Faculty Bibliography

STUDY DESIGN/METHODS:Retrospective single-center cohort study. OBJECTIVE:To evaluate whether preoperative CT-based finite element analysis (FEA) of vertebral bone modulus predicts bone quality-related complications after lumbar spine fusion. SUMMARY OF BACKGROUND DATA/BACKGROUND:In spine surgery patients, poor bone quality increases the risk of proximal junctional kyphosis/failure, pedicle screw loosening, adjacent segment disease, and pseudoarthrosis, leading to higher revision rates. DXA-based areal bone mineral density (BMD) often fails to identify high-risk patients, particularly in degenerative spines. Three-dimensional CT-based methods, such as Hounsfield units (HU), volumetric BMD, and CT-based FEA, may better capture vertebral mechanical competence by integrating density and microarchitecture. METHODS:Patients undergoing lumbar fusion at a single academic center in 2017 with ≥2-year follow-up were included (n=85) and classified by the presence of bone quality-related complications. For L1-L5 on preoperative CT, trabecular VOIs were analyzed to obtain mean HU, phantomless-calibrated BMD, and FEA-derived bone modulus. Group differences were assessed with independent-samples t tests, and ROC analysis and multivariable logistic regression examined associations with complication status. RESULTS:Thirty-one patients (36.5%) experienced ≥1 bone quality-related complication; 18 had ≥2 events. Bone modulus was significantly lower in the complication cohort (-15.7% to -23.2%; all p≤0.02), whereas HU and BMD differences were nonsignificant. Bone modulus showed greater ability to distinguish patients with and without complications (AUC 0.65-0.70; all P<0.03), while HU and BMD did not (AUC ~0.57-0.60; all P>0.10). Multivariable models including modulus, BMD, and demographics achieved AUC up to 0.81 at L5 (P<0.001). CONCLUSION/CONCLUSIONS:Preoperative CT-based FEA of vertebral bone modulus outperforms HU and BMD in identifying lumbar fusion patients at risk for bone quality-related complications and may provide a useful adjunct for preoperative risk stratification and surgical planning.

OBJECTIVES/OBJECTIVE:Early screening is necessary to prevent increasing osteoporosis and fragility fractures. Though Dual-energy X-ray absorptiometry (DEXA) defines osteoporosis, it does not predict fragility-fractures well. Trabecular structure as seen on MRI may be more sensitive and specific for osteoporosis and distal radius trabecular structure may identify changes earlier. We aimed to compare distal-radius trabecular structure as seen on MRI in patients with normal risk for fragility-fracture to those with increased risk of fragility-fracture. METHODS:Ten low-risk and 9 high-risk subjects underwent ultra- short-echo-time (UTE) MRI sequence scanning of an uninjured distal radius. Structural components included: trabecular plate-width, plate-rod ratio, plate volume fraction, rod volume fraction, trabecular thickness, pore size, pore size variation and trabecular density. A T-test or Mann-Whitney U test was conducted to determine differences in trabecular structure between low- and high-risk groups. Specificity and sensitivity were calculated to assess wrist MRI as a screening tool. RESULTS:There were statistically significant differences between low- and risk-risk groups for all parameters except trabecular thickness (p < 0.05). CONCLUSION/CONCLUSIONS:This study supports the feasibility of wrist MRI as a screening tool for early osteoporosis. This could potentially enable early prevention. Further study including longitudinal follow-up to determine the ability of this tool to predict fragility fractures is needed. ADVANCES IN KNOWLEDGE/CONCLUSIONS:We compared trabecular structure in wrist-MRI of high-risk and low-risk for fragility fracture, finding significant differences with optimal sensitivity/specificity to predict osteoporosis. Wrist MRI may offer early and effective screening for osteoporosis.

BACKGROUND:The methods for predicting time-to-total knee replacement (TKR) do not provide enough information to make robust and accurate predictions. PURPOSE/OBJECTIVE:Develop and evaluate an artificial intelligence-based model for predicting time-to-TKR by analyzing longitudinal knee data and identifying key features associated with accelerated knee osteoarthritis progression. METHODS:A total of 547 subjects underwent TKR in the Osteoarthritis Initiative over nine years, and their longitudinal data was used for model training and testing. 518 and 164 subjects from Multi-Center Osteoarthritis Study and internal hospital data were used for external testing, respectively. The clinical variables, magnetic resonance (MR) images, radiographs, and quantitative and semi-quantitative assessments from images were analyzed. Deep learning (DL) models were used to extract features from radiographs and MR images. DL features were combined with clinical and image assessment features for survival analysis. A Lasso Cox feature selection method combined with a random survival forest model was used to estimate time-to-TKR. RESULTS:Utilizing only clinical variables for time-to-TKR predictions provided the estimation accuracy of 60.4% and C-index of 62.9%. Combining DL features extracted from radiographs, MR images with clinical, quantitative, and semi-quantitative image assessment features achieved the highest accuracy of 73.2%, (p=.001) and C-index of 77.3% for predicting time-to-TKR. CONCLUSIONS:The proposed predictive model demonstrated the potential of DL models and multimodal data fusion in accurately predicting time-to-TKR surgery that may help assist physicians to personalize treatment strategies and improve patient outcomes.

BACKGROUND/UNASSIGNED:Neurogenic osteoporosis as a result of bone demineralization is a well-known complication after spinal cord injury (SCI). Bone demineralization is a result of the inevitable mechanical unloading of paralyzed limbs and decreased skeletal muscle activity. OBJECTIVES/UNASSIGNED:To determine the impact of a home-based electrical stimulation (ES)-induced exercise (Excs) protocol plus 2000 IU oral daily vitamin D (vit D) supplementation compared to passive movement training (PMT) plus 2000 IU oral daily vit D supplementation on bone microarchitectural properties as measured by magnetic resonance imaging (MRI), bone mineral density (BMD) as measured by dual-energy x-ray absorptiometry (DXA), and biomarkers of bone formation and bone resorption in persons with chronic SCI. METHODS/UNASSIGNED:Six men with motor complete SCI ranging from C8 to T10 were randomized into either 9 months of vit D+ES-Excs or vit D+PMT groups. The vit D+ES-Excs group underwent daily supplementation of vit D with 4.5 months of neuromuscular electrical stimulation-resistance training (NMES-RT) followed by 4.5 months of functional electrical stimulation (FES) rowing, twice weekly, using a home-based training approach. MRI, DXA, and blood biomarkers were captured at the beginning of the study (baseline), 4.5 months (post-intervention 1), and 9 months after training (post-intervention 2). RESULTS/UNASSIGNED:The percentage changes indicated that 2 persons in the vit D+ES-Excs group showed decreases in trabecular spacing (28%) and increases in trabecular network (33%-49% at post-intervention 2). This was accompanied by attenuation of BMD loss at the pelvis (3.6%-7.7%), femoral necks (4.5%-8.4%), and knees (10.5%-18.7%). The vit D+ES-Excs group showed increases in leg (5.3%) to total body lean mass and decreases in biomarkers of bone resorption (7.0%-23.5%). Similar changes were not demonstrated following 9 months of vit D+PMT. CONCLUSION/UNASSIGNED:Home-based training with 9 months of vit D+ES exercise demonstrated the safety and practicability in mitigating deleterious changes in bone health in persons with chronic SCI. This is concomitant with increased leg lean mass and decreased circulating biomarkers of bone resorption in persons with SCI.

PURPOSE/OBJECTIVE:To investigate the qualitative and quantitative changes seen in quadriceps muscles [QM] following tibial plateau fracture and surgery. METHODS:A consecutive series of patients with an isolated tibial plateau fracture presenting to a single academic center were enrolled and prospectively followed. Bilateral knee MRIs were performed preoperatively and 3 and 12 months postoperatively to assess quantity and quality of the quadriceps muscles. All patients underwent tibial plateau operative repair and were made non-weight-bearing for 10 weeks postoperatively then advanced to weight-bearing as tolerated. Functional status assessed via the short musculoskeletal functional assessment (SMFA); knee range of motion [ROM]; vastus medialis oblique [VMO] and vastus lateralis [VL] muscle quantity (axial width, cross sectional area [CSA] and volume) on injured and contralateral limb; VMO, sartorius, semi-membranous and biceps femoris [BF] muscle quality (fat and water content, and proton density fat fraction). All muscle quantitative and qualitative measurements were compared across all time points. RESULTS:Ten patients were included in the final analysis, 6 males and 4 females, with average age of 43.62 ± 16.3 years. While the VMO and VL axial width and CSA were significantly decreased at 3 months preoperatively, this was not statistically significant. There was no significant difference between any QM quantitative measurements at any time points. There was no difference in fat content, water content or PDFF at any time point for the VMO, sartorius, semi-membranous and BF muscles. Regression analysis also showed no association between 12-month SMFA scores and knee ROM with VMO/VL CSA at 1 year. CONCLUSIONS:QM quantity and quality do not significantly change at 3 months and 1 year postoperatively following tibial plateau fracture surgery. LEVEL OF EVIDENCE/METHODS:Prognostic Level II.

BACKGROUND:Magnetic resonance fingerprinting (MRF) techniques have been recently described for simultaneous multiparameter cartilage mapping of the knee although investigation of their ability to detect early cartilage degeneration remains limited. PURPOSE/OBJECTIVE:relaxation times measured using a three-dimensional (3D) MRF sequence in healthy volunteers. STUDY TYPE/METHODS:Prospective. SUBJECTS/METHODS:The study group consisted of 24 healthy asymptomatic human volunteers (15 males with mean age 34.9 ± 14.4 years and 9 females with mean age 44.5 ± 13.1 years). FIELD STRENGTH/SEQUENCE/UNASSIGNED:maps of knee cartilage. ASSESSMENT/RESULTS:relaxation times of the knee were measured. STATISTICAL TESTS/METHODS:relaxation times. The value of P < 0.05 was considered statistically significant. RESULTS: = 0.54-0.66). CONCLUSION/CONCLUSIONS:relaxation times simultaneously measured using a 3D-MRF sequence in healthy volunteers showed age-dependent changes in knee cartilage, primarily within the medial compartment.

Current methods for assessing knee osteoarthritis (OA) do not provide comprehensive information to make robust and accurate outcome predictions. Deep learning (DL) risk assessment models were developed to predict the progression of knee OA to total knee replacement (TKR) over a 108-month follow-up period using baseline knee MRI. Participants of our retrospective study consisted of 353 case-control pairs of subjects from the Osteoarthritis Initiative with and without TKR over a 108-month follow-up period matched according to age, sex, ethnicity, and body mass index. A traditional risk assessment model was created to predict TKR using baseline clinical risk factors. DL models were created to predict TKR using baseline knee radiographs and MRI. All DL models had significantly higher (p < 0.001) AUCs than the traditional model. The MRI and radiograph ensemble model and MRI ensemble model (where TKR risk predicted by several contrast-specific DL models were averaged to get the ensemble TKR risk prediction) had the highest AUCs of 0.90 (80% sensitivity and 85% specificity) and 0.89 (79% sensitivity and 86% specificity), respectively, which were significantly higher (p < 0.05) than the AUCs of the radiograph and multiple MRI models (where the DL models were trained to predict TKR risk using single contrast or 2 contrasts together as input). DL models using baseline MRI had a higher diagnostic performance for predicting TKR than a traditional model using baseline clinical risk factors and a DL model using baseline knee radiographs.

INTRODUCTION/UNASSIGNED:. Radiomics provides a framework to analyze the textural information of MR images. The purpose of this study was to analyze the radiomic features and its abilityto differentiate between subjects with and without prior fragility fracture. METHODS/UNASSIGNED:= 45 female OP subjects: 15 with fracture history (Fx) and 30 without fracture history (nFx) using a high-resolution 3D Fast Low Angle Shot (FLASH) sequence at 3T. Second and first order radiomic features were calculated in the trabecular region of the proximal femur on T1-weighted MRI signal of a matched dataset. Significance of the feature's predictive ability was measured using Wilcoxon test and Area Under the ROC (AUROC) curve analysis. The features were correlated DXA and FRAX score. RESULT/UNASSIGNED: < 0.05) with low to moderate correlation with FRAX and DXA. CONCLUSION/UNASSIGNED:Radiomic features can measure bone health in MRI of proximal femur and has the potential to predict fracture.

Background/Purpose: Fractures in patients with systemic lupus erythematosus (SLE) are more common than age and sex matched controls. Fracture risk is traditionally assessed by dual-energy X-ray absorptiometry (DEXA) measured BMD and refined using the Fracture Risk Assessment Tool (FRAX). Several studies have demonstrated fractures in SLE patients despite normal DEXA BMD. We hypothesize that changes in bone microarchitecture may explain fracture vulnerability in SLE. This study was initiated to characterize bone quality by evaluating measures of microarchitecture at the proximal femur via 3T MRI in patients with SLE and compare these measurements with a control group of patients with known low bone density (LBD) and osteoporosis (OP).
Method(s): 50 SLE patients and 177 controls with known LBD or OP underwent DEXA and 3T MRI of the non-dominant hip. DEXA measured BMD of the total hip, femoral neck, and spine. LBD was defined as Z score <=-2.0 in premenopausal women and men younger than fifty, and T score <=-1.0 in others. OP was defined as the presence of LBD and history of fragility fracture in premenopausal women and men younger than fifty, and T score <=-2.5 in others. MRI measured favorable microarchitectural characteristics trabecular plate width (PW), trabecular plate-to-rod ratio (PRR), plate volume fraction (PVF), trabecular bone thickness (Tb.Th), and trabecular network area (NA), as well as unfavorable characteristics rod volume fraction (RVF) and trabecular spacing (Tb.Sp). Demographics, medication use and inflammatory markers at the time of the study visit were recorded. Statistical analysis was performed using Pearson correlations, t-scores, and multivariable linear regressions as appropriate.
Result(s): 50 SLE patients and 177 patients with LBD or OP completed all imaging studies. The SLE cohort was younger, and a higher percent of black patients compared to controls (Table 1). SLE patients had lower MRI PW and PRR and higher Tb. Sp as compared to controls, while having higher DEXA BMDs at all sites after adjustment for confounders (Figure 1). SLE patients had an inverse relationship between ESR and PW, PRR, Tb.Th, and NA (Figure 2, A-D). Similar results were found with CRP, which had an inverse relationship with PW, PRR, and NA. Body mass index (BMI) in SLE patients had an inverse relationship between PW, PVF, Tb.Th, and NA (Figure 2, E-H), and a positive relationship between all measured BMDs. In the control group, similar relationships were found between BMI and BMD, but only Tb.Th was inversely associated with BMI. Age, current steroid use, and history of lupus nephritis were not associated with MRI measures of bone microarchitecture.
Conclusion(s): Compared to controls, SLE patients had decreased bone quality as measured by MRI bone microarchitecture, despite having higher DEXA BMD. Elevated inflammatory markers inversely associated with bone quality. Elevated BMI, despite its association with higher BMD, was also associated with lower measures of bone microarchitectural strength, unlike controls. Further connection of bone microarchitecture to fracture risk and change over time in patients with SLE are needed to determine clinical significance of these findings and to guide additional monitoring and potential treatments. A-C: multivariate linear regression adjusting for significant microarchitectural confounders of BMI and gender. D-F: multivariate linear regression adjusting for significant BMD confounders of age, BMI, race, and gender