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SU-F-I-49: Vendor-Independent, Model-Based Iterative Reconstruction On a Rotating Grid with Coordinate-Descent Optimization for CT Imaging Investigations

Purpose: Iterative reconstruction methods show promise for improving image quality and lowering the dose in helical CT. We aim to develop a novel model-based reconstruction method that offers potential for dose reduction with reasonable computation speed and storage requirements for vendor-independent reconstruction from clinical data on a normal desktop computer. Methods: In 2012, Xu proposed reconstructing on rotating slices to exploit helical symmetry and reduce the storage requirements for the CT system matrix. Inspired by this concept, we have developed a novel reconstruction method incorporating the stored-system-matrix approach together with iterative coordinate-descent (ICD) optimization. A penalized-least-squares objective function with a quadratic penalty term is solved analytically voxel-by-voxel, sequentially iterating along the axial direction first, followed by the transaxial direction. 8 in-plane (transaxial) neighbors are used for the ICD algorithm. The forward problem is modeled via a unique approach that combines the principle of Joseph’s method with trilinear B-spline interpolation to enable accurate reconstruction with low storage requirements. Iterations are accelerated with multi-CPU OpenMP libraries. For preliminary evaluations, we reconstructed (1) a simulated 3D ellipse phantom and (2) an ACR accreditation phantom dataset exported from a clinical scanner (Definition AS, Siemens Healthcare). Image quality was evaluated in the resolution module. Results: Image quality was excellent for the ellipse phantom. For the ACR phantom, image quality was comparable to clinical reconstructions and reconstructions using open-source FreeCT-wFBP software. Also, we did not observe any deleterious impact associated with the utilization of rotating slices. The system matrix storage requirement was only 4.5GB, and reconstruction time was 50 seconds per iteration. Conclusion: Our reconstruction method shows potential for furthering research in low-dose helical CT, in particular as part of our ongoing development of an acquisition/reconstruction pipeline for generating images under a wide range of conditions. Our algorithm will be made available open-source as “FreeCT-ICD”. NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

60 APPLIED LIFE SCIENCES↗

TU-FG-209-07: Medical Physics 1.0 Versus Medical Physics 2.0: A Case Study

Purpose: To illustrate how performance analytics can identify performance decrement in digital radiography systems. Methods: Subsequent to a radiologist’s image quality complaint, four different advanced methods contributed to root cause analysis. Our system was a GE Revolution XQi digital radiography unit. Initially, we reviewed weekly GE Quality Assurance Procedures (QAP) results in a database dating from 2001. Next, we evaluated objective image quality metrics of individual PA Chest radiographs acquired. These images were anonymized, securely transferred, and analyzed by the Duke University Clinical Imaging Physics Group with software previously described{sup 1} and validated{sup 2}. Third, we compared the exposure-dependent SNR{sup 2} (NEQ) of the unit with previously established confidence limits{sup 3}. Finally, we explored our service database to reveal events that might affect detector performance. Results: QAP reported a decrease in CNR reflected in a significant increase in lung noise(Ln), mediastinum noise(Mn), and subdiaphragm-lung contrast(Slc) with a significant decrease in lung grey level(Lgl) after detector replacement. Most change occurred during week 1, before the QAP indicated one-half the ultimate decrease in CNR. After detector recalibration, QAP CNR improved, but was not restored to previous levels. Lgl and Slc were no longer significantly different from before, however Ln and Mn remained significantly different. Exposure-dependent SNR2 show the detector to be operating within limits in October 2006 but subsequently became miscalibrated sometime before acquisition of the 2011–2014 data. Service records revealed catastrophic failure of the Image Detection Controller that contained the 2007 calibration. Traditional metrics did not indicate that the system was performing outside of normal limits. Conclusion: Performance analytics are powerful tools whose proper application could allow early intervention in degraded system performance. The image-quality metrics appear to be highly sensitive to system performance and are reported with every acquisition rather than at arbitrary intervals. Confidence intervals may require customization for individual systems or detectors.

60 APPLIED LIFE SCIENCES↗

MO-DE-209-00: DBT Physics Basic to Advanced

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: To understand the fundamental principles behind tomosynthesis image acquisition. To understand the fundamentals of tomosynthesis image reconstruction. To learn the determinants of image quality and dose in DBT, including measurement techniques. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care.

60 APPLIED LIFE SCIENCES↗

MO-DE-209-01: Primer On Tomosynthesis

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: To understand the fundamental principles behind tomosynthesis image acquisition. To understand the fundamentals of tomosynthesis image reconstruction. To learn the determinants of image quality and dose in DBT, including measurement techniques. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care.

60 APPLIED LIFE SCIENCES↗

MO-DE-209-02: Tomosynthesis Reconstruction Methods

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: To understand the fundamental principles behind tomosynthesis image acquisition. To understand the fundamentals of tomosynthesis image reconstruction. To learn the determinants of image quality and dose in DBT, including measurement techniques. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care.

60 APPLIED LIFE SCIENCES↗

MO-DE-209-04: Radiation Dosimetry in Breast Tomosynthesis

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: To understand the fundamental principles behind tomosynthesis image acquisition. To understand the fundamentals of tomosynthesis image reconstruction. To learn the determinants of image quality and dose in DBT, including measurement techniques. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care.

60 APPLIED LIFE SCIENCES↗

Spatial Prediction Filtering for Medical Ultrasound in Aberration and Random Noise

While medical ultrasound imaging has become one of the most widely used imaging modalities in clinics, it often suffers from suboptimal image quality especially in technically difficult patients with a large amount of fat content that induces severe phase aberration effects and decreases the signal-to-noise (SNR) ratio. Several researchers have proposed various techniques, which can be broadly categorized as either a phase aberration correction (PAC) technique or a coherence-based imaging technique, to address the challenges in imaging technically difficult patients. Although both families of techniques have shown some success in improving the image quality in the presence of a mild level of phase aberration and/or random noise, they often fail to achieve meaningful improvements in the image quality and in some cases, and even create severe image artifacts. In this work, we employ an adaptive filtering technique called frequency-space (F-X) prediction filtering, which we recently introduced in ultrasound imaging, to overcome the weaknesses of existing techniques and achieve image quality improvements more effectively under varying levels of phase aberration and random noise. Using simulated and experimental phantom data with varying levels of phase aberration and random noise, we evaluate and compare the performance of FXPF with the most representative technique for each category: NNCC-based PAC and the generalized coherence factor (GCF). Our simulation, experimental phantom, and in vivo results demonstrate that FXPF is highly robust in varying levels of phase aberration and noise, and always outperforms both NNCC-based PAC and GCF in terms of the contrast-to-noise ratio (CNR) and the contrast when both random noise and phase aberration are present.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Stereosat - A new astrodynamics challenge

The paper investigates the astrodynamics requirements for a spacecraft which produces stereo images of the land masses of the earth for use in geoscience investigations, cartography and earth resource exploration. It describes a candidate Stereosat imaging product, presents criteria for evaluating potential image quality and usability, and assesses the impact of various spacecraft and astrodynamic factors on image quality. Several challenges are identified and discussed, namely (1) securing adequate image quality for pixel level elevation measurements, (2) determining absolute location of imaged phenomena in remote regions, (3) satisfying the long-term orbit prediction requirements, and (4) transmitting accurate orbit data along with the image data stream. Meeting these challenges will greatly enhance operational facility.

Driver, J. M.↗

WE-A-12A-01: Medical Physics 1.0 to 2.0, Session 2: Radiography, Mammography and Fluoroscopy

Medical Physics 2.0 is a bold vision for an existential transition of clinical imaging physics in face of the new realities of value-based and evidencebased medicine, comparative effectiveness, and meaningful use. It speaks to how clinical imaging physics can expand beyond traditional insular models of inspection and acceptance testing, oriented toward compliance, towards team-based models of operational engagement, prospective definition and assurance of effective use, and retrospective evaluation of clinical performance. Organized into four sessions of the AAPM, this particular session focuses on three specific modalities as outlined below. Radiography 2.0: The development of electronic capture in recent years has changed the landscape and spurred reinvestment by healthcare providers. The radiography presentation will explore how the diagnostic medical physicist must adapt to these changes to support radiographic imaging, and how she/he can add value in radiography practice over the next 5-10 years. Topics of discussion include new metrology of evaluation, new models of clinical engagement, and effective integration of new technologies. Mammography 2.0: Mammography has been an interesting testing ground on the effectiveness of close involvement of medical physicists with equipment in the past twenty years. The outcomes have clearly shown major improvements in image quality and significant reduction in the average glandular dose. However, the medical physicist's role in mammography has been largely focused to annual surveys and with limited input on operational issues with image artifacts, optimal mammographic acquisition mode and problems with image quality. This mammography presentation will address why and how medical physicists must be prepared to address the new models of practice that include new metrics of performance and the integration of new technologies (DBT, syncretized mammograms, contrast mammography, breast CT) into clinical practice. Fluoroscopy 2.0: Physics support of fluoroscopy should be operationally as opposed to compliance focused. Testing protocols must address new hardware, acquisition methods, and image processing. Future available tools are discussed. Proper configuration of acquisition parameters (focal spot size, voltage and added filter, tube current, pulse width, pulse rate, scatter removal) as a function of patient size from the neonate to bariatric patient is key to providing diagnostic image quality at properly managed radiation doses. Learning Objectives: Appreciate the limitations of the currently available tools and techniques in clinical medical physics in radiography, mammography, and fluoroscopy, and ways to improve upon current deficiencies. Appreciate the changing environment of imaging practice and the need for the medical physicist to be an expert consultant and educator in a capacity that extends beyond the annual survey of equipment. Understand the status of the rapidly changing environment in breast imaging from planar imaging to tomosynthesis and possibly to breast CT. Identify appropriate configuration of acquisition parameters as a function of patient size to manage radiation dose and ensure diagnostic image quality.

60 APPLIED LIFE SCIENCES↗

SU-E-I-12: Characterization of Edge Effects in a Commercial Low-Dose Image Processing System

Purpose: Minimizing radiation dose while preserving image quality is critical in fluoroscopic imaging. One recent development is a noise reduction system (Allura Clarity) offered by Philips. Others have reported approximately 50% reduction in air kerma when using Clarity. These studies, however, provide only a cursory look at how the Clarity system affects image quality. The purpose of this work was to evaluate the effect of Clarity on the appearance of high-frequency image information. Methods: A lead attenuator with a smooth edge was imaged on two Philips Allura FD20 detectors: one with Clarity and one without. The edge was positioned in the center of the field of view and images were obtained under the following conditions: 40cm and 11cm fields of view, single shot and continuous fluoroscopy modes, and using abdomen and cardiac protocols, for a total of sixteen imaging conditions. Profiles were drawn perpendicular to the edge across 80% of its length, averaged to reduce noise, normalized to the maximum pixel value, and plotted as a function of distance. Results: For all single-shot acquisitions and most fluoroscopic images, overshoot of the edge was observed. This effect was more substantial for single-shot acquisitions (∼20%) than for fluoroscopic images (∼50%). For fluoroscopic acquisition, the overshoot decayed more quickly with the Clarity system. However, the system with Clarity introduced a ringing effect for both single-shot and fluoroscopic images that is not present on the non-Clarity system. Conclusion: Previous reports have demonstrated a substantial dose reduction when using Clarity but the impact this has on image appearance has not been characterized. One demonstrated difference is the change in appearance of high-frequency image information. It remains to be determined whether this effect may impact clinical images adversely.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

TU-EF-204-02: Hiigh Quality and Sub-MSv Cerebral CT Perfusion Imaging

Purpose: CT Perfusion (CTP) imaging is of great importance in acute ischemic stroke management due to its potential to detect hypoperfused yet salvageable tissue and distinguish it from definitely unsalvageable tissue. However, current CTP imaging suffers from poor image quality and high radiation dose (up to 5 mSv). The purpose of this work was to demonstrate that technical innovations such as Prior Image Constrained Compressed Sensing (PICCS) have the potential to address these challenges and achieve high quality and sub-mSv CTP imaging. Methods: (1) A spatial-temporal 4D cascaded system model was developed to indentify the bottlenecks in the current CTP technology; (2) A task-based framework was developed to optimize the CTP system parameters; (3) Guided by (1) and (2), PICCS was customized for the reconstruction of CTP source images. Digital anthropomorphic perfusion phantoms, animal studies, and preliminary human subject studies were used to validate and evaluate the potentials of using these innovations to advance the CTP technology. Results: The 4D cascaded model was validated in both phantom and canine stroke models. Based upon this cascaded model, it has been discovered that, as long as the spatial resolution and noise properties of the 4D source CT images are given, the 3D MTF and NPS of the final CTP maps can be analytically derived for a given set of processing methods and parameters. The cascaded model analysis also identified that the most critical technical factor in CTP is how to acquire and reconstruct high quality source images; it has very little to do with the denoising techniques often used after parametric perfusion calculations. This explained why PICCS resulted in a five-fold dose reduction or substantial improvement in image quality. Conclusion: Technical innovations generated promising results towards achieving high quality and sub-mSv CTP imaging for reliable and safe assessment of acute ischemic strokes. K. Li, K. Niu, Y. Wu: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.

60 APPLIED LIFE SCIENCES↗

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinct from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.

60 APPLIED LIFE SCIENCES↗

CBCT with specification of imaging dose and CNR by anatomical volume of interest

Purpose: A novel method has been developed for volume of interest (VOI) cone-beam CT (CBCT) imaging using a 2.35 MV/Carbon target linac imaging beam line combined with dynamic multileaf collimator sequences. Methods: The authors demonstrate the concept of acquisition of multiple, separate imaging volumes, where volumes can be either completely separated or nested, and are associated with predetermined imaging dose and contrast-to-noise ratio (CNR) characteristics. Two individual MLC sequences were established in the planning system (Eclipse, Varian Medical) to collimate the beam according to a defined inner VOI (e.g., containing a target volume under image guidance) and an outer VOI (e.g., including surrounding landmarks or organs-at-risk). MLC sequences were interleaved as a function of gantry angle to produce a reconstructed CBCT image with nested VOIs. By controlling the ratio of inner-to-outer ratio of MLC segments (and thus Monitor Units) during acquisition, the relative dose and CNR in the two volumes can be controlled. Inner-to-outer ratios of 2:1 to 6:1 were examined. Results: The concept was explored using an anatomical head phantom to assess image quality. A geometric phantom was used to quantify absolute dose and CNR values for the various sequences. The authors found that the dose in the outer VOI decreased by a functional relationship dependent on the inner-to-outer sequence ratio, while the CNR varied by the square root of dose, as expected. Conclusions: In this study the authors demonstrate flexibility in VOI CBCT by tailoring the imaging dose and CNR distribution in separate volumes within the patient anatomy. This would allow for high quality imaging of a target volume for alignment purposes, with simultaneous low dose imaging of the surrounding anatomy (e.g., for coregistration)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Rapid estimation of 4DCT motion-artifact severity based on 1D breathing-surrogate periodicity

Purpose: Motion artifacts are common in patient four-dimensional computed tomography (4DCT) images, leading to an ill-defined tumor volume with large variations for radiotherapy treatment and a poor foundation with low imaging fidelity for studying respiratory motion. The authors developed a method to estimate 4DCT image quality by establishing a correlation between the severity of motion artifacts in 4DCT images and the periodicity of the corresponding 1D respiratory waveform (1DRW) used for phase binning in 4DCT reconstruction. Methods: Discrete Fourier transformation (DFT) was applied to analyze 1DRW periodicity. The breathing periodicity index (BPI) was defined as the sum of the largest five Fourier coefficients, ranging from 0 to 1. Distortional motion artifacts (excluding blurring) of cine-scan 4DCT at the junctions of adjacent couch positions around the diaphragm were classified in three categories: incomplete, overlapping, and duplicate anatomies. To quantify these artifacts, discontinuity of the diaphragm at the junctions was measured in distance and averaged along six directions in three orthogonal views. Artifacts per junction (APJ) across the entire diaphragm were calculated in each breathing phase and phase-averaged APJ{sup ¯}, defined as motion-artifact severity (MAS), was obtained for each patient. To make MAS independent of patient-specific motion amplitude, two new MAS quantities were defined: MAS{sup D} is normalized to the maximum diaphragmatic displacement and MAS{sup V} is normalized to the mean diaphragmatic velocity (the breathing period was obtained from DFT analysis of 1DRW). Twenty-six patients’ free-breathing 4DCT images and corresponding 1DRW data were studied. Results: Higher APJ values were found around midventilation and full inhalation while the lowest APJ values were around full exhalation. The distribution of MAS is close to Poisson distribution with a mean of 2.2 mm. The BPI among the 26 patients was calculated with a value ranging from 0.25 to 0.93. The DFT calculation was within 3 s per 1DRW. Correlations were found between 1DRW periodicity and 4DCT artifact severity: −0.71 for MAS{sup D} and −0.73 for MAS{sup V}. A BPI greater than 0.85 in a 1DRW suggests minimal motion artifacts in the corresponding 4DCT images. Conclusions: The breathing periodicity index and motion-artifact severity index are introduced to assess the relationship between 1DRW and 4DCT. A correlation between 1DRW periodicity and 4DCT artifact severity has been established. The 1DRW periodicity provides a rapid means to estimate 4DCT image quality. The rapid 1DRW analysis and the correlative relationship can be applied prospectively to identify irregular breathers as candidates for breath coaching prior to 4DCT scan and retrospectively to select high-quality 4DCT images for clinical motion-management research.

60 APPLIED LIFE SCIENCES↗

Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT

Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold speed-up of the processing (from 1336 to 150 s). Conclusions: Adaptive anisotropic filtering has the potential to substantially improve image quality and/or reduce the radiation dose required for obtaining 3D image data using cone beam CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Application of LANDSAT-2 data to the implementation and enforcement of the Pennsylvania Surface Mining Conservation and Reclamation Act

The author has identified the following significant results. Evaluation of LANDSAT imagery indicates severe limitations in its utility for surface mine land studies. Image stripping resulting from unequal detector response on satellite degrades the image quality to the extent that images of scales larger than 1:125,000 are of limited value for manual interpretation. Computer processing of LANDSAT data to improve image quality is essential; the removal of scanline stripping and enhancement of mine land reflectance data combined with color composite printing permits useful photographic enlargements to approximately 1:60,000.

Russell, O. R.↗

Bowtie filters for dedicated breast CT: Theory and computational implementation

Purpose: To design bowtie filters with improved properties for dedicated breast CT to improve image quality and reduce dose to the patient. Methods: The authors present three different bowtie filters designed for a cylindrical 14-cm diameter phantom with a uniform composition of 40/60 breast tissue, which vary in their design objectives and performance improvements. Bowtie design #1 is based on single material spectral matching and produces nearly uniform spectral shape for radiation incident upon the detector. Bowtie design #2 uses the idea of basis material decomposition to produce the same spectral shape and intensity at the detector, using two different materials. Bowtie design #3 eliminates the beam hardening effect in the reconstructed image by adjusting the bowtie filter thickness so that the effective attenuation coefficient for every ray is the same. All three designs are obtained using analytical computational methods and linear attenuation coefficients. Thus, the designs do not take into account the effects of scatter. The authors considered this to be a reasonable approach to the filter design problem since the use of Monte Carlo methods would have been computationally intensive. The filter profiles for a cone-angle of 0° were used for the entire length of each filter because the differences between those profiles and the correct cone-beam profiles for the cone angles in our system are very small, and the constant profiles allowed construction of the filters with the facilities available to us. For evaluation of the filters, we used Monte Carlo simulation techniques and the full cone-beam geometry. Images were generated with and without each bowtie filter to analyze the effect on dose distribution, noise uniformity, and contrast-to-noise ratio (CNR) homogeneity. Line profiles through the reconstructed images generated from the simulated projection images were also used as validation for the filter designs. Results: Examples of the three designs are presented. Initial verification of performance of the designs was done using analytical computations of HVL, intensity, and effective attenuation coefficient behind the phantom as a function of fan-angle with a cone-angle of 0°. The performance of the designs depends only weakly on incident spectrum and tissue composition. For all designs, the dynamic range requirement on the detector was reduced compared to the no-bowtie-filter case. Further verification of the filter designs was achieved through analysis of reconstructed images from simulations. Simulation data also showed that the use of our bowtie filters can reduce peripheral dose to the breast by 61% and provide uniform noise and CNR distributions. The bowtie filter design concepts validated in this work were then used to create a computational realization of a 3D anthropomorphic bowtie filter capable of achieving a constant effective attenuation coefficient behind the entire field-of-view of an anthropomorphic breast phantom. Conclusions: Three different bowtie filter designs that vary in performance improvements were described and evaluated using computational and simulation techniques. Results indicate that the designs are robust against variations in breast diameter, breast composition, and tube voltage, and that the use of these filters can reduce patient dose and improve image quality compared to the no-bowtie-filter case.

60 APPLIED LIFE SCIENCES↗