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Purpose Although carbon-ion therapy is becoming increasingly attractive to the treatment of tumors, details about the ionization pattern formed by therapeutic carbon-ion beam in tissue have not been fully investigated. In this work, systematic calculations for the nanodosimetric quantities and relative biological effectiveness (RBE) of a clinically relevant carbon-ion beam were studied for the first time. Methods The method combining both track structure and condensed history Monte Carlo (MC) simulations was adopted to calculate the nanodosimetric quantities. Fragments and energy spectra at different positions of the radiation field of a clinically relevant carbon-ion pencil beam were generated by means of MC simulations in water. Nanodosimetric quantities such as mean ionization cluster size ( M 1 ), the first moment of conditional cluster size ( M 1 C 2 ), cumulative probability ( F 2 ), and conditional cumulative probability ( F 3 C 2 ) at these positions were then acquired based on the spectra and the pre-calculated nanodosimetric database created by track structure MC simulations. What's more, a novel approach to calculate RBE based on the said nanodosimetric quantities was introduced. The RBE calculations were then conducted for the carbon-ion beam at different water-equivalent depths. Results Lateral distributions at various water-equivalent depths of both the nanodosimetric quantities and RBE values were obtained. The values of M 1 , M 1 C 2 , F 2 , and F 3 C 2 were 1.49, 2.67, 0.30, and 0.38 at the plateau at the beam central axis and maximized at 2.79, 5.69, 0.47, and 0.68 at the depths around the Bragg peak, respectively. At a given depth, M 1 and F 2 decreased laterally with increasing the distance to the beam central axis while M 1 C 2 and F 3 C 2 remained nearly unchanged at first and then decreased except for M 1 C 2 at the rising edge of the Bragg peak. The calculated RBE values were 1.07 at the plateau and 3.13 around the Bragg peak. Good agreement between the calculated RBE values and experimental data was obtained. Conclusions Different nanodosimetric quantities feature the track structure of therapeutic carbon-ion beam in different manners. Detailed ionization patterns generated by carbon-ion beam could be characterized by nanodosimetric quantities. Moreover the combined method adopted in this work to calculate nanodosimetric quantities is not only valid but also convenient. Nanodosimetric quantities are significantly helpful for the RBE calculations in carbon-ion therapy.

PURPOSE An optimized air ventilation system design for a treatment room in Heavy-ion Medical Facility is an important issue in the aspects of nuclear safety because the activated air produced in a treatment room can directly affect the medical staff and the general public in the radiation-free area. METHODS Optimized design criteria of air ventilation system for a clinical room in 430 MeV/u carbon ion beam medical accelerator facility was performed by using a combination of MCNPX2.7.0 and CINDER'90 codes. Effective dose rate and its accumulated effective dose by inhalation and residual gamma were calculated for a normal treatment scenario (2 min irradiation for one fraction) as a function of decay time. Natural doses around the site were measured before construction and used as reference data. RESULTS With no air ventilation system, the maximum effective dose rate was about 3 μSv/h (total dose of 90 mSv/y) and minimum 0.2 μSv/h (total dose of 6 mSv/y), which are over the legal limits for medical staff and for the general public. Although inhalation dose contribution was relatively small, it was considered seriously because of its long-lasting effects in the body. The integrated dose per year was 1.8 mSv/y in the radiation-free area with the 20-min rate of air ventilation system. CONCLUSION An optimal air ventilation rate of 20 min is proposed for a clinical room, which also agrees with the best mechanical design value.

This book describes the advantages, limitations and similarities between proton beams and carbon ion beams for cancer therapy at an entry level. The author was an associate professor at University of Sao Paulo (USP), Sao Paulo, Brazil, who is known for his electrophysiological studies on biological membranes, applications of thermodynamics of irreversible processes in membranes, and the development of electron paramagnetic resonance to study the behavior of molecular components of the biological membranes. After retirement, the author has devoted himself to writing books in nuclear medicine and advanced physics. This article is protected by copyright. All rights reserved.

Purpose: Investigate the factors which affect the doses of organs at risk (OARs) for head and neck carbon ion therapy. Methods: Ten locally recurrent nasopharyngeal carcinoma cases with similar prescriptions were selected. All patients’ organs at risk (OARs) as well as CTVs were contoured by an experienced physician. Carbon ion treatment plans were created using a Syngo treatment planning system (Siemens, Germany). The CTVs were expanded to make optimized target volumes (OTVs) by considering treatment uncertainties and OAR protections. All plans were reviewed by this physician to be clinically acceptable. The OTV was expanded an additional 3mm to define the volume where beam spots could be put. A volume was also drawn 6 mm around the OTV to approximate the 50 % dose volume. The volumes where the OARs overlapped the OTV + 3 mm and OTV + 6 mm volumes, termed residual volumes, were then calculated. Results: The residual volumes within OTV + 3 mm were directly related to the OAR maximum dose. The percentage of the residual volume within the OTV + 6 mm with respect to the OAR volume was strongly related to the OAR mean doses. OAR mean doses also were affected by the beam setups. For example, if the OARs were in the beam entrance, the superior beams would sharply decrease the mean doses of the OARs hit by the lateral beams while increasing the mean doses of the OARs hit by the superior beam; the mean dose of the OARs which were hit by higher weight beams would be higher than the OARs hit by lower weight beams. Conclusion: Physicians should be cautious when contouring OARs, especially those close to CTVs and sensitive to large doses. Planners should set the OTV and beam parameters properly in order to save the OARs.

Purpose: When particles traversing inhomogeneous materials like lung they show a characteristic range modulation which cannot be observed in homogeneous materials. It is possible to describe the range modulation by a convolution of an unperturbed Bragg-Curve and a normal distribution. The sigma of the normal distribution is a parameter for the strength of the modulation effect. A new material parameter (modulation power, P_mod) is introduced which is independent of the material thickness. It is defined as the square of sigma divided by the mean water equivalent thickness of the target (µ). Methods: The modulation power of lung tissue was determined by actual Bragg-peak measurements after traversing an ex-vivo porcine lung and by Monte-Carlo simulations with micro-CT data of human lung tissue. The determined modulation powers were used to show the effect of range modulation effects in a simplified treatment situation. A four centimeter spread-out Bragg-peak after traversing eight centimeter of lung tissue was simulated in FLUKA. The SOBP with and without consideration of range modulation effects were compared. Results: As well in the measurements as in the MC simulations range modulation effects of lung tissue were observed. The determined modulation powers showed a great range from 0.05 mm, in the micro-CT data, to 0.7 mm in the lung measurements. The SOBP comparison showed that range modulation effects Result in over- and underdosages at the distal and proximal edge of the SOBP. In the investigated case, the last 0.5 cm of the SOBP showed an underdosage of up to 50% at the distal edge, while 0.5 cm distal to the SOBP an overdosage of up to 50% was observed. Conclusion: Range modulation effects occur in inhomogeneous materials like lung. These modulation effects may Result in clinically relevant over- and underdosages but are currently not considered in commercially available treatment planning systems.

Hot- and cold-dose spots at a shallow depth in a target are formed by carbon ions passing through the bolus with sharp gradients. These spots are caused by sidescatter disequilibrium due to various multiple scattering effects in the different bolus thicknesses. When the dose calculation method by the broad beam algorithm (BBA) is used for treatment planning, these spots cannot be predicted, because the BBA neglects the multiple scattering effects in materials (rms error of 3.9%). On the other hand, since the dose calculation method by the pencil beam algorithm (PBA) takes into account the scattering effects, the results calculated by the PBA agreed better than the BBA with the measured hot- and cold-dose spots, having a rms error of 1.9%. Thus, dose calculation by the PBA improves the accuracy of dose prediction at the shallow depth. However, since dose distributions at deeper positions are affected by many light fragment particles generated by fragment reactions, the results calculated by the PBA disagree with the experimental ones. It is necessary that even the PBA accurately models behavior of fragment particles.

Purpose: To evaluate offline Positron Emission Tomography (PET) /Computed Tomography (CT) for in‐vivo verification of scanned proton and carbon ion irradiation of tumours in different anatomical locations. Methods: At our combined ion therapy facility, in‐vivo PET/CT‐based verification of beam delivery is being performed using a commercial scanner (Siemens Biograph mCT) installed just outside of the treatment rooms. More than 70 patients with tumours in different anatomical locations received at least one 30 min long post‐irradiation scan. PET measurements are compared to expectations using in‐house developed software tools based, among others, on the general purpose FLUKA Monte Carlo code. Results: Activation within the irradiated region could be visualised in all treatment sites, regardless of the ion species and applied dose level. For carbon ions, the most promising results could be obtained for irradiation of compact tumours in the head and neck and hypofractionated treatment of liver lesions with restricted motion. Here, range verification benefits from a marked delineation of the distal activated area, due to the dominant contribution of 11C projectile fragments. For abdominopelvic sites (prostate, sacral chordoma) the typical use of opposed fields, the extremely low counting statistics and the insufficient characterization of biological tissue parameters represent major challenges for range monitoring. Nevertheless, useful feedback on the correctness of the treatment delivery could be inferred in some convenient cases. For protons, the data confirmed the expected higher counting statistics and increased sensitivity to the knowledge of the tissue composition. The latter benefited from an improved tissue classification based on multimodal information in the brain region, while known limitations remain in the pelvic area (prostate). Conclusion: Offline PET/CT imaging of scanned ion treatment is feasible, but its clinical value strongly depends on the anatomical location and treatment strategy (ion species, dose level and multi‐field configuration). Parts of this work have been funded via the FP7 EU Project PARTNER (grant agreement 215840‐2), the BMBF Project DOT‐MOBI (grant agreement 01|B08002F), and the FP7 EU Project ENVISION (grant agreement 241851).

Purpose: Upgrade and benchmarking of a research 4D treatment planning system (4DTPS) suitable for realistic patient treatment planning and treatment simulations taking into account specific requirements for scanned ion beam therapy, i.e., modeling of dose heterogeneities due to interplay effects and range changes caused by patient motion and dynamic beam delivery. Methods: The 4DTPS integrates data interfaces to 4D computed tomography (4DCT), deformable image registration and clinically used motion monitoring devices. The authors implemented a novel data model for 4D image segmentation using Boolean mask volume datasets and developed an algorithm propagating a manually contoured reference contour dataset to all 4DCT phases. They further included detailed treatment simulation and dose reconstruction functionality, based on the irregular patient motion and the temporal structure of the beam delivery. The treatment simulation functionality was validated against experimental data from irradiation of moving radiographic films in air, 3D moving ionization chambers in a water phantom, and moving cells in a biological phantom with a scanned carbon ion beam. The performance of the program was compared to results obtained with predecessor programs. Results: The measured optical density distributions of the radiographic films were reproduced by the simulations to (−2 ± 12)%. Compared to earlier versions of the 4DTPS, the mean agreement improved by 2%, standard deviations were reduced by 7%. The simulated dose to the moving ionization chambers in water showed an agreement with the measured dose of (−1 ± 4)% for the typical beam configuration. The mean deviation of the simulated from the measured biologically effective dose determined via cell survival was (617 ± 538) mGy relative biological effectiveness corresponding to (10 ± 9)%. Conclusions: The authors developed a research 4DTPS suitable for realistic treatment planning on patient data and capable of simulating dose delivery to a moving patient geometry for scanned ion beams. The accuracy and reliability of treatment simulations improved considerably with respect to earlier versions of the 4DTPS.