OBJECTIVE: To prospectively analyze the correlation between quantitative parameters of perfusion derived from dynamic contrast-enhanced CT (DCE-CT) and contrast-enhanced ultrasound (DCE-US) in patients with malignant liver tumors. MATERIALS AND METHODS: Thirty patients (mean age: 59.4 ± 12.3 years) with primary malignant liver tumors or hepatic metastases of various origin underwent DCE-CT (4D spiral mode, scan range, 14.8 cm; 15 scans; cycle time, 3 seconds) and DCE-US (low mechanical index, <0.1, 2.4 mL microbubbles). DCE-CT and DCE-US images were evaluated by 2 radiologists regarding quantitative perfusion parameters including arterial liver perfusion (ALP), portal-venous perfusion (PVP), and total perfusion (P = ALP + PVP) from DCE-CT, as well as blood inflow velocity (B) and the normalized slope within the calculation range (CVan) from DCE-US. RESULTS: Quantitative assessment was possible with DCE-CT in 12/30 (40%) patients before and in all patients after automated motion correction. With DCE-US, quantitative assessment could not be performed in 9/30 (30.0%) patients due to respiratory motion. Interreader agreements for quantitative perfusion analysis were good with DCE-CT (r = 0.640-0.892, each P < 0.001) and DCE-US (r = 0.761-0.909, each P < 0.001). Moderate significant correlations were found between the perfusion parameters from DCE-CT (P, ALP) and DCE-US (B, CVan) (r = 0.446-0.621, each P < 0.05). No significant correlations were found between PVP from CT and perfusion parameters from DCE-US (B, CVan; each P = nonsignificant). CONCLUSIONS: Quantitative evaluation of DCE-CT data was feasible in all patients after automated motion correction, whereas DCE-US data could not be quantitatively evaluated in 30% of patients due to respiratory motion and lack of motion correction software. Quantitative arterial perfusion analysis showed moderate significant correlations for blood flow parameters among modalities.
OBJECTIVE: To prospectively analyze the correlation between quantitative parameters of perfusion derived from dynamic contrast-enhanced CT (DCE-CT) and contrast-enhanced ultrasound (DCE-US) in patients with malignant liver tumors. MATERIALS AND METHODS: Thirty patients (mean age: 59.4 ± 12.3 years) with primary malignant liver tumors or hepatic metastases of various origin underwent DCE-CT (4D spiral mode, scan range, 14.8 cm; 15 scans; cycle time, 3 seconds) and DCE-US (low mechanical index, <0.1, 2.4 mL microbubbles). DCE-CT and DCE-US images were evaluated by 2 radiologists regarding quantitative perfusion parameters including arterial liver perfusion (ALP), portal-venous perfusion (PVP), and total perfusion (P = ALP + PVP) from DCE-CT, as well as blood inflow velocity (B) and the normalized slope within the calculation range (CVan) from DCE-US. RESULTS: Quantitative assessment was possible with DCE-CT in 12/30 (40%) patients before and in all patients after automated motion correction. With DCE-US, quantitative assessment could not be performed in 9/30 (30.0%) patients due to respiratory motion. Interreader agreements for quantitative perfusion analysis were good with DCE-CT (r = 0.640-0.892, each P < 0.001) and DCE-US (r = 0.761-0.909, each P < 0.001). Moderate significant correlations were found between the perfusion parameters from DCE-CT (P, ALP) and DCE-US (B, CVan) (r = 0.446-0.621, each P < 0.05). No significant correlations were found between PVP from CT and perfusion parameters from DCE-US (B, CVan; each P = nonsignificant). CONCLUSIONS: Quantitative evaluation of DCE-CT data was feasible in all patients after automated motion correction, whereas DCE-US data could not be quantitatively evaluated in 30% of patients due to respiratory motion and lack of motion correction software. Quantitative arterial perfusion analysis showed moderate significant correlations for blood flow parameters among modalities.
Authors: Andrew B Gill; Nicholas J Hilliard; Simon T Hilliard; Martin J Graves; David J Lomas; Ashley Shaw Journal: Br J Radiol Date: 2017-06-20 Impact factor: 3.039
Authors: Michael Winterdahl; Michael Sørensen; Susanne Keiding; Frank V Mortensen; Aage K O Alstrup; Søren B Hansen; Ole L Munk Journal: Invest Radiol Date: 2012-10 Impact factor: 6.016