The aim of this article is to derive and verify a mathematical formulation for the reduction of the six-dimensional (6D) positional inaccuracies of patients (lateral, longitudinal, vertical, pitch, roll and yaw) to three-dimensional (3D) linear shifts. The formulation was mathematically and experimentally tested and verified for 169 stereotactic radiotherapy patients. The mathematical verification involves the comparison of any (one) of the calculated rotational coordinates with the corresponding value from the 6D shifts obtained by cone beam computed tomography (CBCT). The experimental verification involves three sets of measurements using an ArcCHECK phantom, when (i) the phantom was not moved (neutral position: 0MES), (ii) the position of the phantom shifted by 6D shifts obtained from CBCT (6DMES) from neutral position and (iii) the phantom shifted from its neutral position by 3D shifts reduced from 6D shifts (3DMES). Dose volume histogram and statistical comparisons were made between [Formula: see text] and [Formula: see text]. The mathematical verification was performed by a comparison of the calculated and measured yaw (γ°) rotation values, which gave a straight line, Y = 1X with a goodness of fit as R = 0.9982. The verification, based on measurements, gave a planning target volume receiving 100% of the dose (V100%) as 99.1 ± 1.9%, 96.3 ± 1.8%, 74.3 ± 1.9% and 72.6 ± 2.8% for the calculated treatment planning system values TPSCAL, 0MES, 3DMES and 6DMES, respectively. The statistical significance (p-values: paired sample t-test) of V100% were found to be 0.03 for the paired sample [Formula: see text] and 0.01 for [Formula: see text]. In this paper, a mathematical method to reduce 6D shifts to 3D shifts is presented. The mathematical method is verified by using well-matched values between the measured and calculated γ°. Measurements done on the ArcCHECK phantom also proved that the proposed methodology is correct. The post-correction of the table position condition introduces a minimal spatial dose delivery error in the frameless stereotactic system, using a 6D motion enabled robotic couch. This formulation enables the reduction of 6D positional inaccuracies to 3D linear shifts, and hence allows the treatment of patients with frameless stereotactic radiosurgery by using only a 3D linear motion enabled couch.
Introduction: This study aimed to quantify the difference in setup margin in cone beam computed tomography (CBCT) setup imaging, utilising the van Herk formula for two different image registration methods. Two alternative techniques of registration, bony landmark (BL) matching and soft tissue matching (ST) for head and neck cancer patients, were investigated. Methods: This study included 30 head and neck cancer patients who received a simultaneous integrated boost of 54–60–66 Gy in 30 fractions, using volumetric modulated arc treatment. A total of 867 CBCT images were acquired during patient setup and further analysed for setup margin calculation. A region of interest was described using a clip box between the reference and CBCT image to calculate the patient’s positional inaccuracy in three translational directions, X, Y and Z, where X was mediolateral, Y was the cranial-caudal, and Z was the anterior-posterior direction in the patient-based coordinate system, respectively. The shifts were captured by altering the BL and ST matching, and the setup margin was calculated using the van Herk formula (=2·5Σ + 0·7σ where Σ was the systematic and σ was the random error). Results: The difference between bony and ST matching in most cases was observed to be 1·4 mm in all translational directions at a 95% confidence interval and <1° in all rotational directions. The rotational error was found to be below the action level (±3°); hence, no corrections related to rotational error were made. The translational setup margin for bone and ST-based registration was X (BL) = 4·6 mm, X (ST) = 4·4 mm, Y (BL) = 6·3 mm, Y (ST) = 4·7 mm, Z (BL) = 3·0 mm, Z (ST) = 3·6mm. Conclusion: Two distinct registration approaches for head-neck patient setup did not yield any significant difference in the setup margin calculation. A suitable approach for CBCT and reference CT registration technique was required for the setup margin calculation. Confusion in selecting the correct image registration procedure can result in incorrect treatment execution. The compatibility of the two registration approaches was established in this study. Image fusion was neutralised before the second match (ST) to avoid hysteresis. For setup verification using CBCT for the head and neck region, both bone and ST registration were compatible for setup verification.
Purpose: Patient wait time for every single fraction of every patient treated at our centre for the past year has been presented in this study. The waiting time data were analysed across different treatment sites and modalities. Materials and Methods: Between March 2021 and March 2022, all patients and their corresponding recorded measurements of waiting time were analysed. Times recorded included check-in time (CK), scheduled time to start treatment (SC) and beam-on time for the first beam of therapy (ST). SPSS version 18 was used for statistical calculations, correlations and assessing significance. Results: A total of 181 patients were treated during this duration. The total number of radiotherapy (RT) sessions recorded was 3011. Out of these 3011 sessions, number of times treated by rapid arc (RA), intensity-modulated radiotherapy (IMRT), three-dimensional conformal radiotherapy (3DCRT), stereotactic body radiotherapy (SBRT), stereotactic radiosurgery and stereotactic radiotherapy (SRS/SRT) were 68.18%, 30.19%, 0.167%, 0.565% and 0.19%, respectively. The mean (± standard deviation) times for scheduled time to start treatment (SC) to check-in time (CK), SC to ST (beam-on time for the first beam of treatment), CK to ST and (CK or SC) to ST were −14 ± 48 min, 6 ± 50 min, 19 ± 24 min and −4 ± 31 min, respectively. Conclusion: Patient wait times during RT were presented in this study. This study covered the daily waiting times before RT during modern-day RT treatment sessions. This vast series of consecutive patient data will be a valuable resource for the future planning and management of any modern RT department.
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