Aims and objectives: Testing the effectiveness of CT perfusion parameters computed on liver in patients with colorectal cancer and no liver metastases at baseline to discriminate those who will develop liver metastases within three years from diagnosis. Methods and materials: 55 patients with colorectal cancer, free from liver metastases and any known hepatic disease, underwent axial CTp examinations of liver at colorectal cancer diagnosis. Six of those patients developed liver metastases within the first three years from diagnosis. Perfusion parameters were computed on selected Regions of Interest (ROI) assuming a dual-input one-compartment model. Several statistical and texture features built on top of the main parameter values were selected for this study. An unsupervised classification algorithm was used on single and coupled features to assess their capability to discriminate the two groups of patients. Results: 4 patients who develop liver metastases resulted to be clearly separated by the remaining patients. In particular two patients were detected by 5 coupled features, and 1 patient by even 6 couples. Two coupled features managed to separate the three other patients. Most of the features were related to hepatic perfusion index (HPI). Conclusion: The importance of these, still preliminary, results is twofold. First, HPI is a promising candidate as a prognostic biomarker for metastases development. Second, a multitude of statistical parameters is able to discriminate the two patients groups. This outcome prompts to consider more patients, possibly from different Centres, to finally select at least one feature that could be considered for validation as a prognostic biomarker.
CT perfusion of liver in patients with colorectal cancer allows discriminating patients who will develop liver metastases
Alessandro Bevilacqua;Margherita Mottola;
2019
Abstract
Aims and objectives: Testing the effectiveness of CT perfusion parameters computed on liver in patients with colorectal cancer and no liver metastases at baseline to discriminate those who will develop liver metastases within three years from diagnosis. Methods and materials: 55 patients with colorectal cancer, free from liver metastases and any known hepatic disease, underwent axial CTp examinations of liver at colorectal cancer diagnosis. Six of those patients developed liver metastases within the first three years from diagnosis. Perfusion parameters were computed on selected Regions of Interest (ROI) assuming a dual-input one-compartment model. Several statistical and texture features built on top of the main parameter values were selected for this study. An unsupervised classification algorithm was used on single and coupled features to assess their capability to discriminate the two groups of patients. Results: 4 patients who develop liver metastases resulted to be clearly separated by the remaining patients. In particular two patients were detected by 5 coupled features, and 1 patient by even 6 couples. Two coupled features managed to separate the three other patients. Most of the features were related to hepatic perfusion index (HPI). Conclusion: The importance of these, still preliminary, results is twofold. First, HPI is a promising candidate as a prognostic biomarker for metastases development. Second, a multitude of statistical parameters is able to discriminate the two patients groups. This outcome prompts to consider more patients, possibly from different Centres, to finally select at least one feature that could be considered for validation as a prognostic biomarker.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
