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Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network
David C Newitt1, Dariya Malyarenko2, Thomas L Chenevert2
1University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, California, United States.
Journal of Medical Imaging (Bellingham, Wash.)
|October 13, 2017
Summary
Reproducibility of diffusion weighted MRI apparent diffusion coefficient (ADC) metrics is crucial for quantitative biomarkers. While most software shows good agreement for phantom and in vivo breast cancer studies, some biases exist, potentially impacting multisite research.
Area of Science:
- Medical Imaging
- Quantitative Biomarkers
- Diffusion Weighted MRI
Background:
- Diffusion weighted MRI (DW-MRI) is vital for cancer diagnosis and treatment monitoring.
- Reproducibility of DW-MRI metrics, like apparent diffusion coefficient (ADC), is essential for their use as quantitative biomarkers.
Purpose of the Study:
- To assess the variability in apparent diffusion coefficient (ADC) measurements across different software implementations.
- To evaluate the concordance of ADC values from NCI Quantitative Imaging Network software and online scan-generated ADC maps.
Main Methods:
- Phantom and in vivo breast studies were analyzed using two and four b-value diffusion metrics.
- Apparent diffusion coefficient (ADC) variability was examined across multiple postprocessing software implementations and online maps.
- Implementations were grouped by fitting algorithm to analyze intergroup differences.
Main Results:
- The majority of software implementations showed excellent concordance for phantom ADC and in vivo b=1000 ADC, with minimal bias.
- Higher deviations were observed for ADC at lower phantom ADC values and for online ADC maps.
- Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for in vivo b=1000 data.
Conclusions:
- Generally good concordance exists for apparent diffusion coefficient (ADC) measures across different implementations.
- Implementation biases in ADC can be significant, posing potential concerns for multisite studies.
- Further standardization may be needed to ensure reliable ADC biomarker application.
