Influence of co-registration on lesion characterization in diffusion-weighted breast MRI

Read full text
Authors: Luise Brock, Andrzej Liebert, Hannes Schreiter, Dominika Skwierawska, Chris M. Ehring, Jessica S. Eberle, Shirin Heidarikahkesh, Frederik Bernd Laun, Michael Uder, Lorenz A. Kapsner, Johannes Lach, Evelyn Wenkel
+4 more Sabine Ohlmeyer, Dominique Hadler, Florian Knöll, Sebastian Bickelhaupt
Cited by: 0
References: 40

Abstract

OBJECTIVE: To evaluate if co-registering Diffusion-Weighted Imaging (DWI) before generating Apparent Diffusion Coefficient (ADC) maps can improve differentiating benign and malignant breast lesions in MRI based on the A6702 thresholds. MATERIALS AND METHODS: This IRB-approved study involved an in-house dataset and the publicly available ACRIN-6698 dataset, both including multi b-value DWI. In phase one, 16 ANTs library-based co-registration methods were evaluated on a subset of n = 138 cases from our in-house cohort. The quantitative assessment included mean ADC values of manually segmented lesions (diagnostic metrics using individual and A6702-defined thresholds) and coefficient of Variation. In the second phase, the best-performing methods were tested for generalizability on an unseen set of 40 cases (20 from in-house and 20 from external dataset). Three blinded readers segmented lesions on co-registered and non-co-registered ADC maps. Agreement and consistency were evaluated via Bland-Altman, segmentation distance, and intraclass correlation coefficient. RESULTS: as reference (b750-Rigid) improved accuracy of both optimal/conservative A6702 trial thresholds with sensitivity/specificity increasing from 93%/10% to 97%/30% and 100%/30% respectively. Mean ADC values were not significantly different after co-registration (p > 0.05). DISCUSSION: Co-registration of DWI images before ADC map generation, particularly using b750-Rigid registration, seems promising for improving lesion classification in breast MRI. Further validation is warranted.

Fields of Study & Subjects

MRI in cancer diagnosis Breast Lesions and Carcinomas Medical Image Segmentation Techniques

Publication details

Journal / source
Magnetic Resonance Materials in Physics Biology and Medicine
Volume
39
Issue
4
Pages
645–662
Publication date
31 January 2026
Language
EN