Carbon-ion cancer therapy, characterized by its high dose concentration, effectively controls tumors while minimizing the impact on surrounding normal tissues. When carbon-ion beams are delivered to a living body, positron-emitting radionuclides are secondarily generated. Therefore, to obtain information on the actual treatment beam, in-beam imaging using OpenPET, which features an open gantry, is effective and is expected to enable the evaluation of the beam range and therapeutic effects immediately after irradiation. Since our initial proposal in 2008, we have continued the research and development of OpenPET. After conducting irradiation imaging experiments in the physics laboratory of the Heavy Ion Medical Accelerator in Chiba (HIMAC), a clinical trial targeting head and neck cancer patients was initiated in 2023. This paper provides an overview of the development of OpenPET systems and the ongoing clinical trial.

Proton therapy can deliver high doses to tumors while minimizing damage to surrounding healthy tissue. Despite this physical advantage, there is a relatively large uncertainty in the actual dose distribution within the patient body. Therefore, in vivo beam monitoring is essential to fully utilize the physical advantages of proton therapy in clinical practice. Secondary-electron-bremsstrahlung (SEB) imaging has been proposed for beam monitoring in particle therapy. In this paper, we introduce the physical characteristics of SEB and show the experimental results of proton beam imaging using a dedicated low-energy X-ray camera. We also present a dose estimation method from the SEB image using a deep learning approach.

Optical imaging is a valuable tool for quality assessment (QA)in radiation therapy. During experiments with proton beams, we discovered that water emits light when irradiated by protons. Additionally, we conducted optical imaging studies for various types of radiation exposure. This article provides an overview of optical imaging in radiation therapy, with a primary focus on the studies we have conducted to date.

The introduction of image guidance in radiation therapy has resulted in significant advances in cancer treatment precision. In image-guided radiation therapy (IGRT), techniques such as portal imaging, on-board imaging (OBI), CBCT, and MRI can be used to position the patient precisely based on the internal anatomy. These technological advances allow for more precise delivery of radiation doses to the tumor volume while simultaneously reducing the impact of radiation on surrounding normal tissue. Each image-guided device has its own advantages and disadvantages. This article focuses on CBCT because of its wide availability and potential application in adaptive radiotherapy. Following a discussion of factors that degrade CBCT image quality, previous studies on improving CBCT image-quality in adaptive radiation therapy will be reviewed. The review will present the results and effectiveness of several recently-focused deep-learning-based methods implemented on clinical data.