A simulation study of cell size and volume fraction mapping for tissue with two underlying cell populations using diffusion‐weighted MRI. Issue 2 (28th February 2021)

• Record Type: Journal Article
• Authors: Xing, Shu; Levesque, Ives R.
• Is Part Of: Magnetic resonance in medicine. Volume 86:Issue 2(2021)
• Page Start: 1029
• Page End: 1044
• Publication Date: 2021-02-28
• Subjects: diffusion MRI -- microstructure -- modelling -- tumor; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.28694
• Languages: English
• ISSNs: 0740-3194

Abstract

Abstract : Purpose: To propose a method for voxel‐wise estimation of cell radii and volume fractions of two cell populations when they coexist in the same MR voxel using the combination of diffusion‐weighted MRI and microstructural modeling. Method: Microstructure models were investigated using diffusion data simulated with the matrix method for a range of microstructures mimicking tumor tissue with two cell populations, using acquisition parameters available on preclinical scanners. The effect of noise was investigated for a subset of these microstructures. The accuracy and precision of the estimated radii and volume fractions for large and small cells R l, R s, v i n, l, v i n, s were evaluated by comparing the estimates to their true values. The stability of model fitting was characterized by the percentage of accepted fits. Results: The estimation accuracy and precision, and thus the ability to robustly distinguish the two cell populations, depended on the microstructural properties and SNR. For a SNR of 50, a minimum difference of 3 μm between the radius of the large and small cell populations was required for differentiation. Proposed modifications to the two cell population microstructure model, including constrained fits, improved the stability of fits. Conclusions: This proof‐of‐concept study proposed a diffusion MRI‐based method for voxel‐wise estimation of cell radii and volume fractions of two cell populations when they coexist in the same MR voxel. The ability to reliably characterize tissue with two cell populations opens exciting avenues of potential applications in both tumor diagnosis and treatment monitoring.