Placenta accreta scoring system (PASS)—assessment of a simplified clinico-radiological scoring system for antenatal diagnosis of placenta accreta

Author:

Mahalingam Harsha VardhanORCID,Rangasami Rajeswaran,Premkumar J.,Chandrasekar Anupama

Abstract

Abstract Background Placenta accreta spectrum (PAS) of disorders is an important cause of post-partum hemorrhage and resultant maternal morbidity and mortality. Imaging plays an indispensable role in antenatal diagnosis of PAS. However, diagnosis of PAS on both ultrasonography and magnetic resonance imaging (MRI) is reliant on recognition of multiple imaging signs each of which have a wide range of sensitivity and specificity. There is no single pathognomonic diagnostic feature. This results in interobserver variability. In our study, we aim to assess the accuracy of a combined clinico-radiological scoring system in predicting placenta accreta. Results This retrospective study included 60 MRI examinations done for suspected placenta accreta (PA). MRI findings were assessed by two radiologists in consensus. Clinical details of the patients were obtained from the hospital information system. Two clinical and six imaging criteria were assessed and a total score was calculated for each patient. Patients were stratified into three groups—low, moderate or high probability for placenta accreta based on the total score. The presence of any statistically significant difference in prevalence of PA among these groups was assessed. Intra-operative findings/histopathology were considered the gold standard. The prevalence of PA was 3% (1/33), 28.5% (2/7) and 90% (18/20) in the low-, moderate- and high-risk groups respectively. There was a statistically significant difference in the prevalence between the three groups (chi-square statistic = 41.54, p value < 0.0001). A score of greater than or equal to 6 provided sensitivity, specificity and accuracy of 85.71, 94.87 and 92.5% respectively in diagnosing placenta accreta. Conclusion PASS provides a simple, objective and accurate way to stratify patients into low, intermediate and high probability categories for PA.

Publisher

Springer Science and Business Media LLC

Subject

Radiology Nuclear Medicine and imaging

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