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Introduction We investigated the correlation between optical surface imaging using a three‐dimensional (3D) scanner and magnetic resonance imaging (MRI) for suggesting feasibility in the clinical process of tracking volume changes in head and neck patients during radiation treatment. Methods Ten patients were divided into two groups depending on the location of their tumor (i.e., right or left side). With weekly imaging data, the change in volume based on MRI was evaluated during the treatment course. Four volumes of interest (VOIs) were calculated on the 3D surface image of the facial and cervical areas using an optical 3D scanner, and the correlation between volumetric parameters were analyzed. Results The target volume changed significantly overall for both groups. The changes parotid volume reduced by up to 3.8% and 28.0% for groups A (right side) and B (left side), respectively. In Group A, VOI 1 on the facial area and VOI 3 on the cervical area decreased gradually during the treatment course by up to 3.3% and 10.7%, respectively. In Group B, only VOI 4 decreased gradually during the treatment course and reduced by up to 9.2%. In group A, the change in target volume correlated strongly with right‐side parotid, VOI 1, and VOI 3, respectively. The parotid also showed strong correlations with VOIs (P 0.05). In group B (left side), the change in target volume correlated strongly with each volumetric parameter, including weight loss. For individual patient, PTV showed more correlation with VOIs on the cervical area than VOIs on the facial area. Conclusions An optical 3D scanner can be applied to track changes in volume without radiation exposure during treatment and the optical surface image correlated with MRI.

Purpose The Elekta Active Breathing CoordinatorTM (ABC) is used to control breathing and guide deep inspiration breath hold (DIBH). It has been shown to be accurate in lung cancers, but limited analysis has been performed on the spatial accuracy and reproducibility of the breast surface. The use of optical surface-image guidance for patient positioning has grown in popularity and is an alternative solution for breast DIBH. This study aims to evaluate the breast surface variability of an ABC-guided DIBH by using a three-dimensional (3D) surface imaging system to record surface position. Methods Ten participants were placed in the treatment position, and breathing baselines and inhalation volume threshold baselines were monitored and recorded using the ABC. Over 60 minutes, the breathing patterns were recorded by the ABC and CatalystHDTM (C-RAD, Uppsala, Sweden). For each breath hold, the valve of the ABC closed at the baseline inhalation threshold and a 3D surface image was acquired. For each point on the baseline breast surface, a 3D vector was calculated to the subsequent breath hold surface as well as a root mean square (RMS) vector magnitude for the entire surface. Results The average and standard deviation for the RMS difference between the baseline and subsequent evaluated images were 7.12 ± 2.70 mm. Conclusion This study shows that while the ABC-guided inhalation volume is kept constant, a non-negligible variability of the breast surface position exists. Special considerations should be used in clinical situations, where the positioning of the surface is considered more important than inhalation volume.

A procedure is presented to assess performance at non-zero couch angles and perform routine quality assurance (QA) on surface-guided radiotherapy (SGRT) imaging systems used for stereotactic radiosurgery (SRS). A low-cost anthropomorphic phantom was used to assess the system under patient-like conditions. The phantom is embedded with a tungsten ball bearing (BB) to facilitate the use of surface imaging (SI) with concurrent megavoltage (MV) imaging to cross-compare and validate SI-reported offsets. Data analysis is done via in-house software that utilized the SGRT system's log files for automated analysis. This procedure enables users to assess and inter-compare MV-reported offsets with their SGRT system. The analysis provides SGRT system residual error so that users are aware of inherent offsets present in addition to increases in translational offsets due to couch walkout. The procedure was validated with two commercial SGRT systems. The procedure can be used with any surface imaging system and linear accelerator system.

Background/aim Methods to assess three-dimensionally the breast surface are increasingly used in plastic and reconstructive surgery. The aim of this study was to validate the use of the Structure Sensor 3D scanner (Occipital, Inc., Boulder, CO, USA) connected to an iPad Pro (Apple, Inc., Cupertino, CA, USA) as a novel, inexpensive and handheld three-dimensional scanning process. Materials and methods Surface images of a medical human female anatomy torso model of rigid plastic were repeatedly acquired with Structure Sensor 3D scanner and compared with those obtained using two clinically established 3D imaging systems. Digital measurements of vector and surface breast distances were analyzed using Mimics® Innovation Suite 20 medical imaging software (Materialise, Leuven, Belgium). Results The analysis of variance (ANOVA) revealed no statistically significant difference among measurements obtained using different scanning processes for all the variables examined (p>0.05). Conclusion The study demonstrates analogous practicability and reliability for surface image acquisition using the newly introduced Structure Sensor 3D scanner and other clinically established scanners.

Purpose We calculated setup margins for whole breast radiotherapy during voluntary deep‐inspiration breath‐hold (vDIBH) using real‐time surface imaging (SI). Methods and Materials Patients (n = 58) with a 27‐to‐31 split between right‐ and left‐sided cancers were analyzed. Treatment beams were gated using AlignRT by registering the whole breast region‐of‐interest to the surface generated from the simulation CT scan. AlignRT recorded (three‐dimensional) 3D displacements and the beam‐on‐state every 0.3 s. Means and standard deviations of the displacements during vDIBH for each fraction were used to calculate setup margins. Intra‐DIBH stability and the intrafraction reproducibility were estimated from the medians of the 5th to 95th percentile range of the translations in each breath‐hold and fraction, respectively. Results A total of 7269 breath‐holds were detected over 1305 fractions in which a median dose of 200 cGy was delivered. Each fraction was monitored for 5.95 ± 2.44 min. Calculated setup margins were 4.8 mm (A/P), 4.9 mm (S/I), and 6.4 mm (L/R). The intra‐DIBH stability and the intrafraction reproducibility were ≤0.7 mm and ≤2.2 mm, respectively. The isotropic margin according to SI (9.2 mm) was comparable to other institutions’ calculations that relied on x‐ray imaging and/or spirometry for patients with left‐sided cancer (9.8–11.0 mm). Likewise, intra‐DIBH variability and intrafraction reproducibility of breast surface measured with SI agreed with spirometry‐based positioning to within 1.2 and 0.36 mm, respectively. Conclusions We demonstrated that intra‐DIBH variability, intrafraction reproducibility, and setup margins are similar to those reported by peer studies who utilized spirometry‐based positioning.

Purpose To develop a novel approach to accurately verify patient set up in proton radiotherapy, especially for the verification of the nozzle – body surface air gap and source-to-skin distance (SSD), the consistency and accuracy of which is extremely important in proton treatment. Methods Patient body surfaces can be captured and monitored with the optical surface imaging system during radiation treatment for improved intrafraction accuracy. An in-house software package was developed to reconstruct the patient body surface in the treatment position from the optical surface imaging reference capture and to calculate the corresponding nozzle – body surface air gap and SSD. To validate this method, a mannequin was scanned on a CT simulator and proton plans were generated for a Mevion S250 Proton machine with 20 gantry/couch angle combinations, as well as two different snout sizes, in the Varian Eclipse Treatment Planning Systems (TPS). The surface generated in the TPS from the CT scan was imported into the optical imaging system as an RT Structure for the purpose of validating and establishing a benchmark for ground truth comparison. The optical imaging surface reference capture was acquired at the treatment setup position after orthogonal kV imaging to confirm the positioning. The air gaps and SSDs calculated with the developed method from the surface captured at the treatment setup position (VRT surface) and the CT based surface imported from the TPS were compared to those calculated in TPS. The same approach was also applied to 14 clinical treatment fields for 10 patients to further validate the methodology. Results The air gaps and SSDs calculated from our program agreed well with the corresponding values derived from the TPS. For the phantom results, using the CT surface, the absolute differences in the air gap were 0.45 mm ± 0.33 mm for the small snout, and 0.51 mm ± 0.49 mm for the large snout, and the absolute differences in SSD were 0.68 mm ± 0.42 mm regardless of snout size. Using the VRT surface, the absolute differences in air gap were 1.17 mm ± 1.17 mm and 2.1 mm ± 3.09 mm for the small and large snouts, respectively, and the absolute differences in SSD were 0.81 mm ± 0.45 mm. Similarly, for patient data, using the CT surface, the absolute differences in air gap were 0.42 mm ± 0.49 mm, and the absolute differences in SSD were 1.92 mm ± 1.4 mm. Using the VRT surface, the absolute differences in the air gap were 2.35 mm ± 2.3 mm, and the absolute differences in SSD were 2.7 mm ± 2.17 mm. Conclusion These results showed the feasibility and robustness of using an optical surface imaging approach to conveniently determine the air gap and SSD in proton treatment, providing an accurate and efficient way to confirm the target depth at treatment.

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

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 CatalystHD 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

The purpose of this study was to quantify the variability of the breast surface position when aligning whole‐breast patients to bony landmarks based on MV portal films or skin marks alone. Surface imaging was used to assess the breast surface position of 11 whole‐breast radiotherapy patients, but was not used for patient positioning. On filmed fractions, AlignRT v5.0 was used to capture the patient's surface after initial positioning based on skin marks (28 “preshifts” surfaces), and after treatment couch shifts based on MV films (41 “postshifts” surfaces). Translations and rotations based on surface captures were recorded, as well as couch shifts based on MV films. For nonfilmed treatments, “daily” surface images were captured following positioning to skin marks alone. Group mean and systematic and random errors were calculated for all datasets. Pearson correlation coefficients, setup margins, and 95% limits of agreement (LOA) were calculated for preshifts translations and MV film shifts. LOA between postshifts surfaces and the filmed treatment positions were also computed. All the surface captures collected were retrospectively compared to both a DICOM reference surface created from the planning CT and to an AlignRT reference surface. All statistical analyses were performed using the DICOM reference surface dataset. AlignRT reference surface data was only used to calculate the LOA with the DICOM reference data. This helped assess any outcome differences between both reference surfaces. Setup margins for preshifts surfaces and MV films range between 8.3–12.0 mm and 5.4–13.4 mm, respectively. The largest margin is along the left–right (LR) direction for preshift surfaces, and along craniocaudal (CC) for films. LOA ranges between the preshifts surfaces and MV film shifts are large (12.6–21.9 mm); these decrease for postshifts surfaces (9.8–18.4 mm), but still show significant disagreements between the two modalities due to their focus on different anatomical landmarks (patient's topography versus bony anatomy). Pearson's correlation coefficients further support this by showing low to moderate correlations in the anterior–posterior (AP) and LR directions (0.47–0.69) and no correlation along CC(

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.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.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.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.

Performing a procedure on the wrong patient or site is one of the greatest errors that can occur in medicine. The addition of automation has been shown to reduce errors in many processes. In this work we explore the use of an automated patient identification process using optical surface imaging for radiotherapy treatments. Surface imaging uses visible light to align the patient to a reference surface in the treatment room. It is possible to evaluate the similarity between a daily set‐up surface image and the reference image using distance to agreement between the points on the two surfaces. The higher the percentage overlapping points within a defined distance, the more similar the surfaces. This similarity metric was used to intercompare 16 left‐sided breast patients. The reference surface for each patient was compared to 10 daily treatment surfaces for the same patient, and 10 surfaces from each of the other 15 patients (for a total of 160 comparisons per patient), looking at the percent of points overlapping. For each patient, the minimum same‐patient similarity score was higher than the maximum different‐patient score. For the group as a whole a threshold was able to classify correct and incorrect patients with high levels of accuracy. A 10‐fold cross‐validation using linear discriminant analysis gave cross‐validation loss of 0.0074. An automated process using surface imaging is a feasible option to provide nonharmful daily patient identification verification using currently available technology. PACS number(s): 87.53.Jw, 87.55.N‐, 87.55.Qr, 87.57.N‐, 87.63.L‐

Breast treatments are becoming increasingly complex as the use of modulated and partial breast therapies becomes more prevalent. These methods are predicated on accurate and precise positioning for treatment. However, the ability to quantify intrafraction motion has been limited by the excessive dose that would result from continuous X-ray imaging throughout treatment. Recently, surface imaging has offered the opportunity to obtain 3D measurements of patient position throughout breast treatments without radiation exposure. Thirty free-breathing breast patients were monitored with surface imaging for 831 monitoring sessions. Mean translations and rotations were calculated over each minute, each session, and over all sessions combined. The percentage of each session that the root mean squares (RMS) of the linear translations were outside of defined tolerances was determined for each patient. Correlations between mean translations per minute and time, and between standard deviation per minute and time, were evaluated using Pearson’s r value. The mean RMS translation averaged over all patients was 2.39 mm ± 1.88 mm. The patients spent an average of 34%, 17%, 9%, and 5% of the monitoring time outside of 2 mm, 3 mm, 4 mm, and 5 mm RMS tolerances, respectively. The RMS values averaged over all patients were 2.71 mm ± 1.83 mm, 2.76 ± 2.27, and 2.98 mm ± 2.30 mm over the 5th, 10th, and 15th minutes of monitoring, respectively. The RMS values ( r = 0.73, p = 0) and standard deviations ( r = 0.88, p = 0) over all patients showed strong significant correlations with time. We see that the majority of patients’ treatment time is spent within 5 mm of the isocenter and that patient position drifts with increasing treatment time. Treatment length should be consid- ered in the planning process. An 8 mm margin on a target volume would account for 2 SDs of motion for a treatment up to 15 minutes in length.

AimTo investigate the clinical application of a technique for patient set-up verification in breast cancer radiotherapy based on a 3D surface image registration system.BackgroundAccurate 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 methodsThe 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.ResultsThe 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).ConclusionAlignRT 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.