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Jose Tamez-Pena 1 , Patricia Gonzalez 2 , Edward Schreyer 2 , Saara Totterman 2 ,

SPATIO-TEMPORAL ANALYSIS OF THE SIGNIFICANT CHANGES IN CARTILAGE MORPHOLOGY: DATA FROM THE OSTEOARTHRITIS INITIATIVE. Jose Tamez-Pena 1 , Patricia Gonzalez 2 , Edward Schreyer 2 , Saara Totterman 2 ,

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Jose Tamez-Pena 1 , Patricia Gonzalez 2 , Edward Schreyer 2 , Saara Totterman 2 ,

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  1. SPATIO-TEMPORAL ANALYSIS OF THE SIGNIFICANT CHANGES IN CARTILAGE MORPHOLOGY: DATA FROM THE OSTEOARTHRITIS INITIATIVE Jose Tamez-Pena1, Patricia Gonzalez2, Edward Schreyer2, Saara Totterman2, 1Biomedicine, Tec de Monterrey, Monterrey, Nuevo Leon, Mexico; 2Qmetrics Technologies, Rochester, NY, USA

  2. Objective • Visualize, Follow and Quantitate the Areas of Cartilage Loss in an OA population

  3. Introduction • Problem: • Cartilage Thickness Changes are focal, spatially heterogeneous and bi-directional: Thinning and thickening • Cohort studies look at population averages • The average of this heterogeneous data has a very small responsiveness • Solution: • For a subject: Localize and isolate the changes • For a cohort: Count map of the significant changes in cartilage thickness

  4. Material & Methods • Osteoarthritis Initiative (OAI) 3D DESS data sets: • Releases 0.C.2, 1.C.2 and 3.C.1 from Progression cohort. • Three time points: Baseline, 12 month and 24 month. • 138 subjects with 3 time points • Nonexposed Data Release 0.E.1,1.E.1 and 3.E.1 (n=108) • Three time points: Baseline, 12 month and 24 month. • OAI Pilot Scan-Rescan Longitudinal Data for the estimation of scan-rescan variability (n=24)

  5. Multi-Atlas-Based Segmentation • Generate Atlas • Register and Segment Each MRI to the Atlas (ITK registration modules) • Postprocess the segmentation to match underlying MRI information. • Visually score the quality of the segmentation. • Use the registration data to map each segmentation to the atlas space • Subtract each mapped segmentation to compute change in cartilage thickness • Compute Significant Changes • Compute Cohort Averages

  6. Quantitation

  7. Standardized Analysis: Changes in Cartilage Thickness Medial Lateral -0.5 -0.5 +0.5 +0.5

  8. Change Measurement: Significant Change Maps Minus = 24 Month Baseline Change Map The Scan-Rescan Standard Deviation of the Differences (SDD) is used to mark changes in thickness values that higher than the scan-rescan paired errors ( Delta < -1.96*SDD ) Significant Change Map (Activation Map) Scan-Rescan SDD Map -0.5 -0.75 -0.5 -0.5 0.0 -0.5 +0.75 +0.5 +0.5 +0.5 +0.5 +0.5

  9. Population Maps 12 Month Change Map 24 Month Change Maps Average Referenced Thickness Average Change Map Significant Changes Prevalence Map + = 0.0 0.0 0.3 0.3 -0.5 -0.5 -0.5 +0.5 +0.5 +0.5

  10. 24 Month Results Nonexposed No Denuded Low Denuded High Denuded Baseline 24 Month Change 3.4% 8.1% 9.3% 11.6% 24 Month Heat Map 6.8% 14.7% 17.3% 20.6% n=103 n=51 n=43 n=43 -0.5 -0.5 +0.5 +0.5 0.3 -0.25 0.0 +0.25

  11. P<0.001 P<0.001 SRM=0.73 SRM=0.36 SRM=0.36 SRM=0.39 SRM=0.31 P=0.007 P=0.054

  12. P=0.009 P=0.001 P=0.038 Fisher’s Exact Test

  13. Limitations • Small OA population • Multi-atlas based segmentation is biased towards atlas models • Less accurate at advanced OA cases • Higher noise at advanced OA cases

  14. Conclusion • The automated analysis methodology enabled the localization and mapping of the significant changes in cartilage Thickness. • The significant changes are heterogeneous • Non Exposed OAI cohort did not change • OA subjects with no denuded areas had 2.4% of new areas of cartilage loss every year. SRM=0.73 • The methodology indicated that not all subjects are affected by loss, and that the prevalence of loss is greater at more advanced OA groups.

  15. Acknowledgements • The OAI for all the imaging and clinical data

  16. Change Measurement: Significant Change Maps Baseline 24 Month Change Map -0.5 -0.5 -0.75 +0.75 +0.5 +0.5

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