Cargando…
MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum
Background: Gravid patients at high risk with placenta accreta spectrum (PAS) face life-threatening risk at delivery. Intraoperative risk assessment for patients is currently insufficient. We aimed to develop an assessment system of intraoperative risks through MRI-based radiomics. Methods: A total...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870740/ https://www.ncbi.nlm.nih.gov/pubmed/35204575 http://dx.doi.org/10.3390/diagnostics12020485 |
_version_ | 1784656830434115584 |
---|---|
author | Chu, Caiting Liu, Ming Zhang, Yuzhen Zhao, Shuhui Ge, Yaqiong Li, Wenhua Gao, Chengjin |
author_facet | Chu, Caiting Liu, Ming Zhang, Yuzhen Zhao, Shuhui Ge, Yaqiong Li, Wenhua Gao, Chengjin |
author_sort | Chu, Caiting |
collection | PubMed |
description | Background: Gravid patients at high risk with placenta accreta spectrum (PAS) face life-threatening risk at delivery. Intraoperative risk assessment for patients is currently insufficient. We aimed to develop an assessment system of intraoperative risks through MRI-based radiomics. Methods: A total of 131 patients enrolled were randomly grouped according to a ratio of 7:3. Clinical data were analyzed retrospectively. Radiomic features were extracted from sagittal Fast Imaging Employing State-sate Acquisition images. Univariate and multivariate regression analyses were performed to build models using R software. A receiver operating characteristic curve and decision curve analysis (DCA) were performed to determine the predictive performance of models. Results: Six radiomic features and two clinical variables were used to construct the combined model for selection of removal protocols of the placenta, with an area under the curve (AUC) of 0.90 and 0.91 in the training and test cohorts, respectively. Nine radiomic features and two clinical variables were obtained to establish the combined model for prediction of intraoperative blood loss, with an AUC of 0.90 and 0.88 in the both cohorts, respectively. The DCA confirmed the clinical utility of the combined model. Conclusion: The analysis of combined MRI-based radiomics with clinics could be clinically beneficial for patients. |
format | Online Article Text |
id | pubmed-8870740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88707402022-02-25 MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum Chu, Caiting Liu, Ming Zhang, Yuzhen Zhao, Shuhui Ge, Yaqiong Li, Wenhua Gao, Chengjin Diagnostics (Basel) Article Background: Gravid patients at high risk with placenta accreta spectrum (PAS) face life-threatening risk at delivery. Intraoperative risk assessment for patients is currently insufficient. We aimed to develop an assessment system of intraoperative risks through MRI-based radiomics. Methods: A total of 131 patients enrolled were randomly grouped according to a ratio of 7:3. Clinical data were analyzed retrospectively. Radiomic features were extracted from sagittal Fast Imaging Employing State-sate Acquisition images. Univariate and multivariate regression analyses were performed to build models using R software. A receiver operating characteristic curve and decision curve analysis (DCA) were performed to determine the predictive performance of models. Results: Six radiomic features and two clinical variables were used to construct the combined model for selection of removal protocols of the placenta, with an area under the curve (AUC) of 0.90 and 0.91 in the training and test cohorts, respectively. Nine radiomic features and two clinical variables were obtained to establish the combined model for prediction of intraoperative blood loss, with an AUC of 0.90 and 0.88 in the both cohorts, respectively. The DCA confirmed the clinical utility of the combined model. Conclusion: The analysis of combined MRI-based radiomics with clinics could be clinically beneficial for patients. MDPI 2022-02-14 /pmc/articles/PMC8870740/ /pubmed/35204575 http://dx.doi.org/10.3390/diagnostics12020485 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chu, Caiting Liu, Ming Zhang, Yuzhen Zhao, Shuhui Ge, Yaqiong Li, Wenhua Gao, Chengjin MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum |
title | MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum |
title_full | MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum |
title_fullStr | MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum |
title_full_unstemmed | MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum |
title_short | MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum |
title_sort | mri-based radiomics analysis for intraoperative risk assessment in gravid patients at high risk with placenta accreta spectrum |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870740/ https://www.ncbi.nlm.nih.gov/pubmed/35204575 http://dx.doi.org/10.3390/diagnostics12020485 |
work_keys_str_mv | AT chucaiting mribasedradiomicsanalysisforintraoperativeriskassessmentingravidpatientsathighriskwithplacentaaccretaspectrum AT liuming mribasedradiomicsanalysisforintraoperativeriskassessmentingravidpatientsathighriskwithplacentaaccretaspectrum AT zhangyuzhen mribasedradiomicsanalysisforintraoperativeriskassessmentingravidpatientsathighriskwithplacentaaccretaspectrum AT zhaoshuhui mribasedradiomicsanalysisforintraoperativeriskassessmentingravidpatientsathighriskwithplacentaaccretaspectrum AT geyaqiong mribasedradiomicsanalysisforintraoperativeriskassessmentingravidpatientsathighriskwithplacentaaccretaspectrum AT liwenhua mribasedradiomicsanalysisforintraoperativeriskassessmentingravidpatientsathighriskwithplacentaaccretaspectrum AT gaochengjin mribasedradiomicsanalysisforintraoperativeriskassessmentingravidpatientsathighriskwithplacentaaccretaspectrum |