TY - GEN
T1 - Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features
AU - Leitch, Ka'Toria
AU - Shahedi, Maysam
AU - Dormer, James D.
AU - Do, Quyen N.
AU - Xi, Yin
AU - Lewis, Matthew A.
AU - Herrera, Christina L.
AU - Spong, Catherine Y.
AU - Madhuranthakam, Ananth J.
AU - Twickler, Diane M.
AU - Fei, Baowei
N1 - Funding Information:
This research was supported in part by the U.S. National Institutes of Health (NIH) grants (R01CA156775, R01CA204254, R01HL140325, and R21CA231911) and by the Cancer Prevention and Research Institute of Texas (CPRIT) grant RP190588.
Publisher Copyright:
© 2022 SPIE.
PY - 2022
Y1 - 2022
N2 - In women with placenta accreta spectrum (PAS), patient management may involve cesarean hysterectomy at delivery. Magnetic resonance imaging (MRI) has been used for further evaluation of PAS and surgical planning. This work tackles two prediction problems: predicting presence of PAS and predicting hysterectomy using MR images of pregnant patients. First, we extracted approximately 2,500 radiomic features from MR images with two regions of interest: The placenta and the uterus. In addition to analyzing two regions of interest, we dilated the placenta and uterus masks by 5, 10, 15, and 20 mm to gain insights from the myometrium, where the uterus and placenta overlap in the case of PAS. This study cohort includes 241 pregnant women. Of these women, 89 underwent hysterectomy while 152 did not; 141 with suspected PAS, and 100 without suspected PAS. We obtained an accuracy of 0.88 for predicting hysterectomy and an accuracy of 0.92 for classifying suspected PAS. The radiomic analysis tool is further validated, it can be useful for aiding clinicians in decision making on the care of pregnant women.
AB - In women with placenta accreta spectrum (PAS), patient management may involve cesarean hysterectomy at delivery. Magnetic resonance imaging (MRI) has been used for further evaluation of PAS and surgical planning. This work tackles two prediction problems: predicting presence of PAS and predicting hysterectomy using MR images of pregnant patients. First, we extracted approximately 2,500 radiomic features from MR images with two regions of interest: The placenta and the uterus. In addition to analyzing two regions of interest, we dilated the placenta and uterus masks by 5, 10, 15, and 20 mm to gain insights from the myometrium, where the uterus and placenta overlap in the case of PAS. This study cohort includes 241 pregnant women. Of these women, 89 underwent hysterectomy while 152 did not; 141 with suspected PAS, and 100 without suspected PAS. We obtained an accuracy of 0.88 for predicting hysterectomy and an accuracy of 0.92 for classifying suspected PAS. The radiomic analysis tool is further validated, it can be useful for aiding clinicians in decision making on the care of pregnant women.
KW - Hysterectomy
KW - Machine learning
KW - Magnetic resonance imaging (MRI)
KW - Placenta accreta spectrum (PAS)
KW - Pregnant
KW - Radiomics
KW - Uterus
UR - http://www.scopus.com/inward/record.url?scp=85132799922&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85132799922&partnerID=8YFLogxK
U2 - 10.1117/12.2611587
DO - 10.1117/12.2611587
M3 - Conference contribution
C2 - 36844110
AN - SCOPUS:85132799922
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2022
A2 - Drukker, Karen
A2 - Iftekharuddin, Khan M.
PB - SPIE
T2 - Medical Imaging 2022: Computer-Aided Diagnosis
Y2 - 21 March 2022 through 27 March 2022
ER -