Chest CT at a dose below 0.3 mSv : impact of iterative reconstruction on image quality and lung analysis

Le nombre d'examens tomodensitométriques (Computed Tomography, CT) effectués chaque année étant en constante augmentation, différentes techniques d'optimisation, dont les algorithmes de reconstruction itérative permettant de réduire le bruit tout en maintenant la résolution spatiale, ont étés développées afin de réduire les doses délivrées. Le but de cette étude était d'évaluer l'impact des algorithmes de reconstruction itérative sur la qualité image à des doses effectives inférieures à 0.3 mSv, comparables à celle d'une radiographie thoracique. Vingt CT thoraciques effectués à cette dose effective ont été reconstruits en variant trois paramètres: l'algorithme de reconstruction, rétroprojection filtrée versus reconstruction itérative iDose4; la matrice, 5122 versus 7682; et le filtre de résolution en densité (mou) versus spatiale (dur). Ainsi, 8 séries ont été reconstruites pour chacun des 20 CT thoraciques. La qualité d'image de ces 8 séries a d'abord été évaluée qualitativement par deux radiologues expérimentés en aveugle en se basant sur la netteté des parois bronchiques et de l'interface entre le parenchyme pulmonaire et les vaisseaux, puis quantitativement en utilisant une formule de merit, fréquemment utilisée dans le développement de nouveaux algorithmes et filtres de reconstruction. La performance diagnostique de la meilleure série acquise à une dose effective inférieure à 0.3 mSv a été comparée à celle d'un CT de référence effectué à doses standards en relevant les anomalies du parenchyme pulmonaire. Les résultats montrent que la meilleure qualité d'image, tant qualitativement que quantitativement a été obtenue en utilisant iDose4, la matrice 5122 et le filtre mou, avec une concordance parfaite entre les classements quantitatif et qualitatif des 8 séries. D'autre part, la détection des nodules pulmonaires de plus de 4mm étaient similaire sur la meilleure série acquise à une dose effective inférieure à 0.3 mSv et le CT de référence. En conclusion, les CT thoraciques effectués à une dose effective inférieure à 0.3 mSv reconstruits avec iDose4, la matrice 5122 et le filtre mou peuvent être utilisés avec confiance pour diagnostiquer les nodules pulmonaires de plus de 4mm.

Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 1).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality at CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Effect of Antecolic versus Retrocolic Gastroenteric Reconstruction after Pancreaticoduodenectomy on Delayed Gastric Emptying: A Meta-Analysis of Six Randomized Controlled Trials.

BACKGROUND: One of the most frequent complications of pancreaticoduodenectomy (PD) is delayed gastric emptying (DGE). The study aim was to evaluate the impact of the type of gastro/duodenojejunal reconstruction (antecolic vs. retrocolic) after PD on DGE incidence. METHODS: A systematic review was made according to the PRISMA guidelines. Randomized controlled trials (RCTs) comparing antecolic vs. retrocolic reconstruction were included irrespective of the PD techniques. A meta-analysis was then performed. RESULTS: Six RCTs were included for a total of 588 patients. The overall quality was good. General risk of bias was low. DGE was not statistically significantly different between the antecolic and retrocolic group (OR 0.6, 95% CI 0.31-1.16, p = 0.13). The other main surgery-related complications (pancreatic fistula, hemorrhage, intra-abdominal abscess, bile leak and wound infection) were not dependent on the reconstruction route (OR 0.84, 95% CI 0.41-1.70, p = 0.63). No statistically significant difference in terms of length of hospital stay was found between the 2 groups. There was also no difference of DGE incidence if only pylorus-preserving PD was considered and between the DGE grades A, B or C. CONCLUSION: This meta-analysis shows that antecolic reconstruction after PD is not superior to retrocolic reconstruction in terms of DGE.

Optimization of Radiation Dose and Image Quality in Musculoskeletal CT: Emphasis on Iterative Reconstruction Techniques (Part 2).

Computed tomography (CT) is a modality of choice for the study of the musculoskeletal system for various indications including the study of bone, calcifications, internal derangements of joints (with CT arthrography), as well as periprosthetic complications. However, CT remains intrinsically limited by the fact that it exposes patients to ionizing radiation. Scanning protocols need to be optimized to achieve diagnostic image quality at the lowest radiation dose possible. In this optimization process, the radiologist needs to be familiar with the parameters used to quantify radiation dose and image quality. CT imaging of the musculoskeletal system has certain specificities including the focus on high-contrast objects (i.e., in CT of bone or CT arthrography). These characteristics need to be taken into account when defining a strategy to optimize dose and when choosing the best combination of scanning parameters. In the first part of this review, we present the parameters used for the evaluation and quantification of radiation dose and image quality. In the second part, we discuss different strategies to optimize radiation dose and image quality of CT, with a focus on the musculoskeletal system and the use of novel iterative reconstruction techniques.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Aortic root morphology: a paradigm for successful reconstruction.

Aortic root (AoR) components provide synchronous and precise 3D deformation of the aortic root during the cardiac cycle in order to ensure closure and opening of the three leaflets over a lifetime. Any deviation from the natural 3D morphology, such as with AoR annulus dilatation, enlarged sinuses and/or dilatation of the sinotubular junction, as in the case of ascending aortic dilatation, may result in disruption of the natural AoR function. Surgical treatment of AoR pathology has two modalities: the replacement of the aortic valve by artificial prosthesis or by preservation of the three leaflets and reconstruction of the aortic root components. Currently, there are two basic aortic root reconstruction procedures: aortic root sparing and aortic valve reimplantation techniques. Regardless of the technique used, the restoration of adequate cusp coaptation, is from a technical point of view, the most important element to consider. To achieve this, there are two requirements that need to be met: (i) the valve coaptation should be superior to the level of the aortic root base by at least 8 mm and (ii) the coaptation height per se has to be ≥5 mm. Successful restoration of the aortic root requires adequate technical skills, detailed knowledge of aortic root anatomy and topography, and also knowledge of the spatial pattern of AoR elements. Recently, there has been growing interest in aortic root reconstructive procedures as well their modifications. As such, the aim of this review is to analyse aortic root topography and 3D anatomy from a surgical point of view. The review also focuses on potential risk regions that one should be aware of before the surgical journey into the 'deep waters area' of the AoR begins.

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.

Optimization of OSEM parameters in myocardial perfusion imaging reconstruction as a function of body mass index: a clinical approach

AbstractObjective:The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients' body mass index.Materials and Methods:The present study included 28 adult patients submitted to myocardial perfusion imaging in a public hospital. The OSEM method was utilized in the images reconstruction with six different combinations of iterations and subsets numbers. The images were analyzed by nuclear cardiology specialists taking their diagnostic value into consideration and indicating the most appropriate images in terms of diagnostic quality.Results:An overall scoring analysis demonstrated that the combination of four iterations and four subsets has generated the most appropriate images in terms of diagnostic quality for all the classes of body mass index; however, the role played by the combination of six iterations and four subsets is highlighted in relation to the higher body mass index classes.Conclusion:The use of optimized parameters seems to play a relevant role in the generation of images with better diagnostic quality, ensuring the diagnosis and consequential appropriate and effective treatment for the patient.

Reconstruction and analysis of surface variation using photometric stereo

In many industrial applications, accurate and fast surface reconstruction is essential for quality control. Variation in surface finishing parameters, such as surface roughness, can reflect defects in a manufacturing process, non-optimal product operational efficiency, and reduced life expectancy of the product. This thesis considers reconstruction and analysis of high-frequency variation, that is roughness, on planar surfaces. Standard roughness measures in industry are calculated from surface topography. A fast and non-contact method to obtain surface topography is to apply photometric stereo in the estimation of surface gradients and to reconstruct the surface by integrating the gradient fields. Alternatively, visual methods, such as statistical measures, fractal dimension and distance transforms, can be used to characterize surface roughness directly from gray-scale images. In this thesis, the accuracy of distance transforms, statistical measures, and fractal dimension are evaluated in the estimation of surface roughness from gray-scale images and topographies. The results are contrasted to standard industry roughness measures. In distance transforms, the key idea is that distance values calculated along a highly varying surface are greater than distances calculated along a smoother surface. Statistical measures and fractal dimension are common surface roughness measures. In the experiments, skewness and variance of brightness distribution, fractal dimension, and distance transforms exhibited strong linear correlations to standard industry roughness measures. One of the key strengths of photometric stereo method is the acquisition of higher frequency variation of surfaces. In this thesis, the reconstruction of planar high-frequency varying surfaces is studied in the presence of imaging noise and blur. Two Wiener filterbased methods are proposed of which one is optimal in the sense of surface power spectral density given the spectral properties of the imaging noise and blur. Experiments show that the proposed methods preserve the inherent high-frequency variation in the reconstructed surfaces, whereas traditional reconstruction methods typically handle incorrect measurements by smoothing, which dampens the high-frequency variation.

Splat-based surface reconstruction from defect-laden point sets

We introduce a method for surface reconstruction from point sets that is able to cope with noise and outliers. First, a splat-based representation is computed from the point set. A robust local 3D RANSAC-based procedure is used to filter the point set for outliers, then a local jet surface - a low-degree surface approximation - is fitted to the inliers. Second, we extract the reconstructed surface in the form of a surface triangle mesh through Delaunay refinement. The Delaunay refinement meshing approach requires computing intersections between line segment queries and the surface to be meshed. In the present case, intersection queries are solved from the set of splats through a 1D RANSAC procedure

Patson Approach versus the Standard Approach for increasing breast reconstruction rates in women undergoing mastectomy. A randomized, controlled, open-label clinical trial

Breast cancer is the most prevalent neoplasm among women in the majority of countries worldwide. Breast cancer treatment include mastectomy which is associated to strong impact in women. Breast reconstruction is an option for many women to re-establish their body image and also to decrease psychological impact. However, breast reconstruction rates are low and many factors are involved in not undergoing breast reconstruction. Patient involvement in the decision-making process increases breast reconstruction rates and is associated to higher satisfaction and less anxiety and depression symptoms. More physician-patient relation and more education in terms of breast reconstruction are needed to achieve our objective. A new approach of medical care, called Patson Approach, is created in order to meet our goal with more patient involvement, as well as, physician and psychological counsellingObjective: to increase breast reconstruction rates in women who are candidates for breast reconstruction after mastectomy and are included in the Patson Approach compared to women included in the Standard ApproachMethods: the study design will be a randomized, controlled, open-label clinical trial. 62 patients will be recruited during two years and randomly divided in two groups, 31 will be included in the Standard Approach and 31 will be included in the Patson Approach. Preoperative and postoperative appointments are established in order to do a follow-up of the patients and collect all the data