Darin Okerlund

Effective atomic number accuracy for kidney stone characterization using spectral CT

The clinical application of Gemstone Spectral ImagingTM, a fast kV switching dual energy acquisition, is explored in the context of noninvasive kidney stone characterization. Utilizing projection-based material decomposition, effective atomic number and monochromatic images are generated for kidney stone characterization. Analytical and experimental measurements are reported and contrasted. Phantoms were constructed using stone specimens extracted from patients. This allowed for imaging of the different stone types under similar conditions. The stone specimens comprised of Uric Acid, Cystine, Struvite and Calcium-based compositions. Collectively, these stone types span an effective atomic number range of approximately 7 to 14. While Uric Acid and Calcium based stones are generally distinguishable in conventional CT, stone compositions like Cystine and Struvite are difficult to distinguish resulting in treatment uncertainty. Experimental phantom measurements, made under increasingly complex imaging conditions, illustrate the impact of various factors on measurement accuracy. Preliminary clinical studies are reported.

Automated liver lesion characterization using fast kVp switching dual energy computed tomography imaging

Hypodense metastases are not always completely distinguishable from benign cysts in the liver using conventional Computed Tomography (CT) imaging, since the two lesion types present with overlapping intensity distributions due to similar composition as well as other factors including beam hardening and patient motion. This problem is extremely challenging for small lesions with diameter less than 1 cm. To accurately characterize such lesions, multiple follow-up CT scans or additional Positron Emission Tomography or Magnetic Resonance Imaging exam are often conducted, and in some cases a biopsy may be required after the initial CT finding. Gemstone Spectral Imaging (GSI) with fast kVp switching enables projection-based material decomposition, offering the opportunity to discriminate tissue types based on their energy-sensitive material attenuation and density. GSI can be used to obtain monochromatic images where beam hardening is reduced or eliminated and the images come inherently pre-registered due to the fast kVp switching acquisition. We present a supervised learning method for discriminating between cysts and hypodense liver metastases using these monochromatic images. Intensity-based statistical features extracted from voxels inside the lesion are used to train optimal linear and nonlinear classifiers. Our algorithm only requires a region of interest within the lesion in order to compute relevant features and perform classification, thus eliminating the need for an accurate segmentation of the lesion. We report classifier performance using M-fold cross-validation on a large lesion database with radiologist-provided lesion location and labels as the reference standard. Our results demonstrate that (a) classification using a single projection-based spectral CT image, i.e., a monochromatic image at a specified keV, outperforms classification using an image-based dual energy CT pair, i.e., low and high kVp images derived from the same fast kVp acquisition and (b) classification using monochromatic images can achieve very high accuracy in separating benign liver cysts and metastases, especially for small lesions.

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

PURPOSE Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. METHODS An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three readers using a five point Likert scale. RESULTS There was no statistically significant difference between inter-reader and reader-algorithm agreement for either MAD or CCC metrics (p > 0.1). The algorithm phase was within 2% of the consensus phase in 15/21 of cases. The average absolute difference between consensus and algorithm best phases was 2.29% ± 2.47%, with a maximum difference of 8%. Average image quality scores for the algorithm chosen best phase were 4.01 ± 0.65 overall, 3.33 ± 1.27 for right coronary artery (RCA), 4.50 ± 0.35 for left anterior descending (LAD) artery, and 4.50 ± 0.35 for left circumflex artery (LCX). Average image quality scores for the consensus best phase were 4.11 ± 0.54 overall, 3.44 ± 1.03 for RCA, 4.39 ± 0.39 for LAD, and 4.50 ± 0.18 for LCX. There was no statistically significant difference (p > 0.1) between the image quality scores of the algorithm phase and the consensus phase. CONCLUSIONS The proposed algorithm was statistically equivalent to a reader in selecting an optimal cardiac phase for CCTA exams. When reader and algorithm phases differed by >2%, image quality as rated by blinded readers was statistically equivalent. By detecting the optimal phase for CCTA reconstruction, the proposed algorithm is expected to improve coronary artery visualization in CCTA exams.

Initial Evaluation of Virtual Un-Enhanced Imaging derived from Fast kVp- Switching Dual Energy Contrast Enhanced CT for the Abdomen

The feasibility and utility of creating virtual un-enhanced images from contrast enhanced data acquired using a fast switching dual energy CT acquisition, is explored. Utilizing projection based material decomposition data, monochromatic images are generated and a Multi-material decomposition technique is applied. Quantitative and qualitative evaluation is performed to assess the equivalence of Virtual Un-Enhanced (VUE) and True Un-enhanced (TUE) for multiple tissue types and different organs in the abdomen. Ten patient cases were analyzed where a TUE and a subsequent Contrast Enhanced (CE) acquisition were obtained using fast kVp-switching dual energy CT utilizing Gemstone Spectral Imaging. Quantitative measurements were made by placing multiple Regions of Interest on the different tissues and organs in both the TUE and the VUE images. The absolute Hounsfield Unit (HU) differences in the mean values between TUE & VUE were calculated as well as the differences of the standard deviations. Qualitative analysis was done by two radiologists for overall image quality, presence of residual contrast, appearance of pathology, appearance and contrast of normal tissues and organs in comparison to the TUE. There is a very strong correlation between the TUE and VUE images.

Liver fat quantification using fast kVp-switching dual energy CT

Nonalcoholic steatohepatitis (NASH) is a liver disease that occurs in patients that lack a history of the well-proven association of alcohol use. A major symptom of NASH is increased fat deposition in the liver. Gemstone Spectral Imaging (GSI) with fast kVp-switching enables projection-based material decomposition, offering the opportunity to accurately characterize tissue types, e.g., fat and healthy liver tissue, based on their energy-sensitive material attenuation and density. We describe our pilot efforts to apply GSI to locate and quantify the amount of fat deposition in the liver. Two approaches are presented, one that computes percentage fat from the difference in HU values at high and low energies and the second based on directly computing fat volume fraction at each voxel using multi-material decomposition. Simulation software was used to create a phantom with a set of concentric rings, each composed of fat and soft tissue in different relative amounts with attenuation values obtained from the National Institute of Standards and Technology. Monte Carlo 80 and 140 kVp X-ray projections were acquired and CT images of the phantom were reconstructed. Results demonstrated the sensitivity of dual energy CT to the presence of fat and its ability to distinguish fat from soft tissue. Additionally, actual patient (liver) datasets were acquired using GSI and monochromatic images at 70 and 140 keV were reconstructed. Preliminary results demonstrate a tissue sensitivity that appears sufficient to quantify fat content with a degree of accuracy as may be needed for non-invasive clinical assessment of NASH.

Cardiac imaging in diagnostic VCT using multi-sector data acquisition and image reconstruction: step-and-shoot scan vs. helical scan

Since the advent of multi-slice CT, helical scan has played an increasingly important role in cardiac imaging. With the availability of diagnostic volumetric CT, step-and-shoot scan has been becoming popular recently. Step-and-shoot scan decouples patient table motion from heart beating, and thus the temporal window for data acquisition and image reconstruction can be optimized, resulting in significantly reduced radiation dose, improved tolerance to heart beat rate variation and inter-cycle cardiac motion inconsistency. Multi-sector data acquisition and image reconstruction have been utilized in helical cardiac imaging to improve temporal resolution, but suffers from the coupling of heart beating and patient table motion. Recognizing the clinical demands, the multi-sector data acquisition scheme for step-and-shoot scan is investigated in this paper. The most outstanding feature of the multi-sector data acquisition combined with the stepand- shoot scan is the decoupling of patient table proceeding from heart beating, which offers the opportunities of employing prospective ECG-gating to improve dose efficiency and fine adjusting cardiac imaging phase to suppress artifacts caused by inter-cycle cardiac motion inconsistency. The improvement in temporal resolution and the resultant suppression of motion artifacts are evaluated via motion phantoms driven by artificial ECG signals. Both theoretical analysis and experimental evaluation show promising results for multi-sector data acquisition scheme to be employed with the step-and-shoot scan. With the ever-increasing gantry rotation speed and detector longitudinal coverage in stateof- the-art VCT scanners, it is expected that the step-and-shoot scan with multi-sector data acquisition scheme would play an increasingly important role in cardiac imaging using diagnostic VCT scanners.

Task based assessment of a motion compensation algorithm via simulation of a moving stenotic vessel

An analysis of a task based simulation study of coronary artery imaging via computed tomography (CT). Evaluation of standard filtered backprojection (FBP) reconstruction and motion compensated reconstruction of a moving cylindrical vessel that contains a hyper-intense lesion. Multiple conditions are simulated including: varying rest times of the vessel and varying motion orientations. A reference image with no motion was used for all comparisons. The images were segmented and quantitative metrics for accurate segmentation were compared. The motion compensated images have consistent error metrics with respect to the static case for all rest times. The FBP reconstructions were visually inferior for shorter rest times and had significantly inferior metrics. This is the first demonstration of equivalent performance for a given task when the rest times are reduced well below the temporal aperture of the acquisition, using either advanced algorithms or different data acquisition such as multi-source geometries.

Cardiac imaging with multi-sector data acquisition in volumetric CT: variation of effective temporal resolution and its potential clinical consequences

With increasing longitudinal detector dimension available in diagnostic volumetric CT, step-and-shoot scan is becoming popular for cardiac imaging. In comparison to helical scan, step-and-shoot scan decouples patient table movement from cardiac gating/triggering, which facilitates the cardiac imaging via multi-sector data acquisition, as well as the administration of inter-cycle heart beat variation (arrhythmia) and radiation dose efficiency. Ideally, a multi-sector data acquisition can improve temporal resolution at a factor the same as the number of sectors (best scenario). In reality, however, the effective temporal resolution is jointly determined by gantry rotation speed and patient heart beat rate, which may significantly lower than the ideal or no improvement (worst scenario). Hence, it is clinically relevant to investigate the behavior of effective temporal resolution in cardiac imaging with multi-sector data acquisition. In this study, a 5-second cine scan of a porcine heart, which cascades 6 porcine cardiac cycles, is acquired. In addition to theoretical analysis and motion phantom study, the clinical consequences due to the effective temporal resolution variation are evaluated qualitative or quantitatively. By employing a 2-sector image reconstruction strategy, a total of 15 (the permutation of P(6, 2)) cases between the best and worst scenarios are studied, providing informative guidance for the design and optimization of CT cardiac imaging in volumetric CT with multi-sector data acquisition.

Quantitative image quality evaluation for cardiac CT reconstructions

Maintaining image quality in the presence of motion is always desirable and challenging in clinical Cardiac CT imaging. Different image-reconstruction algorithms are available on current commercial CT systems that attempt to achieve this goal. It is widely accepted that image-quality assessment should be task-based and involve specific tasks, observers, and associated figures of merits. In this work, we developed an observer model that performed the task of estimating the percentage of plaque in a vessel from CT images. We compared task performance of Cardiac CT image data reconstructed using a conventional FBP reconstruction algorithm and the SnapShot Freeze (SSF) algorithm, each at default and optimal reconstruction cardiac phases. The purpose of this work is to design an approach for quantitative image-quality evaluation of temporal resolution for Cardiac CT systems. To simulate heart motion, a moving coronary type phantom synchronized with an ECG signal was used. Three different percentage plaques embedded in a 3 mm vessel phantom were imaged multiple times under motion free, 60 bpm, and 80 bpm heart rates. Static (motion free) images of this phantom were taken as reference images for image template generation. Independent ROIs from the 60 bpm and 80 bpm images were generated by vessel tracking. The observer performed estimation tasks using these ROIs. Ensemble mean square error (EMSE) was used as the figure of merit. Results suggest that the quality of SSF images is superior to the quality of FBP images in higher heart-rate scans.

CT spectral projection imaging

Dual energy x-ray computed tomography (DECT) has gained a significant attention in recent years. The technology offers the potential to differentiate different materials, and therefore provides the possibility of identifying different pathologies. In this paper, we present a dual-energy projection imaging technique by utilizing the scout data acquisition mode of CT in conjunction with the fast-kVp switching capability. Phantom experiments have shown its advantage in removing overlapping structures and improves the visualization of small structure inside the body.