Radiomics in Carotid Plaque: A Systematic Review and Radiomics Quality Score Assessment

Hou, Chao; Liu, Xin-Yao; Du, Yue; Cheng, Ling-Gang; Liu, Lu-Ping; Nie, Fang; Zhang, Wei; He, Wen

doi:10.1016/j.ultrasmedbio.2023.06.008

Cited by 3 publications

(3 citation statements)

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“…Given the status of radiomics in methodological and clinical validation, the evaluation of cost-effectiveness may be perceived to be less urgent ( 18 , 45 ). However, cost-effectiveness analysis can assess the value of radiomics predictive models in health economics when applied clinically ( 19 , 64 ). New models with comparable prediction power should not be more expensive than pre-existing ones.…”

Section: Discussionmentioning

confidence: 99%

“…A rigorous and transparent study process accompanied by standardized reporting can improve the reproducibility and reliability of radiomics models. Several recent studies have attempted to evaluate the prediction power and the methodological quality of radiomics models based on the radiomics quality score (RQS) tool ( 18 , 19 ), assessing the risk of bias using the Prediction Model Risk of Bias Assessment Tool (PROBAST) ( 20 ) and investigating the report quality of the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Diagnosis) checklist ( 21 ). In our previous study, radiomics models for CAS had low RQS scores ( 19 ); however, there are no published results concerning the use of PROBAST or TRIPOD for CAS.…”

Section: Introductionmentioning

confidence: 99%

“…Several recent studies have attempted to evaluate the prediction power and the methodological quality of radiomics models based on the radiomics quality score (RQS) tool ( 18 , 19 ), assessing the risk of bias using the Prediction Model Risk of Bias Assessment Tool (PROBAST) ( 20 ) and investigating the report quality of the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Diagnosis) checklist ( 21 ). In our previous study, radiomics models for CAS had low RQS scores ( 19 ); however, there are no published results concerning the use of PROBAST or TRIPOD for CAS. Therefore, in this review, we aimed to analyze the current status of radiomics research related to diagnosing and/or predicting CAS by combining these three above-mentioned tools (TRIPOD, PROBAST, and RQS) to evaluate their scientific reporting quality, risk of bias, and radiomics methodological quality.…”

Section: Introductionmentioning

confidence: 99%

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Quality assessment of radiomics models in carotid plaque: a systematic review

Hou,

Li,

Zheng

et al. 2024

Quant Imaging Med Surg

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Background Although imaging techniques provide information about the morphology and stability of carotid plaque, they are operator dependent and may miss certain subtleties. A variety of radiomics models for carotid plaque have recently been proposed for identifying vulnerable plaques and predicting cardiovascular and cerebrovascular diseases. The purpose of this review was to assess the risk of bias, reporting, and methodological quality of radiomics models for carotid atherosclerosis plaques. Methods A systematic search was carried out to identify available literature published in PubMed, Web of Science, and the Cochrane Library up to March 2023. Studies that developed and/or validated machine learning models based on radiomics data to identify and/or predict unfavorable cerebral and cardiovascular events in carotid plaque were included. The basic information of each piece of included literature was identified, and the reporting quality, risk of bias, and radiomics methodology quality were assessed according the TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) checklist, the Prediction Model Risk of Bias Assessment Tool (PROBAST), and the radiomics quality score (RQS), respectively. Results A total of 2,738 patients from 19 studies were included. The mean overall TRIPOD adherence rate was 66.1% (standard deviation 12.8%), with a range of 45–87%. All studies had a high overall risk of bias, with the analysis domain being the most common source of bias. The mean RQS was 9.89 (standard deviation 5.70), accounting for 27.4% of the possible maximum value of 36. The mean area under the curve for diagnostic or predictive properties of these included radiomics models was 0.876±0.09, with a range of 0.741–0.989. Conclusions Radiomics models may have value in the assessment of carotid plaque, the overall scientific validity and reporting quality of current carotid plaque radiomics reports are still lacking, and many barriers must be overcome before these models can be applied in clinical practice.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quality assessment of radiomics models in carotid plaque: a systematic review

Hou,

Li,

Zheng

et al. 2024

Quant Imaging Med Surg

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Atherosclerotic carotid artery disease Radiomics: A systematic review with meta-analysis and radiomic quality score assessment

Vacca,

Scicolone,

Gupta

et al. 2024

European Journal of Radiology

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Management of carotid atherosclerosis in stroke

Evans,

Bhakta,

Chowdhury

et al. 2024

Pract Neurol

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Internal carotid artery atherosclerosis is a major risk factor for stroke, accounting for 15–20% of ischaemic strokes. Revascularisation procedures—either carotid endarterectomy or carotid artery stenting—can reduce the risk of stroke for those with significant (>50%) luminal stenosis but particularly for those with more severe (70–99%) stenosis. However, advances in medical pharmacotherapy have implications for the relative benefit from surgery for symptomatic carotid atherosclerosis, as well as our approach to asymptomatic disease. This review considers the evidence underpinning the current medical and surgical management of symptomatic carotid atherosclerosis, the importance of factors beyond the degree of luminal stenosis, and developments in therapeutic strategies. We also discuss the importance of non-stenotic but high-risk carotid atherosclerotic plaques on the cause of stroke, and their implications for clinical practice.

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Radiomics in Carotid Plaque: A Systematic Review and Radiomics Quality Score Assessment

Cited by 3 publications

References 56 publications

Quality assessment of radiomics models in carotid plaque: a systematic review

Quality assessment of radiomics models in carotid plaque: a systematic review

Atherosclerotic carotid artery disease Radiomics: A systematic review with meta-analysis and radiomic quality score assessment

Management of carotid atherosclerosis in stroke

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