Program Information
Enhancement of CT-Texture Based Treatment Response Detection for Pancreatic Cancer Using Dual-Energy CT
G Noid*, D Schott , X Chen , A Tai , Y Liu , X Li , Medical College of Wisconsin, Milwaukee, WI
Presentations
SU-F-FS4-2 (Sunday, July 30, 2017) 2:05 PM - 3:00 PM Room: Four Seasons 4
Purpose: Radiation can induce changes in CT textures during radiation therapy (RT) and the change can potentially be used to assess RT response for pancreatic cancer. These changes will be amplified if the X-Ray energy is reduced due to the rapid growth of the photoelectric effect below 100 keV. The purpose of this work is to investigate the use of low energy mono-energetic images (MEI) obtained from dual energy (DE) CT to enhance the detection of radiation induced changes during RT delivery.
Methods: DECT data for selected pancreatic cancer patients during routine CT-guided RT delivery using an in-room CT scanner (Definition AS Open, Siemens) equipped with a sequential DE protocol were analyzed. MEI images across a range of energies were reconstructed using an image-based material decomposition. Quantitative features including mean CT number (mCTN) and first order textures (skewness, kurtosis, entropy, variance) were extracted as a function of treatment week. The results from the MEI data were compared to those obtained from the standard 120 kVp CTs of the same subjects.
Results: The analysis on the MEI data shows an enhancement in mCTN change at the lowest available mono-energy. The average change in mCTN between the first and last week of treatment was 2.7 times larger for 40keV images than that for the 120 kVp CTs. Changes in the first order texture features were also amplified at the lowest available mono-energy. For a representative patient the entropy in the target increased by over a factor of 5 during RT delivery as measured on 40keV MEI, 4 times larger than for 120 kVp CTs.
Conclusion: Radiation-induced changes in CT textures during RT delivery for pancreatic cancer are amplified if they are measured from MEI of DECT, enhancing the viability of using CT texture changes as a biomarker for early RT response assessment.
Funding Support, Disclosures, and Conflict of Interest: Partially supported by Siemens
Contact Email: