Objective: To assess the impact on absolute values and reproducibility of adding portal venous (PV) to arterial input functions in computed tomographic perfusion (CTp) evaluations of liver tumors and normal liver.
Methods: Institutional review board approval and written informed consent were obtained; the study complied with Health Insurance Portability and Accountability Act regulations. Computed tomographic perfusion source data sets, obtained from 7 patients (containing 9 liver tumors) on 2 occasions, 2 to 7 days apart, were analyzed by deconvolution modeling using dual (“Liver” protocol: PV and aorta) and single (“Body” protocol: aorta only) vascular inputs. Identical tumor, normal liver, aortic and, where applicable, PV regions of interest were used in corresponding analyses to generate tissue blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability (PS) values. Test-retest variability was assessed by within-patient coefficients of variation.
Results: For liver tumor and normal liver, median BF, BV, and PS were significantly higher for the Liver protocol than for the Body protocol: 171.3 to 177.8 vs 39.4 to 42.0 mL/min per 100 g, 17.2 to 18.7 vs 3.1 to 4.2 mL/100 g, and 65.1 to 78.9 vs 50.4 to 66.1 mL/min per 100 g, respectively (P < 0.01 for all). There were no differences in MTT between protocols. Within-patient coefficients of variation were lower for all parameters with the Liver protocol than with the Body protocol: BF, 7.5% to 11.2% vs 11.7% to 20.8%; BV, 10.1% to 14.4% vs 16.6% to 30.1%; MTT, 4.2% to 5.5% vs 10.4% to 12.9%; and PS, 7.3% to 12.1% vs 12.6% to 20.3%, respectively.
Conclusion: Utilization of dual vascular input CTp liver analyses has substantial impact on absolute CTp parameter values and test-retest variability. Incorporation of the PV inputs may yield more precise results; however, it imposes substantial practical constraints on acquiring the necessary data.
From the Departments of *Diagnostic Radiology, †Imaging Physics, The University of Texas MD Anderson Cancer Center; ‡CT research, GE Healthcare, Waukesha, WI; Departments of §Biostatistics, and ∥Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX.
Received for publication February 9, 2012; accepted March 21, 2012.
Reprints: Chaan S. Ng, MD, Department of Diagnostic Radiology, Unit 1473, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX 77030-4009 (e-mail: email@example.com).
The authors report no conflicts of interest.