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.

PFO closure vs. medical therapy in cryptogenic stroke or transient ischemic attack: A systematic review and meta-analysis.

BACKGROUND/OBJECTIVES: This study aims to assess whether patent foramen ovale (PFO) closure is superior to medical therapy in preventing recurrence of cryptogenic ischemic stroke or transient ischemic attack (TIA). METHODS: We searched PubMed for randomized trials which compared PFO closure with medical therapy in cryptogenic stroke/TIA using the items: "stroke or cerebrovascular accident or TIA" and "patent foramen ovale or paradoxical embolism" and "trial or study". RESULTS: Among 650 potentially eligible articles, 3 were included including 2303 patients. There was no statistically significant difference between PFO-closure and medical therapy in ischemic stroke recurrence (1.91% vs. 2.94% respectively, OR: 0.64, 95%CI: 0.37-1.10), TIA (2.08% vs. 2.42% respectively, OR: 0.87, 95%CI: 0.50-1.51) and death (0.60% vs. 0.86% respectively, OR: 0.71, 95%CI: 0.28-1.82). In subgroup analysis, there was significant reduction of ischemic strokes in the AMPLATZER PFO Occluder arm vs. medical therapy (1.4% vs. 3.04% respectively, OR: 0.46, 95%CI: 0.21-0.98, relative-risk-reduction: 53.2%, absolute-risk-reduction: 1.6%, number-needed-to-treat: 61.8) but not in the STARFlex device (2.7% vs. 2.8% with medical therapy, OR: 0.93, 95%CI: 0.45-2.11). Compared to medical therapy, the number of patients with new-onset atrial fibrillation (AF) was similar in the AMPLATZER PFO Occluder arm (0.72% vs. 1.28% respectively, OR: 1.81, 95%CI: 0.60-5.42) but higher in the STARFlex device (0.64% vs. 5.14% respectively, OR: 8.30, 95%CI: 2.47-27.84). CONCLUSIONS: This meta-analysis does not support PFO closure for secondary prevention with unselected devices in cryptogenic stroke/TIA. In subgroup analysis, selected closure devices may be superior to medical therapy without increasing the risk of new-onset AF, however. This observation should be confirmed in further trials using inclusion criteria for patients with high likelihood of PFO-related stroke recurrence.

Images in clinical urology. Nail of glans penis.

A 56-year-old man presented with a "nail" growing at the base of his glans penis. The tumor was locally excised, and microscopic examination revealed papillomatosis and hyperkeratosis of the malpighian epithelium, with a strong inflammatory reaction of the chorion and signs of local microinvasion, as well as the presence of well-differentiated squamous epithelial cells. The surgical margins were negative. The differential diagnosis was made between a benign papillomatous proliferation and verrucous carcinoma.

Training medical students to conduct motivational interviewing: a randomized controlled trial.

OBJECTIVE: To examine the effectiveness of motivational interviewing (MI) training among medical students. METHODS: All students (n=131) (year 5) at Lausanne Medical School, Switzerland were randomized into an experimental or a control group. After a training in basic communication skills (control condition), an 8-h MI training was completed by 84.8% students in the exprimental group. One week later, students in both groups were invited to meet with two standardized patients. MI skills were coded by blinded research assistants using the Motivational Interviewing Treatment Integrity 3.0. RESULTS: Superior MI performance was shown for trained versus control students, as demonstrated by higher scores for "Empathy" [p<0.001] and "MI Spirit" [p<0.001]. Scores were similar between groups for "Direction", indicating that students in both groups invited the patient to talk about behavior change. Behavior counts assessment demonstrated better performance in MI in trained versus untrained students regarding occurences of MI-adherent behavior [p<0.001], MI non-adherent behavior [p<0.001], Closed questions [p<0.001], Open questions [p=0.001], simple reflections [p=0.03], and Complex reflections [p<0.001]. Occurrences were similar between groups regarding "Giving information". CONCLUSION: An 8-h training workshop was associated with improved MI performance. PRACTICE IMPLICATIONS: These findings lend support for the implementation of MI training in medical schools.

Trends of pre-hospital emergency medical services activity over 10 years : a population-based registry analysis

BACKGROUND: The number of requests to pre-hospital emergency medical services (PEMS) has increased in Europe over the last 20 years, but epidemiology of PEMS interventions has little be investigated. The aim of this analysis was to describe time trends of PEMS activity in a region of western Switzerland. METHODS: Use of data routinely and prospectively collected for PEMS intervention in the Canton of Vaud, Switzerland, from 2001 to 2010. This Swiss Canton comprises approximately 10% of the whole Swiss population. RESULTS: We observed a 40% increase in the number of requests to PEMS between 2001 and 2010. The overall rate of requests was 35/1000 inhabitants for ambulance services and 10/1000 for medical interventions (SMUR), with the highest rate among people aged ≥ 80. Most frequent reasons for the intervention were related to medical problems, predominantly unconsciousness, chest pain respiratory distress, or cardiac arrest, whereas severe trauma interventions decreased over time. Overall, 89% were alive after 48 h. The survival rate after 48 h increased regularly for cardiac arrest or myocardial infarction. CONCLUSION: Routine prospective data collection of prehospital emergency interventions and monitoring of activity was feasible over time. The results we found add to the understanding of determinants of PEMS use and need to be considered to plan use of emergency health services in the near future. More comprehensive analysis of the quality of services and patient safety supported by indicators are also required, which might help to develop prehospital emergency services and new processes of care.

Does readiness to change predict subsequent alcohol consumption in medical inpatients with unhealthy alcohol use?

We studied whether readiness to change predicts alcohol consumption (drinks per day) 3 months later in 267 medical inpatients with unhealthy alcohol use. We used 3 readiness to change measures: a 1 to 10 visual analog scale (VAS) and two factors of the Stages of Change Readiness and Treatment Eagerness Scale: Perception of Problems (PP) and Taking Action (TA). Subjects with the highest level of VAS-measured readiness consumed significantly fewer drinks 3 months later [Incidence rate ratio (IRR) and 95% confidence interval (CI): 0.57 (0.36, 0.91) highest vs. lowest tertile]. Greater PP was associated with more drinking [IRR (95%CI): 1.94 (1.02, 3.68) third vs. lowest quartile]. Greater TA scores were associated with less drinking [IRR (95%CI): 0.42 (0.23, 0.78) highest vs. lowest quartile]. Perception of Problems' association with more drinking may reflect severity rather than an aspect of readiness associated with ability to change; high levels of Taking Action appear to predict less drinking. Although assessing readiness to change may have clinical utility, assessing the patient's planned actions may have more predictive value for future improvement in alcohol consumption.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.