High-resolution three-dimensional aortic magnetic resonance angiography and quantitative vessel wall characterization of different atherosclerotic stages in a rabbit model

PURPOSE: Atherosclerosis results in a considerable medical and socioeconomic impact on society. We sought to evaluate novel magnetic resonance imaging (MRI) angiography and vessel wall sequences to visualize and quantify different morphologic stages of atherosclerosis in a Watanabe hereditary hyperlipidemic (WHHL) rabbit model. MATERIAL AND METHODS: Aortic 3D steady-state free precession angiography and subrenal aortic 3D black-blood fast spin-echo vessel wall imaging pre- and post-Gadolinium (Gd) was performed in 14 WHHL rabbits (3 normal, 6 high-cholesterol diet, and 5 high-cholesterol diet plus endothelial denudation) on a commercial 1.5 T MR system. Angiographic lumen diameter, vessel wall thickness, signal-/contrast-to-noise analysis, total vessel area, lumen area, and vessel wall area were analyzed semiautomatically. RESULTS: Pre-Gd, both lumen and wall dimensions (total vessel area, lumen area, vessel wall area) of group 2 + 3 were significantly increased when compared with those of group 1 (all P < 0.01). Group 3 animals had significantly thicker vessel walls than groups 1 and 2 (P < 0.01), whereas angiographic lumen diameter was comparable among all groups. Post-Gd, only diseased animals of groups 2 + 3 showed a significant (>100%) signal-to-noise ratio and contrast-to-noise increase. CONCLUSIONS: A combination of novel 3D magnetic resonance angiography and high-resolution 3D vessel wall MRI enabled quantitative characterization of various atherosclerotic stages including positive arterial remodeling and Gd uptake in a WHHL rabbit model using a commercially available 1.5 T MRI system.

Navigator-gated free-breathing 3D balanced FFE projection renal MRA: Comparison with contrast-enhanced breath-hold 3D MRA in a swine model.

A cardiac-triggered, free-breathing, 3D balanced FFE projection renal MR angiography (MRA) technique with a 2D pencil beam aortic labeling pulse for selective aortic spin tagging was developed. For respiratory motion artifact suppression during free breathing, a prospective real-time navigator was implemented for renal MRA. Images obtained with the new approach were compared with standard contrast-enhanced (CE) 3D breath-hold MRA in seven swine. Signal properties and vessel visualization were analyzed. With the presented technique, high-resolution, high-contrast renal projection MRA with superior vessel length visualization (including a greater visible number of distal branches of the renal arteries) compared to standard breath-hold CE-MRA was obtained. The present results warrant clinical studies in patients with renal artery disease.

Selective in vivo visualization of immune-cell infiltration in a mouse model of autoimmune myocarditis by fluorine-19 cardiac magnetic resonance.

BACKGROUND: The goal of this study was to characterize the performance of fluorine-19 ((19)F) cardiac magnetic resonance (CMR) for the specific detection of inflammatory cells in a mouse model of myocarditis. Intravenously administered perfluorocarbons are taken up by infiltrating inflammatory cells and can be detected by (19)F-CMR. (19)F-labeled cells should, therefore, generate an exclusive signal at the inflamed regions within the myocardium. METHODS AND RESULTS: Experimental autoimmune myocarditis was induced in BALB/c mice. After intravenous injection of 2×200 µL of a perfluorocarbon on day 19 and 20 (n=9) after immunization, in vivo (19)F-CMR was performed at the peak of myocardial inflammation (day 21). In 5 additional animals, perfluorocarbon combined with FITC (fluorescein isothiocyanate) was administered for postmortem immunofluorescence and flow-cytometry analyses. Control experiments were performed in 9 animals. In vivo (19)F-CMR detected myocardial inflammation in all experimental autoimmune myocarditis-positive animals. Its resolution was sufficient to identify even small inflammatory foci, that is, at the surface of the right ventricle. Postmortem immunohistochemistry and flow cytometry confirmed the presence of perfluorocarbon in macrophages, dendritic cells, and granulocytes, but not in lymphocytes. The myocardial volume of elevated (19)F signal (rs=0.96; P<0.001), the (19)F signal-to-noise ratio (rs=0.92; P<0.001), and the (19)F signal integral (rs=0.96; P<0.001) at day 21 correlated with the histological myocarditis severity score. CONCLUSIONS: In vivo (19)F-CMR was successfully used to visualize the inflammation specifically and robustly in experimental autoimmune myocarditis, and thus allowed for an unprecedented insight into the involvement of inflammatory cells in the disease process.

A dynamic model of keratinocyte stem cell renewal and differentiation: role of the p21WAF1/Cip1 and Notch1 signaling pathways.

We present here a dynamic model of functional equilibrium between keratinocyte stem cells, transit amplifying populations and cells that are reversibly versus irreversibly committed to differentiation. According to this model, the size of keratinocyte stem cell populations can be controlled at multiple levels, including relative late steps in the sequence of events leading to terminal differentiation and by the influences of a heterogeneous extra-cellular environment. We discuss how work in our laboratory, on the interconnection between the cyclin/CDK inhibitor p21WAF1/Cip1 and the Notch1 signaling pathways, provides strong support to this dynamic model of stem cell versus committed and/or differentiated keratinocyte populations.

Model-based iterative reconstruction in pediatric chest CT: assessment of image quality in a prospective study of children with cystic fibrosis.

BACKGROUND: The potential effects of ionizing radiation are of particular concern in children. The model-based iterative reconstruction VEO(TM) is a technique commercialized to improve image quality and reduce noise compared with the filtered back-projection (FBP) method. OBJECTIVE: To evaluate the potential of VEO(TM) on diagnostic image quality and dose reduction in pediatric chest CT examinations. MATERIALS AND METHODS: Twenty children (mean 11.4 years) with cystic fibrosis underwent either a standard CT or a moderately reduced-dose CT plus a minimum-dose CT performed at 100 kVp. Reduced-dose CT examinations consisted of two consecutive acquisitions: one moderately reduced-dose CT with increased noise index (NI = 70) and one minimum-dose CT at CTDIvol 0.14 mGy. Standard CTs were reconstructed using the FBP method while low-dose CTs were reconstructed using FBP and VEO. Two senior radiologists evaluated diagnostic image quality independently by scoring anatomical structures using a four-point scale (1 = excellent, 2 = clear, 3 = diminished, 4 = non-diagnostic). Standard deviation (SD) and signal-to-noise ratio (SNR) were also computed. RESULTS: At moderately reduced doses, VEO images had significantly lower SD (P < 0.001) and higher SNR (P < 0.05) in comparison to filtered back-projection images. Further improvements were obtained at minimum-dose CT. The best diagnostic image quality was obtained with VEO at minimum-dose CT for the small structures (subpleural vessels and lung fissures) (P < 0.001). The potential for dose reduction was dependent on the diagnostic task because of the modification of the image texture produced by this reconstruction. CONCLUSIONS: At minimum-dose CT, VEO enables important dose reduction depending on the clinical indication and makes visible certain small structures that were not perceptible with filtered back-projection.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

Hind limb ischemia in rabbit model: T2-prepared versus time-of-flight MR angiography at 3 T.

PURPOSE: To prospectively compare various parameters of vessels imaged at 3 T by using time-of-flight (TOF) and T2-prepared magnetic resonance (MR) angiography in a rabbit model of hind limb ischemia. MATERIALS AND METHODS: Experiments were approved by the institutional animal care and use committee. Endovascular occlusion of the left superficial femoral artery was induced in 14 New Zealand white rabbits. After 2 weeks, MR angiography and conventional (x-ray) angiography were performed. Vessel sharpness was evaluated visually in the ischemic and nonischemic limbs, and the presence of small collateral vessels was evaluated in the ischemic limbs. Vessel sharpness was also quantified by evaluating the magnitude of signal intensity change at the vessel borders. RESULTS: The sharpness of vessels in the nonischemic limbs was similar between the TOF and the T2-prepared images. In the ischemic limbs, however, T2-prepared imaging, as compared with TOF imaging, generated higher vessel sharpness in arteries with diminished blood flow (mean vessel sharpness: 44% vs 30% for popliteal arteries, 45% vs 28% for saphenous arteries; P < .001 for both comparisons) and enabled better detection of small collateral vessels (93% vs 36% of vessels, P < .001). CONCLUSION: T2-prepared imaging can facilitate high-spatial-resolution MR angiography of small vessels with low blood flow and thus has potential as a tool for noninvasive evaluation of arteriogenic therapies, without use of contrast material. Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/2452062067/DC1.

Metabolic alterations in the cortex of a mouse model with glutathione deficit - relevance to schizophrenia

Background: Glutathione (GSH) is a major redox regulator and antioxidant and is decreased in cerebrospinal fluid and prefrontal cortex of schizophrenia patients [Do et al. (2000) Eur J Neurosci 12:3721]. The genes of the key GSH-synthesizing enzyme, glutamate- cysteine ligase catalytic (GCLC) and modifier (GCLM) subunits, are associated with schizophrenia, suggesting that the deficit in GSH synthesis is of genetic origin [Gysin et al. (2007) PNAS 104:16621]. GCLM knock-out (KO) mice, which display an 80% decrease in brain GSH levels, have abnormal brain morphology and function [Do et al. (2009) Curr Opin Neurobiol 19:220]. Developmental redox deregulation by impaired GSH synthesis and environmental risk factors generating oxidative stress may have a central role in schizophrenia. Here, we used GCLM KO mice to investigate the impact of a genetically dysregulated redox system on the neurochemical profile of the developing brain. Methods: The neurochemical profile of the anterior and posterior cortical areas of male and female GCLM KO and wild-type mice was determined by in vivo 1H NMR spectroscopy on postnatal days 10, 20, 30, 60 and 90, under 1 to 1.5% isoflurane anaesthesia. Localised 1H NMR spectroscopy was performed on a 14.1 T, 26 cm VNMRS spectrometer (Varian, Magnex) using a home-built 8 mm diameter quadrature surface coil (used both for RF excitation and signal reception). Spectra were acquired using SPECIAL with TE of 2.8 ms and TR of 4 s from VOIs placed in anterior or posterior regions of the cortex [Mlynárik et al. (2006) MRM 56:965]. LCModel analysis allowed in vivo quantification of a neurochemical profile composed of 18 metabolites. Results: GCLM KO mice displayed nearly undetectable GSH levels as compared to WT mice, demonstrating their drastic redox deregulation. Depletion of GSH triggered alteration of metabolites related to its synthesis, namely increase of glycine and glutamate levels during development (P20 and P30). Concentrations of glutamine and aspartate that are produced from glutamate were also increased in GCLM KO animals relative to WT. In addition, GCLM KO mice also showed higher levels of N-acetylaspartate that originates from the acetylation of aspartate. These metabolites are particularly implicated in neurotransmission processes and in mitochondrial oxidative metabolism. Their increase may indicate impaired mitochondrial metabolism with concomitant accumulation of lactate in the adult mice (P60 and P90). In addition, the GSH depletion triggers reduction of GABA concentration in anterior cortex of the P60 mice, which is in accordance with known impairment of GABAergic interneurons in that area. Changes were generally more pronounced in males than in females at P60, which is consistent with earlier disease onset in male patients. Discussion: In conclusion, the observed metabolic alterations in the cortex of a mouse model of redox deregulation suggest impaired mitochondrial metabolism and altered neurotransmission. The results also highlight the age between P20 and P30 as a sensitive period during the development for these alterations.

Signal transduction in plant-beneficial rhizobacteria with biocontrol properties.

Biological control of root pathogens--mostly fungi--can be achieved by the introduction of selected bacterial inoculants acting as 'biopesticides'. Successful inoculants have been identified among Gram-negative and Gram-positive bacteria, often belonging to Pseudomonas spp. and Bacillus spp., respectively. Biocontrol activity of a model rhizobacterium, P. fluorescens CHAO, depends to a considerable extent on the synthesis of extracellular antimicrobial secondary metabolites and exoenzymes, thought to antagonize the pathogenicity of a variety of phytopathogenic fungi. The regulation of exoproduct formation in P. fluorescens (as well as in other bacteria) depends essentially on the GacS/GacA two-component system, which activates a largely unknown signal transduction pathway. However, recent evidence indicates that GacS/GacA control has a major impact on target gene expression at a post-transcriptional level, involving an mRNA target sequence (typically near the ribosome binding site), two RNA binding proteins (designated RsmA and RsmE), and a regulatory RNA (RsmZ) capable of binding RsmA. The expression and activity of the regulatory system is stimulated by at least one low-molecular-weight signal. The timing and specificity of this switch from primary to secondary metabolism are essential for effective biocontrol.

A qualitative continuous model of cellular auxin and brassinosteroid signaling and their crosstalk.

Motivation: Hormone pathway interactions are crucial in shaping plant development, such as synergism between the auxin and brassinosteroid pathways in cell elongation. Both hormone pathways have been characterized in detail, revealing several feedback loops. The complexity of this network, combined with a shortage of kinetic data, renders its quantitative analysis virtually impossible at present.Results: As a first step towards overcoming these obstacles, we analyzed the network using a Boolean logic approach to build models of auxin and brassinosteroid signaling, and their interaction. To compare these discrete dynamic models across conditions, we transformed them into qualitative continuous systems, which predict network component states more accurately and can accommodate kinetic data as they become available. To this end, we developed an extension for the SQUAD software, allowing semi-quantitative analysis of network states. Contrasting the developmental output depending on cell type-specific modulators enabled us to identify a most parsimonious model, which explains initially paradoxical mutant phenotypes and revealed a novel physiological feature.

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Adaptation of a Gaussia princeps Luciferase reporter system in Candida albicans for in vivo detection in the Galleria mellonella infection model.

For the past 10 years, mini-host models and in particular the greater wax moth Galleria mellonella have tended to become a surrogate for murine models of fungal infection mainly due to cost, ethical constraints and ease of use. Thus, methods to better assess the fungal pathogenesis in G. mellonella need to be developed. In this study, we implemented the detection of Candida albicans cells expressing the Gaussia princeps luciferase in its cell wall in infected larvae of G. mellonella. We demonstrated that detection and quantification of luminescence in the pulp of infected larvae is a reliable method to perform drug efficacy and C. albicans virulence assays as compared to fungal burden assay. Since the linearity of the bioluminescent signal, as compared to the CFU counts, has a correlation of R(2) = 0.62 and that this method is twice faster and less labor intensive than classical fungal burden assays, it could be applied to large scale studies. We next visualized and followed C. albicans infection in living G. mellonella larvae using a non-toxic and water-soluble coelenterazine formulation and a CCD camera that is commonly used for chemoluminescence signal detection. This work allowed us to follow for the first time C. albicans course of infection in G. mellonella during 4 days.

A comprehensive model for quantum noise characterization in digital mammography.

NlmCategory="UNASSIGNED">A version of cascaded systems analysis was developed specifically with the aim of studying quantum noise propagation in x-ray detectors. Signal and quantum noise propagation was then modelled in four types of x-ray detectors used for digital mammography: four flat panel systems, one computed radiography and one slot-scan silicon wafer based photon counting device. As required inputs to the model, the two dimensional (2D) modulation transfer function (MTF), noise power spectra (NPS) and detective quantum efficiency (DQE) were measured for six mammography systems that utilized these different detectors. A new method to reconstruct anisotropic 2D presampling MTF matrices from 1D radial MTFs measured along different angular directions across the detector is described; an image of a sharp, circular disc was used for this purpose. The effective pixel fill factor for the FP systems was determined from the axial 1D presampling MTFs measured with a square sharp edge along the two orthogonal directions of the pixel lattice. Expectation MTFs were then calculated by averaging the radial MTFs over all possible phases and the 2D EMTF formed with the same reconstruction technique used for the 2D presampling MTF. The quantum NPS was then established by noise decomposition from homogenous images acquired as a function of detector air kerma. This was further decomposed into the correlated and uncorrelated quantum components by fitting the radially averaged quantum NPS with the radially averaged EMTF(2). This whole procedure allowed a detailed analysis of the influence of aliasing, signal and noise decorrelation, x-ray capture efficiency and global secondary gain on NPS and detector DQE. The influence of noise statistics, pixel fill factor and additional electronic and fixed pattern noises on the DQE was also studied. The 2D cascaded model and decompositions performed on the acquired images also enlightened the observed quantum NPS and DQE anisotropy.

Iterative reconstruction in CT : using mathematical model observers to determine low dose images' trustworthiness

La tomodensitométrie (TDM) est une technique d'imagerie pour laquelle l'intérêt n'a cessé de croitre depuis son apparition au début des années 70. De nos jours, l'utilisation de cette technique est devenue incontournable, grâce entre autres à sa capacité à produire des images diagnostiques de haute qualité. Toutefois, et en dépit d'un bénéfice indiscutable sur la prise en charge des patients, l'augmentation importante du nombre d'examens TDM pratiqués soulève des questions sur l'effet potentiellement dangereux des rayonnements ionisants sur la population. Parmi ces effets néfastes, l'induction de cancers liés à l'exposition aux rayonnements ionisants reste l'un des risques majeurs. Afin que le rapport bénéfice-risques reste favorable au patient il est donc nécessaire de s'assurer que la dose délivrée permette de formuler le bon diagnostic tout en évitant d'avoir recours à des images dont la qualité est inutilement élevée. Ce processus d'optimisation, qui est une préoccupation importante pour les patients adultes, doit même devenir une priorité lorsque l'on examine des enfants ou des adolescents, en particulier lors d'études de suivi requérant plusieurs examens tout au long de leur vie. Enfants et jeunes adultes sont en effet beaucoup plus sensibles aux radiations du fait de leur métabolisme plus rapide que celui des adultes. De plus, les probabilités des évènements auxquels ils s'exposent sont également plus grandes du fait de leur plus longue espérance de vie. L'introduction des algorithmes de reconstruction itératifs, conçus pour réduire l'exposition des patients, est certainement l'une des plus grandes avancées en TDM, mais elle s'accompagne de certaines difficultés en ce qui concerne l'évaluation de la qualité des images produites. Le but de ce travail est de mettre en place une stratégie pour investiguer le potentiel des algorithmes itératifs vis-à-vis de la réduction de dose sans pour autant compromettre la qualité du diagnostic. La difficulté de cette tâche réside principalement dans le fait de disposer d'une méthode visant à évaluer la qualité d'image de façon pertinente d'un point de vue clinique. La première étape a consisté à caractériser la qualité d'image lors d'examen musculo-squelettique. Ce travail a été réalisé en étroite collaboration avec des radiologues pour s'assurer un choix pertinent de critères de qualité d'image. Une attention particulière a été portée au bruit et à la résolution des images reconstruites à l'aide d'algorithmes itératifs. L'analyse de ces paramètres a permis aux radiologues d'adapter leurs protocoles grâce à une possible estimation de la perte de qualité d'image liée à la réduction de dose. Notre travail nous a également permis d'investiguer la diminution de la détectabilité à bas contraste associée à une diminution de la dose ; difficulté majeure lorsque l'on pratique un examen dans la région abdominale. Sachant que des alternatives à la façon standard de caractériser la qualité d'image (métriques de l'espace Fourier) devaient être utilisées, nous nous sommes appuyés sur l'utilisation de modèles d'observateurs mathématiques. Nos paramètres expérimentaux ont ensuite permis de déterminer le type de modèle à utiliser. Les modèles idéaux ont été utilisés pour caractériser la qualité d'image lorsque des paramètres purement physiques concernant la détectabilité du signal devaient être estimés alors que les modèles anthropomorphes ont été utilisés dans des contextes cliniques où les résultats devaient être comparés à ceux d'observateurs humain, tirant profit des propriétés de ce type de modèles. Cette étude a confirmé que l'utilisation de modèles d'observateurs permettait d'évaluer la qualité d'image en utilisant une approche basée sur la tâche à effectuer, permettant ainsi d'établir un lien entre les physiciens médicaux et les radiologues. Nous avons également montré que les reconstructions itératives ont le potentiel de réduire la dose sans altérer la qualité du diagnostic. Parmi les différentes reconstructions itératives, celles de type « model-based » sont celles qui offrent le plus grand potentiel d'optimisation, puisque les images produites grâce à cette modalité conduisent à un diagnostic exact même lors d'acquisitions à très basse dose. Ce travail a également permis de clarifier le rôle du physicien médical en TDM: Les métriques standards restent utiles pour évaluer la conformité d'un appareil aux requis légaux, mais l'utilisation de modèles d'observateurs est inévitable pour optimiser les protocoles d'imagerie. -- Computed tomography (CT) is an imaging technique in which interest has been quickly growing since it began to be used in the 1970s. Today, it has become an extensively used modality because of its ability to produce accurate diagnostic images. However, even if a direct benefit to patient healthcare is attributed to CT, the dramatic increase in the number of CT examinations performed has raised concerns about the potential negative effects of ionising radiation on the population. Among those negative effects, one of the major risks remaining is the development of cancers associated with exposure to diagnostic X-ray procedures. In order to ensure that the benefits-risk ratio still remains in favour of the patient, it is necessary to make sure that the delivered dose leads to the proper diagnosis without producing unnecessarily high-quality images. This optimisation scheme is already an important concern for adult patients, but it must become an even greater priority when examinations are performed on children or young adults, in particular with follow-up studies which require several CT procedures over the patient's life. Indeed, children and young adults are more sensitive to radiation due to their faster metabolism. In addition, harmful consequences have a higher probability to occur because of a younger patient's longer life expectancy. The recent introduction of iterative reconstruction algorithms, which were designed to substantially reduce dose, is certainly a major achievement in CT evolution, but it has also created difficulties in the quality assessment of the images produced using those algorithms. The goal of the present work was to propose a strategy to investigate the potential of iterative reconstructions to reduce dose without compromising the ability to answer the diagnostic questions. The major difficulty entails disposing a clinically relevant way to estimate image quality. To ensure the choice of pertinent image quality criteria this work was continuously performed in close collaboration with radiologists. The work began by tackling the way to characterise image quality when dealing with musculo-skeletal examinations. We focused, in particular, on image noise and spatial resolution behaviours when iterative image reconstruction was used. The analyses of the physical parameters allowed radiologists to adapt their image acquisition and reconstruction protocols while knowing what loss of image quality to expect. This work also dealt with the loss of low-contrast detectability associated with dose reduction, something which is a major concern when dealing with patient dose reduction in abdominal investigations. Knowing that alternative ways had to be used to assess image quality rather than classical Fourier-space metrics, we focused on the use of mathematical model observers. Our experimental parameters determined the type of model to use. Ideal model observers were applied to characterise image quality when purely objective results about the signal detectability were researched, whereas anthropomorphic model observers were used in a more clinical context, when the results had to be compared with the eye of a radiologist thus taking advantage of their incorporation of human visual system elements. This work confirmed that the use of model observers makes it possible to assess image quality using a task-based approach, which, in turn, establishes a bridge between medical physicists and radiologists. It also demonstrated that statistical iterative reconstructions have the potential to reduce the delivered dose without impairing the quality of the diagnosis. Among the different types of iterative reconstructions, model-based ones offer the greatest potential, since images produced using this modality can still lead to an accurate diagnosis even when acquired at very low dose. This work has clarified the role of medical physicists when dealing with CT imaging. The use of the standard metrics used in the field of CT imaging remains quite important when dealing with the assessment of unit compliance to legal requirements, but the use of a model observer is the way to go when dealing with the optimisation of the imaging protocols.