ArticleWorld journal of hepatology2022
Can the computed tomography texture analysis of colorectal liver metastases predict the response to first-line cytotoxic chemotherapy?
Article in World journal of hepatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Radiomic signatures from baseline CT predict chemotherapy response in unresectable colorectal liver metastases.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Preoperative assessment of grade, T stage, and lymph node involvement: machine learning-based CT texture analysis in colon cancer.Japanese journal of radiology · 2024Article
- Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment.La Radiologia medica · 2023Article
- Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics.Infectious agents and cancer · 2023Review
- Role of advanced imaging techniques in the evaluation of oncological therapies in patients with colorectal liver metastases.World journal of gastroenterology · 2023Review
- Magnetic Resonance Features of Liver Mucinous Colorectal Metastases: What the Radiologist Should Know.Journal of clinical medicine · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
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Abstract
backgroundArtificial intelligence in radiology has the potential to assist with the diagnosis, prognostication and therapeutic response prediction of various cancers. A few studies have reported that texture analysis can be helpful in predicting the response to chemotherapy for colorectal liver metastases, however, the results have varied. Necrotic metastases were not clearly excluded in these studies and in most studies the full range of texture analysis features were not evaluated. This study was designed to determine if the computed tomography (CT) texture analysis results of non-necrotic colorectal liver metastases differ from previous reports. A larger range of texture features were also evaluated to identify potential new biomarkers.
aimTo identify potential new imaging biomarkers with CT texture analysis which can predict the response to first-line cytotoxic chemotherapy in non-necrotic colorectal liver metastases (CRLMs).
methodsPatients who presented with CRLMs from 2012 to 2020 were retrospectively selected on the institutional radiology information system of our private radiology practice. The inclusion criteria were non-necrotic CRLMs with a minimum size of 10 mm (diagnosed on archived 1.25 mm portal venous phase CT scans) which were treated with standard first-line cytotoxic chemotherapy (FOLFOX, FOLFIRI, FOLFOXIRI, CAPE-OX, CAPE-IRI or capecitabine). The final study cohort consisted of 29 patients. The treatment response of the CRLMs was classified according to the RECIST 1.1 criteria. By means of CT texture analysis, various first and second order texture features were extracted from a single non-necrotic target CRLM in each responding and non-responding patient. Associations between features and response to chemotherapy were assessed by logistic regression models. The prognostic accuracy of selected features was evaluated by using the area under the curve.
resultsThere were 15 responders (partial response) and 14 non-responders (7 stable and 7 with progressive disease). The responders presented with a higher number of CRLMs (
conclusionEight first and second order texture features, but particularly minimum histogram gradient intensity and long run low grey level emphasis are significantly correlated with treatment response in non-necrotic CRLMs.
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