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

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Presentation on theme: "SPATIO-TEMPORAL ANALYSIS OF THE SIGNIFICANT CHANGES IN CARTILAGE MORPHOLOGY: DATA FROM THE OSTEOARTHRITIS INITIATIVE Jose Tamez-Pena 1, Patricia Gonzalez."— Presentation transcript:

1 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, 1 Biomedicine, Tec de Monterrey, Monterrey, Nuevo Leon, Mexico; 2 Qmetrics 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

8 Change Measurement: Significant Change Maps Minus Change Map Scan-Rescan SDD Map Significant Change Map (Activation Map) Baseline24 Month = 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 )

9 Population Maps Average Referenced Thickness 12 Month Change Map 24 Month Change Maps Average Change Map Significant Changes Prevalence Map =

10 24 Month Results NonexposedNo DenudedLow DenudedHigh Denuded n=103n=51n= % 9.3%8.1%11.6% 17.3% 14.7% 3.4% 6.8% Baseline 24 Month Change 24 Month Heat Map

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

12 P=0.009P=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 Baseline24 MonthChange Map Change Measurement: Significant Change Maps


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