Technical note: TROG 15.01 SPARK trial multi-institutional imaging dose measurement.

PURPOSE: The Trans-Tasman Radiation Oncology Group (TROG) 15.01 Stereotactic Prostate Adaptive Radiotherapy utilizing Kilovoltage intrafraction monitoring (SPARK) trial is a multicenter trial using Kilovoltage Intrafraction Monitoring (KIM) to monitor prostate position during the delivery of prostate radiation therapy. KIM increases the accuracy of prostate radiation therapy treatments and allows for hypofractionation. However, an additional imaging dose is delivered to the patient. A standardized procedure to determine the imaging dose per frame delivered using KIM was developed and applied at four radiation therapy centers on three different types of linear accelerator. METHODS: Dose per frame for kilovoltage imaging in fluoroscopy mode was measured in air at isocenter using an ion chamber. Beam quality and dose were determined for a Varian Clinac iX linear accelerator, a Varian Trilogy, four Varian Truebeams and one Elekta Synergy at four different radiation therapy centers. The imaging parameters used on the Varian machines were 125 kV, 80 mA, and 13 ms. The Elekta machine was measured at 120 kV, 80 mA, and 12 ms. Absorbed doses to the skin and the prostate for a typical SBRT prostate treatment length were estimated according to the IPEMB protocol. RESULTS: The average dose per kV frame to the skin was 0.24 ± 0.03 mGy. The average estimated absorbed dose to the prostate for all five treatment fractions across all machines measured was 39.9 ± 2.6 mGy for 1 Hz imaging, 199.7 ± 13.2 mGy for 5 Hz imaging and 439.3 ± 29.0 mGy for 11 Hz imaging. CONCLUSIONS: All machines measured agreed to within 20%. Additional dose to the prostate from using KIM is at most 1.3% of the prescribed dose of 36.25 Gy in five fractions delivered during the trial.

Setup and intra-fractional motion measurements using surface scanning in head and neck cancer radiotherapy- A feasibility study.

Background and purpose: Surface-guided radiotherapy (SGRT) is applied to improve patient set-up and to monitor intra-fraction motion. Head and neck cancer (H&N) patients are usually fixated using 5-point thermoplastic masks, that are experienced as uncomfortable or even stressful. Therefore, the feasibility of irradiating H&N patients without a mask by using SGRT was examined. Material and methods: Nineteen H&N patients were included in a simulation study. Once a week, before the standard treatment, a maskless treatment was simulated, using SGRT for setup and intrafraction motion monitoring. Initial patient setup accuracy and intrafraction motion was determined using ConeBeam CT (CBCT) images as well as SGRT before and after the (simulated) treatment. The clinical target volume to planning target volume (CTV-PTV) margin for intrafraction motion was calculated. Using patient questionnaires, the patient-friendliness H&N irradiation with and without mask was determined. Results: Maskless setup with SGRT and CBCT was as accurate as with a mask. SGRT showed that intrafraction motion was gradual during the treatment. The CTV-PTV margin correcting for intrafraction motion was 1.7 mm for maskless treatment without interventions, and 1.2 mm if corrected for motions > 2 mm. For 19 % of fractions, the intrafraction motion, as detected by both SGRT and CBCT, was larger than 2 mm in at least one direction. Sixteen patients preferred maskless treatment, while 3 worried they would move too much. Conclusions: Using SGRT and a standard head rest resulted in a patient-friendly treatment with accurate patient setup and acceptably small intrafraction motion for H&N patients.

Clinical validation of the Varian Truebeam intra-fraction motion review (IMR) system for prostate treatment guidance.

This study quantified the performance of Intra-fraction Motion Review (IMR) during prostate Stereotactic Body Radiotherapy (SBRT) treatments. IMR was evaluated using prostate motion data from patients treated in an SBRT clinical trial (PROMETHEUS, NCT00587990).IMR measured prostate displacements were compared to those of two 3D motion management methods: Kilovoltage Intra-fraction Motion management (KIM) and MV/kV triangulation. A planning study assessing the impact of a defined prostate motion (2-5 mm) on the PTV coverage with and without IMR was performed. A clinically relevant IMR search region for prostate cancer SBRT treatments was determined using a customised anthropomorphic pelvis phantom with implanted gold seeds and a motion platform. IMR showed submillimeter agreement with corresponding 2D projections from both KIM and MV/kV triangulation. However, IMR detected actual displacements consistently in considerably fewer frames than KIM (3D), with the actual numbers depending on the settings. The Default Search Region (DSR) method employing a circular search region proved superior to user-contoured structures in detecting clinically relevant prostate motion. Reducing the DSR search region radius can reduce the impact of the 2D nature of IMR and improve the detectability of actual motion (by 10% per 0.5 mm reduction) but must be balanced against increased beam interruptions from minor, clinically irrelevant motion. The use of IMR for SBRT prostate treatments has the potential to improve target dose coverage (minimum dose to 98% of the PTV, D98%) by > 20% compared to treatment without IMR. Calculated D98% of IMR monitored treatments with motion was within 1.5% of plans without motion.

Automatic stent recognition using perceptual attention U-net for quantitative intrafraction motion monitoring in pancreatic cancer radiotherapy.

PURPOSE: Stent has often been used as an internal surrogate to monitor intrafraction tumor motion during pancreatic cancer radiotherapy. Based on the stent contours generated from planning CT images, the current intrafraction motion review (IMR) system on Varian TrueBeam only provides a tool to verify the stent motion visually but lacks quantitative information. The purpose of this study is to develop an automatic stent recognition method for quantitative intrafraction tumor motion monitoring in pancreatic cancer treatment. METHODS: A total of 535 IMR images from 14 pancreatic cancer patients were retrospectively selected in this study, with the manual contour of the stent on each image serving as the ground truth. We developed a deep learning-based approach that integrates two mechanisms that focus on the features of the segmentation target. The objective attention modeling was integrated into the U-net framework to deal with the optimization difficulties when training a deep network with 2D IMR images and limited training data. A perceptual loss was combined with the binary cross-entropy loss and a Dice loss for supervision. The deep neural network was trained to capture more contextual information to predict binary stent masks. A random-split test was performed, with images of ten patients (71%, 380 images) randomly selected for training, whereas the rest of four patients (29%, 155 images) were used for testing. Sevenfold cross-validation of the proposed PAUnet on the 14 patients was performed for further evaluation. RESULTS: Our stent segmentation results were compared with the manually segmented contours. For the random-split test, the trained model achieved a mean (±standard deviation) stent Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), the center-of-mass distance (CMD), and volume difference V o l d i f f $Vo{l_{diff}}$ were 0.96 (±0.01), 1.01 (±0.55) mm, 0.66 (±0.46) mm, and 3.07% (±2.37%), respectively. The sevenfold cross-validation of the proposed PAUnet had the mean (±standard deviation) of 0.96 (±0.02), 0.72 (±0.49) mm, 0.85 (±0.96) mm, and 3.47% (±3.27%) for the DSC, HD95, CMD, and V o l d i f f $Vo{l_{diff}}$ . CONCLUSION: We developed a novel deep learning-based approach to automatically segment the stent from IMR images, demonstrated its clinical feasibility, and validated its accuracy compared to manual segmentation. The proposed technique could be a useful tool for quantitative intrafraction motion monitoring in pancreatic cancer radiotherapy.

Assessment of the accuracy of truebeam intrafraction motion review (IMR) system for prostate treatment guidance.

Intrafraction motion review (IMR), a real-time 2D, motion management feature of the Varian Truebeam™ incorporates triggered imaging, automatic fiducial marker detection and automatic beam hold. With the increasing adoption of high dose per fraction stereotactic body radiotherapy (SBRT) this system provides a potential means to ensure treatment accuracy. The goal of this study was therefore to investigate and quantify key performance characteristics of IMR for prostate treatment guidance. Phantom experiments were performed with a custom Computerized Imaging Reference Systems, Inc (CIRS) pelvis phantom with implanted gold seeds and the Hexamotion™ 5D motion platform. The system accuracy was assessed statically and under typical prostate motion trajectories. The IMR functionality and marker detectability was tested under different anatomical conditions and with different imaging acquisition modes. Imaging dose for triggered imaging modes was determined using an ionisation chamber based on IPEMB dose calibration protocol for kV energies. For zero displacement, the IMR demonstrated submillimeter agreement with the known position. Similarly, dynamic motion differences between the IMR reported position and 2D trajectory displacement were within 1 mm. Static displacement in the anterior direction was reported by IMR as sinusoidal motion on the x-axis (kV angle). The 2D nature of IMR limits the ability to detect motion out of the plane of the kV image detector. Using typical clinical imaging settings, imaging dose determined at the patient surface was 2.58 mGy/frame and the corresponding IMR displayed dose was 2.63 mGy/frame. The methodology used was able to quantify the accuracy of the IMR system. The IMR was able to accurately and consistently report fiducial positions within the limitations inherent of a 2D system. IMR is fully integrated with the Truebeam system with an easy to use and efficient workflow and is clinically beneficial especially within the context of SBRT.

Kilovoltage intrafraction motion monitoring and target dose reconstruction for stereotactic volumetric modulated arc therapy of tumors in the liver.

PURPOSE: To use intrafraction kilovoltage (kV) imaging during liver stereotactic body radiotherapy (SBRT) delivered by volumetric modulated arc therapy (VMAT) to estimate the intra-treatment target motion and to reconstruct the delivered target dose. METHODS: Six liver SBRT patients with 2-3 implanted gold markers received SBRT in three fractions of 18.75 Gy or 25 Gy. CTV-to-PTV margins of 5 mm in the axial plane and 10 mm in the cranio-caudal directions were applied. A VMAT plan was designed to give minimum target doses of 95% (CTV) and 67% (PTV). At each fraction, the 3D marker trajectory was estimated by fluoroscopic kV imaging throughout treatment delivery and used to reconstruct the actually delivered CTV dose. The reduction in D95 (minimum dose to 95% of the CTV) relative to the planned D95 was calculated. RESULTS: The kV position estimation had mean root-mean-square errors of 0.36 mm and 0.47 mm parallel and perpendicular to the kV imager, respectively. Intrafraction motion caused a mean 3D target position error of 2.9 mm and a mean D95 reduction of 6.0%. The D95 reduction correlated with the mean 3D target position error during a fraction. CONCLUSIONS: Kilovoltage imaging for detailed motion monitoring with dose reconstruction of VMAT-based liver SBRT was demonstrated for the first time showing large dosimetric impact of intrafraction tumor motion.