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Baseline tibiofemoral bone marrow lesions are predictive for higher incidence of knee OA after 6.7 years in overweight and obese women
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
Conclusions: A novel and efficient method to segment IPFP and calculate its signal intensity on T2-weighted MRI images is documented. This method is reproducible, and has concurrent and clinical construct validity, but its predictive validity needs to be examined by future longitudinal studies.
Baseline characteristics of participants (n¼100) Characteristic
Values
Age (years) Height (cm) Weight (kg) BMI (kg/m2) TF cartilage defects scores TF BML scores Total ROA scores Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor (H)
63.9(6.8) 169.9(9.6) 85.7(15.0) 29.7(4.7) 14.0(4.1) 4.1(3.8) 7.9(5.1) 0.2(0.03) 0.1(0.02) 0.3(0.05) 0.4(0.1) 2.0(0.6) 0.1(0.01) 6.0(0.7)
S273
Associations between IPFP measurements and ROA score
Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor (H)
Univariable b(95% CI)
Multivariable* b(95% CI)
0.04(40.83,59.50) 0.76 (0.09, 1.43) 0.17(6.02,41.74) 1.31 (0.50, 3.11) 0.36(1.22,5.05) 1.38 (0.36, 2.39) 2.28 (0.42, 4.13)
0.09(30.08,69.69) 0.76 (0.05, 1.47) 0.18(5.60,42.72) 1.35 (0.53, 3.22) 0.41(1.10,6.19) 1.18 (0.15, 2.21) 1.82 (¡0.08, 3.72)
*adjusted for age, sex and BMI. BMI, body mass index; ROA: radiographic osteoarthritis; IPFP: infrapatellar fat pad; Mean (IPFP), mean value of IPFP intensity; sDev (IPFP), standard deviation of IPFP signal intensity; Median (H), median value of high signal intensity region; UQ(H), upper quartile value of high signal intensity region; Volume (H), volume of high signal intensity region; Percentage (H): ratio of volume of high signal intensity region/whole IPFP volume; Clustering factor(H): clustering factor of high signal intensity. Significant differences are shown in bold.
Intra- and inter-observer correlation coefficients for IPFP measurements
Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor(H)
Intra-observer
Inter-observer
0.99 0.97 0.95 0.98 0.99 0.95 0.96
1.00 0.90 0.99 0.91 0.99 0.96 0.93
Associations between IPFP measurements and TF cartilage defects
Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage(H) Clustering factor(H)
Univariableb(95% CI)
Multivariableb*(95% CI)
0.01(22.93,24.87) 0.35(0.01,0.70) 0.14(3.73,20.40) 0.57(0.35,1.49) 0.30(0.53,2.56) 0.7(0.28,1.21) 1.69(0.88,2.50)
0.02(23.49,27.44) 0.38(0.01,0.76) 0.15(3.90,21.50) 0.60(0.37,1.58) 0.44(1.00,3.66) 0.73(0.26,1.20) 1.67(0.85,2.50)
*adjusted for age, sex and body mass index. TF, tibiofemoral; IPFP: infrapatellar fat pad; Mean (IPFP), mean value of IPFP intensity; sDev (IPFP), standard deviation of IPFP signal intensity; Median (H), median value of high signal intensity region; UQ(H), upper quartile value of high signal intensity region; Volume (H), volume of high signal intensity region; Percentage (H): ratio of volume of high signal intensity region/whole IPFP volume; Clustering factor(H): clustering factor of high signal intensity. Significant differences are shown in bold.
Associations between IPFP measurements and TF bone marrow lesions
Mean(IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor (H)
Univariable b(95% CI)
Multivariable* b(95% CI)
0.01(26.76,28.44) 0.44 (0.08, 0.80) 0.19(0.34,27.26) 0.87 (0.08,1.83) 0.19(0.03,2.36) 0.48 (0.02,0.98) 1.73 (0.88,2.58)
0.01(28.16,30.21) 0.42 (0.03, 0.81) 0.18(2.06,26.90) 0.81 (0.21, 1.82) 0.20(0.41,2.78) 0.50 (0.01, 1.01) 1.73 (0.86, 2.60)
*adjusted for age, sex and body mass index. TF, tibiofemoral; IPFP: infrapatellar fat pad; Mean (IPFP), mean value of IPFP intensity; sDev (IPFP), standard deviation of IPFP signal intensity; Median (H), median value of high signal intensity region; UQ(H), upper quartile value of high signal intensity region; Volume (H), volume of high signal intensity region; Percentage (H): ratio of volume of high signal intensity region/whole IPFP volume; Clustering factor(H): clustering factor of high signal intensity. Significant differences are shown in bold.
Figure 1. Segmentation and intensity calculation of infrapatellar fat pad on sagittal planes of fat-saturated T2-weighted images using MATLAB. (a) The segmentation of IPFP is performed first. An initial lasso is created by a set of points near the outer contour of infrapatellar fat pad and then contracts inward to approximate the real boundary of infrapatellar fad pad automatically. (b) The red areas within the IPFP represent the high signal regions which are obtained by newly developed algorithm. The regions with high signal intensity scatter over whole IPFP. The total volume of these regions is 2.07 and clustering factor (H) is 5.15. (c) The sagittal slice of T2-weighted MRI shows regions with clustering high signal intensity. The total volume of these regions is 2.06 and clustering factor (H) is 7.51. 459 BASELINE TIBIOFEMORAL BONE MARROW LESIONS ARE PREDICTIVE FOR HIGHER INCIDENCE OF KNEE OA AFTER 6.7 YEARS IN OVERWEIGHT AND OBESE WOMEN B. Schouten y, z, J. Runhaar z, D. Vroegindeweij y, E. Oei z, S. Bierma-Zeinstra z. y Maasstadziekenhuis, Rotterdam, Netherlands; z Erasmus Med. Ctr., Rotterdam, Netherlands Purpose: The aim of this study was to investigate whether there is an association between bone marrow lesions (BMLs) in the knee joint at baseline and the incidence of knee osteoarthritis (OA) after 6.7 years follow up in overweight and obese women free of knee OA at baseline.
S274
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
Methods: We analysed data from the PROOF study. In this preventive RCT, women in the area of Rotterdam aged 50e60 with a BMI 27 kg/ m2 and without knee complaints, were invited for baseline physical examination, questionnaire, radiography and MRI. The first 2.5 years of the follow-up was part of a 2x2 factorial design RCT without significant main effects, after which an observational period of 4.2 years followed. Women with baseline Kellgren & Lawrence (K & L) grade 1 and complete follow-up after 6.7 years, were selected for the analyses. The primary outcome measures after 6.7 years were: incident radiographic knee OA (K & L grade 2 or higher), clinical knee OA according to radiographic and clinical ACR criteria, or frequent knee pain defined as pain on most days of the past month. Using generalized estimating equations, we compared knees with and without BMLs at baseline, separating tibiofemoral and patellofemoral joint compartments. Baseline group characteristics were determined (Table 1 and 2) and adjusted for. Results: A total of 440 knees in 229 women were included in the analysis. After 6.7 years, a total of 65 knees (14.8%) developed radiographic OA. The presence of tibiofemoral BMLs at baseline showed a significantly higher risk in development of radiographic OA (9.0% vs. 24.8%, adjusted OR 2.98, 95% CI 1.77e5.03), whereas there was no significantly higher risk of developing clinical knee OA and frequent knee pain (9.7% vs. 14.3%, adjusted OR 1.36, 95% CI 0.81e2.29 and 10.0% vs. 15.5%, 1.46, 95% CI 0.87e2.48, respectively). The presence of patellofemoral BMLs at baseline showed no significant risk towards developing radiographic knee OA (10.5% vs. 18.6%, adjusted OR 1.17, 95% CI 0.63e2.17), clinical knee OA (9.1% vs. 13.4%, adjusted OR 1.29, 95% CI 0.70e2.39) or frequent knee pain (10.0% vs. 13.9%, adjusted OR 1.23, 95% CI 0.68e2.22). Conclusions: Presence of tibiofemoral BMLs is associated with a higher incidence of radiographic OA after 6.7 years follow-up in overweight and obese women, providing further insight in pathogenesis of OA and identification of high-risk groups. Table 1. Baseline characteristics of knees with and without tibiofemoral bone marrow lesions Tibiofemoral BMLs
Age (years) BMI (kg/m2) History of knee injury (yes) Postmenopausal status (yes) Baseline K & L: 1 HbA1c (42 mmol/mol) Cholesterol ( 6.5 mmol/mol) Physical activity (Squash questionnaire) Heberden's nodes (1 or 2 hands) Concurrent patellofemoral BMLs (present)
P-value
Absent
Present
55,7 (±3,1) 31,7 (±3,7) 10,2% 68,1% 46,2% 9,2% 33,3% 7134 (±3437)
55,7 (±3,2) 32,0 (±3,6) 13,8% 73,2% 52,2% 7,7% 35,3% 7149 (±3680)
0,905 0,443 0,276 0,276 0,236 0,719 0,749 0,965
25,8% 45,9%
30,6% 64,0%
0,314 0,000
Table 2. Baseline characteristics of knees with and without patellofemoral bone marrow lesions Patellofemoral BMLs
Age (years) BMI (kg/m2) History of knee injury (yes) Postmenopausal status (yes) Baseline K & L: 1 HbA1c (42 mmol/mol) Cholesterol ( 6.5 mmol/mol) Physical activity (Squash questionnaire) Heberden's nodes (1 or 2 hands) Concurrent tibiofemoral BMLs (present)
P-value
Absent
Present
55,5 (±3,3) 31,3 (±3,4) 13,1% 70,2% 40,2% 7,2% 35,0% 7514 (±3903)
55,9 (±3,0) 32,2 (±3,9) 10,1% 69,9% 55,8% 9,9% 33,2% 6800 (±3112)
0,207 0,009 0,368 1,000 0,001 0,384 0,757 0,034
25,4% 27,8%
29,5% 44,6%
0,388 0,000
460 PRESENCE OF CARTILAGE LESIONS AT THE TIME OF INJURY INFLUENCES THE LONGITUDINAL PROGRESSION OF T1r AND T2 6 MONTHS AFTER ANTERIOR CRUCIATE LIGAMENT INJURY C. Russell y, V. Pedoia y, K. Amano y, H. Potter z, S. Majumdar y. y Univ. of California, San Francisco, San Francisco, CA, USA; z Hosp. for Special Surgery, New York City, NY, USA Purpose: This study investigates the relationship between anterior cruciate ligament (ACL) injury and subsequent osteoarthritis (OA) progression. The first experiment correlates T1r and T2 relaxation times with clinical grading, while the second analyzes progression of T1r and T2 in cohorts defined by baseline cartilage quality. Both analyses use voxel-based relaxometry (VBR), a novel technique offering information on localized cartilage change. Methods: 64 patients sustaining acute, unilateral ACL tears (28 Female; Age¼28.7±2.9 yrs; BMI¼24.5±3.1 kg/m2) were scanned using a 3T MR (GE Healthcare). 2 patients had previous surgery in the contralateral knee, and 2 patients did not undergo reconstructive surgery. Bilateral scans were performed with an 8-channel phased array knee coil (Invivo Inc.) at time of injury (baseline). 56 patients (24 Female; Age¼29.3±12.7 yrs; BMI¼24.7±3.0 kg/m2) were imaged 6 months after surgery. MRI protocol included combined T1r/T2 (T1r TSL¼ 0/10/40/80 ms, FSL¼500 Hz, FOV 14 cm, 256128 matrix, slice thickness 4 mm, T2 preparation TE¼0/12.87/25.69/51.39ms). Non-rigid registration aligned images onto a template image. A board-certified musculoskeletal radiologist evaluated cartilage seen on MRI using the Noyes Score (NS) system. Inhouse programs calculated T1r and T2 Pearson Partial correlations with NS at the voxel-level, adjusted for age, gender and BMI. In the second experiment, baseline medial and PFJ compartment NS of the injured knee of patients with 6-month scans determined two cohorts: 37 with no lesions pre-injury (16 Female; Age¼22.8±9.4 yrs; BMI¼23.9±2.5 kg/ m2), and 17 with previous lesions (7 Female; Age¼40.8±10.4 yrs; BMI¼26.1±3.5 kg/m2). Cross-sectional and longitudinal analyses compared baseline and 6-month relaxation times of patients with lesions at baseline, “pre-OA”, and those without lesions. Longitudinal evaluations of T1r and T2 adjusted for age, gender, BMI, meniscal lesions, MCL lesions, surgery type, and graft source. Results: Trochlea and patella NS correlations displayed the most significant associations with T1r and T2. T2 trends were similar to those of T1r. In the injured knee at baseline, trochlea NS were correlated with T1r in the trochlea, patella, and lateral tibia (LT; R¼0.32, 0.34, 0.35; Fig. 1A). Contralateral trochlea NS were correlated with T1r in the trochlea, patella and LT, and also with the medial femoral condyle (MFC; R¼0.29, 0.35, 0.31, 0.33; Fig. 1B). Trochlea NS of the injured knee at 6 months did not significantly correlate with any regions (Fig. 1C), whereas contralateral trochlea NS remained correlated with patella and LT (R¼0.42, 0.33), and also with the lateral femoral condyle (LFC; R¼0.39) and medial tibia (MT; R¼0.34; Fig. 1D). Similar trends were observed with patella NS correlations. Significant cross-sectional differences between cohorts were most observed at 6 months in the MFC (Fig. 2B; MFC T1r volume significantly different between cohorts¼30%, avg p-value in compartment¼0.02) and the trochlea (Fig. 3B; trochlea T1r volume significantly different between cohorts¼10%, avg p-value in compartment¼0.02). Longitudinally, pre-OA patients showed greater T1r over 6 months in medial weight-bearing regions (Fig. 2D) and superficial trochlea (Fig. 3D), compared to those without baseline lesions (Fig. 2C, 3C). Similar trends were observed in LT and LFC. Conclusions: In NS correlations, association between the scored compartment with lesions and elevated T1r and T2 was expected, such as trochlear NS with T1r in the trochlea. However, other compartments were significantly correlated with trochlea NS, indicating intricate connections between compartments. Stratification by NS analyzes groups based on baseline cartilage lesions, utilizing NS as an indicator of cartilage quality before the injury. Results obtained suggest that cartilage of patients with baseline lesions deteriorates at an accelerated rate, as observed at 6 months, compared to those without baseline lesions (Fig. 2 and 3). This proposes that the presence of previous lesions may be a major contributor to post-injury OA progression. Future longitudinal studies can characterize these specific regions affected by ACL tears after several years, as well as further examine connections between cartilage compartments.
Conclusions: A novel and efficient method to segment IPFP and calculate its signal intensity on T2-weighted MRI images is documented. This method is reproducible, and has concurrent and clinical construct validity, but its predictive validity needs to be examined by future longitudinal studies.
Baseline characteristics of participants (n¼100) Characteristic
Values
Age (years) Height (cm) Weight (kg) BMI (kg/m2) TF cartilage defects scores TF BML scores Total ROA scores Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor (H)
63.9(6.8) 169.9(9.6) 85.7(15.0) 29.7(4.7) 14.0(4.1) 4.1(3.8) 7.9(5.1) 0.2(0.03) 0.1(0.02) 0.3(0.05) 0.4(0.1) 2.0(0.6) 0.1(0.01) 6.0(0.7)
S273
Associations between IPFP measurements and ROA score
Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor (H)
Univariable b(95% CI)
Multivariable* b(95% CI)
0.04(40.83,59.50) 0.76 (0.09, 1.43) 0.17(6.02,41.74) 1.31 (0.50, 3.11) 0.36(1.22,5.05) 1.38 (0.36, 2.39) 2.28 (0.42, 4.13)
0.09(30.08,69.69) 0.76 (0.05, 1.47) 0.18(5.60,42.72) 1.35 (0.53, 3.22) 0.41(1.10,6.19) 1.18 (0.15, 2.21) 1.82 (¡0.08, 3.72)
*adjusted for age, sex and BMI. BMI, body mass index; ROA: radiographic osteoarthritis; IPFP: infrapatellar fat pad; Mean (IPFP), mean value of IPFP intensity; sDev (IPFP), standard deviation of IPFP signal intensity; Median (H), median value of high signal intensity region; UQ(H), upper quartile value of high signal intensity region; Volume (H), volume of high signal intensity region; Percentage (H): ratio of volume of high signal intensity region/whole IPFP volume; Clustering factor(H): clustering factor of high signal intensity. Significant differences are shown in bold.
Intra- and inter-observer correlation coefficients for IPFP measurements
Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor(H)
Intra-observer
Inter-observer
0.99 0.97 0.95 0.98 0.99 0.95 0.96
1.00 0.90 0.99 0.91 0.99 0.96 0.93
Associations between IPFP measurements and TF cartilage defects
Mean (IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage(H) Clustering factor(H)
Univariableb(95% CI)
Multivariableb*(95% CI)
0.01(22.93,24.87) 0.35(0.01,0.70) 0.14(3.73,20.40) 0.57(0.35,1.49) 0.30(0.53,2.56) 0.7(0.28,1.21) 1.69(0.88,2.50)
0.02(23.49,27.44) 0.38(0.01,0.76) 0.15(3.90,21.50) 0.60(0.37,1.58) 0.44(1.00,3.66) 0.73(0.26,1.20) 1.67(0.85,2.50)
*adjusted for age, sex and body mass index. TF, tibiofemoral; IPFP: infrapatellar fat pad; Mean (IPFP), mean value of IPFP intensity; sDev (IPFP), standard deviation of IPFP signal intensity; Median (H), median value of high signal intensity region; UQ(H), upper quartile value of high signal intensity region; Volume (H), volume of high signal intensity region; Percentage (H): ratio of volume of high signal intensity region/whole IPFP volume; Clustering factor(H): clustering factor of high signal intensity. Significant differences are shown in bold.
Associations between IPFP measurements and TF bone marrow lesions
Mean(IPFP) sDev (IPFP) Median (H) UQ (H) Volume (H) Percentage (H) Clustering factor (H)
Univariable b(95% CI)
Multivariable* b(95% CI)
0.01(26.76,28.44) 0.44 (0.08, 0.80) 0.19(0.34,27.26) 0.87 (0.08,1.83) 0.19(0.03,2.36) 0.48 (0.02,0.98) 1.73 (0.88,2.58)
0.01(28.16,30.21) 0.42 (0.03, 0.81) 0.18(2.06,26.90) 0.81 (0.21, 1.82) 0.20(0.41,2.78) 0.50 (0.01, 1.01) 1.73 (0.86, 2.60)
*adjusted for age, sex and body mass index. TF, tibiofemoral; IPFP: infrapatellar fat pad; Mean (IPFP), mean value of IPFP intensity; sDev (IPFP), standard deviation of IPFP signal intensity; Median (H), median value of high signal intensity region; UQ(H), upper quartile value of high signal intensity region; Volume (H), volume of high signal intensity region; Percentage (H): ratio of volume of high signal intensity region/whole IPFP volume; Clustering factor(H): clustering factor of high signal intensity. Significant differences are shown in bold.
Figure 1. Segmentation and intensity calculation of infrapatellar fat pad on sagittal planes of fat-saturated T2-weighted images using MATLAB. (a) The segmentation of IPFP is performed first. An initial lasso is created by a set of points near the outer contour of infrapatellar fat pad and then contracts inward to approximate the real boundary of infrapatellar fad pad automatically. (b) The red areas within the IPFP represent the high signal regions which are obtained by newly developed algorithm. The regions with high signal intensity scatter over whole IPFP. The total volume of these regions is 2.07 and clustering factor (H) is 5.15. (c) The sagittal slice of T2-weighted MRI shows regions with clustering high signal intensity. The total volume of these regions is 2.06 and clustering factor (H) is 7.51. 459 BASELINE TIBIOFEMORAL BONE MARROW LESIONS ARE PREDICTIVE FOR HIGHER INCIDENCE OF KNEE OA AFTER 6.7 YEARS IN OVERWEIGHT AND OBESE WOMEN B. Schouten y, z, J. Runhaar z, D. Vroegindeweij y, E. Oei z, S. Bierma-Zeinstra z. y Maasstadziekenhuis, Rotterdam, Netherlands; z Erasmus Med. Ctr., Rotterdam, Netherlands Purpose: The aim of this study was to investigate whether there is an association between bone marrow lesions (BMLs) in the knee joint at baseline and the incidence of knee osteoarthritis (OA) after 6.7 years follow up in overweight and obese women free of knee OA at baseline.
S274
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
Methods: We analysed data from the PROOF study. In this preventive RCT, women in the area of Rotterdam aged 50e60 with a BMI 27 kg/ m2 and without knee complaints, were invited for baseline physical examination, questionnaire, radiography and MRI. The first 2.5 years of the follow-up was part of a 2x2 factorial design RCT without significant main effects, after which an observational period of 4.2 years followed. Women with baseline Kellgren & Lawrence (K & L) grade 1 and complete follow-up after 6.7 years, were selected for the analyses. The primary outcome measures after 6.7 years were: incident radiographic knee OA (K & L grade 2 or higher), clinical knee OA according to radiographic and clinical ACR criteria, or frequent knee pain defined as pain on most days of the past month. Using generalized estimating equations, we compared knees with and without BMLs at baseline, separating tibiofemoral and patellofemoral joint compartments. Baseline group characteristics were determined (Table 1 and 2) and adjusted for. Results: A total of 440 knees in 229 women were included in the analysis. After 6.7 years, a total of 65 knees (14.8%) developed radiographic OA. The presence of tibiofemoral BMLs at baseline showed a significantly higher risk in development of radiographic OA (9.0% vs. 24.8%, adjusted OR 2.98, 95% CI 1.77e5.03), whereas there was no significantly higher risk of developing clinical knee OA and frequent knee pain (9.7% vs. 14.3%, adjusted OR 1.36, 95% CI 0.81e2.29 and 10.0% vs. 15.5%, 1.46, 95% CI 0.87e2.48, respectively). The presence of patellofemoral BMLs at baseline showed no significant risk towards developing radiographic knee OA (10.5% vs. 18.6%, adjusted OR 1.17, 95% CI 0.63e2.17), clinical knee OA (9.1% vs. 13.4%, adjusted OR 1.29, 95% CI 0.70e2.39) or frequent knee pain (10.0% vs. 13.9%, adjusted OR 1.23, 95% CI 0.68e2.22). Conclusions: Presence of tibiofemoral BMLs is associated with a higher incidence of radiographic OA after 6.7 years follow-up in overweight and obese women, providing further insight in pathogenesis of OA and identification of high-risk groups. Table 1. Baseline characteristics of knees with and without tibiofemoral bone marrow lesions Tibiofemoral BMLs
Age (years) BMI (kg/m2) History of knee injury (yes) Postmenopausal status (yes) Baseline K & L: 1 HbA1c (42 mmol/mol) Cholesterol ( 6.5 mmol/mol) Physical activity (Squash questionnaire) Heberden's nodes (1 or 2 hands) Concurrent patellofemoral BMLs (present)
P-value
Absent
Present
55,7 (±3,1) 31,7 (±3,7) 10,2% 68,1% 46,2% 9,2% 33,3% 7134 (±3437)
55,7 (±3,2) 32,0 (±3,6) 13,8% 73,2% 52,2% 7,7% 35,3% 7149 (±3680)
0,905 0,443 0,276 0,276 0,236 0,719 0,749 0,965
25,8% 45,9%
30,6% 64,0%
0,314 0,000
Table 2. Baseline characteristics of knees with and without patellofemoral bone marrow lesions Patellofemoral BMLs
Age (years) BMI (kg/m2) History of knee injury (yes) Postmenopausal status (yes) Baseline K & L: 1 HbA1c (42 mmol/mol) Cholesterol ( 6.5 mmol/mol) Physical activity (Squash questionnaire) Heberden's nodes (1 or 2 hands) Concurrent tibiofemoral BMLs (present)
P-value
Absent
Present
55,5 (±3,3) 31,3 (±3,4) 13,1% 70,2% 40,2% 7,2% 35,0% 7514 (±3903)
55,9 (±3,0) 32,2 (±3,9) 10,1% 69,9% 55,8% 9,9% 33,2% 6800 (±3112)
0,207 0,009 0,368 1,000 0,001 0,384 0,757 0,034
25,4% 27,8%
29,5% 44,6%
0,388 0,000
460 PRESENCE OF CARTILAGE LESIONS AT THE TIME OF INJURY INFLUENCES THE LONGITUDINAL PROGRESSION OF T1r AND T2 6 MONTHS AFTER ANTERIOR CRUCIATE LIGAMENT INJURY C. Russell y, V. Pedoia y, K. Amano y, H. Potter z, S. Majumdar y. y Univ. of California, San Francisco, San Francisco, CA, USA; z Hosp. for Special Surgery, New York City, NY, USA Purpose: This study investigates the relationship between anterior cruciate ligament (ACL) injury and subsequent osteoarthritis (OA) progression. The first experiment correlates T1r and T2 relaxation times with clinical grading, while the second analyzes progression of T1r and T2 in cohorts defined by baseline cartilage quality. Both analyses use voxel-based relaxometry (VBR), a novel technique offering information on localized cartilage change. Methods: 64 patients sustaining acute, unilateral ACL tears (28 Female; Age¼28.7±2.9 yrs; BMI¼24.5±3.1 kg/m2) were scanned using a 3T MR (GE Healthcare). 2 patients had previous surgery in the contralateral knee, and 2 patients did not undergo reconstructive surgery. Bilateral scans were performed with an 8-channel phased array knee coil (Invivo Inc.) at time of injury (baseline). 56 patients (24 Female; Age¼29.3±12.7 yrs; BMI¼24.7±3.0 kg/m2) were imaged 6 months after surgery. MRI protocol included combined T1r/T2 (T1r TSL¼ 0/10/40/80 ms, FSL¼500 Hz, FOV 14 cm, 256128 matrix, slice thickness 4 mm, T2 preparation TE¼0/12.87/25.69/51.39ms). Non-rigid registration aligned images onto a template image. A board-certified musculoskeletal radiologist evaluated cartilage seen on MRI using the Noyes Score (NS) system. Inhouse programs calculated T1r and T2 Pearson Partial correlations with NS at the voxel-level, adjusted for age, gender and BMI. In the second experiment, baseline medial and PFJ compartment NS of the injured knee of patients with 6-month scans determined two cohorts: 37 with no lesions pre-injury (16 Female; Age¼22.8±9.4 yrs; BMI¼23.9±2.5 kg/ m2), and 17 with previous lesions (7 Female; Age¼40.8±10.4 yrs; BMI¼26.1±3.5 kg/m2). Cross-sectional and longitudinal analyses compared baseline and 6-month relaxation times of patients with lesions at baseline, “pre-OA”, and those without lesions. Longitudinal evaluations of T1r and T2 adjusted for age, gender, BMI, meniscal lesions, MCL lesions, surgery type, and graft source. Results: Trochlea and patella NS correlations displayed the most significant associations with T1r and T2. T2 trends were similar to those of T1r. In the injured knee at baseline, trochlea NS were correlated with T1r in the trochlea, patella, and lateral tibia (LT; R¼0.32, 0.34, 0.35; Fig. 1A). Contralateral trochlea NS were correlated with T1r in the trochlea, patella and LT, and also with the medial femoral condyle (MFC; R¼0.29, 0.35, 0.31, 0.33; Fig. 1B). Trochlea NS of the injured knee at 6 months did not significantly correlate with any regions (Fig. 1C), whereas contralateral trochlea NS remained correlated with patella and LT (R¼0.42, 0.33), and also with the lateral femoral condyle (LFC; R¼0.39) and medial tibia (MT; R¼0.34; Fig. 1D). Similar trends were observed with patella NS correlations. Significant cross-sectional differences between cohorts were most observed at 6 months in the MFC (Fig. 2B; MFC T1r volume significantly different between cohorts¼30%, avg p-value in compartment¼0.02) and the trochlea (Fig. 3B; trochlea T1r volume significantly different between cohorts¼10%, avg p-value in compartment¼0.02). Longitudinally, pre-OA patients showed greater T1r over 6 months in medial weight-bearing regions (Fig. 2D) and superficial trochlea (Fig. 3D), compared to those without baseline lesions (Fig. 2C, 3C). Similar trends were observed in LT and LFC. Conclusions: In NS correlations, association between the scored compartment with lesions and elevated T1r and T2 was expected, such as trochlear NS with T1r in the trochlea. However, other compartments were significantly correlated with trochlea NS, indicating intricate connections between compartments. Stratification by NS analyzes groups based on baseline cartilage lesions, utilizing NS as an indicator of cartilage quality before the injury. Results obtained suggest that cartilage of patients with baseline lesions deteriorates at an accelerated rate, as observed at 6 months, compared to those without baseline lesions (Fig. 2 and 3). This proposes that the presence of previous lesions may be a major contributor to post-injury OA progression. Future longitudinal studies can characterize these specific regions affected by ACL tears after several years, as well as further examine connections between cartilage compartments.