Implementation of the DW-MRI Calibrated with the Histological Data to Estimate the Tumor Cell Load and Heterogeneity

Abstract

Diffusion-Weighted Imaging (DWI) or Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is a key non-intrusive imaging procedure for the analysis of cancer and tumor treatment evaluation, based on Brownian movement of water molecules in tumor tissue. The formation of tumor makes the cells very tightly packed blocking the movement of cells in the molecule. Thus the tumor tissues compared to normal healthy tissues produce signals with less attenuation on isotropic maps. However, there is no possible evidence stating the relation between the Diffusion Weighted Data and the densities of cells.

To link the clinical cross-sectional data of low-resolution with the histological data of high-resolution, we have invented a digital image processing algithm, in order to assess the relation between the Diffusion Coefficient values (D value) and tumor cellularity obtained from Diffusion Weighted MRI Scan Images of Large cell carcinoma of the lung and the Endometrial papillary serous carcinoma (EPSC). Color de-convolution was performed followed by cell nuclei classification and division on the obtained histology pictures to examine the neighborhood and cell-type explicit densities.

In rundown, our outcomes show that tumor cell check i.e., number of cells influenced and non-influenced from disease and heterogeneity of the cells can be anticipated from DWI imaging information, which may open new gates to refine and manage the patient-explicit improvement of the treatment methods, customized analysis and treatment enhancement.