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Prognostic Value of Ct Scan-Based Radiomics in Intracerebral Hemorrhage Patients: A Systematic Review and Meta-Analysis Publisher Pubmed



Hajiesmailpoor Z1 ; Kargar Z1 ; Baradaran M2 ; Shojaeshafiei F3 ; Tabnak P1 ; Mandalou L1 ; Klontzas ME4, 5 ; Shahidi R6
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Authors Affiliations
  1. 1. Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
  2. 2. Department of Radiology, Imam Ali Hospital, North Khorasan University of Medical Science, Bojnurd, Iran
  3. 3. Department of Radiology, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Department of Medical Imaging, University Hospital of Heraklion, Crete, Heraklion, 71110, Greece
  5. 5. Department of Radiology, School of Medicine, University of Crete, Crete, Heraklion, 71003, Greece
  6. 6. School of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran

Source: European Journal of Radiology Published:2024


Abstract

Objectives: We conducted a systematic review and meta-analysis of current publications on the potential role of non-contrast-enhanced computed tomography (NCCT) radiomics as a prognostic indicator in patients with intracerebral hemorrhage (ICH). Methods: We systematically searched PubMed, EMBASE, and the Web of Science from inception until January 8, 2024. Studies with NCCT-based radiomics features for predicting the prognostic outcomes of ICH patients were included. We calculated the pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under curve (AUC) values. The radiomics quality score (RQS), METhodological RadiomICs Score (METRICS), and the quality assessment of diagnostic accuracy studies (QUADAS-2) were used for quality assessment. Results: Twenty-two studies were included. The pooled sensitivity, specificity, DOR, and AUC of radiomics models were 0.73, 0.78, 10.03, and 0.83, respectively, while on the combined radiomics models with other non-radiomics features were 0.80, 0.80, 16.28, and 0.86. Subgroup analysis showed that studies with the following covariates have a higher accuracy: single center, modified Rankin Scale (mRS) criteria for the ICH outcomes assessment, following patients for evaluation of ICH outcomes for more than a month, automatic segmentation, capturing the radiomics feature from the only intra-hematomal region, using PyRadiomic tool for features extraction, and using non-logistic regression for modeling. The quality of literature using QUADAS-2 and METRICS tools was good and was under-average using the RQS tool. No publication bias was detected. Conclusions: Radiomics features showed moderate to high accuracy for predicting ICH prognostic outcomes. Although the QUADAS-2 and METRICS assessments indicated good quality, the radiomics pipeline quality was under-average. Clinical Relevance: NCCT-based radiomics features can provide information about the prognostic outcomes of ICH patients after patient admission. This study exploits the value of current evidence on NCCT-based radiomics methodology in the prediction of ICH prognosis. © 2024 Elsevier B.V.
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