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1.
Br J Radiol ; 2024 Aug 17.
Artigo em Inglês | MEDLINE | ID: mdl-39152998

RESUMO

OBJECTIVE: We previously demonstrated the potential of radiomics for prediction of severe histological Placenta Accreta Spectrum (PAS) subtypes using T2-weighted MRI. We aim is to validate our model using an additional dataset. Secondly, we explore whether performance is improved using a new approach to develop a new multivariate radiomics model. METHODS: Multi-centre retrospective analysis conducted between 2018-2023. Inclusion criteria: MRI performed for suspicion of PAS from ultrasound, clinical findings of PAS at laparotomy and/or histopathological confirmation. Radiomic features were extracted from T2-weighted MRI. The previous multivariate model was validated. Secondly, a 5-radiomic feature random forest classifier was selected from a randomised feature selection scheme to predict invasive placenta increta PAS cases. Prediction performance was assessed based on several metrics including Area Under the Curve (AUC) of the receiver operating characteristic curve (ROC), sensitivity and specificity. RESULTS: We present 100 women (mean age 34.6 (±3.9) with PAS, 64 of whom had placenta increta. Firstly, we validated the previous multivariate model and found a Support Vector Machine classifier had a sensitivity of 0.620 (95% CI: 0.068; 1.0), specificity of 0.619 (95% CI: 0.059; 1.0), an AUC of 0.671 (95% CI: 0.440; 0.922) and accuracy of 0.602 (95% CI: 0.353; 0.817) for predicting placenta increta. From the new multivariate model, the best 5-feature subset selected via the random subset feature selection scheme comprised of 4 radiomic features and 1 clinical variable (number of previous caesareans). This clinical-radiomic model achieved an AUC of 0.713 (95% CI: 0.551; 0.854), accuracy of 0.695 (95% CI 0.563; 0.793), sensitivity of 0.843 (95% CI 0.682; 0.990) and specificity of 0.447 (95% CI 0.167; 0.667). CONCLUSION: We validated our previous model and present a new multivariate radiomic model for prediction of severe placenta increta from a well-defined, cohort of PAS cases. ADVANCES IN KNOWLEDGE: Radiomic features demonstrate good predictive potential for identifying placenta increta. This suggests radiomics may be a useful adjunct to clinicians caring for women with this high-risk pregnancy condition.

2.
Artigo em Inglês | MEDLINE | ID: mdl-39045676

RESUMO

Placenta accreta spectrum (PAS) is a relatively new obstetric condition which, until recently, was poorly understood. The true incidence is unknown because of the poor quality and heterogeneous diagnostic criteria. Classification systems have attempted to provide clarity on how to grade and diagnose PAS, but these are no longer reflective of our current understanding of PAS. This is particularly true for placenta percreta, which referred to extrauterine disease, as recent studies have demonstrated that placental villi associated with PAS have minimal potential to invade beyond the uterine serosa. It is accepted that PAS is a direct consequence of previous iatrogenic uterine injury, most commonly a previous cesarean section. Here, we "look back to look forwards"-starting with the primary predisposing factor for PAS, an iatrogenic uterine injury and subsequent wound healing. We then consider the evolution of definitions and diagnostic criteria of PAS from its first description over a century ago to current classifications. Finally, we discuss why modifications to the current classifications are needed to allow accurate diagnosis of this rare but life-threatening complication, while avoiding overdiagnosis and potential patient harm.

3.
J Clin Pathol ; 2024 Aug 02.
Artigo em Inglês | MEDLINE | ID: mdl-38555103

RESUMO

AIMS: This study aimed to re-evaluate the incidence of hydatidiform mole (HM) and determine gestational trophoblastic disease (GTD) registration rates in Ireland following the establishment of the National GTD Registry in 2017. METHODS: We performed a 3-year retrospective audit of HM cases (January 2017 to December 2019) reported in our centre. In 2019, we surveyed Irish pathology laboratories to determine the number of HMs diagnosed nationally and compared this data to that recorded in the National GTD Registry. Additionally, we compared both local and national HM incidence rates to those reported internationally. RESULTS: In the 3-year local audit, we identified 87 HMs among 1856 products of conception (POCs) providing a local HM incidence rate of 3.92 per 1000 births. The 1-year pathology survey recorded 170 HMs in 6008 POCs, yielding a national incidence rate of 2.86 per 1000 births. Importantly, the local HM incidence rate exceeded the national incidence rate by 37% and the local partial HM incidence (1 in 296 births) was 64% higher than the nationally incidence rate (1 in 484 births). Notably, 42% of the HM and atypical POCs diagnosed nationally were not reported to the National GTD Registry. CONCLUSIONS: Our study reveals increased HM incidence rates both locally and nationally compared with previous Irish studies. The higher local PHM incidence may reflect more limited access to ploidy analysis in other pathology laboratories nationally. Significantly, almost half of the women with diagnosed or suspected HM were not registered with the National GTD Centre.

5.
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