Published August 1, 2018 | Version v1
Journal article

Variations of quantitative perfusion measurement on dynamic contrast enhanced CT for colorectal cancer: implication of standardized image protocol

  • 1. Institute of Translational Medicine, Zhejiang University, Hangzhou 310013 (China)
  • 2. Department of Radiation Oncology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310019 (China)
  • 3. Department of Electrical Engineering, Columbia University, New York, NY 10027 (United States)
  • 4. Department of Radiation Oncology, Rutgers—Cancer Institute of New Jersey, Rutgers—Robert Wood Johnson Medical School, 195 Little Albany St., New Brunswick, NJ 08903 (United States)
  • 5. Department of Medical Physics, University of Nevada, Las Vegas, Las Vegas, NV 89121 (United States)

Description

Tumor angiogenesis is considered an important prognostic factor. With an increasing emphasis on imaging evaluation of the tumor microenvironment, dynamic contrast enhanced-computed tomography (DCE-CT) has evolved as an important functional technique in this setting. Yet many questions remain as to how and when these functional measurements should be performed for each agent and tumor type, and what quantitative models should be used in the fitting process. In this study, we evaluated the variations of perfusion measurement on DCE-CT for rectal cancer patients from (1) different tracer kinetic models, (2) different scan acquisition lengths, and (3) different scan intervals. A total of seven commonly used models were studied: the adiabatic approximation to the tissue homogeneity (AATH) model, adiabatic approximation to the homogeneity tissue with fixed transit time (AATHFT) model, the Tofts model (TM), the extended Tofts model (ETM), Patlak model, Logan model, and the model-free deconvolution method. Akaike's information criterion was used to identify the best fitting model. The interchangeability of different models was further evaluated using Bland–Altman analysis. All models gave comparable blood volume (BV) measurements except the Patlak method. While for the volume transfer constant (Ktrans) estimation, AATHFT, AATH, and ETM generated reasonable agreement among each other but not for the other models. Regarding the blood flow (BF) measurement, no two models were interchangeable. In addition, the perfusion parameters were compared with four acquisition times (45, 65, 85, and 105 s) and four temporal intervals (1, 2, 3, and 4 s). No significant difference was observed in the volume transfer constant (Ktrans), BV, and BF measurements when comparing data acquired over 65 s with data acquired over 105 s using any of the DCE models in this study. Yet increasing the temporal interval led to a significant overestimation of BF in the deconvolution method. In conclusion, the perfusion measurement is indeed model dependent and the image acquisition/processing technique is dependent. The radiation dose of DCE-CT was an average of 1.5–2 times an abdomen/pelvic CT, which is not insubstantial. To take the DCE-CT forward as a biomarker in oncology, prospective studies should be carefully designed with the optimal image acquisition and analysis technique. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1361-6560/aacb99

Additional details

Identifiers

Publishing Information

Journal Title
Physics in Medicine and Biology
Journal Volume
63
Journal Issue
16
Journal Page Range
[14 p.]
ISSN
0031-9155
CODEN
PHMBA7

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52003075
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
BIOLOGICAL MARKERS; BLOOD FLOW; COMPUTERIZED TOMOGRAPHY; IMAGE PROCESSING; NEOPLASMS; RADIATION DOSES
Descriptors DEC
DIAGNOSTIC TECHNIQUES; DISEASES; DOSES; PROCESSING; TOMOGRAPHY