ABSTRACT
Background and purpose: This work reports on the results of a survey performed on the use of computed tomography (CT) imaging for motion management, surface guidance devices, and their quality assurance (QA). Additionally, it details the collected user insights regarding professional needs in CT for radiotherapy. The purpose of the survey is to understand current practice, professional needs and future directions in the field of fan-beam CT in radiation therapy (RT). Materials and methods: An online institutional survey was conducted between 1-Sep-2022 and 10-Oct-2022 among medical physics experts at Belgian and Dutch radiotherapy institutions, to assess the current status, challenges, and future directions of motion management and surface image-guided radiotherapy. The survey consisted of a maximum of 143 questions, with the exact number depending on participants' responses. Results: The response rate was 66 % (31/47). Respiratory management was reported as standard practice in all but one institution; surface imaging during CT-simulation was reported in ten institutions. QA procedures are applied with varying frequencies and methodologies, primarily with commercial anatomy-like phantoms. Surface guidance users report employing commercial static and dynamic phantoms. Four main subjects are considered clinically important by the respondents: surface guidance, CT protocol optimisation, implementing gated imaging (4DCT, breath-hold), and a tattoo-less workflow. Conclusions: The survey highlights the scattered pattern of QA procedures for respiratory motion management, indicating the need for well-defined, unambiguous, and practicable guidelines. Surface guidance is considered one of the most important techniques that should be implemented in the clinical radiotherapy simulation workflow.
ABSTRACT
Background and purpose: To obtain an understanding of current practice, professional needs and future directions in the field of fan-beam CT in RT, a survey was conducted. This work presents the collected information regarding the use of CT imaging for dose calculation and structure delineation. Materials and methods: An online institutional survey was distributed to medical physics experts employed at Belgian and Dutch radiotherapy institutions to assess the status, challenges, and future directions of QA practices for fan-beam CT. A maximum of 143 questions covered topics such as CT scanner availability, CT scanner specifications, QA protocols, treatment simulation workflow, and radiotherapy dose calculation. Answer forms were collected between 1-Sep-2022 and 10-Oct-2022. Results: A 66 % response rate was achieved, yielding data on a total of 58 CT scanners. For MV photon therapy, all single-energy CT scans are reconstructed in Hounsfield Units for delineation or dose calculation, and a direct- or stoichiometric method was used to convert CT numbers for dose calculation. Limited use of dual-energy CT is reported for photon (N = 3) and proton dose calculations (N = 1). For brachytherapy, most institutions adopt water-based dose calculation, while approximately 26 % of the institutions take tissue heterogeneity into account. Commissioning and regular QA include eleven tasks, which are performed by two or more professions (29/31) with varying frequencies. Conclusions: Dual usage of a planning CT limits protocol optimization for both tissue characterization and delineation. DECT has been implemented only gradually. A variation of QA testing frequencies and tests are reported.
ABSTRACT
PURPOSE: This article reports on the integration of a sliding-gantry CT-on-rails with a robotic linear accelerator. METHODS: The system consists of a SOMATOM Definition AS CT scanner (Siemens Healthcare, Forchheim, Germany) and a CyberKnife M6 FIM (Accuray, Inc., Sunnyvale, CA, USA). Additional movement programs were implemented in the robotic treatment table (RoboCouch, Accuray Inc.) to move between CT and treatment position. Acceptance testing was performed on the CT scanner according to AAPM83 guidelines, as well as safety tests for collision avoidance and electromagnetic (EM) compatibility. For the first clinical application of the system, daily dose was evaluated in five pancreas SBRT patients. A second envisioned use is the optimal alignment of the treatment beams to soft-tissue targets without the use of implanted fiducials. To this end, an offset vector feature has been implemented, which shifts the treatment center according to the daily position of the tumor relative to the spine (established by a CT scan). This offset can be applied by either moving the treatment couch (physical couch shift) or by moving the CyberKnife robot (virtual couch shift). An End-to-End (E2E) test was specifically designed to evaluate the accuracy of this feature using the Xsight Lung Tracking Phantom (Computerized Imaging Reference Systems, Inc., Norfolk, VA, USA). The position of the tumor with respect to the spine was varied by moving the insert inside the phantom and a CT scan was made for each position. The treatment plan was subsequently delivered to the phantom employing spine tracking. The test was repeated four times for a physical couch shift and four times for a virtual couch shift. RESULTS: All acceptance, safety and EM compatibility testing was successful. For the first pancreas SBRT patients treated using daily CT imaging, the volume of stomach, duodenum, or small bowel receiving >35 Gy was found to increase or remain constant during treatment; however, the clinical constraint of 5 cc was not violated. For the offset vector E2E test, the reference accuracy (without any tumor shift) was (0.74, -0.61, -0.33) mm in the inferior, left, and anterior direction respectively. The difference in deviation with respect to the reference was (-0.1 ± 0.15, 0.01 ± 0.16, -0.17 ± 0.25) mm, when applying a physical couch shift. With a virtual couch shift, the deviations were (0.02 ± 0.15, 0.06 ± 0.23, -0.4 ± 0.31) mm. CONCLUSIONS: The first combination of a CyberKnife treatment unit with a sliding-gantry CT scanner is operational in our department enabling future developments toward image-guided online-adaptive SBRT supported by diagnostic-quality CT imaging.
