Possible use of ADC in detecting the glioma infiltration

High-grade gliomas are the most common primary brain tumors and their prognosis is highly unfavorable. MRI imaging is not only considered a gold standard in the diagnostic algorithm. The precise bordering of the tumor by using MRI is also essential during surgical tumor resection as well as for proper targeting of radiotherapy. The removal of the area of enhancement after contrast injection on MRI T1 weighted image is nowadays considered a state of the art technique during the surgical treatment. In our previous studies, we aimed to describe the glioma peritumoral brain zone after tumor removal and to correlate its histological features with MRI characteristics. We have proven that the tumor infiltration is present behind the border of post-contrast enhancement, mostly in the area described as perifocal edema (hyperintensity on T2 weighted image surrounding the tumor) and sometimes even in the area of a healthy-looking brain area according to MRI. Further, we focused on the diffusion-weighted image (DWI) with apparent diffusion coefficient (ADC) mapping as a quantitative imaging biomarker which reflects the degree of mean water diffusivity within tissues. As increased cellularity leads to restriction of water molecule diffusion within the tight extracellular space, ADC values could have a better ability to describe and delineate glioma infiltration rather than a structural T1 and T2 sequences on MRI. We found out that from the area of the tumor core (post-contrast enhancement) to periphery the ADC values first steeply increase until reaching the maximum, then stay stable usually forming a plateau and gradually decrease to normal values afterward. This happens with the simultaneous gradual decrease of cellularity, proliferation rate, and vascularisation in the same direction. That means ADC cannot be only in negative correlation to cellularity, as often claimed in the literature. In our further research, we would like to analyze the graph of ADC values more in detail and form a mathematical model. We are planning to make a retrospective correlation with histological characteristics of the tissue from the precisely aimed brain biopsy samples of the peritumoral brain tissue. Besides our two-dimensional analysis, we are also creating a 3D model of ADC values to analyze the whole spectrum among the peritumoral brain zone. Nonetheless, we will try to compare ADC characteristics of glioma peritumoral zone to different entities like brain metastases or brain abscess. Our method could improve the glioma delineation on MRI images. Furthermore, it could help to better differentiate lesions of different biological characters which could look very similar to conventional MRI imaging.