This proposal aims to establish a hybrid virtual-MRI/CBCT system for precision image guidance in radiation therapy of liver cancer. Stereotactic body radiation therapy (SBRT) improves the treatment outcome over conventional fractionated radiotherapy by delivering high fractional dose in few fractions. However, SBRT of liver cancer still has high local failure rate up to 20-30% at 2-3 years and high overall grade>=3 toxicity rate up to 30% with patient deaths from the treatment. Previous studies demonstrated a strong correlation between the treatment outcome and the tumor localization accuracy of the image guidance technique used. Currently, cone beam CT (CBCT) is the most widely used imaging technique for liver SBRT. However, CBCT has extremely limited soft tissue contrast with no visualization of most liver tumors. As a result, its localization error is frequently over 6mm, and the dose coverage of tumor volume can fall below 90%, which is far from enough for tumor control. Drastically reducing localization errors is imperative to improve the outcome of liver SBRT. Combined MRI-Radiotherapy machines could provide MRI contrast for liver tumor localization. However, such machines are rare and expensive for most clinics. As such, an alternative solution is urgently required to meet the ubiquitous need of all radiation oncology departments: a solution in the form of a novel low-cost imaging system with MRI equivalent contrast. Since CBCT is readily available on most radiotherapy machines, creating CBCT-based imaging systems would be the most effective strategy. Our recent publication demonstrated the feasibility of such strategy. (Harris, Med Phys 2018) Our long-term goal is to establish the next generation of CBCT systems with virtual multi-modality imaging capabilities for high precision tumor localization and adaptive therapy in radiation therapy. In this application, our overall objective is to establish a novel system to generate hybrid virtual-MRI/CBCT from CBCT, with virtual-MRI inside the liver for target localization and augmented CBCT outside the liver for healthy tissue verification.
The specific aims are: (1). Establish a 3D hybrid virtual- MRI/CBCT system for image guidance in breath-hold liver SBRT without respiratory motion. (2). Establish a 4D hybrid virtual-MRI/CBCT system for image guidance in free-breathing liver SBRT with respiratory motion. (3). Optimize and clinically evaluate the systems through simulation studies and a prospective clinical trial. Our expected deliverables through the academic-industrial partnership are novel hybrid virtual-MRI/CBCT systems ready to be integrated to all radiotherapy machines with only CBCT systems. This new imaging capability will have significant clinical impact because it will create a paradigm shift in image-guided radiation therapy by revolutionizing the widely used CBCT systems to enable a new era of low-cost high-precision virtual multi- modality guided radiotherapy. This precision guidance can lead to breakthrough in escalating the tumor control and minimizing the toxicities of liver SBRT as well as treatments of other sites with tumors in the soft tissue.

Public Health Relevance

The hybrid virtual-MRI/CBCT system will be a low-cost imaging system with superb soft tissue contrast to provide precise image guidance for liver SBRT, which paves the road to further margin reduction and dose escalation. As a result, this novel system has a great potential to enhance the tumor local control and reduce the normal tissue toxicities for all patients under liver SBRT treatments. Finally yet importantly, the hybrid virtual-MRI/CBCT system can also be potentially applicable for improving the image guidance precision of radiation therapy treatments of other clinical sites with tumors in the soft tissue, such as breast and prostate cancers.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB028324-01
Application #
9801976
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Duan, Qi
Project Start
2019-09-30
Project End
2023-06-30
Budget Start
2019-09-30
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Duke University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705