Feasibility study of mean temporal phase images calculated from perfusion CT datasets onthe third-generation dual-source CT in the diagnosis of hepatocellular carcinoma_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

YU Xin ^1,2 , ZHENG Xingju ^1,2 , WANG Yuquan ^1,2 , ZHANG Xiaoyong ^1,2 , TANG Ying ^1,2 , ZHANG Yuan ^1,2 ,  WANG Rongpin ^1,2

1. Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang 550002, P. R. China;
2. Key Laboratory of Intelligent Medical Imaging Analysis and Accurate Diagnosis, Guiyang 550002, P. R. China;

Corresponding?author：

WANG Rongpin, Email: wangrongpin@126.com

Keywords：

CT perfusion; the third-generation dual-source CT; hepatocellular carcinoma

DOI：

10.7507/1007-9424.201804004

Video：

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Objective To explore the feasibility of mean temporal phase images calculated from perfusion CT datasets by using CT perfusion (CTP) of liver on the third-generation dual-source CT. Methods Twenty-two consecutive patients with suspected hepatocellular carcinoma were enrolled, we retrospectively compared objective and subjective image quality, leson detectability, and radiation dose between mean temporal arterial (mTA) and mean temporal portal venous (mTPV) images which calculated from perfusion CT datasets with conventional enhanced arterial and portal venous datasets. Results ① Image quality: compared with the conventional enhancement image, the standard deviation (SD) values of CTP images on liver (arterial phase), portal vein (arterial phase), and liver (portal vein phase) were lower (P<0.05); the signal-to-noise ratio (SNR) values of CTP images on aorta (arterial phase), portal vein (arterial phase), aorta (portal vein phase), and portal vein (portal vein phase) were all higher (P<0.05), the contrast-to-noise ratio (CNR) value of CTP images on aorta (arterial phase) was higher (P<0.05). ② The subjective image quality: the subjective image quality scores of CTP images (mTA and mTPV images) were higher when compared to responding conventional enhanced arterial and portal venous datasets (P<0.05). ③ The diagnostic efficiency: the CTP images and conventional enhancement images showed all the lesions, but the diagnostic efficiency images of CTP images was better than the conventional enhancement images, both on lesions of blood supply and lack of blood supply (P<0.05). Conclusions The image quality of mTA and mTPV datasets calculated from CTP datasets are non-inferior when compared to conventional enhanced arterial and portal venous acquisitions in patients with suspected hepatic lesions. Thus, CTP could be used as a stand-alone imaging technique without additionally performed conventional arterial and portal venous CT acquisitions.

Citation： YU Xin, ZHENG Xingju, WANG Yuquan, ZHANG Xiaoyong, TANG Ying, ZHANG Yuan, WANG Rongpin. Feasibility study of mean temporal phase images calculated from perfusion CT datasets onthe third-generation dual-source CT in the diagnosis of hepatocellular carcinoma. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2018, 25(8): 997-1003. doi: 10.7507/1007-9424.201804004 Copy

1.	Kartalis N, Brehmer K, Loizou L. Multi-detector CT: liver protocol and recent developments. Eur J Radiol, 2017, 97: 101-109.
2.	Kurucay M, Kloth C, Kaufmann S, et al. Multiparametric imaging for detection and characterization of hepatocellular carcinoma using gadoxetic acid-enhanced MRI and perfusion-CT: which parameters work bests? Cancer Imaging, 2017, 28, 17(1): 18.
3.	Guo M, Yu Y. Application of 128 slice 4D CT whole liver perfusion imaging in hepatic tumor. Cell Biochem Biophys, 2014, 70(1): 173-178.
4.	Lee DH, Lee JM, Klotz E, et al. Multiphasic Dynamic Computed Tomography Evaluation of Liver Tissue Perfusion Characteristics Using the Dual Maximum Slope Model in Patients With Cirrhosis and Hepatocellular Carcinoma: A Feasibility Study. Invest Radiol, 2016, 51(7): 430-434.
5.	Wang L, Fan J, Ding X, et al. Assessment of liver fibrosis in the early stages with perfusion CT. Int J Clin Exp Med, 2015, 8(9): 15276-15282.
6.	Rosenkrantz AB, Mendiratta-Lala M, Bartholmai BJ, et al. Clinical utility of quantitative imaging. Acad Radiol, 2015, 22(1): 33-49.
7.	Ippolito D, Sironi S, Pozzi M, et al. Perfusion CT in cirrhotic patients with early stage hepatocellular carcinoma: assessment of tumor-related vascularization. Eur J Radiol, 2010, 73(1): 148-152.
8.	Frampas E, Lassau N, Zappa M, et al. Advanced Hepatocellular Carcinoma: early evaluation of response to targeted therapy and prognostic value of Perfusion CT and Dynamic Contrast Enhanced-Ultrasound. Preliminary results. Eur J Radiol, 2013, 82(5): e205-e211.
9.	Popovic P, Leban A, Kregar K, et al. Computed Tomographic Perfusion Imaging for the Prediction of Response and Survival to Transarterial Chemoembolization of Hepatocellular Carcinoma. Radiol Oncol, 2017, 52(1): 14-22.
10.	Roberson PK, Shema SJ, Mundfrom DJ, et al. Analysis of paired Likert data: how to evaluate change and preference questions. Fam Med, 1995, 27(10): 671-675.
11.	Wang X, Henzler T, Gawlitza J, et al. Image quality of mean temporal arterial and mean temporal portal venous phase images calculated from low dose dynamic volume perfusion CT datasets in patients with hepatocellular carcinoma and pancreatic cancer. Eur J Radiol, 2016, 85(11): 2104-2110.
12.	Brix G, Lechel U, Veit R, et al. Assessment of a theoretical formalism for dose estimation in CT: an anthropomorphic phantom study. Eur Radiol, 2004, 14(7): 1275-1284.
13.	鄧錫佳, 劉愛連, 劉靜紅, 等. 寬體探測器 CT 胰腺軸位灌注" 一站式”成像的可行性. 中國醫學影像技術, 2017, 33(6): 938-943.
14.	Nakaura T, Kidoh M, Nakamura S, et al. Low-dose abdominal CT protocols with a tube voltage setting of 100 kVp or 80 kVp: Performance of radiation dose reduction and influence on visual contrast. Clin Radiol, 2014, 69(8): 804-811.
15.	Tang K, Wang L, Li R, et al. Effect of low tube voltage on image quality, radiation dose, and low-contrast detectability at abdominal multidetector CT: phantom study. J Biomed Biotechnol, 2012, 2012: 130-169.
16.	Lin CJ, Wu TH, Lin CH, et al. Can iterative reconstruction improve imaging quality for lower radiation CT perfusion? Initial experience. AJNR Am J Neuroradiol, 2013, 34(8): 1516-1521.
17.	楊嵐清, 余鑫, 張菁, 等. 低劑量 CT 灌注掃描定量評估近側胃癌可行性的初步研究. 中國普外基礎與臨床雜志, 2017, 24(8): 1014-1020.
18.	Niesten JM, van der Schaaf IC, Riordan AJ, et al. Radiation dose reduction in cerebral CT perfusion imaging using iterative reconstruction. Eur Radiol, 2014, 24(2): 484-493.
19.	Martin T, Hoffman J, Alger JR, et al. Low-dose CT perfusion with projection view sharing. Med Phys, 2018, 45(1): 101-113.
20.	Prezzi D, Goh V, Virdi S, et al. Adaptive statistical iterative reconstruction improves image quality without affecting perfusion CT quantitation in primary colorectal cancer. Eur J Radiol Open, 2017, 4: 69-74.
21.	Wu D, Tan M, Zhou M, et al. Impact of image denoising on image quality, quantitative parameters and sensitivity of ultra-low-dose volume perfusion CT imagings. Eur Radiol, 2016, 26(1): 167-174.
22.	Topcuo?lu OM, Kar?aalt?ncaba M, Akata D, et al. Reproducibility and variability of very low dose hepatic perfusion CT in metastatic liver disease. Diagn Interv Radiol, 2016, 22(6): 495-500.
23.	Djuric-Stefanovic A, Micev M, Stojanovic-Rundic S, et al. Absolute CT perfusion parameter values after the neoadjuvant chemoradiotherapy of the squamous cell esophageal carcinoma correlate with the histopathologic tumor regression grade. Eur J Radiol, 2015, 84(12): 2477-2484.
24.	Fischer MA, Leidner B, Kartalis N, et al. Time-resolved computed tomography of the liver: retrospective, multi-phase image reconstruction derived from volumetric perfusion imaging. Eur Radiol, 2014, 24(1): 151-161.
25.	Spargias K, Adreanides E, Demerouti E, et al. Iloprost prevents contrast-induced nephropathy in patients with renal dysfunction undergoing coronary angiography or intervention. Circulation, 2009, 120(18): 1793-1799.

1. Kartalis N, Brehmer K, Loizou L. Multi-detector CT: liver protocol and recent developments. Eur J Radiol, 2017, 97: 101-109.
2. Kurucay M, Kloth C, Kaufmann S, et al. Multiparametric imaging for detection and characterization of hepatocellular carcinoma using gadoxetic acid-enhanced MRI and perfusion-CT: which parameters work bests? Cancer Imaging, 2017, 28, 17(1): 18.
3. Guo M, Yu Y. Application of 128 slice 4D CT whole liver perfusion imaging in hepatic tumor. Cell Biochem Biophys, 2014, 70(1): 173-178.
4. Lee DH, Lee JM, Klotz E, et al. Multiphasic Dynamic Computed Tomography Evaluation of Liver Tissue Perfusion Characteristics Using the Dual Maximum Slope Model in Patients With Cirrhosis and Hepatocellular Carcinoma: A Feasibility Study. Invest Radiol, 2016, 51(7): 430-434.
5. Wang L, Fan J, Ding X, et al. Assessment of liver fibrosis in the early stages with perfusion CT. Int J Clin Exp Med, 2015, 8(9): 15276-15282.
6. Rosenkrantz AB, Mendiratta-Lala M, Bartholmai BJ, et al. Clinical utility of quantitative imaging. Acad Radiol, 2015, 22(1): 33-49.
7. Ippolito D, Sironi S, Pozzi M, et al. Perfusion CT in cirrhotic patients with early stage hepatocellular carcinoma: assessment of tumor-related vascularization. Eur J Radiol, 2010, 73(1): 148-152.
8. Frampas E, Lassau N, Zappa M, et al. Advanced Hepatocellular Carcinoma: early evaluation of response to targeted therapy and prognostic value of Perfusion CT and Dynamic Contrast Enhanced-Ultrasound. Preliminary results. Eur J Radiol, 2013, 82(5): e205-e211.
9. Popovic P, Leban A, Kregar K, et al. Computed Tomographic Perfusion Imaging for the Prediction of Response and Survival to Transarterial Chemoembolization of Hepatocellular Carcinoma. Radiol Oncol, 2017, 52(1): 14-22.
10. Roberson PK, Shema SJ, Mundfrom DJ, et al. Analysis of paired Likert data: how to evaluate change and preference questions. Fam Med, 1995, 27(10): 671-675.
11. Wang X, Henzler T, Gawlitza J, et al. Image quality of mean temporal arterial and mean temporal portal venous phase images calculated from low dose dynamic volume perfusion CT datasets in patients with hepatocellular carcinoma and pancreatic cancer. Eur J Radiol, 2016, 85(11): 2104-2110.
12. Brix G, Lechel U, Veit R, et al. Assessment of a theoretical formalism for dose estimation in CT: an anthropomorphic phantom study. Eur Radiol, 2004, 14(7): 1275-1284.
13. 鄧錫佳, 劉愛連, 劉靜紅, 等. 寬體探測器 CT 胰腺軸位灌注" 一站式”成像的可行性. 中國醫學影像技術, 2017, 33(6): 938-943.
14. Nakaura T, Kidoh M, Nakamura S, et al. Low-dose abdominal CT protocols with a tube voltage setting of 100 kVp or 80 kVp: Performance of radiation dose reduction and influence on visual contrast. Clin Radiol, 2014, 69(8): 804-811.
15. Tang K, Wang L, Li R, et al. Effect of low tube voltage on image quality, radiation dose, and low-contrast detectability at abdominal multidetector CT: phantom study. J Biomed Biotechnol, 2012, 2012: 130-169.
16. Lin CJ, Wu TH, Lin CH, et al. Can iterative reconstruction improve imaging quality for lower radiation CT perfusion? Initial experience. AJNR Am J Neuroradiol, 2013, 34(8): 1516-1521.
17. 楊嵐清, 余鑫, 張菁, 等. 低劑量 CT 灌注掃描定量評估近側胃癌可行性的初步研究. 中國普外基礎與臨床雜志, 2017, 24(8): 1014-1020.
18. Niesten JM, van der Schaaf IC, Riordan AJ, et al. Radiation dose reduction in cerebral CT perfusion imaging using iterative reconstruction. Eur Radiol, 2014, 24(2): 484-493.
19. Martin T, Hoffman J, Alger JR, et al. Low-dose CT perfusion with projection view sharing. Med Phys, 2018, 45(1): 101-113.
20. Prezzi D, Goh V, Virdi S, et al. Adaptive statistical iterative reconstruction improves image quality without affecting perfusion CT quantitation in primary colorectal cancer. Eur J Radiol Open, 2017, 4: 69-74.
21. Wu D, Tan M, Zhou M, et al. Impact of image denoising on image quality, quantitative parameters and sensitivity of ultra-low-dose volume perfusion CT imagings. Eur Radiol, 2016, 26(1): 167-174.
22. Topcuo?lu OM, Kar?aalt?ncaba M, Akata D, et al. Reproducibility and variability of very low dose hepatic perfusion CT in metastatic liver disease. Diagn Interv Radiol, 2016, 22(6): 495-500.
23. Djuric-Stefanovic A, Micev M, Stojanovic-Rundic S, et al. Absolute CT perfusion parameter values after the neoadjuvant chemoradiotherapy of the squamous cell esophageal carcinoma correlate with the histopathologic tumor regression grade. Eur J Radiol, 2015, 84(12): 2477-2484.
24. Fischer MA, Leidner B, Kartalis N, et al. Time-resolved computed tomography of the liver: retrospective, multi-phase image reconstruction derived from volumetric perfusion imaging. Eur Radiol, 2014, 24(1): 151-161.
25. Spargias K, Adreanides E, Demerouti E, et al. Iloprost prevents contrast-induced nephropathy in patients with renal dysfunction undergoing coronary angiography or intervention. Circulation, 2009, 120(18): 1793-1799.

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Feasibility study of mean temporal phase images calculated from perfusion CT datasets onthe third-generation dual-source CT in the diagnosis of hepatocellular carcinoma

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