ArticleEuropean radiology2019
Quantitative imaging features of pretreatment CT predict volumetric response to chemotherapy in patients with colorectal liver metastases.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advanced analytics and artificial intelligence in gastrointestinal cancer: a systematic review of radiomics predicting response to treatment.European journal of nuclear medicine and molecular imaging · 2021Pooled it
- Automated Radiomics Model for Preoperative Pancreatic Neuroendocrine Tumor Grade Prediction.Annals of surgical oncology · 2026Article
- Multi-Phasic CECT Peritumoral Radiomics Predict Treatment Response to Bevacizumab-Based Chemotherapy in RAS-Mutated Colorectal Liver Metastases.Bioengineering (Basel, Switzerland) · 2026Article
- Radiomic signatures from baseline CT predict chemotherapy response in unresectable colorectal liver metastases.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy.Annals of surgical oncology · 2024Article
- Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment.NPJ precision oncology · 2024Review
- Role of advanced imaging techniques in the evaluation of oncological therapies in patients with colorectal liver metastases.World journal of gastroenterology · 2023Review
- Analysis of Hepatic Artery Infusion (HAI) Chemotherapy Using Randomized Trials of Floxuridine (FUDR) for Colon Cancer Patients with Multiple Liver Metastases.Gastroenterology research and practice · 2022Article
- Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade.JCO clinical cancer informatics · 2021Article
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19 authors.
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Abstract
objectivesThis study investigates whether quantitative image analysis of pretreatment CT scans can predict volumetric response to chemotherapy for patients with colorectal liver metastases (CRLM).
methodsPatients treated with chemotherapy for CRLM (hepatic artery infusion (HAI) combined with systemic or systemic alone) were included in the study. Patients were imaged at baseline and approximately 8 weeks after treatment. Response was measured as the percentage change in tumour volume from baseline. Quantitative imaging features were derived from the index hepatic tumour on pretreatment CT, and features statistically significant on univariate analysis were included in a linear regression model to predict volumetric response. The regression model was constructed from 70% of data, while 30% were reserved for testing. Test data were input into the trained model. Model performance was evaluated with mean absolute prediction error (MAPE) and R
results157 patients were included, split into training (n = 110) and validation (n = 47) sets. MAPE from the multivariate linear regression model was 16.5% (R
conclusionQuantitative imaging features extracted from pretreatment CT are promising predictors of volumetric response to chemotherapy in patients with CRLM. Pretreatment predictors of response have the potential to better select patients for specific therapies. KEY POINTS: • Colorectal liver metastases (CRLM) are downsized with chemotherapy but predicting the patients that will respond to chemotherapy is currently not possible. • Heterogeneity and enhancement patterns of CRLM can be measured with quantitative imaging. • Prediction model constructed that predicts volumetric response with 20% error suggesting that quantitative imaging holds promise to better select patients for specific treatments.
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