A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT.

On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames per second) acquired using a MR image-guided radiotherapy (MR-IGRT) system. Manual con-tours of the kidney, bladder, duodenum, and a liver tumor by an experienced radiation oncologist were used as the ground truth for performance evaluation. Besides the manual segmentation, images were automatically segmented using thresholding, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE) algorithms, as well as the tissue tracking algorithm provided by the ViewRay treatment planning and delivery system (VR-TPDS). The performance of the five algorithms was evaluated quantitatively by comparing with the manual segmentation using the Dice coefficient and target registration error (TRE) measured as the distance between the centroid of the manual ROI and the centroid of the automatically segmented ROI. All methods were able to successfully segment the bladder and the kidney, but only FKM, KHM, and VR-TPDS were able to segment the liver tumor and the duodenum. The performance of the thresholding, FKM, KHM, and RD-LSE algorithms degraded as the local image contrast decreased, whereas the performance of the VP-TPDS method was nearly independent of local image contrast due to the reference registration algorithm. For segmenting high-contrast images (i.e., kidney), the thresholding method provided the best speed (< 1 ms) with a satisfying accuracy (Dice = 0.95). When the image contrast was low, the VR-TPDS method had the best automatic contour. Results suggest an image quality determination procedure before segmentation and a combination of different methods for optimal segmentation with the on-board MR-IGRT system.

Online Magnetic Resonance Image Guided Adaptive Radiation Therapy: First Clinical Applications.

PURPOSE: To demonstrate the feasibility of online adaptive magnetic resonance (MR) image guided radiation therapy (MR-IGRT) through reporting of our initial clinical experience and workflow considerations. METHODS AND MATERIALS: The first clinically deployed online adaptive MR-IGRT system consisted of a split 0.35T MR scanner straddling a ring gantry with 3 multileaf collimator-equipped (60)Co heads. The unit is supported by a Monte Carlo-based treatment planning system that allows real-time adaptive planning with the patient on the table. All patients undergo computed tomography and MR imaging (MRI) simulation for initial treatment planning. A volumetric MRI scan is acquired for each patient at the daily treatment setup. Deformable registration is performed using the planning computed tomography data set, which allows for the transfer of the initial contours and the electron density map to the daily MRI scan. The deformed electron density map is then used to recalculate the original plan on the daily MRI scan for physician evaluation. Recontouring and plan reoptimization are performed when required, and patient-specific quality assurance (QA) is performed using an independent in-house software system. RESULTS: The first online adaptive MR-IGRT treatments consisted of 5 patients with abdominopelvic malignancies. The clinical setting included neoadjuvant colorectal (n=3), unresectable gastric (n=1), and unresectable pheochromocytoma (n=1). Recontouring and reoptimization were deemed necessary for 3 of 5 patients, and the initial plan was deemed sufficient for 2 of the 5 patients. The reasons for plan adaptation included tumor progression or regression and a change in small bowel anatomy. In a subsequently expanded cohort of 170 fractions (20 patients), 52 fractions (30.6%) were reoptimized online, and 92 fractions (54.1%) were treated with an online-adapted or previously adapted plan. The median time for recontouring, reoptimization, and QA was 26 minutes. CONCLUSION: Online adaptive MR-IGRT has been successfully implemented with planning and QA workflow suitable for routine clinical application. Clinical trials are in development to formally evaluate adaptive treatments for a variety of disease sites.

Catching errors with patient-specific pretreatment machine log file analysis.

PURPOSE: A robust, efficient, and reliable quality assurance (QA) process is highly desired for modern external beam radiation therapy treatments. Here, we report the results of a semiautomatic, pretreatment, patient-specific QA process based on dynamic machine log file analysis clinically implemented for intensity modulated radiation therapy (IMRT) treatments delivered by high energy linear accelerators (Varian 2100/2300 EX, Trilogy, iX-D, Varian Medical Systems Inc, Palo Alto, CA). The multileaf collimator machine (MLC) log files are called Dynalog by Varian. METHODS AND MATERIALS: Using an in-house developed computer program called "Dynalog QA," we automatically compare the beam delivery parameters in the log files that are generated during pretreatment point dose verification measurements, with the treatment plan to determine any discrepancies in IMRT deliveries. Fluence maps are constructed and compared between the delivered and planned beams. RESULTS: Since clinical introduction in June 2009, 912 machine log file analyses QA were performed by the end of 2010. Among these, 14 errors causing dosimetric deviation were detected and required further investigation and intervention. These errors were the result of human operating mistakes, flawed treatment planning, and data modification during plan file transfer. Minor errors were also reported in 174 other log file analyses, some of which stemmed from false positives and unreliable results; the origins of these are discussed herein. CONCLUSIONS: It has been demonstrated that the machine log file analysis is a robust, efficient, and reliable QA process capable of detecting errors originating from human mistakes, flawed planning, and data transfer problems. The possibility of detecting these errors is low using point and planar dosimetric measurements.

Initial experience with TrueBeam trajectory log files for radiation therapy delivery verification.

PURPOSE: Traditionally, initial and weekly chart checks involve checking various parameters in the treatment management system against the expected treatment parameters and machine settings. This process is time-consuming and labor intensive. We explore utilizing the Varian TrueBeam log files (Varian Medical System, Palo Alto, CA), which contain the complete delivery parameters for an end-to-end verification of daily patient treatments. METHODS AND MATERIALS: An in-house software tool for 3-dimensional (3D) conformal therapy, enhanced dynamic wedge delivery, intensity modulated radiation therapy (IMRT), volumetric modulated radiation therapy, flattening filter-free mode, and electron therapy treatment verification was developed. The software reads the Varian TrueBeam log files, extracts the delivered parameters, and compares them against the original treatment planning data. In addition to providing an end-to-end data transfer integrity check, the tool also verifies the accuracy of treatment deliveries. This is performed as part of the initial chart check for IMRT plans and after first fraction for the 3D plans. The software was validated for consistency and accuracy for IMRT and 3D fields. RESULTS: Based on the validation results the accuracy of MLC, jaw and gantry positions were well within the expected values. The patient quality assurance results for 127 IMRT patients and 51 conventional fields were within 0.25 mm for multileaf collimator positions, 0.3 degree for gantry angles, 0.13 monitor units for monitor unit delivery accuracy, and 1 mm for jaw positions. The delivered dose rates for the flattening filter-free modes were within 1% of the planned dose rates. CONCLUSIONS: The end-to-end data transfer check using TrueBeam log files and the treatment delivery parameter accuracy check provides an efficient, reliable beam parameter check process for various radiation delivery techniques.

Evaluation of the efficiency and effectiveness of independent dose calculation followed by machine log file analysis against conventional measurement based IMRT QA.

Experimental methods are commonly used for patient-specific IMRT delivery verification. There are a variety of IMRT QA techniques which have been proposed and clinically used with a common understanding that not one single method can detect all possible errors. The aim of this work was to compare the efficiency and effectiveness of independent dose calculation followed by machine log file analysis to conventional measurement-based methods in detecting errors in IMRT delivery. Sixteen IMRT treatment plans (5 head-and-neck, 3 rectum, 3 breast, and 5 prostate plans) created with a commercial treatment planning system (TPS) were recalculated on a QA phantom. All treatment plans underwent ion chamber (IC) and 2D diode array measurements. The same set of plans was also recomputed with another commercial treatment planning system and the two sets of calculations were compared. The deviations between dosimetric measurements and independent dose calculation were evaluated. The comparisons included evaluations of DVHs and point doses calculated by the two TPS systems. Machine log files were captured during pretreatment composite point dose measurements and analyzed to verify data transfer and performance of the delivery machine. Average deviation between IC measurements and point dose calculations with the two TPSs for head-and-neck plans were 1.2 ± 1.3% and 1.4 ± 1.6%, respectively. For 2D diode array measurements, the mean gamma value with 3% dose difference and 3 mm distance-to-agreement was within 1.5% for 13 of 16 plans. The mean 3D dose differences calculated from two TPSs were within 3% for head-and-neck cases and within 2% for other plans. The machine log file analysis showed that the gantry angle, jaw position, collimator angle, and MUs were consistent as planned, and maximal MLC position error was less than 0.5 mm. The independent dose calculation followed by the machine log analysis takes an average 47 ± 6 minutes, while the experimental approach (using IC and 2D diode array measurements) takes an average about 2 hours in our clinic. Independent dose calculation followed by machine log file analysis can be a reliable tool to verify IMRT treatments. Additionally, independent dose calculations have the potential to identify several problems (heterogeneity calculations, data corruptions, system failures) with the primary TPS, which generally are not identifiable with a measurement-based approach. Additionally, machine log file analysis can identify many problems (gantry, collimator, jaw setting) which also may not be detected with a measurement-based approach. Machine log file analysis could also detect performance problems for individual MLC leaves which could be masked in the analysis of a measured fluence.