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Diffusion
MedQIA, in collaboration with UCLA faculty, has developed a new diffusion biomarker based on bimodal ADC histogram analysis.
The bimodal modeling of the ADC histogram allows for quantitative analysis of cellularity and edema components. In a multicenter clinical trial of an anti angiogenic GBM treatment, the mean ADC of the lower (cellularity) component and its relative proportion were found to be significant predictors of patient response to treatment. The ADC biomarker on a single baseline scan was found to be a better predictor of outcome than follow-up size change metrics. This research was published in the journal Radiology (Pope 2009).
The development of the ADC biomarker included a standardized MRI protocol for multicenter clinical trials. This protocol provides MRI acquisition parameters for different scanners that produce comparable images. We have also developed an image quality control metric based on analysis of normal brain white matter.
Tumors are contoured on T1 scans (left) and then mapped to the corresponding ADC image (right).
The bimodal ADC histogram modeling allows for quantitative analysis of cellularity and edema components.
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