Clinical interest in perfusion imaging for cancer has gained impetus in recent years due to developing clinical need and to technological advances that have facili tated such imaging. In oncology this has been driven by the development of drugs targeted at the tumor vasculature. Conven tional assessment of the therapeutic efficacy of such anti-angiogenic and anti-vascular drugs has been shown to be of limited value in recent clinical trials. Such assess ment is based on size change, e.g., Response Evaluation Criteria in Solid Tumours (RECIST) or World Health Organisation (WHO) criteria, yet these drugs may not necessarily cause tumor shrinkage. For example, a 5 month improvement in over all survival was reported in a Phase III study of patients with metastatic color-ectal cancer, treated with conventional chemotherapy, and bevacizumab (Avastin; Genentech, San Francisco, CA, USA), a drug targeted against vascular endothelial growth factor; however, this was accompa nied by an increase in objective response rate of only 10% (Hurwitz et al., 2004). While time-to-progression is probably the best method of assessing drug efficacy as it reflects disease stability, a disadvantage of using such progression as an endpoint in clinical trials is that large patient num bers may be needed, and such studies are expensive. Furthermore, patients could be treated potentially with ineffective drugs for prolonged periods. Perfusion imaging techniques such as perfusion computed tomography (CT) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) have been promoted particu larly for early clinical studies (phase I and II) as these techniques may provide in vivo pharmacodynamic information. Such information may help in dose selection and scheduling, and in supporting deci sions to take new therapeutic compounds forward to larger phase clinical studies with efficacy endpoints.
Both perfusion CT and DCE-MRI are attractive imaging techniques as they com bine functional information regarding the tumor vasculature with good anatomical detail. Computed Tomography and MRI are widely available, and these perfusion techniques, which are based on contrast media enhancement, can be incorporated relatively easily into standard imaging protocols. Both qualitative and quantita tive information of tissue vascularity can be obtained. Using mathematical model ling to generate quantitative perfusion measurements, these techniques may dem onstrate the increased vascular volume and flow within tumors, display the spa tial and temporal heterogeneity of per-fusion, demonstrate the hyperpermeability of the tumor vasculature, and provide a surrogate measure of tissue hypoxia. Of course, there are differences between tech niques that should be taken into account. For example, a simple linear relationship exists between tissue enhancement and contrast concentration with CT, and quan tification is relatively straightforward. In contrast, the signal intensity change with MRI is dependent on many factors, and not necessarily proportional to contrast dose, thus greater care has to be taken with quantitative perfusion assessment using DCE-MRI.
Keywords
- Perfusion Compute Tomography
- Dynamic Compute Tomography
- Solitary Pulmonary Nodule
- Dynamic Contrast Enhance Magnetic Resonance Imaging
- Tumor Perfusion
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Goh, V. (2009). Quantitative Assessment of Colorectal Cancer Perfusion: Perfusion Computed Tomography and Dynamic Contrast Enhanced Magnetic Resonance Imaging. In: Hayat, M.A. (eds) Colorectal Cancer. Methods of Cancer Diagnosis, Therapy, and Prognosis, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9545-0_12
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