To better understand how radiotherapy delivery parameters affect the depletion of circulating lymphocytes in patients treated for intra-cranial tumors, we developed a computational human body blood flow model (BFM), that enables to estimate the dose to the circulating blood during the course of fractionated radiation therapy. A hemodynamic cardiovascular system based on human body reference values was developed to distribute the cardiac output to 24 different organs, described by a discrete Markov Chain. For explicit intracranial blood flow modeling, we extracted major cerebral vasculature from MRI data of a patient and complemented them with an extension network of generic vessels in the frontal and occipital lobes to guarantee even overall blood supply to the entire brain volume. An explicit Monte Carlo simulation was implemented to track the propagation of each individual blood particle (BP) through the brain and time-dependent radiation fields, accumulating dose along their trajectories. The cerebral model includes 1050 path lines and explicitly simulates more than 266 000 BP at any given time that are tracked with a time resolution of 10 ms. The entire BFM for the whole body contains 22 178 000 BP, corresponding to 4200 BP per ml of blood. We have used the model to investigate the difference between proton and photon therapy, and the effect of different dose rates and patient characteristics on the dose to the circulating blood pool. The mean dose to the blood pool is estimated to be 0.06 and 0.13 Gy after 30 fractions of proton and photon therapy, respectively, and the highest dose to 1% of blood was found to be 0.19 Gy and 0.34 Gy. The fraction of blood volume receiving any dose after the first fraction is significantly lower for proton therapy, 10.1% compared to 18.4% for the photon treatment plan. 90% of the blood pool will have received dose after the 11th fraction using photon therapy compared to the 21st fraction with proton therapy. Higher dose rates can effectively reduce the fraction of blood irradiated to low doses but increase the amount of blood receiving high doses. Patient characteristics such as blood pressure, gender and age lead to smaller effects than variations in the dose rate. We developed a 4D human BFM including recirculating to estimate the radiation dose to the circulating blood during intracranial treatment and demonstrate its application to proton- versus photon-based delivery, various dose rates and patient characteristics. The radiation dose estimation to the circulating blood provides us better insight into the origins of radiation-induced lymphopenia.

We have developed a time-dependent computational framework, hematological dose (HEDOS), to estimate dose to circulating blood cells from radiation therapy treatment fields for any treatment site. Two independent dynamic models were implemented in HEDOS: one describing the spatiotemporal distribution of blood particles (BPs) in organs and the second describing the time-dependent radiation field delivery. A whole-body blood flow network based on blood volumes and flow rates from ICRP Publication 89 was simulated to produce the spatiotemporal distribution of BPs in organs across the entire body using a discrete-time Markov process. Constant or time-varying transition probabilities were applied and their impact on transition time was investigated. The impact of treatment time and anatomical site were investigated using imaging data and dose distributions from a liver cancer and a brain cancer patient. The simulations revealed different dose levels to the circulating blood for brain irradiation compared to liver irradiation even for similar field sizes due to the different blood flow properties of the two organs. The volume of blood receiving any dose (V >0 Gy) after a single radiation fraction increases from 1.2% for a 1 s delivery time to 20.9% for 120 s delivery time for the brain cancer treatment, and from 10% (1 s) to 48.7% (120 s) for a liver cancer treatment. Other measures of the low-dose bath to the circulating blood such as the dose to small volumes of blood (D 2%) decreases with longer delivery time. Furthermore, we demonstrate that the blood dose-volume histogram is highly sensitive to changes in the treatment time, indicating that dynamic modeling of blood flow and radiation fields is necessary to evaluate dose to circulating blood cells for the assessment of radiation-induced lymphopenia. HEDOS is publicly available and allows for the estimation of patient-specific dose to circulating blood cells based on organ DVHs, thus enabling the study of the impact of different treatment plans, dose rates, and fractionation schemes.

To exploit the full potential of proton therapy, accurate and on-line methods to verify the patient positioning and the proton range during the treatment are desirable. Here we propose and validate an innovative technique for determining patient misalignment uncertainties through the use of a small number of low dose, carefully selected proton pencil beams ('range probes') (RP) with sufficient energy that their residual Bragg peak (BP) position and shape can be measured on exit. Since any change of the patient orientation in relation to these beams will result in changes of the density heterogeneities through which they pass, our hypothesis is that patient misalignments can be deduced from measured changes in Bragg curve (BC) shape and range. As such, a simple and robust methodology has been developed that estimates average proton range and range dilution of the detected residual BC, in order to locate range probe positions with optimal prediction power for detecting misalignments. The validation of this RP based approach has been split into two phases. First we retrospectively investigate its potential to detect translational patient misalignments under real clinical conditions. Second, we test it for determining rotational errors of an anthropomorphic phantom that was systematically rotated using an in-house developed high precision motion stage. Simulations of RPs in these two scenarios show that this approach could potentially predict translational errors to lower than1.5 mm and rotational errors to smaller than 1° using only three or five RPs positions respectively.