Benjamin Ma
University of California, San Francisco
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Magnetic Resonance in Medicine | 2009
Xiaojuan Li; Alex Pai; Gabrielle Blumenkrantz; Julio Carballido-Gamio; Thomas M. Link; Benjamin Ma; Michael D. Ries; Sharmila Majumdar
T1ρ and T2 relaxation time constants have been proposed to probe biochemical changes in osteoarthritic cartilage. This study aimed to evaluate the spatial correlation and distribution of T1ρ and T2 values in osteoarthritic cartilage. Ten patients with osteoarthritis (OA) and 10 controls were studied at 3T. The spatial correlation of T1ρ and T2 values was investigated using Z‐scores. The spatial variation of T1ρ and T2 values in patellar cartilage was studied in different cartilage layers. The distribution of these relaxation time constants was measured using texture analysis parameters based on gray‐level co‐occurrence matrices (GLCM). The mean Z‐scores for T1ρ and T2 values were significantly higher in OA patients vs. controls (P < 0.05). Regional correlation coefficients of T1ρ and T2 Z‐scores showed a large range in both controls and OA patients (0.2–0.7). OA patients had significantly greater GLCM contrast and entropy of T1ρ values than controls (P < 0.05). In summary, T1ρ and T2 values are not only increased but are also more heterogeneous in osteoarthritic cartilage. T1ρ and T2 values show different spatial distributions and may provide complementary information regarding cartilage degeneration in OA. Magn Reson Med, 2009.
American Journal of Sports Medicine | 2007
John E. Kuhn; Warren R. Dunn; Benjamin Ma; Rick W. Wright; Grant L. Jones; Edwin E. Spencer; Brian R. Wolf; Marc R. Safran; Kurt P. Spindler; Eric C. McCarty; Brian T. Kelly; Brian G. Holloway
Background Six classification systems have been proposed for describing rotator cuff tears designed to help understand their natural history and make treatment decisions. Purpose To assess the interobserver variation for these classification systems and identify the method with the best interob-server agreement. Study Design Cohort study (diagnosis); Level of evidence, 2. Methods Six rotator cuff tear classification systems were identified in a literature search. The components of these systems included partial-thickness rotator cuff tears and classification by size, shape, configuration, number of tendons involved, and by extent, topography, and nature of the biceps. Twelve fellowship-trained orthopaedic surgeons who each perform at least 30 rotator cuff repairs per year reviewed arthroscopy videos from 30 patients with a random assortment of rotator cuff tears and classified them by the 6 classification systems. Interobserver variation was determined by a kappa analysis. Results Interobserver agreement was high when distinguishing between full-thickness and partial-thickness tears (0.95, [UNKNOWN]=0.85). The investigators agreed on the side (articular vs bursal) of involvement for partial-thickness tears (observed agreement 0.92, [UNKNOWN]= 0.85) but could not agree when classifying the depth of the partial-thickness tear (observed agreement 0.49, [UNKNOWN]= 0.19). The best agreement for full-thickness tears was seen when the tear was classified by topography (degree of retraction) in the frontal plane (observed agreement 0.70, [UNKNOWN]= 0.54). Conclusion With the exception of distinguishing partial-thickness from full-thickness rotator cuff tears and identifying the side (articular vs bursal) of involvement with partial-thickness tears, currently described rotator cuff classification systems have little interobserver agreement among experienced shoulder surgeons. Researchers should consider describing full-thickness rotator cuff tears by topography (degree of retraction) in the frontal plane.
American Journal of Sports Medicine | 2010
Anthony Luke; Christoph Stehling; Robert Stahl; Xiaojuan Li; Terry Kay; Stephen Takamoto; Benjamin Ma; S. Majumdar; Thomas M. Link
Background There is continuing controversy whether long-distance running results in irreversible articular cartilage damage. New quantitative magnetic resonance imaging (MRI) techniques used at 3.0 T have been developed including T1rho (T1ρ) and T2 relaxation time measurements that detect early cartilage proteoglycan and collagen breakdown. Hypothesis Marathon runners will demonstrate T1ρ and T2 changes in articular cartilage on MRI after a marathon, which are not seen in nonrunners. These changes are reversible. Study Design Cohort study; Level of evidence, 2. Methods Ten asymptomatic marathon runners had 3-T knee MRI scans 2 weeks before, within 48 hours after, and 10 to 12 weeks after running a marathon. The T1ρ and T2 MRI sequences in runners were compared with those of 10 age- and gender-matched controls who had MRI performed at baseline and 10 to 12 weeks. Results Runners did not demonstrate any gross morphologic MRI changes after running a marathon. Postmarathon studies, however, revealed significantly higher T2 and T1ρ values in all articular cartilage areas of the knee (P < .01) except the lateral compartment. The T2 values recovered to baseline except in the medial femoral condyle after 3 months. Average T1ρ values increased after the marathon from 37.0 to 38.9 (P < .001) and remained increased at 3 months. Conclusion Runners showed elevated T1ρ and T2 values after a marathon, suggesting biochemical changes in articular cartilage, T1ρ values remain elevated after 3 months of reduced activity. The patellofemoral joint and medial compartment of the knee show the highest signal changes, suggesting they are at higher risk for degeneration.
Magnetic Resonance Imaging | 2014
Riti Gupta; Warapat Virayavanich; Daniel Kuo; Favian Su; Thomas M. Link; Benjamin Ma; Xiaojuan Li
OBJECTIVE Quantitative T1ρ MRI has been suggested as a promising tool to detect changes in cartilage composition that are characteristic of cartilage damage and degeneration. The objective of this study was to evaluate the capability of MR T1ρ to detect cartilage lesions as evaluated by arthroscopy in acutely ACL-injured knees and to compare with the Whole-Organ Magnetic Resonance Imaging Score (WORMS) using clinical standard MRI. METHOD Ten healthy controls (mean age 35) with no ACL injury or history of osteoarthritis (OA) and 10 patients with acute ACL injuries (mean age 39) were scanned at 3 Tesla (3T). ACL patients underwent ACL reconstruction, where focal lesions were graded according to an Outerbridge grading system during arthroscopic evaluation. Normalized MR T1ρ values (T1ρ z-scores normalized to control values in matched regions) in full thickness, and superficial and deep layers of cartilage were compared between defined sub-compartments with and without focal lesions. Intraclass (ICC) correlation and the root mean square coefficient of variation (RMS-CV) were performed to evaluate the inter-observer reproducibility of T1ρ quantification. Sub-compartments of cartilage were also evaluated using WORMS scoring and compared to their Outerbridge score respectively. RESULTS The inter-observer ICC and the RMS-CV of the sub-compartment T1ρ quantification were 0.961 and 3.9%, respectively. The average T1ρ z-scores were significantly increased in sub-compartments with focal lesions compared to those without focal lesions and to the control cohort (p<0.05). CONCLUSION Our results indicate that T1ρ provided a better diagnostic capability than clinical standard MRI grading in detecting focal cartilage abnormalities after acute injuries. Quantitative MRI may have great potential in detecting cartilage abnormalities and degeneration non-invasively, which are occult with standard morphological MRI.
European Radiology | 2007
Cameron Barr; Jan S. Bauer; David Malfair; Benjamin Ma; Tobias D. Henning; Lynne S. Steinbach; Thomas M. Link
Osteoarthritis and Cartilage | 2005
Keh-Yang Lee; Jeffrey N. Masi; Christian A. Sell; Robert Schier; Thomas M. Link; Lynne S. Steinbach; Marc R. Safran; Benjamin Ma; Sharmila Majumdar
Skeletal Radiology | 2015
Valentin Lance; Ursula Heilmeier; G. B. Joseph; Lynne S. Steinbach; Benjamin Ma; Thomas M. Link
Osteoarthritis and Cartilage | 2017
Z. Xiao; A.K. Li; Thomas M. Link; M. Sharmila; Benjamin Ma; Xiaojuan Li
Osteoarthritis and Cartilage | 2017
Ursula Heilmeier; K. Amano; M. Tanaka; Benedikt J. Schwaiger; Janet L. Huebner; Thomas Stabler; Virginia B. Kraus; Benjamin Ma; Thomas M. Link; Xiaojuan Li
Osteoarthritis and Cartilage | 2017
Q. Zhong; M. Tanaka; Benjamin Ma; Xiaojuan Li