Radiotherapy, a crucial technique in cancer therapy, has traditionally relied on the premise of largely unchanging patient anatomy during the treatment course and encompassing uncertainties by target margins. This review introduces adaptive radiotherapy (ART), a notable innovation that addresses anatomy changes and optimizes the therapeutic ratio. ART utilizes advanced imaging techniques such as CT, MRI, and PET to modify the treatment plan based on observed anatomical changes and even biological changes during the course of treatment. The narrative review provides a comprehensive guide on ART for healthcare professionals and trainees in radiation oncology and anyone else interested in the topic. The incorporation of artificial intelligence in ART has played a crucial role in improving effectiveness, particularly in contour segmentation, treatment planning, and quality assurance. This has expedited the process to render online ART feasible, lowered the burden for radiation oncology practitioners, and enhanced the precision of dynamically personalized treatment. Current technical and clinical progress on ART is discussed in this review, highlighting the ongoing development of imaging technologies and AI and emphasizing their contribution to enhancing the applicability and effectiveness of ART.

Purpose: This study aims to characterize the performance of a prototype rapid kilovoltage (kV) x‐ray image guidance system onboard the newly released Halcyon 2.0 linear accelerator (Varian Medical Systems, Palo Alto, CA) by use of conventional and innovatively designed testing procedures.Methods: Basic imaging system performance tests and radiation dose measurements were performed for all eleven kV‐cone beam computed tomography (CBCT) imaging protocols available on a preclinical Halcyon 2.0 LINAC. Both conventional CBCT reconstruction using the Feldkamp–Davis–Kress (FDK) algorithm and a novel, advanced iterative reconstruction (iCBCT) available on this platform were evaluated. Standard image quality metrics, including slice thickness accuracy, high‐contrast resolution, low‐contrast resolution, regional uniformity and noise, and CT Hounsfield unit (HU) number accuracy and linearity were evaluated using a manufacturer‐supplied QUART phantom (GmbH, Zorneding, Germany) and an independent image quality phantom (Catphan 500, The Phantom Laboratory, New York, NY). Due to the simplified design of the QUART phantom, we developed surrogate and clinically feasible strategies for measuring slice thickness and high‐ and low‐contrast resolution. Imaging dose delivered by these eleven protocols was measured using a computed tomography dose index phantom and pencil chamber with commonly accepted methods and procedures. A subset of measurements were repeated on a conventional C‐arm LINAC (TrueBeam and Trilogy, Varian Medical System) for comparison. Clinical patient images of pelvic and abdominal regions are also presented for qualitative assessment as part of a feasibility study for clinical implementation.Results: Image acquisition time was 17–42 s on the Halcyon system compared with 60 s on the C‐arm LINAC systems. The kV imager projection offset, imaging and treatment isocenter coincidence and the couch three‐dimensional match movement all achieved less than1 mm mechanical accuracy. All major image quality metrics were within either the national guideline or vendor‐recommended tolerances. The designed surrogate approach with the QUART phantom showed a range of 0.24–0.35 cycles/mm for spatial resolution, a contrast‐to‐noise ratio (CNR) of 2–20 for FDK reconstruction and a tolerance of 0.5 mm for slice thickness. Other metrics derived from the Catphan images obtained on the Halcyon and C‐arm LINACs showed comparable values for the FDK reconstruction. The iterative reconstruction tended to reduce noise, as evidenced by a higher CNR ratio. The fast scan pelvis protocols for Halcyon resulted in 50% lower dose compared to the standard scans, and the thorax fast protocol similarly delivered 10% lower dose than the standard thoracic scan. Preliminary patient images indicated that rapid kV CBCT with breath‐hold is feasible, with improved imaging quality compared to free‐breathing scans.Conclusion: Independent and comprehensive characterization of the kV imaging guidance system on the Halcyon 2.0 system demonstrated acceptable image quality for clinical use. The imaging unit onboard the Halcyon meets vendor specifications and satisfies requirements for routine clinical use. The fast kV imaging system enables the potential for volumetric CBCT acquisition during a single breath‐hold and the iterative reconstruction tends to reduce the noise therefore has the potential to improve the CNR for normal size patient.

Normalize the response of electronic portal imaging device (EPID) is the first step toward an EPID‐based standardization of Linear Accelerator (linac) dosimetry quality assurance. In this study, we described an approach to generate two‐dimensional (2D) pixel sensitivity maps (PSM) for EPIDs response normalization utilizing an alternative beam and dark‐field (ABDF) image acquisition technique and large overlapping field irradiations. The automated image acquisition was performed by XML‐controlled machine operation and the PSM was generated based on a recursive calculation algorithm for Varian linacs equipped with aS1000 and aS1200 imager panels. Cross‐comparisons of normalized beam profiles and 1.5%/1.5 mm 1D Gamma analysis was adopted to quantify the improvement of beam profile matching before and after PSM corrections. PSMs were derived for both photon (6, 10, 15 MV) and electron (6, 20 MeV) beams via proposed method. The PSM‐corrected images reproduced a horn‐shaped profile for photon beams and a relative uniform profiles for electrons. For dosimetrically matched linacs equipped with aS1000 panels, PSM‐corrected images showed increased 1D‐Gamma passing rates for all energies, with an average 10.5% improvement for crossline and 37% for inline beam profiles. Similar improvements in the phantom study were observed with a maximum improvement of 32% for 15 MV and 22% for 20 MeV. The PSM value showed no significant change for all energies over a 3‐month period. In conclusion, the proposed approach correct EPID response for both aS1000 and aS1200 panels. This strategy enables the possibility to standardize linac dosimetry QA and to benchmark linac performance utilizing EPID as the common detector.