Abstract
Purpose:: Studies have shown that cellularity of glial tumors are inversely correlated to minimum apparent diffusion coefficient (ADC) values derived on diffusion-weighted imaging (DWI). The purpose of this prospective exploratory study was to evaluate whether temporal change in minimum ADC values during follow-up predict progressive disease in glial tumors post radiotherapy and surgery. Materials and Methods:: Adult patients of glial tumors, subjected to surgery followed by Radiotherapy (RT), were included in the study. Serial conventional magnetic resonance imaging with DWI at the following time points presurgery, pre-RT, post-RT imaging at 3, 7, and 15 months were done. For minimum ADC values, multiple regions of interest (ROI) were identified on ADC maps derived from DWI. A mean of 5 minimum ADC values was chosen as minimum ADC value. The correlation was drawn between histology and minimum ADC values and time trends were studied. Results:: Fourteen patients were included in this study. Histologies were low-grade glioma (LGG) 5, anaplastic oligodendroglioma (ODG) -5, and glioblastoma multiforme (GBM) 4. Minimum ADC values were significantly higher in LGG and GBM than ODG. Presurgery, the values were 0.812, 0.633, and 0.787 103 mm2/s for LGG, ODG, and GBM, respectively. DWI done at the time of RT planning showed values of 0.786, 0.636, 0.869 103 mm2/s, respectively. During follow-up, the increasing trend of minimum ADC was observed in LGG (P = 0.02). All these patients were clinically and radiologically stable. Anaplastic ODGs, however, showed an initial increase followed by the fall of minimum ADC in all the 5 cases (P = 0.00). Four of the five cases developed progressive disease subsequently. In all the 4 GBM cases, a consistent fall of minimum ADC values was observed (P = 0.00), and they all progressed in spite of RT. Conclusions:: The DWI-derived minimum ADC values are an important yet simple quantitative tool to assess the treatment response and disease progression before they are evident on conventional imaging during the follow-up of glial tumors.
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This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
