

We retrospectively reviewed the medical records of patients who underwent DLM-reshaping surgery and attended ≥2 years of follow-up. Magnetic resonance imaging (MRI) was performed preoperatively and at 24 months postoperatively, and residual midbody meniscal extrusion was measured. Cartilage degeneration was detected when the Whole-Organ Magnetic Resonance Imaging Score (WORMS) of the lateral compartment was grade ≥3 at 2 years postoperatively. Factors associated with MRI cartilage degeneration were evaluated.

Results:

Included in this study were 48 knees in 39 patients; the mean patient age at the time of surgery was 12.0 years. The mean midbody meniscal extrusion significantly increased from 0.8 mm preoperatively to 1.6 mm at 24 months postoperatively ( P < .001). According to the WORMS cartilage score, 16 patients were categorized as having MRI cartilage degeneration. Multivariate logistic analysis showed that an inferior preoperative Lysholm score (odds ratio, 0.89; P = .024) and postoperative extrusion (odds ratio, 6.18; P = .010) significantly increased the risk of cartilage degeneration. The receiver operating characteristic curve showed that a residual meniscal extrusion of 2.0 mm was the cutoff value indicating cartilage degeneration (sensitivity, 87.5%; specificity, 78.1%).

Conclusion:

DLM extrusion significantly increased from 0.8 mm preoperatively to 1.6 mm at 2 years postoperatively. Postoperative extrusion and a lower preoperative Lysholm score were factors related to MRI cartilage degeneration postoperatively. A postoperative extrusion of 2.0 mm was the cutoff value for MRI cartilage degeneration.

SPHARM-PDM based image preprocessing pipeline for quantitative morphometric analysis (QMA) for in situ joint assessment in rabbit and rat models

The accessibility of quantitative measurements of joint morphometry depends on appropriate tibial alignment and volume of interest (VOI) selection of joint compartments; often a challenging and time-consuming manual task. In this work, we developed a novel automatic, efficient, and model-invariant image preprocessing pipeline that allows for highly reproducible 3D quantitative morphometric analysis (QMA) of the joint. The pipeline addresses the problem by deploying two modules: an alignment module and a subdivision module. Alignment is achieved by representing the tibia in its basic form using lower degree spherical harmonic basis functions and aligning using principal component analysis. The second module subdivides the joint into lateral and medial VOIs via a watershedding approach based on persistence homology. Multiple repeated micro-computed tomography scans of small (rat) and medium (rabbit) animal knees were processed using the pipeline to demonstrate model invariance. Existing QMA was performed to evaluate the pipeline’s ability to generate reproducible measurements. Intraclass correlation coefficient and mean-normalised root-mean-squared error of more than 0.75 and lower than 9.5%, respectively, were achieved for joint centre of mass, joint contact area under virtual loading, joint space width, and joint space volume. Processing time and technical requirements were reduced compared to manual processing in previous studies.

Fully Automatic Knee Bone Detection and Segmentation on Three-Dimensional MRI

In the medical sector, three-dimensional (3D) images are commonly used like computed tomography (CT) and magnetic resonance imaging (MRI). The 3D MRI is a non-invasive method of studying the soft-tissue structures in a knee joint for osteoarthritis studies. It can greatly improve the accuracy of segmenting structures such as cartilage, bone marrow lesion, and meniscus by identifying the bone structure first. U-net is a convolutional neural network that was originally designed to segment the biological images with limited training data. The input of the original U-net is a single 2D image and the output is a binary 2D image. In this study, we modified the U-net model to identify the knee bone structures using 3D MRI, which is a sequence of 2D slices. A fully automatic model has been proposed to detect and segment knee bones. The proposed model was trained, tested, and validated using 99 knee MRI cases where each case consists of 160 2D slices for a single knee scan. To evaluate the model's performance, the similarity, dice coefficient (DICE), and area error metrics were calculated. Separate models were trained using different knee bone components including tibia, femur, patella, as well as a combined model for segmenting all the knee bones. Using the whole MRI sequence (160 slices), the method was able to detect the beginning and ending bone slices first, and then segment the bone structures for all the slices in between. On the testing set, the detection model accomplished 98.79% accuracy and the segmentation model achieved DICE 96.94% and similarity 93.98%. The proposed method outperforms several state-of-the-art methods, i.e., it outperforms U-net by 3.68%, SegNet by 14.45%, and FCN-8 by 2.34%, in terms of DICE score using the same dataset.

Quantitative evaluation of ankle cartilage in asymptomatic adolescent football players after season by T2-mapping magnetic resonance imaging

BACKGROUND

Ankle sprain affects the structure and function of ankle cartilage. However, it is not clear whether the daily training and competition affect the ankle cartilage without acute injury. Changes in ankle cartilage without injury may influence future strategies to protect ankle function in athletes. This study aimed to evaluate whether the composition of ankle cartilage significantly altered in asymptomatic adolescent football players after a whole season of training and competition using T2-mapping magnetic resonance imaging (MRI).

MATERIALS AND METHODS

12 local club's U17 asymptomatic adolescent football players without abnormalities in routine MRI were included. Routine and T2-mapping MRI were performed to measure the cartilage thickness of tibiotalar joint (TT) and posterior subtalar joint (pST) and T2 values in pre- and post-seasons. All of them took the right side as dominant foot.

RESULTS

In the pre- and post-seasons, cartilage T2 values in TT (talus side) and pST (calcaneus side) were higher than that of TT (tibial side) and pST (talus side) (all p < 0.05), which was caused by magic angle effect and gravity load. No statistically significant differences in thickness after season in the other cartilages of ankle were found compared with that before the season (all p > 0.05). However, T2 values of TT (tibial side and talus side) cartilage in the dominant foot were significantly reduced after season (p = 0.008; p = 0.034). These results indicate that the microstructure of articular cartilage changes in the joints with greater mobility, although no trauma occurred and the gross morphology of cartilage did not change.

CONCLUSION

Changes in the T2 values of tibiotalar joint cartilage in the dominant foot of healthy young athletes before and after the season suggest that the microstructure of cartilage had changed during sports even without injury. This finding suggests that the dominant ankle joint should be protected during football to delay degeneration of the articular cartilage.

Enhancing Stem Cell Therapy for Cartilage Repair in Osteoarthritis-A Hydrogel Focused Approach

Sem cells hold tremendous promise for the treatment of cartilage repair in osteoarthritis. In addition to their multipotency, stem cells possess immunomodulatory effects that can alleviate inflammation and enhance cartilage repair. However, the widely clinical application of stem cell therapy to cartilage repair and osteoarthritis has proven difficult due to challenges in large-scale production, viability maintenance in pathological tissue site and limited therapeutic biological activity. This review aims to provide a perspective from hydrogel-focused approach to address few key challenges in stem cell-based therapy for cartilage repair and highlight recent progress in advanced hydrogels, particularly microgels and dynamic hydrogels systems for improving stem cell survival, retention and regulation of stem cell fate. Finally, progress in hydrogel-assisted gene delivery and genome editing approaches for the development of next generation of stem cell therapy for cartilage repair in osteoarthritis are highlighted.

Open Source Software for Automatic Subregional Assessment of Knee Cartilage Degradation Using Quantitative T2 Relaxometry and Deep Learning

OBJECTIVE

We evaluated a fully automated femoral cartilage segmentation model for measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo (MESE) magnetic resonance imaging (MRI). We open sourced this model and developed a web app available at https://kl.stanford.edu into which users can drag and drop images to segment them automatically.

DESIGN

We trained a neural network to segment femoral cartilage from MESE MRIs. Cartilage was divided into 12 subregions along medial-lateral, superficial-deep, and anterior-central-posterior boundaries. Subregional T2 values and four-year changes were calculated using a radiologist's segmentations (Reader 1) and the model's segmentations. These were compared using 28 held-out images. A subset of 14 images were also evaluated by a second expert (Reader 2) for comparison.

RESULTS

Model segmentations agreed with Reader 1 segmentations with a Dice score of 0.85 ± 0.03. The model's estimated T2 values for individual subregions agreed with those of Reader 1 with an average Spearman correlation of 0.89 and average mean absolute error (MAE) of 1.34 ms. The model's estimated four-year change in T2 for individual subregions agreed with Reader 1 with an average correlation of 0.80 and average MAE of 1.72 ms. The model agreed with Reader 1 at least as closely as Reader 2 agreed with Reader 1 in terms of Dice score (0.85 vs. 0.75) and subregional T2 values.

CONCLUSIONS

Assessments of cartilage health using our fully automated segmentation model agreed with those of an expert as closely as experts agreed with one another. This has the potential to accelerate osteoarthritis research.

Detecting Articular Cartilage and Meniscus Deformation Effects Using Magnetization Transfer Ultrashort Echo Time (MT-UTE) Modeling during Mechanical Load Application: Ex Vivo Feasibility Study

OBJECTIVE

Ultrashort echo time (UTE) magnetic resonance imaging (MRI) sequences have improved imaging of short T2 musculoskeletal (MSK) tissues. UTE-MRI combined with magnetization transfer modeling (UTE-MT) has demonstrated robust assessment of MSK tissues. This study aimed to investigate the variation of UTE-MT measures under mechanical loading in tibiofemoral cartilage and meniscus of cadaveric knee joints.

DESIGN

Fourteen knee joints from young (n = 8, 42 ± 12 years old) and elderly (n = 6, 89 ± 4 years old) donors were scanned on a 3-T scanner under 3 loading conditions: load = 300 N (Load1), load = 500 N (Load2), and load = 0 N (Unload). UTE-MT sequences were performed at each loading condition. Macromolecular proton fraction (MMF) was calculated from UTE-MT modeling. Wilcoxon rank sum test was used to examine the MRI data differences between loading conditions.

RESULTS

For young donors, MMF increased in all grouped regions of interest (meniscus [M], femoral articular cartilage [FAC], tibial articular cartilage [TAC], articular cartilage regions covered by meniscus [AC-MC], and articular cartilage regions uncovered by meniscus [AC-UC]) when the load increased from 300 to 500 N. The increases in MMF were significant for M (13.3%, P < 0.01) and AC-MC (9.2%, P = 0.04). MMF decreased in all studied regions after unloading, which was significant only for AC-MC (-8.9%, P = 0.01). For elderly donors, MRI parameters did not show significant changes by loading or unloading.

CONCLUSION

This study highlights the potential of the UTE-MT modeling combined with knee loading in differentiating between normal and abnormal knees. Average tissue deformation effects were likely higher and more uniformly distributed in the joints of young donors compared with elderly donors.

Intra-Articular Injection of Autologous Microfat and Platelet-Rich Plasma in the Treatment of Knee Osteoarthritis: A Double-Blind Randomized Comparative Study

PURPOSE

To compare a single abdominal microfat (MF) injection mixed or not with platelet-rich plasma (PRP) Low Dose (LD) or High Dose (HD) in order to improve MRI parameters, alleviate pain and enhance functional capacity in knee osteoarthritis.

METHODS

Patients with symptomatic grade 2 to 4 knee osteoarthritis according to the International Cartilage Repair Society MRI classification were selected. They were prospectively assessed at baseline and at 3 and 6 months of follow-up. The primary endpoint was change in the maximum of value of cartilage relaxation time in T2 mapping sequences (T2max) at 3 months. Secondary endpoints were MRI grade severity and joint space assessment, Western Ontario and McMaster Universities Arthritis Index score, pain evaluation, knee range of motion, and patients' satisfaction. Adverse events were also collected. The complete cell counts and growth factors content of injected products were assessed to analyze their potential relationship with MRI and clinical outcomes.

RESULTS

Three groups of 10 patients received a single injection of 10 cc of a mix (1:1) containing MF-Saline, MF-PRP LD or MF-PRP HD. T2max did not change significantly over the time for any of the groups. All treatments significantly improved knee functional status and symptom relief at 3 and 6 months. All patients were responders in the MF/PRP HD at 3 months and significantly higher compared to MF/PRP LD. Half of the injected PRP in the MF/PRP LD group displayed red blood cell contamination of over 8%, which was correlated with an impairment of T2max.

CONCLUSION

A single intra-articular injection of MF with or without PRP is safe and may offer a significant clinical improvement in patients with osteoarthritis.

LEVEL OF EVIDENCE

2; randomized double-blind comparative parallel-group trial (RCT No.: NCT04352075).

Difference in the joint space of the medial knee compartment between full extension and Rosenberg weight-bearing radiographs

Objectives

Radiographs are the most widespread imaging tool for diagnosing osteoarthritis (OA) of the knee. Our purpose was to determine which of the two factors, medial meniscus extrusion (MME) or cartilage thickness, had a greater effect on the difference in the minimum joint space width (mJSW) at the medial compartment between the extension anteroposterior view (extension view) and the 45° flexion posteroanterior view (Rosenberg view).

Methods

The subjects were 546 participants (more than 50 females and 50 males in their 30 s, 40 s, 50 s, 60 s, and 70 s) in the Kanagawa Knee Study. The mJSW at the medial compartment was measured from both the extension and the Rosenberg views, and the “mJSW difference” was defined as the mJSW in the Rosenberg view subtracted from the mJSW in the extension view. The cartilage region was automatically extracted from MRI data and constructed in three dimensions. The medial region of the femorotibial joint cartilage was divided into 18 subregions, and the cartilage thickness in each subregion was determined. The MME was also measured from MRI data.

Results

The mJSW difference and cartilage thickness were significantly correlated at 4 subregions, with 0.248 as the highest absolute value of the correlation coefficient. The mJSW difference and MME were also significantly correlated, with a significantly higher correlation coefficient (0.547) than for the mJSW difference and cartilage thickness.

Conclusions

The MME had a greater effect than cartilage thickness on the difference between the mJSW at the medial compartment in the extension view and in the Rosenberg view.

Key Points

• The difference in the width at the medial compartment of the knee between the extension and the flexion radiographic views was more affected by medial meniscus extrusion than by cartilage thickness.

T2-mapping MRI evaluation of patellofemoral cartilage in patients submitted to intra-articular platelet-rich plasma (PRP) injections

This study evaluated the ability of T2 mapping magnetic resonance imaging at 3 T, in addition to morphological sequences, to assess efficacy of platelet-rich plasma (PRP) injections, characterizing qualitatively and quantitatively the grade of knee cartilage repair in patients with patellofemoral chondropathy. We retrospectively studied 34 patients (22 men, 12 women, mean age 41.8 years, including 22 men) with patellofemoral knee chondropathy, who underwent intra-articular PRP injections and completed a clinical and instrumental follow-up. As control group, we evaluated 34 patients who underwent non-operative therapy. All patients were submitted to clinical (using VAS and WOMAC index) and imaging studies with 3 T magnetic resonance with cartilage analysis with T2 mapping sequences for cartilage analysis before and after treatment. In the study group, mean pre-treatment T2 relaxation time values were 44.2 ± 2.5 ms, considering all articular cartilage compartments, with significant reduction at the follow-up (p < 0.001). At the index compartment, mean pre-treatment T2 relaxation times values were 47.8 ± 3.6 ms, with statistically significant reduction at the follow-up (p < 0.001). Evaluation of focal cartilage lesions reported pre-treatment mean T2 value of 70.1 ± 13.0 ms and post-treatment mean value of 59.9 ± 4.6 ms (p < 0.001). From a clinical point of view, the pre-treatment WOMAC and VAS scores were 18.3 ± 4.5 and 7 (IQR:6-7.2), respectively; the post-treatment values were 7.3 ± 3.2 and 2 (IQR: 1.7-3.0), respectively (p < 0.001). In the control group, despite clinical improvement, we didn't find significant T2 values change during the follow-up period. In conclusion, T2 mapping is a valuable indicator for chondropathy and treatment-related changes over time.

Association between meniscal volume and development of knee osteoarthritis

OBJECTIVE

To assess the association between meniscal volume, its change over time and the development of knee OA after 30 months in overweight/obese women.

METHODS

Data from the PRevention of knee Osteoarthritis in Overweight Females study were used. This cohort included 407 women with a BMI ≥ 27 kg/m2, free of OA-related symptoms. The primary outcome measure was incident OA after 30 months, defined by one out of the following criteria: medial or lateral joint space narrowing (JSN)  ≥ 1.0 mm, incident radiographic OA [Kellgren and Lawrence (K&L)  ≥ 2], or incident clinical OA. The secondary outcomes were either of these items separately. Menisci at both baseline and follow-up were automatically segmented to obtain meniscal volume and delta-volumes. Generalized estimating equations were used to evaluate associations between the volume measures and the outcomes.

RESULTS

Medial and lateral baseline and delta-volumes were not significantly associated to the primary outcome. Lateral meniscal baseline volume was significantly associated to lateral JSN [odds ratio (OR) = 0.87; 95% CI: 0.75, 0.99], while other measures were not. Medial and lateral baseline volume were positively associated to K&L incidence (OR = 1.32 and 1.22; 95% CI: 1.15, 1.50 and 1.03, 1.45, respectively), while medial and lateral delta-volume were negatively associated to K&L incidence (OR = 0.998 and 0.997; 95% CI: 0.997, 1.000 and 0.996, 0.999, respectively). None of the meniscal measures were significantly associated to incident clinical OA.

CONCLUSION

Larger baseline meniscal volume and the decrease of meniscal volume over time were associated to the development of structural OA after 30 months in overweight and obese women.

Serum cartilage oligomeric matrix protein is correlated with quantitative magnetic resonance imaging and arthroscopic cartilage findings in anterior cruciate ligament deficient knees without osteoarthritic changes

INTRODUCTION/OBJECTIVES

To investigate the association between serum biomarker [cartilage oligomeric matrix protein (COMP) and matrix metalloproteinase-3 (MMP-3)] levels and clinical, magnetic resonance imaging (MRI), and arthroscopic findings in anterior cruciate ligament (ACL)-deficient knees without osteoarthritic changes on radiographs.

METHOD

Patients with ACL injury of Kellgren-Lawrence grade 0 or 1 were enrolled. Serum COMP and MMP-3 levels were measured preoperatively. Correlations of serum biomarker levels with age, body mass index (BMI), duration from time of injury, Tegner activity scale (TAS) score, Lysholm knee score, International Knee Documentation Committee score, KT-1000 arthrometer measurements, whole-organ MRI score (WORMS), MRI T2 relaxation time, and arthroscopic International Cartilage Research Society (ICRS) grade were assessed by calculating Spearman correlation coefficients. Associations between intraoperative findings (cartilage, meniscus) and serum biomarker levels were determined using the Mann-Whitney U test. Multiple regression analysis was performed to investigate the correlations between serum biomarker levels and MRI and arthroscopic findings.

RESULTS

Ninety-eight patients with a mean age of 23.7 years were enrolled. Higher serum COMP level was correlated with older age and higher BMI, TAS score, serum MMP-3 level, WORMS, and T2 relaxation times (medial femur, medial tibia). Multivariate analysis showed that the serum COMP level was independently associated with WORMS and ICRS grade.

CONCLUSIONS

The serum COMP level was correlated with age, BMI, TAS score, and MMP-3 level in ACL-deficient knees and was independently correlated with WORMS and ICRS grade. Thus, the serum COMP level can help detect cartilage degeneration even in patients without radiographic osteoarthritic changes. Key Points • Serum COMP correlated with WORMS and ICRS grade in ACL deficient knee. • The serum COMP level could help in detecting cartilage degeneration, even in patients with no radiographic osteoarthritic changes.

Improving subspace constrained radial fast spin echo MRI using block matching driven non-local low rank regularization

Subspace-constrained reconstruction methods restrict the relaxation signals (of size M) in the scene to a pre-determined subspace (of size K≪M) and allow multi-contrast imaging and parameter mapping from accelerated acquisitions. However, these constraints yield poor image quality at some imaging contrasts, which can impact the parameter mapping performance. Additional regularization such as the use of joint-sparse (JS) or locally-low-rank (LLR) constraints can help improve the recovery of these images but are not sufficient when operating at high acceleration rates. We propose a method, non-local rank 3D (NLR3D), that is built on block matching and transform domain low rank constraints to allow high quality recovery of subspace-coefficient images (SCI) and subsequent multi-contrast imaging and parameter mapping. The performance of NLR3D was evaluated using Monte-Carlo (MC) simulations and compared against the JS and LLR methods. In vivo T 2 mapping results are presented on brain and knee datasets. MC results demonstrate improved bias, variance, and MSE behavior in both the multi-contrast images and parameter maps when compared to the JS and LLR methods. In vivo brain and knee results at moderate and high acceleration rates demonstrate improved recovery of high SNR early TE images as well as parameter maps. No significant difference was found in the T2 values measured in ROIs between the NLR3D reconstructions and the reference images (Wilcoxon signed rank test). The proposed method, NLR3D, enables recovery of high-quality SCI and, consequently, the associated multi-contrast images and parameter maps.

Calcified cartilage in patients with osteoarthritis of the hip compared to that of healthy subjects. A design-based histological study

OBJECTIVE

Calcified cartilage is suggested to be involved in the pathogenesis of osteoarthritis (OA) by facilitating endochondral ossification at the bone-cartilage unit. Therefore, the objective was to quantify the volume and surface area of the calcified cartilage in the femoral head in OA patients and healthy subjects.

MATERIALS AND METHODS

We used design-based stereological principles, i.e., systematic uniform random sampling and vertical uniform random sections of the entire femoral head. We investigated the articular and calcified cartilage and femoral head surface area and volume, excluding fovea capitis and marginal osteophytes, in 20 patients with OA and 15 healthy subjects.

RESULTS

The volume of the calcified cartilage was significantly larger for the patients with OA compared with the healthy subjects (mean difference [95% CI]) (284 [110,457] mm³, p = 0.002). The upper and lower surface area of the calcified cartilage, i.e. the tidemark and cement line, were both significantly larger for OA patients compared with the healthy subjects (17.8 [8.4,27.3] cm², p < 0.001) and (38.7 [20.8,56.7] cm², p = 0.002), respectively. The volume of the calcified cartilage and the volume of the femoral head were significantly correlated for the patients with OA (Spearman's ρ = 0.51, p = 0.021), but not for the healthy subjects (ρ = 0.41, p = 0.123).

CONCLUSIONS

Patients with OA had a larger femoral head surface area and more calcified cartilage compared to healthy subjects. The volume of the calcified cartilage correlated positively with the volume of the femoral head for patients with OA, but not for healthy subjects. This strongly supports the existing view that bone growth in OA is associated with endochondral ossification.

Relationship between medial meniscus extrusion and cartilage measurements in the knee by fully automatic three-dimensional MRI analysis

BACKGROUND

We developed a fully automatic three-dimensional knee MRI analysis software that can quantify meniscus extrusion and cartilage measurements, including the projected cartilage area ratio (PCAR), which represents the ratio of the subject's actual cartilage area to their ideal cartilage area. We also collected 3D MRI knee data from 561 volunteers (aged 30-79 years) from the "Kanagawa Knee Study." Our purposes were to verify the accuracy of the software for automatic cartilage and meniscus segmentation using knee MRI and to examine the relationship between medial meniscus extrusion measurements and cartilage measurements from Kanagawa Knee Study data.

METHODS

We constructed a neural network for the software by randomly choosing 10 healthy volunteers and 103 patients with knee pain. We validated the algorithm by randomly selecting 108 of these 113 subjects for training, and determined Dice similarity coefficients from five other subjects. We constructed a neural network using all data (113 subjects) for training. Cartilage thickness, cartilage volume, and PCAR in the medial femoral, lateral femoral, medial tibial, and lateral tibial regions were quantified by using the trained software on Kanagawa Knee Study data and their relationship with subject height was investigated. We also quantified the medial meniscus coverage ratio (MMCR), defined as the ratio of the overlapping area between the medial meniscus area and the medial tibial cartilage area to the medial tibial cartilage area. Finally, we examined the relationship between MMCR and PCAR at middle central medial tibial (mcMT) subregion located in the center of nine subregions in the medial tibial cartilage.

RESULTS

Dice similarity coefficients for cartilage and meniscus were both approximately 0.9. The femoral and tibial cartilage thickness and volume at each region correlated with height, but PCAR did not correlate with height in most settings. PCAR at the mcMT was significantly correlated with MMCR.

CONCLUSIONS

Our software showed high segmentation accuracy for the knee cartilage and meniscus. PCAR was more useful than cartilage thickness or volume since it was less affected by height. Relations ips were observed between the medial tibial cartilage measurements and the medial meniscus extrusion measurements in our cross-sectional study.

TRIAL REGISTRATION

UMIN, UMIN000032826 ; 1 September 2018.

Quantitative measurement of cartilage volume with automatic cartilage segmentation in knee osteoarthritis

PURPOSE

To determine the reproducibility of the automatic cartilage segmentation method using a prototype KneeCaP software (version 1.3; Siemens Healthcare, Erlangen, Germany) and to compare the difference in cartilage volume (CV) between the normal knee joint and knee osteoarthritis (KOA) of different degrees by using the above software.

MATERIALS AND METHODS

The study included 62 subjects with knee OA and 29 healthy control subjects. The cartilage lesion patients were divided into a mild-to-moderate OA group (n = 29) and severe OA group (n = 33). Automatic cartilage segmentation was performed on all the subjects, and among them, 19 knee cases were randomly selected to also do the manual cartilage segmentation. Statistical significance was determined with one-way analysis of variance (ANOVA), intraclass correlation coefficient (ICC), and Pearson correlation coefficient. Automatic segmentation was compared with the manual one. The relative cartilage volume percentages of the femur, tibia, and patella in the normal control/mild-to-moderate/severe OA groups were assessed.

RESULTS

Comparing the cartilage volumes derived by manual and automatic segmentation, the ICC value for the knee joint, patella, femur, or tibia was 0.784, 0.815, 0.740, and 0.797. The relative cartilage volume percentages of the femur, tibia, and patella in the normal control/mild-to-moderate/severe OA groups were 57.28%/59.30%/62.45% (femur), 25.35%/23.46%/21.84% (tibia), and 17.37%/17.24%/15.71% (patella), respectively. Compared with the normal control group, the relative tibia cartilage volume percentage was lower in the mild-to-moderate OA group and the severe OA group. Corresponding index showed a similar difference between the mild-to-moderate OA group and the severe OA group (p < 0.001).

CONCLUSION

This study demonstrated that the relative cartilage volume percentage is correlated with the semi-quantitative systems and may be a preferred outcome measure in clinical studies of OA. Automatic cartilage segmentation using KneeCaP delivered reliable results on high-spatial-resolution 3 T MR images for the healthy, mild-moderate OA patients. Key Points • The cartilage automatic segmentation has excellent reproducibility and was not affected by inter-observer variation. • The relative cartilage volume percentage is correlated with the semi-quantitative systems and may be a preferred outcome measure in clinical studies of OA.

Bone Age Assessment Empowered with Deep Learning: A Survey, Open Research Challenges and Future Directions

Deep learning is a quite useful and proliferating technique of machine learning. Various applications, such as medical images analysis, medical images processing, text understanding, and speech recognition, have been using deep learning, and it has been providing rather promising results. Both supervised and unsupervised approaches are being used to extract and learn features as well as for the multi-level representation of pattern recognition and classification. Hence, the way of prediction, recognition, and diagnosis in various domains of healthcare including the abdomen, lung cancer, brain tumor, skeletal bone age assessment, and so on, have been transformed and improved significantly by deep learning. By considering a wide range of deep-learning applications, the main aim of this paper is to present a detailed survey on emerging research of deep-learning models for bone age assessment (e.g., segmentation, prediction, and classification). An enormous number of scientific research publications related to bone age assessment using deep learning are explored, studied, and presented in this survey. Furthermore, the emerging trends of this research domain have been analyzed and discussed. Finally, a critical discussion section on the limitations of deep-learning models has been presented. Open research challenges and future directions in this promising area have been included as well.

T1rho and T2 mapping of ankle cartilage of female and male ballet dancers

BACKGROUND

Since ballet dancers begin their training before skeletal maturity, accurate and non-invasive identification of cartilage diseases is clinically important. Angle-dependent analysis of T1rho and T2 sequences can be useful for quantification of the composition of cartilage.

PURPOSE

To investigate the angle-dependent T1rho and T2 profiles of ankle cartilage in non-dancers and dancers.

MATERIAL AND METHODS

Ten female non-dancers, ten female dancers, and 9 male dancers were evaluated using T1rho and T2 mapping sequences. Manual segmentation of talar and tibial cartilage on these images was performed by two radiologists. Inter- and intra-rater reliabilities were calculated using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. Mean thickness and volume of cartilage were estimated. Angle-dependent relaxation time profiles of talar and tibial cartilage were created.

RESULTS

ICCs of the number of segmented pixels were poor to excellent. Bland-Altman plots indicated that differences were associated with segment sizes. Segmented cartilage on T1rho demonstrated larger thickness and volume than those on T2 in all populations. Male dancers showed larger cartilage thickness and volume than female dancers and non-dancers. Each cartilage demonstrated angular-dependent T1rho and T2 profiles. Minimal T1rho and T2 values were observed at approximately 180°-200°; higher values were seen at the angle closer to the magic angle. Minimal T2 value of talar cartilage of dancers was larger than that of non-dancers.

CONCLUSION

In this small cohort study, regional and sex variations of ankle cartilage T1rho and T2 values in dancers and non-dancers were demonstrated using an angle-dependent approach.

Magic angle effect on adiabatic T1ρ imaging of the Achilles tendon using 3D ultrashort echo time cones trajectory

The protons in collagen-rich musculoskeletal (MSK) tissues such as the Achilles tendon are subject to strong dipolar interactions which are modulated by the term (3cos² θ-1) where θ is the angle between the fiber orientation and the static magnetic field B₀ . The purpose of this study was to investigate the magic angle effect in three-dimensional ultrashort echo time Cones Adiabatic T_1ρ (3D UTE Cones-AdiabT_1ρ ) imaging of the Achilles tendon using a clinical 3 T scanner. The magic angle effect was investigated by Cones-AdiabT_1ρ imaging of five cadaveric human Achilles tendon samples at five angular orientations ranging from 0° to 90° relative to the B₀ field. Conventional Cones continuous wave T_1ρ (Cones-CW-T_1ρ ) and Cones T₂ * (Cones-T₂ *) sequences were also applied for comparison. On average, Cones-AdiabT_1ρ increased 3.6-fold from 13.6 ± 1.5 ms at 0° to 48.4 ± 5.4 ms at 55°, Cones-CW-T_1ρ increased 6.1-fold from 7.0 ± 1.1 ms at 0° to 42.6 ± 5.2 ms at 55°, and Cones-T2* increased 12.3-fold from 2.9 ± 0.5 ms at 0° to 35.8 ± 6.4 ms at 55°. Although Cones-AdiabT_1ρ is still subject to significant angular dependence, it shows a much-reduced magic angle effect compared to Cones-CW-T_1ρ and Cones-T₂ *, and may be used as a novel and potentially more effective approach for quantitative evaluation of the Achilles tendon and other MSK tissues.

Improving Quantitative Magnetic Resonance Imaging Using Deep Learning

Deep learning methods have shown promising results for accelerating quantitative musculoskeletal (MSK) magnetic resonance imaging (MRI) for T2 and T1ρ relaxometry. These methods have been shown to improve musculoskeletal tissue segmentation on parametric maps, allowing efficient and accurate T2 and T1ρ relaxometry analysis for monitoring and predicting MSK diseases. Deep learning methods have shown promising results for disease detection on quantitative MRI with diagnostic performance superior to conventional machine-learning methods for identifying knee osteoarthritis.

Convincing evidence for magic angle less-sensitive quantitative T1ρ imaging of articular cartilage using the 3D ultrashort echo time cones adiabatic T1ρ (3D UTE cones-AdiabT1ρ ) sequence

PURPOSE

To investigate the magic angle effect in three-dimensional ultrashort echo time Cones Adiabatic T_1ρ (3D UTE Cones-AdiabT_1ρ ) imaging of articular cartilage at 3T.

METHODS

The magic angle effect was investigated by repeated 3D UTE Cones-AdiabT_1ρ imaging of eight human patellar samples at five angular orientations ranging from 0° to 90° relative to the B₀ field. Cones continuous wave T_1ρ (Cones-CW-T_1ρ ) and Cones- T 2 ∗ sequences were also applied for comparison. Cones-AdiabT_1ρ , Cones-CW-T_1ρ and Cones- T 2 ∗ values were measured for four regions of interest (ROIs) (10% superficial layer, 60% transitional layer, 30% radial layer, and a global ROI) for each sample at each orientation to evaluate their angular dependence.

RESULTS

3D UTE Cones-AdiabT_1ρ values increased from the radial layer to the superficial layer for all angular orientations. The superficial layer showed the least angular dependence (around 4.4%), while the radial layer showed the strongest angular dependence (around 34.4%). Cones-AdiabT_1ρ values showed much reduced magic angle effect compared to Cones-CW-T_1ρ and Cones- T 2 ∗ values for all four ROIs. On average over eight patellae, Cones-AdiabT_1ρ values increased by 27.2% (4.4% for superficial, 23.8% for transitional, and 34.4% for radial layers), Cones-CW-T_1ρ values increased by 76.9% (11.3% for superficial, 59.1% for transitional, and 117.8% for radial layers), and Cones- T 2 ∗ values increased by 237.5% (87.9% for superficial, 262.9% for transitional, and 327.3% for radial layers) near the magic angle.

CONCLUSIONS

The 3D UTE Cones-AdiabT_1ρ sequence is less sensitive to the magic angle effect in the evaluation of articular cartilage compared to Cones- T 2 ∗ and Cones-CW-T_1ρ .

Time-saving opportunities in knee osteoarthritis: T2 mapping and structural imaging of the knee using a single 5-min MRI scan

OBJECTIVES

To assess the discriminative power of a 5-min quantitative double-echo steady-state (qDESS) sequence for simultaneous T2 measurements of cartilage and meniscus, and structural knee osteoarthritis (OA) assessment, in a clinical OA population, using radiographic knee OA as reference standard.

METHODS

Fifty-three subjects were included and divided over three groups based on radiographic and clinical knee OA: 20 subjects with no OA (Kellgren-Lawrence grade (KLG) 0), 18 with mild OA (KLG2), and 15 with moderate OA (KLG3). All patients underwent a 5-min qDESS scan. We measured T2 relaxation times in four cartilage and four meniscus regions of interest (ROIs) and performed structural OA evaluation with the MRI Osteoarthritis Knee Score (MOAKS) using qDESS with multiplanar reformatting. Between-group differences in T2 values and MOAKS were calculated using ANOVA. Correlations of the reference standard (i.e., radiographic knee OA) with T2 and MOAKS were assessed with correlation analyses for ordinal variables.

RESULTS

In cartilage, mean T2 values were 36.1 ± SD 4.3, 40.6 ± 5.9, and 47.1 ± 4.3 ms for no, mild, and moderate OA, respectively (p < 0.001). In menisci, mean T2 values were 15 ± 3.6, 17.5 ± 3.8, and 20.6 ± 4.7 ms for no, mild, and moderate OA, respectively (p < 0.001). Statistically significant correlations were found between radiographic OA and T2 and between radiographic OA and MOAKS in all ROIs (p < 0.05).

CONCLUSION

Quantitative T2 and structural assessment of cartilage and meniscus, using a single 5-min qDESS scan, can distinguish between different grades of radiographic OA, demonstrating the potential of qDESS as an efficient tool for OA imaging.

KEY POINTS

• Quantitative T2values of cartilage and meniscus as well as structural assessment of the knee with a single 5-min quantitative double-echo steady-state (qDESS) scan can distinguish between different grades of knee osteoarthritis (OA). • Quantitative and structural qDESS-based measurements correlate significantly with the reference standard, radiographic degree of OA, for all cartilage and meniscus regions. • By providing quantitative measurements and diagnostic image quality in one rapid MRI scan, qDESS has great potential for application in large-scale clinical trials in knee OA.

Quantitative three-dimensional ultrashort echo time cones imaging of the knee joint with motion correction

Knee degeneration involves all the major tissues in the joint. However, conventional MRI sequences can only detect signals from long T2 tissues such as the superficial cartilage, with little signal from the deep cartilage, menisci, ligaments, tendons and bone. It is highly desirable to develop new sequences that can detect signal from all major tissues in the knee. We aimed to develop a comprehensive quantitative three-dimensional ultrashort echo time (3D UTE) cones imaging protocol for a truly "whole joint" evaluation of knee degeneration. The protocol included 3D UTE cones actual flip angle imaging (3D UTE-Cones-AFI) for T₁ mapping, multiecho UTE-Cones with fat suppression for T₂ * mapping, UTE-Cones with adiabatic T_1ρ (AdiabT_1ρ ) preparation for AdiabT_1ρ mapping, and UTE-Cones magnetization transfer (UTE-Cones-MT) for MT ratio (MTR) and modeling of macromolecular proton fraction (f). An elastix registration technique was used to compensate for motion during scans. Quantitative data analyses were performed on the registered data. Three knee specimens and 15 volunteers were evaluated at 3 T. The elastix motion correction algorithm worked well in correcting motion artifacts associated with relatively long scan times. Much improved curve fitting was achieved for all UTE-Cones biomarkers with greatly reduced root mean square errors. The averaged T₁ , T₂ *, AdiabT_1ρ , MTR and f for knee joint tissues of 15 healthy volunteers were reported. The 3D UTE-Cones quantitative imaging techniques (ie, T₁ , T₂ *, AdiabT_1ρ , MTR and MT modeling) together with elastix motion correction provide robust volumetric measurement of relaxation times, MTR and f of both short and long T₂ tissues in the knee joint.

Magnetic resonance imaging (MRI) studies of knee joint under mechanical loading: Review

Osteoarthritis (OA) is a very common disease that affects the human knee joint, particularly the articular cartilage and meniscus components which are regularly under compressive mechanical loads. Early-stage OA diagnosis is essential as it allows for timely intervention. The primary non-invasive approaches currently available for OA diagnosis include magnetic resonance imaging (MRI), which provides excellent soft tissue contrast at high spatial resolution. MRI-based knee investigation is usually performed on joints at rest or in a non-weight-bearing condition that does not mimic the actual physiological condition of the joint. This discrepancy may lead to missed detections of early-stage OA or of minor lesions. The mechanical properties of degenerated musculoskeletal (MSK) tissues may vary markedly before any significant morphological or structural changes detectable by MRI. Recognizing distinct deformation characteristics of these tissues under known mechanical loads may reveal crucial joint lesions or mechanical malfunctions which result from early-stage OA. This review article summarizes the large number of MRI-based investigations on knee joints under mechanical loading which have been reported in the literature including the corresponding MRI measures, the MRI-compatible devices employed, and potential challenges due to the limitations of clinical MRI sequences.

Cartilage evaluation in finger joints in healthy controls and early hand osteoarthritis patients using high-resolution MRI

OBJECTIVE

To compare direct evaluation of cartilage with high resolution MRI (hrMRI) to indirect cartilage evaluation using MRI inter-bone distance in hand OA patients and healthy controls.

DESIGN

41 hand OA patients and 18 healthy controls underwent hrMRI of the 2^nd and 3^rd metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints. The images were read by two independent readers using OMERACT hand OA MRI inter-bone distance score (0-3 scale) and a new hrMRI cartilage score with direct evaluation of the cartilage (0-3 scale). Inter-reader and intra-reader reliability was calculated using exact and close agreement and kappa values. The prevalence of abnormal scores and agreement between methods was assessed in both hand OA patients and healthy controls.

RESULTS

The intra- and inter-reader reliability of both scores was comparable, with exact agreement in 73-83% and close agreement in 95-100%. In hand OA patients 27% of 161 joints had both cartilage damage and loss of inter-bone distance, cartilage damage by hrMRI only was present in 20% of joints and reduced inter-bone distance only in 4% of joints. In the healthy controls, 1 of 71 joints were scored as abnormal by both hrMRI and inter bone distance scoring, 1 joint was scored as abnormal using the hrMRI cartilage score only, whereas 15% of joints had only reduced inter bone distance.

CONCLUSIONS

Direct cartilage evaluation of MCP and PIP joints using hrMRI has a good reliability, and the higher prevalence of hrMRI cartilage damage in hand OA patients and the lower prevalence in healthy controls in comparison to evaluation of inter-bone distance suggests a better validity.

Longitudinal Changes in the Total Knee Joint Moment After Anterior Cruciate Ligament Reconstruction Correlate With Cartilage Thickness Changes

This study investigated associations between changes in the total joint moment (TJM) at the knee and changes in cartilage thickness after anterior cruciate ligament reconstruction (ACLR). Seventeen subjects (five males; age: 29.6 ± 7.3 years) with unilateral ACLR underwent gait analysis and magnetic resonance imaging at baseline (2.2 ± 0.3 years post-ACLR) and at long-term follow-up (7.7 ± 0.7 years post-ACLR). Knee loading was assessed using the TJM, and differences in loading were analyzed using repeated measures analysis of variance. Pearson correlation coefficients assessed associations between changes in TJM and changes in (medial-to-lateral) M/L femoral cartilage thickness ratios in the ACLR limb. Bilaterally, there was no significant change in the magnitude of the TJM first peak (TJM1), however, there was a significant increase in the percent contribution of the knee flexion moment (KFM) (p < 0.001) and decrease in the percent contribution of the knee adduction moment (KAM) to TJM1 (p < 0.001). The change in the percent contributions of KFM and KAM to TJM1 were associated with changes in M/L femoral cartilage thickness in the ACLR limb. Specifically, subjects with smaller increases in KFM contribution (R = 0.521, p = 0.032) and smaller decreases in KAM contribution (R = -0.521, p = 0.032) had a reduction in the M/L ratio in the central femoral subregion over the follow-up period, with similar trends in the external femoral subregion. The study results provide new insight into changes in the loading environment at the knee joint prospectively following ACL reconstruction and give evidence that there are modifiable gait metrics that are associated with cartilage changes after ACLR. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1546-1554, 2019.

The trends in robotic-assisted knee arthroplasty: A statewide database study

Objective

Recent technological advancements have led to the utilization of robotic-assisted knee arthroplasty (raKA) in the operating room.

Methods

All patients who underwent knee arthroplasty from 2009 to 2013 in NYS SPARCS were reviewed. raKAs and non-raKAs were compared for utilization and institutional trends.

Results

Robotic-assistance increased by 500%. 80% of raKAs were performed in teaching hospitals. The trend increase was greater in teaching hospitals. Blood transfusion rates differed between raKA and non-raKA (6.6% vs. 10.9%, p < 0.001).

Conclusion

raKA utilization increased in NYS, moreso within teaching hospitals. raKA transfusion rates were lower but higher in teaching hospitals, potentially related to learning curve.

The Possibilities of Magnetic Resonance Imaging in the Diagnosis of Microstructural Changes of the Subchondral Bone in Osteoarthritis

Background. Magnetic resonance imaging not only has powerful capabilities for visualization, but is also of interest in terms of obtaining ideas about microstructural and biochemical changes in the tissues of the joints in osteoarthritis.

Aims. To assess the possibility of T2-images of magnetic resonance imaging in the diagnosis of microstructural changes in the subchondral bone in osteoarthritis.

Materials and methods. 62 patients with osteoarthritis and 8 volunteers without osteoarthritis were examined. All patients underwent magnetic resonance imaging of knee. To assess the variability of transverse relaxation time, the T2-images segmentation of the subchondral segmentation in the frontal projection was performed by hand. The proton density was estimated from a 3D histogram on a scale of 0 to 255.

Results. At the first stage of osteoarthritis, the intensity of the magnetic resonance signal decreases over the entire surface of the tibial plateau, with minimal values in the region of the medial part of the knee joint. At stage 2 osteoarthritis, there was an even greater decrease in the number of protons that made the phase transition with the lowest value in the medial region. The subchondral bone texture in stage 3 was characterized by a significant decrease in signal intensity in the region of the medial plateau of the tibia. In the terminal stage of osteoarthritis.

Conclusion. The revealed regularity of the change in the relaxation time spectrum of T2-images reflects the degenerative process in subchondral bone with osteoarthritis.

Assessment of frequency drift on CEST MRI and dynamic correction: application to gagCEST at 7 T

PURPOSE

To investigate the effect of a frequency drift of the static magnetic field on 3D CEST MRI based on glycosaminoglycans (GAGs) of articular cartilage at 7 T and to introduce a retrospective correction method that uses the phase images of the gradient-echo readout.

METHODS

Repeated gagCEST and B0 measurements were performed in a glucose model solution and in vivo in the knee joint of 3 healthy volunteers at 7 T. Phase images of the modified 3D rectangular spiral centric-reordered gradient-echo CEST sequence were used to quantify and compensate the apparent frequency drift in repeated gagCEST measurements.

RESULTS

The frequency drift of the MRI scanner strongly influences the gagCEST signal in the articular cartilage of the human knee joint. The gagCEST signal in the articular cartilage is changed by 0.18%/Hz while an average drift of 0.7 ± 0.2 Hz/minute was observed. The proposed correction method can be applied retrospectively without the need of additional measurements and provides improved comparability and reproducibility for gagCEST studies. This correction method may also be of interest for other applications of CEST MRI.

CONCLUSION

Prospective or retrospective correction of the frequency drift of the MRI scanner is essential for reproducible gagCEST measurements. The proposed retrospective correction method fulfills this requirement without the need of additional measurements.

Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative

We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imaging (MRI) that combines a priori knowledge of anatomical shape with Convolutional Neural Networks (CNNs). The proposed approach incorporates 3D Statistical Shape Models (SSMs) as well as 2D and 3D CNNs to achieve a robust and accurate segmentation of even highly pathological knee structures. The shape models and neural networks employed are trained using data from the Osteoarthritis Initiative (OAI) and the MICCAI grand challenge "Segmentation of Knee Images 2010" (SKI10), respectively. We evaluate our method on 40 validation and 50 submission datasets from the SKI10 challenge. For the first time, an accuracy equivalent to the inter-observer variability of human readers is achieved in this challenge. Moreover, the quality of the proposed method is thoroughly assessed using various measures for data from the OAI, i.e. 507 manual segmentations of bone and cartilage, and 88 additional manual segmentations of cartilage. Our method yields sub-voxel accuracy for both OAI datasets. We make the 507 manual segmentations as well as our experimental setup publicly available to further aid research in the field of medical image segmentation. In conclusion, combining localized classification via CNNs with statistical anatomical knowledge via SSMs results in a state-of-the-art segmentation method for knee bones and cartilage from MRI data.

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.

New Approaches to Treat Osteoarthritis with Mesenchymal Stem Cells

Osteoarthritis is one of the most common chronic health problems in the world that causes disability and chronic pain with reduced mobility and is a progressive degenerative disease in weight-bearing joints such as the knee. The pathology of the joint resulting from OA includes loss of cartilage volume and cartilage lesions leading to inflammation of the articular joint structures; its incidence and progression are associated with a variety of risk factors. Most of the current treatments focus on symptom management such as physical and occupational therapies, pharmacological intervention for pain management, and surgical intervention with limited success and do not address nor halt the progression of the disease. In this review, we will describe the current treatment options for OA and the exciting new translational medical research currently underway utilising mesenchymal stem cells for OA therapy.

Imaging of nuclear magnetic resonance spin-lattice relaxation activation energy in cartilage

Samples of human and bovine cartilage have been examined using magnetic resonance imaging to determine the proton nuclear magnetic resonance spin-lattice relaxation time, T₁, as a function of depth within through the cartilage tissue. T₁ was measured at five to seven temperatures between 8 and 38°C. From this, it is shown that the T₁ relaxation time is well described by Arrhenius-type behaviour and the activation energy of the relaxation process is quantified. The activation energy within the cartilage is approximately 11 ± 2 kJ mol^-1 with this notably being less than that for both pure water (16.6 ± 0.4 kJ mol^-1) and the phosphate-buffered solution in which the cartilage was immersed (14.7 ± 1.0 kJ mol^-1). It is shown that this activation energy increases as a function of depth in the cartilage. It is known that cartilage composition varies with depth, and hence, these results have been interpreted in terms of the structure within the cartilage tissue and the association of the water with the macromolecular constituents of the cartilage.

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging

PURPOSE

To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint.

METHODS

A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts.

RESULTS

The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions.

CONCLUSION

The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine.