PURPOSE: The aim of this study was to systematically analyze the correlation between computed tomography (CT) perfusion and histopathological angiogenic and prognostic markers in patients with renal cell carcinoma (RCC). MATERIAL AND METHODS: Fifteen patients (12 men; mean age, 64.5 ± 9.4 years) with RCC underwent contrast-enhanced CT perfusion imaging (scan range, 10 cm; scan time, 40 seconds; dual-source 128-section CT) 1 day before surgery. The procedure for surgical specimen processing was modified to obtain an exact match with CT images. Microvessel density (MVD) was quantified by CD34 staining, and lymphatic vessel density (LVD) was stained with D2-40 antibodies. The CT perfusion values blood flow (BF), blood volume (BV), and flow extraction product (K(Trans)) were calculated using the maximum-slope and a delay-corrected modified Patlak approach and were correlated to MVD and LVD. The relationship between CT perfusion and the prognostic markers pT stage, Fuhrman grade, and tumor necrosis was evaluated. RESULTS: Histopathology revealed varying high MVD but low or absent intratumoral LVD. The BF and BV of RCC, both including and excluding necrotic regions, showed significant correlations with MVD (r = 0.600-0.829, P < 0.05 each). Significant correlations between MVD and K(Trans) were found only in small tumor areas exhibiting no necrosis (r = 0.550, P < 0.05). No significant correlation was found between BF, BV, and K(Trans) with intratumoral LVD (P = 0.35-0.82). With higher pT stage and Fuhrman grade, BF, BV, and K(Trans) were lower, similar to the MVD, but without reaching statistical significance. Blood flow, BV, and K(Trans) were significantly higher in RCCs with less than 50% necrosis than in those with 50% or grater necrosis (P < 0.05 each). CONCLUSION: Our study indicates that BF and BV from CT perfusion reflect blood vessels of RCC. Computed tompgraphic perfusion parameters differ significantly depending upon the degree of tumor necrosis.
PURPOSE: The aim of this study was to systematically analyze the correlation between computed tomography (CT) perfusion and histopathological angiogenic and prognostic markers in patients with renal cell carcinoma (RCC). MATERIAL AND METHODS: Fifteen patients (12 men; mean age, 64.5 ± 9.4 years) with RCC underwent contrast-enhanced CT perfusion imaging (scan range, 10 cm; scan time, 40 seconds; dual-source 128-section CT) 1 day before surgery. The procedure for surgical specimen processing was modified to obtain an exact match with CT images. Microvessel density (MVD) was quantified by CD34 staining, and lymphatic vessel density (LVD) was stained with D2-40 antibodies. The CT perfusion values blood flow (BF), blood volume (BV), and flow extraction product (K(Trans)) were calculated using the maximum-slope and a delay-corrected modified Patlak approach and were correlated to MVD and LVD. The relationship between CT perfusion and the prognostic markers pT stage, Fuhrman grade, and tumor necrosis was evaluated. RESULTS: Histopathology revealed varying high MVD but low or absent intratumoral LVD. The BF and BV of RCC, both including and excluding necrotic regions, showed significant correlations with MVD (r = 0.600-0.829, P < 0.05 each). Significant correlations between MVD and K(Trans) were found only in small tumor areas exhibiting no necrosis (r = 0.550, P < 0.05). No significant correlation was found between BF, BV, and K(Trans) with intratumoral LVD (P = 0.35-0.82). With higher pT stage and Fuhrman grade, BF, BV, and K(Trans) were lower, similar to the MVD, but without reaching statistical significance. Blood flow, BV, and K(Trans) were significantly higher in RCCs with less than 50% necrosis than in those with 50% or grater necrosis (P < 0.05 each). CONCLUSION: Our study indicates that BF and BV from CT perfusion reflect blood vessels of RCC. Computed tompgraphic perfusion parameters differ significantly depending upon the degree of tumor necrosis.
Authors: Michael A Fischer; Bart Vrugt; Hatem Alkadhi; Dieter Hahnloser; Thomas F Hany; Patrick Veit-Haibach Journal: Eur J Nucl Med Mol Imaging Date: 2014-04-24 Impact factor: 9.236
Authors: Brooks D Lindsey; Sarah E Shelton; K Heath Martin; Kathryn A Ozgun; Juan D Rojas; F Stuart Foster; Paul A Dayton Journal: Ann Biomed Eng Date: 2016-11-10 Impact factor: 3.934
Authors: Andrew J Gunn; Benjamin J Mullenbach; May M Poundstone; Jennifer B Gordetsky; Edgar S Underwood; Soroush Rais-Bahrami Journal: Diagn Interv Radiol Date: 2018-11 Impact factor: 2.630