ArticleAbdominal radiology (New York)2021
Prediction of placenta accreta spectrum using texture analysis on coronal and sagittal T2-weighted imaging.
Article in Abdominal radiology (New York), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of MRI-Based Radiomics in Diagnosis of Placenta Accreta Spectrum: A PRISMA Systematic Review and Meta-Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2024Pooled it
- A nomogram based on MR radiomics and MR sign score for prenatal diagnosis of placenta accreta spectrum disorders and risk assessment of adverse clinical outcomes.Abdominal radiology (New York) · 2026Article
- Increased intra-myometrial vascularity adds diagnostic value to MRI for high-risk placenta accreta spectrum.Scientific reports · 2025Article
- Deep Learning-Assisted Diagnosis of Placenta Accreta Spectrum Using the DenseNet-121 Model: A Multicenter, Retrospective Study.Journal of imaging informatics in medicine · 2025Article
- Magnetic Resonance Imaging-Based Radiomics of Axial and Sagittal Orientation in Pregnant Patients with Suspected Placenta Accreta Spectrum.Academic radiology · 2025Article
- Magnetic Resonance Imaging Texture Analysis Based on Intraosseous and Extraosseous Lesions to Predict Prognosis in Patients with Osteosarcoma.Diagnostics (Basel, Switzerland) · 2024Article
- Placental T2WI MRI-based radiomics-clinical nomogram predicts suspicious placenta accreta spectrum in patients with placenta previa.BMC medical imaging · 2024Article
- Application of Texture and Volume Model Analysis to Dedicated Axillary High-resolution 3D T2-weighted MR Imaging: A Novel Method for Diagnosing Lymph Node Metastasis in Patients with Clinically Node-negative Breast Cancer.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Article
- Prediction of placenta accreta spectrum by combining deep learning and radiomics using T2WI: a multicenter study.Abdominal radiology (New York) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo separately perform visual and texture analyses of the axial, coronal, and sagittal planes of T2-weighted images and identify the optimal method for differentiating between the normal placenta and placenta accreta spectrum (PAS).
methodsEighty consecutive patients (normal group, n = 50; PAS group, n = 30) underwent preoperative MRI. A scoring system (0-2) was used to evaluate the degree of abnormality observed in visual analysis (bulging, abnormal vascularity, T2 dark band, placental heterogeneity). The axial, coronal, and sagittal planes were manually segmented separately to obtain texture features, and seven combinations were obtained: axial; coronal; sagittal; axial and coronal; axial and sagittal; coronal and sagittal; and axial, coronal, and sagittal. Feature selection using the least absolute shrinkage and selection operator method and model construction using a support vector machine algorithm with k-fold cross-validation were performed. AUC was used to evaluate diagnostic performance.
resultsThe AUC of visual analysis was 0.75. The model 'coronal and sagittal' had the highest AUC (0.98) amongst the seven combinations. The fivefold cross-validation for the model 'coronal and sagittal' showed AUCs of 0.85 and 0.97 in training and validation sets, respectively. The AUC of the model 'coronal and sagittal' for all subjects was significantly higher than that of visual analysis (0.98 vs. 0.75; p < 0.0001).
conclusionThe model 'coronal and sagittal' can accurately differentiate between the normal placenta and PAS, with a significantly better diagnostic performance than visual analysis. Texture analysis is an optimal method for differentiating between the normal placenta and PAS.
Indexed as
Identifiers
34331104What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.