Quantification accuracy for dynamic contrast enhanced (DCE) CT imaging: phantom and quality assurance framework.

PURPOSE: Standardization and protocol optimization is essential for quantification of Dynamic Contrast Enhanced CT as an imaging biomarker. Currently, no commercially available quality assurance (QA) phantoms can provide for testing a complete set of imaging parameters pertaining to routine quality control for contrast-enhanced (CE) CT, as well as spatiotemporal accuracy. The purpose of this work was, therefore: (a) developing a solid calibration phantom for routine CE CT quality assurance; (b) investigating the sensitivity of CECT to organ motion, and (c) characterizing a volumetric CT scanner for CECT. METHODS: CECT calibration phantom consisting of an acrylic uniform cylinder containing multiple capsules of varying diameters and orientations was designed and built. The capsules contain different solid density materials mimicking iodine contrast enhancement. Sensitivity and accuracy of CECT measurements on all capsules was performed using a 320-slice CT scanner for a range of scan parameters both with and without phantom motion along the transaxial axis of the scanner. RESULTS: Routine commissioning tests such as uniformity, spatial resolution and image noise were successfully determined using the CECT phantom. Partial volume effect and motion blurring both contribute to a general decrease in contrast enhancement and this was further dependent on capsule orientation (least pronounced for the transaxial orientation). Scanning with a rotation time of less than 0.5 s, the effect of blurring is less than 3% for all orientations and phantom speeds. CONCLUSION: A new robust contrast calibration phantom was developed and used to evaluate the performance of a 320-slice volumetric CT scanner for DCE-CT.

Computational fluid dynamics modelling of perfusion measurements in dynamic contrast-enhanced computed tomography: development, validation and clinical applications.

Dynamic contrast-enhanced computed tomography (DCE-CT) is an imaging tool that aids in evaluating functional characteristics of tissue at different stages of disease management: diagnostic, radiation treatment planning, treatment effectiveness, and monitoring. Clinical validation of DCE-derived perfusion parameters remains an outstanding problem to address prior to perfusion imaging becoming a widespread standard as a non-invasive quantitative measurement tool. One approach to this validation process has been the development of quality assurance phantoms in order to facilitate controlled perfusion ex vivo. However, most of these systems fail to establish and accurately replicate physiologically relevant capillary permeability and exchange performance. The current work presents the first step in the development of a prospective suite of physics-based perfusion simulations based on coupled fluid flow and particle transport phenomena with the goal of enhancing the understanding of clinical contrast agent kinetics. Existing knowledge about a controllable, two-compartmental fluid exchange phantom was used to validate the computational fluid dynamics (CFD) simulation model presented herein. The sensitivity of CFD-derived contrast uptake curves to contrast injection parameters, including injection duration and flow rate, were quantified and found to be within 10% accuracy. The CFD model was employed to evaluate two commonly used clinical kinetic algorithms used to derive perfusion parameters: Fick's principle and the modified Tofts model. Neither kinetic model was able to capture the true transport phenomena it aimed to represent but if the overall contrast concentration after injection remained identical, then successive DCE-CT evaluations could be compared and could indeed reflect differences in regional tissue flow. This study sets the groundwork for future explorations in phantom development and pharmaco-kinetic modelling, as well as the development of novel contrast agents for DCE imaging.

Development of a dynamic quality assurance testing protocol for multisite clinical trial DCE-CT accreditation.

PURPOSE: Credentialing can have an impact on whether or not a clinical trial produces useful quality data that is comparable between various institutions and scanners. With the recent increase of dynamic contrast enhanced-computed tomography (DCE-CT) usage as a companion biomarker in clinical trials, effective quality assurance, and control methods are required to ensure there is minimal deviation in the results between different scanners and protocols at various institutions. This paper attempts to address this problem by utilizing a dynamic flow imaging phantom to develop and evaluate a DCE-CT quality assurance (QA) protocol. METHODS: A previously designed flow phantom, capable of producing predictable and reproducible time concentration curves from contrast injection was fully validated and then utilized to design a DCE-CT QA protocol. The QA protocol involved a set of quantitative metrics including injected and total mass error, as well as goodness of fit comparison to the known truth concentration curves. An additional region of interest (ROI) sensitivity analysis was also developed to provide additional details on intrascanner variability and determine appropriate ROI sizes for quantitative analysis. Both the QA protocol and ROI sensitivity analysis were utilized to test variations in DCE-CT results using different imaging parameters (tube voltage and current) as well as alternate reconstruction methods and imaging techniques. The developed QA protocol and ROI sensitivity analysis was then applied at three institutions that were part of clinical trial involving DCE-CT and results were compared. RESULTS: The inherent specificity of robustness of the phantom was determined through calculation of the total intraday variability and determined to be less than 2.2±1.1% (total calculated output contrast mass error) with a goodness of fit (R2) of greater than 0.99±0.0035 (n=10). The DCE-CT QA protocol was capable of detecting significant deviations from the expected phantom result when scanning at low mAs and low kVp in terms of quantitative metrics (Injected Mass Error 15.4%), goodness of fit (R2) of 0.91, and ROI sensitivity (increase in minimum input function ROI radius by 146±86%). These tests also confirmed that the ASIR reconstruction process was beneficial in reducing noise without substantially increasing partial volume effects and that vendor specific modes (e.g., axial shuttle) did not significantly affect the phantom results. The phantom and QA protocol were finally able to quickly (<90 min) and successfully validate the DCE-CT imaging protocol utilized at the three separate institutions of a multicenter clinical trial; thereby enhancing the confidence in the patient data collected. CONCLUSIONS: A DCE QA protocol was developed that, in combination with a dynamic multimodality flow phantom, allows the intrascanner variability to be separated from other sources of variability such as the impact of injection protocol and ROI selection. This provides a valuable resource that can be utilized at various clinical trial institutions to test conformance with imaging protocols and accuracy requirements as well as ensure that the scanners are performing as expected for dynamic scans.

Poster - Thur Eve - 05: Safety systems and failure modes and effects analysis for a magnetic resonance image guided radiation therapy system.

INTRODUCTION: An online Magnetic Resonance guided Radiation Therapy (MRgRT) system is under development. The system is comprised of an MRI with the capability of travel between and into HDR brachytherapy and external beam radiation therapy vaults. The system will provide on-line MR images immediately prior to radiation therapy. The MR images will be registered to a planning image and used for image guidance. With the intention of system safety we have performed a failure modes and effects analysis. METHODS: A process tree of the facility function was developed. Using the process tree as well as an initial design of the facility as guidelines possible failure modes were identified, for each of these failure modes root causes were identified. For each possible failure the assignment of severity, detectability and occurrence scores was performed. Finally suggestions were developed to reduce the possibility of an event. RESULTS/DISCUSSION: The process tree consists of nine main inputs and each of these main inputs consisted of 5 - 10 sub inputs and tertiary inputs were also defined. The process tree ensures that the overall safety of the system has been considered. Several possible failure modes were identified and were relevant to the design, construction, commissioning and operating phases of the facility. The utility of the analysis can be seen in that it has spawned projects prior to installation and has lead to suggestions in the design of the facility.

Development of a dynamic flow imaging phantom for dynamic contrast-enhanced CT.

PURPOSE: Dynamic contrast enhanced CT (DCE-CT) studies with modeling of blood flow and tissue perfusion are becoming more prevalent in the clinic, with advances in wide volume CT scanners allowing the imaging of an entire organ with sub-second image frequency and sub-millimeter accuracy. Wide-spread implementation of perfusion DCE-CT, however, is pending fundamental validation of the quantitative parameters that result from dynamic contrast imaging and perfusion modeling. Therefore, the goal of this work was to design and construct a novel dynamic flow imaging phantom capable of producing typical clinical time-attenuation curves (TACs) with the purpose of developing a framework for the quantification and validation of DCE-CT measurements and kinetic modeling under realistic flow conditions. METHODS: The phantom is based on a simple two-compartment model and was printed using a 3D printer. Initial analysis of the phantom involved simple flow measurements and progressed to DCE-CT experiments in order to test the phantoms range and reproducibility. The phantom was then utilized to generate realistic input TACs. A phantom prediction model was developed to compute the input and output TACs based on a given set of five experimental (control) parameters: pump flow rate, injection pump flow rate, injection contrast concentration, and both control valve positions. The prediction model is then inversely applied to determine the control parameters necessary to generate a set of desired input and output TACs. A protocol was developed and performed using the phantom to investigate image noise, partial volume effects and CT number accuracy under realistic flow conditions. RESULTS: This phantom and its surrounding flow system are capable of creating a wide range of physiologically relevant TACs, which are reproducible with minimal error between experiments (sigma/micro < 5% for all metrics investigated). The dynamic flow phantom was capable of producing input and output TACs using either step function based or typical clinical arterial input function (AIF) inputs. The measured TACs were in excellent agreement with predictions across all comparison metrics with goodness of fit (R2) for the input function between 0.95 and 0.98, while the maximum enhancement differed by no more than 3.3%. The predicted output functions were similarly accurate producing R2 values between 0.92 and 0.99 and maximum enhancement to within 9.0%. The effect of ROI size on the arterial input function (AIF) was investigated in order to determine an operating range of ROI sizes which were minimally affected by noise for small dimensions and partial volume effects for large dimensions. It was possible to establish the measurement sensitivity of both the Toshiba (ROI radius range from 1.5 to 3.2 mm "low dose", 1.4 to 3.0 mm "high dose") and GE scanner (1.5 to 2.6 mm "low dose", 1.1 to 3.4 mm "high dose"). This application of the phantom also provides the ability to evaluate the effect of the AIF error on kinetic model parameter predictions. CONCLUSIONS: The dynamic flow imaging phantom is capable of producing accurate and reproducible results which can be predicted and quantified. This results in a unique tool for perfusion DCE-CT validation under realistic flow conditions which can be applied not only to compare different CT scanners and imaging protocols but also to provide a ground truth across multimodality dynamic imaging given its MRI and PET compatibility.

Implementation and characterization of a 320-slice volumetric CT scanner for simulation in radiation oncology.

PURPOSE: Effective target definition and broad employment of treatment response assessment with dynamic contrast-enhanced CT in radiation oncology requires increased speed and coverage for use within a single bolus injection. To this end, a novel volumetric CT scanner (Aquilion One, Toshiba, Tochigi Pref., Japan) has been installed at the Princess Margaret Hospital for implementation into routine CT simulation. This technology offers great advantages for anatomical and functional imaging in both scan speed and coverage. The aim of this work is to investigate the system's imaging performance and quality as well as CT quantification accuracy which is important for radiotherapy dose calculations. METHODS: The 320-slice CT scanner uses a 160 mm wide-area (2D) solid-state detector design which provides the possibility to acquire a volumetric axial length of 160 mm without moving the CT couch. This is referred to as "volume" and can be scanned with a rotation speed of 0.35-3 s. The scanner can also be used as a 64-slice CT scanner and perform conventional (axial) and helical acquisitions with collimation ranges of 1-32 and 16-32 mm, respectively. Commissioning was performed according to AAPM Reports TG 66 and 39 for both helical and volumetric imaging. Defrise and other cone-beam image analysis tests were performed. RESULTS: Overall, the imaging spatial resolution and geometric efficiency (GE) were found to be very good (>10 lp/mm, <1 mm spatial integrity and GE160 mm=85%) and within the AAPM guidelines as well as IEC recommendations. Although there is evidence of some cone-beam artifacts when scanning the Defrise phantom, image quality was found to be good and sufficient for treatment planning (soft tissue noise <10 HU). Measurements of CT number stability and contrast-to-noise values across the volume indicate clinically acceptable scan accuracy even at the field edge. CONCLUSIONS: Initial experience with this exciting new technology confirms its accuracy for routine CT simulation within radiation oncology and allows for future investigations into specialized dynamic volumetric imaging applications.

Motion artifact correction in free-breathing abdominal MRI using overlapping partial samples to recover image deformations.

This article presents a method to reconstruct liver MRI data acquired continuously during free breathing, without any external sensor or navigator measurements. When the deformations associated with k-space data are known, generalized matrix inversion reconstruction has been shown to be effective in reducing the ghosting and blurring artifacts of motion. This article describes a novel method to obtain these nonrigid deformations. A breathing model is built from a fast dynamic series: low spatial resolution images are registered and their deformations parameterized by overall superior-inferior displacement. The correct deformation for each subset of the subsequent imaging data is then found by comparing a few lines of k-space with the equivalent lines from a deformed reference image while varying the deformation over the model parameter. This procedure is known as image deformation recovery using overlapping partial samples (iDROPS). Simulations using 10 rapid dynamic studies from volunteers showed the average error in iDROPS-derived deformations within the liver to be 1.43 mm. A further four volunteers were imaged at higher spatial resolution. The complete reconstruction process using data from throughout several breathing cycles was shown to reduce blurring and ghosting in the liver. Retrospective respiratory gating was also demonstrated using the iDROPS parameterization.

Calibration of CT Hounsfield units for radiotherapy treatment planning of patients with metallic hip prostheses: the use of the extended CT-scale.

Heterogeneity corrections for radiotherapy dose calculations are based on the electron density of the disturbing heterogeneity. However, when CT planning a radiotherapy treatment, where metallic hip implants are present, considerable artefacts are seen in the images. Often, an additional problem arises whereby no information regarding the artificial hip's composition and geometry is available. This study investigates whether the extended CT range can be used to determine the composition (hence electron density) of artificial hips in radiotherapy patients. Two CT-calibration methods were evaluated, one based on material substitution, the other a stoichiometric calibration. We also evaluate whether the physical dimensions of metal prostheses can be accurately imaged for subsequent use in treatment planning computers. Neither calibration method successfully predicted electron densities. However, the limited range of implant-materials used in patients means that the extended CT range can still successfully distinguish between implant densities. The physical dimensions can be determined to +/-2 mm by establishing the required windowing of displays for each material. The cross-sectional area of the prosthesis and the presence of other high-density objects in a CT slice can influence the generated CT number and careful design of calibration phantoms is essential.