- Email: [email protected]
Diffusion MRI models for cartilage: beyond the diffusion tensor
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
We compared the ability of the five regions to differentiate between the case-control status of the study cohort. Results: Change in medial femoral cartilage volume was associated strongly with radiographic progression, especially for the R2 region. However, smaller areas (R3 and R4) were able to predict the casecontrol status with only slightly lower ORs (Table 1). For the second analysis, there was a lower but still significant association of measured cartilage volume with radiographic and pain progression. Again, the association was strongest for R2. Here as well, smaller regions (R3 and R4) resulted only in slightly lower ORs (Table 2). The average reader time for R1 was less than 20 minutes per scan. Smaller areas (R3 and R4) could be assessed with substantially less reader time, since smaller regions require less user attention. Conclusions: There is a strong association between our cartilage volume measurements in the medial femoral region and radiographic progression. This correlation is significant but less prominent with combined radiographic and pain progression. Smaller areas of segmented cartilage deliver the same associations with slightly reduced but similar ORs. This implies that comparable performance can be achieved with substantially less reader time, and the method could be used for studies requiring assessment of several thousand MRI scans.
S283
Change in medial femoral cartilage volume predicting radiographic progression versus others Region of interest
OR
95% CI
R1 R2 R3 R4 R5
3.50 3.82 3.25 3.22 1.63
[2.28e5.38] [2.42e6.03] [2.13e4.95] [2.14e4.84] [1.22e2.17]
Change in medial femoral cartilage volume predicting radiographic and pain progression versus others Region of interest
OR
95% CI
R1 R2 R3 R4 R5
1.65 1.72 1.63 1.63 1.40
[1.26e2.16] [1.30e2.28] [1.24e2.14] [1.23e2.16] [1.04e1.88]
472 DIFFUSION MRI MODELS FOR CARTILAGE: BEYOND THE DIFFUSION TENSOR U. Ferizi, I. Rossi, C. Glaser, J. Bencardino, J. Raya. New York Univ. Sch. of Med., New York, NY, USA Purpose: To investigate if new models provide increased sensitivity and specificity in detecting cartilage damage compared to standard DTI. Methods: Cylindrical samples were drilled from human (aged 34±14y) patellae. Using a 17.6-T MRI (Bruker Advance) scanner with a 5-mm birdcage coil, the samples underwent DTI and OARSI scoring. The DTI protocol had TR/TE¼938/15.0ms, b¼550s/mm2, D¼8 ms, d¼3 ms, resolution¼(50100mm2)x800mm. We select 11 samples from a previous study: three OARSI¼0, two OARSI¼1, three OARSI¼2, three at OARSI¼3e4). We fit the three models described in figure 1. The first is the standard 6parameter DT, which provides us with the derived metrics of mean diffusivity (MD) and fractional anisotropy (FA). The second is a 4parameter cylindrically-symmetric DT, commonly called Zeppelin, from which MD and FA can be extracted. The third model, the 4-parameter Ball-Stick, is a multicompartment model which is often used in neuroimaging applications. Even though the extracellular matrix in the cartilage is very different to that found in brain's white matter (e.g. cells only account for 3% of the total volume), the anisotropy induced by collagen fibers could be captured by the Stick component of the model. In this model, the Ball compartment is effectively an isotropic DT, while the Stick is a one dimensional DT. The cartilage was then segmented on the b¼0, and divided into surface and bottom layers. We also investigated the correlation of the diffusion parameters with the OARSI score. Improvement of correlation is indicative of better ability to predict damage (p-value¼0.05 indicates statistical significance). Results: Figure 2 shows the diffusivity maps from the three models, across six representative OARSI-scored samples. The first column shows the MD from the DT model, the second column shows the MD from the Zeppelin, and the third column shows the estimated diffusivity for both Ball and Stick compartments. In all samples, the DT diffusivity estimate is higher than Zeppelin's or Ball-Stick's (this is particularly visible from the diffusivity in water). Figure 3 represents the anisotropic metric in the same samples of Fig. 2 (FA in DT and Zeppelin, and Stick volume fraction in the Ball-Stick). The simplicity of the Zeppelin and Ball-Stick benefits the fitting; the maps are clearly less noisy than those for DT. We also fitted the models to a large ROI in the water, above the cartilage. Here, the standard DT gave an average FA of 0.043±0.018, the Zeppelin gave 0.0195±0.0124, and the Ball-Stick gave 0.004±0.008. Because of the isotropy of the water, we can deduce that the DT is more affected by SNR, hence giving the worst estimates. The estimated MD of DT was on average 1.941±0.014mm2/mm2, versus 1.838±0.013 for Zeppelin and 1.846±0.024 for Ball-Stick.
S284
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
In Figure 4 we compare the statistics (mean and std) of the models' parameters for the three segmentations of the cartilage. Across all OARSI grades, the bulk Zeppelin mean and variance are lowest among most entries, in both diffusivity and anisotropy. The DT and Ball-Stick are more alike in their mean estimates and variances. Figure 5 provides the correlations of the models metrics with histology's OARSI scores. Here we see that the diffusivity correlations and significance are similar across both DT and the Zeppelin, while the Ball-Stick is only significant to the changes in the surface layer. In the anisotropy measures, however, the two new models provide more significance in the deep layer results than the DT. This is consistent with the findings in Raya-2013, which used a much larger sample size (n¼43). Conclusions: In this study we have shown that alternative models to DT, such as the Ball-Stick and Zeppelin, can provide more robust estimations of anisotropy. These models helped identify significant correlations with cartilage degradation that standard DT missed. These alternative models provide more robust estimation of diffusion parameters with potential application for in vivo DTI.
OARSI grade DT
Zeppelin
Ball Stick
Mean Std bulk bulk
Mean surface
Std surface
Mean Std deep deep
Mean Std bulk bulk
Mean surface
Std surface
Mean Std deep deep
Mean Std bulk bulk
Mean surface
Std surface
Mean Std deep deep
Diffusivity
OARSI 0 OARSI 1 OARSI 2 OARSI 3-4
1.06 1.10 1.15 1.25
0.08 0.06 0.04 0.10
1.18 1.17 1.23 1.41
0.05 0.03 0.06 0.13
0.93 1.04 1.07 1.09
0.11 0.09 0.01 0.08
1.01 1.01 1.09 1.19
0.08 0.08 0.03 0.08
1.12 1.06 1.17 1.33
0.05 0.05 0.06 0.09
0.90 0.95 1.02 1.04
0.11 0.10 0.01 0.07
1.13 1.09 1.17 1.26
0.11 0.10 0.05 0.06
1.16 1.13 1.19 1.38
0.05 0.09 0.05 0.06
1.11 1.05 1.15 1.14
0.16 0.12 0.05 0.06
Anisotropy
OARSI 0 OARSI 1 OARSI 2 OARSI 3-4
0.25 0.20 0.17 0.19
0.04 0.01 0.03 0.05
0.08 0.16 0.07 0.11
0.01 0.02 0.00 0.06
0.44 0.24 0.26 0.26
0.07 0.03 0.05 0.06
0.15 0.15 0.10 0.10
0.02 0.05 0.03 0.03
0.05 0.14 0.04 0.07
0.00 0.06 0.01 0.03
0.25 0.16 0.15 0.14
0.04 0.04 0.04 0.03
0.14 0.07 0.08 0.08
0.01 0.04 0.03 0.03
0.04 0.05 0.03 0.04
0.01 0.06 0.02 0.03
0.24 0.10 0.14 0.11
0.03 0.02 0.05 0.04
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
DT
Diffusivity
Anisotropy
Bulk Surface Deep Bulk Surface Deep
r 0.75 0.78 0.58 -0.58 0.07 -0.58
Zeppelin P 0.01 0.01 0.06 0.06 0.85 0.06
r 0.74 0.77 0.58 -0.54 -0.01 -0.65
Ball-Stick P 0.01 0.01 0.06 0.09 0.97 0.03
r 0.58 0.80 0.16 -0.58 0.01 -0.63
P 0.06 0.00 0.64 0.06 0.99 0.04
S285
Conclusions: In this study VBR was used to assess the local correlation between cartilage composition, symptoms and PFJ Stress. Elevation in the PFJ Cartilage T1r was observed to be associated with excessive mechanical loading and worst patient reported outcomes. Moreover PFJ stress was observed to be significantly correlated, not just with PFJ cartilage changes, but also with T1r values in central lateral tibia and medial femur, probably due to the close relationship between PFJ stress and vertical ground reaction forces (R¼0.55). The results in this study show the association of cartilage biochemical composition with PFJ stress and symptoms, suggesting that prevention and rehabilitation programs for PFJ OA may focus on reducing the mechanical demands on the PFJ.
473 ELEVATION IN PFJ CARTILAGE T1r IS ASSOCIATED WITH EXCESSIVE MECHANICAL LOADING AND WORST PATIENT REPORTED OUTCOMES: A LOCAL VOXEL-BASED RELAXOMETRY ANALYSIS V. Pedoia, H.-L. Teng, A. Randolph, V.R.B. Souza, S. Majumdar. Dept. of Radiology and BioMed. Imaging, Musculoskeletal and Quantitative Imaging Res., UCSF, San Francisco, CA, USA Purpose: Patellofemoral joint (PFJ) osteoarthritis (OA) is a progressive degenerative disorder observed in almost 70% of adults with knee pain. Compositional imaging, such as T1r and T2 relaxation time mapping are well known as a suitable method for studying the biochemical degenerative changes in the articular cartilage. Despite the wide use of MRI compositional imaging for the assessment of the cartilage health, there remains limited evidence of a direct association between cartilage composition and symptoms. Furthermore, while non-modifiable risk factors (i.e. age, gender, race and generic predisposition) have been well established to be associated with OA, it is critical to identify modifiable risk factors of PFJ OA. At the PFJ, increased knee flexion moment is indicative of higher quadriceps force, which can result in greater compressive force at the PFJ and higher PFJ stress. To date, limited reports have been presented on the association of PFJ stress and cartilage composition. In this study Voxel Based Relaxometry, a technique able to detect local cartilage changes, will be used for two purposes: (i) to locally assess the association between cartilage composition and patients reported outcome, and (ii) to locally assess the association between PFJ cartilage composition and PFJ stress, also studying secondary effects on the overall knee. Methods: 84 subjects were considered for this study: 58 OA patients (age¼55.58±9.5 years; BMI¼25.1±3.1 kg/m2; KL ¼1.83) and 26 control subjects (age¼45.9±9.56; BMI¼23.8±3.1 kg/m2; KL ¼ 0). All imaging was done using a 3T MRI scanner (GE Healthcare, Milwaukee, WI, USA) with an 8-channel phased array knee coil (Invivo Inc, Orlando, FL, USA). Sagittal 3D T1r imaging sequences were obtained with the following parameters: TR/TE¼9ms/min full, FOV¼14 cm, matrix¼256x128, slice thickness¼4 mm, spin-lock frequency¼500 Hz, time of spin lock (TSL) ¼ 0/2/4/8/12/20/40/80 ms. All images were morphed to the space of a reference using a previously proposed technique, after which, voxel-byvoxel statistics could be conducted, producing Statistical Parametric Maps (SPMs). All subjects completed patient-reported questionnaires, including Knee-injury and Osteoarthritis Outcome Score (KOOS). Knee kinematics (250 Hz, VICON) and ground reaction forces (1000 Hz, AMTI) were recorded while subjects walked at a self-selected speed. Sagittal plane knee joint angles and moments were computed using Visual3D and Matlab software. PFJ stress during the stance phase of walking was estimated using a previously described biomechanical model. Subjectspecific knee flexion angles and knee flexion moments as well as quadriceps effective moment arms, quadriceps force/patella ligament force ratios and joint contact area reported in the literature were used in the model. Voxel based Pearson partial correlation adjusted for age, gender and BMI were evaluated between T1r values and each of the five KOOS categories and computed PFJ stress. Results: Significant negative correlation was observed between T1r and KOOS (Figure 1A). The femoral trochlea compartment (TrF) showed the most diffuse association 24% of the overall voxels in the compartment showed a significant correlation with KOOS (average on the 5 scores). Patella compartment (P) showed the strongest association (average R ¼ 0.3). Significant positive association was also observed between T1r and the first peak of the PFJ stress (Figure 1B). Medial Femur (MF) and TrF are the compartments with the largest associated: 40% and 29% respectively. Lateral Tibia (LT) and TrF showed the strongest correlation (average R ¼ 0.31). P-values and R SPMs are shown in Figure 2.
Figure 1. Summary of the local coirelation analysis: first row % volume of each compartment that show significant correlated voxel, second row average R values in each cluster. (A) KOOS; (B) PFJ Stress
Figure 2. Voxel based partial correlation between T1r and (A) KOOS, first row: activities of daily living (ADL), second row knee related quality of Life, third row symptoms. (B) PFJ stress. R and p-values indicated in the figures are computed considering the average T1r in the white boxes. 474 ASSOCIATION BETWEEN THE DEGENERATION AND MEDIAL RADIAL DISPLACEMENT OF THE MEDIAL MENISCUS ON T2 MAPPING AT 3T MRI IN PATIENTS WITH EARLY-STAGE KNEE OSTEOARTHRITIS S. Hada y, M. Ishijima y, z, H. Kaneko y, R. Sadatsuki y, L. Liz y, z, M. Kinoshita y, H. Arita y, J. Shiozawa y, A. Yusup y, Y. Takazawa y, H. Ikeda y, K. Kaneko y, z. y Dept. of Med. for Orthopaedics and Motor Organ, Juntendo Univ. Graduate Sch. of Med., Tokyo, Japan; z Sportology Ctr., Juntendo Univ. Graduate Sch. of Med., Tokyo, Japan Purpose: It is still remained unclear how knee osteoarthritis (OA) is really progressed, although recent development of the imaging technology for knee OA has advanced the real developmental process of knee OA. We recently reported that the degeneration and destruction of femoral articular cartilage and osteophytes showed a greater degree of deterioration than those of the tibial and patellar side in early-stage of knee OA using 3TMRI and T2 mapping sequence (Osteoarthritis Cartilage, 2014). In the present study, we examined whether there was any association between medial radial displacement of the medial meniscus (MRD) and the degeneration of the medial meniscus (MM) in earlystage of knee OA using the MRI-T2 mapping technique based analyses.
We compared the ability of the five regions to differentiate between the case-control status of the study cohort. Results: Change in medial femoral cartilage volume was associated strongly with radiographic progression, especially for the R2 region. However, smaller areas (R3 and R4) were able to predict the casecontrol status with only slightly lower ORs (Table 1). For the second analysis, there was a lower but still significant association of measured cartilage volume with radiographic and pain progression. Again, the association was strongest for R2. Here as well, smaller regions (R3 and R4) resulted only in slightly lower ORs (Table 2). The average reader time for R1 was less than 20 minutes per scan. Smaller areas (R3 and R4) could be assessed with substantially less reader time, since smaller regions require less user attention. Conclusions: There is a strong association between our cartilage volume measurements in the medial femoral region and radiographic progression. This correlation is significant but less prominent with combined radiographic and pain progression. Smaller areas of segmented cartilage deliver the same associations with slightly reduced but similar ORs. This implies that comparable performance can be achieved with substantially less reader time, and the method could be used for studies requiring assessment of several thousand MRI scans.
S283
Change in medial femoral cartilage volume predicting radiographic progression versus others Region of interest
OR
95% CI
R1 R2 R3 R4 R5
3.50 3.82 3.25 3.22 1.63
[2.28e5.38] [2.42e6.03] [2.13e4.95] [2.14e4.84] [1.22e2.17]
Change in medial femoral cartilage volume predicting radiographic and pain progression versus others Region of interest
OR
95% CI
R1 R2 R3 R4 R5
1.65 1.72 1.63 1.63 1.40
[1.26e2.16] [1.30e2.28] [1.24e2.14] [1.23e2.16] [1.04e1.88]
472 DIFFUSION MRI MODELS FOR CARTILAGE: BEYOND THE DIFFUSION TENSOR U. Ferizi, I. Rossi, C. Glaser, J. Bencardino, J. Raya. New York Univ. Sch. of Med., New York, NY, USA Purpose: To investigate if new models provide increased sensitivity and specificity in detecting cartilage damage compared to standard DTI. Methods: Cylindrical samples were drilled from human (aged 34±14y) patellae. Using a 17.6-T MRI (Bruker Advance) scanner with a 5-mm birdcage coil, the samples underwent DTI and OARSI scoring. The DTI protocol had TR/TE¼938/15.0ms, b¼550s/mm2, D¼8 ms, d¼3 ms, resolution¼(50100mm2)x800mm. We select 11 samples from a previous study: three OARSI¼0, two OARSI¼1, three OARSI¼2, three at OARSI¼3e4). We fit the three models described in figure 1. The first is the standard 6parameter DT, which provides us with the derived metrics of mean diffusivity (MD) and fractional anisotropy (FA). The second is a 4parameter cylindrically-symmetric DT, commonly called Zeppelin, from which MD and FA can be extracted. The third model, the 4-parameter Ball-Stick, is a multicompartment model which is often used in neuroimaging applications. Even though the extracellular matrix in the cartilage is very different to that found in brain's white matter (e.g. cells only account for 3% of the total volume), the anisotropy induced by collagen fibers could be captured by the Stick component of the model. In this model, the Ball compartment is effectively an isotropic DT, while the Stick is a one dimensional DT. The cartilage was then segmented on the b¼0, and divided into surface and bottom layers. We also investigated the correlation of the diffusion parameters with the OARSI score. Improvement of correlation is indicative of better ability to predict damage (p-value¼0.05 indicates statistical significance). Results: Figure 2 shows the diffusivity maps from the three models, across six representative OARSI-scored samples. The first column shows the MD from the DT model, the second column shows the MD from the Zeppelin, and the third column shows the estimated diffusivity for both Ball and Stick compartments. In all samples, the DT diffusivity estimate is higher than Zeppelin's or Ball-Stick's (this is particularly visible from the diffusivity in water). Figure 3 represents the anisotropic metric in the same samples of Fig. 2 (FA in DT and Zeppelin, and Stick volume fraction in the Ball-Stick). The simplicity of the Zeppelin and Ball-Stick benefits the fitting; the maps are clearly less noisy than those for DT. We also fitted the models to a large ROI in the water, above the cartilage. Here, the standard DT gave an average FA of 0.043±0.018, the Zeppelin gave 0.0195±0.0124, and the Ball-Stick gave 0.004±0.008. Because of the isotropy of the water, we can deduce that the DT is more affected by SNR, hence giving the worst estimates. The estimated MD of DT was on average 1.941±0.014mm2/mm2, versus 1.838±0.013 for Zeppelin and 1.846±0.024 for Ball-Stick.
S284
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
In Figure 4 we compare the statistics (mean and std) of the models' parameters for the three segmentations of the cartilage. Across all OARSI grades, the bulk Zeppelin mean and variance are lowest among most entries, in both diffusivity and anisotropy. The DT and Ball-Stick are more alike in their mean estimates and variances. Figure 5 provides the correlations of the models metrics with histology's OARSI scores. Here we see that the diffusivity correlations and significance are similar across both DT and the Zeppelin, while the Ball-Stick is only significant to the changes in the surface layer. In the anisotropy measures, however, the two new models provide more significance in the deep layer results than the DT. This is consistent with the findings in Raya-2013, which used a much larger sample size (n¼43). Conclusions: In this study we have shown that alternative models to DT, such as the Ball-Stick and Zeppelin, can provide more robust estimations of anisotropy. These models helped identify significant correlations with cartilage degradation that standard DT missed. These alternative models provide more robust estimation of diffusion parameters with potential application for in vivo DTI.
OARSI grade DT
Zeppelin
Ball Stick
Mean Std bulk bulk
Mean surface
Std surface
Mean Std deep deep
Mean Std bulk bulk
Mean surface
Std surface
Mean Std deep deep
Mean Std bulk bulk
Mean surface
Std surface
Mean Std deep deep
Diffusivity
OARSI 0 OARSI 1 OARSI 2 OARSI 3-4
1.06 1.10 1.15 1.25
0.08 0.06 0.04 0.10
1.18 1.17 1.23 1.41
0.05 0.03 0.06 0.13
0.93 1.04 1.07 1.09
0.11 0.09 0.01 0.08
1.01 1.01 1.09 1.19
0.08 0.08 0.03 0.08
1.12 1.06 1.17 1.33
0.05 0.05 0.06 0.09
0.90 0.95 1.02 1.04
0.11 0.10 0.01 0.07
1.13 1.09 1.17 1.26
0.11 0.10 0.05 0.06
1.16 1.13 1.19 1.38
0.05 0.09 0.05 0.06
1.11 1.05 1.15 1.14
0.16 0.12 0.05 0.06
Anisotropy
OARSI 0 OARSI 1 OARSI 2 OARSI 3-4
0.25 0.20 0.17 0.19
0.04 0.01 0.03 0.05
0.08 0.16 0.07 0.11
0.01 0.02 0.00 0.06
0.44 0.24 0.26 0.26
0.07 0.03 0.05 0.06
0.15 0.15 0.10 0.10
0.02 0.05 0.03 0.03
0.05 0.14 0.04 0.07
0.00 0.06 0.01 0.03
0.25 0.16 0.15 0.14
0.04 0.04 0.04 0.03
0.14 0.07 0.08 0.08
0.01 0.04 0.03 0.03
0.04 0.05 0.03 0.04
0.01 0.06 0.02 0.03
0.24 0.10 0.14 0.11
0.03 0.02 0.05 0.04
Abstracts / Osteoarthritis and Cartilage 24 (2016) S63eS534
DT
Diffusivity
Anisotropy
Bulk Surface Deep Bulk Surface Deep
r 0.75 0.78 0.58 -0.58 0.07 -0.58
Zeppelin P 0.01 0.01 0.06 0.06 0.85 0.06
r 0.74 0.77 0.58 -0.54 -0.01 -0.65
Ball-Stick P 0.01 0.01 0.06 0.09 0.97 0.03
r 0.58 0.80 0.16 -0.58 0.01 -0.63
P 0.06 0.00 0.64 0.06 0.99 0.04
S285
Conclusions: In this study VBR was used to assess the local correlation between cartilage composition, symptoms and PFJ Stress. Elevation in the PFJ Cartilage T1r was observed to be associated with excessive mechanical loading and worst patient reported outcomes. Moreover PFJ stress was observed to be significantly correlated, not just with PFJ cartilage changes, but also with T1r values in central lateral tibia and medial femur, probably due to the close relationship between PFJ stress and vertical ground reaction forces (R¼0.55). The results in this study show the association of cartilage biochemical composition with PFJ stress and symptoms, suggesting that prevention and rehabilitation programs for PFJ OA may focus on reducing the mechanical demands on the PFJ.
473 ELEVATION IN PFJ CARTILAGE T1r IS ASSOCIATED WITH EXCESSIVE MECHANICAL LOADING AND WORST PATIENT REPORTED OUTCOMES: A LOCAL VOXEL-BASED RELAXOMETRY ANALYSIS V. Pedoia, H.-L. Teng, A. Randolph, V.R.B. Souza, S. Majumdar. Dept. of Radiology and BioMed. Imaging, Musculoskeletal and Quantitative Imaging Res., UCSF, San Francisco, CA, USA Purpose: Patellofemoral joint (PFJ) osteoarthritis (OA) is a progressive degenerative disorder observed in almost 70% of adults with knee pain. Compositional imaging, such as T1r and T2 relaxation time mapping are well known as a suitable method for studying the biochemical degenerative changes in the articular cartilage. Despite the wide use of MRI compositional imaging for the assessment of the cartilage health, there remains limited evidence of a direct association between cartilage composition and symptoms. Furthermore, while non-modifiable risk factors (i.e. age, gender, race and generic predisposition) have been well established to be associated with OA, it is critical to identify modifiable risk factors of PFJ OA. At the PFJ, increased knee flexion moment is indicative of higher quadriceps force, which can result in greater compressive force at the PFJ and higher PFJ stress. To date, limited reports have been presented on the association of PFJ stress and cartilage composition. In this study Voxel Based Relaxometry, a technique able to detect local cartilage changes, will be used for two purposes: (i) to locally assess the association between cartilage composition and patients reported outcome, and (ii) to locally assess the association between PFJ cartilage composition and PFJ stress, also studying secondary effects on the overall knee. Methods: 84 subjects were considered for this study: 58 OA patients (age¼55.58±9.5 years; BMI¼25.1±3.1 kg/m2; KL ¼1.83) and 26 control subjects (age¼45.9±9.56; BMI¼23.8±3.1 kg/m2; KL ¼ 0). All imaging was done using a 3T MRI scanner (GE Healthcare, Milwaukee, WI, USA) with an 8-channel phased array knee coil (Invivo Inc, Orlando, FL, USA). Sagittal 3D T1r imaging sequences were obtained with the following parameters: TR/TE¼9ms/min full, FOV¼14 cm, matrix¼256x128, slice thickness¼4 mm, spin-lock frequency¼500 Hz, time of spin lock (TSL) ¼ 0/2/4/8/12/20/40/80 ms. All images were morphed to the space of a reference using a previously proposed technique, after which, voxel-byvoxel statistics could be conducted, producing Statistical Parametric Maps (SPMs). All subjects completed patient-reported questionnaires, including Knee-injury and Osteoarthritis Outcome Score (KOOS). Knee kinematics (250 Hz, VICON) and ground reaction forces (1000 Hz, AMTI) were recorded while subjects walked at a self-selected speed. Sagittal plane knee joint angles and moments were computed using Visual3D and Matlab software. PFJ stress during the stance phase of walking was estimated using a previously described biomechanical model. Subjectspecific knee flexion angles and knee flexion moments as well as quadriceps effective moment arms, quadriceps force/patella ligament force ratios and joint contact area reported in the literature were used in the model. Voxel based Pearson partial correlation adjusted for age, gender and BMI were evaluated between T1r values and each of the five KOOS categories and computed PFJ stress. Results: Significant negative correlation was observed between T1r and KOOS (Figure 1A). The femoral trochlea compartment (TrF) showed the most diffuse association 24% of the overall voxels in the compartment showed a significant correlation with KOOS (average on the 5 scores). Patella compartment (P) showed the strongest association (average R ¼ 0.3). Significant positive association was also observed between T1r and the first peak of the PFJ stress (Figure 1B). Medial Femur (MF) and TrF are the compartments with the largest associated: 40% and 29% respectively. Lateral Tibia (LT) and TrF showed the strongest correlation (average R ¼ 0.31). P-values and R SPMs are shown in Figure 2.
Figure 1. Summary of the local coirelation analysis: first row % volume of each compartment that show significant correlated voxel, second row average R values in each cluster. (A) KOOS; (B) PFJ Stress
Figure 2. Voxel based partial correlation between T1r and (A) KOOS, first row: activities of daily living (ADL), second row knee related quality of Life, third row symptoms. (B) PFJ stress. R and p-values indicated in the figures are computed considering the average T1r in the white boxes. 474 ASSOCIATION BETWEEN THE DEGENERATION AND MEDIAL RADIAL DISPLACEMENT OF THE MEDIAL MENISCUS ON T2 MAPPING AT 3T MRI IN PATIENTS WITH EARLY-STAGE KNEE OSTEOARTHRITIS S. Hada y, M. Ishijima y, z, H. Kaneko y, R. Sadatsuki y, L. Liz y, z, M. Kinoshita y, H. Arita y, J. Shiozawa y, A. Yusup y, Y. Takazawa y, H. Ikeda y, K. Kaneko y, z. y Dept. of Med. for Orthopaedics and Motor Organ, Juntendo Univ. Graduate Sch. of Med., Tokyo, Japan; z Sportology Ctr., Juntendo Univ. Graduate Sch. of Med., Tokyo, Japan Purpose: It is still remained unclear how knee osteoarthritis (OA) is really progressed, although recent development of the imaging technology for knee OA has advanced the real developmental process of knee OA. We recently reported that the degeneration and destruction of femoral articular cartilage and osteophytes showed a greater degree of deterioration than those of the tibial and patellar side in early-stage of knee OA using 3TMRI and T2 mapping sequence (Osteoarthritis Cartilage, 2014). In the present study, we examined whether there was any association between medial radial displacement of the medial meniscus (MRD) and the degeneration of the medial meniscus (MM) in earlystage of knee OA using the MRI-T2 mapping technique based analyses.