2023
DOI: 10.1016/j.acra.2022.04.008
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Differentiation of Lung Metastases Originated From Different Primary Tumors Using Radiomics Features Based on CT Imaging

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Cited by 9 publications
(6 citation statements)
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“…The model developed by the group ultimately achieved a robust predictive capability (validation area under the curve: 0.922) 31 . This approach also has promises in further radiographically discriminating PM from primary lung tumors 34,35 …”
Section: Discussionmentioning
confidence: 95%
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“…The model developed by the group ultimately achieved a robust predictive capability (validation area under the curve: 0.922) 31 . This approach also has promises in further radiographically discriminating PM from primary lung tumors 34,35 …”
Section: Discussionmentioning
confidence: 95%
“…33 31 This approach also has promises in further radiographically discriminating PM from primary lung tumors. 34,35 There are limitations associated with this work. First, the review of characteristics was performed in a retrospective manner, and thus bias may be present, despite our databases being prospectively maintained.…”
Section: Discussionmentioning
confidence: 99%
“…Shang et al [ 76 ] explored the role of radiomics to differentiate lung metastatic nodules from breast, colorectal and renal cancer by means of MDCT radiomics features. They performed a retrospective analysis including 252 LM from 78 patients, which were randomly divided into a training cohort ( n = 176) and a test cohort ( n = 76).…”
Section: Discussionmentioning
confidence: 99%
“…Three studies (37.5%) [ 55 , 56 , 68 ] evaluated the potential applicability of radiomics models in a clinical setting by means of DCA. In most studies (75%) [ 71 , 72 , 74 , 75 , 76 , 77 ] multiple segmentations were performed to evaluate the robustness of radiomics features in relation to segmentation variability.…”
Section: Discussionmentioning
confidence: 99%
“…However, there are currently few percutaneous puncture procedure path planning systems specifically designed for pulmonary masses. Most systems require interaction with clinicians for semi-automatic path selection (Cifci 2023, Mkindu et al 2023, Shang et al 2023.…”
Section: Introductionmentioning
confidence: 99%