Surface Guided Radiation Therapy Research Articles

Optical Surface-guided Radiation Therapy for Upper and Lower Limb Sarcomas: An Analysis of Setup Errors and Clinical Target Volume-To-Planning Target Volume Margins

PurposeTo assess the clinical benefits of surface-guided radiotherapy (SGRT) in terms of setup error, positioning time, and clinical target volume-to-planning target volume (CTV-PTV) margin in extremity soft tissue sarcoma (STS). Methods and MaterialsFifty consecutive patients treated with radiotherapy were retrospectively selected. Treatment setup was performed with either laser-based imaging only (control group), or with laser-based and daily optical surface-based imaging (SGRT group). Pre-treatment cone beam computed tomography images were acquired daily for the first 3 – 5 fractions and weekly thereafter, with the frequency adjusted as necessary. Translational and rotational errors were collected. CTV-PTV margin was calculated using the formula, 2.5Σ + 0.7σ. ResultsEach group consisted of 10 and 15 upper and lower limb STSs, respectively. For patients with upper limb sarcomas, the translation errors were (1.64 ± 1.34) mm, (1.10 ± 1.50) mm, and (1.24 ± 1.45) mm in SGRT group, and (1.48 ± 3.16) mm, (2.84 ± 2.85) mm, and (3.14 ± 3.29) mm in control group in the left-right (LR), supero-inferior (SI), and antero-posterior (AP) directions, respectively. Correspondingly, for patients with lower limb sarcomas, the translation errors were (1.21 ± 1.65) mm, (1.39 ± 1.71) mm, and (1.48 ± 2.10) mm in SGRT group, and (1.81 ± 2.60) mm, (2.93 ± 3.28) mm, and (3.53 ± 3.75) mm in control group, respectively. The calculated CTV-PTV margins of SGRT group and control group were 5.0 mm, 3.8 mm, 4.1 mm vs. 5.9 mm, 9.1 mm, 10.1 mm for upper limb sarcomas; and 4.2 mm, 4.7 mm, 5.2 mm vs. 6.3 mm, 9.6 mm, 11.4 mm for lower limb sarcomas in the LR, SI, and AP directions, respectively. ConclusionDaily optical surface guidance can effectively improve the setup accuracy of extremity STS patients, and safely reduce the required CTV-PTV margins.

The impact of a prophylactic skin dressing on surface-guided patient positioning in chest wall Radiation Therapy.

Surface-guided radiation therapy (SGRT) has emerged as a powerful tool to improve patient setup accuracy in radiation therapy (RT). Combined with the goal of increasing RT accuracy is an ongoing effort to decrease RT side effects. The application of a prophylactic skin dressing to the treatment site is a well-documented method of reducing skin-related side effects from RT. This paper aims to investigate whether the application of Mepitel, a prophylactic skin dressing, has an impact on the accuracy of surface-guided patient setups in chest wall RT. A retrospective analysis of daily image-guided Online Corrections (OLCs) from patients undergoing chest wall irradiation with SGRT was performed. Translational (superior-inferior, lateral, and anterior-posterior) OLC magnitude and direction were compared between patients treated with Mepitel applied and those treated without. Systematic and random errors were calculated and compared between groups. OLCs from 275 fractions were analysed. Mean OLCs were larger for patients with Mepitel applied in the superior_inferior axis (0.34 vs. 0.22 cm, P = 0.049) and for the combined translational vector (0.54 vs. 0.43 cm, P = 0.043). Combined translational systematic error was slightly larger for patients with Mepitel applied (0.15 vs. 0.09 cm). Mepitel can impact the accuracy of SGRT patient-positioning in chest wall RT. The variation however is small and unlikely to have any clinical impact if SGRT is coupled with image guidance and appropriate PTV margins. Further investigation is required to assess the effect of Mepitel on SGRT accuracy in other treatment sites, as well as any potential dosimetric impacts.

Characterization of the IDENTIFYTM surface scanning system for radiation therapy setup on a closed-bore linac.

In radiation therapy, surface guidance can be used for patient setup and intra-fraction motion monitoring. The surface guided radiation therapy (SGRT) system from Varian Medical systems, IDENTIFYTM, consists of three pods, including cameras and a random pattern projector, mounted on the ceiling. The information captured by the cameras is used to make a reconstruction of the surface. The aim of the study was to assess the technical performance of this SGRT system on a closed-bore linac. Phantom measurements were performed to assess the accuracy, precision, reproducibility and temporal stability of the system, both in align and in load position. Translations of the phantoms in lateral, longitudinal, and vertical direction, and rotations around three axes (pitch, roll and yaw) were performed with an accurate, in-house built, positioning stage. Different phantom geometries and different surface colors were used, and various ambient light intensities were tested. The accuracy of the IDENTIFYTM system at the closed-bore linac was 0.07mm and 0.07 degrees at load position, and 0.06mm and 0.01 degrees at align position for the white head phantom. The precision was 0.02mm and 0.02 degrees in load position, and 0.01mm and 0.02 degrees in align position. The accuracy for the Penta-Guide phantom was comparable to the white head phantom, with 0.06mm and 0.01 degrees in align position. The system was slightly less accurate for translations of the CIRS lung phantom in align position (0.20mm, 0.05 degrees). Reproducibility measurements showed a variation of 0.02mm in load position. Regarding the temporal stability, the maximum drift over 30min was 0.33mm and 0.02 degrees in load position. No effect of ambient light level on the accuracy of the IDENTIFYTM system was observed. Regarding different surface colors, the accuracy of the system for a black phantom was slightly worse compared to a white surface, but not clinical relevant. The IDENTIFYTM system can adequately be used for motion monitoring on a closed-bore linac with submillimeter accuracy. The results of the performed measurements meet the clinical requirements described in the guidelines of the AAPM and the ESTRO.

Automated Test for Monthly Quality Assurance of Optical Surface Imaging Dynamic Localization Accuracy.

The American Association of Physicists in Medicine (AAPM) recently published the report of Task Group (TG) 302, which provides recommendations on acceptance, commissioning, and ongoing routine quality assurance (QA) for surface-guided radiation therapy (SGRT) systems. One of the recommended monthly QA tests is a dynamic localization accuracy test. This work aimed to develop an automated procedure for monthly SGRT dynamic localization QA. An anthropomorphic head phantom was rigidly attached to the 6-dof couch of a TrueBeam linac. TrueBeam Developer Mode was used to take an MV image of the phantom at the starting position, then automatically drive the couch through a series of translations and rotations, taking an MV image after each translation. The Identify SGRT system monitored the motion of the phantom surface from the starting position. Translations assessed on MV images were compared to translations reported in trajectory log files and Identify log files. Rotations were compared between trajectory log files and Identify log files. Three experiments were conducted. None of the translations or rotations from any experiment exceeded the tolerance values for stereotactic ablative body radiation therapy (SABR) recommended by AAPM TG-142. Maximum deviations from the expected translation values from MV imaging, trajectory log files, and Identify log files were -0.94mm, -0.11mm, and -0.78mm, respectively. Maximum deviations from the expected rotation values from trajectory log files and Identify log files were 0.01 and -0.2 degrees, respectively. The proposed method is a simple automated way to complete monthly dynamic localization QA of SGRT systems.

Verification of surface-guided radiation therapy (SGRT) alignment for proton breast and chest wall patients by comparison to CT-on-rails and kV-2D alignment.

Surface-guided radiation therapy (SGRT) systems have been widely installed and utilized on linear accelerators. However, the use of SGRT with proton therapy is still a newly developing field, and published reports are currently very limited. To assess the clinical application and alignment agreement of SGRT with CT-on-rails (CTOR) and kV-2D image-guided radiation therapy (IGRT) for breast treatment using proton therapy. Four patients receiving breast or chest wall treatment with proton therapy were the subjects of this study. Patient #1's IGRT modalities were a combination of kV-2D and CTOR. CTOR was the only imaging modality for patients #2 and #3, and kV-2D was the only imaging modality for patient #4. The patients' respiratory motions were assessed using a 2-min surface position recorded by the SGRT system during treatment. SGRT offsets reported after IGRT shifts were recorded for each fraction of treatment. The agreement between SGRT and either kV-2D or CTOR was evaluated. The respiratory motion amplitude was<4mm in translation and <2.0° in rotation for all patients. The mean and maximum amplitude of SGRT offsets after application of IGRT shifts were ≤(2.6mm, 1.6° ) and (6.8mm, 4.5° ) relative to kV-2D-based IGRT; ≤(3.0mm, 2.6° ) and (5.0mm, 4.7° ) relative to CTOR-based IGRT without breast tissue inflammation. For patient #3, breast inflammation was observed for the last three fractions of treatment, and the maximum SGRT offsets post CTOR shifts were up to (14.0mm, 5.2° ). Due to the overall agreement between SGRT and IGRT within reasonable tolerance, SGRT has the potential to serve as a valuable auxiliary IGRT tool for proton breast treatment and may improve the efficiency of proton breast treatment.

The Remove-the-Mask Open-Source head and neck Surface-Guided radiation therapy system

Background and PurposeSurface Guided Radiotherapy (SGRT) for head and neck radiotherapy is challenging as obstructions are common and non-rigid facial motion can compromise surface accuracy. The purpose of this work was to develop and benchmark the Remove the Mask (RtM) SGRT system, an open-source system especially designed to address the challenges faced in radiotherapy of head and neck cancer. Materials and MethodsThe accuracy of the RtM SGRT system was benchmarked using a head phantom positioned on a robotic motion platform capable of sub-millimetre accuracy which was used to induce unidirectional shifts and to reproduce three real head motion traces. We also assessed the accuracy of the system in ten humans volunteers. The ground truth motion of the volunteers was obtained using a commercial motion capture system with an accuracy < 0.3 mm. ResultsThe mean tracking error of the RtM SGRT system for the ten volunteers was of −0.1 ± 0.4 mm −0.6 ± 0.6 mm and 0.3 ± 0.2 mm, and 0.0 ± 0.2° 0.0 ± 0.1° and 0.0 ± 0.2° for translations and rotations along the left–right, superior-inferior and anterior-posterior axes respectively and we also found similar results in measurements with the head phantom. Forced facial motion was associated with lower tracking accuracy. The RtM SGRT system achieved submillimetre accuracy. ConclusionThe RtM SGRT system is a low-cost, easy to build and open-source SGRT system that can achieve an accuracy that meets international commissioning guidelines. Its open-source and modular design allows for the development and easy translation of novel surface tracking techniques.

Development of automated region of interest selection algorithms for surface-guided radiation therapy of breast cancer.

To investigate automation of the preparation of the region of interest (ROI) for surface-guided radiotherapy (SGRT) of the whole breast with two algorithms based on contour anatomies: using the body contour, and using the breast contour. The patient dataset used for modeling consisted of 39 breast cancer patients previously treated with SGRT. The patient's anatomical structures (body and ipsilateral breast) were retrieved from the planning system, and the clinical ROI (cROI) drawn by the planners was retrieved from the SGRT system for comparison. For the body-contour-based algorithm, a convolutional neural network (MobileNet-v2) was utilized to train a synthetic human model dataset to predict body joint locations. With the body joint location knowledge, an automated ROI (aROIbody ) can be created based on: (1) the superior-inferior (S-I) borders defined by the joint locations, (2) the left-right (L-R) borders defined with 3/4 of chest width, and (3) a curation of the ROI to avoid the ipsilateral armpit. For the breast-contour-based algorithm, an aROIbreast was created by first defining the ROI in the S-I direction with the ipsilateral breast boundaries. Other steps are the same as with the body-contour-based algorithm. Among the 39 patients, 24 patients were used to fine-tune the algorithm parameters, and the remaining 15 patients were used to evaluate the quality of the aROIs against the cROIs. A blinded evaluation was performed by three SGRT expert physicists to rate the acceptability and the quality (1-10 scale) of the aROIs and cROIs, and the dice similarity coefficient (DSC) was also calculated to compare the similarity between the aROIs and cROIs. The results showed that the average acceptability was 14/15 (range: 13/15-15/15) for cROIs, 13.3/15 (range: 13/15-14/15) for aROIbody , and 14.6/15 (range: 14/15-15/15) for aROIbreast . The average quality was 7.4 ± 0.8 for cROIs, 8.1 ± 1.2 for aROIbody , and 8.2 ± 0.9 for aROIbreast . The DSC with cROIs was 0.81 ± 0.06 for aROIbody , and 0.83 ± 0.04 for aROIbreast . The ROI creation time was ∼120s for clinical, 1.3s for aROIbody , and 1.2s for aROIbreast . The proposed automated algorithms can improve the ROI compliance with the SGRT protocol, with a shortened preparation time. It is ready to be integrated into the clinical workflow for automated ROI preparation.

A Couch Mounted Smartphone-based Motion Monitoring System for Radiation Therapy

PurposeSurface-guided radiation-therapy (SGRT) systems are being adopted into clinical practice for patient setup and motion monitoring. However, commercial systems remain cost prohibitive to resource-limited clinics around the world. Our aim is to develop and validate a smartphone-based application using LiDAR cameras (such as on recent Apple iOS devices) for facilitating SGRT in low-resource centers. The proposed SGRT application was tested at multiple institutions, and validated using phantoms and volunteers against various commercial systems to demonstrate feasibility. Methods and MaterialsAn iOS application was developed in Xcode and written in Swift using the Augmented-Reality (AR) Kit and implemented on an Apple iPhone 13 Pro with a built-in LiDAR camera. The application contains multiple features: 1) visualization of both the camera and depth video feeds (at a ∼60Hz sample-frequency), 2) region-of-interest (ROI) selection over the patient's anatomy where motion is measured, 3) chart displaying the average motion over time in the ROI, and 4) saving/exporting the motion traces and surface map over the ROI for further analysis. The iOS application was tested to evaluate depth measurement accuracy for: 1) different angled surfaces, 2) different field-of-views over different distances, and 3) similarity to a commercially available SGRT systems (Vision RT AlignRT® and Varian IDENTIFY™) with motion phantoms and healthy volunteers across three institutions. Measurements were analyzed using linear-regressions and Bland-Altman analysis. ResultsCompared to the clinical system measurements (reference), the iOS application showed excellent agreement for depth (r=1.000,p<0.0001; bias=-0.07±0.24cm) and angle (r=1.000,p<0.0001; bias=0.02±0.69°) measurements. For free-breathing traces, the iOS application was significantly correlated to phantom motion (institute 1: r=0.99,p<0.0001; bias=-0.003±0.03cm; institute 2: r=0.98,p<0.0001; bias=-0.001±0.10cm; institute 3: r=0.97,p<0.0001; bias=0.04±0.06cm) and healthy volunteer motion (institute 1: r=0.98,p<0.0001; bias=-0.008±0.06cm; institute 2: r=0.99,p<0.0001; bias=-0.007±0.12cm; institute 3: r=0.99,p<0.0001; bias=-0.001±0.04cm). ConclusionThe proposed approach using a smartphone-based application provides a low-cost platform that could improve access to surface-guided radiation therapy accounting for motion.

RADT-47. MARGIN REDUCTION WITH THE INTRODUCTION OF INTRA-FRACTIONAL MONITORING USING IDENTIFY SGRT FOR FRAMELESS STEREOTACTIC CRANIAL RADIOSURGERY (SRS)

Abstract The purpose of this study was to evaluate the potential for margin reduction in clinical treatment settings based on the accuracy of Varian Identify SGRT (Surface-Guided Radiation Therapy). The study considered various factors such as patient setup variations, intrafraction movement, and unique facial features. Identify version 2.3.1 was installed on a Truebeam v2.7 system and commissioned according to AAPM TG3021 test recommendations. Identify generated reports on patient offsets in all six degrees of freedom during motion monitoring. These offsets were retrospectively compared with radiographic images (CBCT and MV planar images) to determine the accuracy of patient positioning achieved using surface guidance. A retrospective analysis of 36 patients was performed for a total of 125 fractions. The characteristics of the patient cohort (age range from 39 – 92 years) consisted of a mixture of 8 benign, 28 malignant lesions, 11 single, 25 standard fully-fractionated treatments and anatomical sites such as parietal, frontal, ventricle, base of skull, pons and acoustic neuromas. RESULTS: show that for this clinical cohort, the variance between Identify and radiographic imaging ranges from -0.02 to 0.08 cm, -0.09 to 0.10 cm, -0.09 to 0.09 cm and -0.81 to 0.74 degrees for the vertical, longitudinal, lateral and rotation respectively. This average variance in the translational axes is 0.0cm ± 0.0014 cm, indicating no directional preference. The 3D vector of the displacement detected achievable by Identify is 1 mm within a 95% confidence interval (CI). Based on the findings, the researchers concluded that a minimum GTV-PTV (Gross Tumor Volume-Planning Target Volume) margin of 1 mm is appropriate for intrafraction monitoring with Identify SGRT on the TrueBeam system for stereotactic cranial treatments. This information can increase the radiation oncologist's confidence in patient positioning during treatment delivery and potentially lead to a decrease in the GTV-PTV margin.

Characteristics of detection accuracy of the patient setup using InBore optical patient positioning system.

This study aimed to evaluate the detection accuracy of the AlignRT-InBore system in surface-guided radiation therapy using a phantom and to determine the feasibility of the system by conducting a comparative analysis with cone-beam computed tomography (CBCT) registration. The AlignRT-InBore system integrated with the ETHOS Therapy was used. A phantom and a QUASAR phantom were employed to examine the specific areas of interest relevant to clinical cases. The evaluation involved monitoring translations for approximately 30 min and assessing the position detection accuracy for static and moving objects. Fifty clinical cases were used to evaluate the position detection accuracy and its relationship with the localization accuracy of CBCT before treatment. The detection accuracy of static and moving objects was within 1.0 mm using the phantom. However, the longitudinal direction tended to be larger than the other directions. Regarding the accuracy of localization in clinical cases, a strong and statistically significant (p<0.01) correlation was observed in each direction. A detection accuracy within 1.0 mm is possible for static and moving objects. The detection accuracy of the patient setup using the InBore optical patient positioning system was extremely high, and the patient could be detected with high precision, suggesting its usefulness.

Application of surface-guided radiation therapy in prostate cancer: comparative analysis of differences with skin marking-guided patient setup.

Surface-guided radiation therapy is an image-guided method using optical surface imaging that has recently been adopted for patient setup and motion monitoring during treatment. We aimed to determine whether the surface guide setup is accurate and efficient compared to the skin-marking guide in prostate cancer treatment. The skin-marking setup was performed, and vertical, longitudinal, and lateral couch values (labeled as "M") were recorded. Subsequently, the surface-guided setup was conducted, and couch values (labeled as "S") were recorded. After performing cone-beam computed tomography (CBCT), the final couch values was recorded (labeled as "C"), and the shift value was calculated (labeled as "Gap (M-S)," "Gap (M-C)," "Gap (S-C)") and then compared. Additionally, the setup times for the skin marking and surface guides were also compared. One hundred and twenty-five patients were analyzed, totaling 2,735 treatment fractions. Gap (M-S) showed minimal differences in the vertical, longitudinal, and lateral averages (-0.03 cm, 0.07 cm, and 0.06 cm, respectively). Gap (M-C) and Gap (S-C) exhibited a mean difference of 0.04 cm (p = 0.03) in the vertical direction, a mean difference of 0.35 cm (p = 0.52) in the longitudinal direction, and a mean difference of 0.11 cm (p = 0.91) in the lateral direction. There was no correlation between shift values and patient characteristics. The average setup time of the skin-marking guide was 6.72 minutes, and 7.53 minutes for the surface guide. There was no statistically significant difference between the surface and skin-marking guides regarding final CBCT shift values and no correlation between translational shift values and patient characteristics. We also observed minimal difference in setup time between the two methods. Therefore, the surface guide can be considered an accurate and time-efficient alternative to skin-marking guides.

Robustness Analysis of Reference Surfaces for Surface Guided Radiation Therapy of the Breast

Surface guided radiation therapy (SGRT) implements an optical imaging system in radiation therapy for positioning and motion management. This system projects visible light onto a patient and the reflected light is used to generate 3D positional information so that clinicians can accurately reproduce body positions. Patient setup shifts are calculated with six degrees of freedom by a registration algorithm comparing a reference surface (RS) of the patient to a live surface map of the patient on treatment day. SGRT has been an effective tool in daily localization for the treatment of breast cancer patients. It is common for patients to have multiple RS throughout the course of their treatment to account for anatomical variation between fractions. We sought to evaluate the robustness of reference surfaces and vendor specific algorithms used for SGRT. At our institution, positional shift data for five patients treated for right-sided breast cancer were retrospectively analyzed. SGRT performance was compared between RS using bilateral breasts or a single ipsilateral breast. Shift parameters were calculated over the entire treatment course for all patients with a vendor supplied software tool that offers rigid and deformable registration algorithms. The deformable algorithm was used for treatment setups, with the treatment RS encompassing both breasts plus a margin. Two robustness tests were carried out: 1) a trimmed down RS encompassing just the ipsilateral breast and 2) a comparison of deformable vs rigid registration of the clinically used RS. After obtaining translational and angular shift data, the absolute mean differences between shifts were calculated to compare differences between RS size and algorithm performance. On average, 1.4 new RS were created per patient guided by weekly radiographic imaging to adjust for anatomical changes. The absolute value of the average of the discrepancies between shifts using the clinical RS subtracted from the trimmed external (89 fractions) were <1mm and 1° and the maximum differences were: Lateral: 2.6mm, Longitudinal: 1.4mm, Vertical: 1.1mm, Yaw: 1.1°, Roll: 1.5°, Pitch: 1.7°. Discrepancies between tracking algorithms (83 fractions) were <1.5mm and 1° and the maximum differences were: Lateral: 3.4mm, Longitudinal: 3.5mm, Vertical: 2.0mm, Yaw: 2.4°, Roll: 2.7°, Pitch: 1.9°. Clinically negligible mean discrepancies were observed for both robustness tests showing that neither the reference surface size nor the algorithms investigated caused systematic variations in the shifts for this group of patients. Maximum discrepancies of up to 3 mm and 3° were found between the algorithms, which indicate some variation, but within clinical tolerance. Overall, different selection of reference surfaces and algorithms had a minor effect on clinical shifts for SGRT of the breast.

Initial clinical evaluation of a novel combined biometric, radio-frequency identification, and surface imaging system

PurposeTo evaluate and characterize the overall clinical functionality and workflow of the newly released Varian Identify system (version 2.3). MethodsThree technologies included in the Varian Identify system were evaluated: patient biometric authentication, treatment accessory device identification, and surface-guided radiation therapy (SGRT) function. Biometric authentication employs a palm vein reader. Treatment accessory device verification utilizes two technologies: device presence via Radio Frequency Identification (RFID) and position via optical markers. Surface-guidance was evaluated on both patient orthopedic setup at loading position and surface matching and tracking at treatment isocenter. A phantom evaluation of the consistency and accuracy for Identify SGRT function was performed, including a system consistency test, a translational shift and rotational accuracy test, a pitch and roll accuracy test, a continuous recording test, and an SGRT vs Cone-Beam CT (CBCT) agreement test. Results201 patient authentications were verified successfully with palm reader. All patient treatment devices were successfully verified for their presences and positions (indexable devices). The patient real-time orthopedic pose was successfully adjusted to match the reference surface captured at simulation. SGRT-reported shift consistency against couch readout was within (0.1 mm, 0.030). The shift accuracy was within (0.3 mm, 0.10). In continuous recording mode, the maximum variation was 0.2 ± 0.12 mm, 0.030 ± 0.020. The difference between Identify SGRT offset and CBCT was within (1 mm, 10). ConclusionsThis clinical evaluation confirms that Identify accurately functions for patient palm identification and patient treatment device presence and position verification. Overall SGRT consistency and accuracy was within (1 mm, 10), within the 2 mm criteria of AAPM TG302.

Plan robustness analysis for threshold determination of SGRT-based intrafraction motion control in 3DCRT breast cancer radiation therapy

PurposeThe goal of this study was to obtain maximum allowed shift deviations from planning position in six degrees of freedom (DOF), that can serve as threshold values in surface guided radiation therapy (SGRT) of breast cancer patients.MethodsThe robustness of conformal treatment plans of 50 breast cancer patients against 6DOF shifts was investigated. For that, new dose distributions were calculated on shifted computed tomography scans and evaluated with respect to target volume and spinal cord dose. Maximum allowed shift values were identified by imposing dose constraints on the target volume dose coverage for 1DOF, and consecutively, for 6DOF shifts using an iterative approach and random sampling.ResultsSubstantial decreases in target dose coverage and increases of spinal cord dose were observed. Treatment plans showed highly differing robustness for different DOFs or treated area. The sensitivity was particularly high if clavicular lymph nodes were irradiated, for shifts in lateral, vertical, roll or yaw direction, and showed partly pronounced asymmetries. Threshold values showed similar properties with an absolute value range of 0.8 mm to 5 mm and 1.4° to 5°.ConclusionThe robustness analysis emphasized the necessity of taking differences between DOFs and asymmetrical sensitivities into account when evaluating the dosimetric impact of position deviations. It also highlighted the importance of rotational shifts, especially if clavicular lymph nodes were irradiated. A practical approach of determining 6DOF shift limits was introduced and a set of threshold values applicable for SGRT based patient motion control was identified.

Technical note: Clinical evaluation of a newly released surface-guided radiation therapy system on DIBH for left breast radiation therapy.

It has been shown that a significant reduction of mean heart dose and left anterior descending artery (LAD) dose can be achieved through the use of DIBH for left breast radiation therapy. Surface-guided DIBH has been widely adopted during the last decade, and there are mainly three commercially available SGRT systems. The reports of the performance of a newly released SGRT system for DIBH application are currently very limited. To evaluate the clinical performance of a newly released SGRT system on DIBH for left breast radiation therapy. Twenty-five left breast cancer patients treated with DIBH utilizing Varian's Identify system were included (total 493-fraction treatments). Four aspects of the clinical performance were evaluated: Identify offsets of free breathing post patient setup from tattoos, Identify offsets during DIBH, Identify agreement with radiographic ports during DIBH, and DIBH reference surface re-capture post patient shifts. The systematic and random errors of free breathing Identify offsets post patient setup were calculated for each patient, as well as for offsets during DIBH. Radiographic ports were taken when the patient's DIBH position was within the clinical tolerance of (±0.3cm,±30 ), and these were then compared with treatment field DRRs. If the ports showed that the patient alignment did not agree with the DRRs within 3mm, a patient shift was performed. A new reference surface was captured and verification ports were taken. The all-patient average systematic and random errors of Identify offsets for free breathing were within (0.4cm, 1.50 ) post tattoo setup. The maximum per-patient systematic and random errors were (1.1cm, 6.20 ) and (0.9cm, 20 ), and the maximum amplitude of Identify offsets were (2.59cm, 90 ). All 493-fraction DIBH treatments were delivered and successfully guided by the Identify SGRT system. The systematic and random errors of Identify offsets for DIBH were within (0.2cm, 2.30 ). Seven patients needed re-captured surface references due to surface variation or position shifts based on the ports. All patient DIBH verification ports guided by Identify were approved by attending physicians. This evaluation showed that the Identify system performed effectively for surface-guided patient setup and surface-guided DIBH imaging and treatment delivery. The feature of color-coded real-time patient surface matching feedback facilitated the evaluation of the patient alignment accuracy and the adjustment of the patient position to match the reference.

72 A Deep Learning Approach to Tumour Motion Forecasting for Surface Guided Radiation Therapy Based on Volumetric 4D-CT

72 A Deep Learning Approach to Tumour Motion Forecasting for Surface Guided Radiation Therapy Based on Volumetric 4D-CT

Surface guided radiation therapy with an innovative open-face mask and mouth bite: patient motion management in brain stereotactic radiotherapy.

To guarantee treatment reproducibility and stability, immobilization devices are essential. Additionally, surface-guided radiation therapy (SGRT) serves as an accurate complement to frameless stereotactic radiosurgery (SRS) and stereotactic radiotherapy (SRT) by aiding patient positioning and real-time monitoring, especially when non-coplanar fields are in use. At our institute, we have developed a surface-guided SRS (SG-SRS) workflow that incorporates our innovative open-face mask (OM) and mouth bite (MB) to guarantee a precise and accurate dose delivery. This study included 40 patients, and all patients were divided into closed mask (CM) and open-face mask (OM) groups according to different positioning flow. Cone beam computed tomography (CBCT) scans were performed, and the registration results were recorded before and after the treatment. Then Bland-Altman method was used to analyze the consistency of AlignRT-guided positioning errors and CBCT scanning results in the OM group. The error changes between 31 fractions in one patient were recorded to evaluate the feasibility of monitoring during treatment. The median of translation error between stages of the AlignRT positioning process was (0.03-0.07) cm, and the median of rotation error was (0.20-0.40)°, which were significantly better than those of the Fraxion positioning process (0.09-0.11) cm and (0.60-0.75)°. The mean bias values between the AlignRT guided positioning errors and CBCT were 0.01cm, -0.07cm, 0.03cm, -0.30°, -0.08° and 0.00°. The 31 inter-fractional errors of a single patient monitored by SGRT were within 0.10cm and 0.50°. The application of the SGRT with an innovative open-face mask and mouth bite device could achieve precision positioning accuracy and stability, and the accuracy of the AlignRT system exhibits excellent constancy with the CBCT gold standard. The non-coplanar radiation field monitoring can provide reliable support for motion management in fractional treatment.

A Potential Pitfall and Clinical Solutions in Surface-Guided Deep Inspiration Breath Hold Radiation Therapy for Left-Sided Breast Cancer

Deep inspiration breath hold (DIBH) is an effective technique to spare the heart in treating left-sided breast cancer. Surface-guided radiation therapy (SGRT) is increasingly applied in DIBH setup and motion monitoring. Patient-specific breathing behavior, either thoracically driven or abdominally driven (A-DIBH), should be unaltered, online identified, and monitored accordingly to ensure reproducible heart-sparing treatment. Sixty patients with left-sided breast cancer treated with SGRT were analyzed: 20 A-DIBH patients with vertical chest elevation (VCE ≤ 5 mm) were prospectively identified, and 40 control patients were retrospectively and randomly selected for comparison. At simulation, both free-breathing (FB) and DIBH computed tomography (CT) were acquired, guided by a motion surrogate placed around the xiphoid process. For SGRT treatment setups, the region of interest (ROI) was defined on the CT chest surface, and the surrogate-based setup was a backup. For all 60 patients, the VCE was measured as the average of the FB-to-DIBH elevations at the breast and xiphoid process, together with abdominal elevation. In the 40-patient control group, A-DIBH patients (VCE ≤ 5 mm) were identified. Of the 20 A-DIBH patients, 10 were treated with volumetric modulated arc therapy plans, and 10 patients were treated with tangent plans. Clinical DIBH plans were recalculated on FB CT to compare maximum dose (DMax), 5% of the maximum dose (D5%), mean dose (DMean), and V30Gy, V20Gy, and V5Gy of the heart and lungs and their significance. In the 20 A-DIBH patients, VCE=3 ± 2 mm, surrogate motion (9 ± 6 mm), and abdomen motion of 14 ± 5 mm are found. Heart dose reduction from FB to DIBH is significant (P < .01): ∆DMax=-8.4 ± 9.8 Gy, ∆D5%=-2.4 ± 4.4 Gy, and ∆DMean=-0.6 ± 0.9 Gy. Six out of 40 control patients (15%) are found to have VCE ≤ 5 mm. A-DIBH (VCE ≤ 5 mm) patient population is significant (15%), and they should be identified in the SGRT workflow and monitored accordingly. A new abdominal ROI or an abdominal surrogate should be used instead of the conventional chest-only ROI. Patient-specific DIBH should be preserved for higher reproducibility to ensure heart sparing.

Evaluation of initial patient setup methods for breast cancer between surface-guided radiation therapy and laser alignment based on skin marking in the Halcyon system

BackgroundThis study was conducted to evaluate the efficiency and accuracy of the daily patient setup for breast cancer patients by applying surface-guided radiation therapy (SGRT) using the Halcyon system instead of conventional laser alignment based on the skin marking method.Methods and materialsWe retrospectively investigated 228 treatment fractions using two different initial patient setup methods. The accuracy of the residual rotational error of the SGRT system was evaluated by using an in-house breast phantom. The residual translational error was analyzed using the couch position difference in the vertical, longitudinal, and lateral directions between the reference computed tomography and daily kilo-voltage cone beam computed tomography acquired from the record and verification system. The residual rotational error (pitch, yaw, and roll) was also calculated using an auto rigid registration between the two images based on Velocity. The total setup time, which combined the initial setup time and imaging time, was analyzed to evaluate the efficiency of the daily patient setup for SGRT.ResultsThe average residual rotational errors using the in-house fabricated breast phantom for pitch, roll, and yaw were 0.14°, 0.13°, and 0.29°, respectively. The average differences in the couch positions for laser alignment based on the skin marking method were 2.7 ± 1.6 mm, 2.0 ± 1.2 mm, and 2.1 ± 1.0 mm for the vertical, longitudinal, and lateral directions, respectively. For SGRT, the average differences in the couch positions were 1.9 ± 1.2 mm, 2.9 ± 2.1 mm, and 1.9 ± 0.7 mm for the vertical, longitudinal, and lateral directions, respectively. The rotational errors for pitch, yaw, and roll without the surface-guided radiation therapy approach were 0.32 ± 0.30°, 0.51 ± 0.24°, and 0.29 ± 0.22°, respectively. For SGRT, the rotational errors were 0.30 ± 0.22°, 0.51 ± 0.26°, and 0.19 ± 0.13°, respectively. The average total setup times considering both the initial setup time and imaging time were 314 s and 331 s, respectively, with and without SGRT.ConclusionWe demonstrated that using SGRT improves the accuracy and efficiency of initial patient setups in breast cancer patients using the Halcyon system, which has limitations in correcting the rotational offset.

Reproducibility of surface-based deep inspiration breath-hold technique for lung stereotactic body radiotherapy on a closed-bore gantry linac.

Tumor motion and delivery efficiency are two main challenges of lung stereotactic body radiotherapy (SBRT). The present work implemented the deep inspiration breath hold technique (DIBH) with surface guided radiation therapy (SGRT) on closed-bore linacs and investigated the correlation between SGRT data and internal target position. Thirteen lung SBRT patients treated in DIBH using a closed-bore gantry linac and a ring-mounted SGRT system were retrospectively analysed. Visual coaching was used to achieve DIBH with a±1mm threshold window in the anterior-posterior direction. Three kV-CBCTs were added to the treatment workflow and examined offline to verify intra-fraction tumor position. Surface-based DIBH was analysed using SGRT treatment reports and an in-house python script. Data from 73 treatment sessions and 175kV-CBCTs were studied. Correlations between target and surface positions were studied with Linear Mixed Models. Median intra-fraction tumor motion was 0.8mm (range: 0.7-1.3 mm) in the anterior-posterior direction, 1.2mm (range: 1-1.7 mm) in the superior-inferior direction, and 1mm (range: 0.7-1.1 mm) in the left-right direction, with rotations of <1° (range: 0.6°-1.1°) degree in all three directions. Planned target volumes and healthy lung volumes receiving 12.5Gy and 13.5Gy were reduced on average by 67% and 54%, respectively. Lung SBRT in DIBH with the ring-mounted SGRT system proved reproducible. The surface monitoring provided by SGRT was found to be a reliable surrogate for internal target motion. Moreover, the implementation of DIBH technique helped reduce target volumes and lung doses.