Diagnostic Utility of MRI Features of Placental Adhesion Disorder for Abnormal Placentation and Massive Postpartum Hemorrhage

Stewart, Michael John; Richmond, Danielle; Mooney, Samantha; Esler, Stephen; Чурилов, Леонид; Israelsohn, N.; Yang, Natalie

doi:10.2214/ajr.19.22661

Cited by 7 publications

(2 citation statements)

References 43 publications

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“…They are extensively employed in the prediction of tumorigenesis and prognosis for various cancers, including breast, gastric, and prostate cancers 18 – 20 . Prior research has primarily focused on the association between MRI signs and the occurrence of PAS 21 – 27 . In this study, we developed and validated a nomogram for predicting PAS in patients with placenta previa, incorporating clinical features and MRI signs.…”

Section: Discussionmentioning

confidence: 99%

“…While numerous MRI features of PAS have been extensively described in literature 21 – 27 , and many studies have demonstrated a strong correlation between MRI findings and intraoperative observations of invasive placentas 6 , 16 , 21 , certain MRI signs were excluded from our study. These include myometrial thinning, interrupted myometrium, heterogeneous placenta, abnormal uterine bulging, loss of the placental-myometrial interface, and percretism signs.…”

Section: Discussionmentioning

confidence: 99%

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Nomogram model for predicting invasive placenta in patients with placenta previa: integrating MRI findings and clinical characteristics

Huang,

Lyu,

Lai

et al. 2024

Sci Rep

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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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