Technical Note: Integrating an open source Monte Carlo code "MCsquare" for clinical use in intensity-modulated proton therapy.

PURPOSE: To commission an open source Monte Carlo (MC) dose engine, "MCsquare" for a synchrotron-based proton machine, integrate it into our in-house C++-based I/O user interface and our web-based software platform, expand its functionalities, and improve calculation efficiency for intensity-modulated proton therapy (IMPT). METHODS: We commissioned MCsquare using a double Gaussian beam model based on in-air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread-out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++-based dose calculation code and web-based second check platform "DOSeCHECK." We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well-benchmarked GPU-accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)-related model-dependent biological dose calculation. RESULTS: Differences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients' geometries using an inexpensive CPU workstation (Intel Xeon E5-2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min. CONCLUSIONS: MCsquare was successfully commissioned for a synchrotron-based proton beam therapy delivery system and integrated into our web-based second check platform. After adopting CT resampling and implementing LET model-dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo-based and LET-guided robust optimization in IMPT, which will be done in the future studies.

Automation of routine elements for spot-scanning proton patient-specific quality assurance.

PURPOSE: At our institution, all proton patient plans undergo patient-specific quality assurance (PSQA) prior to treatment delivery. For intensity-modulated proton beam therapy, quality assurance is complex and time consuming, and it may involve multiple measurements per field. We reviewed our PSQA workflow and identified the steps that could be automated and developed solutions to improve efficiency. METHODS: We used the treatment planning system's (TPS) capability to support C# scripts to develop an Eclipse scripting application programming interface (ESAPI) script and automate the preparation of the verification phantom plan for measurements. A local area network (LAN) connection between our measurement equipment and shared database was established to facilitate equipment control, measurement data transfer, and storage. To improve the analysis of the measurement data, a Python script was developed to automatically perform a 2D-3D γ-index analysis comparing measurements in the plane of a two-dimensional detector array with TPS predictions in a water phantom for each acquired measurement. RESULTS: Device connection via LAN granted immediate access to the plan and measurement information for downstream analysis using an online software suite. Automated scripts applied to verification plans reduced time from preparation steps by at least 50%; time reduction from automating γ-index analysis was even more pronounced, dropping by a factor of 10. On average, we observed an overall time savings of 55% in completion of the PSQA per patient plan. CONCLUSIONS: The automation of the routine tasks in the PSQA workflow significantly reduced the time required per patient, reduced user fatigue, and frees up system users from routine and repetitive workflow steps allowing increased focus on evaluating key quality metrics.

Clinical Implementation of a Proton Dose Verification System Utilizing a GPU Accelerated Monte Carlo Engine.

PURPOSE: To develop a clinical infrastructure that allows for routine Monte Carlo dose calculation verification of spot scanning proton treatment plans and includes a simple biological model to aid in normal tissue protection. MATERIALS AND METHODS: A graphical processing unit accelerated Monte Carlo dose engine was used as the calculation engine for dose verification on spot scanning proton plans. An infrastructure was built around this engine that allows for seamless exporting of treatment plans from the treatment planning system and importing of dose distribution from the Monte Carlo calculation via DICOM (digital imaging and communications in medicine). An easy-to-use Web-based interface was developed so that the application could be run from any computer. In addition to the standard relative biological effectiveness = 1.1 for proton therapy, a simple linear equation dependent on dose-weighted linear energy transfer was included. This was used to help detect possible high biological dose in critical structures. RESULTS: More than 270 patients were treated at our proton center in the first year of operation. Because most plans underwent multiple iterations before final approval, more than 1000 plans have been run through the system from multiple users with minimal downtime. The average time from plan export to importing of the Monte Carlo doses was less than 15 minutes. Treatment plans have been modified based on the nominal Monte Carlo dose or the biological dose. CONCLUSION: Monte Carlo dose calculation verification of spot scanning proton treatment plans is feasible in a clinical environment. The 3-dimensional dose verification, particularly near heterogeneities, has resulted in plan modifications. The biological dose data provides actionable feedback for end of range effects, especially in pediatric patients.

Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction.

PURPOSE: To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). MATERIALS AND METHODS: This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per-malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than -0.10. RESULTS: Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: -0.041 [95% CI: -0.090, 0.009] and -0.003 [95% CI: -0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: -0.077, 0.106]), whereas lower-dose FBP images were not (difference -0.049 [95% CI: -0.140, 0.043]). In 37 patients with SAFIRE reconstructions, the three lower-dose alternatives were found to be noninferior to the routine-dose FBP. CONCLUSION: At moderate levels of dose reduction, lower-dose FBP images without ANLM or SAFIRE were noninferior to routine-dose images for abdominal CT but not for liver or pancreas CT.

Mapping high-fidelity volume rendering for medical imaging to CPU, GPU and many-core architectures.

Medical volumetric imaging requires high fidelity, high performance rendering algorithms. We motivate and analyze new volumetric rendering algorithms that are suited to modern parallel processing architectures. First, we describe the three major categories of volume rendering algorithms and confirm through an imaging scientist-guided evaluation that ray-casting is the most acceptable. We describe a thread- and data-parallel implementation of ray-casting that makes it amenable to key architectural trends of three modern commodity parallel architectures: multi-core, GPU, and an upcoming many-core Intel architecture code-named Larrabee. We achieve more than an order of magnitude performance improvement on a number of large 3D medical datasets. We further describe a data compression scheme that significantly reduces data-transfer overhead. This allows our approach to scale well to large numbers of Larrabee cores.

An immersive simulation system for provoking and analyzing cataplexy.

Cataplexy, a sudden loss of voluntary muscle control, is one of the hallmark symptoms of narcolepsy, a sleep disorder characterized by excessive daytime sleepiness. Cataplexy is usually triggered by strong, spontaneous emotions, such as laughter, surprise, fear or anger, and is more common in times of stress. The Sleep Disorders Unit and the Biomedical Imaging Resource at Mayo Clinic are developing interactive display technology for reliably inducing cataplexy during clinical monitoring. The use of immersive displays may help bypass patient defenses, and game-like "unreality" allows introduction of surprising, threatening, or humorous elements, with little risk of offending patients. The project is referred to as the "Cataplexy/Narcolepsy Activation Program", or CatNAP. We have developed an automobile driving simulation to allow the introduction of humorous, surprising, or stress-inducing events and objects as the patient attempts to navigate a simulated vehicle through a virtual town. The patient wears a stereoscopic head-mounted display, by which he views the virtual town through the windows of his simulated vehicle. The vehicle is controlled via a driving simulator steering wheel and pedal cluster. The patient is instructed to drive his vehicle to another location in town, given initial directions and street signs. As he attempts to accomplish the task, various objects, sounds or conditions occur which may distract, startle, frustrate or cause laughter; responses which may trigger a cataplectic episode. The patient can be monitored by reflex tests and EMG recordings during the driving experience. An evaluation phase with volunteer patients previously diagnosed with cataplexy has been completed. The goal of these trials was to gain insight from the volunteers as to improvements that could be made to the simulation. All patients that participated in the evaluation phase have been under a physician's care for a number of years and control their cataplexy with medication. We believe this is a novel and innovative approach to a difficult problem. CatNAP is a compelling example of the potentially effective application of virtual reality technology to an important clinical problem that has resisted previous approaches. Preliminary results suggest that an immersive simulation system like CatNAP will be able to reliably induce cataplexy in a controlled environment. The project is continuing through a final stage of refinement prior to conducting a full clinical study.