Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
360-05-008 ISMRM Abstract

Development and Validation of a Multichannel 2.5D Deep Learning Model for Predicting Postpartum Hemorrhage from Placental MRI

Primary: Body - Placenta
Secondary: Analysis Methods - Classification and Prediction
360-05-008 · Acquisition, Reconstruction, and Analysis · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row A
Keywords: Deep learning MRI Postpartum Hemorrhage Placental
Accepted
Lingsong Meng 1,2,3, Xiaoan Zhang2, Xin Zhao2, Lin Lu2, Wenzhe Zhang2, Xiang Meng1, Fuming Shao3
1Department of Medical Technology, Shangqiu Medical College, Shangqiu, China
2Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
3Department of Magnetic Resonance Imaging, The Second Affiliated Hospital of Shangqiu Medical College, Shangqiu, China
Presenting Author: Lingsong Meng

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. 1 Chandraharan E, Krishna A. Diagnosis and management of postpartum haemorrhage. BMJ. 2017;358:j3875. doi:10.1136/bmj.j3875 [doi]
2. 2 Shamshirsaz AA, Fox KA, Salmanian B, et al. Maternal morbidity in patients with morbidly adherent placenta treated with and without a standardized multidisciplinary approach. Am J Obstet Gynecol. 2015;212(2):218.e1-218.e2189. doi:10.1016/j.ajog.2014.08.019 [doi]
3. 3 Liu CN, Yu FB, Xu YZ, et al. Prevalence and risk factors of severe postpartum hemorrhage: a retrospective cohort study. BMC Pregnancy Childbirth. 2021;21(1):332. doi:10.1186/s12884-021-03818-1 [doi]
4. 4 Bulas D, Egloff A. Benefits and risks of MRI in pregnancy. Semin Perinatol. 2013;37(5):301-304. doi:10.1053/j.semperi.2013.06.005 [doi]
5. 5 Akazawa M, Hashimoto K. Prediction of hemorrhage in placenta previa: Radiomics analysis of pelvic MRI images. Eur J Obstet Gynecol Reprod Biol. 2024;299:37-42. doi:10.1016/j.ejogrb.2024.05.033 [doi]
6. 6 Wu Q, Yao K, Liu Z, et al. Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study. EBioMedicine. 2019;50:355-365. doi:10.1016/j.ebiom.2019.11.010 [doi]
7. 7 Chi Z, Zhang S, Wang Y, Yang L, Yang Y, Li X. Research of the assessable method of postpartum hemorrhage. Technol Health Care. 2016;24 Suppl 2:S465-S469. doi:10.3233/THC-161169 [doi]
8. 8 Kim JW, Lee YK, Chin JH, et al. Development of a scoring system to predict massive postpartum transfusion in placenta previa totalis. J Anesth. 2017;31(4):593-600. doi:10.1007/s00540-017-2365-8 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/360-05-008