Grading magnetic resonance imaging signs for diagnosing invasive placenta accreta spectrum disorders
Year: 2025
Type: article
Study design: Observational Study
Abstract: INTRODUCTION: Placenta accreta spectrum (PAS) disorders result from abnormal placental attachment, leading to varying degrees of myometrial invasion. Magnetic resonance imaging (MRI) plays a crucial role in assessing the depth and extent of placental invasion. This study aims to evaluate the correlation between quantified MRI findings and the diagnosis of PAS, as classified according to the FIGO system. MATERIALS AND METHODS: A retrospective analysis was conducted on 556 high-risk PAS patients, defined as those with placenta previa or a history of previous cesarean sections. Ten predefined MRI signs were assessed board certified radiologists. Multivariate logistic regression was used to identify independent predictors of invasive PAS. The positive predictive value (PPV) and negative predictive value (NPV) were calculated to assess the diagnostic performance of signs. RESULTS: Among the 556 cases, 150 (26.98 %) were classified as non-PAS, 180 (32.37 %) as placenta accreta, 158 (28.42 %) as placenta increta, and 68 (12.23 %) as placenta percreta. Four MRI signs were identified as significant predictors of invasive PAS: bladder wall interruption (odd ratio [OR] = 160.17), placental ischemic infarction (OR = 19.91), placental protrusion (OR = 14.66), and myometrial thinning (OR = 14.07). The PPV of these signs ranged from 70 % to 85 %, while the NPV ranged from 65 % to 72 %. Multivariate analysis confirmed these MRI findings as independent predictors of invasive PAS. CONCLUSIONS: This study identified four key MRI signs as reliable predictors of invasive PAS, which can effectively inform clinical decision-making regarding surgical interventions, such as cesarean hysterectomy.
Source: Placenta
Authors: Fengying Chen, Dazhi Fan, Rufang Chen, Ying Zhang, Gan Tian, Donghua Zhou, Haojie Ning, Dawei Zhang, Shuixing Zhang
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,720
Awards: G1051926703, G8075961798
OpenAlex ID: W4409261189
