A typical proton CT (pCT) detector comprises a tracking system, used to measure the proton position before and after the imaged object, and an energy/range detector to measure the residual proton range after crossing the object. The Bergen pCT collaboration was established to design and build a prototype pCT scanner with a high granularity digital tracking calorimeter used as both tracking and energy/range detector. In this work the conceptual design and the layout of the mechanical and electronics implementation, along with Monte Carlo simulations of the new pCT system are reported. The digital tracking calorimeter is a multilayer structure with a lateral aperture of 27 cm × 16.6 cm, made of 41 detector/absorber sandwich layers (calorimeter), with aluminum (3.5 mm) used both as absorber and carrier, and two additional layers used as tracking system (rear trackers) positioned downstream of the imaged object; no tracking upstream the object is included. The rear tracker’s structure only differs from the calorimeter layers for the carrier made of ∼200 μm carbon fleece and carbon paper (carbon-epoxy sandwich), to minimize scattering. Each sensitive layer consists of 108 ALICE pixel detector (ALPIDE) chip sensors (developed for ALICE, CERN) bonded on a polyimide flex and subsequently bonded to a larger flexible printed circuit board. Beam tests tailored to the pCT operation have been performed using high-energetic (50–220 MeV/u) proton and ion beams at the Heidelberg Ion-Beam Therapy Center (HIT) in Germany. These tests proved the ALPIDE response independent of occupancy and proportional to the particle energy deposition, making the distinction of different ion tracks possible. The read-out electronics is able to handle enough data to acquire a single 2D image in few seconds making the system fast enough to be used in a clinical environment. For the reconstructed images in the modeled Monte Carlo simulation, the water equivalent path length error is lower than 2 mm, and the relative stopping power accuracy is better than 0.4%. Thanks to its ability to detect different types of radiation and its specific design, the pCT scanner can be employed for additional online applications during the treatment, such as in-situ proton range verification.

Intensity modulated proton therapy (IMPT) could yield high linear energy transfer (LET) in critical structures and increased biological effect. For head and neck cancers at the skull base this could potentially result in radiation-associated brain image change (RAIC). The purpose of the current study was to investigate voxel-wise dose and LET correlations with RAIC after IMPT. For 15 patients with RAIC after IMPT, contrast enhancement observed on T1-weighted magnetic resonance imaging was contoured and coregistered to the planning computed tomography. Monte Carlo calculated dose and dose-averaged LET (LET_d) distributions were extracted at voxel level and associations with RAIC were modelled using uni- and multivariate mixed effect logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve and precision-recall curve. An overall statistically significant RAIC association with dose and LET_d was found in both the uni- and multivariate analysis. Patient heterogeneity was considerable, with standard deviation of the random effects of 1.81 (1.30-2.72) for dose and 2.68 (1.93-4.93) for LET_d, respectively. Area under the receiver operating characteristic curve was 0.93 and 0.95 for the univariate dose-response model and multivariate model, respectively. Analysis of the LET_d effect demonstrated increased risk of RAIC with increasing LET_d for the majority of patients. Estimated probability of RAIC with LET_d = 1 keV/µm was 4% (95% confidence interval, 0%, 0.44%) and 29% (95% confidence interval, 0.01%, 0.92%) for 60 and 70 Gy, respectively. The TD₁₅ were estimated to be 63.6 and 50.1 Gy with LET_d equal to 2 and 5 keV/µm, respectively. Our results suggest that the LET_d effect could be of clinical significance for some patients; LET_d assessment in clinical treatment plans should therefore be taken into consideration.

Background: Children with brain tumors undergoing radiotherapy are at particular risk of radiation-induced morbidity and are therefore routinely considered for proton therapy (PT) to reduce the dose to healthy tissues. The aim of this study was to apply pediatric constraints and normal tissue complication probability (NTCP) models when evaluating the differences between PT and contemporary photon-based radiotherapy, volumetric modulated arc therapy (VMAT). Methods: Forty patients (aged 1-17 years) referred from Norwegian institutions to cranial PT abroad during 2014-2016 were selected for VMAT re-planning using the original CT sets and target volumes. The VMAT and delivered PT plans were compared by dose/volume metrics and NTCP models related to growth hormone deficiency, auditory toxicity, visual impairment, xerostomia, neurocognitive outcome and secondary brain and parotid gland cancers. Results: The supratentorial brain, temporal lobes, hippocampi, hypothalamus, pituitary glands, cochleas, salivary glands, optic nerves and chiasm received lower mean doses from PT. Reductions in population median NTCP were significant for auditory toxicity (VMAT: 3.8%; PT: 0.3%), neurocognitive outcome (VMAT: 3.0 IQ points decline at 5 years post RT; PT: 2.5 IQ points), xerostomia (VMAT: 2.0%; PT: 0.6%), excess absolute risk of secondary cancer of the brain (VMAT: 9.2%; PT: 6.7%) and salivary glands (VMAT: 2.8%; PT:0.5%). Across all patients, 23/38 PT plans had better or comparable estimated risks for all endpoints (within ±10% of the risk relative to VMAT), whereas for 1/38 patients all estimates were better or comparable with VMAT. Conclusions: PT reduced the volumes of normal tissues exposed to radiation, particularly low-to-intermediate dose levels, and this was reflected in lower NTCP. Of the included endpoints, substantial reductions in population medians were seen from the delivered PT plans for auditory complications, xerostomia, and risk of secondary cancers of the brain and salivary glands.