This paper presents Neutron Capture Enhanced Particle Therapy (NCEPT), a method for enhancing the radiation dose delivered to a tumour relative to surrounding healthy tissues during proton and carbon ion therapy by capturing thermal neutrons produced inside the treatment volume during irradiation. NCEPT utilises extant and in-development boron-10 and gadolinium-157-based drugs from the related field of neutron capture therapy. Using Monte Carlo simulations, we demonstrate that a typical proton or carbon ion therapy treatment plan generates an approximately uniform thermal neutron field within the target volume, centred around the beam path. The tissue concentrations of neutron capture agents required to obtain an arbitrary 10% increase in biological effective dose are estimated for realistic treatment plans, and compared to concentrations previously reported in the literature. We conclude that the proposed method is theoretically feasible, and can provide a worthwhile improvement in the dose delivered to the tumour relative to healthy tissue with readily achievable concentrations of neutron capture enhancement drugs.

Parallax error caused by the detector crystal thickness degrades spatial resolution at the peripheral regions of the field-of-view (FOV) of a scanner. To resolve this issue, depth-of-interaction (DOI) measurement is a promising solution to improve the spatial resolution and its uniformity over the entire FOV. Even though DOI detectors have been used in dedicated systems with a small ring diameter such as for the human brain, breast and small animals, the use of DOI detectors for a large bore whole-body PET system has not been demonstrated yet. We have developed a four-layered DOI detector, and its potential for a brain dedicated system has been proven in our previous development. In the present work, we investigated the use of the four-layer DOI detector for a large bore PET system by developing the world’s first whole-body prototype. We evaluated its performance characteristics in accordance with the NEMA NU 2 standard. Furthermore, the impact of incorporating DOI information was evaluated with the NEMA NU 4 image quality phantom. Point source images were reconstructed with a filtered back projection (FBP), and an average spatial resolution of 5.2  ±  0.7 mm was obtained. For the FBP image, the four-layer DOI information improved the radial spatial resolution by 48% at the 20 cm offset position. The peak noise-equivalent count rate (NECR) was 22.9 kcps at 7.4 kBq ml−1 and the scatter fraction was 44%. The system sensitivity was 5.9 kcps MBq−1. For the NEMA NU 2 image quality phantom, the 10 mm sphere was clearly visualized without any artifacts. For the NEMA NU 4 image quality phantom, we measured the phantom at 0, 10 and 20 cm offset positions. As a result, we found the image with four-layer DOI could visualize the 2 mm-diameter hot cylinder although it could not be recognized on the image without DOI. The average improvements in the recovery coefficients for the five hot rods (1–5 mm) were 0.3%, 4.4% and 26.3% at the 0, 10 and 20 cm offset positions, respectively (except for the 1 mm-diameter rod at the 20 cm offset position). Although several practical issues (such as adding end-shields) remain to be addressed before the scanner is ready for clinical use, we showed that the four-layer DOI technology provided higher and more uniform spatial resolution over the FOV and improved contrast for small uptake regions located at the peripheral FOV, which could improve detectability of small and distal lesions such as nodal metastases, especially in obese patients.

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 -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.