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Surface guided radiation therapy (SGRT) is a non-radiation, non-invasive technology that provides continuous postural monitoring of patients during radiotherapy. Using advanced 3D optical surface localization and tracking technology, SGRT quickly captures the surface contour information of patients through optical means to generate high-precision 3D surface contours, enabling real-time monitoring of patients during radiotherapy to ensure its accuracy. This image-guided technology has been widely applied in radiotherapy for tumors in different parts of the body, such as breast, intracranial, head and neck, and limbs. SGRT can reduce initial setup errors and provide real-time monitoring during treatment, or be combined with respiratory gating and deep inspiration breath-hold techniques. SGRT can also reduce radiation dose by reducing the use of CBCT, improve patient comfort with the use of immobilization devices, and enhance clinical speed, efficiency, and safety. This review aims to provide an overview of the commonly used technology and clinical applications of SGRT, and discuss its current limitations and future prospects.

Background: Administration of external radiation therapy via proton therapy systems carries a risk of occasional collisions between the patient's body and gantry, which is increased by the snout placed near the patient for better dose distribution. Although treatment planning software (TPS) can simulate controlled collisions, the computed tomography (CT) data used for treatment planning are insufficient given that collisions can occur outside the CT imaging region. Thus, imaging the three‐dimensional (3D) surface outside the CT range and combining the data with those obtained by CT are essential for avoiding collisions. Purpose: To construct a prototype for 3D surface imaging and an end‐to‐end framework for preventing collisions between the patient's body and the gantry. Methods: We obtained 3D surface data using a light sectioning method (LSM). By installing only cameras in front of the CT, we achieved LSM using the CT couch motion and preinstalled patient‐positioning lasers. The camera image contained both sagittal and coronal lines, which are unnecessary for LSM and were removed by deep learning. We combined LSM 3D surface data and original CT data to create synthetic Digital Imaging and Communications in Medicine (DICOM) data. Subsequently, we compared the TPS snout auto‐optimization using the original CT data with the synthetic DICOM data. Results: The mean positional error for LSM of the arms and head was 0.7 ± 0.8 and 0.8 ± 0.8 mm for axial and sagittal imaging, respectively. The TPS snout auto‐optimization indicated that the original CT data would cause collisions; however, the synthetic DICOM data prevented these collisions. Conclusions: The prototype system's acquisition accuracy for 3D surface data was approximately 1 mm, which was sufficient for the collision simulation. The use of a TPS with collision avoidance can help optimize the snout position using synthetic DICOM data. Our proposed method requires no external software for collision simulation and can be integrated into the clinical workflow to improve treatment planning efficiency. [ABSTRACT FROM AUTHOR]

Purpose: In the last few years, there has been a growing interest in surface imaging for patient positioning in external radiation therapy. The aim of this study is to evaluate the accuracy of daily patient positioning using the Azure Kinect surface imaging. Methods: A total of 50 fractions in 10 patients including lung, pelvic, and head and neck tumors were analyzed in real time. A rigid registration algorithm, based on the iterative closest point (ICP) approach, is employed to estimate the patient position in 6 degrees of freedom (DOF). This position is compared to the reference values obtained by the radiograph imaging. The mean setup error and its standard deviation were calculated for all measured fractions. Results: The positioning error showed 1.1 ± 1.1 mm in lateral, 1.8 ± 2.1 mm in longitudinal, and 0.8 ± 1.1 mm in vertical, and 0.3°± 0.4° in yaw, 0.2°± 0.2° in pitch, and 0.2°± 0.2° in roll directions. The larger setup error occurred in pelvic regions. Conclusion: We have evaluated in a radiotherapy set‐up considering different patient anatomical locations, a depth measurement based surface imaging solution for patient positioning considering the 6 DOF couch motion. We showed that the proposed solution allows an accurate patient positioning without the need for patient markings or the use of additional radiation dose. [ABSTRACT FROM AUTHOR]

• 21% of all relevant events found in three different incident learning databases were likely to be preventable with SGRT. • The most preventable events with SGRT were incorrect isocenter and incorrect immobilization. • Events with the potential to be mitigated by SGRT were generally of higher severity. • SGRT was found to also introduce new failure modes. • Improved vendor integration could further enhance patient safety. Emerging data indicates SGRT could improve safety and quality by preventing errors in its capacity as an independent system in the treatment room. The aim of this work is to investigate the utility of SGRT in the context of safety and quality. Three incident learning systems (ILS) were reviewed to categorize and quantify errors that could have been prevented with SGRT: SAFRON (International Atomic Energy Agency), UW-ILS (University of Washington) and AvIC (Skåne University Hospital). A total of 849/9737 events occurred during the pre-treatment review/verification and treatment stages. Of these, 179 (21%) events were predicted to have been preventable with SGRT. The most common preventable events were wrong isocentre (43%) and incorrect accessories (34%), which appeared at comparable rates among SAFRON and UW-ILS. The proportion of events due to wrong accessories was much smaller in the AvIC ILS, which may be attributable to the mandatory use of SGRT in Sweden. Several case scenarios are presented to demonstrate that SGRT operates as a valuable complement to other quality-improvement tools routinely used in radiotherapy. Cases are noted in which SGRT itself caused incidents. These were mostly related to workflow issues and were of low severity. Severity data indicated that events with the potential to be mitigated by SGRT were of higher severity for all categories except wrong accessories. Improved vendor integration of SGRT systems within the overall workflow could further enhance its clinical utility. SGRT is a valuable tool with the potential to increase patient safety and treatment quality in radiotherapy. [ABSTRACT FROM AUTHOR]

Purpose: Electron radiation therapy dose distributions are affected by irregular body surface contours. This study investigates the feasibility of three‐dimensional (3D) cameras to substitute for the treatment planning computerized tomography (CT) scan by capturing the body surfaces to be treated for accurate electron beam dosimetry. Methods: Dosimetry was compared for six electron beam treatments to the nose, toe, eye, and scalp using full CT scan, CT scan with Hounsfield Unit (HU) overridden to water (mimic 3D camera cases), and flat‐phantom techniques. Radiation dose was prescribed to a depth on the central axis per physician's order, and the monitor units (MUs) were calculated. The 3D camera spatial accuracy was evaluated by comparing the 3D surface of a head phantom captured by a 3D camera and that generated with the CT scan in the treatment planning system. A clinical case is presented, and MUs were calculated using the 3D camera body contour with HU overridden to water. Results: Across six cases the average change in MUs between the full CT and the 3Dwater (CT scan with HU overridden to water) calculations was 1.3% with a standard deviation of 1.0%. The corresponding hotspots had a mean difference of 0.4% and a standard deviation of 1.9%. The 3D camera captured surface of a head phantom was found to have a 0.59 mm standard deviation from the surface derived from the CT scan. In‐vivo dose measurements (213 ± 8 cGy) agreed with the 3D‐camera planned dose of 209 ± 6 cGy, compared to 192 ± 6 cGy for the flat‐phantom calculation (same MUs). Conclusions: Electron beam dosimetry is affected by irregular body surfaces. 3D cameras can capture irregular body contours which allow accurate dosimetry of electron beam treatment as an alternative to costly CT scans with no extra exposure to radiation. Tools and workflow for clinical implementation are provided. [ABSTRACT FROM AUTHOR]

Purpose: Patients undergoing external beam accelerated partial breast irradiation (APBI) receive permanent tattoos to aid with daily setup alignment and verification. With the advent of three‐dimensional (3D) body surface imaging and two‐dimensional (2D) x‐ray imaging‐based matching to surgical clips, tattoos may not be necessary to ensure setup accuracy. We compared the accuracy of conventional tattoo‐based setups to a patient setup without tattoos. Materials/methods: Twenty consecutive patients receiving APBI at our institution from July 10, 2017 to February 13, 2018 were identified. All patients received tattoos per standard of care. Ten patients underwent setup using tattoos for initial positioning followed by surface imaging and 2D matching of surgical clips. The other ten patients underwent positioning using surface imaging followed by 2D matching without reference to tattoos. Overall setup time and orthogonal x‐ray‐based shifts after surface imaging per fraction were recorded. Shift data were used to calculate systematic and random error. Results: Among ten patients in the "no tattoo" group, the average setup time per fraction was 6.83 min vs 8.03 min in the tattoo cohort (P < 0.01). Mean 3D vector shifts for patients in the "no tattoo" group were 4.6 vs 5.9 mm in the "tattoo" cohort (P = NS). Mean systematic errors in the "no tattoo" group were: 1.2 mm (1.5 mm SD) superior/inferior, 0.5 mm (1.6 mm SD) right/left, and 2.3 mm (1.9 mm SD) anterior/posterior directions. Mean systematic errors in the "tattoo" group were: 0.8 mm (2.2 mm SD) superior/inferior, 0.3 mm (2.5 mm SD) right/left, and 1.4 mm (4.4 mm SD) anterior/posterior directions. The random errors in the "no tattoo" group ranged from 0.6 to 0.7 mm vs 1.2 to 1.7 mm in the "tattoo" group. Conclusions: Using both surface imaging and 2D matching to surgical clips provides excellent accuracy in APBI patient alignment and setup verification with reduced setup time relative to the tattoo cohort. Skin‐based tattoos may no longer be warranted for patients receiving external beam APBI. [ABSTRACT FROM AUTHOR]

Purpose Historically, the process of positioning a patient prior to imaging verification used a set of permanent patient marks, or tattoos, placed subcutaneously. After aligning to these tattoos, plan specific shifts are applied and the position is verified with imaging, such as cone-beam computed tomography ( CBCT). Due to a variety of factors, these marks may deviate from the desired position or it may be hard to align the patient to these marks. Surface-based imaging systems are an alternative method of verifying initial positioning with the entire skin surface instead of tattoos. The aim of this study was to retrospectively compare the CBCT-based 3D corrections of patients initially positioned with tattoos against those positioned with the C- RAD Catalyst HD surface imager system. Methods A total of 6000 individual fractions (600-900 per site per method) were randomly selected and the post- CBCT 3D corrections were calculated and recorded. For both positioning methods, four common treatment site combinations were evaluated: pelvis/lower extremities, abdomen, chest/upper extremities, and breast. Statistical differences were evaluated using a paired sample Wilcoxon signed-rank test with significance level of <0.01. Results The average magnitudes of the 3D shift vectors for tattoos were 0.9 ± 0.4 cm, 1.0 ± 0.5 cm, 0.9 ± 0.6 cm and 1.4 ± 0.7 cm for the pelvis/lower extremities, abdomen, chest/upper extremities and breast, respectively. For the Catalyst HD, the average magnitude of the 3D shifts for the pelvis/lower extremities, abdomen, chest/upper extremities and breast were 0.6 ± 0.3 cm, 0.5 ± 0.3 cm, 0.5 ± 0.3 cm and 0.6 ± 0.2 cm, respectively. Statistically significant differences ( P < 0.01) in the 3D shift vectors were found for all four sites. Conclusion This study shows that the overall 3D shift corrections for patients initially aligned with the C- RAD Catalyst HD were significantly smaller than those aligned with subcutaneous tattoos. Surface imaging systems can be considered a viable option for initial patient setup and may be preferable to permanent marks for specific clinics and patients. [ABSTRACT FROM AUTHOR]

Purpose: Surface-based image guided radiotherapy (IGRT) allows positioning and/or monitoring patients in 3 dimensions (3D), without the use of ionizing radiation. In this study, we report on intra-fraction motion measured by acquisition of multiple images of 3D body surfaces. Materials and methods: Twenty-nine patients treated for pelvic tumors were enrolled. Setup variations (SV) through three consecutive body surfaces acquired by the optical IGRT system Align-RT (Vision-RT, London, UK) were analyzed before, during and at the end of treatment delivery. Displacements along the main axes ( X, Y and Z) from initial (I) to mid-treatment (MT) and final (F) acquisitions were recorded. Time and direction of SV were assessed. Results: A total of 6272 images from 792 fractions of 29 patients were available. The main source of misalignment was between I and MT acquisition ( p < 0.001). The dominant SV direction was the vertical one ( Z axis), with mean SV of −1.20 ± 0.06 mm and −1.55 ± 0.06 mm for I-MT and I-F acquisitions, respectively. The Y mean components of SV were, respectively, −0.95 ± 0.10 mm and −1.0 ± 0.10 for I-MT and I-F acquisitions, while the X deviations were 0.07 ± 0.08 mm for I-MT and 0.26 ± 0.08 mm I-F. Conclusion: Three-D surface imaging for patient setup monitoring highlighted remarkable mobility of patients during RT session, especially in the anterior-posterior direction ( Z axis). The largest magnitude in patient movements occurred during the first part of delivery. These findings suggest that the initial setup control cannot not to be sufficient to guarantee treatment reproducibility, especially for long-lasting RT treatments. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the patient positioning accuracy in radiotherapy using a stereo-time of flight (ToF)-camera system. Methods: A system using two ToF cameras was used to scan the surface of the patients in order to position them daily on the treatment couch. The obtained point clouds were registered to (a) detect translations applied to the table (intrafraction motion) and (b) predict the displacement to be applied in order to place the patient in its reference position (interfraction motion). The measures provided by this system were compared to the effectively applied translations. The authors analyzed 150 fractions including lung, pelvis/prostate, and head and neck cancer patients. Results: The authors obtained small absolute errors for displacement detection: 0.8 ± 0.7, 0.8 ± 0.7, and 0.7 ± 0.6 mm along the vertical, longitudinal, and lateral axes, respectively, and 0.8 ± 0.7 mm for the total norm displacement. Lung cancer patients presented the largest errors with a respective mean of 1.1 ± 0.9, 0.9 ± 0.9, and 0.8 ± 0.7 mm. Conclusions: The proposed stereo-ToF system allows for sufficient accuracy and faster patient repositioning in radiotherapy. Its capability to track the complete patient surface in real time could allow, in the future, not only for an accurate positioning but also a real time tracking of any patient intrafraction motion (translation, involuntary, and breathing). [ABSTRACT FROM AUTHOR]

Purpose: This work presents a method of collision predictions for external beam radiotherapy using surface imaging. The present methodology focuses on collision prediction during treatment simulation to evaluate the clearance of a patient's treatment position and allow for its modification if necessary. Methods: A Kinect camera (Microsoft, Redmond,WA) is used to scan the patient and immobilization devices in the treatment position at the simulator. The surface is reconstructed using the SKANECT software (Occipital, Inc., San Francisco, CA). The treatment isocenter is marked using simulated orthogonal lasers projected on the surface scan. The point cloud of this surface is then shifted to isocenter and converted from Cartesian to cylindrical coordinates. A slab models the treatment couch. A cylinder with a radius equal to the normal distance from isocenter to the collimator plate, and a height defined by the collimator diameter is used to estimate collisions. Points within the cylinder clear through a full gantry rotation with the treatment couch at 0?, while points outside of it collide. The angles of collision are reported. This methodology was experimentally verified using a mannequin positioned in an alpha cradle with both arms up. A planning CT scan of the mannequin was performed, two isocenters were marked in PINNACLE, and this information was exported to AlignRT (VisionRT, London, UK)--a surface imaging system for patient positioning. This was used to ensure accurate positioning of the mannequin in the treatment room, when available. Collision calculations were performed for the two treatment isocenters and the results compared to the collisions detected the room. The accuracy of the Kinect-Skanect surface was evaluated by comparing it to the external surface of the planning CT scan. Results: Experimental verification results showed that the predicted angles of collision matched those recorded in the room within 0.5°, in most cases (largest deviation -1.2°). The accuracy study for the Kinect-Skanect surface showed an average discrepancy between the CT external contour and the surface scan of 2.2 mm. Conclusions: This methodology provides fast and reliable collision predictions using surface imaging. The use of the Kinect-Skanect system allows for a comprehensive modeling of the patient topography including all the relevant anatomy and immobilization devices that may lead to collisions. The use of this tool at the treatment simulation stage may allow therapists to evaluate the clearance of a patient's treatment position and optimize it before the planning CT scan is performed. This can allow for safer treatments for the patients due to better collision predictions and improved clinical workflow by minimizing replanning and resimulations due to unforeseen clearance issues. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To investigate the heart position variability in deep-inspiration breath-hold (DIBH) radiation therapy (RT) for breast cancer when 3D surface imaging would be used for monitoring the BH depth during treatment delivery. For this purpose, surface setup data were compared with heart setup data. Materials and methods: Twenty patients treated with DIBH-RT after breast-conserving surgery were included. Retrospectively, heart registrations were performed for cone-beam computed tomography (CBCT) to planning CT. Further, breast-surface registrations were performed for a surface, captured concurrently with CBCT, to planning CT. The resulting setup errors were compared with linear regression analysis. Furthermore, geometric uncertainties of the heart (systematic [Σ] and random [σ]) were estimated relative to the surface registration. Based on these uncertainties planning organ at risk volume (PRV) margins for the heart were calculated: 1.3Σ −0.5σ. Results: Moderate correlation between surface and heart setup errors was found: R 2 =0.64, 0.37, 0.53 in left–right (LR), cranio-caudal (CC), and in anterior–posterior (AP) direction, respectively. When surface imaging would be used for monitoring, the geometric uncertainties of the heart (cm) are [Σ =0.14, σ =0.14]; [Σ =0.66, σ =0.38]; [Σ =0.27, σ =0.19] in LR; CC; AP. This results in PRV margins of 0.11; 0.67; 0.25cm in LR; CC; AP. Conclusion: When DIBH-RT after breast-conserving surgery is guided by the breast-surface position then PRV margins should be used to take into account the heart-position variability relative to the breast-surface. [Copyright &y& Elsevier]

Abstract: Aim: To investigate the clinical application of a technique for patient set-up verification in breast cancer radiotherapy based on a 3D surface image registration system. Background: Accurate and reproducible patient set-up is a prerequisite to correctly deliver fractionated radiotherapy. Various approaches are available to verify and correct patient setup for 3D image acquisition in a radiation treatment room. Materials and methods: The study analyzed the setup reproducibility of 15 patients affected by breast cancer and candidates for conformal radiotherapy by using the AlignRT system (VisionRT, London, UK). At the initial setup, electronic portal imaging device (EPID) images were compared with Digitally Reconstructed Radiographs (DRRs) and a reference three-dimensional (3D) surface image was obtained by AlignRT. Surface images were acquired prior to every subsequent setup procedure. The systematic and random errors along longitudinal and vertical directions were measured and compared for the two systems. Results: The procedure for surface registration, image acquisition and comparison with the reference image took less than 1min on average. The T test for systematic error showed no significant difference between the 2 verification systems along the longitudinal (p =0.69) and vertical (p =0.67) axes. The T-test for random error showed a significant difference between the 2 systems along the vertical axis (p =0.05). Conclusion: AlignRT is fast, simple, non-invasive and seems to be reliable in detecting patient setup errors. Our results suggest that it could be used to assess the setup reproducibility for breast cancer patients. [Copyright &y& Elsevier]

Surface imaging is in use in radiotherapy clinical practice for patient setup optimization and monitoring. Breast alignment is accomplished by searching for a tentative spatial correspondence between the reference and daily surface shape models. In this study, the authors quantify whole breast shape alignment by relying on texture features digitized on 3D surface models. Texture feature localization was validated through repeated measurements in a silicone breast phantom, mounted on a high precision mechanical stage. Clinical investigations on breast shape alignment included 133 fractions in 18 patients treated with accelerated partial breast irradiation. The breast shape was detected with a 3D video based surface imaging system so that breathing was compensated. An in-house algorithm for breast alignment, based on surface fitting constrained by nipple matching (constrained surface fitting), was applied. Results were compared with a commercial software where no constraints are utilized (unconstrained surface fitting). Texture feature localization was validated within 2 mm in each anatomical direction. Clinical data show that unconstrained surface fitting achieves adequate accuracy in most cases, though nipple mismatch is considerably higher than residual surface distances (3.9 mm vs 0.6 mm on average). Outliers beyond 1 cm can be experienced as the result of a degenerate surface fit, where unconstrained surface fitting is not sufficient to establish spatial correspondence. In the constrained surface fitting algorithm, average surface mismatch within 1 mm was obtained when nipple position was forced to match in the [1.5; 5] mm range. In conclusion, optimal results can be obtained by trading off the desired overall surface congruence vs matching of selected landmarks (constraint). Constrained surface fitting is put forward to represent an improvement in setup accuracy for those applications where whole breast positional reproducibility is an issue. [ABSTRACT FROM AUTHOR]

Purpose: To assess the utility of surface imaging on patient setup for accelerated partial-breast irradiation (APBI). Methods and Material: A photogrammetry system was used in parallel to APBI setup by laser and portal imaging. Surface data were acquired after laser and port-film setup for 9 patients. Surfaces were analyzed in comparison to a reference surface from the first treatment session by use of rigid transformations. The surface model after laser setup was used in a simulated photogrammetry setup procedure. In addition, breathing data were acquired by surface acquisition at a frame rate of 7 Hz. Results: Mean 3D displacement was 7.3 mm (SD, 4.4 mm) and 7.6 mm (SD, 4.2 mm) for laser and port film, respectively. Simulated setup with the photogrammetry system yielded mean displacement of 1 mm (SD, 1.2 mm). Distance analysis resulted in mean distances of 3.7 mm (SD, 4.9 mm), 4.3 mm (SD, 5.6 mm), and 1.6 mm (SD, 2.4 mm) for laser, port film, and photogrammetry, respectively. Breathing motion at isocenter was smaller than 3.7 mm, with a mean of 1.9 mm (SD, 1.1 mm). Conclusions: Surface imaging for PBI setup appears promising. Alignment of the 3D breast surface achieved by stereo-photogrammetry shows greater breast topology congruence than when patients are set up by laser or portal imaging. A correlation of breast surface and CTV must be quantitatively established. [Copyright &y& Elsevier]