OBJECTIVES: To examine whether dynamic contrast-enhanced CT (DCE-CT) could be used to characterise and safely distinguish between malignant and benign lung tumours in patients with suspected lung cancer. METHODS: Using a quantitative approach to DCE-CT, two separate sets of regions of interest (ROIs) in tissues were placed in each tumour: large ROIs over the entire tumour and small ROIs over the maximally perfused parts of the tumour. Using mathematical modelling techniques and dedicated perfusion software, this yielded a plethora of results. RESULTS: First, because of their non-normal distribution, DCE-CT measurements must be analysed using log scale data transformation. Second, there were highly significant differences between large ROI and small ROI measurements (p<0.001). Thus, the ROI method used in a given study should always be specified in advance. Third, neither quantitative parameters (blood flow and blood volume) nor semi-quantitative parameters (peak enhancement) could be used to distinguish between malignant and benign tumours. This was irrespective of the method of quantification used for large ROIs (0.13<p<0.76) and small ROIs (0.084<p<0.31). Fourth, although there were no indications of systematic reproducibility bias, the 95% limits of agreement were so broad that the risk of disagreement between the measurements could affect the clinical use of the measurements. This lack of reproducibility should be addressed. CONCLUSION AND ADVANCES IN KNOWLEDGE: A quantitative approach to DCE-CT is not a clinically usable method for characterising lung tumours.
OBJECTIVES: To examine whether dynamic contrast-enhanced CT (DCE-CT) could be used to characterise and safely distinguish between malignant and benign lung tumours in patients with suspected lung cancer. METHODS: Using a quantitative approach to DCE-CT, two separate sets of regions of interest (ROIs) in tissues were placed in each tumour: large ROIs over the entire tumour and small ROIs over the maximally perfused parts of the tumour. Using mathematical modelling techniques and dedicated perfusion software, this yielded a plethora of results. RESULTS: First, because of their non-normal distribution, DCE-CT measurements must be analysed using log scale data transformation. Second, there were highly significant differences between large ROI and small ROI measurements (p<0.001). Thus, the ROI method used in a given study should always be specified in advance. Third, neither quantitative parameters (blood flow and blood volume) nor semi-quantitative parameters (peak enhancement) could be used to distinguish between malignant and benign tumours. This was irrespective of the method of quantification used for large ROIs (0.13<p<0.76) and small ROIs (0.084<p<0.31). Fourth, although there were no indications of systematic reproducibility bias, the 95% limits of agreement were so broad that the risk of disagreement between the measurements could affect the clinical use of the measurements. This lack of reproducibility should be addressed. CONCLUSION AND ADVANCES IN KNOWLEDGE: A quantitative approach to DCE-CT is not a clinically usable method for characterising lung tumours.
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