Kurt E. Augustine

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 Intelreg 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.

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.

Optimization of spine surgery planning with 3D image templating tools

The current standard of care for patients with spinal disorders involves a thorough clinical history, physical exam, and imaging studies. Simple radiographs provide a valuable assessment but prove inadequate for surgery planning because of the complex 3-dimensional anatomy of the spinal column and the close proximity of the neural elements, large blood vessels, and viscera. Currently, clinicians still use primitive techniques such as paper cutouts, pencils, and markers in an attempt to analyze and plan surgical procedures. 3D imaging studies are routinely ordered prior to spine surgeries but are currently limited to generating simple, linear and angular measurements from 2D views orthogonal to the central axis of the patient. Complex spinal corrections require more accurate and precise calculation of 3D parameters such as oblique lengths, angles, levers, and pivot points within individual vertebra. We have developed a clinician friendly spine surgery planning tool which incorporates rapid oblique reformatting of each individual vertebra, followed by interactive templating for 3D placement of implants. The template placement is guided by the simultaneous representation of multiple 2D section views from reformatted orthogonal views and a 3D rendering of individual or multiple vertebrae enabling superimposition of virtual implants. These tools run efficiently on desktop PCs typically found in clinician offices or workrooms. A preliminary study conducted with Mayo Clinic spine surgeons using several actual cases suggests significantly improved accuracy of pre-operative measurements and implant localization, which is expected to increase spinal procedure efficiency and safety, and reduce time and cost of the operation.

ITK and ANALYZE: a synergistic integration

The Insight Toolkit (ITK) is a C++ open-source software toolkit developed under sponsorship of the National Library of Medicine. It provides advanced algorithms for performing image registration and segmentation, but does not provide support for visualization and analysis, nor does it offer any graphical user interface (GUI). The purpose of this integration project is to make ITK readily accessible to end-users with little or no programming skills, and provide interactive processing, visualization and measurement capabilities. This is achieved through the integration of ITK with ANALYZE, a multi-dimension image visualization/analysis application installed in over 300 institutions around the world, with a user-base in excess of 4000. This integration is carried out at both the software foundation and GUI levels. The foundation technology upon which ANALYZE is built is a comprehensive C-function library called AVW. A new set of AVW-ITK functions have been developed and integrated into the AVW library, and four new ITK modules have been added to the ANALYZE interface. Since ITK is a software developer’s toolkit, the only way to access its intrinsic power is to write programs that incorporate it. Integrating ITK with ANALYZE opens the ITK algorithms to end-users who otherwise might never be able to take advantage of the toolkit’s advanced functionality. In addition, this integration provides end-to-end interactive problem solving capabilities which allow all users, including programmers, an integrated system to readily display and quantitatively evaluate the results from the segmentation and registration routines in ITK, regardless of the type or format of input images, which are comprehensively supported in ANALYZE.

Plan to procedure: combining 3D templating with rapid prototyping to enhance pedicle screw placement

Spinal fusion procedures involving the implantation of pedicle screws have steadily increased over the past decade because of demonstrated improvement in biomechanical stability of the spine. However, current methods of spinal fusion carries a risk of serious vascular, visceral, and neurological injury caused by inaccurate placement or inappropriately sized instrumentation, which may lead to patient paralysis or even fatality. 3D spine templating software developed by the Biomedical Imaging Resource (BIR) at Mayo Clinic allows the surgeon to virtually place pedicle screws using pre-operative 3D CT image data. With the template plan incorporated, a patient-specific 3D anatomic model is produced using a commercial rapid prototyping system. The pre-surgical plan and the patient-specific model then are used in the procedure room to provide real-time visualization and quantitative guidance for accurate placement of each pedicle screw, significantly reducing risk of injury. A pilot study was conducted at Mayo Clinic by the Department of Radiology, the Department of Orthopedics, and the BIR, involving seven complicated pediatric spine cases. In each case, pre-operative 3D templating was carried out and patient specific models were generated. The plans and the models were used intra-operatively, providing precise pedicle screw starting points and trajectories. Postoperative assessment by the surgeon confirmed all seven operations were successful. Results from the study suggest that patient-specific, 3D anatomic models successfully acquired from 3D templating tools are valuable for planning and conducting pedicle screw insertion procedures.

Toward Virtual Modeling and Templating for Enhanced Spine Surgery Planning

Traditional 2D images provide limited use for accurate planning of spine interventions, due to their inability to display the complex 3D spine anatomy and close proximity of nerve bundles and vascular structures that must be avoided during the procedure. We have developed a platform for spine surgery planning that employs standard of care 3D pre-operative images and enables oblique reformatting and 3D rendering of individual or multiple vertebrae, interactive templating, and placement of virtual pedicle implants into the patient-specific CT data. Here we propose a combined surrogate metric—the Fastening Strength—to provide estimates of the optimal implant selection and trajectory based on implant dimension and bone mineral density of the displaced bone substrate. We conducted a retrospective clinical study based on pre- and post-operative data from four patients who underwent procedures involving pedicle screw implantation. We assessed the retrospective plans against the post-operative imaging data according to implant dimension, mean voxel intensity of implant trajectory, and Fastening Strength and showed consistency between the proposed plans and the post-operative procedure outcome. Our preliminary studies have demonstrated the feasibility of the platform in assisting the surgeon with the selection of appropriate size implant and trajectory that optimizes Fastening Strength, given the intrinsic vertebral geometry and bone mineral density. Herein we describe the platform infrastructure and capabilities, present preliminary studies conducted to assess impact on typical instrumentation procedures, and share our initial clinical experience in employing the proposed tool for the planning of several complicated spinal correction procedures for which the traditional planning approaches proved insufficient. Lastly, we also disseminate on several clinical cases and their post-operative assessment for which the proposed platform was employed by the surgical team.

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.

Fracture risk assessment: improved evaluation of vertebral integrity among metastatic cancer patients to aid in surgical decision-making

Failure of the spines structural integrity from metastatic disease can lead to both pain and neurologic deficit. Fractures that require treatment occur in over 30% of bony metastases. Our objective is to use computed tomography (CT) in conjunction with analytic techniques that have been previously developed to predict fracture risk in cancer patients with metastatic disease to the spine. Current clinical practice for cancer patients with spine metastasis often requires an empirical decision regarding spinal reconstructive surgery. Early image-based software systems used for CT analysis are time consuming and poorly suited for clinical application. The Biomedical Image Resource (BIR) at Mayo Clinic, Rochester has developed an image analysis computer program that calculates from CT scans, the residual load-bearing capacity in a vertebra with metastatic cancer. The Spine Cancer Assessment (SCA) program is built on a platform designed for clinical practice, with a workflow format that allows for rapid selection of patient CT exams, followed by guided image analysis tasks, resulting in a fracture risk report. The analysis features allow the surgeon to quickly isolate a single vertebra and obtain an immediate pre-surgical multiple parallel section composite beam fracture risk analysis based on algorithms developed at Mayo Clinic. The analysis software is undergoing clinical validation studies. We expect this approach will facilitate patient management and utilization of reliable guidelines for selecting among various treatment option based on fracture risk.

Enhanced planning of interventions for spinal deformity correction using virtual modeling and visualization techniques

Traditionally spinal correction procedures have been planned using 2D radiographs or image slices extracted from conventional computed tomography scans. Such images prove inadequate for accurately and precisely planning interventions, mainly due to the complex 3D anatomy of the spinal column, as well as the close proximity of nerve bundles and vascular structures that must be avoided during the procedure. To address these limitations and provide the surgeon with more representative information while taking full advantage of the 3D volumetric imaging data, we have developed a clinician-friendly application for spine surgery planning. This tool enables rapid oblique reformatting of each individual vertebral image, 3D rendering of each or multiple vertebrae, as well as interactive templating and placement of virtual implants. Preliminary studies have demonstrated improved accuracy and confidence of pre-operative measurements and implant localization and suggest that the proposed application may lead to increased procedure efficiency, safety, shorter intra-operative time, and lower costs.

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 systems (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.