Principal Process Analysis of dynamic GlucoCEST MRI data

TL;DR

This paper applies principal process analysis to dynamic GlucoCEST MRI data to better understand tumor glucose metabolism by analyzing the underlying biological processes.

Contribution

It introduces a process analysis method to interpret complex glucose metabolism dynamics in MRI data, enhancing understanding of tumor biology.

Findings

Identifies key metabolic processes influencing GlucoCEST signals

Provides a new framework for analyzing MRI-based glucose metabolism data

Improves interpretation of tumor versus normal tissue metabolism

Abstract

GlucoCEST is an MRI contrast enhancement technique sensitive to the concentration of sugar in the tissue. Because of a differencein metabolism, it is thought that tumors consume more sugar than normal tissue. However, glucose metabolism is complex and depends onmany processes, which are all important to understand the origin of the measured signal. To achieve this goal we apply here a process analysismethod to a deterministic system describing the metabolism of glucose in the tissue.