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Meyers ML, Mirsky DM. MR Imaging of Placenta Accreta Spectrum: A Comprehensive Literature Review of the Most Recent Advancements. Magn Reson Imaging Clin N Am 2024; 32:573-584. [PMID: 38944441 DOI: 10.1016/j.mric.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2024]
Abstract
This article delves into the latest MR imaging developments dedicated to diagnosing placenta accreta spectrum (PAS). PAS, characterized by abnormal placental adherence to the uterine wall, is of paramount concern owing to its association with maternal morbidity and mortality, particularly in high-risk pregnancies featuring placenta previa and prior cesarean sections. Although ultrasound (US) remains the primary screening modality, limitations have prompted heightened emphasis on MR imaging. This review underscores the utility of quantitative MR imaging, especially where US findings prove inconclusive or when maternal body habitus poses challenges, acknowledging, however, that interpreting placenta MR imaging demands specialized training for radiologists.
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Affiliation(s)
- Mariana L Meyers
- Department of Radiology, Pediatric Section, University of Colorado School of Medicine; Children's Hospital Colorado.
| | - David M Mirsky
- Department of Radiology, Pediatric Section, University of Colorado School of Medicine; Children's Hospital Colorado
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Yu H, Yin H, Zhang H, Zhang J, Yue Y, Lu Y. Placental T2WI MRI-based radiomics-clinical nomogram predicts suspicious placenta accreta spectrum in patients with placenta previa. BMC Med Imaging 2024; 24:146. [PMID: 38872133 PMCID: PMC11177524 DOI: 10.1186/s12880-024-01328-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 06/07/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND The incidence of placenta accreta spectrum (PAS) increases in women with placenta previa (PP). Many radiologists sometimes cannot completely and accurately diagnose PAS through the simple visual feature analysis of images, which can affect later treatment decisions. The study is to develop a T2WI MRI-based radiomics-clinical nomogram and evaluate its performance for non-invasive prediction of suspicious PAS in patients with PP. METHODS The preoperative MR images and related clinical data of 371 patients with PP were retrospectively collected from our hospital, and the intraoperative examination results were used as the reference standard of the PAS. Radiomics features were extracted from sagittal T2WI MR images and further selected by LASSO regression analysis. The radiomics score (Radscore) was calculated with logistic regression (LR) classifier. A nomogram integrating Radscore and selected clinical factors was also developed. The model performance was assessed with respect to discrimination, calibration and clinical usefulness. RESULTS A total of 6 radiomics features and 1 clinical factor were selected for model construction. The Radscore was significantly associated with suspicious PAS in both the training (p < 0.001) and validation (p < 0.001) datasets. The AUC of the nomogram was also higher than that of the Radscore in the training dataset (0.891 vs. 0.803, p < 0.001) and validation dataset (0.897 vs. 0.780, p < 0.001), respectively. The calibration was good, and the decision curve analysis demonstrated the nomogram had higher net benefit than the Radscore. CONCLUSIONS The T2WI MRI-based radiomics-clinical nomogram showed favorable diagnostic performance for predicting PAS in patients with PP, which could potentially facilitate the obstetricians for making clinical decisions.
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Affiliation(s)
- Hongchang Yu
- Department of Radiology, Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 26 Daoqian Street, Gusu District, Suzhou, China
| | - Hongkun Yin
- Infervision Medical Technology Co., Ltd, Beijing, China
| | - Huiling Zhang
- Infervision Medical Technology Co., Ltd, Beijing, China
| | - Jibin Zhang
- Department of Radiology, Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 26 Daoqian Street, Gusu District, Suzhou, China
| | - Yongfei Yue
- Department of Obstetrics and Gynecology, Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 26 Daoqian Street, Gusu District, Suzhou, China.
| | - Yanli Lu
- Department of Radiology, Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 26 Daoqian Street, Gusu District, Suzhou, China.
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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. [PMID: 38830301 DOI: 10.1016/j.ejogrb.2024.05.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 05/20/2024] [Accepted: 05/25/2024] [Indexed: 06/05/2024]
Abstract
INTRODUCTION Prediction of intraoperative massive hemorrhage is still challenging in placenta previa. Radiomics analysis has been investigated as a new evaluation method for analyzing medical images. We used radiomics analysis on placental magnetic resonance imaging (MRI) images to predict intraoperative hemorrhage in placenta previa. METHODS We used the sagittal MRI T2-weighted sequence in placenta previa. Using the rectangular region from the uterine os to the anterior wall, we extracted 97 radiomics features. We also collected patient demographics and blood test data as clinical variables. Combining these radiomics features and clinical variables, logistic regression models with a stepwise method were built to predict the risk of hemorrhage, defined as blood loss of > 2000 ml. We evaluated the prediction performance of the models using accuracy and area under the curve (AUC), also analyzing the important variables for the prediction by stepwise methods. RESULTS We enrolled a total of 63 placenta previa cases including 30 hemorrhage cases from two institutes. The model combining clinical variables and radiomics features showed the best prediction performance with an accuracy of 0.70 and an AUC of 0.69 in the internal validation data, and accuracy of 0.41 and an AUC of 0.70 in the external validation data, compared with human experts (accuracy of 0.62). Regarding variable selection, two radiomics features. 'original_glrlm_LowGrayLevelRunEmphasis,' and 'diagnostics_Image-original_Minimum,' were important predictors for hemorrhage by the stepwise method. DISCUSSION Radiomics features based on MRI could be used as effective predictive variables for hemorrhage in placenta previa. Radiomics analysis of placental imaging could lead to further analysis of quantitative variables related to obstetric diseases.
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Affiliation(s)
- Munetoshi Akazawa
- Department of Obstetrics and Gynecology, Tokyo Women's Medical University Adachi Medical Center, Adachi‑ku, Kohoku 2‑1‑10, Tokyo, Japan.
| | - Kazunori Hashimoto
- Department of Obstetrics and Gynecology, Tokyo Women's Medical University Adachi Medical Center, Adachi‑ku, Kohoku 2‑1‑10, Tokyo, Japan
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Liu Q, Zhou W, Yan Z, Li D, Lou T, Yuan Y, Rong P, Feng Z. Development and validation of MRI-based scoring models for predicting placental invasiveness in high-risk women for placenta accreta spectrum. Eur Radiol 2024; 34:957-969. [PMID: 37589907 DOI: 10.1007/s00330-023-10058-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/12/2023] [Accepted: 06/26/2023] [Indexed: 08/18/2023]
Abstract
OBJECTIVES To develop and validate MRI-based scoring models for predicting placenta accreta spectrum (PAS) invasiveness. MATERIALS AND METHODS This retrospective study comprised a derivation cohort and a validation cohort. The derivation cohort came from a systematic review of published studies evaluating the diagnostic performance of MRI signs for PAS and/or placenta percreta in high-risk women. The significant signs were identified and used to develop prediction models for PAS and placenta percreta. Between 2016 and 2021, consecutive high-risk pregnant women for PAS who underwent placental MRI constituted the validation cohort. Two radiologists independently evaluated the MRI signs. The reference standard was intraoperative and pathologic findings. The predictive ability of MRI-based models was evaluated using the area under the curve (AUC). RESULTS The derivation cohort included 26 studies involving 2568 women and the validation cohort consisted of 294 women with PAS diagnosed in 258 women (88%). Quantitative meta-analysis revealed that T2-dark bands, placental/uterine bulge, loss of T2 hypointense interface, bladder wall interruption, placental heterogeneity, and abnormal intraplacental vascularity were associated with both PAS and placenta percreta, and myometrial thinning and focal exophytic mass were exclusively associated with PAS. The PAS model was validated with an AUC of 0.90 (95% CI: 0.86, 0.93) for predicting PAS and 0.85 (95% CI: 0.79, 0.90) for adverse peripartum outcome; the placenta percreta model showed an AUC of 0.92 (95% CI: 0.86, 0.98) for predicting placenta percreta. CONCLUSION MRI-based scoring models established based on quantitative meta-analysis can accurately predict PAS, placenta percreta, and adverse peripartum outcome. CLINICAL RELEVANCE STATEMENT These proposed MRI-based scoring models could help accurately predict PAS invasiveness and provide evidence-based risk stratification in the management of high-risk pregnant women for PAS. KEY POINTS • Accurately identifying placenta accreta spectrum (PAS) and assessing its invasiveness depending solely on individual MRI signs remained challenging. • MRI-based scoring models, established through quantitative meta-analysis of multiple MRI signs, offered the potential to predict PAS invasiveness in high-risk pregnant women. • These MRI-based models allowed for evidence-based risk stratification in the management of pregnancies suspected of having PAS.
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Affiliation(s)
- Qianyun Liu
- Department of Radiology, The Third Xiangya Hospital of Central South University, No. 138 Tongzipo Road, Changsha, 410013, Hunan, China
- Department of Medical Imaging, Yueyang Central Hospital, Yueyang, Hunan, China
| | - Wenming Zhou
- Department of Medical Imaging, Yueyang Central Hospital, Yueyang, Hunan, China
| | - Zhimin Yan
- Department of Radiology, The Third Xiangya Hospital of Central South University, No. 138 Tongzipo Road, Changsha, 410013, Hunan, China
| | - Da Li
- Department of Medical Imaging, Yueyang Central Hospital, Yueyang, Hunan, China
| | - Tuo Lou
- Department of Medical Imaging, Yueyang Central Hospital, Yueyang, Hunan, China
| | - Yishu Yuan
- Department of Pathology, The Third Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Pengfei Rong
- Department of Radiology, The Third Xiangya Hospital of Central South University, No. 138 Tongzipo Road, Changsha, 410013, Hunan, China
| | - Zhichao Feng
- Department of Radiology, The Third Xiangya Hospital of Central South University, No. 138 Tongzipo Road, Changsha, 410013, Hunan, China.
- Department of Medical Imaging, Yueyang Central Hospital, Yueyang, Hunan, China.
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Verde F, Stanzione A, Romeo V, Maurea S. Reply to "Letter to the editor". Abdom Radiol (NY) 2023; 48:3778-3779. [PMID: 37787961 DOI: 10.1007/s00261-023-04072-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/21/2023] [Indexed: 10/04/2023]
Affiliation(s)
- Francesco Verde
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via S. Pansini, 5, 80123, Naples, Italy.
| | - Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via S. Pansini, 5, 80123, Naples, Italy
| | - Valeria Romeo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via S. Pansini, 5, 80123, Naples, Italy
| | - Simone Maurea
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via S. Pansini, 5, 80123, Naples, Italy
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Bartels HC, O'Doherty J, Wolsztynski E, Brophy DP, MacDermott R, Atallah D, Saliba S, Young C, Downey P, Donnelly J, Geoghegan T, Brennan DJ, Curran KM. Radiomics-based prediction of FIGO grade for placenta accreta spectrum. Eur Radiol Exp 2023; 7:54. [PMID: 37726591 PMCID: PMC10509122 DOI: 10.1186/s41747-023-00369-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 06/26/2023] [Indexed: 09/21/2023] Open
Abstract
BACKGROUND Placenta accreta spectrum (PAS) is a rare, life-threatening complication of pregnancy. Predicting PAS severity is critical to individualise care planning for the birth. We aim to explore whether radiomic analysis of T2-weighted magnetic resonance imaging (MRI) can predict severe cases by distinguishing between histopathological subtypes antenatally. METHODS This was a bi-centre retrospective analysis of a prospective cohort study conducted between 2018 and 2022. Women who underwent MRI during pregnancy and had histological confirmation of PAS were included. Radiomic features were extracted from T2-weighted images. Univariate regression and multivariate analyses were performed to build predictive models to differentiate between non-invasive (International Federation of Gynecology and Obstetrics [FIGO] grade 1 or 2) and invasive (FIGO grade 3) PAS using R software. Prediction performance was assessed based on several metrics including sensitivity, specificity, accuracy and area under the curve (AUC) at receiver operating characteristic analysis. RESULTS Forty-one women met the inclusion criteria. At univariate analysis, 0.64 sensitivity (95% confidence interval [CI] 0.0-1.00), specificity 0.93 (0.38-1.0), 0.58 accuracy (0.37-0.78) and 0.77 AUC (0.56-.097) was achieved for predicting severe FIGO grade 3 PAS. Using a multivariate approach, a support vector machine model yielded 0.30 sensitivity (95% CI 0.18-1.0]), 0.74 specificity (0.38-1.00), 0.58 accuracy (0.40-0.82), and 0.53 AUC (0.40-0.85). CONCLUSION Our results demonstrate a predictive potential of this machine learning pipeline for classifying severe PAS cases. RELEVANCE STATEMENT This study demonstrates the potential use of radiomics from MR images to identify severe cases of placenta accreta spectrum antenatally. KEY POINTS • Identifying severe cases of placenta accreta spectrum from imaging is challenging. • We present a methodological approach for radiomics-based prediction of placenta accreta. • We report certain radiomic features are able to predict severe PAS subtypes. • Identifying severe PAS subtypes ensures safe and individualised care planning for birth.
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Affiliation(s)
- Helena C Bartels
- Department of UCD Obstetrics and Gynaecology, School of Medicine, University College Dublin, National Maternity Hospital, Holles Street, Dublin 2, Ireland.
| | - Jim O'Doherty
- Siemens Medical Solutions, Malvern, PA, USA
- Department of Radiology & Radiological Science, Medical University of South Carolina, Charleston, SC, USA
- Radiography & Diagnostic Imaging, University College Dublin, Dublin, Ireland
| | - Eric Wolsztynski
- Statistics Department, University College Cork, Cork, Ireland
- Insight Centre for Data Analytics, Dublin, Ireland
| | - David P Brophy
- Department of Radiology, St. Vincent's University Hospital, Dublin, Ireland
| | - Roisin MacDermott
- Department of Radiology, St. Vincent's University Hospital, Dublin, Ireland
| | - David Atallah
- Department of Gynecology and Obstetrics, Hôtel-Dieu de France University Hospital, Saint Joseph University, Beirut, Lebanon
| | - Souha Saliba
- Department of Radiology: Fetal and Placental Imaging, Hôtel-Dieu de France University Hospital, Saint Joseph University, Beirut, Lebanon
| | - Constance Young
- Department of Histopathology, National Maternity Hospital, Dublin, Ireland
| | - Paul Downey
- Department of Histopathology, National Maternity Hospital, Dublin, Ireland
| | - Jennifer Donnelly
- Department of Obstetrics and Gynaecology, Rotunda Hospital, Dublin, Ireland
| | - Tony Geoghegan
- Department of Radiology, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Donal J Brennan
- Department of UCD Obstetrics and Gynaecology, School of Medicine, University College Dublin, National Maternity Hospital, Holles Street, Dublin 2, Ireland
- University College Dublin Gynaecological Oncology Group (UCD-GOG), Mater Misericordiae University Hospital and St Vincent's University Hospital, Dublin, Ireland
- Systems Biology Ireland, School of Medicine, University College Dublin, Dublin, Ireland
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Chang WH, Chou FW, Wang PH. The conservative management of pregnant women with placenta accreta spectrum remains challenging. Taiwan J Obstet Gynecol 2023; 62:202-204. [PMID: 36965887 DOI: 10.1016/j.tjog.2023.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2023] [Indexed: 03/27/2023] Open
Affiliation(s)
- Wen-Hsun Chang
- Department of Nursing, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Fang-Wei Chou
- Department of Nursing, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Peng-Hui Wang
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan; Female Cancer Foundation, Taipei, Taiwan; Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.
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The Role of Radiomics in Salivary Gland Imaging: A Systematic Review and Radiomics Quality Assessment. Diagnostics (Basel) 2022; 12:diagnostics12123002. [PMID: 36553009 PMCID: PMC9777175 DOI: 10.3390/diagnostics12123002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/16/2022] [Accepted: 11/29/2022] [Indexed: 12/04/2022] Open
Abstract
Background: Radiomics of salivary gland imaging can support clinical decisions in different clinical scenarios, such as tumors, radiation-induced xerostomia and sialadenitis. This review aims to evaluate the methodological quality of radiomics studies on salivary gland imaging. Material and Methods: A systematic search was performed, and the methodological quality was evaluated using the radiomics quality score (RQS). Subgroup analyses according to the first author's professional role (medical or not medical), journal type (radiological journal or other) and the year of publication (2021 or before) were performed. The correlation of RQS with the number of patients was calculated. Results: Twenty-three articles were included (mean RQS 11.34 ± 3.68). Most studies well-documented the imaging protocol (87%), while neither prospective validations nor cost-effectiveness analyses were performed. None of the included studies provided open-source data. A statistically significant difference in RQS according to the year of publication was found (p = 0.009), with papers published in 2021 having slightly higher RQSs than older ones. No differences according to journal type or the first author's professional role were demonstrated. A moderate relationship between the overall RQS and the number of patients was found. Conclusions: Radiomics application in salivary gland imaging is increasing. Although its current clinical applicability can be affected by the somewhat inadequate quality of the papers, a significant improvement in radiomics methodologies has been demonstrated in the last year.
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Stanzione A. Feasible does not mean useful: Do we always need radiomics? Eur J Radiol 2022; 156:110545. [PMID: 36208506 DOI: 10.1016/j.ejrad.2022.110545] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 09/20/2022] [Indexed: 11/25/2022]
Affiliation(s)
- Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Italy.
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