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Liver Perfusion Imaging in Patients with Primary and Metastatic Liver Malignancy

Rationale and Objectives

To prospectively analyze the correlation between parameters of liver perfusion from technetium 99m -macroaggregates of albumin ( 99m Tc-MAA) single photon emission computed tomography (SPECT) with those obtained from dynamic CT perfusion in patients with primary or metastatic liver malignancy.

Materials and Methods

Twenty-five consecutive patients (11 women, 14 men; mean age 60.9 ± 10.8; range: 32–78 years) with primary ( n = 5) or metastatic ( n = 20) liver malignancy planned to undergo selective internal radiotherapy underwent dynamic contrast-enhanced CT liver perfusion imaging (four-dimensional spiral mode, scan range 14.8 cm, 15 scans, cycle time 3 seconds) and 99m Tc-MAA SPECT after intraarterial injection of 180 MBq 99m Tc–MAA on the same day. Data were evaluated by two blinded and independent readers for the parameters arterial liver perfusion (ALP), portal venous perfusion (PVP), and total liver perfusion (TLP) from CT, and the 99m Tc-MAA uptake-ratio of tumors in relation to normal liver parenchyma from SPECT.

Results

Interreader agreements for quantitative perfusion parameters were high for dynamic CT ( r = 0.90–0.98, each P < .01) and 99m Tc -MAA SPECT ( r = 0.91, P < .01). Significant correlation was found between 99m Tc-MAA uptake ratio and ALP ( r = 0.7, P < .01) in liver tumors. No significant correlation was found between 99m Tc-MAA uptake ratio, PVP ( r = −0.381, P = .081), and TLP ( r = 0.039, P = .862).

Conclusion

This study indicates that in patients with primary and metastatic liver malignancy, ALP obtained by dynamic CT liver perfusion significantly correlates with the 99m Tc-MAA uptake ratio obtained by SPECT.

Selective internal radiotherapy (SIRT) with radioembolization of yttrium-90 ( 90 Y) microspheres is a catheter-based, liver-directed therapy that has gained recent acceptance for the treatment of primary and metastatic liver malignancies not qualifying for surgery . 90 Y microspheres are selectively injected via the hepatic artery and preferentially flow into tumor areas with a high arterial vascularization , whereas normal liver parenchyma, which is predominantly perfused over the portal venous system, is not affected . This allows administration of high radiation doses to tumors, whereas radiation exposure of normal liver parenchyma remains tolerably low.

To assess distribution of radiolabeled microspheres and to minimize side effects resulting from microsphere deposition in normal liver parenchyma, the lung, or the gastrointestinal tract, an angiography study is routinely performed before SIRT, and a tracer dose of technetium 99m -labeled macroaggregates of albumin ( 99m Tc-MAA) is injected via the hepatic artery with the catheter tip in treatment position to simulate the distribution of the therapeutic agent . Immediately after angiography, a single photon emission computed tomography (SPECT) is performed showing the distribution of 99m Tc-MAA particles, which demonstrates perfusion patterns of the normal and diseased liver parenchyma and indicates potential shunting to the lung and gastrointestinal tract .

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Material and methods

Patient Population

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Table 1

Patient Demographics

Characteristics No. of Patients (%) Mean age, mean ± SD (range, years) 60.9 ± 10.8 (32–78) Gender, M/F 11/14 Body mass index, mean ± SD (range, kg/m 2 ) 27.4 ± 5.3 (18.7–34.1) Primary liver malignancy 5 (20%) Hepatocellular carcinoma 3 Intrahepatic cholangiocarcinoma 1 Epithelioid hemangioendothelioma 1 Secondary liver malignancy 20 (80%) Colorectal cancer 9 Extrahepatic cholangiocarcinoma 2 Breast cancer 2 Pancreatic adenocarcinoma 1 Gastric adenocarcinoma 1 Melanoma 1 Sarcoma 1 Renal cell cancer 1 Non-small-cell lung cancer 1 Anal squamous cell carcinoma 1 Number of liver tumors 1–4 lesions 8 (32%) 7 or 8 lesions 2 (8%) >10 lesions 15 (60%) Previous therapy Surgery 7 (28%) Chemotherapy 15 (60%) Ongoing chemotherapy 2 (8%) VEGF-antibody treatment 2 (8%) Radiofrequency ablation 2 (8%) Transarterial chemoembolization 1 (4%) Portal vein ligation or embolization 3 (12%)

F, female; M, male; SD, standard deviation; VEGF, vascular endothelial growth factor.

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CT Data Acquisition

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Catheter Angiography

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99m Tc-MAA Scintigraphy

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Image Analysis

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Figure 1, A 52-year-old female patient with multiple liver metastases originating from rectal cancer. Fusion of (a) technetium 99m -macroaggregates of albumin single photon emission computed tomography and (b) dynamic computed tomography perfusion images for better correlation of liver tumors and placement of volumes of interest (c) .

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99m Tc-MAA SPECT Images

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Figure 2, Technetium 99m -macroaggregates of albumin single photon emission computed tomography images (a,b) and maximum intensity projection images over time of dynamic computed tomography perfusion (c,d) in axial and coronal plane with volumes of interest placed in the liver tumor and in normal liver parenchyma.

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CT Perfusion Images

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Figure 3, Screenshot of the applied body perfusion software with axial maximum intensity projection images over time (a) with the region of interest set in the portal vein and the spleen and the corresponding input curves (b) . The perfusion color maps show arterial (c) and portal-venous liver perfusion (d) .

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Statistical Analysis

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Results

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99m Tc-MAA SPECT and CT Perfusion Measurements

Interreader agreement

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Table 2

Interreader Variability of Semiquantitative and Quantitative 99m Tc-MAA SPECT and Dynamic CT Perfusion Measurements

Mean Difference Range of Mean Difference Correlation 99m Tc-MAA SPECT 99m Tc-MAA uptake ratio 0.81 ± 1.64 −3.78, 3.76 0.91 ( P < .001) CT perfusion ALP T 0.28 ± 3.15 −7.09, 8.49 0.98 ( P < .001) PVP T −0.61 ± 12.58 −21.67, 34.04 0.91 ( P < .001) TLP T −0.26 ± 10.79 −18.71, 31.42 0.94 ( P < .001) ALP L 0.56 ± 2.23 −4.55, 5.19 0.95 ( P < .001) PVP L 3.63 ± 13.34 −9.29, 46.83 0.90 ( P < .001) TLP L 4.17 ± 12.37 −7.87, 42.71 0.95 ( P < .001)

99m Tc-MAA, technetium 99m -macroaggregates of albumin; ALP T and L , arterial liver perfusion in liver tumor and normal liver (in mL × min −1 × 100 mL −1 ); PVP T and L , portal-venous perfusion in liver tumor and normal liver (in mL × min −1 × 100 mL −1 ); SPECT, single photon emission computerized tomography; TLP T and L , total liver perfusion in liver tumor and normal liver (= ALP+PVP, in mL × min −1 × 100 mL −1 ).

Mean difference ± standard deviation.

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VOI sizes among modalities

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99m Tc-MAA SPECT parameters

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Table 3

Liver Perfusion Parameters from 99m Tc-MAA SPECT and from Dynamic CT Perfusion

Mean ± SD Range_P_ Values 99m Tc-MAA uptake ratio 6.00 ± 3.65 1.64–14.33 ALP Liver tumor 26.25 ± 15.88 3.34–73.96 <.001 Normal liver 11.60 ± 7.20 3.77–34.54 PVP Liver tumor 43.66 ± 27.97 0.02–107.55 <.001 Normal liver 73.79 ± 28.05 25.62–125.81 TLP Liver tumor 64.67 ± 30.05 18.96–142.14 <.05 Normal liver 86.06 ± 26.68 40.81–136.27

99m Tc-MAA uptake ratio, averaged technetium 99m -macroaggregates of albumin uptake tumor/averaged 99m Tc-MAA uptake liver; ALP, arterial liver perfusion (mL × min −1 × 100 mL −1 ); PVP, portal-venous perfusion (mL × min −1 × 100 mL −1 ); SD, standard deviation; TLP, total liver perfusion (mL × min −1 × 100 mL −1 ).

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CT perfusion parameters

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Correlation between 99m Tc-MAA SPECT and dynamic CT perfusion

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Figure 4, Scatter plots of technetium 99m -macroaggregates of albumin uptake ratio versus arterial liver perfusion in liver tumors (ALP T ) (a) and portal-venous perfusion in liver tumors (PVP T ) (b) .

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Discussion

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Acknowledgment

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References

  • 1. Jakobs T.F., Hoffmann R.T., Poepperl G., et. al.: Mid-term results in otherwise treatment refractory primary or secondary liver confined tumours treated with selective internal radiation therapy (SIRT) using (90)Yttrium resin-microspheres. Eur Radiol 2007; 17: pp. 1320-1330.

  • 2. Dancey J.E., Shepherd F.A., Paul K., et. al.: Treatment of nonresectable hepatocellular carcinoma with intrahepatic 90Y-microspheres. J Nucl Med 2000; 41: pp. 1673-1681.

  • 3. Dudeck O., Zeile M., Wybranski C., et. al.: Early prediction of anticancer effects with diffusion-weighted MR imaging in patients with colorectal liver metastases following selective internal radiotherapy. Eur Radiol 2010; 20: pp. 2699-2706.

  • 4. Campbell A.M., Bailey I.H., Burton M.A.: Analysis of the distribution of intra-arterial microspheres in human liver following hepatic yttrium-90 microsphere therapy. Phys Med Biol 2000; 45: pp. 1023-1033.

  • 5. Leen E., Goldberg J.A., Anderson J.R., et. al.: Hepatic perfusion changes in patients with liver metastases: comparison with those patients with cirrhosis. Gut 1993; 34: pp. 554-557.

  • 6. Bledin A.G., Kim E.E., Chuang V.P., et. al.: Changes of arterial blood flow patterns during infusion chemotherapy, as monitored by intra-arterially injected technetium 99m macroaggregated albumin. Br J Radiol 1984; 57: pp. 197-203.

  • 7. Bilbao J.I., de Martino A., de Luis E., et. al.: Biocompatibility, inflammatory response, and recannalization characteristics of nonradioactive resin microspheres: histological findings. Cardiovasc Intervent Radiol 2009; 32: pp. 727-736.

  • 8. Flamen P., Vanderlinden B., Delatte P., et. al.: Multimodality imaging can predict the metabolic response of unresectable colorectal liver metastases to radioembolization therapy with Yttrium-90 labeled resin microspheres. Phys Med Biol 2008; 53: pp. 6591-6603.

  • 9. Ho S., Lau W.Y., Leung T.W., et. al.: Tumour-to-normal uptake ratio of 90Y microspheres in hepatic cancer assessed with 99Tcm macroaggregated albumin. Br J Radiol 1997; 70: pp. 823-828.

  • 10. Knesaurek K., Machac J., Muzinic M., et. al.: Quantitative comparison of yttrium-90 (90Y)-microspheres and technetium-99m (99mTc)-macroaggregated albumin SPECT images for planning 90Y therapy of liver cancer. Technol Cancer Res Treat 2010; 9: pp. 253-262.

  • 11. Miles K.A., Hayball M.P., Dixon A.K.: Functional images of hepatic perfusion obtained with dynamic CT. Radiology 1993; 188: pp. 405-411.

  • 12. Haberland U., Klotz E., Abolmaali N.: Performance assessment of dynamic spiral scan modes with variable pitch for quantitative perfusion computed tomography. Invest Radiol 2010; 45: pp. 378-386.

  • 13. Goetti R., Leschka S., Desbiolles L., et. al.: Quantitative computed tomography liver perfusion imaging using dynamic spiral scanning with variable pitch: feasibility and initial results in patients with cancer metastases. Invest Radiol 2010; 45: pp. 419-426.

  • 14. Meijerink M.R., van Waesberghe J.H., van der Weide L., et. al.: Early detection of local RFA site recurrence using total liver volume perfusion CT initial experience. Acad Radiol 2009; 16: pp. 1215-1222.

  • 15. Ippolito D., Sironi S., Pozzi M., et. al.: Hepatocellular carcinoma in cirrhotic liver disease: functional computed tomography with perfusion imaging in the assessment of tumor vascularization. Acad Radiol 2008; 15: pp. 919-927.

  • 16. Fournier L.S., Oudard S., Thiam R., et. al.: Metastatic renal carcinoma: evaluation of antiangiogenic therapy with dynamic contrast-enhanced CT. Radiology 2010; 256: pp. 511-518.

  • 17. Chen Y., Zhang J., Dai J., et. al.: Angiogenesis of renal cell carcinoma: perfusion CT findings. Abdom Imaging 2010; 35: pp. 622-628.

  • 18. Goh V., Halligan S., Wellsted D.M., et. al.: Can perfusion CT assessment of primary colorectal adenocarcinoma blood flow at staging predict for subsequent metastatic disease? A pilot study. Eur Radiol 2009; 19: pp. 79-89.

  • 19. Chen G., Ma D.Q., He W., et. al.: Computed tomography perfusion in evaluating the therapeutic effect of transarterial chemoembolization for hepatocellular carcinoma. World J Gastroenterol 2008; 14: pp. 5738-5743.

  • 20. Saddi KA, Chefd’hotel C, Cheriet F. Large deformation registration of contrast-enhanced images with volume-preserving constraint. In: Pluim JPW, Reinhard JM, eds. Medical Imaging 2007: Image Processing. Bellingham, WA: Proceedings of The International Society for Optical Engineering (SPIE), 2007.

  • 21. Blomley M.J., Coulden R., Dawson P., et. al.: Liver perfusion studied with ultrafast CT. J Comput Assist Tomogr 1995; 19: pp. 424-433.

  • 22. Tsushima Y., Funabasama S., Aoki J., et. al.: Quantitative perfusion map of malignant liver tumors, created from dynamic computed tomography data. Acad Radiol 2004; 11: pp. 215-223.

  • 23. Hamami M.E., Poeppel T.D., Muller S., et. al.: SPECT/CT with 99mTc-MAA in radioembolization with 90Y microspheres in patients with hepatocellular cancer. J Nucl Med 2009; 50: pp. 688-692.

  • 24. Ahmadzadehfar H., Sabet A., Biermann K., et. al.: The significance of 99mTc-MAA SPECT/CT liver perfusion imaging in treatment planning for 90Y-microsphere selective internal radiation treatment. J Nucl Med 2010; 51: pp. 1206-1212.

  • 25. Gyves J.W., Ziessman H.A., Ensminger W.D., et. al.: Definition of hepatic tumor microcirculation by single photon emission computerized tomography (SPECT). J Nucl Med 1984; 25: pp. 972-977.

  • 26. Goldberg J.A., Bradnam M.S., Kerr D.J., et. al.: Single photon emission computed tomographic studies (SPECT) of hepatic arterial perfusion scintigraphy (HAPS) in patients with colorectal liver metastases: improved tumour targetting by microspheres with angiotensin II. Nucl Med Commun 1987; 8: pp. 1025-1032.

  • 27. Ho S., Lau W.Y., Leung T.W., et. al.: Partition model for estimating radiation doses from yttrium-90 microspheres in treating hepatic tumours. Eur J Nucl Med 1996; 23: pp. 947-952.

  • 28. Bilbao J.I., Garrastachu P., Herraiz M.J., et. al.: Safety and efficacy assessment of flow redistribution by occlusion of intrahepatic vessels prior to radioembolization in the treatment of liver tumors. Cardiovasc Intervent Radiol 2010; 33: pp. 523-531.

  • 29. Veit-Haibach P., Treyer V., Strobel K., et. al.: Feasibility of integrated CT-liver perfusion in routine FDG-PET/CT. Abdom Imaging 2010; 35: pp. 528-536.

  • 30. Cuenod C., Leconte I., Siauve N., et. al.: Early changes in liver perfusion caused by occult metastases in rats: detection with quantitative CT. Radiology 2001; 218: pp. 556-561.

  • 31. Breedis C., Young G.: The blood supply of neoplasms in the liver. Am J Pathol 1954; 30: pp. 969-977.

  • 32. Kandel S., Kloeters C., Meyer H., et. al.: Whole-organ perfusion of the pancreas using dynamic volume CT in patients with primary pancreas carcinoma: acquisition technique, post-processing and initial results. Eur Radiol 2009; 19: pp. 2641-2646.

  • 33. Youn S.W., Kim J.H., Weon Y.C., et. al.: Perfusion CT of the brain using 40-mm-wide detector and toggling table technique for initial imaging of acute stroke. AJR Am J Roentgenol 2008; 191: pp. W120-W126.

  • 34. Helck A., Sommer W.H., Klotz E., et. al.: Determination of glomerular filtration rate using dynamic CT-angiography: simultaneous acquisition of morphological and functional information. Invest Radiol 2010; 45: pp. 387-392.

  • 35. Goh V., Liaw J., Bartram C.I., et. al.: Effect of temporal interval between scan acquisitions on quantitative vascular parameters in colorectal cancer: implications for helical volumetric perfusion CT techniques. AJR Am J Roentgenol 2008; 191: pp. W288-W292.

  • 36. Goh V., Dattani M., Farwell J., et. al.: Radiation dose from volumetric helical perfusion CT of the thorax, abdomen or pelvis. Eur Radiol 2011; 21: pp. 974-981.

  • 37. Kierkels R.G., Backes W.H., Janssen M.H., et. al.: Comparison between perfusion computed tomography and dynamic contrast-enhanced magnetic resonance imaging in rectal cancer. Int J Radiat Oncol Biol Phys 2010; 77: pp. 400-408.

  • 38. Goetti R., Reiner C.S., Knuth A., et. al.: Quantitative perfusion analysis of malignant liver tumors: dynamic computed tomography and contrast-enhanced ultrasound. Invest Radiol 2012; 47: pp. 18-24.

  • 39. Kapanen M., Halavaara J., Hakkinen A.M.: Comparison of liver perfusion parameters studied with conventional extravascular and experimental intravascular CT contrast agents. Acad Radiol 2007; 14: pp. 951-958.

  • 40. Leung W.T., Lau W.Y., Ho S.K., et. al.: Measuring lung shunting in hepatocellular carcinoma with intrahepatic-arterial technetium-99m macroaggregated albumin. J Nucl Med 1994; 35: pp. 70-73.

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