Setup Errors Research Articles

Implementing the optimized hippo-avoidance prophylactic cranial irradiation for limited-stage small cell lung cancer by tomotherapy and volumetric modulated arc therapy.

Hippo-avoidance prophylactic cranial irradiation (HA-PCI) requires a hippocampal avoidance zone expanded from hippocampus to ensure dose fall-off and compensate for setup errors. Most studies recommend a 5-mm margin, while it could be optimized to a 2-mm expansion. Here, we showed the details of optimized HA-PCI for limited-stage small cell lung cancer (LS-SCLC). This cohort study reviewed patients with LS-SCLC receiving optimized HA-PCI from August 2014 to June 2020 in the National Cancer Center of China. The hippo-related dose parameters were summarized. The comparison of the Hopkins Verbal Learning Test-Revised (HVLT-R) scores in different time points was conducted. The Kaplan-Meier method was used to calculate the survival rates. A total of 112 patients were included. The average doses of hippocampus and hippocampal avoidance zone were 6.80 Gy (IQR: 6.40-7.44) and 7.63 Gy (IQR: 7.14-8.39). No differences were observed in the two radiation techniques (tomotherapy [TOMO] vs. volumetric-modulated arc therapy [VMAT]). The decline of HVLT-R score remained in a low level and not significant in assessable patients (p = 0.095). With a median follow-up of 52 months (95% CI: 47.2-56.7), the 2-year overall survival and progression-free survival were 74.1% and 50.0%, respectively. Two intracranial recurrence lesions (2.3%) located <2 mm from the hippocampus. Optimized HA-PCI could achieve similar dose limitation by TOMO and VMAT techniques with favorable efficacy and minor toxicity.

Dosimetric benefit and clinical feasibility of deep inspiration breath-hold and volumetric modulated arc therapy-based postmastectomy radiotherapy for left-sided breast cancer

To evaluate the dosimetric benefits and clinical feasibility of deep inspiratory breath-hold (DIBH) combined with volumetric modulated arc therapy (VMAT) in left-sided postmastectomy radiotherapy (PMRT). Eligible patients with left-sided breast cancer undergoing DIBH-based PMRT were prospectively included. Chest wall, supra/infraclavicular fossa, and/or internal mammary node irradiation (IMNI) were planned with a prescription dose of 43.5 Gy in 15 fractions. VMAT plans were designed on free breathing (FB)—and DIBH-CT to compare dosimetric parameters in heart, left anterior descending artery (LAD) and lung. Cone-beam computed tomography (CBCT) was performed before and after treatment to evaluate inter- and intra-fractional setup errors. Heart position and dose variations during treatment were estimated by fusing CBCT with DIBH-CT scans.Twenty patients were included with 10 receiving IMNI. In total, 193 pre-treatment and 39 pairs pre- and post-treatment CBCT scans were analyzed. The Dmean, Dmax, and V5−40 of the heart, LAD, and left lung were significantly lower in DIBH than FB (p < 0.05 for all), except for V5 of LAD (p = 0.167). The cardiopulmonary dosimetric benefits were maintained regardless of IMNI. The inter- and intra-fractional setup errors were < 0.3 cm; and the overall estimated PTV margins were < 1.0 cm. During treatment, the mean dice similarity coefficient of heart position and the mean ratio of heart Dmean between CBCT and DIBH-CT plans was 0.95 (0.88–1.00) and 100% (70.6–119.5%), respectively. DIBH-VMAT could effectively reduce the cardiopulmonary doses with acceptable reproducibility and stability in left-sided PMRT regardless of IMNI.

Quality management of head and neck patient treatments using statistical process control techniques.

The treatment, planning, simulation, and setup of radiotherapy patients contain many processes subject to errors involving both staff and equipment. Cone-beam-CT (CBCT) provides a final check of patient positioning and corrections based on this can be made prior to treatment delivery. Statistical Process Control (SPC) techniques are used in various industries for quality management and error mitigation. The utility of SPC techniques to monitor process and equipment changes in our Head and Neck patient treatments was assessed by application to CBCT results from a quality-focused longitudinal study. Individuals and moving range (XmR) as well as exponentially-weighted moving average (EWMA) techniques were explored. The SPC techniques were sensitive to process changes and trends over the 12 years of data collected. A reduction in the random component of patient setup errors needing correction was observed. Systematic components of error remained more stable. An uptick in both datasets was observed correlating with the COVID-19 pandemic. Process control limits for use in prospective process monitoring were established. Challenges that arose from using SPC techniques in a retrospective study are outlined.

A comparative study on automatic treatment planning for online adaptive proton therapy of esophageal cancer: which combination of deformable registration and deep learning planning tools performs the best?

Objective.To demonstrate the feasibility of integrating fully-automated online adaptive proton therapy strategies (OAPT) within a commercially available treatment planning system and underscore what limits their clinical implementation. These strategies leverage existing deformable image registration (DIR) algorithms and state-of-the-art deep learning (DL) networks for organ segmentation and proton dose prediction.Approach.Four OAPT strategies featuring automatic segmentation and robust optimization were evaluated on a cohort of 17 patients, each undergoing a repeat CT scan. (1) DEF-INIT combines deformably registered contours with template-based optimization. (2) DL-INIT, (3) DL-DEF, and (4) DL-DL employ a nnU-Net DL network for organ segmentation and a controlling ROIs-guided DIR algorithm for internal clinical target volume (iCTV) segmentation. DL-INIT uses this segmentation alongside template-based optimization, DL-DEF integrates it with a dose-mimicking (DM) step using a reference deformed dose, and DL-DL merges it with DM on a reference DL-predicted dose. All strategies were evaluated on manual contours and contours used for optimization and compared with manually adapted plans. Key dose volume metrics like iCTV D98% are reported.Main results.iCTV D98% was comparable in manually adapted plans and for all strategies in nominal cases but dropped to 20 Gy in worst-case scenarios for a few patients per strategy, highlighting the need to correct segmentation errors in the target volume. Evaluations on optimization contours showed minimal relative error, with some outliers, particularly in template-based strategies (DEF-INIT and DL-INIT). DL-DEF achieves a good trade-off between speed and dosimetric quality, showing a passing rate (iCTV D98% > 94%) of 90% when evaluated against 2, 4 and 5 mm setup error and of 88% when evaluated against 7 mm setup error. While template-based methods are more rigid, DL-DEF and DL-DL have potential for further enhancements with proper DM algorithm tuning.Significance.Among investigated strategies, DL-DEF and DL-DL demonstrated promising within 10 min OAPT implementation results and significant potential for improvements.

Setup errors analysis in iterative kV CBCT: A clinical study of cervical cancer treated with Volumetric Modulated Arc Therapy.

This study aims to analyze setup errors in pelvic Volumetric Modulated Arc Therapy (VMAT) for patients with non-surgical primary cervical cancer, utilizing the onboard iterative kV cone beam CT (iCBCT) imaging system on the Varian Halcyon 2.0 ring gantry structure accelerator to enhance radiotherapy precision. We selected 132 cervical cancer patients who underwent VMAT with daily iCBCT imaging guidance. Before each treatment session, a registration method based on the bony structure was employed to acquire iCBCT images with the corresponding planning CT images. Following verification and adjustment of image registration results along the three axes (but not rotational), setup errors in the lateral (X-axis), longitudinal (Y-axis), and vertical (Z-axis) directions were recorded for each patient. Subsequently, we analyzed 3642 iCBCT image setup errors. The mean setup errors for the X, Y, and Z axes were 4.50±3.79mm, 6.08±6.30mm, and 1.48±2.23mm, respectively. Before correction with iCBCT, setup margins based on the Van Herk formula for the X, Y, and Z axes were 6.28, 12.52, and 3.26mm, respectively. In individuals aged 60 years and older, setup errors in the X and Y axes were significantly larger than those in the younger group (p<0.05). Additionally, there is no significant linear correlation between setup errors and treatment fraction numbers. Data analysis underscores the importance of precise Y-axis setup for cervical cancer patients undergoing VMAT. Radiotherapy centers without daily iCBCT should appropriately extend the planning target volume (PTV) along the Y-axis for cervical cancer patients receiving pelvic VMAT. Elderly patients exhibit significantly larger setup errors compared to younger counterparts. In conclusion, iCBCT-guided radiotherapy is recommended for cervical cancer patients undergoing VMAT to improve setup precision.

Assessment of setup error in Three-Dimensional Conformal Radiotherapy (3-DCRT) during the treatment of patients with prostate or bladder cancers in Ayadi El-Mostakbal hospital (Alexandria, Egypt)

Assessment of setup error in Three-Dimensional Conformal Radiotherapy (3-DCRT) during the treatment of patients with prostate or bladder cancers in Ayadi El-Mostakbal hospital (Alexandria, Egypt)

309 - Analyzing the Impact of BMI on Breast Cancer Setup Errors in Prone Position Radiation Therapy: A Comparison of Manual and Automated Image Matching

309 - Analyzing the Impact of BMI on Breast Cancer Setup Errors in Prone Position Radiation Therapy: A Comparison of Manual and Automated Image Matching

Modeling and prediction of set‑up errors in breast cancer image‑guided radiotherapy using the Gaussian mixture model.

The aim of the present study was to develop a prediction model for set-up error distribution in breast cancer image-guided radiotherapy (IGRT) using a Gaussian mixture model (GMM). To achieve this, the image-guided set-up errors data of 80 patients with breast cancer were selected, and the GMM was used to develop the set-up errors distribution prediction model. The predicted error center points, covariance and probability were calculated and compared with the planning target volume (PTV) margin formula. A total of 1,200 sets of set-up errors in IGRT for breast cancer were collected. The results of the Gaussian model parameters showed that the set-up errors were mainly in the direction of µ1-µ4 center points. All the raw errors in the lateral, longitudinal and vertical directions were -6.30-4.60, -5.40-1.47 and -2.70-1.70 mm, respectively. According to the probability of each center, the set-up error was most likely to shift in the µ1 direction, reaching 0.53. The set-up errors of the other three centers, µ2, µ3 and µ4, were 0.11, 0.34 and 0.12, respectively. According to the covariance parameters of the GMM, the maximum statistical standard deviation of the set-up errors reached 29.06. In conclusion, the results of the present study demonstrated that the GMM can be used to quantitatively describe and predict the distribution of set-up errors in IGRT for breast cancer, and these findings could be useful as a reference for set-up error control and tumor PTV expansion in breast cancer radiotherapy without routine, daily IGRT.

The accuracy of cone beam computed tomography (CBCT) technique as an image-guided radiation therapy (IGRT) technique.

To measure the setup error of the patient's positioning using cone-beam computed tomography during radiation therapy treatment fractions by finding systematic, random errors and the planned target volume errors. The observational, longitudinal cohort study was conducted at the Al-Warith International Cancer Institute, Karbala, Iraq, from January to May 2022, and comprised patients with head and neck cancer who underwent radiation therapy. The oncologist delineated and the medical physicist planned. Then the medical physicist modified the positioning system using the cone beam computed tomography option workstation. The vertical value was taken in anteroposterior site, longitudinal in superoinferior, and lateral in e mediolateral. The SPSS 25 were used to analyse data. Of the 31 patients, 17(54.8%) were females and 14(45.2%) were males. The overall mean age was 48.3 ± 10.22 (range: 4-77 years), and 22(70.96%) patients had been treated previously with chemotherapy. The lateral shifting inaccuracy 2.501mm was above the limit, whereas the vertical shifting 1.164mm was within acceptable limits (±2mm). The longitudinal shifting had the smallest displacement 0.436mm. Random error displayed longitudinal moving 1.965mm, lateral shifting 0.623mm and vertical shifting 0.276mm. The planned target volume margins were too wide in longitudinal shifting 3.333mm. Vertical shifting 0.481mm was greater than lateral 1.092mm, but both were within limits (±2mm). Radiation-induced errors in normal tissues must be reduced by reducing planned target volume margins, especially for longitudinal and lateral directions.

Preliminary study of feasibility of surface-guided radiotherapy with concurrent tumor treating fields for glioblastoma: region of interest

ObjectiveTo evaluate the impact of the residual setup errors from differently shaped region of interest (ROI) and investigate if surface-guided setup can be used in radiotherapy with concurrent tumor treating fields (TTFields) for glioblastoma.MethodsFifteen patients undergone glioblastoma radiotherapy with concurrent TTFields were involved. Firstly, four shapes of region of interest (ROI) (strip-shaped, T-shaped, ⊥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\perp$$\\end{document}-shaped and cross-shaped) with medium size relative to the whole face were defined dedicate for patients wearing TTFields transducer arrays. Then, ROI-shape-dependent residual setup errors in six degrees were evaluated using an anthropomorphic head and neck phantom taking CBCT data as reference. Finally, the four types of residual setup errors were converted into corresponding dosimetry deviations (including the target coverage and the organ at risk sparing) of the fifteen radiotherapy plans using a feasible and robust geometric-transform-based method.ResultsThe algebraic sum of the average residual setup errors in six degrees (mm in translational directions and ° in rotational directions) of the four types were 6.9, 1.1, 4.1 and 3.5 respectively. In terms of the ROI-shape-dependent dosimetry deviations, the D98% of PTV dropped off by (3.4 ± 2.0)% (p < 0.05), (0.3 ± 0.5)% (p < 0.05), (0.9 ± 0.9)% (p < 0.05) and (1.1 ± 0.8)% (p < 0.05). The D98% of CTV dropped off by (0.5 ± 0.6)% (p < 0.05) for the strip-shaped ROI while remained unchanged for others.ConclusionSurface-guided setup is feasible in radiotherapy with concurrent TTFields and a medium-sized T-shaped ROI is appropriate for the surface-based guidance.

Clinical advantages of incorporating predicted weekly anatomy in IMPT optimization with reduced setup error

AbstractBackgroundIn head and neck (H&amp;N) cancer treatment, a conventional setup error (SE) of 3mm is often used in robust optimization (cRO3mm). However, cRO3mm may lead to excessive radiation doses to organs at risk (OARs) and does not purposefully compensate for interfractional anatomy variations.PurposeThis study introduces a method using predicted images from an anatomical model and a reduced 1mm SE uncertainty for robust optimization (aRO1mm), aiming to decrease the dose to OARs without affecting the coverage of the clinical target volume (CTV).MethodsThis retrospective study involved 10 nasopharynx radiotherapy patients. Validation CT scans (vCT) from treatment weeks 1 to 6 were analyzed. A predictive anatomical model, designed to capture the average anatomical changes over time, provided predicted CT images for weeks 1, 3, and 5. We compared three optimization scenarios: (1) aRO1mm, using three predicted images with 1mm setup shift and 3% range uncertainty, (2) cRO3mm, with a robust 3mm setup shift and 3% range uncertainty, and (3) cRO1mm, a robust 1mm setup shift and 3% range uncertainty. The accumulated dose to CTVs and serial organs was evaluated under these uncertainties, while parallel OARs were assessed using the accumulated nominal dose (without errors).ResultsThe accumulated volume receiving 94% of the prescribed dose (V94) for CTVs in cRO3mm exceeded 98%, meeting the clinical goal. For high‐risk CTV, the minimum V94 was 96.44% in aRO1mm and 94.05% in cRO1mm. For low‐risk CTV, these values were 97.68% in aRO1mm and 97.15% in cRO1mm. When comparing aRO1mm to cRO3mm on OARs, aRO1mm reduced normal tissue complication probability (NTCP) for grade 2 xerostomia and dysphagia by averages of 3.67% and 1.54%, respectively.ConclusionaRO1mm lowers the radiation dose to OARs compared to the traditional approach, while maintaining adequate dose coverage on the target area. This method offers an improved strategy for managing uncertainties in radiation therapy planning for H&amp;N cancer, enhancing treatment effectiveness.

Mitigating Risks in Cone Beam Computed Tomography Guided Online Adaptive Radiation Therapy: A Preventative Reference Planning Review Approach

PurposeOnline adaptive radiotherapy (oART) treatment planning requires evaluating the temporal robustness of reference plans, anticipating the potential changes during treatment courses that may even lead to risks unique to the adaptive workflow. This study conducted a risk analysis of the CBCT-guided adaptive workflow and is the first to assess an adaptive specific reference planning review that mitigates risk in the planning process to prevent events and treatment deficiencies during adaptation. Methods and MaterialsA quality management team of medical physicists, residents, physicians, and radiation therapists performed a fault tree analysis, and failure mode and effects analysis (FMEA). Fault trees were created for under/overdosing targets, treatment deficiencies, as well as assisted in identifying failure modes for the FMEA. Treatment deficiency was defined to include a non-ideal oART plan resulting in treatment with a lower quality plan (either oART or scheduled plan), treatment delay, or cancelling treatment for the day. A reference planning checklist was created to catch failure modes before reaching the patient. Risk priority numbers (RPN=Severity*Detectability*Occurrence) were scored with and without the reference planning checklist to quantify risk mitigation. A root cause analysis was conducted for an event where an adaptive plan failed to generate. ResultsThe reference planning checklist (with items covering patient background, contouring/planning robustness for anatomy variability, and machine limitations) reduced the RPN for all failure modes. Only 1 failure mode with a risk priority number >150 occurred with the reference planning checklist compared to 29 failure modes without, including 14 adaptive specific failure modes. Contouring, planning, setup, scheduling, and documentation errors were identified during the fault tree analysis. 29/70 errors were adaptive specific. The reference planning checklist could address 23/33 for over/under dosing and 28/37 errors for treatment deficiency. The root cause analysis highlighted the need for checking setup prior to adaptive plan delivery, and time-out checklist. ConclusionsThe reference planning checklist improved detection of the failure modes and improves the quality and robustness of the plans produced for oART. It is ideally performed before physician plan review to prevent last minute re-plan (before or after first adaptive treatment) and delay of patient start. The checklist presented can be modified based on failures specific to individual clinics and utilized at various planning steps based on available resources.

Assessment of using an Octavius 4D Measuring System for Patient-specific VMAT Quality Assurance in Togo

Purpose and objective: Quality assurance (QA) programs are designed to improve the quality and the safety of radiation treatments, including machine- and patient-specific QA (PSQA). The objective of this study was to evaluate the current state of PSQA practice and identify the area for potential improvement for VMAT delivery. Materials and methods: The Octavius 4D (O4D) system accuracy was evaluated using an O4D homogeneous phantom for different field sizes. The system response to dose linearity, field sizes, and PDD difference tests were performed against the calculated dose of the treatment planning system (TPS) for a 6 MV photon beam. The deviation of the delivered dose was evaluated at the isocenter and different depths. Moreover, pretreatment verification of 40 VMAT plans was performed including prostate cancer (PC), head and neck cancer (HNC), uterine and cervical cancer (UCC), and breast cancer (BC). The PTW VeriSoft software was used to perform the local and global 3D gamma analysis by comparing the reconstructed 3D dose against the calculated dose using criteria 2%/2 mm and 3%/3 mm, 20% of low-dose threshold, and 95% of gamma passing rate (%GP) tolerance level. In the clinical scenario, the sensitivity of the O4D system in detecting VMAT delivery and setup errors has been investigated by measuring the variation of %GP values before and after the simulated errors using one of the VMAT plans related to each treatment site. Results: The O4D system reported good agreement for linearity, field size, and PDD differences with TPS dose being within ± 2% tolerance for a 6 MV photon beam. Output factors were consistent between the ionization chamber and the O4D detector 1500 array down to 4 x 4 cm2 field size with a maximum deviation of less than 1%. The introduction of deliberate errors caused the decrease of %GP values. In most scenarios, the %GP value of simulated errors was detected with 2%/2 mm and ranged between the detection threshold and gamma passing threshold. Conclusion: The results indicate that the O4D system is sensitive to detect delivery and setup errors with restrictive criteria of 2%/2 mm for routine pretreatment verification. Moreover, this system should be used in combination with kV-CBCT to improve dosimetry accuracy and treatment reproducibility.

Effect of body contour changes on the setup and dosimetric accuracy of radiotherapy after cervical cancer surgery.

The body contour of patients with cervical cancer is prone to change between radiotherapy sessions. This study aimed to investigate the effect of body contour changes on the setup and dosimetric accuracy of radiotherapy. 15 patients with cervical cancer after surgery were randomly selected for retrospective analysis. The body contours on the once-per-week cone-beam computed tomography (CBCT) were registered to the planning CT (pCT) for subsequent evaluation. A body contour conformity index (CIbody) was defined to quantify the variation of body changes. The body volume measured by CBCT was collected, and its relative difference in reference with the first CBCT was calculated and denoted by ΔVn. The relative setup errors, denoted by ΔSELR, ΔSEAP, ΔSESI, and ΔSEvec for left-right, anterior-posterior, superior-inferior, and vectorial shifts, respectively, were defined as the difference in measured setup errors between the reference and following CBCTs. The planned dose was calculated on the basis of virtual CT generated from CBCT and pCT by altering the CT body contour to fit the body on CBCT without deformable registration. The correlations between body contour changes and relative setup errors as well as dosimetric parameters were evaluated using Spearman's correlation coefficient rs . CIbody was found to be negatively correlated with the superior-inferior and vectorial relative setup errors ΔSESI (rs = -0.448, p = 0.001) and ΔSEvec (rs = -0.387, p = 0.002), and no significant correlation was found between relative setup errors and ΔVn. Moreover, ΔVn was negatively correlated with ΔD2 (rs = -0.829, p < 0.001), ΔD98 (rs = -0.797, p < 0.001), and ΔTVPIV (rs = -0.819, p < 0.001). ΔD2, ΔD98, and ΔTVPIV were negatively correlated with ΔVn (p < 0.005). No correlation was found for other examined dosimetric parameters. The body contour change of patients could be associated with the setup variability. The effect of body contour changes on dose distribution is minimal. The extent of body change could be used as a metric for radiation therapists to estimate the setup errors.

370: Impact of two different Immobilization devices in reducing set-up errors during pelvic radiotherapy

370: Impact of two different Immobilization devices in reducing set-up errors during pelvic radiotherapy

ACSwinNet: A Deep Learning-Based Rigid Registration Method for Head-Neck CT-CBCT Images in Image-Guided Radiotherapy.

Accurate and precise rigid registration between head-neck computed tomography (CT) and cone-beam computed tomography (CBCT) images is crucial for correcting setup errors in image-guided radiotherapy (IGRT) for head and neck tumors. However, conventional registration methods that treat the head and neck as a single entity may not achieve the necessary accuracy for the head region, which is particularly sensitive to radiation in radiotherapy. We propose ACSwinNet, a deep learning-based method for head-neck CT-CBCT rigid registration, which aims to enhance the registration precision in the head region. Our approach integrates an anatomical constraint encoder with anatomical segmentations of tissues and organs to enhance the accuracy of rigid registration in the head region. We also employ a Swin Transformer-based network for registration in cases with large initial misalignment and a perceptual similarity metric network to address intensity discrepancies and artifacts between the CT and CBCT images. We validate the proposed method using a head-neck CT-CBCT dataset acquired from clinical patients. Compared with the conventional rigid method, our method exhibits lower target registration error (TRE) for landmarks in the head region (reduced from 2.14 ± 0.45 mm to 1.82 ± 0.39 mm), higher dice similarity coefficient (DSC) (increased from 0.743 ± 0.051 to 0.755 ± 0.053), and higher structural similarity index (increased from 0.854 ± 0.044 to 0.870 ± 0.043). Our proposed method effectively addresses the challenge of low registration accuracy in the head region, which has been a limitation of conventional methods. This demonstrates significant potential in improving the accuracy of IGRT for head and neck tumors.

Optimal Correction Strategy of Image Guided Radiation Therapy Including the Paraortic Lymph Node Region in Patients With Cervical Cancers

The clinically accepted planning target volume margin for radiation therapy to the paraortic nodal region in cervical cancer patients is 5 mm. However, the comprehensive alignment and variability from the pelvic bone to all lumbar vertebrae are undetermined. This study aims to quantify the residual setup errors between the pelvic bone and lumbar vertebrae and determine the optimal correction strategy for patients with cervical cancer. Fifteen patients underwent pretreatment mega-voltage computed tomography scans (375 total fractions). Residual setup errors and required margins for each lumbar vertebra were calculated based on registrations accounting for pelvic rotation and translation. The systematic residual errors (1 SD) at L1, L2, L3, L4, and L5 using pelvic bone registration were 6.5, 4.9, 3.1, 1.5, and 0.6 mm in the anterior-posterior (AP) direction, 3.1, 2.3, 1.4, 0.6, and 0.3 mm in the right-left direction, and 2.7, 2.2, 1.7, 1.0, and 0.5 mm in the superior-inferior direction, respectively. The residual setup errors were the largest in the AP direction. Registration based on the pelvic bone required margins in the AP direction of 16.0, 12.1, 7.7, 3.6, and 1.3 mm for L1, L2, L3, L4, and L5, respectively, whereas registration based on L3 required margins of 8.8, 4.8, 4.4, 7.1, and 7.7 mm for L1, L2, L4, L5, and pelvic bone, respectively. Considerable local setup variability was found in patients with cervical cancer. After reviewing the corrective strategies, we determined that L3-based registration effectively minimized the required margins.

Treatment Reproducibility in Brain Stereotactic Radiotherapy Using a Shim Mask Versus a Standard Mask.

Introduction This study aimed to evaluate the setup accuracy of the new shim mask with mouth bite compared to the standard full brain mask in stereotactic radiosurgery (SRS) and radiotherapy (SRT) treatments for brain metastases or tumors. Method A combined retrospective and prospective design was employed, involving 40 patients treated at our center. Patients previously treated using standard head masks formed the retrospective cohort, while those treated with the Shim mask and mouth bite formed the prospective cohort. Daily cone-beam computed tomography (CBCT) scans were obtained before each treatment session to ensure patient setup accuracy. Key metrics included absolute shifts in translational and rotational directions, the number of repeat CBCTs, and the time interval between CBCTs. Results The Shim mask significantly reduced the mean setup errors in the lateral translation (p=0.022) from 0.17 cm (SD=0.10) to 0.10 cm (SD=0.10), and in X-axis rotation (p=0.030) from 0.79° (SD=0.43) to 0.47° (SD=0.47). By considering cutoff points of 1 mm in translational and 1° in rotational directions, the Shim mask was significantly more accurate in the lateral direction (p=0.004). Moreover, while 70% of patients in the standard group required repeat CBCT scans, none in the Shim group did, resulting in an average time saving of 10.4 minutes per patient. Conclusion The Shim mask with mouth bite offers enhanced immobilization accuracy in SRT/SRS treatments, leading to time and potential cost savings by reducing the need for repeat CBCT scans. This underscores the importance of adopting innovative immobilization techniques to optimize patient outcomes.

40 Evaluation of set-up errors using CBCT in Head and Neck cancer patients treated with IMRT in UMMC

40 Evaluation of set-up errors using CBCT in Head and Neck cancer patients treated with IMRT in UMMC

A visual management and augmented-reality-based training module for the enhancement of short and long-term procedural knowledge retention in complex machinery setup

Proper training for operators is essential, given the complexity of modern manufacturing and the challenges posed by diverse worker demographics and high workforce turnover. Since conventional training methods are inadequate when considering the mentioned challenges, digital technologies and assistive devices can be used to improve information management. This work studies how the combination of Augmented Reality (AR) and Visual Management (VM) supports worker training by considering short- and long-term efficacy. The literature gaps on researching the training and knowledge retention of manufacturing workers using combined lean tools and digital technologies indicate that current studies focus on short-term training performed in laboratories, overlooking the integration of VM and AR for industrial training. Thus, the authors developed and validated in practice a VMAR-based training module for the setup of complex machinery in the process industry. To assess its efficacy, a comparison between a test group and a confirmation group of company’s workers has been performed. The number and types of setup error have been collected and analysed to evaluate and compare short- and long-term procedural knowledge retention. The results reveal that the VMAR-based training module better supports workers both in the short- and long-period compared with traditional working procedures. Furthermore, the analysis demonstrates the inefficacy of traditional approaches in properly supporting the training of complex machinery setups considering the study’s application. Future works should address the assessment of knowledge retention by considering a longer period, as well as on physiological data collection to better understand which elements of the training module are most crucial to the transfer of knowledge.