Share:
Share this content in WeChat
X
Clinical Article
Clinical value of MRI-based scoring system in predicting placenta accreta spectrum disorders
ZHU Xiaoman  ZOU Lue  LIU Peng  ZHANG Jun 

Cite this article as: Zhu XM, Zou L, Liu P, et al. Clinical value of MRI-based scoring system in predicting placenta accreta spectrum disorders[J]. Chin J Magn Reson Imaging, 2021, 12(11): 37-41. DOI:10.12015/issn.1674-8034.2021.11.008.


[Abstract] Objective To investigate the clinical value of MRI-based scoring system in predicting placenta accreta spectrum disorders.Materials and Methods: The data of 102 pregnant women suspected of placenta accreta spectrum disorders in our hospital were analyzed retrospectively. Nine items including MRI signs and clinical risk factors were selected to develop the MRI-based scoring system in predicting placenta accreta spectrum. Calculate average total score of each type of placenta implantation. The variance analysis and least-significant difference were used for comparison among groups and the ROC curve was drawn to calculate the cut-off score of each type of placenta implantation.Results Among 102 pregnant women, there were 35 cases of non-implantation type, score was (2.94±1.28), 28 cases of placenta accreta type, score was (5.54±1.75), 32 cases of placenta increta type, score was (9.88±2.37), and 7 cases of placenta percreta type, score was (13.57±1.90). There was statistically significant difference in scores among all groups (F=115.688, P<0.05). The ROC curve showed that the cut-off score between non-implantation and placenta accreta, between placenta accreta and placenta increta, and between placenta increta and placenta percreta were 3.5, 7.5, and 10.5, respectively.Conclusions MRI-based scoring system has a good value in predicting placenta accreta spectum disorders and depth of placenta imlantation.
[Keywords] placenta accreta spectrum disorders;depth of placenta implantation;magnetic resonance imaging;scoring system;prenatal diagnosis

ZHU Xiaoman   ZOU Lue   LIU Peng   ZHANG Jun*  

Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China

Zhang J, E-mail: zhangj1@sj-hospital.org

Conflicts of interest   None.

Received  2021-05-26
Accepted  2021-08-06
DOI: 10.12015/issn.1674-8034.2021.11.008
Cite this article as: Zhu XM, Zou L, Liu P, et al. Clinical value of MRI-based scoring system in predicting placenta accreta spectrum disorders[J]. Chin J Magn Reson Imaging, 2021, 12(11): 37-41. DOI:10.12015/issn.1674-8034.2021.11.008.

[1]
Silver RM. Abnormal placentation placenta previa, vasa previa, and placenta accreta[J]. Obstet Gynecol, 2015, 126(3): 654-668. DOI: 10.1097/aog.0000000000001005.
[2]
Vintzileos AM, Ananth CV, Smulian JC. Using ultrasound in the clinical management of placental implantation abnormalities[J]. Am J Obstet Gynecol, 2015, 213(4): S70-S77. DOI: 10.1016/j.ajog.2015.05.059.
[3]
Chen DJ, Yang HX. Clinical guideline for diagnosis and treatment of placenta intreta(2015)[J]. Chin J Obstet Gynecol, 2015, 50(12): 970-972. DOI: 10.3760/cma.j.issn.0529-567x.2015.12.020.
[4]
Familiari A, Liberati M, Lim P, et al. Diagnostic accuracy of magnetic resonance imaging in detecting the severity of abnormal invasive placenta: a systematic review and meta-analysis[J]. Acta Obstet Gynecol Scand, 2018, 97(5): 507-520. DOI: 10.1111/aogs.13258.
[5]
Marsoosi V, Ghotbizadeh F, Hashemi N, et al. Development of a scoring system for prediction of placenta accreta and determine the accuracy of its results[J]. J Matern Fetal Neonatal Med, 2020, 33(11): 1824-1830. DOI: 10.1080/14767058.2018.1531119.
[6]
Abu Hashim H, Shalaby EM, Hussien MH, et al. Diagnostic accuracy of the placenta accreta index for placenta accreta spectrum: a prospective study[J]. Int J Gynaecol Obstet, 2021. DOI: 10.1002/ijgo.13610.
[7]
Jauniaux E, Bhide A, Kennedy A, et al. FIGO consensus guidelines on placenta accreta spectrum disorders: Prenatal diagnosis and screening[J]. Int J Gynecol Obstet, 2018, 140(3): 274-280. DOI: 10.1002/ijgo.12408.
[8]
Jha P, Poder 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.
[9]
Novis MI, Moura APC, Watanabe APF, et al. Placental magnetic resonance imaging: normal appearance, anatomical variations, and pathological findings[J]. Radiol Bras, 2021, 54(2): 123-129. DOI: 10.1590/0100-3984.2020.0010.
[10]
Goergen SK, Posma E, Wrede D, et al. Interobserver agreement and diagnostic performance of individual MRI criteria for diagnosis of placental adhesion disorders[J]. Clin Radiol, 2018, 73(10): 908. e1-908. e9. DOI: 10.1016/j.crad.2018.05.021.
[11]
Derman AY, Nikac V, Haberman S, et al. MRI of placenta accreta: a new imaging perspective[J]. AJR Am J Roentgenol, 2011, 197(6): 1514-1521. DOI: 10.2214/ajr.10.5443.
[12]
Chantraine F, Blacher S, Berndt S, et al. Abnormal vascular architecture at the placental-maternal interface in placenta increta[J]. Am J Obstet Gynecol, 2012, 207(3): 188. e1-9. DOI: 10.1016/j.ajog.2012.06.083.
[13]
Kapoor H, Hanaoka M, Dawkins A, et al. Review of MRI imaging for placenta accreta spectrum: pathophysiologic insights, imaging signs, and recent developments[J]. Placenta, 2021, 104: 31-39. DOI: 10.1016/j.placenta.2020.11.004.
[14]
D'antonio F, Bhide A. Ultrasound in placental disorders[J]. Best Pract Res Clin Obstet Gynaecol, 2014, 28(3): 429-442. DOI: 10.1016/j.bpobgyn.2014.01.001.
[15]
Jauniaux E, Kingdom JC, Silver RM. A comparison of recent guidelines in the diagnosis and management of placenta accreta spectrum disorders[J]. Best Pract Res Clin Obstet Gynaecol, 2021, 72: 102-116. DOI: 10.1016/j.bpobgyn.2020.06.007.
[16]
Srisajjakul S, Prapaisilp P, Bangchokdee S. Magnetic resonance imaging of placenta accreta spectrum: a step-by-step approach[J]. Korean J Radiol, 2021, 22(2): 198-212. DOI: 10.3348/kjr.2020.0580.
[17]
Zheng CN, Yang TH, Lin JZ, et al. MRI in the diagnosis of placenta accreta[J]. Chin J Magn Reson Imaging, 2017, 8(8): 593-597. DOI: 10.12015/issn.1674-8034.2017.08.007.
[18]
D'antonio F, Iacovella C, Palacios-Jaraquemada J, et al. Prenatal identification of invasive placentation using magnetic resonance imaging: systematic review and meta-analysis[J]. Ultrasound Obstet Gynecol, 2014, 44(1): 8-16. DOI: 10.1002/uog.13327.
[19]
Ishibashi H, Miyamoto M, Shinmoto H, et al. The use of magnetic resonance imaging to predict placenta previa with placenta accreta spectrum[J]. Acta Obstet Gynecol Scand, 2020, 99(12): 1657-1665. DOI: 10.1111/aogs.13937.
[20]
Ueno Y, Maeda T, Tanaka U, et al. Evaluation of interobserver variability and diagnostic performance of developed MRI-based radiological scoring system for invasive placenta previa[J]. J Magn Reson Imaging, 2016, 44(3): 573-583. DOI: 10.1002/jmri.25184.
[21]
Delli Pizzi A, Tavoletta A, Narciso R, et al. Prenatal planning of placenta previa: diagnostic accuracy of a novel MRI-based prediction model for placenta accreta spectrum (PAS) and clinical outcome[J]. Abdom Radiol (NY), 2019, 44(5): 1873-1882. DOI: 10.1007/s00261-018-1882-8.
[22]
Meng LS, Yang ZQ, Yan Y, et al. The application value of Likert scale's scoring system in predicting the depth of placental implantation by MRI[J]. China Medical Equipment, 2020, 17(8): 79-84. DOI: 10.3969/J.ISSN.1672-8270.2020.08.020.
[23]
Tanimura K, Morizane M, Deguchi M, et al. A novel scoring system for predicting adherent placenta in women with placenta previa[J]. Placenta, 2018, 64: 27-33. DOI: 10.1016/j.placenta.2018.02.005.
[24]
Knight JC, Lehnert S, Shanks AL, et al. A comprehensive severity score for the morbidly adherent placenta: combining ultrasound and magnetic resonance imaging[J]. Pediatr Radiol, 2018, 48(13): 1945-1954. DOI: 10.1007/s00247-018-4235-4.
[25]
Chen L, Chen M, Pei XL, et al. Predictive value of MRI image-based scoring model for diagnosis and adverse clinical outcomes of invasive placenta accreta[J]. Chin J Perinat Med, 2021, 24(1): 32-39. DOI: 10.3760/cma.j.cn113903-20200706-00639.

PREV Multiparametric MRI radiomics signature for prediction of KRAS gene mutation in rectal cancer
NEXT Cerebellar-cortical functional connectivity abnormalities in individuals with nicotine dependence
  



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