Sci-Sat AM(1): Imaging-03: On-line dynamic contrast enhanced cone-beam CT for measuring
Q Tang1, S Kim1, R Clarkson1
1Department of Radiation Physics, Princess Margaret Hospital, Toronto, ON.
Medical Physics
|May 18, 2017
Summary
This study introduces a new X-ray imaging method using cone beam CT (CBCT) to measure tumor perfusion in real-time. The technique accurately quantifies changes in the tumor microenvironment during treatment.
Area of Science:
- Medical Imaging
- Oncology
- Radiology
Background:
- Accurate quantification of the tumor microenvironment is crucial for effective cancer treatment.
- Current methods for assessing tumor perfusion lack real-time capabilities at the treatment unit.
- Functional imaging offers a promising approach to monitor treatment response.
Purpose of the Study:
- To develop and validate a novel on-line functional imaging method for quantifying tumor microenvironment.
- To establish a surrogate measurement of tumor perfusion using X-ray contrast enhanced cone beam CT (CBCT).
- To assess the sensitivity of the method in detecting treatment-induced changes in the tumor microenvironment.
Main Methods:
- An X-ray contrast enhanced method based on the cone beam CT (CBCT) platform was developed.
- The technique involves synchronized contrast injection and CBCT acquisition, followed by mathematical parameterization of contrast uptake.
- Non-linear optimization was used to derive tumor perfusion parameters from projection data.
Main Results:
- Dynamic contrast enhanced images were successfully reconstructed from CBCT projections in a rabbit VX2 tumor model.
- The proposed CBCT method demonstrated excellent agreement with conventional CT measurements of contrast enhancement.
- The method showed sensitivity in detecting alterations in the tumor microenvironment post-radiation treatment.
Conclusions:
- The novel on-line functional imaging method provides a reliable means to quantify tumor microenvironment and perfusion at the treatment unit.
- This CBCT-based technique offers a valuable tool for real-time monitoring of cancer treatment response.
- The method has the potential to improve personalized cancer therapy through dynamic assessment of tumor characteristics.
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