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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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Lu X, Zhang H, Wu X, Chen X, Zhang Q, Song W, Jin Y, Yuan M. The value of the combined MR imaging features and clinical factors Nomogram model in predicting intractable postpartum hemorrhage due to placenta accreta. Medicine (Baltimore) 2024; 103:e37665. [PMID: 38552054 PMCID: PMC10977557 DOI: 10.1097/md.0000000000037665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 02/29/2024] [Indexed: 04/02/2024] Open
Abstract
To explore the value of the combined MR imaging features and clinical factors Nomogram model in predicting intractable postpartum hemorrhage (IPH) due to placenta accreta (PA). We conducted a retrospective study with 270 cases of PA patients admitted to our hospital from January 2015 to December 2022. The clinical data of these patients were analyzed, and they were divided into 2 groups: the IPH group and the non-IPH group based on the presence of IPH. The differences in data between the 2 groups were compared, and the risk factors for IPH were analyzed. A Nomogram model was constructed using independent high-risk factors, and the predictive value of this model for IPH was analyzed. The results of multivariable binary Logistic regression analysis showed higher number of cesareans, placenta previa, placenta accreta type (implantation, penetration), low signal strip on T2 weighted image (T2WI) were independent high-risk factor for IPH (P < .05). ROC analysis and Hosmer-Lemeshow goodness-of-fit test showed the Nomogram predictive model constructed with the high-risk factor has good discrimination and calibration. Decision curve analysis (DCA) showed that when the probability threshold for the Nomogram model's prediction was in the range from 0.125 to 0.99, IPH patients could obtain more net benefits, making it suitable for clinical application. The higher number of cesareans, placenta previa, placental accreta type (implantation, penetration), and low signal strip on T2WI are independent high-risk factor for IPH. The Nomogram predictive model constructed with the high-risk factor demonstrates good clinical efficacy in predicting the occurrence of IPH due to PA.
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Affiliation(s)
- Xian Lu
- Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China
| | - Haibo Zhang
- Department of Emergency Medicine, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China
| | - Xianhua Wu
- Department of Radiology, Affiliated Hospital of Nantong University, Nantong, China
| | - Xianfeng Chen
- Department of Ultrasound, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China
| | - Qin Zhang
- Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China
| | - Wei Song
- Department of Radiology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China
| | - Yanqi Jin
- Department of Obstetrics, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China
| | - Mingming Yuan
- Department of Pathology, Affiliated Maternity and Child Health Care Hospital of Nantong University, Nantong, China
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Huang F, Lyu GR, Lai QQ, Li YZ. Nomogram model for predicting invasive placenta in patients with placenta previa: integrating MRI findings and clinical characteristics. Sci Rep 2024; 14:200. [PMID: 38167630 PMCID: PMC10761737 DOI: 10.1038/s41598-023-50900-z] [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] [Received: 02/18/2023] [Accepted: 12/27/2023] [Indexed: 01/05/2024] Open
Abstract
This study aims to validate a nomogram model that predicts invasive placenta in patients with placenta previa, utilizing MRI findings and clinical characteristics. A retrospective analysis was conducted on a training cohort of 269 patients from the Second Affiliated Hospital of Fujian Medical University and a validation cohort of 41 patients from Quanzhou Children's Hospital. Patients were classified into noninvasive and invasive placenta groups based on pathological reports and intraoperative findings. Three clinical characteristics and eight MRI signs were collected and analyzed to identify risk factors and develop the nomogram model. The mode's performance was evaluated in terms of its discrimination, calibration, and clinical utility. Independent risk factors incorporated into the nomogram included the number of previous cesarean sections ≥ 2 (odds ratio [OR] 3.32; 95% confidence interval [CI] 1.28-8.59), type-II placental bulge (OR 17.54; 95% CI 3.53-87.17), placenta covering the scar (OR 2.92; CI 1.23-6.96), and placental protrusion sign (OR 4.01; CI 1.06-15.18). The area under the curve (AUC) was 0.908 for the training cohort and 0.803 for external validation. The study successfully developed a highly accurate nomogram model for predicting invasive placenta in placenta previa cases, based on MRI signs and clinical characteristics.
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Affiliation(s)
- Fang Huang
- Department of Radiology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- Department of Radiology, The Second Affiliated Clinical Medical College of Fujian Medical University, Quanzhou, China
| | - Guo-Rong Lyu
- Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
- Department of Ultrasound, The Second Affiliated Clinical Medical College of Fujian Medical University, Quanzhou, China.
| | - Qing-Quan Lai
- Department of Radiology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- Department of Radiology, The Second Affiliated Clinical Medical College of Fujian Medical University, Quanzhou, China
| | - Yuan-Zhe Li
- Department of Radiology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- Department of Radiology, The Second Affiliated Clinical Medical College of Fujian Medical University, Quanzhou, China
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Maurea S, Verde F, Romeo V, Stanzione A, Mainenti PP, Raia G, Barbuto L, Iacobellis F, Santangelo F, Sarno L, Migliorini S, Petretta M, D'Armiento M, De Dominicis G, Santangelo C, Guida M, Romano L, Brunetti A. Prediction of placenta accreta spectrum in patients with placenta previa using a clinical, US and MRI combined model: A retrospective study with external validation. Eur J Radiol 2023; 168:111116. [PMID: 37801998 DOI: 10.1016/j.ejrad.2023.111116] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 09/11/2023] [Accepted: 09/26/2023] [Indexed: 10/08/2023]
Abstract
PURPOSE To build and validate a predictive model of placental accreta spectrum (PAS) in patients with placenta previa (PP) combining clinical risk factors (CRF) with US and MRI signs. METHOD Our retrospective study included patients with PP from two institutions. All patients underwent US and MRI examinations for suspicion of PAS. CRF consisting of maternal age, cesarean section number, smoking and hypertension were retrieved. US and MRI signs suggestive of PAS were evaluated. Logistic regression analysis was performed to identify CRF and/or US and MRI signs associated with PAS considering histology as the reference standard. A nomogram was created using significant CRF and imaging signs at multivariate analysis, and its diagnostic accuracy was measured using the area under the binomial ROC curve (AUC), and the cut-off point was determined by Youden's J statistic. RESULTS A total of 171 patients were enrolled from two institutions. Independent predictors of PAS included in the nomogram were: 1) smoking and number of previous CS among CRF; 2) loss of the retroplacental clear space at US; 3) intraplacental dark bands, focal interruption of the myometrial border and placental bulging at MRI. A PAS-prediction nomogram was built including these parameters and an optimal cut-off of 14.5 points was identified, showing the highest sensitivity (91%) and specificity (88%) with an AUC value of 0.95 (AUC of 0.80 in the external validation cohort). CONCLUSION A nomogram-based model combining CRF with US and MRI signs might help to predict PAS in PP patients, with MRI contributing more than US as imaging evaluation.
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Affiliation(s)
- Simone Maurea
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy
| | - Francesco Verde
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy; Department of General and Emergency Radiology, "Antonio Cardarelli" Hospital, Naples, Italy
| | - Valeria Romeo
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy
| | - Arnaldo Stanzione
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy.
| | - Pier Paolo Mainenti
- Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples, Italy
| | - Giorgio Raia
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy
| | - Luigi Barbuto
- Department of General and Emergency Radiology, "Antonio Cardarelli" Hospital, Naples, Italy
| | - Francesca Iacobellis
- Department of General and Emergency Radiology, "Antonio Cardarelli" Hospital, Naples, Italy
| | - Fabrizia Santangelo
- Department of Obstetrics and Gynecology, "Antonio Cardarelli" Hospital, Naples, Italy
| | - Laura Sarno
- University of Naples "Federico II", Department of Neuroscience, Reproductive and Dentistry Sciences, Naples, Italy
| | - Sonia Migliorini
- University of Naples "Federico II", Department of Neuroscience, Reproductive and Dentistry Sciences, Naples, Italy
| | | | - Maria D'Armiento
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy
| | - Gianfranco De Dominicis
- Department of Anatomical Pathology, "Antonio Cardarelli" Hospital, Antonio Cardarelli, Naples, Italy
| | - Claudio Santangelo
- Department of Obstetrics and Gynecology, "Antonio Cardarelli" Hospital, Naples, Italy
| | - Maurizio Guida
- University of Naples "Federico II", Department of Neuroscience, Reproductive and Dentistry Sciences, Naples, Italy
| | - Luigia Romano
- Department of General and Emergency Radiology, "Antonio Cardarelli" Hospital, Naples, Italy
| | - Arturo Brunetti
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples, Italy
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Song Z, Wang P, Zou L, Zhou Y, Wang X, Liu T, Zhang D. Enhancing postpartum hemorrhage prediction in pernicious placenta previa: a comparative study of magnetic resonance imaging and ultrasound nomogram. Front Physiol 2023; 14:1177795. [PMID: 37614762 PMCID: PMC10443221 DOI: 10.3389/fphys.2023.1177795] [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: 03/02/2023] [Accepted: 07/25/2023] [Indexed: 08/25/2023] Open
Abstract
Objective: To explore the risk factors of postpartum hemorrhage (PPH) in patients with pernicious placenta previa (PPP) and to develop and validate a clinical and imaging-based predictive model. Methods: A retrospective analysis was conducted on patients diagnosed surgically and pathologically with PPP between January 2018 and June 2022. All patients underwent PPP magnetic resonance imaging (MRI) and ultrasound scoring in the second trimester and before delivery, and were categorized into two groups according to PPH occurrence. The total imaging score and sub-item prediction models of the MRI risk score/ultrasound score were used to construct Models A and B/Models C and D. Models E and F were the total scores of the MRI combined with the ultrasound risk and sub-item prediction model scores. Model G was based on the subscores of MRI and ultrasound with the introduction of clinical data. Univariate logistic regression analysis and the logical least absolute shrinkage and selection operator (LASSO) model were used to construct models. The receiver operating characteristic curve andision curve analysis (DCA) were drawn, and the model with the strongest predictive ability and the best clinical effect was selected to construct a nomogram. Internal sampling was used to verify the prediction model's consistency. Results: 158 patients were included and the predictive power and clinical benefit of Models B and D were better than those of Models A and C. The results of the area under the curve of Models B, D, E, F, and G showed that Model G was the best, which could reach 0.93. Compared with Model F, age, vaginal hemorrhage during pregnancy, and amniotic fluid volume were independent risk factors for PPH in patients with PPP (p < 0.05). We plotted the DCA of Models B, D, E, F, and G, which showed that Model G had better clinical benefits and that the slope of the calibration curve of Model G was approximately 45°. Conclusion: LASSO regression nomogram based on clinical risk factors and multiple conventional ultrasound plus MRI signs has a certain guiding significance for the personalized prediction of PPH in patients with PPP before delivery.
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Affiliation(s)
- Zixuan Song
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Pengyuan Wang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lue Zou
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yangzi Zhou
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaoxue Wang
- Department of Health Management, Shengjing Hospital of China Medical University, Shenyang, China
| | - Tong Liu
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Dandan Zhang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
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Maurea S, Verde F, Mainenti PP, Barbuto L, Iacobellis F, Romeo V, Liuzzi R, Raia G, De Dominicis G, Santangelo C, Romano L, Brunetti A. Qualitative evaluation of MR images for assessing placenta accreta spectrum disorders in patients with placenta previa: A pilot validation study. Eur J Radiol 2021; 146:110078. [PMID: 34871935 DOI: 10.1016/j.ejrad.2021.110078] [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: 10/10/2021] [Revised: 11/22/2021] [Accepted: 11/25/2021] [Indexed: 11/03/2022]
Abstract
PURPOSE To validate a qualitative imaging method using magnetic resonance (MR) for predicting placental accreta spectrum (PAS) in patients with placenta previa (PP). METHOD Two MR imaging methods built in our previous experience was tested in an external comparable group of sixty-five patients with PP; these methods consisted of presence of at least one (Method 1) or two (Method 2) of the following abnormal MR imaging signs: intraplacental dark bands, focal interruption of myometrial border and abnormal placental vascularity. Three groups of radiologists with different level of expertise evaluated MR images: at least 5 years of experience in body imaging (Group 1); at least 10 (Group 2) or 20 (Group 3) years of experience in genito-urinary MR. While radiologists of Group 1 routinely evaluated MR images, those of Groups 2 and 3 used both Methods 1 and 2. RESULTS A significant (p < 0.005) difference was found between the diagnostic accuracy values of imaging evaluation performed by Group 3 using Method 1 (63%) and Method 2 (89%); of note, the accuracy of Method 2 by Group 3 was also significantly (p < 0.005) higher compared to that of both Methods 1 (46%) and 2 (63%) by Group 2 as well as to that of the routine evaluation by Group 1 (60%). CONCLUSIONS The qualitative identification of at least two abnormal MR signs (Method 2) represents an accurate method for predicting PAS in patients with PP particularly when this method was used by more experienced radiologists; thus, imaging expertise and methodology is required for this purpose.
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Affiliation(s)
- Simone Maurea
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Francesco Verde
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
| | - Pier Paolo Mainenti
- Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples, Italy
| | - Luigi Barbuto
- Department of General and Emergency Radiology, "Antonio Cardarelli" Hospital, Antonio Cardarelli st 9, 80131 Naples, Italy
| | - Francesca Iacobellis
- Department of General and Emergency Radiology, "Antonio Cardarelli" Hospital, Antonio Cardarelli st 9, 80131 Naples, Italy
| | - Valeria Romeo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Raffaele Liuzzi
- Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples, Italy
| | - Giorgio Raia
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Gianfranco De Dominicis
- Department of Anatomical Pathology, "Antonio Cardarelli" Hospital, Antonio Cardarelli st 9, 80131 Naples, Italy
| | - Claudio Santangelo
- Department of Obstetrics and Gynecology, "Antonio Cardarelli" Hospital, Antonio Cardarelli st 9, 80131 Naples, Italy
| | - Luigia Romano
- Department of General and Emergency Radiology, "Antonio Cardarelli" Hospital, Antonio Cardarelli st 9, 80131 Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
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Ren H, Mori N. Letter to "Development and validation of a magnetic resonance imaging-based nomogram for predicting invasive forms of placental accreta spectrum disorders". J Obstet Gynaecol Res 2021; 47:4502-4503. [PMID: 34494342 DOI: 10.1111/jog.15024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 08/31/2021] [Indexed: 11/30/2022]
Affiliation(s)
- Hainan Ren
- Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Naoko Mori
- Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, Sendai, Japan
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