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2023 article

Assessment of Hidden Blood Loss in Spinal Metastasis Surgery: A Comprehensive Approach with MRI ‐Based Radiomics Models

6Citations signalées, ce qui n’est pas une note de qualité
2Institutions déclarées
1Pays d’affiliation déclarés

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Le résumé fourni par la source

BACKGROUND: Patients undergoing surgery for spinal metastasis are predisposed to hidden blood loss (HBL), which is associated with poor surgical outcomes but unpredictable. PURPOSE: To evaluate the role of MRI-based radiomics models for assess the risk of HBL in patients undergoing spinal metastasis surgery. STUDY TYPE: Retrospective. SUBJECTS: 202 patients (42.6% female) operated on for spinal metastasis with a mean age of 58 ± 11 years were divided into a training (n = 162) and a validation cohort (n = 40). FIELD STRENGTH/SEQUENCE: 1.5T or 3.0T scanners. Sagittal T1-weighted and fat-suppressed T2-weighted imaging sequences. ASSESSMENT: HBL was calculated using the Gross formula. Patients were classified as low and high HBL group, with 1000 mL as the threshold. Radiomics models were constructed with radiomics features. The radiomics score (Radscore) was obtained from the optimal radiomics model. Clinical variables were accessed using univariate and multivariate logistic regression analyses. Independent risk variables were used to build a clinical model. Clinical variables combined with Radscore were used to establish a combined model. STATISTICAL TESTS: Predictive performance was evaluated using area under the curve (AUC), accuracy, sensitivity, specificity, and F1 score. Calibration curves and decision curves analyses were produced to evaluate the accuracy and clinical utility. RESULTS: Among the radiomics models, the fusion (T1WI + FS-T2WI) model demonstrated the highest predictive efficacy (AUC: 0.744, 95% confidence interval [CI]: 0.576-0.914). The Radscore model (AUC: 0.809, 95% CI: 0.664-0.954) performs slightly better than the clinical model (AUC: 0.721, 95% CI: 0.524-0.918; P = 0.418) and the combined model (AUC: 0.752, 95% CI: 0.593-0.911; P = 0.178). DATA CONCLUSION: A radiomics model may serve as a promising assessment tool for the risk of HBL in patients undergoing spinal metastasis surgery, and guide perioperative planning to improve surgical outcomes. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé, mais le titre doit être comparé manuellement.

Titre Crossref
Assessment of Hidden Blood Loss in Spinal Metastasis Surgery: A Comprehensive Approach with <scp>MRI</scp>‐Based Radiomics Models
Date Crossref
14/08/2023
Éditeur
Wiley
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Où se fait cette recherche

  • Peking University Department of Radiology pays non établi dans la notice
    Université ou école supérieure
  • Peking University Third Hospital pays non établi dans la notice
    Établissement de santé

Department of Radiology — Peking University et Peking University Third Hospital.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Radiomics and Machine Learning in Medical ImagingManagement of metastatic bone diseaseAdvanced X-ray and CT Imaging

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