Faculty Bibliography

PURPOSE/OBJECTIVE:To implement a novel technique for simultaneous, quantitative multiparametric mapping of the knee articular cartilage. METHODS:relaxation time (P = .02) in medial femoral cartilage. CONCLUSION/CONCLUSIONS:

Purpose: Osteoporosis (OP) is a disease of weak bone associated with increased fracture risk (Fx). An important component of bone tissue is bone marrow adipose tissue (BAT), which has been previously associated with Fx and OP. Recent studies have shown an association between BMD and fat quantity in the spine and femur using Chemical Shift Encoded MRI (CSE-MRI). The aim of our study was to apply CSE-MRI in thigh muscle (MUS), BAT, and subcutaneous fat (SAT) of the pelvic region in osteoporosis patients with varying degrees of Fx.
Material(s) and Method(s): This study had institutional review board approval and written informed consent was obtained from all n=128 recruited female subjects with OP. Patients were divided into three groups for analysis based upon overall FRAX score: low (LOW, FRAX < 10, n=42, 57+/-6.9y, BMI 23+/-4.1 kg/m2), moderate (MOD, 10>FRAX>20, n=52, 62+/-6.9y, BMI 22+/-3.4 kg/m2) and high (HIGH, FRAX>20, n=34, 64+/-5.8y, BMI 22+/-3.1 kg/m2). 3T MRI acquisition were performed a 3T using a 3D spoiled gradient-echo sequence. An automatic reconstruction pipeline allowed computation of proton density fat fraction (PDFF), susceptibility mapping (QSM) and R2*. BAT, MUS and SAT were segmented by thresholding the PDFF map. An unpaired one-way ANOVA test was used to assess significant differences.
Result(s): Overall, in BAT, we found a higher amount of PDFF in HIGH subjects compared to LOW subjects (+5%, p= 0.032). In muscle, we found a higher amount of PDFF in HIGH compared to both LOW (+8.87%, p =0.008) and MOD subjects (+9.25%, p= 0.006). There were no differences between groups with regards to R2*measured. We found diamagnetic BAT and MUS and paramagnetic SAT. Susceptibility of SAT was higher in LOW compared to both HIGH (-31%, p= 0.008) and MOD (-23%, p= 0.04) subjects. Volume of MUS was lower in MOD compared to LOW (-8%, p=0.009) and HIGH (-9%, p=0.045).
Conclusion(s): Our result suggests that fracture risk is related to an increased amount of adipose tissue. 3T CSE-MRI could be used in the future to study the relationship between adipose tissue and bone health and possibly even provide an additional surrogate marker of Fx beyond BMD

OBJECTIVE:Predictive biomarkers of progression in knee osteoarthritis are sought to enable clinical trials of structure-modifying drugs. A peripheral blood leukocyte (PBL) inflammatory gene signature, MRI-based bone marrow lesions (BML) and meniscus extrusion scores, meniscal lesions, and osteophytes on X-ray each have been shown separately to predict radiographic joint space narrowing (JSN) in subjects with symptomatic knee osteoarthritis (SKOA). In these studies, we determined whether the combination of the PBL inflammatory gene expression and these imaging findings at baseline enhanced the prognostic value of either alone. METHODS:PBL inflammatory gene expression (increased mRNA for IL-1β, TNFα, and COX-2), routine radiographs, and 3T knee MRI were assessed in two independent populations with SKOA: an NYU cohort and the Osteoarthritis Initiative (OAI). At baseline and 24 months, subjects underwent standardized fixed-flexion knee radiographs and knee MRI. Medial JSN (mJSN) was determined as the change in medial JSW. Progressors were defined by an mJSN cut-point (≥ 0.5 mm/24 months). Models were evaluated by odds ratios (OR) and area under the receiver operating characteristic curve (AUC). RESULTS:We validated our prior finding in these two independent (NYU and OAI) cohorts, individually and combined, that an inflammatory PBL inflammatory gene expression predicted radiographic progression of SKOA after adjustment for age, sex, and BMI. Similarly, the presence of baseline BML and meniscal lesions by MRI or semiquantitative osteophyte score on X-ray each predicted radiographic medial JSN at 24 months. The combination of the PBL inflammatory gene expression and medial BML increased the AUC from 0.66 (p = 0.004) to 0.75 (p < 0.0001) and the odds ratio from 6.31 to 19.10 (p < 0.0001) in the combined cohort of 473 subjects. The addition of osteophyte score to BML and PBL inflammatory gene expression further increased the predictive value of any single biomarker. A causal analysis demonstrated that the PBL inflammatory gene expression and BML independently influenced mJSN. CONCLUSION/CONCLUSIONS:The use of the PBL inflammatory gene expression together with imaging biomarkers as combinatorial predictive biomarkers, markedly enhances the identification of radiographic progressors. The identification of the SKOA population at risk for progression will help in the future design of disease-modifying OA drug trials and personalized medicine strategies.

Background The methods for assessing knee osteoarthritis (OA) do not provide enough comprehensive information to make robust and accurate outcome predictions. Purpose To develop a deep learning (DL) prediction model for risk of OA progression by using knee radiographs in patients who underwent total knee replacement (TKR) and matched control patients who did not undergo TKR. Materials and Methods In this retrospective analysis that used data from the OA Initiative, a DL model on knee radiographs was developed to predict both the likelihood of a patient undergoing TKR within 9 years and Kellgren-Lawrence (KL) grade. Study participants included a case-control matched subcohort between 45 and 79 years. Patients were matched to control patients according to age, sex, ethnicity, and body mass index. The proposed model used a transfer learning approach based on the ResNet34 architecture with sevenfold nested cross-validation. Receiver operating characteristic curve analysis and conditional logistic regression assessed model performance for predicting probability and risk of TKR compared with clinical observations and two binary outcome prediction models on the basis of radiographic readings: KL grade and OA Research Society International (OARSI) grade. Results Evaluated were 728 participants including 324 patients (mean age, 64 years ± 8 [standard deviation]; 222 women) and 324 control patients (mean age, 64 years ± 8; 222 women). The prediction model based on DL achieved an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI]: 0.85, 0.90), outperforming a baseline prediction model by using KL grade with an AUC of 0.74 (95% CI: 0.71, 0.77; P < .001). The risk for TKR increased with probability that a person will undergo TKR from the DL model (odds ratio [OR], 7.7; 95% CI: 2.3, 25; P < .001), KL grade (OR, 1.92; 95% CI: 1.17, 3.13; P = .009), and OARSI grade (OR, 1.20; 95% CI: 0.41, 3.50; P = .73). Conclusion The proposed deep learning model better predicted risk of total knee replacement in osteoarthritis than did binary outcome models by using standard grading systems. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Richardson in this issue.

Osteoporosis (OP) is a major disease that affects 200 million people worldwide. Fatty acid metabolism plays an important role in bone health and plays an important role in bone quality and remodeling. Increased bone marrow fat quantity has been shown to be associated with a decrease in bone mineral density (BMD), which is used to predict fracture risk. Chemical-Shift Encoded magnetic resonance imaging (CSE-MRI) allows noninvasive and quantitative assessment of adipose tissues (AT). The aim of our study was to assess hip or proximal femoral bone marrow adipose tissue (BMAT), thigh muscle (MUS), and subcutaneous adipose tissue (SAT) in 128 OP subjects matched for age, BMD, weight and height with different degrees of fracture risk assessed through the FRAX score (low, moderate and high). Our results showed an increase in BMAT and in MUS in high compared to low fracture risk patients. We also assessed the relationship between fracture risk as assessed by FRAX and AT quantities. Overall, the results of this study suggest that assessment of adipose tissue via 3T CSE-MRI provides insight into the pathophysiology fracture risk by showing differences in the bone marrow and muscle fat content in subjects with similarly osteoporotic BMD as assessed by DXA, but with varying degrees of fracture risk as assessed by FRAX.

PURPOSE OF REVIEW/OBJECTIVE:Osteoarthritis is a major source of disability, pain and socioeconomic cost worldwide. The epidemiology of the disorder is multifactorial including genetic, biological and biomechanical components, some of them detectable by MRI. This review provides the most recent update on MRI biomarkers which can provide functional information of the joint structures for diagnosis, prognosis and treatment response monitoring in osteoarthritis trials. RECENT FINDINGS/RESULTS:Compositional or functional MRI can provide clinicians with valuable information on glycosaminoglycan content (chemical exchange saturation transfer, sodium MRI, T1ρ) and collagen organization (T2, T2, apparent diffusion coefficient, magnetization transfer) in joint structures. Other parameters may also provide useful information, such as volumetric measurements of joint structures or advanced image data postprocessing and analysis. Automated tools seem to have a great potential to be included in these efforts providing standardization and acceleration of the image data analysis process. SUMMARY/CONCLUSIONS:Functional or compositional MRI has great potential to provide noninvasive imaging biomarkers for osteoarthritis. Osteoarthritis as a whole joint condition needs to be diagnosed in early stages to facilitate selection of patients into clinical trials and/or to measure treatment effectiveness. Advanced evaluation including machine learning, neural networks and multidimensional data analysis allow for wall-to-wall understanding of parameter interactions and their role in clinical evaluation of osteoarthritis.

BACKGROUND:tissues may provide a more comprehensive evaluation of OA. PURPOSE/OBJECTIVE:tissues on a clinical 3 T scanner. STUDY TYPE/METHODS:Prospective. POPULATION/METHODS:Phantom, two bovine whole knee joint and Achilles tendon specimens, 10 healthy volunteers with no known inflammation, trauma or pain in the knee or ankle. FIELD STRENGTH/SEQUENCE/UNASSIGNED: ASSESSMENT/RESULTS:relaxation components were assessed in the patellar tendon (PT), anterior cruciate ligament (ACL), posterior cruciate ligament (PCL), and Achilles tendon (AT). STATISTICAL TESTS/UNASSIGNED:Kruskal-Wallis with post-hoc Dunn's test for multiple pairwise comparisons. RESULTS:relaxation of (median [IQR]) 15.9 [14.5] msec, 23.6 [9.4] msec, 17.4 [7.4] msec, and 5.8 [10.2] msec in the PT, ACL, PCL, and AT, respectively. The bicomponent analysis showed the short and long components (with their relative fractions) of 0.65 [1.0] msec (46.9 [15.3]%) and 37.3 [18.4] msec (53.1 [15.3]%) for PT, 1.7 [2.1] msec (42.5 [12.5]%) and 43.7 [17.8] msec (57.5 [12.5]%) for ACL, and 1.2 [1.9] msec (42.6 [14.0]%) and 27.7 [14.7] msec (57.3 [14.0]%) for PCL and 0.4 [0.02] msec (58.8 [13.3]%/) and 31.3 [10.8] msec (41.2 [13.3]%) for AT. Statistically significant (P ≤ 0.05) differences were observed in the mono- and biexponential relaxation between several regions. DATA CONCLUSION/UNASSIGNED: LEVEL OF EVIDENCE/METHODS:2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019.

Background/Purpose : Osteoporosis and bone fractures are a frequent cause of morbidity in systemic lupus erythematosus (SLE), and are felt to be related both to disease activity and glucocorticoid (GC) exposure. Dual energy X-ray absorptiometry (DEXA) is the standard tool to assess bone density, but it does not measure bone quality or strength and is not a robust predictor of fractures in SLE. Clinical 3T MRI scans have been shown to assess information about bone not captured by DEXA. This study aims to evaluate factors associated with bone structure measured by DEXA and MRI in an SLE cohort. Methods : DEXAs were performed on 31 women with SLE and 3T MRI of the non-dominant hip were performed on 29 of these cases. Results were associated with multiple demographic, clinical and laboratory measures. MRI parameters measured included trabecular plate width (PW), trabecular plate to rod ratio (PRR), plate volume fraction (PVF), rod volume fraction (RVF), trabecular bone thickness (Tb.Th), trabecular spacing (Tb.Sp) and trabecular network area (TNA). DEXA BMD was measured, and osteoporosis (OP) was defined as hip, spine or femoral neck Z score < -2.0 in premenopausal women, and T score < -2.5 in others, and low bone density (LBD) as Z score < -2.0 in premenopausal women and T score < -1.0 in others. Results : By DEXA, 8/31 (25.8%) had OP and 12 (38.7%) had LBD. History of lymphopenia (75.0% vs. 31.8%, p=0.049) and lower concurrent HCQ dose (340 vs. 400 mg, p=0.006) associated with DEXA OP, while older age (48.3 vs. 36.3 y, p=0.024) associated with LBD. Higher ESR was inversely correlated with favorable bone structure (PW r(22) = -.49, p=0.025, PRR rs = -.51, p=0.018, PVF rs = -.51, p=0.018, RVF rs = .51, p=0.018, Tb.Th rs = -.58, p=0.005, Tb.Sp rs = .44, p=0.046, TNA rs = -.50, p=0.022). Higher CRP was likewise inversely correlated with favorable bone structure (PW r(20) = -.61, p=0.004, PRR rs = -.57, p=0.009, PVF rs = -.57, p=0.009, RVF rs =.57, p=0.009, Tb.Th rs = -.56, p=.011, Tb.Sp rs =.67, p=0.001, TNA rs = -.64, p=0.002). A history of lupus nephritis was associated with unfavorable bone structure (PW 705.3 vs. 833.3 mum, p=0.048, PRR 6.6 vs. 8.1, p=0.024, PVF 0.83 vs. 0.89, p=0.024, RVF 0.17 vs. 0.11, p=0.024, Tb.Th 178.1 vs. 193.4 mm, p=0.012, Tb.Sp 358.6 vs. 296.5 mm, p=0.056, TNA 0.41 vs. 0.54 (1/mm), p=0.009). ESR, CRP and history of lupus nephritis were not significantly associated with DEXA hip BMD, OP or LBD. MRI parameters for favorable bone structure were inversely correlated with DEXA hip BMD (PW r(28) = -.47, p=0.011, Tb.Th rs = -.53, p=0.003) and BMI (PW r(28) = -.54, p=0.003, TbTh rs = -.72, p< 0.001, TNA rs = -.44, p=0.017). Conclusion : Higher ESR and CRP and a history of lupus nephritis associated with MRI parameters of unfavorable bone structure, but did not associate with DEXA abnormalities in SLE patients. MRI may be a more sensitive tool than DEXA to measure inflammatory effects on bone and potentially cumulative dose of steroid exposure. There were inverse correlations of MRI parameters with traditional osteoporosis risk factors and BMD measures on DEXA, and it is possible that each tool evaluates different aspects of bone health. Further evaluation of MRI screening for fracture risk in SLE and GC exposed individuals is warranted to better quantify risk and guide treatment