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TU-G-BRA-02: Can We Extract Lung Function Directly From 4D-CT Without Deformable Image Registration?

Purpose: Dynamic CT ventilation imaging (CT-VI) visualizes air volume changes in the lung by evaluating breathing-induced lung motion using deformable image registration (DIR). Dynamic CT-VI could enable functionally adaptive lung cancer radiation therapy, but its sensitivity to DIR parameters poses challenges for validation. We hypothesize that a direct metric using CT parameters derived from Hounsfield units (HU) alone can provide similar ventilation images without DIR. We compare the accuracy of Direct and Dynamic CT-VIs versus positron emission tomography (PET) images of inhaled {sup 68}Ga-labelled nanoparticles (‘Galligas’). Methods: 25 patients with lung cancer underwent Galligas 4D-PET/CT scans prior to radiation therapy. For each patient we produced three CT- VIs. (i) Our novel method, Direct CT-VI, models blood-gas exchange as the product of air and tissue density at each lung voxel based on time-averaged 4D-CT HU values. Dynamic CT-VIs were produced by evaluating: (ii) regional HU changes, and (iii) regional volume changes between the exhale and inhale 4D-CT phase images using a validated B-spline DIR method. We assessed the accuracy of each CT-VI by computing the voxel-wise Spearman correlation with free-breathing Galligas PET, and also performed a visual analysis. Results: Surprisingly, Direct CT-VIs exhibited better global correlation with Galligas PET than either of the dynamic CT-VIs. The (mean ± SD) correlations were (0.55 ± 0.16), (0.41 ± 0.22) and (0.29 ± 0.27) for Direct, Dynamic HU-based and Dynamic volume-based CT-VIs respectively. Visual comparison of Direct CT-VI to PET demonstrated similarity for emphysema defects and ventral-to-dorsal gradients, but inability to identify decreased ventilation distal to tumor-obstruction. Conclusion: Our data supports the hypothesis that Direct CT-VIs are as accurate as Dynamic CT-VIs in terms of global correlation with Galligas PET. Visual analysis, however, demonstrated that different CT-VI algorithms might have varying accuracy depending on the underlying cause of ventilation abnormality. This research was supported by a National Health and Medical Research Council (NHMRC) Australia Fellowship, an Cancer Institute New South Wales Early Career Fellowship 13-ECF-1/15 and NHMRC scholarship APP1038399. No commercial funding was received for this work.

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TU-G-BRA-03: Predicting Radiation Therapy Induced Ventilation Changes Using 4DCT Jacobian Calculations

Purpose: Longitudinal changes in lung ventilation following radiation therapy can be mapped using four-dimensional computed tomography(4DCT) and image registration. This study aimed to predict ventilation changes caused by radiation therapy(RT) as a function of pre-RT ventilation and delivered dose. Methods: 4DCT images were acquired before and 3 months after radiation therapy for 13 subjects. Jacobian ventilation maps were calculated from the 4DCT images, warped to a common coordinate system, and a Jacobian ratio map was computed voxel-by-voxel as the ratio of post-RT to pre-RT Jacobian calculations. A leave-one-out method was used to build a response model for each subject: post-RT to pre-RT Jacobian ratio data and dose distributions of 12 subjects were applied to the subject’s pre-RT Jacobian map to predict the post-RT Jacobian. The predicted Jacobian map was compared to the actual post-RT Jacobian map to evaluate efficacy. Within this cohort, 8 subjects had repeat pre-RT scans that were compared as a reference for no ventilation change. Maps were compared using gamma pass rate criteria of 2mm distance-to-agreement and 6% ventilation difference. Gamma pass rates were compared using paired t-tests to determine significant differences. Further analysis masked non-radiation induced changes by excluding voxels below specified dose thresholds. Results: Visual inspection demonstrates the predicted post-RT ventilation map is similar to the actual map in magnitude and distribution. Quantitatively, the percentage of voxels in agreement when excluding voxels receiving below specified doses are: 74%/20Gy, 73%/10Gy, 73%/5Gy, and 71%/0Gy. By comparison, repeat scans produced 73% of voxels within the 6%/2mm criteria. The agreement of the actual post-RT maps with the predicted maps was significantly better than agreement with pre-RT maps (p<0.02). Conclusion: This work validates that significant changes to ventilation post-RT can be predicted. The differences between the predicted and actual outcome are similar to differences between repeat scans with equivalent ventilation. This work was supported by NIH grant CA166703 and a Pilot Grant from University of Iowa Carver College of Medicine.

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TU-G-BRA-04: Changes in Regional Lung Function Measured by 4D-CT Ventilation Imaging for Thoracic Radiotherapy

Purpose: To test the hypothesis: 4D-CT ventilation imaging can show the known effects of radiotherapy on lung function: (1) radiation-induced ventilation reductions, and (2) ventilation increases caused by tumor regression. Methods: Repeat 4D-CT scans (pre-, mid- and/or post-treatment) were acquired prospectively for 11 thoracic cancer patients in an IRB-approved clinical trial. A ventilation image for each time point was created using deformable image registration and the Hounsfield unit (HU)-based or Jacobian-based metric. The 11 patients were divided into two subgroups based on tumor volume reduction using a threshold of 5 cm{sup 3}. To quantify radiation-induced ventilation reduction, six patients who showed a small tumor volume reduction (<5 cm{sup 3}) were analyzed for dose-response relationships. To investigate ventilation increase caused by tumor regression, two of the other five patients were analyzed to compare ventilation changes in the lung lobes affected and unaffected by the tumor. The remaining three patients were excluded because there were no unaffected lobes. Results: Dose-dependent reductions of HU-based ventilation were observed in a majority of the patient-specific dose-response curves and in the population-based dose-response curve, whereas no clear relationship was seen for Jacobian-based ventilation. The post-treatment population-based dose-response curve of HU-based ventilation demonstrated the average ventilation reductions of 20.9±7.0% at 35–40 Gy (equivalent dose in 2-Gy fractions, EQD2), and 40.6±22.9% at 75–80 Gy EQD2. Remarkable ventilation increases in the affected lobes were observed for the two patients who showed an average tumor volume reduction of 37.1 cm{sup 3} and re-opening airways. The mid-treatment increase in HU-based ventilation of patient 3 was 100.4% in the affected lobes, which was considerably greater than 7.8% in the unaffected lobes. Conclusion: This study has demonstrated that 4D-CT ventilation imaging shows the known effects of radiotherapy on lung function: radiation-induced ventilation reduction and ventilation increase caused by tumor regression, providing validation for 4D-CT ventilation imaging. This study was supported in part by a National Lung Cancer Partnership Young Investigator Research grant.

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TU-G-204-04: A Unified Strategy for Bi-Factorial Optimization of Radiation Dose and Contrast Dose in CT Imaging

Purpose: To substantiate the interdependency of contrast dose, radiation dose, and image quality in CT towards the patient- specific optimization of the imaging protocols Methods: The study deployed two phantom platforms. A variable sized (12, 18, 23, 30, 37 cm) phantom (Mercury-3.0) containing an iodinated insert (8.5 mgI/ml) was imaged on a representative CT scanner at multiple CTDI values (0.7–22.6 mGy). The contrast and noise were measured from the reconstructed images for each phantom diameter. Linearly related to iodine-concentration, contrast-to-noise ratio (CNR), were calculated for 16 iodine-concentration levels (0–8.5 mgI/ml). The analysis was extended to a recently developed suit of 58 virtual human models (5D XCAT) with added contrast dynamics. Emulating a contrast-enhanced abdominal image procedure and targeting a peak-enhancement in aorta, each XCAT phantom was “imaged” using a simulation platform (CatSim, GE). 3D surfaces for each patient/size established the relationship between iodine-concentration, dose, and CNR. The ratios of change in iodine-concentration versus dose (IDR) to yield a constant change in CNR were calculated for each patient size. Results: Mercury phantom results show the image-quality size- dependence on CTDI and IC levels. For desired image-quality values, the iso-contour-lines reflect the trade off between contrast-material and radiation doses. For a fixed iodine-concentration (4 mgI/mL), the IDR values for low (1.4 mGy) and high (11.5 mGy) dose levels were 1.02, 1.07, 1.19, 1.65, 1.54, and 3.14, 3.12, 3.52, 3.76, 4.06, respectively across five sizes. The simulation data from XCAT models confirmed the empirical results from Mercury phantom. Conclusion: The iodine-concentration, image quality, and radiation dose are interdependent. The understanding of the relationships between iodine-concentration, image quality, and radiation dose will allow for a more comprehensive optimization of CT imaging devices and techniques, providing the methodology to balance iodine-concentration and dose based on patient’s attributes.

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TU-G-204-06: Correlation Between Texture Analysis-Based Model Observer and Human Observer in Diagnosis of Ischemic Infarct in Non-Contrast Head CT of Adults

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIs over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast, subtle texture changes in addition to human observers.

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TU-G-204-09: The Effects of Reduced- Dose Lung Cancer Screening CT On Lung Nodule Detection Using a CAD Algorithm

Purpose: While Lung Cancer Screening CT is being performed at low doses, the purpose of this study was to investigate the effects of further reducing dose on the performance of a CAD nodule-detection algorithm. Methods: We selected 50 cases from our local database of National Lung Screening Trial (NLST) patients for which we had both the image series and the raw CT data from the original scans. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. 10 of the cases had at least one nodule reported on the NLST reader forms. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, the CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST reports. Subject-level mean sensitivities and false-positive rates were calculated for each dose level. Results: The mean sensitivities of the CAD algorithm were 35% at the original dose, 20% at 50% dose, and 42.5% at 25% dose. The false-positive rates, in decreasing-dose order, were 3.7, 2.9, and 10 per case. In certain cases, particularly in larger patients, there were severe photon-starvation artifacts, especially in the apical region due to the high-attenuating shoulders. Conclusion: The detection task was challenging for the CAD algorithm at all dose levels, including the original NLST dose. However, the false-positive rate at 25% dose approximately tripled, suggesting a loss of CAD robustness somewhere between 0.5 and 1.0 mGy. NCI grant U01 CA181156 (Quantitative Imaging Network); Tobacco Related Disease Research Project grant 22RT-0131.

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TU-G-207-00: Emerging Applications of X-Ray Imaging

Last few years has witnessed the development of novel of X-ray imaging modalities, such as spectral CT, phase contrast CT, and X-ray acoustic/fluorescence/luminescence imaging. This symposium will present the recent advances of these emerging X-ray imaging modalities and update the attendees with knowledge in various related topics, including X-ray photon-counting detectors, X-ray physics underlying the emerging applications beyond the traditional X-ray imaging, image reconstruction for the novel modalities, characterization and evaluation of the systems, and their practical implications. In addition, the concept and practical aspects of X-ray activatable targeted nanoparticles for molecular X-ray imaging will be discussed in the context of X-ray fluorescence and luminescence CT. Learning Objectives: Present background knowledge of various emerging X-ray imaging techniques, such as spectral CT, phase contrast CT and X-ray fluorescence/luminescence CT. Discuss the practical need, technical aspects and current status of the emerging X-ray imaging modalities. Describe utility and future impact of the new generation of X-ray imaging applications.

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TU-G-207-01: CT Imaging Using Energy-Sensitive Photon-Counting Detectors

Last few years has witnessed the development of novel of X-ray imaging modalities, such as spectral CT, phase contrast CT, and X-ray acoustic/fluorescence/luminescence imaging. This symposium will present the recent advances of these emerging X-ray imaging modalities and update the attendees with knowledge in various related topics, including X-ray photon-counting detectors, X-ray physics underlying the emerging applications beyond the traditional X-ray imaging, image reconstruction for the novel modalities, characterization and evaluation of the systems, and their practical implications. In addition, the concept and practical aspects of X-ray activatable targeted nanoparticles for molecular X-ray imaging will be discussed in the context of X-ray fluorescence and luminescence CT. Learning Objectives: Present background knowledge of various emerging X-ray imaging techniques, such as spectral CT, phase contrast CT and X-ray fluorescence/luminescence CT. Discuss the practical need, technical aspects and current status of the emerging X-ray imaging modalities. Describe utility and future impact of the new generation of X-ray imaging applications.

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TU-G-207-02: Clinical Applications of X-Ray Phase Contrast Imaging: Where Do We Stand?

Last few years has witnessed the development of novel of X-ray imaging modalities, such as spectral CT, phase contrast CT, and X-ray acoustic/fluorescence/luminescence imaging. This symposium will present the recent advances of these emerging X-ray imaging modalities and update the attendees with knowledge in various related topics, including X-ray photon-counting detectors, X-ray physics underlying the emerging applications beyond the traditional X-ray imaging, image reconstruction for the novel modalities, characterization and evaluation of the systems, and their practical implications. In addition, the concept and practical aspects of X-ray activatable targeted nanoparticles for molecular X-ray imaging will be discussed in the context of X-ray fluorescence and luminescence CT. Learning Objectives: Present background knowledge of various emerging X-ray imaging techniques, such as spectral CT, phase contrast CT and X-ray fluorescence/luminescence CT. Discuss the practical need, technical aspects and current status of the emerging X-ray imaging modalities. Describe utility and future impact of the new generation of X-ray imaging applications.

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TU-G-207-03: High Spatial Resolution and High Sensitivity X-Ray Fluorescence Imaging

Last few years has witnessed the development of novel of X-ray imaging modalities, such as spectral CT, phase contrast CT, and X-ray acoustic/fluorescence/luminescence imaging. This symposium will present the recent advances of these emerging X-ray imaging modalities and update the attendees with knowledge in various related topics, including X-ray photon-counting detectors, X-ray physics underlying the emerging applications beyond the traditional X-ray imaging, image reconstruction for the novel modalities, characterization and evaluation of the systems, and their practical implications. In addition, the concept and practical aspects of X-ray activatable targeted nanoparticles for molecular X-ray imaging will be discussed in the context of X-ray fluorescence and luminescence CT. Learning Objectives: Present background knowledge of various emerging X-ray imaging techniques, such as spectral CT, phase contrast CT and X-ray fluorescence/luminescence CT. Discuss the practical need, technical aspects and current status of the emerging X-ray imaging modalities. Describe utility and future impact of the new generation of X-ray imaging applications.

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TU-F-CAMPUS-J-04: Setup Uncertainties in the Mediastinum Area for IMRT Treatment of Lymphoma Patients

Purpose: Despite daily image guidance setup uncertainties can be high when treating large areas of the body. The aim of this study was to measure local uncertainties inside the PTV for patients receiving IMRT to the mediastinum region. Methods: Eleven lymphoma patients that received radiotherapy (breath-hold) to the mediastinum were included in this study. The treated region could range all the way from the neck to the diaphragm. Each patient had a CT scan with a CT-on-rails system prior to every treatment. The entire PTV region was matched to the planning CT using automatic rigid registration. The PTV was then split into 5 regions: neck, supraclavicular, superior mediastinum, upper heart, lower heart. Additional auto-registrations for each of the 5 local PTV regions were performed. The residual local setup errors were calculated as the difference between the final global PTV position and the individual final local PTV positions for the AP, SI and RL directions. For each patient 4 CT scans were analyzed (1 per week of treatment). Results: The residual mean group error (M) and standard deviation of the inter-patient (or systematic) error (Σ) were lowest in the RL direction of the superior mediastinum (0.0mm and 0.5mm) and highest in the RL direction of the lower heart (3.5mm and 2.9mm). The standard deviation of the inter-fraction (or random) error (σ) was lowest in the RL direction of the superior mediastinum (0.5mm) and highest in the SI direction of the lower heart (3.9mm) The directionality of local uncertainties is important; a superior residual error in the lower heart for example keeps it in the global PTV. Conclusion: There is a complex relationship between breath-holding and positioning uncertainties that needs further investigation. Residual setup uncertainties can be significant even under daily CT image guidance when treating large regions of the body.

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TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images), image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.

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TU-F-CAMPUS-I-03: Preliminary Study of Size-Specific Dose Estimates in Adult Abdomenal CT Examinations in Taiwan

Purpose: This study was to investigate size-specific dose estimates (SSDE) for routine adult abdominal CT examinations in Taiwan. Methods: A national survey was conducted in Taiwan in 2014 to investigate SSDEs for routine adult abdominal CT examinations. The hospitals involved in this study provided CT images of their typical patients. The CT image in the level of the middle liver was selected to record the corresponding tube current, slice mAs or effective mAs. The image was also used to estimate the dimensions of patient as measuring the lengths in the anterior to posterior (AP) and lateral (LAT) directions. The effective diameter was then calculated from AP and LAT, and used to look up conversion factors in the AAPM 204 report. The volume CTDI (CTDIvol) for each CT unit was measured on sites using a 32-cm cylindrical standard dose phantom and a calibrated pencil-type ionization chamber. Individual patient’s SSDEs were then calculated from the corresponding SSDE conversion factor and the CTDIvol. Results: The study cohort included 111 CT units. The ratio of turning on automatic tube current modulation (ATCM) or not is 88:23. Effective diameters are 258.7±25.1 mm (167–366 mm). 99.3% of typical patients selected by each hospital have smaller effective diameter than the 32-cm dosimetry phantom. Adult abdomenal SSDE is 17.5 ± 8.8 mGy (1.9-58 mGy). The SSDE seems to decrease as the effective diameter increases as the ATCM turns off, and independent with the effective diameter as the ATCM turns on. Conclusion: The SSDE for typical patients in Taiwan was investigated. We continue to complete this investigation in 2015 to include more valid data to establish SSDE reference level in Taiwan. This study was financially supported by the Atomic Energy Council in Taiwan.

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TU-F-CAMPUS-I-04: A Novel Phantom to Evaluate Longitudinal and Angular Automatic Tube Current Modulation (ATCM) in CT

Purpose: To manufacture a phantom specifically designed for the purpose of evaluating the performance of the longitudinal and angular automatic tube current modulation (ATCM) on modern CT scanners. Methods: In order to evaluate angular ATCM, the phantom has an elliptical cross section (aspect ratio 3:2). To evaluate longitudinal ATCM, the phantom consists of 3 sections, with different major axes (25 cm, 30 cm and 35 cm). Each section is 15 cm long in the longitudinal direction. Between each section is a smooth transition. The phantom was milled from a solid block of PMMA. ATCM performance is evaluated by 1) analyzing the applied tube current for each slice of the phantom and 2) analyzing the distribution of image noise (σ) along the scan direction at different positions in the phantom. A demonstration of the ATCM performance evaluation is given by investigating the effects of miscentering during a CT scan. Results: The developed phantom has proven useful for evaluating both the longitudinal and angular ATCM on modern CT scanners (spiral collimations ≥ 4 cm). Further benefits are the smooth transitions between the sections that prevent abnormal responses in the ATCM and the invariant sections that provide a means for investigating the stability of image noise. The homogeneity of the phantom makes image noise at different positions along the scan direction easy to quantify, which is crucial to understand how well the applied ATCM can produce a desired image quality. Conclusion: It is important to understand how the ATCM functions on CT scanners as it can directly affect dose and image quality. The phantom that has been developed is a most valuable tool to understand how different variables during a scan can affect the outcome of the longitudinal and angular ATCM.

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TU-F-CAMPUS-I-05: Parameterization of the Noise Power Spectrum in X-Ray Computed Tomography

Purpose: The purpose of this work was to develop a method so that the noise power spectrum (NPS) can be approximated for arbitrary levels of mAs, from a single determination in CT. Methods: The NPS is factorized into 2 components, 1) a parameterized function representing the 1D normalized spatial frequency distribution and 2) a function to scale the magnitude of 1) for arbitrary values of mAs. The 1D NPS, normalized by image variance (NNPS), was determined for 2 FBP reconstruction kernels (smoothing and edge enhancing) for 400 mAs. The NNPS were fit to the parameterized function and a scaling function was established to approximate the image variance at arbitrary values of mAs. Using the root mean square error normalized by the maximum value (NRMSE), the NPS approximated with the factorization method was compared to the NPS determined at 5 different mAs levels. Results: The factorization resulted in a set of 7 coefficients that can be used to approximate the 1D NPS, for arbitrary levels of mAs, for the convolution kernels studied in this work. The approximated NPS (factorization) agreed well with the determined NPS for all mAs levels. The greatest NRMSE was 0.02 and was observed for the edge enhancing kernel. Conclusion: The proposed factorization method has been demonstrated as applicable for FBP reconstruction. It can be used to approximate the 1D NPS for arbitrary levels of mAs, from a single NPS determination. Furthermore, approximations of the 1D NPS can conveniently be distributed since the factorization method only used 7 coefficients in the approximation.

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TU-F-CAMPUS-J-03: Evaluation of a New GE Device-Less Cine 4D-CT

Purpose: Standard cine 4D-CT (S-4DCT) is the cine CT scan of the thorax followed by image sorting with the respiratory signal recorded by the RPM. Although the feasibility of cine 4D-CT without RPM or device-less 4DCT (DL-4DCT) has been reported in a laboratory setting, the only commercial implementation of DL-4DCT was made recently by GE based on the measurements of the lung, body and air area and density. We report the initial results of this new DL-4DCT on its determination of gross tumor volume (GTV). Methods: 30 stereotactic body radiation therapy (SBRT) patients with NSCLC were included in the study. All patients received the S-4DCT for their treatment planning. Their cine CT data without the respiratory signal from RPM were submitted to the DL-4DCT. The DL-4DCT image quality was assessed in reference to S-4DCT. Using maximum intensity projection (MIP) images, the GTVs of the S-4DCT and DL-4DCT were compared on a subset of 9 patients whose tumors in the low density lung regions could be contoured using a region growing algorithm in MIM without contouring bias from the user. A lower threshold of −424 HU was used for all patients and other algorithm parameters were held constant for each patient. Results: The DL-4DCT was able to produce the 4DCT images on 29 out of the 30 SBRT cases. One case failed due to the enhanced calcification surrounding both the breast implants. The GTVs determined on the 9 patients with DL-4DCT were 4.2 ± 4.8% smaller than the GTVs with S-4DCT. However, this was statistically insignificant (p=0.15). The Dice similarity coefficients were 95.1 ± 1.8%. The image quality of DL-4DCT and S-4DCT was similar on the 29 cases. Conclusion: The first commercial DL-4DCT was promising in generating 4D-CT images without a respiratory monitoring device in this preliminary study of 30 patients.

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WE-AB-BRA-01: 3D-2D Image Registration for Target Localization in Spine Surgery: Comparison of Similarity Metrics Against Robustness to Content Mismatch

Purpose: In image-guided spine surgery, mapping 3D preoperative images to 2D intraoperative images via 3D-2D registration can provide valuable assistance in target localization. However, the presence of surgical instrumentation, hardware implants, and soft-tissue resection/displacement causes mismatches in image content, confounding existing registration methods. Manual/semi-automatic methods to mask such extraneous content is time consuming, user-dependent, error prone, and disruptive to clinical workflow. We developed and evaluated 2 novel similarity metrics within a robust registration framework to overcome such challenges in target localization. Methods: An IRB-approved retrospective study in 19 spine surgery patients included 19 preoperative 3D CT images and 50 intraoperative mobile radiographs in cervical, thoracic, and lumbar spine regions. A neuroradiologist provided truth definition of vertebral positions in CT and radiography. 3D-2D registration was performed using the CMA-ES optimizer with 4 gradient-based image similarity metrics: (1) gradient information (GI); (2) gradient correlation (GC); (3) a novel variant referred to as gradient orientation (GO); and (4) a second variant referred to as truncated gradient correlation (TGC). Registration accuracy was evaluated in terms of the projection distance error (PDE) of the vertebral levels. Results: Conventional similarity metrics were susceptible to gross registration error and failure modes associated with the presence of surgical instrumentation: for GI, the median PDE and interquartile range was 33.0±43.6 mm; similarly for GC, PDE = 23.0±92.6 mm respectively. The robust metrics GO and TGC, on the other hand, demonstrated major improvement in PDE (7.6 ±9.4 mm and 8.1± 18.1 mm, respectively) and elimination of gross failure modes. Conclusion: The proposed GO and TGC similarity measures improve registration accuracy and robustness to gross failure in the presence of strong image content mismatch. Such registration capability could offer valuable assistance in target localization without disruption of clinical workflow. G. Kleinszig and S. Vogt are employees of Siemens Healthcare.

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WE-AB-BRA-04: Evaluation of the Tumor Registration Error in Biopsy Procedures Performed Under Real Time PET/CT Guidance

Purpose: PET/CT guidance is used for biopsies of metabolically active lesions, which are not well seen on CT alone or to target the metabolically active tissue in tumor ablations. It has also been shown that PET/CT guided biopsies provide an opportunity to verify the location of the lesion border at the place of needle insertion. However the error in needle placement with respect to the metabolically active region may be affected by motion between the PET/CT scan performed at the start of the procedure and the CT scan performed with the needle in place and this error has not been previously quantified. Methods: Specimens from 31 PET/CT guided biopsies were investigated and correlated to the intraoperative PET scan under an IRB approved HIPAA compliant protocol. For 4 of the cases in which larger motion was suspected a second PET scan was obtained with the needle in place. The CT and the PET images obtained before and after the needle insertion were used to calculate the displacement of the voxels along the needle path. CTpost was registered to CTpre using a free form deformable registration and then fused with PETpre. The shifts between the PET image contours (42% of SUVmax) for PETpre and PETpost were obtained at the needle position. Results: For these extreme cases the displacement of the CT voxels along the needle path ranged from 2.9 to 8 mm with a mean of 5 mm. The shift of the PET image segmentation contours (42% of SUVmax) at the needle position ranged from 2.3 to 7 mm between the two scans. Conclusion: Evaluation of the mis-registration between the CT with the needle in place and the pre-biopsy PET can be obtained using deformable registration of the respective CT scans and can be used to indicate the need of a second PET in real-time. This work is supported in part by a grant from Biospace Lab, S.A.

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