In this section
@article{Tänzer:2026:10.1016/j.media.2026.104115,
author = {Tänzer, M and Lim, EJ and Qiu, HH and Munoz, C and Scott, A and Pennell, D and Ferreira, P and Rueckert, D and Yang, G and Nielles-Vallespin, S},
doi = {10.1016/j.media.2026.104115},
journal = {Med Image Anal},
title = {Simultaneous multi-slice Cardiac Diffusion Tensor Imaging with variable CAIPIRINHA shifts and artefact-aware AI.},
url = {http://dx.doi.org/10.1016/j.media.2026.104115},
volume = {112},
year = {2026}
}
TY - JOUR
AB - Cardiac Diffusion Tensor Imaging (cDTI) provides unique insights into myocardial microstructure in-vivo but requires averaging multiple repetitions for adequate signal quality, leading to prohibitively long acquisition times. Standard acceleration strategies, such as reducing repetitions and employing simultaneous multi-slice (SMS) imaging, are limited by low signal-to-noise ratio (SNR) and inter-slice leakage artefacts, respectively. We introduce ORCAS, a unified framework that synergistically combines a novel variable CAIPIRINHA acquisition with an artefact-aware AI reconstruction to overcome these challenges. The variable CAIPIRINHA scheme decoheres SMS artefacts across repetitions, while our dual-domain deep learning model simultaneously suppresses these artefacts and combats the low SNR from fewer repetitions. The model is guided by patient-specific single-band auxiliary data to preserve anatomical fidelity. Validated on ex-vivo hearts with and without anomalies, ORCAS achieves an over 18-fold acceleration by combining these strategies, reducing a whole-heart scan from over two hours to under 7 min. This is accomplished while reducing errors in key biomarkers, such as Fractional Anisotropy, by up to 64%. The framework preserves essential microstructural properties and the delineation of abnormalities, representing a significant step towards the clinical translation of whole-heart cDTI.
AU - Tänzer,M
AU - Lim,EJ
AU - Qiu,HH
AU - Munoz,C
AU - Scott,A
AU - Pennell,D
AU - Ferreira,P
AU - Rueckert,D
AU - Yang,G
AU - Nielles-Vallespin,S
DO - 10.1016/j.media.2026.104115
PY - 2026///
TI - Simultaneous multi-slice Cardiac Diffusion Tensor Imaging with variable CAIPIRINHA shifts and artefact-aware AI.
T2 - Med Image Anal
UR - http://dx.doi.org/10.1016/j.media.2026.104115
UR - https://www.ncbi.nlm.nih.gov/pubmed/42155271
VL - 112
ER -
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