Ultrasound Radiomics Correlating With Clinical Markers for Enhanced Detection of Placenta Accreta Spectrum
Bibliographic record
Abstract
OBJECTIVES: (i) To develop an accurate and robust ultrasound-based quantitative index for placenta accreta spectrum (PAS) diagnosis by amalgamating texture features from B-mode and color Doppler imaging. (ii) To test the correlation of this index with established sonographic markers for PAS. METHODS: In this retrospective study, we collected 2106 texture features extracted from the midsagittal placental view of mid-trimester B-mode and Doppler ultrasound images. These images were acquired during ultrasound examinations conducted between 24 and 34 wk gestation from patients diagnosed with placenta previa and at least one prior uterine surgery risk factor for PAS at a tertiary center in Toronto, Canada. Three distinct models were developed: one using B-mode data (n = 174), another using color Doppler data (n = 98), and a third integrating both modalities (n = 98). Integrated features, derived from weighted z-scores, were employed to generate a quantitative index for detecting PAS. A feature selection pipeline was implemented, combining linear discriminant analysis, extra trees regression and recursive feature elimination. The pipeline identified 15-feature subsets for both B-mode and Doppler models, and a 20-feature subset for the multimodal model, both of which were used for training. The predictive performance of each model (presence/absence of PAS) was assessed using five-fold cross-validation and tested on a separate hold-out test set. Subsequently, the optimized quantitative metrics were examined for any statistically significant correlations with established sonographic clinical markers. RESULTS: The five-fold cross-validation accuracies across the developed B-mode, color Doppler and multimodal models were 88.7% (±5.3), 85.1% (±9.1) and 90% (±6.7), respectively. All eight of the clinical disease markers evaluated from each ultrasound image were determined to be discriminative of the quantitative index generated from B-mode and multimodal models, and six of the eight markers were discriminative of the index generated from Doppler alone. CONCLUSION: Combined B-mode and Doppler ultrasound-based radiomics can accurately detect PAS in patients with placenta previa and provide a surgical risk factor for PAS using simple and computationally inexpensive operations. The rank correlations between B-mode and color Doppler quantitative indices and their corresponding clinical markers highlight that this multimodal approach captures crucial diagnostic information that may be missed by individual models. All models exhibit notably higher accuracy than projected clinical standards and suggest their potential as aids for clinical decision-making at routine mid-trimester scans.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".