Intra-voxel incoherent motion (IVIM) analysis of fetal lungs Diffusion-Weighted MRI (DWI) data shows potential in providing quantitative imaging bio-markers that reflect, indirectly, diffusion and pseudo-diffusion for non-invasive fetal lung maturation assessment. However, long acquisition times, due to the large number of different “b-value” images required for IVIM analysis, precluded clinical feasibility. We introduce SUPER-IVIM-DC a deep-neural-networks (DNN) approach which couples supervised loss with a data-consistency term to enable IVIM analysis of DWI data acquired with a limited number of b-values. We demonstrated the added-value of SUPER-IVIM-DC over both classical and recent DNN approaches for IVIM analysis through numerical simulations, healthy volunteer study, and IVIM analysis of fetal lung maturation from fetal DWI data. Our numerical simulations and healthy volunteer study show that SUPER-IVIM-DC estimates of the IVIM model parameters from limited DWI data had lower normalized root mean-squared error compared to previous DNN-based approaches. Further, SUPER-IVIM-DC estimates of the pseudo-diffusion fraction parameter from limited DWI data of fetal lungs correlate better with gestational age compared to both to classical and DNN-based approaches (0.555 vs. 0.463 and 0.310). SUPER-IVIM-DC has the potential to reduce the long acquisition times associated with IVIM analysis of DWI data and to provide clinically feasible bio-markers for non-invasive fetal lung maturity assessment.
|Title of host publication||Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 - 25th International Conference, Proceedings|
|Editors||Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||10|
|State||Published - 2022|
|Event||25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022 - Singapore, Singapore|
Duration: 18 Sep 2022 → 22 Sep 2022
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022|
|Period||18/09/22 → 22/09/22|
Bibliographical noteFunding Information:
Keywords: Fetal DWI · Intra-voxel incoherent motion · Deep-neural-networks This research was supported in part by a grant from the United States-Israel Binational Science Foundation (BSF), Jerusalem, Israel.
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Fetal DWI
- Intra-voxel incoherent motion
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science (all)