Overestimation of the Apparent Diffusion Coefficient in Diffusion-Weighted Imaging Due to Residual Fat Signal and Out-of-Phase Conditions

Read full text
Authors: Maher Dhanani, Dominika Skwierawska, Tristan Anselm Kuder, Sabine Ohlmeyer, Michael Uder, Sebastian Bickelhaupt, Frederik Bernd Laun
Cited by: 0

Abstract

Background/Objectives: Diffusion-weighted imaging (DWI) is a magnetic resonance technique used to map the apparent diffusion coefficient (ADC) of water in human tissue. ADC assessment plays a central role in clinical diagnostics, as malignant tissues typically exhibit reduced water mobility and, thus, lower ADC values. Accurately measuring the ADC requires effective fat suppression to prevent contamination from the residual fat signal, which is commonly believed to cause ADC underestimation. This study aimed to demonstrate that ADC overestimation may occur as well. Methods: Our theoretical analysis shows that out-of-phase conditions between fat and water signals lead to ADC overestimations. We performed demonstration experiments on fat–water phantoms and the breasts of 10 healthy female volunteers. In particular, we considered three out-of-phase conditions: First and second, short-time inversion recovery (STIR) fat suppression with incorrect inversion time and incorrect flip angle, respectively. Third, phase differences due to spectral fat saturation. The ADC values were assessed in regions of interest (ROIs) that included both water and residual fat signals. Results: In the phantoms and the volunteer data, ROIs containing both fat and water signals consistently exhibited lower ADC values under in-phase conditions and higher ADC values under out-of-phase conditions. Conclusions: We demonstrated that out-of-phase conditions can result in ADC overestimation in the presence of residual fat signals, potentially resulting in false-negative classifications where malignant lesions are misinterpreted as benign due to an elevated ADC. Out-of-phase fat and water signals might also reduce lesion conspicuity in high b-value images, potentially masking clinically relevant findings.

Fields of Study & Subjects

Advanced MRI Techniques and Applications MRI in cancer diagnosis Advanced Neuroimaging Techniques and Applications

Publication details

Journal / source
Tomography
Volume
12
Issue
1
Pages
11–11
Publication date
16 January 2026
Language
EN