Sensitivity to change of cartilage morphometry using coronal FLASH, sagittal DESS, and coronal MPR DESS...

Area of Science:

• Biomedical Imaging
• Osteoarthritis Research
• Quantitative MRI

Background:

• The Osteoarthritis Initiative (OAI) seeks biomarkers for knee osteoarthritis (OA) onset and progression.
• Current quantitative cartilage imaging uses Fast Low Angle Shot (FLASH) and Double Echo Steady-State (DESS) sequences.
• FLASH sequences have long acquisition times, while DESS offers near-isotropic resolution.

Purpose of the Study:

• To directly compare the sensitivity to cartilage thickness changes between FLASH and DESS MRI protocols.
• To evaluate the longitudinal correlation of cartilage thickness measurements from these protocols.
• To assess the utility of reduced DESS data (every second slice) for OA progression monitoring.

Main Methods:

• Acquired baseline and 12-month follow-up MRI data from 80 knees using 1.5 mm coronal FLASH and 0.7 mm sagittal DESS sequences.
• Performed cartilage segmentation on FLASH, sagittal DESS (sagDESS), and coronal multi-planar reconstructions (MPR) of DESS.
• Analyzed cartilage thickness changes in specific weight-bearing regions of the medial femorotibial compartment.

Main Results:

• Standardized response means (SRMs) for cartilage thickness change were comparable across FLASH, coronal MPR DESS, and sagDESS protocols.
• SRMs ranged from -0.34 (coronal FLASH) to -0.38 (sagDESS, 75% ROI), indicating similar sensitivity to change.
• High baseline correlations (r >= 0.94) and moderate-to-high longitudinal correlations (Pearson >= 0.79, Spearman >= 0.45) were observed between protocols.

Conclusions:

• Both FLASH and DESS MRI techniques demonstrate similar longitudinal sensitivity for assessing cartilage morphometry changes in knee OA.
• Analyzing every second slice of the 0.7 mm DESS sequence provides adequate sensitivity for detecting cartilage thickness changes.
• These findings support the use of DESS MRI, potentially with reduced data acquisition, for efficient OA progression monitoring in large cohorts like OAI.