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.

New diagnostic and therapeutic approaches to treat ventricular tachycardias originating at the summit of the left ventricle role of merged hemodynamic-MRI and alternative ablation sources

The left ventricular (LV) summit is the most common site of idiopathic epicardial LV arrhythmias and frequently represents a diagnostic and a therapeutic challenge.1 We present a case of sustained monomorphic ventricular tachycardia (SMVT) originating at the LV summit that underwent failed cryosurgical epicardial ablation and was successfully treated with the aid of merged hemodynamic and contrast-enhanced MRI (CE-MRI).

Intracerebral injection of human immunodeficiency virus type 1 coat protein gp120 differentially affects the expression of nerve growth factor and nitric oxide synthase in the hippocampus of rat.

We have studied the neuropathological characteristics of the brain of rats receiving daily intracerebroventricular administration of freshly dissolved human immunodeficiency virus type 1 recombinant protein gp120 (100 ng per rat per day) given for up to 14 days. Histological examination of serial brain sections revealed no apparent gross damage to the cortex or hippocampus, nor did cell counting yield significant neuronal cell loss. However, the viral protein caused after 7 and 14 days of treatment DNA fragmentation in 10% of brain cortical neurons. Interestingly, reduced neuronal nitric oxide synthase (NOS) expression along with significant increases in nerve growth factor (NGF) were observed in the hippocampus, where gp120 did not cause neuronal damage. No changes in NGF and NOS expression were seen in the cortex, where cell death is likely to be of the apoptotic type. The present data demonstrate that gp120-induced cortical cell death is associated with the lack of increase of NGF in the cerebral cortex and suggest that the latter may be important for the expression of neuropathology in the rat brain. By contrast, enhanced levels of NGF may prevent or delay neuronal death in the hippocampus, where reduced NOS expression may be a reflection of a subcellular insult inflicted by the viral protein.

Avaliação da gordura hepática utilizando ressonância magnética

A esteatose hepática, que se caracteriza pelo acúmulo excessivo de gordura nas células do fígado, é um problema que vem preocupando a comunidade médico-científica, pois sua incidência vem aumentando a nível global, com expectativa de se tornar a doença crônica hepática de maior predominância em várias partes do mundo. Apesar de ser considerada uma doença benigna, a esteatose pode evoluir para doenças mais graves como cirrose, fibrose avançada, esteato hepatite (com ou sem fibrose) ou carcinoma. Entretanto, é potencialmente reversível, mesmo em quadros mais graves, o que reforça a urgência de se desenvolver métodos confiáveis para detecção e avaliação, inclusive ao longo de tratamento. Os métodos atuais para diagnóstico e quantificação da gordura hepática ainda são falhos: com a ultrassonografia não se é capaz de realizar quantificação; a tomografia computadorizada faz uso de radiação ionizante; a punção (biópsia), considerada o padrão ouro, é precisa, mas invasiva e pontual. A Ressonância Magnética (RM), tanto com espectroscopia (MRS) como com imagem (MRI), são alternativas completamente não invasivas, capazes de fornecer o diagnóstico e quantificação da gordura infiltrada no fígado. Entretanto, os trabalhos encontrados na literatura utilizam sequências de pulsos desenvolvidas especialmente para esse fim, com métodos de pós-processamento extremamente rebuscados, o que não é compatível com o estado atual dos equipamentos encontrados em ambientes clínicos nem mesmo ao nível de experiência e conhecimento das equipes técnicas que atuam em clínicas de radiodiagnóstico. Assim, o objetivo central do presente trabalho foi avaliar o potencial da RM como candidato a método de diagnóstico e de quantificação de gordura em ambientes clínicos, utilizando, para isso, sequências de pulsos convencionais, disponíveis em qualquer sistema comercial de RM, com protocolos de aquisição e processamento compatíveis com àqueles realizados em exames clínicos, tanto no que se refere à simplicidade como ao tempo total de aquisição. Foram avaliadas diferentes abordagens de MRS e MRI utilizando a biópsia hepática como padrão de referência. Foram avaliados pacientes portadores de diabetes tipo II, que apresentam alta prevalência de esteatose hepática não alcoólica, além de grande variabilidade nos percentuais de gordura. Foram realizadas medidas de correlação, acurácia, sensibilidade e especificidade de cada uma das abordagens utilizadas. Todos os métodos avaliados apresentaram alto grau de correlação positiva (> 87%) com os dados obtidos de maneira invasiva, o que revela que os valores obtidos utilizando RM estão de acordo com aquilo observado pela biópsia hepática. Muito embora os métodos de processamento utilizados não sejam tão complexos quanto seriam necessários caso uma quantificação absoluta fosse desejada, nossas análises mostraram alta acurácia, especificidade e sensibilidade da RM na avaliação da esteatose. Em conclusão, a RM se apresenta, de fato, como uma excelente candidata para avaliar, de forma não invasiva, a fração de gordura hepática, mesmo quando se considera as limitações impostas por um ambiente clínico convencional. Isso sugere que essas novas metodologias podem começar a migrar para ambientes clínicos sem depender das sequências complexas e dos processamentos exóticos que estão descritos na literatura mais atual.

Susac's syndrome: Leptomeningeal enhancement on 3D FLAIR MRI

BACKGROUND Contrast-enhanced (ce) fluid-attenuated inversion recovery magnetic resonance imaging (FLAIR MRI) has recently been shown to identify leptomeningeal pathology in multiple sclerosis. OBJECTIVE To demonstrate leptomeningeal enhancement on three-dimensional (3D) FLAIR in a case of Susac's syndrome. METHODS Leptomeningeal enhancement was correlated with clinical activity over 20 months and compared to retinal fluorescein angiography. RESULTS The size, number, and location of leptomeningeal enhancement varied over time and generally correlated with symptom severity. The appearance was remarkably similar to that of retinal vasculopathy. CONCLUSION Ce 3D FLAIR may aid in diagnosis and understanding of pathophysiology in Susac's syndrome and may serve as a biomarker for disease activity.

Screening with magnetic resonance imaging and mammography of a UK population at high familial risk of breast cancer: a prospective multicentre cohort study (MARIBS)

Background Women genetically predisposed to breast cancer often develop the disease at a young age when dense breast tissue reduces the sensitivity of X-ray mammography. Our aim was, therefore, to compare contrast enhanced magnetic resonance imaging (CE MRI) with mammography for screening. Methods We did a prospective multicentre cohort study in 649 women aged 35-49 years with a strong family history of breast cancer or a high probability of a BRCA1, BRCA2, or TP53 mutation. We recruited participants from 22 centres in the UK, and offered the women annual screening with CE MRI and mammography for 2-7 years. Findings We diagnosed 35 cancers in the 649 women screened with both mammography and CE MRI (1881 screens): 19 by CE MRI only, six by mammography only, and eight by both, with two interval cases. Sensitivity was significantly higher for CE MRI (77%, 95% CI 60-90) than for mammography (40%, 24-58; p=0.01), and was 94% (81-99) when both methods were used. Specificity was 93% (92-95) for mammography, 81% (80-83) for CE MRI (p

Coronary revascularization can improve regional left ventricular volumes in non-transmural scars without contractile reserve

Revascularization (RVS) of scar segts does not lead to recovery of left ventricular (LV) function, but its effect on post-infarct remodeling is unclear. We examined the impact of RVS on regional remodeling in different transmural extents of scar (TME). Dobutamine echo (DbE) and contrast enhanced magnetic resonance imaging (ce- MRI) were performed in 72 pts post MI (age 63±10, EF 49±12%). Pts were selected for RVS (n = 31) or medical treatment (n = 41). Segts were classified as scar if there were no contractile reserve during lowdose DbE.TMEwas measured by ce-MRI; a cutoff of 75% was used to differentiate transmural (TM) from non-transmural (NT) scars. Regional end systolic (ESV) and end diastolic volumes (EDV) were measured at baseline and 12 months follow up.Of 218 segts identified as scar on DbE, 164wereNTand 54 were TM on ce-MRI. Revascularization was performed to 62 NT and 11 TM segts. In the RVS group, there was reverse remodeling with significant reduction in LV volumes in NT (ESV, 6.8±3.2 ml versus 5.8±3.7 ml, p = 0.002; EDV, 10.9±4.9 ml versus 9.8±5.6 ml, p = 0.02), but no significant change in volumes in TM (ESV, 6.9±3.7 ml versus 5.4±2.1 ml, p = 0.09; EDV, 10.2±4.4 ml versus 9.4±4.3 ml, p = 0.5). In the medically treated group, there were no changes in LV volumes in both NT (ESV, 12.0±11.9 ml versus 12.7±13.8 ml, p = 0.3; EDV, 12.5±7.8 ml versus 12.6±9.7 ml, p = 0.8) and TM (ESV, 8.0±3.8 ml versus 7.9±4.6 ml, p = 0.8; EDV, 10.3±4.8 ml versus 10.4±5.4 ml, p = 0.9). Despite absence of contractile reserve on DbE, NT benefit from coronary revascularization with regional reverse LV remodeling.

Local geometric changes in left ventricular remodeling post-infarction can lead to apparent reduction in scar thickness

Serial reduction in scar thickness has been shown in animal models. We sought whether this reduction in scar thickness may be a result of dilatation of the left ventricle (LV) with stretching and thinning of the wall. Contrast enhanced magnetic resonance imaging (CMRI) was performed to delineate radial scar thickness in 25 patients (age 63±10, 21 men) after myocardial infarction. The LV was divided into 16 segts and the absolute radial scar thickness (ST) and percentage scar to total wall thickness (%ST) were measured. Regional end diastolic (EDV) and end systolic volumes (ESV) of corresponding segments were measured on CMRI. All patients underwent revascularization and serial changes in ST, %ST, and regional volumes were assessed with a mean follow up of 15±5 months. CMRI identified a total of 93 scar segments. An increase in EDV or ESV was associated with a serial reduction inST(versusEDV, r =−0.3, p = 0.01; versusESV, r =−0.3, p = 0.005) and%ST(versusEDV, r =−0.2, p = 0.04; versus ESV, r =−0.3, p = 0.001). For segts associated with a positive increase in EDV (group I) or ESV (group II) there was a significant decrease in ST and %ST, but in those segts with stable EDV (group III) or ESV (group IV) there were no significant changes in ST and %ST (Table).

Valutazione della cardiotossicità in pazienti oncologici mediante tecniche ecocardiografiche

L'elaborato si inserisce in un progetto sviluppato presso l'Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (I.R.S.T.) di Meldola che riguarda la valutazione di parametri cardiologici che possano risultare indici predittivi di uno scompenso cardiaco in pazienti affetti da linfoma. Tutti i soggetti considerati nel progetto sono stati sottoposti a trattamenti chemioterapici facenti uso di antracicline e la cui funzionalità cardiaca è stata controllata periodicamente tramite ecografia bidimensionale e volumetrica, utilizzando il sistema VividE9 della GE Healthcare. L'obiettivo dell'analisi è quello di ricercare se oltre alla frazione di eiezione esistono parametri più predittivi di una eventuale cardiotossicità come gli strain, calcolati attraverso l'ausilio della tecnica ecografica.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

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.

Epigastric Pain in Acute Renal Infarction: The Forgotten Presentation

Epigastric pain is a manifestation of several medical and surgical conditions. However, when persistent epigastric pain is associated with microscopic or frank haematuria and elevated lactate dehydrogenase (LDH), especially in patients with increased risk of thromboembolic events, acute renal infarction (ARI) should be considered. We report the case of a 77-year-old male patient who presented with sudden persistent epigastric pain and elevated LDH who was found to have atrial fibrillation. The patient was diagnosed with ARI. ARI is not usually a typical differential diagnosis in patients with persistent epigastric pain and elevated LDH in whom the risk of thromboembolic events is high. Thus, physicians should perform a contrast-enhanced CT scan as early as possible to rule out or confirm renal infarction.

A Fatal Case of Neuroleptic Malignant Syndrome After Paralytic Bowel in a Patient Taking Antiparkinson Medication

Objectives: We report a fatal case of neuroleptic malignant-like syndrome, which occurred as a consequence of paralytic bowel in a 72-year-old woman on treatment with antiparkinson medication. Case description: Contrast enhanced computerized tomography of the chest and abdomen demonstrated the presence of paralytic bowel. Results: The patient died. Conclusions: Physicians involved in the treatment of patients affected by Parkinson’s disease should take into consideration the possibility of dopaminergic drug malabsorption due to paralytic bowel as a possible cause of neuroleptic malignant-like syndrome.

Fingering Instabilities in Dewetting Nanofluids

The growth of fingering patterns in dewetting nanofluids (colloidal solutions of thiol-passivated gold nanoparticles) has been followed in real time using contrast-enhanced video microscopy. The fingering instability on which we focus here arises from evaporatively-driven nucleation and growth a nanoscopically thin "precursor" solvent film behind the macroscopic contact line. We find that well-developed isotropic fingering structures only form for a narrow range of experimental parameters. Numerical simulations, based on a modification of the Monte Carlo approach introduced by Rabani et al. [Nature 426, 271 (2003)], reproduce the patterns we observe experimentally.

Applications of advanced and dual energy computed tomography in proton therapy

This thesis focuses on advanced reconstruction methods and Dual Energy (DE) Computed Tomography (CT) applications for proton therapy, aiming at improving patient positioning and investigating approaches to deal with metal artifacts. To tackle the first goal, an algorithm for post-processing input DE images has been developed. The outputs are tumor- and bone-canceled images, which help in recognising structures in patient body. We proved that positioning error is substantially reduced using contrast enhanced images, thus suggesting the potential of such application. If positioning plays a key role in the delivery, even more important is the quality of planning CT. For that, modern CT scanners offer possibility to tackle challenging cases, like treatment of tumors close to metal implants. Possible approaches for dealing with artifacts introduced by such rods have been investigated experimentally at Paul Scherrer Institut (Switzerland), simulating several treatment plans on an anthropomorphic phantom. In particular, we examined the cases in which none, manual or Iterative Metal Artifact Reduction (iMAR) algorithm were used to correct the artifacts, using both Filtered Back Projection and Sinogram Affirmed Iterative Reconstruction as image reconstruction techniques. Moreover, direct stopping power calculation from DE images with iMAR has also been considered as alternative approach. Delivered dose measured with Gafchromic EBT3 films was compared with the one calculated in Treatment Planning System. Residual positioning errors, daily machine dependent uncertainties and film quenching have been taken into account in the analyses. Although plans with multiple fields seemed more robust than single field, results showed in general better agreement between prescribed and delivered dose when using iMAR, especially if combined with DE approach. Thus, we proved the potential of these advanced algorithms in improving dosimetry for plans in presence of metal implants.