Clinical Impact of Uncertainties in the Mean Excitation Energy of Human Tissues During Proton Therapy
A Besemer1*, H Paganetti2, B Bednarz1, (1) Department of Medical Physics, Wisconsin Institutes for Medical Research, University of Wisconsin, Madison, WI, (2) Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MAWE-C-BRB-6 Wednesday 10:30:00 AM - 12:30:00 PM Room: Ballroom B
Purpose: Uncertainties in the estimated mean excitation energies (I-value) needed for
calculating proton stopping power can be in the order of 10-15%, which introduces a
fundamental limitation in the accuracy of proton range determination. Previous efforts have
quantified shifts in proton depth dose distributions due to I-value uncertainties in homogenous
tissue phantoms. This study is the first to quantify the clinical impact of I-value uncertainties on
proton dose distributions within patient geometries.
Methods: A previously developed Geant4 based Monte Carlo code was used to simulate a
proton treatment plan for prostate cancer with varying tissue I-values. A total of five cases were
simulated using nominal I-values as well as I-values modified by ±5% and ±10% of the nominal
values. Dose volume histograms were generated for the GTV, CTV, PTV and relevant organs-at-risk (OARs).
Results: Modification of tissue I-values impacted both the proton range and SOBP width. D90
range shifts up to 4 mm from the nominal range were recorded whereas D80 range shifts
reached up to 2 mm. For an increase in I-value of 10% of the nominal value, the increase in
range and SOBP width resulted in a 1.4% decrease in the CTV mean dose. Inversely,
decreasing the I-value by 10% increased the CTV mean dose by 0.8%. The difference in the
mean dose to the OARs was relatively small except for the rectum that differed
by up to 5%.
Conclusions: This study demonstrated that the impact of I-value uncertainties on patient dose
distributions. Clearly, sub-millimeter precision in proton therapy would necessitate reduction in I-value uncertainties to ensure an efficacious clinical outcome.