Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas?

Marius Horger, Petra Fallier-Becker, Wolfgang M. Thaiss, Alexander Sauter, Hans Bösmüller, Manuela Martella, Heike Preibsch, Jan Fritz, Konstantin Nikolaou, Christopher Kloth

Research output: Contribution to journalArticle

Abstract

Rationale and Objectives: This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics. Materials and Methods: Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28–74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m2), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness. Results: Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BFdeconvolution (P =.047, r = 0.418) and additionally was significantly associated with higher mean BVdeconvolution (P <.005). Mean k-transPatlak correlated strongly with mean k-transdeconvolution (r = 0.939, P =.001), and both correlated with mean BFdeconvolution (P =.001, r = 0.748), max BFdeconvolution (P =.028, r = 0.564), mean BVdeconvolution (P =.001, r = 0.752), and max BVdeconvolution (P =.001, r = 0.771). Microvessel density correlated with max k-transdeconvolution (r = 0.564, P =.023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-transPatlak (P =.041, r = 0.686) and mean BFdeconvolution (P =.038, r = 0.695). Conclusion: k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs.

Original languageEnglish (US)
JournalAcademic Radiology
DOIs
StateAccepted/In press - Jan 1 2018

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Lymphoma
Perfusion
Tomography
Microvessels
Pericytes
Tight Junctions
Basement Membrane
Extracellular Matrix
Vascular Endothelial Growth Factor Receptor-3
Research Ethics Committees
Blood Volume
Electron Microscopy
Prospective Studies
Staining and Labeling
Biopsy

Keywords

  • endothelial fenestrations
  • Immunohistochemical staining
  • lymphoma
  • Perfusion CT
  • ultrastructural microvessel features

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas? / Horger, Marius; Fallier-Becker, Petra; Thaiss, Wolfgang M.; Sauter, Alexander; Bösmüller, Hans; Martella, Manuela; Preibsch, Heike; Fritz, Jan; Nikolaou, Konstantin; Kloth, Christopher.

In: Academic Radiology, 01.01.2018.

Research output: Contribution to journalArticle

Horger, Marius ; Fallier-Becker, Petra ; Thaiss, Wolfgang M. ; Sauter, Alexander ; Bösmüller, Hans ; Martella, Manuela ; Preibsch, Heike ; Fritz, Jan ; Nikolaou, Konstantin ; Kloth, Christopher. / Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas?. In: Academic Radiology. 2018.
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abstract = "Rationale and Objectives: This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics. Materials and Methods: Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28–74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m2), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness. Results: Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BFdeconvolution (P =.047, r = 0.418) and additionally was significantly associated with higher mean BVdeconvolution (P <.005). Mean k-transPatlak correlated strongly with mean k-transdeconvolution (r = 0.939, P =.001), and both correlated with mean BFdeconvolution (P =.001, r = 0.748), max BFdeconvolution (P =.028, r = 0.564), mean BVdeconvolution (P =.001, r = 0.752), and max BVdeconvolution (P =.001, r = 0.771). Microvessel density correlated with max k-transdeconvolution (r = 0.564, P =.023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-transPatlak (P =.041, r = 0.686) and mean BFdeconvolution (P =.038, r = 0.695). Conclusion: k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs.",
keywords = "endothelial fenestrations, Immunohistochemical staining, lymphoma, Perfusion CT, ultrastructural microvessel features",
author = "Marius Horger and Petra Fallier-Becker and Thaiss, {Wolfgang M.} and Alexander Sauter and Hans B{\"o}sm{\"u}ller and Manuela Martella and Heike Preibsch and Jan Fritz and Konstantin Nikolaou and Christopher Kloth",
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T1 - Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas?

AU - Horger, Marius

AU - Fallier-Becker, Petra

AU - Thaiss, Wolfgang M.

AU - Sauter, Alexander

AU - Bösmüller, Hans

AU - Martella, Manuela

AU - Preibsch, Heike

AU - Fritz, Jan

AU - Nikolaou, Konstantin

AU - Kloth, Christopher

PY - 2018/1/1

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N2 - Rationale and Objectives: This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics. Materials and Methods: Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28–74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m2), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness. Results: Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BFdeconvolution (P =.047, r = 0.418) and additionally was significantly associated with higher mean BVdeconvolution (P <.005). Mean k-transPatlak correlated strongly with mean k-transdeconvolution (r = 0.939, P =.001), and both correlated with mean BFdeconvolution (P =.001, r = 0.748), max BFdeconvolution (P =.028, r = 0.564), mean BVdeconvolution (P =.001, r = 0.752), and max BVdeconvolution (P =.001, r = 0.771). Microvessel density correlated with max k-transdeconvolution (r = 0.564, P =.023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-transPatlak (P =.041, r = 0.686) and mean BFdeconvolution (P =.038, r = 0.695). Conclusion: k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs.

AB - Rationale and Objectives: This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics. Materials and Methods: Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28–74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m2), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness. Results: Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BFdeconvolution (P =.047, r = 0.418) and additionally was significantly associated with higher mean BVdeconvolution (P <.005). Mean k-transPatlak correlated strongly with mean k-transdeconvolution (r = 0.939, P =.001), and both correlated with mean BFdeconvolution (P =.001, r = 0.748), max BFdeconvolution (P =.028, r = 0.564), mean BVdeconvolution (P =.001, r = 0.752), and max BVdeconvolution (P =.001, r = 0.771). Microvessel density correlated with max k-transdeconvolution (r = 0.564, P =.023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-transPatlak (P =.041, r = 0.686) and mean BFdeconvolution (P =.038, r = 0.695). Conclusion: k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs.

KW - endothelial fenestrations

KW - Immunohistochemical staining

KW - lymphoma

KW - Perfusion CT

KW - ultrastructural microvessel features

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