Assessment of Tissue Perfusion of Pancreatic Cancer As Potential Imaging Biomarker by Means of Intravoxel Incoherent Motion MRI and CT Perfusion: Correlation with Histological Microvessel Density As Ground Truth

Overview

Journal Cancer Imaging

Publisher Springer Nature

Specialties Oncology
Radiology

Date 2021 Jan 20

PMID 33468259

Citations 11

Authors

Philipp Mayer

Franziska Fritz

Marco Koell

Stephan Skornitzke

Frank Bergmann

Matthias M Gaida

Thilo Hackert

Klaus Maier-Hein

Frederik B Laun

Hans-Ulrich Kauczor

Lars Grenacher

Miriam Klauss

Wolfram Stiller

Affiliations

Soon will be listed here.

Abstract

Background/objectives: The aim of this study was to compare intravoxel incoherent motion (IVIM) diffusion weighted (DW) MRI and CT perfusion to assess tumor perfusion of pancreatic ductal adenocarcinoma (PDAC).

Methods: In this prospective study, DW-MRI and CT perfusion were conducted in nineteen patients with PDAC on the day before surgery. IVIM analysis of DW-MRI was performed and the parameters perfusion fraction f, pseudodiffusion coefficient D*, and diffusion coefficient D were extracted for tumors, upstream, and downstream parenchyma. With a deconvolution-based analysis, the CT perfusion parameters blood flow (BF) and blood volume (BV) were estimated for tumors, upstream, and downstream parenchyma. In ten patients, intratumoral microvessel density (MVD) and microvessel area (MVA) were analyzed microscopically in resection specimens. Correlation coefficients between IVIM parameters, CT perfusion parameters, and histological microvessel parameters in tumors were calculated. Receiver operating characteristic (ROC) analysis was performed for differentiation of tumors and upstream parenchyma.

Results: f significantly positively correlated with BF (r = 0.668, p = 0.002) and BV (r = 0.672, p = 0.002). There were significant positive correlations between f and MVD/ MVA (r ≥ 0.770, p ≤ 0.009) as well as between BF and MVD/ MVA (r ≥ 0.697, p ≤ 0.025). Correlation coefficients between f and MVD/ MVA were not significantly different from correlation coefficients between BF and MVD/ MVA (p ≥ 0.400). Moreover, f, BF, BV, and permeability values (PEM) showed excellent performance in distinguishing tumors from upstream parenchyma (area under the ROC curve ≥0.874).

Conclusions: The study shows that IVIM derived f and CT perfusion derived BF similarly reflect vascularity of PDAC and seem to be comparably applicable for the evaluation of tumor perfusion for tumor characterization and as potential quantitative imaging biomarker.

Trial Registration: DRKS, DRKS00022227, Registered 26 June 2020, retrospectively registered. https://www.drks.de/drks_web/navigate.do?navigationId=trial . HTML&TRIAL_ID=DRKS00022227.

Citing Articles

A machine learning model based on preoperative multiparametric quantitative DWI can effectively predict the survival and recurrence risk of pancreatic ductal adenocarcinoma.

Qu C, Zeng P, Li C, Hu W, Yang D, Wang H Insights Imaging. 2025; 16(1):38.

PMID: 39962007 PMC: 11833029. DOI: 10.1186/s13244-025-01915-9.

The radiomorphological appearance of the invasive margin in pancreatic cancer is associated with tumor budding.

Mayer P, Hausen A, Steinle V, Bergmann F, Kauczor H, Loos M Langenbecks Arch Surg. 2024; 409(1):167.

PMID: 38809279 PMC: 11136832. DOI: 10.1007/s00423-024-03355-3.

Pancreatic CT perfusion: quantitative meta-analysis of disease discrimination, protocol development, and effect of CT parameters.

Skornitzke S, Vats N, Mayer P, Kauczor H, Stiller W Insights Imaging. 2023; 14(1):132.

PMID: 37477754 PMC: 10361925. DOI: 10.1186/s13244-023-01471-0.

Evaluation and timing optimization of CT perfusion first pass analysis in comparison to maximum slope model in pancreatic adenocarcinoma.

Vats N, Mayer P, Kortes F, Klauss M, Grenacher L, Stiller W Sci Rep. 2023; 13(1):10595.

PMID: 37391443 PMC: 10313720. DOI: 10.1038/s41598-023-37381-w.

Development and validation of a contrast-enhanced CT-based radiomics nomogram for preoperative diagnosis in neuroendocrine carcinoma of digestive system.

Xu L, Yang X, Xiang W, Hu P, Zhang X, Li Z Front Endocrinol (Lausanne). 2023; 14:1155307.

PMID: 37124722 PMC: 10130364. DOI: 10.3389/fendo.2023.1155307.

References

Niedergethmann M, Hildenbrand R, Wostbrock B, Hartel M, Sturm J, Richter A . High expression of vascular endothelial growth factor predicts early recurrence and poor prognosis after curative resection for ductal adenocarcinoma of the pancreas. Pancreas. 2002; 25(2):122-9. DOI: 10.1097/00006676-200208000-00002. View

Linnebacher A, Mayer P, Marnet N, Bergmann F, Herpel E, Revia S . Interleukin 21 Receptor/Ligand Interaction Is Linked to Disease Progression in Pancreatic Cancer. Cells. 2019; 8(9). PMC: 6770770. DOI: 10.3390/cells8091104. View

Li H, Sun C, Xu Z, Miao F, Zhang D, Chen J . Low-dose whole organ CT perfusion of the pancreas: preliminary study. Abdom Imaging. 2013; 39(1):40-7. DOI: 10.1007/s00261-013-0045-1. View

Ikeda N, Adachi M, Taki T, Huang C, Hashida H, Takabayashi A . Prognostic significance of angiogenesis in human pancreatic cancer. Br J Cancer. 1999; 79(9-10):1553-63. PMC: 2362700. DOI: 10.1038/sj.bjc.6690248. View

Song M, Yue Y, Jin Y, Guo J, Zuo L, Peng H . Intravoxel incoherent motion and ADC measurements for differentiating benign from malignant thyroid nodules: utilizing the most repeatable region of interest delineation at 3.0 T. Cancer Imaging. 2020; 20(1):9. PMC: 6977258. DOI: 10.1186/s40644-020-0289-2. View

Miles K . Perfusion CT for the assessment of tumour vascularity: which protocol?. Br J Radiol. 2004; 76 Spec No 1:S36-42. DOI: 10.1259/bjr/18486642. View

Alam M, Gaida M, Bergmann F, Lasitschka F, Giese T, Giese N . Selective inhibition of the p38 alternative activation pathway in infiltrating T cells inhibits pancreatic cancer progression. Nat Med. 2015; 21(11):1337-43. PMC: 4636461. DOI: 10.1038/nm.3957. View

Garcia-Figueiras R, Goh V, Padhani A, Baleato-Gonzalez S, Garrido M, Leon L . CT perfusion in oncologic imaging: a useful tool?. AJR Am J Roentgenol. 2012; 200(1):8-19. DOI: 10.2214/AJR.11.8476. View

Wetscherek A, Stieltjes B, Laun F . Flow-compensated intravoxel incoherent motion diffusion imaging. Magn Reson Med. 2014; 74(2):410-9. DOI: 10.1002/mrm.25410. View

10.

Richter G, Wunsch C, Schneider B, Dux M, Klar E, Seelos R . [Hydro-CT in detection and staging of pancreatic carcinoma]. Radiologe. 1998; 38(4):279-86. DOI: 10.1007/s001170050355. View

11.

Mayer P, Dinkic C, Jesenofsky R, Klauss M, Schirmacher P, Dapunt U . Changes in the microarchitecture of the pancreatic cancer stroma are linked to neutrophil-dependent reprogramming of stellate cells and reflected by diffusion-weighted magnetic resonance imaging. Theranostics. 2018; 8(1):13-30. PMC: 5743457. DOI: 10.7150/thno.21089. View

12.

Fritzsche K, Neher P, Reicht I, van Bruggen T, Goch C, Reisert M . MITK diffusion imaging. Methods Inf Med. 2012; 51(5):441-8. DOI: 10.3414/ME11-02-0031. View

13.

Klau M, Mayer P, Bergmann F, Maier-Hein K, Hase J, Hackert T . Correlation of Histological Vessel Characteristics and Diffusion-Weighted Imaging Intravoxel Incoherent Motion-Derived Parameters in Pancreatic Ductal Adenocarcinomas and Pancreatic Neuroendocrine Tumors. Invest Radiol. 2015; 50(11):792-7. DOI: 10.1097/RLI.0000000000000187. View

14.

Mandrekar J . Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010; 5(9):1315-6. DOI: 10.1097/JTO.0b013e3181ec173d. View

15.

DAssignies G, Couvelard A, Bahrami S, Vullierme M, Hammel P, Hentic O . Pancreatic endocrine tumors: tumor blood flow assessed with perfusion CT reflects angiogenesis and correlates with prognostic factors. Radiology. 2008; 250(2):407-16. DOI: 10.1148/radiol.2501080291. View

16.

Fritz F, Skornitzke S, Hackert T, Kauczor H, Stiller W, Grenacher L . Dual-Energy Perfusion-CT in Recurrent Pancreatic Cancer - Preliminary Results. Rofo. 2016; 188(6):559-65. DOI: 10.1055/s-0042-105765. View

17.

Pang Y, Turkbey B, Bernardo M, Kruecker J, Kadoury S, Merino M . Intravoxel incoherent motion MR imaging for prostate cancer: an evaluation of perfusion fraction and diffusion coefficient derived from different b-value combinations. Magn Reson Med. 2012; 69(2):553-62. PMC: 3413736. DOI: 10.1002/mrm.24277. View

18.

Klaassen R, Gurney-Champion O, Engelbrecht M, Stoker J, Wilmink J, Besselink M . Evaluation of Six Diffusion-weighted MRI Models for Assessing Effects of Neoadjuvant Chemoradiation in Pancreatic Cancer Patients. Int J Radiat Oncol Biol Phys. 2018; 102(4):1052-1062. DOI: 10.1016/j.ijrobp.2018.04.064. View

19.

Van der Zee J, van Eijck C, Hop W, van Dekken H, Dicheva B, Seynhaeve A . Angiogenesis: a prognostic determinant in pancreatic cancer?. Eur J Cancer. 2011; 47(17):2576-84. DOI: 10.1016/j.ejca.2011.08.016. View

20.

Benckert C, Thelen A, Cramer T, Weichert W, Gaebelein G, Gessner R . Impact of microvessel density on lymph node metastasis and survival after curative resection of pancreatic cancer. Surg Today. 2011; 42(2):169-76. DOI: 10.1007/s00595-011-0045-0. View