Share：
Share this content in WeChat
X
[Chinese] [PDF] 9 1
• Clinical Article •
A prenatal MRI signs- clinical scoring system to predict the classifications of placenta accreta spectrum
ZHANG Yu  WANG Xinlian  LIANG Yuting 

DOI:10.12015/issn.1674-8034.2026.01.014.


[Abstract] Objective To establish a prenatal MRI-clinical scoring system and to explore its predictive value for the classifications of placenta accreta spectrum (PAS).Materials and Methods We retrospectively collected the clinical and imaging data of pregnant women who visited the obstetrics clinic of our hospital and were suspected of PAS based on ultrasound or clinical screening, from January 2018 to June 2023. PAS disorders were diagnosed and classified by the surgical and pathological examinations. According to the updated joint consensus of the American Society of Abdominal Radiology and the European Society of Urogenital Radiology, 11 MRI signs related to PAS were selected. The clinical independent risk factors for PAS were selected by univariate and multivariate logistic regression. The logistic regression analysis combining independent risk factors and all MRI signs was used to screen the features with P < 0.05. The weighting of each feature was calculated based on its β coefficient. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of the scoring system, and the threshold of the score for each classification, area under the curve (AUC), sensitivity, specificity, and other diagnostic indicators were calculated.Results A total of 404 pregnant women who met the inclusion and exclusion criteria were collected. Seven features based on MRI and clinics were included in our scoring system. For the comparison between the non-PAS and PA groups, the cut-off value was 6.0. The optimal cut-off value between PA and PI groups was 11.0. The threshold value for PI and PP groups was 17.0.Conclusions The prenatal MRI signs-clinical scoring system possesses favorable clinical feasibility. It plays an important role for assisting in the diagnosis of PAS disorders and identifying the high-risk patients.
[Keywords] placenta accreta spectrum disorders；placenta accrete；placenta increta；placenta percreta；magnetic resonance imaging；scoring system；prenatal diagnosis

ZHANG Yu   WANG Xinlian   LIANG Yuting*  

Department of Radiology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University/Beijing Maternal and Child Health Care Hospital, Beijing 100006, China

Corresponding author: LIANG Y T, E-mail: liangyuting@ccmu.edu.cn

Conflicts of interest   None.

Received  2025-08-24
Accepted  2025-12-29
DOI: 10.12015/issn.1674-8034.2026.01.014
DOI:10.12015/issn.1674-8034.2026.01.014.

[1]
DONOVAN B M, SHAINKER S A. Placenta accreta spectrum[J/OL]. Neoreviews, 2021, 22(11): e722-e733 [2025-08-23]. https://pubmed.ncbi.nlm.nih.gov/34725137. DOI: 10.1542/neo.22-11-e722.
[2]
HORGAN R, ABUHAMAD A. Placenta accreta spectrum: prenatal diagnosis and management[J]. Obstet Gynecol Clin North Am, 2022, 49(3): 423-438. DOI: 10.1016/j.ogc.2022.02.004.
[3]
EINERSON B D, GILNER J B, ZUCKERWISE L C. Placenta accreta spectrum[J]. Obstet Gynecol, 2023, 142(1): 31-50. DOI: 10.1097/AOG.0000000000005229.
[4]
PATEL-LIPPMANN K K, PLANZ V B, PHILLIPS C H, et al. Placenta accreta spectrum disorders: update and pictorial review of the SAR-ESUR joint consensus statement for MRI[J/OL]. Radiographics, 2023, 43(5): e220090 [2025-08-23]. https://pubmed.ncbi.nlm.nih.gov/37079459. DOI: 10.1148/rg.220090.
[5]
WALLER J, SHAMSHIRSAZ A, ABUHAMAD A. Advances in imaging for placenta accreta spectrum disorder[J]. Obstet Gynecol, 2025, 145(6): 621-627. DOI: 10.1097/AOG.0000000000005905.
[6]
YE C H, LING L, LI S, et al. Comparisons of the diagnostic accuracy of the ultrasonic sign-score method and MRI for PA, PI and PP in high-risk gravid women: a retrospective study[J/OL]. Ann Transl Med, 2023, 11(2): 81 [2025-08-23]. https://pmc.ncbi.nlm.nih.gov/articles/PMC9929761. DOI: 10.21037/atm-22-6508.
[7]
JHA P, PŌDER L, BOURGIOTI C, et al. Society of Abdominal Radiology (SAR) and European Society of Urogenital Radiology (ESUR) joint consensus statement for MR imaging of placenta accreta spectrum disorders[J]. Eur Radiol, 2020, 30(5): 2604-2615. DOI: 10.1007/s00330-019-06617-7.
[8]
ZOU J L, HU Z Y, WANG X L, et al. Radiomics model based on MR T2WI for prenatal diagnosis and classification of placenta accreta spectrum disorders[J]. Chin J Magn Reson Imag, 2024, 15(1): 137-144. DOI: 10.12015/issn.1674-8034.2024.01.022.
[9]
WANG Z W, JIAO X Y, LIU W W, et al. Comparative evaluation of clinical-MRI, radiomics, and integrated nomogram models for preoperative prediction of placenta accreta spectrum[J]. Acad Radiol, 2025, 32(4): 2041-2052. DOI: 10.1016/j.acra.2024.10.021.
[10]
LI Q, ZHOU H, ZHOU K F, et al. Development and validation of a magnetic resonance imaging-based nomogram for predicting invasive forms of placental accreta spectrum disorders[J]. J Obstet And Gynaecol, 2021, 47(10): 3488-3497. DOI: 10.1111/jog.14982.
[11]
YU H C, YIN H K, ZHANG H L, et al. Placental T2WI MRI-based radiomics-clinical nomogram predicts suspicious placenta accreta spectrum in patients with placenta previa[J/OL]. BMC Med Imaging, 2024, 24(1): 146 [2025-08-23]. https://pmc.ncbi.nlm.nih.gov/articles/PMC11177524. DOI: 10.1186/s12880-024-01328-y.
[12]
KOU X M, XU C Q, LI J J, et al. Radiomics model based on T2WI for predicting pernicious placenta previa analysis with placenta percreta[J]. J Clin Radiol, 2025, 44(3): 502-507. DOI: 10.13437/j.cnki.jcr.2025.03.006.
[13]
ZOU L, WANG P Y, SONG Z X, et al. Effectiveness of a fetal magnetic resonance imaging scoring system for predicting the prognosis of pernicious placenta previa: A retrospective study[J/OL]. Front Physiol, 2022, 13: 921273 [2025-08-23]. https://pmc.ncbi.nlm.nih.gov/articles/PMC9402898. DOI: 10.3389/fphys.2022.921273.
[14]
PEKAR ZLOTIN M, SHARABI-NOV A, MEIRI H, et al. Clinical-sonographic scores for the screening of placenta accreta spectrum: a systematic review and meta-analysis[J/OL]. Am J Obstet Gynecol MFM, 2024, 6(8): 101369 [2025-08-23]. https://pubmed.ncbi.nlm.nih.gov/38636601. DOI: 10.1016/j.ajogmf.2024.101369.
[15]
ZHANG J L, LI H Z, FENG D M, et al. Ultrasound scoring system for prenatal diagnosis of placenta accreta spectrum[J/OL]. BMC Pregnancy Childbirth, 2023, 23(1): 569 [2025-08-23]. https://pmc.ncbi.nlm.nih.gov/articles/PMC10405485. DOI: 10.1186/s12884-023-05886-x.
[16]
AGARWAL N, HERNANDEZ-ANDRADE E, SIBAI B M, et al. Quantifying placenta accreta spectrum severity and its associated blood loss: a novel transvaginal ultrasound scoring system[J/OL]. Am J Obstet Gynecol MFM, 2024, 6(10): 101451 [2025-08-23]. https://pubmed.ncbi.nlm.nih.gov/39096965. DOI: 10.1016/j.ajogmf.2024.101451.
[17]
MAUREA S, VERDE F, ROMEO V, et al. Prediction of placenta accreta spectrum in patients with placenta previa using a clinical, US and MRI combined model: A retrospective study with external validation[J/OL]. Eur J Radiol, 2023, 168: 111116 [2025-08-23]. https://pubmed.ncbi.nlm.nih.gov/37801998. DOI: 10.1016/j.ejrad.2023.111116.
[18]
HU Y M, CHEN W Y, KONG C L, et al. Prediction of placenta accreta spectrum with nomogram combining radiomic and clinical factors: a novel developed and validated integrative model[J]. Int J Gynaecol Obstet, 2023, 162(2): 639-650. DOI: 10.1002/ijgo.14710.
[19]
CHE J L, MENG Y Y, LONG Y Y, et al. Development of a clinical and magnetic resonance imaging-based nomogram for predicting invasive forms of placental accreta spectrum disorders[J]. Diagn Imag Interv Radiol, 2022, 31(3): 175-181. DOI: 10.3969/j.issn.1005-8001.2022.03.003.
[20]
DU W Q, NOVIN A, LIU Y M, et al. Scar matrix drives Piezo1 mediated stromal inflammation leading to placenta accreta spectrum[J/OL]. Nat Commun, 2024, 15(1): 8379 [2025-08-23]. https://pmc.ncbi.nlm.nih.gov/articles/PMC11436960. DOI: 10.1038/s41467-024-52351-0.
[21]
JAUNIAUX E, COLLINS S, BURTON G J. Placenta accreta spectrum: pathophysiology and evidence-based anatomy for prenatal ultrasound imaging[J]. Am J Obstet Gynecol, 2018, 218(1): 75-87. DOI: 10.1016/j.ajog.2017.05.067.
[22]
TIMOR-TRITSCH I E, MONTEAGUDO A, CALÌ G, et al. Cesarean scar pregnancy: diagnosis and pathogenesis[J]. Obstet Gynecol Clin North Am, 2019, 46(4): 797-811. DOI: 10.1016/j.ogc.2019.07.009.
[23]
JAUNIAUX E, BURTON G J. Pathophysiology of placenta accreta spectrum disorders: a review of current findings[J]. Clin Obstet Gynecol, 2018, 61(4): 743-754. DOI: 10.1097/GRF.0000000000000392.
[24]
WHITE A, MALIK M, PRUSZYNSKI J E, et al. Contemporary placenta accreta spectrum disorder incidence and risk factors[J]. Obstet Gynecol, 2025, 145(6): 665-673. DOI: 10.1097/AOG.0000000000005919.
[25]
OYELESE Y, SHAINKER S A. Placenta previa[J]. Clin Obstet Gynecol, 2025, 68(1): 86-92. DOI: 10.1097/GRF.0000000000000911.
[26]
JENABI E, SALIMI Z, BASHIRIAN S, et al. The risk factors associated with placenta previa: an umbrella review[J]. Placenta, 2022, 117: 21-27. DOI: 10.1016/j.placenta.2021.10.009.
[27]
ASIM Z, KHATTAK K, ALI E, et al. Investigating the frequency of placenta previa and the associated risk factors during pregnancy[J/OL]. Cureus, 2025, 17(6): e86053 [2025-08-23]. https://pmc.ncbi.nlm.nih.gov/articles/PMC12261999. DOI: 10.7759/cureus.86053.
[28]
PARNES B, KAMATH A, FRIEDMAN B, et al. Endorsing consensus interpretation for diagnosing placenta accreta spectrum disorders on MRI[J]. Eur Radiol, 2026, 36(1): 278-287. DOI: 10.1007/s00330-025-11832-6.
[29]
YANG H C, WU X, LIU W H, et al. A quantitative analysis framework of placenta accreta spectrum: placenta subtype, intraoperative bleeding, and hysterectomy risk evaluation based on magnetic resonance imaging-anatomical-clinical features[J]. Quant Imaging Med Surg, 2023, 13(10): 7105-7116. DOI: 10.21037/qims-23-142.
[30]
HU Y M, WANG Y, WENG Q Y, et al. Intraplacental T2-hypointense bands may help predict placental invasion depth and postpartum hemorrhage in placenta accrete spectrum disorders in high-risk gravid patients[J]. Magn Reson Imaging, 2022, 94: 73-79. DOI: 10.1016/j.mri.2022.09.005.
[31]
PARNES B, LEWIS S, FRIEDMAN B, et al. Reproducibility of MRI features for the diagnosis of placenta accreta spectrum disorders[J/OL]. Radiology, 2024, 312(3): e240386 [2025-08-23]. https://pubmed.ncbi.nlm.nih.gov/39315895. DOI: 10.1148/radiol.240386.
[32]
THIRAVIT S, LAPATIKARN S, MUANGSOMBOON K, et al. MRI of placenta percreta: differentiation from other entities of placental adhesive disorder[J]. Radiol Med, 2017, 122(1): 61-68. DOI: 10.1007/s11547-016-0689-3.
[33]
LI H, LU T, LI M, et al. Differentiation of placenta percreta through MRI features and diffusion-weighted magnetic resonance imaging[J/OL]. Insights Imaging, 2023, 14(1): 93 [2025-08-23]. https://pmc.ncbi.nlm.nih.gov/articles/PMC10209373. DOI: 10.1186/s13244-023-01448-z.
[34]
THIRAVIT S, MA K, GOLDMAN I, et al. Role of ultrasound and MRI in diagnosis of severe placenta accreta spectrum disorder: an intraindividual assessment with emphasis on placental bulge[J]. AJR Am J Roentgenol, 2021, 217(6): 1377-1388. DOI: 10.2214/AJR.21.25581.
[35]
TANAKA Y, ANDO H, MIYAMOTO T, et al. Usefulness of decision tree analysis of MRI features for diagnosis of placenta accreta spectrum in cases with placenta previa[J]. Jpn J Radiol, 2025, 43(3): 492-501. DOI: 10.1007/s11604-024-01684-3.

PREV Prognostic value of an MRI-based radiomics machine learning model for patients with locally advanced cervical cancer undergoing concurrent chemoradiotherapy
NEXT The diagnostic value of radiomics features of the lateral pterygoid muscle, articular disc, and bilaminar zone on MRI in temporomandibular disorders
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn