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Photon-counting computed tomography (PCCT) marks a significant advancement over conventional energy-integrating detector (EID) CT systems. This review highlights PCCT's superior spatial and contrast resolution, reduced radiation dose, and multi-energy imaging capabilities, which address key challenges in radiotherapy, such as accurate tumor delineation, precise dose calculation, and treatment response monitoring. PCCT's improved anatomical clarity enhances tumor targeting while minimizing damage to surrounding healthy tissues. Additionally, metal artifact reduction (MAR) and quantitative imaging capabilities optimize workflows, enabling adaptive radiotherapy and radiomics-driven personalized treatment. Emerging clinical applications in brachytherapy and radiopharmaceutical therapy (RPT) show promising outcomes, although challenges like high costs and limited software integration remain. With advancements in artificial intelligence (AI) and dedicated radiotherapy packages, PCCT is poised to transform precision, safety, and efficacy in cancer radiotherapy, marking it as a pivotal technology for future clinical practice.

We aim to investigate the feasibility of online monitoring of irradiation time (IRT) and scan time for FLASH radiotherapy using a pixelated semiconductor detector. Measurements of the time structure of FLASH irradiations were performed using fast, pixelated spectral detectors, AdvaPIX-TPX3 and Minipix-TPX3. The latter has a fraction of its sensor coated with a neutron sensitive material. With little or no dead time and an ability to resolve events that are closely spaced in time (tens of ns), both detectors can accurately determine IRTs as long as pile-ups are avoided. To avoid pile-ups, we placed the detectors beyond the Bragg peak or at a large scattering angle. We acquired prompt gamma rays and secondary neutrons and calculated IRTs based on timestamps of the first (beam-on) and the last (beam-off) charged species. We also measured scan times in x, y, and diagonal directions. We performed these measurements for a single spot, a small animal field, a patient field, and a ridge filter optimized field to demonstrate in vivo online monitoring of IRT. All measurements were compared to vendor log files. Differences between measurements and log files for a single spot, a small animal field, and a patient field were within 1%, 0.3% and 1%, respectively. In vivo monitoring of IRTs was accurate within 0.1% for AdvaPIX-TPX3 and within 6.1% for Minipix-TPX3. The scan times in x, y, and diagonal directions were 4.0, 3.4, and 4.0 ms, respectively. Overall, the AdvaPIX-TPX3 can measure FLASH IRTs within 1% accuracy, indicating that prompt gamma rays are a good surrogate for primary protons. The Minipix-TPX3 showed a higher discrepancy, suggesting a need for further investigation. The scan times (3.4 \pm 0.05 ms) in the 60-mm distance of y-direction were less than (4.0 \pm 0.06 ms) in the 24-mm distance of x-direction, confirming the much faster scanning speed of the Y magnets than that of X., Comment: 11 pages, 5 figures

Recently, shoot-through proton FLASH has been proposed where the highest energy is extracted from the cyclotron to maximize the dose rate (DR). Even though our proton pencil beam scanning system can deliver 250 MeV (the highest energy), it is not typical to use 250 MeV protons for routine clinical treatments and as such 250 MeV may not have been characterized in the commissioning. In this study, we aim to characterize 250 MeV protons from Varian ProBeam system for FLASH RT as well as assess the ability of clinical monitoring ionization chamber (MIC) for FLASH-readiness. We measured data needed for beam commissioning: integral depth dose (IDD) curve, spot sigma, and absolute dose calibration. To evaluate MIC, we measured output as a function of beam current. To characterize a 250 MeV FLASH beam, we measured: (1) central axis DR as a function of current and spot spacing and arrangement, (2) for a fixed spot spacing, the maximum field size that still achieves FLASH DR (i.e., > 40 Gy/s), (3) DR reproducibility. All FLASH DR measurements were performed using ion chamber for the absolute dose and irradiation times were obtained from log files. We verified dose measurements using EBT-XD films and irradiation times using a fast, pixelated spectral detector. R90 and R80 from IDD were 37.58 and 37.69 cm, and spot sigma at isocenter were {\sigma}x=3.336 and {\sigma}y=3.332 mm, respectively. The absolute dose output was measured as 0.377 GyE*mm2/MU for the commissioning conditions. Output was stable for beam currents up to 15 nA, and it gradually increased to 12-fold for 115 nA. DR depended on beam current, spot spacing and arrangement and could be reproduced within 4.2% variations. Even though FLASH was achieved and the largest field size that delivers FLASH DR was determined as 35x35 mm2, current MIC has DR dependence and users should measure DR each time for their FLASH applications., Comment: 11 pages, 6 figures

Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated approach aided by synthetic MRI for rapid and accurate CBCT multi-organ contouring in head-and-neck (HN) cancer patients. MRI has superb soft-tissue contrasts, while CBCT offers bony-structure contrasts. Using the complementary information provided by MRI and CBCT is expected to enable accurate multi-organ segmentation in HN cancer patients. In our proposed method, MR images are firstly synthesized using a pre-trained cycle-consistent generative adversarial network given CBCT. The features of CBCT and synthetic MRI are then extracted using dual pyramid networks for final delineation of organs. CBCT images and their corresponding manual contours were used as pairs to train and test the proposed model. Quantitative metrics including Dice similarity coefficient (DSC) were used to evaluate the proposed method. The proposed method was evaluated on a cohort of 65 HN cancer patients. CBCT images were collected from those patients who received proton therapy. Overall, DSC values of 0.87, 0.79/0.79, 0.89/0.89, 0.90, 0.75/0.77, 0.86, 0.66, 0.78/0.77, 0.96, 0.89/0.89, 0.832, and 0.84 for commonly used OARs for treatment planning including brain stem, left/right cochlea, left/right eye, larynx, left/right lens, mandible, optic chiasm, left/right optic nerve, oral cavity, left/right parotid, pharynx, and spinal cord, respectively, were achieved. In this study, we developed a synthetic MRI-aided HN CBCT auto-segmentation method based on deep learning. It provides a rapid and accurate OAR auto-delineation approach, which can be used for adaptive radiation therapy.