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.
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.
Contrast enhanced imaging – IB Delta Suite™
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 – IB Neuro™
IB Neuro™ v2.0 automatically analyzes dynamically acquired MR datasets and generates parametric perfusion maps quantifying changes in contrast over time. Advancements in IB Neuro are designed to fit routine clinical and research workflow and address advanced clinical and research needs.
IB DCE™ v2.0 software analyzes conventional T1 weighted images and generates an array of relevant perfusion and permeability parameters. Employing the extended Tofts, Tofts, and Patlak models, contrast agent permeability analysis is now intuitive and designed with the same user interface as other IB software products.
IB DiffusionTM v2.0 is software that analyzes MR diffusion-weighted images (DWI) and generates Apparent Diffusion Coefficient (ADC) maps. ADC values have been shown to be useful in the initial diagnosis and treatment monitoring of all solid tumors.
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).