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Region-of-interest-based analysis of clustered BOLD MRI data in experimental arthritis
1Department of Diagnostic Imaging, The Hospital for Sick Children, 555 University Avenue, University of Toronto, Toronto, ON, Canada M5G1X8. andrea.doria@sickkids.ca
Rationale And Objectives:
BOLD MRI provides functional information based on minimal changes. Problems inherent in data processing of the very low signal-to-noise-ratio of BOLD experiments have created obstacles for validation of certain techniques using standard strength-field MR scanners. Measures of diagnostic accuracy of clustered data are directly related to the reading parameters used to define regions-of-interest (ROIs). Our primary aim was to determine the combination of ROI-related reading parameters that provides highest accuracy for discrimination of presence or absence of arthritis in acute and subacute stages of the disease using paired comparisons of BOLD MRI data.
Materials And Methods:
Six male New Zealand white rabbits were injected with albumin into one knee and saline into the contralateral knee, 3 animals had albumin injected into only one of the knees, 2 had saline injected into one of the knees, and 3 animals were not injected. The rabbits' knees underwent BOLD MRI on days 1 and 28 after induction of arthritis, except for the knees of 3 animals (albumin- vs saline-injected knees, n = 2 animals; saline- vs noninjected knees, n = 1 animal) that died before expected and had only the first MRI examination done. Percentage of activated voxels and differences in on-and-off signal intensities were the BOLD MRI methods applied. Data were analyzed using anatomic-driven small ROI, voxel-chaser-driven small ROI and anatomic-driven large ROI techniques.
Results:
Diagnostic areas-under-the curve (AUCs) were obtained only for acute arthritis and only when percentage of activated voxels was used. Low threshold, positive voxel activations and small ROIs generated the largest AUCs (AUC +/- SE, .911 +/- .092, P = .014) using either anatomic-driven or voxel-chaser-driven techniques. A sensitivity analysis confirmed the importance of threshold as a parameter for analysis.
Conclusion:
Low threshold, positive voxel activations and small ROIs constituted the set of reading parameters that provided the most accurate BOLD MRI results.
Insights
BOLD MRI accurately detects arthritis using specific parameters. Small regions of interest (ROIs) and low thresholds for positive voxel activation yield the highest diagnostic accuracy in acute stages.
Area of Science:
- Radiology
- Medical Imaging
- Orthopedics
Background:
- Blood-oxygen-level-dependent (BOLD) MRI offers functional insights but faces challenges due to low signal-to-noise ratios in standard scanners.
- Accurate interpretation of BOLD MRI data is crucial for diagnosing conditions like arthritis, especially in early disease stages.
- The choice of parameters for defining regions of interest (ROIs) significantly impacts diagnostic accuracy.
Purpose of the Study:
- To identify the optimal combination of ROI-related parameters for accurate BOLD MRI discrimination of arthritis.
- To evaluate diagnostic accuracy in acute and subacute arthritis using paired comparisons of BOLD MRI data.
- To determine the influence of different ROI analysis techniques on diagnostic performance.
Main Methods:
- Albumin-induced arthritis was created in rabbit knees, with contralateral saline injections as controls.
- BOLD MRI scans were performed on days 1 and 28 post-induction.
- Data analysis involved calculating the percentage of activated voxels and signal intensity differences, using anatomic-driven small ROI, voxel-chaser-driven small ROI, and anatomic-driven large ROI techniques.
Main Results:
- Diagnostic accuracy (Area Under the Curve - AUC) was achieved only for acute arthritis and when using the percentage of activated voxels.
- The highest AUCs (.911 +/- .092, P = .014) were obtained with a low threshold for positive voxel activation and small ROIs.
- Sensitivity analysis underscored the critical role of the threshold parameter in BOLD MRI analysis.
Conclusions:
- A combination of low threshold, positive voxel activation, and small ROIs provides the most accurate BOLD MRI results for arthritis detection.
- These specific parameters are essential for improving the diagnostic utility of BOLD MRI in acute arthritis.
- The findings highlight the importance of parameter selection in optimizing BOLD MRI for clinical applications.
