Modern radiotherapy of cancer relies heavily on computerized inverse treatment planning, which typically uses diagnostic CT images as input data to delineate anatomy and compute optimized intensity modulated radiotherapy (IMRT) plans. Image guided radiotherapy also requires good CT image quality to verify patient positioning and to identify tumor shrinkage. However the presence of metal, for example hip implants or dental work in the patient, causes image artifacts in diagnostic and conebeam kV-CT that severely impact treatment planning. Megavoltage CT is largely free of such metal artifacts due to the relatively low absorption of high energy photons by metal, but at the expense of poor soft tissue delineation essential to accurate treatment planning. Our hypothesis is that the combination of diagnostic cone beam CT imaging with limited megavoltage CT data acquisition can largely eliminate these metal artifacts from a composite CT data set, in a cost effective and dose-efficient manner. We will design and optimize a novel, high DQE, thin strip, MV scintillator placed on a standard Electronic Portal Imaging Device in combination with targeted multi-leaf collimator control. This hypothesis of significantly improved, image guided radiotherapy intervention in a multi-modal approach will be tested with the following specific aims: 1) develop the MV strip detector with a DQE(0) >25% and a resolving power of 8 lp/cm, 2) develop new software for hardware control, image correction and reconstruction that provides 120 Hounsfield unit accuracy from a combined dose of less than 100 mGy, and 3) validate the radiation therapy treatment plan improvement in a preliminary in-vivo clinical study on at least 80 cancer patients. The rapid translation of these advances into clinical practice should greatly improve the accuracy of IMRT planning and image guidance, for those patients with metal object in or near their treatment fields, leading to significantly reduced morbidity combined with improved local tumor control. The potential impact of this research extends beyond the applications listed here, to include other therapy treatment fields affected by metallic implants such as spinal rods, as well as quantitative CT imaging in the vicinity of orthopaedic implants.

Public Health Relevance

Modern radiation therapy treatment of cancer depends on the automated computer generation of complex radiation delivery treatment plans to ensure that the correct dose is delivered only to the tumor. The accuracy of these plans is critically dependent on the clarity of the diagnostic X-ray CT images of the cancer region. A large fraction of the patients who receive radiation therapy of head and neck cancer have teeth filled with metal amalgams or covered with gold crowns, and those with prostate cancer may have artificial hips, both of which degrade the quality of the CT images and the accuracy of the resulting treatment plans. We plan to overcome this limitation by designing and building a new, combined kV/MV imaging system that provides excellent images without requiring a significant increase in dose to the patient.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA138426-05
Application #
8607143
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Baker, Houston
Project Start
2010-04-15
Project End
2015-01-31
Budget Start
2014-02-01
Budget End
2015-01-31
Support Year
5
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94304
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Star-Lack, Josh; Sun, Mingshan; Meyer, Andre et al. (2014) Rapid Monte Carlo simulation of detector DQE(f). Med Phys 41:031916
Wu, Meng; Keil, Andreas; Constantin, Dragos et al. (2014) Metal artifact correction for x-ray computed tomography using kV and selective MV imaging. Med Phys 41:121910
Sun, Mingshan; Nagy, Tamás; Virshup, Gary et al. (2011) Correction for patient table-induced scattered radiation in cone-beam computed tomography (CBCT). Med Phys 38:2058-73