Evidence map›Paper›PMID 36844110›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering

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 and 1 more

Open access · greenAbstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Machine learning applications in placenta accreta spectrum disorders.European journal of obstetrics & gynecology and reproductive biology: X · 2025
    Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Ka'Toria LeitchDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX.
Maysam ShahediDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX.
James D DormerDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX.
Quyen N DoDepartment of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX.
Yin XiDepartment of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX.
Matthew A LewisDepartment of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX.
Christina L HerreraDepartment of Obstetrics and Gynecology, The University of Texas Southwestern Medical Center, Dallas, TX.
Catherine Y SpongDepartment of Obstetrics and Gynecology, The University of Texas Southwestern Medical Center, Dallas, TX.
Ananth J MadhuranthakamDepartment of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX.
Diane M TwicklerDepartment of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX.
Baowei FeiDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX.
The University of Texas Southwestern Medical Center · USThe University of Texas at Dallas · US

Funding

Image-guided Intravascular Robotic System for Mitral Valve Repair and ImplantsR01HL140325 · NHLBI · GEORGIA INSTITUTE OF TECHNOLOGY · PI DESAI, JAYDEV P., FEI, BAOWEI · 2018 to 2021
$3.0M
ACADEMIC-INDUSTRIAL PARTNERSHIP FOR TRANSLATION OF PET/TRUS GUIDED INTERVENTIONR01CA204254 · NCI · UNIVERSITY OF TEXAS DALLAS · PI FEI, BAOWEI · 2017 to 2021
$2.0M
MOLECULAR IMAGING DIRECTED, 3D ULTRASOUND-GUIDED, BIOPSY SYSTEMR01CA156775 · NCI · UNIVERSITY OF TEXAS DALLAS · PI FEI, BAOWEI · 2011 to 2016
$1.7M
Quantitative magnetic resonance imaging and automated textural radiomics for assessment of human placenta accreta spectrumK25HD104004 · NICHD · UT SOUTHWESTERN MEDICAL CENTER · PI DO, QUYEN NGOC · 2020 to 2024
$570k
STAN-CT: Standardization and Normalization of CT images for Lung Cancer PatientsR21CA231911 · NCI · UNIVERSITY OF KENTUCKY · PI CHEN, JIN, FEI, BAOWEI · 2019 to 2020
$389k
NCI NIH HHS R01 CA156775NCI NIH HHS R01 CA204254NCI NIH HHS R21 CA231911NHLBI NIH HHS R01 HL140325NICHD NIH HHS K25 HD104004
6 · The paper itself

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.

Indexed as

hysterectomymachine learningmagnetic resonance imaging (MRI)Placenta accreta spectrum (PAS)pregnantradiomicsuterus

Identifiers

PMID36844110
PMCPMC9956938
OpenAlexW4220973488

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.