Dose reconstruction from PET images in carbon ion therapy: a deconvolution approach.

Dose and range verification have become important tools to bring carbon ion therapy to a higher level of confidence in clinical applications. Positron emission tomography is among the most commonly used approaches for this purpose and relies on the creation of positron emitting nuclei in nuclear interactions of the primary ions with tissue. Predictions of these positron emitter distributions are usually obtained from time-consuming Monte Carlo simulations or measurements from previous treatment fractions, and their comparison to the current, measured image allows for treatment verification. Still, a direct comparison of planned and delivered dose would be highly desirable, since the dose is the quantity of interest in radiation therapy and its confirmation improves quality assurance in carbon ion therapy. In this work, we present a deconvolution approach to predict dose distributions from PET images in carbon ion therapy. Under the assumption that the one-dimensional PET distribution is described by a convolution of the depth dose distribution and a filter kernel, an evolutionary algorithm is introduced to perform the reverse step and predict the depth dose distribution from a measured PET distribution. Filter kernels are obtained from either a library or are created for any given situation on-the-fly, using predictions of the [Formula: see text]-decay and depth dose distributions, and the very same evolutionary algorithm. The applicability of this approach is demonstrated for monoenergetic and polyenergetic carbon ion irradiation of homogeneous and heterogeneous solid phantoms as well as a patient computed tomography image, using Monte Carlo simulated distributions and measured in-beam PET data. Carbon ion ranges are predicted within less than 0.5 mm and 1 mm deviation for simulated and measured distributions, respectively.

Experimental validation of the FLUKA Monte Carlo code for dose and [Formula: see text]-emitter predictions of radioactive ion beams.

In the context of hadrontherapy, whilst ions are capable of effectively destroying radio resistant, deep seated tumors, their treatment localization must be well assessed to ensure the sparing of surrounding healthy tissue and treatment effectiveness. Thus, range verification techniques, such as online positron-emission-tomography (PET) imaging, hold great potential in clinical practice, providing information on the in vivo beam range and consequent tumor targeting. Furthermore, [Formula: see text] emitting radioactive ions can be an asset in online PET imaging, depending on their half-life, compared to their stable counterparts. It is expected that using these radioactive ions the signal obtained by a PET apparatus during beam delivery will be greatly increased, and exhibit a better correlation to the Bragg Peak. To this end, FLUKA Monte Carlo particle transport and interaction code was used to evaluate, in terms of annihilation events at rest and dose, the figure of merit in using [Formula: see text] emitter, radioactive ion beams (RI [Formula: see text]). For this purpose, the simulation results were compared with experimental data obtained with an openPET prototype in various online PET acquisitions at the Heavy Ion Medical Accelerator in Chiba (HIMAC), in collaboration with colleagues from the National Institute of Radiological Sciences' (NIRS) Imaging Physics Team. The dosimetry performance evaluation with FLUKA benefits from its recent developments in fragmentation production models. The present work estimated that irradiations with RI [Formula: see text], produced via projectile fragmentation and their signal acquisition with state-of-the-art PET scanner, lead to nearly a factor of two more accurate definition of the signals' peak position. In addition to its more advantageous distribution shape, it was observed at least an order magnitude higher signal acquired from 11C and 15O irradiations, with respect to their stable counterparts.

Optimum size of a calibration phantom for x-ray CT to convert the Hounsfield units to stopping power ratios in charged particle therapy treatment planning.

In charged-particle therapy treatment planning, the volumetric distribution of stopping power ratios (SPRs) of body tissues relative to water is used for patient dose calculation. The distribution is conventionally obtained from computed tomography (CT) images of a patient using predetermined conversion functions from the CT numbers to the SPRs. One of the biggest uncertainty sources of patient SPR estimation is insufficient correction of beam hardening arising from the mismatch between the size of the patient cross section and the calibration phantom for producing the conversion functions. The uncertainty would be minimized by selecting a suitable size for the cylindrical water calibration phantom, referred to as an 'effective size' of the patient cross section, Leffective. We investigated the Leffective for pelvis, abdomen, thorax, and head and neck regions by simulating an ideal CT system using volumetric models of the reference male and female phantoms. The Leffective values were 23.3, 20.3, 22.7 and 18.8 cm for the pelvis, abdomen, thorax, and head and neck regions, respectively, and the Leffective for whole body was 21.0 cm. Using the conversion function for a 21.0-cm-diameter cylindrical water phantom, we could reduce the root mean square deviation of the SPRs and their mean deviation to ≤0.011 and ≤0.001, respectively, in the whole body. Accordingly, for simplicity, the effective size of 21.0 cm can be used for the whole body, irrespective of body-part regions for treatment planning in clinical practice.