State-of-the-art Imaging Biomarkers
for Brain Oncology
QMENTA has amassed the most advanced and widely used imaging biomarkers on its platform to enable experts to measure the efficacy of treatments under trial or research in a single environment.
Imaging biomarkers are beneficial to quantify the characteristics of the blood flow & the volume of the tumor and to differentiate the tumor & non-tumor regions.
Contrast enhanced imaging
T1 weighted imaging pre-post contrast Delta T1 quantification differentiates perfused and non-perfused regions of tumor tissue and allows for monitoring of tumor changes in patients treated with anti-angiogenesis agents.(37, 38)
Perfusion imaging quantifies the characteristics of blood flow in tissues: Dynamic susceptibility contrast MRI quantifies relative cerebral blood volume. These quantitative maps offer information to predict tumor grade and analyze post-treatment changes for glioblastoma multiforme, meningioma, astrocytoma, and oligodendroglioma.(39,40)
Brain Tumor Volume Quantification
The QMENTA platform offers a multi-modal brain tumor segmentation tool yielding multi-compartmental volume quantification of gliomas, delineating the different tumoral tissues, enhancing regions, necrotic tissue, and edema, allowing for an automated and reproducible way to monitor tumor progression.
QMENTA has developed an automated quantification pipeline to measure alteration in the magnetic properties of tissue due to gadolinium retention by combining automated segmentation with quantitative maps. This enables analysis of gadolinium retention over the course of time in patients undergoing contrast-enhanced imaging.
37. Warmuth, Carsten, Matthias Gunther, and Claus Zimmer. "Quantification of blood flow in brain tumors: comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging." Radiology 228.2 (2003): 523-532.
38. Jackson, Alan, and David L. Buckley. Dynamic contrast-enhanced magnetic resonance imaging in oncology. Ed. Geoffrey JM Parker. Berlin: Springer, 2005.
39. Çoban, G., et al. "Prognostic value of dynamic susceptibility contrast-enhanced and diffusion-weighted MR imaging in patients with glioblastomas." American Journal of Neuroradiology (2015).
40. Lee, B., et al. "Clinical Value of Vascular Permeability Estimates Using Dynamic Susceptibility Contrast MRI: Improved Diagnostic Performance in Distinguishing Hypervascular Primary CNS Lymphoma from Glioblastoma." American Journal of Neuroradiology (2018).