Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features

Ka'Toria Leitch; Maysam Shahedi; James D. Dormer; Quyen N. Do; Yin Xi; Matthew A. Lewis; Christina L. Herrera; Catherine Y. Spong; Ananth J. Madhuranthakam; Diane M. Twickler; Baowei Fei

doi:10.1117/12.2611587

Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features

Ka'Toria Leitch, Maysam Shahedi, James D. Dormer, Quyen N. Do, Yin Xi, Matthew A. Lewis, Christina L. Herrera, Catherine Y. Spong, Ananth J. Madhuranthakam, Diane M. Twickler, Baowei Fei

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

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.

Original language	English (US)
Title of host publication	Medical Imaging 2022
Subtitle of host publication	Computer-Aided Diagnosis
Editors	Karen Drukker, Khan M. Iftekharuddin
Publisher	SPIE
ISBN (Electronic)	9781510649415
DOIs	https://doi.org/10.1117/12.2611587
State	Published - 2022
Event	Medical Imaging 2022: Computer-Aided Diagnosis - Virtual, Online Duration: Mar 21 2022 → Mar 27 2022

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	12033
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2022: Computer-Aided Diagnosis
City	Virtual, Online
Period	3/21/22 → 3/27/22

Keywords

Hysterectomy
Machine learning
Magnetic resonance imaging (MRI)
Placenta accreta spectrum (PAS)
Pregnant
Radiomics
Uterus

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Biomaterials
Radiology Nuclear Medicine and imaging

Access to Document

10.1117/12.2611587

Cite this

Leitch, KT., Shahedi, M., Dormer, J. D., Do, Q. N., Xi, Y., Lewis, M. A., Herrera, C. L., Spong, C. Y., Madhuranthakam, A. J., Twickler, D. M., & Fei, B. (2022). Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features. In K. Drukker, & K. M. Iftekharuddin (Eds.), Medical Imaging 2022: Computer-Aided Diagnosis Article 120331I (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 12033). SPIE. https://doi.org/10.1117/12.2611587

Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features. / Leitch, Ka'Toria; Shahedi, Maysam; Dormer, James D. et al.
Medical Imaging 2022: Computer-Aided Diagnosis. ed. / Karen Drukker; Khan M. Iftekharuddin. SPIE, 2022. 120331I (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 12033).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Leitch, KT, Shahedi, M, Dormer, JD, Do, QN , Xi, Y , Lewis, MA , Herrera, CL , Spong, CY, Madhuranthakam, AJ, Twickler, DM & Fei, B 2022, Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features. in K Drukker & KM Iftekharuddin (eds), Medical Imaging 2022: Computer-Aided Diagnosis., 120331I, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 12033, SPIE, Medical Imaging 2022: Computer-Aided Diagnosis, Virtual, Online, 3/21/22. https://doi.org/10.1117/12.2611587

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title = "Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features",

abstract = "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.",

keywords = "Hysterectomy, Machine learning, Magnetic resonance imaging (MRI), Placenta accreta spectrum (PAS), Pregnant, Radiomics, Uterus",

author = "Ka'Toria Leitch and Maysam Shahedi and Dormer, {James D.} and Do, {Quyen N.} and Yin Xi and Lewis, {Matthew A.} and Herrera, {Christina L.} and Spong, {Catherine Y.} and Madhuranthakam, {Ananth J.} and Twickler, {Diane M.} and Baowei Fei",

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year = "2022",

doi = "10.1117/12.2611587",

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AU - Lewis, Matthew A.

AU - Herrera, Christina L.

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AU - Fei, Baowei

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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.

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ER -

Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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