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Validation of functional diffusion maps (fDMs) as a biomarker for human glioma cellularity. J Magn Reson Imaging 2010 Mar;31(3):538-48



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Scopus ID

2-s2.0-77649224700   188 Citations


PURPOSE: To present comprehensive examinations of the assumptions made in functional diffusion map (fDM) analyses and provide a biological basis for fDM classification.

MATERIALS AND METHODS: Sixty-nine patients with gliomas were enrolled in this study. To determine the sensitivity of apparent diffusion coefficients (ADCs) to cellularity, cell density from stereotactic biopsy specimens was correlated with preoperative ADC maps. For definition of ADC thresholds used for fDMs, the 95% confidence intervals (CI) for changes in voxel-wise ADC measurements in normal appearing tissue was analyzed. The sensitivity and specificity to progressing disease was examined using both radiographic and neurological criteria.

RESULTS: Results support the hypothesis that ADC is inversely proportional to cell density with a sensitivity of 1.01 x 10(-7) [mm(2)/s]/[nuclei/mm(2)]. The 95% CI for white matter = 0.25 x 10(-3) mm(2)/s, gray matter = 0.31 x 10(-3) mm(2)/s, a mixture of white and gray matter = 0.40 x 10(-3) mm(2)/s, and a mixture of white matter, gray matter, and cerebrospinal fluid = 0.75 x 10(-3) mm(2)/s. Application of these measurements as ADC thresholds produce varying levels of sensitivity and specificity to disease progression, which were all significantly better than chance.

CONCLUSION: This study suggests fDMs are valid biomarkers for brain tumor cellularity.

Author List

Ellingson BM, Malkin MG, Rand SD, Connelly JM, Quinsey C, LaViolette PS, Bedekar DP, Schmainda KM


Jennifer M. Connelly MD Professor in the Neurology department at Medical College of Wisconsin
Peter LaViolette PhD Associate Professor in the Radiology department at Medical College of Wisconsin
Kathleen M. Schmainda PhD Professor in the Biophysics department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Aged, 80 and over
Brain Neoplasms
Computer Simulation
Diffusion Magnetic Resonance Imaging
Image Enhancement
Image Interpretation, Computer-Assisted
Middle Aged
Models, Biological
Reproducibility of Results
Sensitivity and Specificity