Can the apparent diffusion coefficient be used as a noninvasive parameter to distinguish tumor tissue from peritumoral tissue in cerebral gliomas?

Abstract

Purpose:To determine whether the apparent diffusion coefficient (ADC) can be used to distinguish between tumor tissue and peritumoral brain tissue in cerebral gliomas. Materials and Methods:Twenty-two patients with 44 biopsies were enrolled in this study. ADC maps calculated from a diffusion-weighted (DW) multislice EPI sequence were coregistered with conventional MR images. Neuronavigated biopsies and intraoperative markers were used for correlation with the histologic specimens. ADC values and lesion-to-brain ratios of the different sequences were calculated and compared for tumor tissue and peritumoral brain tissue. A logistic regression analysis was performed to determine the diagnostic value of the ADC maps. Results:The ADC values and ratios demonstrated a large overlap between tumor tissue and peritumoral tissue. Group comparisons revealed a significantly (P ϭ 0.03) lower ADC ratio in tumor tissue (mean ϭ 1.28 Ϯ 0.39) compared to peritumoral tissue (mean ϭ 1.48 Ϯ 0.30), whereas the absolute ADC values did not differ significantly. In the logistic regression analysis, the lesion-to-brain ratio of the gadolinium (Gd)-enhanced T1-weighted sequence was the most valuable predictor of the presence of tumor tissue. The ADC value and ratio were not identified as significant predictors. Conclusion:The ADC is not helpful for distinguishing tumor tissue from peritumoral brain tissue in gliomas.

Imaging biomarkers of brain tumour margin and tumour invasion

“…A number of studies have tried to correlate imageguided biopsy material with DTI measurements. Pauleit et al [57] tried to correlate these peritumoural ADC measurements with histology determined by image-guided biopsies. Although the ADC from the peritumoural tissue was higher than the tumour tissue ( ) it was not significant.…”

Physiologic characterisation of glioblastoma multiforme using MRI-based hypoxia mapping, chemical shift imaging, perfusion and diffusion maps

“…[5][6][7]19 However, recent comparisons show some lack of reliability in using individual techniques as well as new trends when combining parameters. 19,20 As increasing numbers of biomarkers are developed for MRI, it is increasingly important to determine which techniques are most significant in a patient at a particular time. In addition to evaluation against gold standards, determination of how these techniques relate to each other is relevant.…”

Tumour progression or pseudoprogression? A review of post-treatment radiological appearances of glioblastoma

“…The area sampled is usually determined by regions of enhancement on T1WGd, which has a poor specificity for differentiating between different pathological features, and ADC has been shown to be poor in differentiating tumour from peritumoural oedema. 20,26 Secondly, a potential pitfall is interobserver variance in drawing the region of interest (ROI) and, therefore, measuring inconsistent ADC values. 27 Finally, the diffusion anisotropy of different areas of normal brain varies considerably and care must be taken to compare the fractional anisotropy (FA) values of the ROI to an area as similar as possible in the contralateral hemisphere.…”