Body Height Estimation from Femur Measurements in Postmortem Computed Tomography

After attending this presentation, attendees will: (1) understand how body height from computed tomography data can be estimated; and, (2) gain knowledge about the accuracy of estimated body height and limitations. The presentation will impact the forensic science community by providing knowledge and competence which will enable attendees to develop formulas for single bones to reconstruct body height using postmortem Computer Tomography (p-CT) data. The estimation of Body Height (BH) is an important component of the identification of corpses and skeletal remains. Stature can be estimated with relative accuracy via the measurement of long bones, such as the femora. Compared to time-consuming maceration procedures, p-CT allows fast and simple measurements of bones. This study undertook four objectives concerning the accuracy of BH estimation via p-CT: (1) accuracy between measurements on native bone and p-CT imaged bone (F1 according to Martin 1914); (2) intra-observer p-CT measurement precision; (3) accuracy between formula-based estimation of the BH and conventional body length measurement during autopsy; and, (4) accuracy of different estimation formulas available.1 In the first step, the accuracy of measurements in the CT compared to those obtained using an osteometric board was evaluated on the basis of eight defleshed femora. Then the femora of 83 female and 144 male corpses of a Swiss population for which p-CTs had been performed, were measured at the Institute of Forensic Medicine in Bern. After two months, 20 individuals were measured again in order to assess the intraobserver error. The mean age of the men was 53±17 years and that of the women was 61±20 years. Additionally, the body length of the corpses was measured conventionally. The mean body length was 176.6±7.2cm for men and 163.6±7.8cm for women. The images that were obtained using a six-slice CT were reconstructed with a slice thickness of 1.25mm. Analysis and measurements of CT images were performed on a multipurpose workstation. As a forensic standard procedure, stature was estimated by means of the regression equations by Penning & Riepert developed on a Southern German population and for comparison, also those referenced by Trotter & Gleser “American White.”2,3 All statistical tests were performed with a statistical software. No significant differences were found between the CT and osteometric board measurements. The double p-CT measurement of 20 individuals resulted in an absolute intra-observer difference of 0.4±0.3mm. For both sexes, the correlation between the body length and the estimated BH using the F1 measurements was highly significant. The correlation coefficient was slightly higher for women. The differences in accuracy of the different formulas were small. While the errors of BH estimation were generally ±4.5–5.0cm, the consideration of age led to an increase in accuracy of a few millimetres to about 1cm. BH estimations according to Penning & Riepert and Trotter & Gleser were slightly more accurate when age-at-death was taken into account.2,3 That way, stature estimations in the group of individuals older than 60 years were improved by about 2.4cm and 3.1cm.2,3 The error of estimation is therefore about a third of the common ±4.7cm error range. Femur measurements in p-CT allow very accurate BH estimations. Estimations according to Penning led to good results that (barely) come closer to the true value than the frequently used formulas by Trotter & Gleser “American White.”2,3 Therefore, the formulas by Penning & Riepert are also validated for this substantial recent Swiss population.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

Comparison between magnetic resonance imaging and computed tomography of the lung in patients with cystic fibrosis with regard to clinical, laboratory, and pulmonary functional parameters

OBJECTIVE To evaluate whether magnetic resonance imaging (MRI) is effective as computed tomography (CT) in determining morphologic and functional pulmonary changes in patients with cystic fibrosis (CF) in association with multiple clinical parameters. MATERIALS AND METHODS Institutional review board approval and patient written informed consent were obtained. In this prospective study, 30 patients with CF (17 men and 13 women; mean (SD) age, 30.2 (9.2) years; range, 19-52 years) were included. Chest CT was acquired by unenhanced low-dose technique for clinical purposes. Lung MRI (1.5 T) comprised T2- and T1-weighted sequences before and after the application of 0.1-mmol·kg gadobutrol, also considering lung perfusion imaging. All CT and MR images were visually evaluated by using 2 different scoring systems: the modified Helbich and the Eichinger scores. Signal intensity of the peribronchial walls and detected mucus on T2-weighted images as well as signal enhancement of the peribronchial walls on contrast-enhanced T1-weighted sequences were additionally assessed on MRI. For the clinical evaluation, the pulmonary exacerbation rate, laboratory, and pulmonary functional parameters were determined. RESULTS The overall modified Helbich CT score had a mean (SD) of 15.3 (4.8) (range, 3-21) and median of 16.0 (interquartile range [IQR], 6.3). The overall modified Helbich MR score showed slightly, not significantly, lower values (Wilcoxon rank sum test and Student t test; P > 0.05): mean (SD) of 14.3 (4.7) (range, 3-20) and median of 15.0 (IQR, 7.3). Without assessment of perfusion, the overall Eichinger score resulted in the following values for CT vs MR examinations: mean (SD), 20.3 (7.2) (range, 4-31); and median, 21.0 (IQR, 9.5) vs mean (SD), 19.5 (7.1) (range, 4-33); and median, 20.0 (IQR, 9.0). All differences between CT and MR examinations were not significant (Wilcoxon rank sum tests and Student t tests; P > 0.05). In general, the correlations of the CT scores (overall and different imaging parameters) to the clinical parameters were slightly higher compared to the MRI scores. However, if all additional MRI parameters were integrated into the scoring systems, the correlations reached the values of the CT scores. The overall image quality was significantly higher for the CT examinations compared to the MRI sequences. CONCLUSIONS One major diagnostic benefit of lung MRI in CF is the possible acquisition of several different morphologic and functional imaging features without the use of any radiation exposure. Lung MRI shows reliable associations with CT and clinical parameters, which suggests its implementation in CF for routine diagnosis, which would be particularly important in follow-up imaging over the long term.

Systematic analysis of the radiologic findings of aortic dissections on unenhanced postmortem computed tomography

The aim of this study was to evaluate the diagnostic criteria and to identify the radiological signs (derived from known radiological signs) for the detection of aortic dissections using postmortem computed tomography (PMCT). Thirty-three aortic dissection cases were retrospectively evaluated; all underwent PMCT and autopsy. The images were initially evaluated independently by two readers and were subsequently evaluated in consensus. Known radiological signs, such as dislocated calcification and an intimomedial flap, were identified. The prevalence of the double sedimentation level in the true and false lumen of the dissected aorta was assessed and defined as a postmortem characteristic sign of aortic dissection. Dislocated calcification was detected in 85% of the cases with aortic calcification; whereas in 54% of the non-calcified aortas, the intimomedial flap could also be recognized. Double sedimentation was identified in 16/33 of the cases. Overall, in 76% (25/33) of the study cases, the described signs, which are indicative for aortic dissection, could be identified. In this study, three diagnostic criteria of aortic dissection were identified using non-enhanced PMCT images of autopsy-confirmed dissection cases.

Metal Artifact Reduction in Pelvic Computed Tomography With Hip Prostheses: Comparison of Virtual Monoenergetic Extrapolations From Dual-Energy Computed Tomography and an Iterative Metal Artifact Reduction Algorithm in a Phantom Study.

OBJECTIVE The aim of this study was to directly compare metal artifact reduction (MAR) of virtual monoenergetic extrapolations (VMEs) from dual-energy computed tomography (CT) with iterative MAR (iMAR) from single energy in pelvic CT with hip prostheses. MATERIALS AND METHODS A human pelvis phantom with unilateral or bilateral metal inserts of different material (steel and titanium) was scanned with third-generation dual-source CT using single (120 kVp) and dual-energy (100/150 kVp) at similar radiation dose (CT dose index, 7.15 mGy). Three image series for each phantom configuration were reconstructed: uncorrected, VME, and iMAR. Two independent, blinded radiologists assessed image quality quantitatively (noise and attenuation) and subjectively (5-point Likert scale). Intraclass correlation coefficients (ICCs) and Cohen κ were calculated to evaluate interreader agreements. Repeated measures analysis of variance and Friedman test were used to compare quantitative and qualitative image quality. Post hoc testing was performed using a corrected (Bonferroni) P < 0.017. RESULTS Agreements between readers were high for noise (all, ICC ≥ 0.975) and attenuation (all, ICC ≥ 0.986); agreements for qualitative assessment were good to perfect (all, κ ≥ 0.678). Compared with uncorrected images, VME showed significant noise reduction in the phantom with titanium only (P < 0.017), and iMAR showed significantly lower noise in all regions and phantom configurations (all, P < 0.017). In all phantom configurations, deviations of attenuation were smallest in images reconstructed with iMAR. For VME, there was a tendency toward higher subjective image quality in phantoms with titanium compared with uncorrected images, however, without reaching statistical significance (P > 0.017). Subjective image quality was rated significantly higher for images reconstructed with iMAR than for uncorrected images in all phantom configurations (all, P < 0.017). CONCLUSIONS Iterative MAR showed better MAR capabilities than VME in settings with bilateral hip prosthesis or unilateral steel prosthesis. In settings with unilateral hip prosthesis made of titanium, VME and iMAR performed similarly well.

Accuracy of conventional radiography and computed tomography in predicting implant position in relation to the vertebral canal in dogs.

OBJECTIVE To compare the accuracy of radiography and computed tomography (CT) in predicting implant position in relation to the vertebral canal in the cervical and thoracolumbar vertebral column. STUDY DESIGN In vitro imaging and anatomic study. ANIMALS Medium-sized canine cadaver vertebral columns (n=12). METHODS Steinmann pins were inserted into cervical and thoracolumbar vertebrae based on established landmarks but without predetermination of vertebral canal violation. Radiographs and CT images were obtained and evaluated by 6 individuals. A random subset of pins was evaluated for ability to distinguish left from right pins on radiographs. The ability to correctly identify vertebral canal penetration for all pins was assessed both on radiographs and CT. Spines were then anatomically prepared and visual examination of pin penetration into the canal served as the gold standard. RESULTS Left/right accuracy was 93.1%. Overall sensitivity of radiographs and CT to detect vertebral canal penetration by an implant were significantly different and estimated as 50.7% and 93.4%, respectively (P<.0001). Sensitivity was significantly higher for complete versus partial penetration and for radiologists compared with nonradiologists for both imaging modalities. Overall specificity of radiographs and CT to detect vertebral canal penetration was 82.9% and 86.4%, respectively (P=.049). CONCLUSIONS CT was superior to radiographic assessment and is the recommended imaging modality to assess penetration into the vertebral canal. CLINICAL RELEVANCE CT is significantly more accurate in identifying vertebral canal violation by Steinmann pins and should be performed postoperatively to assess implant position.

Assessment of cone beam computed tomography techniques for imaging lung damage in mice in vivo

Lung damage is a common side effect of chemotherapeutic drugs such as bleomycin. This study used a bleomycin mouse model which simulates the lung damage observed in humans. Noninvasive, in vivo cone-beam computed tomography (CBCT) was used to visualize and quantify fibrotic and inflammatory damage over the entire lung volume of mice. Bleomycin was used to induce pulmonary damage in vivo and the results from two CBCT systems, a micro-CT and flat panel CT (fpCT), were compared to histologic measurements, the standard method of murine lung damage quantification. Twenty C57BL/6 mice were given either 3 U/kg of bleomycin or saline intratracheally. The mice were scanned at baseline, before the administration of bleomycin, and then 10, 14, and 21 days afterward. At each time point, a subset of mice was sacrificed for histologic analysis. The resulting CT images were used to assess lung volume. Percent lung damage (PLD) was calculated for each mouse on both the fpCT (PLDfpcT) and the micro-CT (PLDμCT). Histologic PLD (PLDH) was calculated for each histologic section at each time point (day 10, n = 4; day 14, n = 4; day 21, n = 5; control group, n = 5). A linear regression was applied to the PLDfpCT vs. PLDH, PLDμCT vs. PLDH and PLDfpCT vs. PLDμCT distributions. This study did not demonstrate strong correlations between PLDCT and PLDH. The coefficient of determination, R, was 0.68 for PLDμCT vs. PLDH and 0.75 for the PLD fpCT vs. PLDH. The experimental issues identified from this study were: (1) inconsistent inflation of the lungs from scan to scan, (2) variable distribution of damage (one histologic section not representative of overall lung damage), (3) control mice not scanned with each group of bleomycin mice, (4) two CT systems caused long anesthesia time for the mice, and (5) respiratory gating did not hold the volume of lung constant throughout the scan. Addressing these issues might allow for further improvement of the correlation between PLDCT and PLDH. ^

Animation of micro-computed tomography of bioerosion trace Entobia megastoma made by East Australian bioeroding sponge Cliona celata

Endolithic bioerosion is difficult to analyse and to describe, and it usually requires damaging of the sample material. Sponge erosion (Entobia) may be one of the most difficult to evaluate as it is simultaneously macroscopically inhomogeneous and microstructurally intricate. We studied the bioerosion traces of the two Australian sponges Cliona celata Grant, 1826 (sensu Schönberg 2000) and Cliona orientalis Thiele, 1900 with a newly available radiographic technology: high resolution X-ray micro-computed tomography (MCT). MCT allows non-destructive visualisation of live and dead structures in three dimensions and was compared to traditional microscopic methods. MCT and microscopy showed that C. celata bioerosion was more intense in the centre and branched out in the periphery. In contrast, C. orientalis produced a dense, even trace meshwork and caused an overall more intense erosion pattern than C. celata. Extended pioneering filaments were not usually found at the margins of the studied sponge erosion, but branches ended abruptly or tapered to points. Results obtained with MCT were similar in quality to observations from transparent optical spar under the dissecting microscope. Microstructures could not be resolved as well as with e.g. scanning electron microscopy (SEM). Even though sponge scars and sponge chips were easily recognisable on maximum magnification MCT images, they lacked the detail that is available from SEM. Other drawbacks of MCT involve high costs and presently limited access. Even though MCT cannot presently replace traditional techniques such as corrosion casts viewed by SEM, we obtained valuable information. Especially for the possibility to measure endolithic pore volumes, we regard MCT as a very promising tool that will continue to be optimised. A combination of different methods will produce the best results in the study of Entobia.

Technical developments for computed tomography on the CENBG nanobeam line

The use of ion microbeams as probes for computedtomography has proven to be a powerful tool for the three-dimensional characterization of specimens a few tens of micrometers in size. Compared to other types of probes, the main advantage is that quantitative information about mass density and composition can be obtained directly, using specific reconstruction codes. At the Centre d’Etudes Nucléaires de Bordeaux Gradignan (CENBG), this technique was initially developed for applications in cellular biology. However, the observation of the cell ultrastructure requires a sub-micron resolution. The construction of the nanobeamline at the Applications Interdisciplinaires des Faisceaux d’Ions en Region Aquitaine (AIFIRA) irradiation facility has opened new perspectives for such applications. The implementation of computedtomography on the nanobeamline of CENBG has required a careful design of the analysis chamber, especially microscopes for precise sample visualization, and detectors for scanning transmission ion microscopy (STIM) and for particle induced X-ray emission (PIXE). The sample can be precisely positioned in the three directions X, Y, Z and a stepper motor coupled to a goniometer ensures the rotational motion. First images of 3D tomography were obtained on a reference sample containing microspheres of certified diameter, showing the good stability of the beam and the sample stage, and the precision of the motion.

Geometrical characterization of undisturbed soil samples using X-ray computed tomography image analysis. Effect of soil management on soil structure

El estudio de la estructura del suelo es de vital importancia en diferentes campos de la ciencia y la tecnología. La estructura del suelo controla procesos físicos y biológicos importantes en los sistemas suelo-planta-microorganismos. Estos procesos están dominados por la geometría de la estructura del suelo, y una caracterización cuantitativa de la heterogeneidad de la geometría del espacio poroso es beneficiosa para la predicción de propiedades físicas del suelo. La tecnología de la tomografía computerizada de rayos-X (CT) nos permite obtener imágenes digitales tridimensionales del interior de una muestra de suelo, proporcionando información de la geometría de los poros del suelo y permitiendo el estudio de los poros sin destruir las muestras. Las técnicas de la geometría fractal y de la morfología matemática se han propuesto como una poderosa herramienta para analizar y cuantificar características geométricas. Las dimensiones fractales del espacio poroso, de la interfaz poro-sólido y de la distribución de tamaños de poros son indicadores de la complejidad de la estructura del suelo. Los funcionales de Minkowski y las funciones morfológicas proporcionan medios para medir características geométricas fundamentales de los objetos geométricos tridimensionales. Esto es, volumen, superficie, curvatura media de la superficie y conectividad. Las características del suelo como la distribución de tamaños de poros, el volumen del espacio poroso o la superficie poro-solido pueden ser alteradas por diferentes practicas de manejo de suelo. En este trabajo analizamos imágenes tomográficas de muestras de suelo de dos zonas cercanas con practicas de manejo diferentes. Obtenemos un conjunto de medidas geométricas, para evaluar y cuantificar posibles diferencias que el laboreo pueda haber causado en el suelo. ABSTRACT The study of soil structure is of vital importance in different fields of science and technology. Soil structure controls important physical and biological processes in soil-plant-microbial systems. Those processes are dominated by the geometry of soil pore structure, and a quantitative characterization of the spatial heterogeneity of the pore space geometry is beneficial for prediction of soil physical properties. The technology of X-ray computed tomography (CT) allows us to obtain three-dimensional digital images of the inside of a soil sample providing information on soil pore geometry and enabling the study of the pores without disturbing the samples. Fractal geometry and mathematical morphological techniques have been proposed as powerful tools to analyze and quantify geometrical features. Fractal dimensions of pore space, pore-solid interface and pore size distribution are indicators of soil structure complexity. Minkowski functionals and morphological functions provide means to measure fundamental geometrical features of three-dimensional geometrical objects, that is, volume, boundary surface, mean boundary surface curvature, and connectivity. Soil features such as pore-size distribution, pore space volume or pore-solid surface can be altered by different soil management practices. In this work we analyze CT images of soil samples from two nearby areas with contrasting management practices. We performed a set of geometrical measures, some of them from mathematical morphology, to assess and quantify any possible difference that tillage may have caused on the soil.

Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

Single photon emission with computed tomography (SPECT) hexamethylphenylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elderly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects. After initial image preprocessing and registration, image features were obtained that were representative of the mean regional tissue uptake. These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks. After training, the network classified independent trials of patients whose clinical diagnoses conformed to published criteria for probable AD or probable/possible VD. For the SPECT data used in the current tests, the OINN agreement was 80 and 86% for probable AD and probable/possible VD, respectively. These results suggest that artificial neural network methods offer potential in diagnoses from brain images and possibly in other areas of scientific research where complex patterns of data may have scientifically meaningful groupings that are not easily identifiable by the researcher.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

When static meets dynamic: Comparing cone-beam computed tomography and acoustic reflection for upper airway analysis

INTRODUCTION: Upper airway measurement can be important for the diagnosis of breathing disorders. Acoustic reflection (AR) is an accepted tool for studying the airway. Our objective was to investigate the differences between cone-beam computed tomography (CBCT) and AR in calculating airway volumes and areas. METHODS: Subjects with prescribed CBCT images as part of their records were also asked to have AR performed. A total of 59 subjects (mean age, 15 ± 3.8 years) had their upper airway (5 areas) measured from CBCT images, acoustic rhinometry, and acoustic pharyngometry. Volumes and minimal cross-sectional areas were extracted and compared with software. RESULTS: Intraclass correlation on 20 randomly selected subjects, remeasured 2 weeks apart, showed high reliability (r >0.77). Means of total nasal volume were significantly different between the 2 methods (P = 0.035), but anterior nasal volume and minimal cross-sectional area showed no differences (P = 0.532 and P = 0.066, respectively). Pharyngeal volume showed significant differences (P = 0.01) with high correlation (r = 0.755), whereas pharyngeal minimal cross-sectional area showed no differences (P = 0.109). The pharyngeal volume difference may not be considered clinically significant, since it is 758 mm3 for measurements showing means of 11,000 ± 4000 mm3. CONCLUSIONS: CBCT is an accurate method for measuring anterior nasal volume, nasal minimal cross-sectional area, pharyngeal volume, and pharyngeal minimal cross-sectional area.

Iterative reconstruction as a novel method of radiation dose reduction at computed tomography in patients with Crohn's disease

Prior work of our research group, that quantified the alarming levels of radiation dose to patients with Crohn’s disease from medical imaging and the notable shift towards CT imaging making these patients an at risk group, provided context for this work. CT delivers some of the highest doses of ionising radiation in diagnostic radiology. Once a medical imaging examination is deemed justified, there is an onus on the imaging team to endeavour to produce diagnostic quality CT images at the lowest possible radiation dose to that patient. The fundamental limitation with conventional CT raw data reconstruction was the inherent coupling of administered radiation dose with observed image noise – the lower the radiation dose, the noisier the image. The renaissance, rediscovery and refinement of iterative reconstruction removes this limitation allowing either an improvement in image quality without increasing radiation dose or maintenance of image quality at a lower radiation dose compared with traditional image reconstruction. This thesis is fundamentally an exercise in optimisation in clinical CT practice with the objectives of assessment of iterative reconstruction as a method for improvement of image quality in CT, exploration of the associated potential for radiation dose reduction, and development of a new split dose CT protocol with the aim of achieving and validating diagnostic quality submillisiever t CT imaging in patients with Crohn’s disease. In this study, we investigated the interplay of user-selected parameters on radiation dose and image quality in phantoms and cadavers, comparing traditional filtered back projection (FBP) with iterative reconstruction algorithms. This resulted in the development of an optimised, refined and appropriate split dose protocol for CT of the abdomen and pelvis in clinical patients with Crohn’s disease allowing contemporaneous acquisition of both modified and conventional dose CT studies. This novel algorithm was then applied to 50 patients with a suspected acute complication of known Crohn’s disease and the raw data reconstructed with FBP, adaptive statistical iterative reconstruction (ASiR) and model based iterative reconstruction (MBIR). Conventional dose CT images with FBP reconstruction were used as the reference standard with which the modified dose CT images were compared in terms of radiation dose, diagnostic findings and image quality indices. As there are multiple possible user-selected strengths of ASiR available, these were compared in terms of image quality to determine the optimal strength for this modified dose CT protocol. Modified dose CT images with MBIR were also compared with contemporaneous abdominal radiograph, where performed, in terms of diagnostic yield and radiation dose. Finally, attenuation measurements in organs, tissues, etc. with each reconstruction algorithm were compared to assess for preservation of tissue characterisation capabilities. In the phantom and cadaveric models, both forms of iterative reconstruction examined (ASiR and MBIR) were superior to FBP across a wide variety of imaging protocols, with MBIR superior to ASiR in all areas other than reconstruction speed. We established that ASiR appears to work to a target percentage noise reduction whilst MBIR works to a target residual level of absolute noise in the image. Modified dose CT images reconstructed with both ASiR and MBIR were non-inferior to conventional dose CT with FBP in terms of diagnostic findings, despite reduced subjective and objective indices of image quality. Mean dose reductions of 72.9-73.5% were achieved with the modified dose protocol with a mean effective dose of 1.26mSv. MBIR was again demonstrated superior to ASiR in terms of image quality. The overall optimal ASiR strength for the modified dose protocol used in this work is ASiR 80%, as this provides the most favourable balance of peak subjective image quality indices with less objective image noise than the corresponding conventional dose CT images reconstructed with FBP. Despite guidelines to the contrary, abdominal radiographs are still often used in the initial imaging of patients with a suspected complication of Crohn’s disease. We confirmed the superiority of modified dose CT with MBIR over abdominal radiographs at comparable doses in detection of Crohn’s disease and non-Crohn’s disease related findings. Finally, we demonstrated (in phantoms, cadavers and in vivo) that attenuation values do not change significantly across reconstruction algorithms meaning preserved tissue characterisation capabilities with iterative reconstruction. Both adaptive statistical and model based iterative reconstruction algorithms represent feasible methods of facilitating acquisition diagnostic quality CT images of the abdomen and pelvis in patients with Crohn’s disease at markedly reduced radiation doses. Our modified dose CT protocol allows dose savings of up to 73.5% compared with conventional dose CT, meaning submillisievert imaging is possible in many of these patients.