422 research outputs found
Author Correction: Attributes and predictors of long COVID
No full textIn the version of this article initially published, linkage of the following authors to affiliation 3 (Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK) was incorrect: Benjamin Murray, Thomas Varsavsky, Mark S. Graham, Kerstin Klaser, Michela Antonelli, Liane S. Canas, Erika Molteni, Marc Modat, M. Jorge Cardoso and Sebastien Ourselin. The correct linkage is to affiliation 1 (School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK). The error has been corrected in the HTML and PDF versions of the article
Author Correction: Attributes and predictors of long COVID
No full textIn the version of this article initially published, linkage of the following authors to affiliation 3 (Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK) was incorrect: Benjamin Murray, Thomas Varsavsky, Mark S. Graham, Kerstin Klaser, Michela Antonelli, Liane S. Canas, Erika Molteni, Marc Modat, M. Jorge Cardoso and Sebastien Ourselin. The correct linkage is to affiliation 1 (School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK). The error has been corrected in the HTML and PDF versions of the article.</p
Atazanavir/ritonavir monotherapy: 96 week efficacy, safety and bone mineral density from the MODAt randomized trial
No full textTo report the 96 week results on efficacy, safety and bone mineral density (BMD) in subjects with HIV-1 that were virologically suppressed and treated with atazanavir/ritonavir monotherapy versus atazanavir/ritonavir triple therapy
GAS: A genetic atlas selection strategy in multi-atlas segmentation framework
No full textMulti-Atlas based Segmentation (MAS) algorithms have been successfully applied to many medical image segmentation tasks, but their success relies on a large number of atlases and good image registration performance. Choosing well-registered atlases for label fusion is vital for an accurate segmentation. This choice becomes even more crucial when the segmentation involves organs characterized by a high anatomical and pathological variability. In this paper, we propose a new genetic atlas selection strategy (GAS) that automatically chooses the best subset of atlases to be used for segmenting the target image, on the basis of both image similarity and segmentation overlap. More precisely, the key idea of GAS is that if two images are similar, the performances of an atlas for segmenting each image are similar. Since the ground truth of each atlas is known, GAS first selects a predefined number of similar images to the target, then, for each one of them, finds a near-optimal subset of atlases by means of a genetic algorithm. All these near-optimal subsets are then combined and used to segment the target image. GAS was tested on single-label and multi-label segmentation problems. In the first case, we considered the segmentation of both the whole prostate and of the left ventricle of the heart from magnetic resonance images. Regarding multi-label problems, the zonal segmentation of the prostate into peripheral and transition zone was considered. The results showed that the performance of MAS algorithms statistically improved when GAS is used
Atazanavir/ritonavir monotherapy : 96 week efficacy, safety and bone mineral density from the MODAt randomized trial
No full textObjectives: To report the 96 week results on efficacy, safety and bone mineral density (BMD) in subjects with HIV-1 that were virologically suppressed and treated with atazanavir/ritonavir monotherapy versus atazanavir/ ritonavir triple therapy. Methods: MODAt is a prospective, multicentre, open-label, non-inferiority, randomized, 96 week trial (NCT01511809) comparing efficacy of atazanavir/ritonavir monotherapy versus atazanavir/ritonavir triple therapy. Treatment success was defined as no occurrence of confirmed viral rebound (two consecutive HIV-RNA >50 copies/mL) or discontinuation for any cause of the ongoing regimen. Results: The 96 week treatment success was 64% in the atazanavir/ritonavir monotherapy arm and 63% in the triple-therapy arm (difference 1.3%, 95% CI: 217.5 to 20.1). In the atazanavir/ritonavir monotherapy arm, no PI- or NRTI-associated resistance mutations were observed at virological failure and all patients re-suppressed after re-intensification. In the monotherapy arm, treatment failure was more frequent in patients coinfected with hepatitis C virus [64%versus 28%(difference 35.4%, 95%CI: 3.7-67.2)]. Drug-related adverse events leading to discontinuation were 3 (6%) in the atazanavir/ritonavir monotherapy arm and 11 (21.5%) in the triple-therapy arm(P=0.041). The 96 week adjusted mean percentage change in total proximal femur (not at lumbar spine) BMD was +1.16% and 21.64% in the atazanavir/ritonavir monotherapy arm and the triple-therapy arm, respectively (P=0.012). Conclusions: The 96 week analyses suggested that long-term efficacy of atazanavir/ritonavir monotherapy was inferior as compared with atazanavir/ritonavir triple therapy, particularly when administered in subjects coinfected with hepatitis C virus. In the atazanavir/ritonavir monotherapy arm, reintroduction of nucleosides, as needed, was always effective with no new resistance mutation; monotherapy was also associated with a lower incidence of adverse events and improvement in femur BMD
Automated registration of 3D TEE datasets of the descending aorta for improved examination and quantication of atheromas burden
No full textAtazanavir/ritonavir monotherapy: 96 week efficacy, safety and bone mineral density from the MODAt randomized trial
No full textObjectives: To report the 96 week results on efficacy, safety and bone mineral density (BMD) in subjects with HIV-1 that were virologically suppressed and treated with atazanavir/ritonavir monotherapy versus atazanavir/ ritonavir triple therapy. Methods: MODAt is a prospective, multicentre, open-label, non-inferiority, randomized, 96 week trial (NCT01511809) comparing efficacy of atazanavir/ritonavir monotherapy versus atazanavir/ritonavir triple therapy. Treatment success was defined as no occurrence of confirmed viral rebound (two consecutive HIV-RNA >50 copies/mL) or discontinuation for any cause of the ongoing regimen. Results: The 96 week treatment success was 64% in the atazanavir/ritonavir monotherapy arm and 63% in the triple-therapy arm (difference 1.3%, 95% CI: 217.5 to 20.1). In the atazanavir/ritonavir monotherapy arm, no PI- or NRTI-associated resistance mutations were observed at virological failure and all patients re-suppressed after re-intensification. In the monotherapy arm, treatment failure was more frequent in patients coinfected with hepatitis C virus [64%versus 28%(difference 35.4%, 95%CI: 3.7-67.2)]. Drug-related adverse events leading to discontinuation were 3 (6%) in the atazanavir/ritonavir monotherapy arm and 11 (21.5%) in the triple-therapy arm(P=0.041). The 96 week adjusted mean percentage change in total proximal femur (not at lumbar spine) BMD was +1.16% and 21.64% in the atazanavir/ritonavir monotherapy arm and the triple-therapy arm, respectively (P=0.012). Conclusions: The 96 week analyses suggested that long-term efficacy of atazanavir/ritonavir monotherapy was inferior as compared with atazanavir/ritonavir triple therapy, particularly when administered in subjects coinfected with hepatitis C virus. In the atazanavir/ritonavir monotherapy arm, reintroduction of nucleosides, as needed, was always effective with no new resistance mutation; monotherapy was also associated with a lower incidence of adverse events and improvement in femur BMD
Potential associations between atazanavir exposure and clinical outcome: a pharmacokinetic sub-study from the MODAt randomized trial
No full textThe 96-week results of the Monotherapy Once a Day with Atazanavir/r (MODAt) study [NCT01511809] showed an inferior virological efficacy of atazanavir (ATV)/ritonavir monotherapy versus triple therapy, which was promptly retrieved by the reintroduction of nucleoside/nucleotide inhibitors of reverse transcriptase [N(n)RTIs]. We aimed to identify potential relationships between ATV exposure and clinical outcome in HIV-1 subjects treated with ATV/ritonavir monotherapy [ATV/r 300/100mg] versus ATV/ritonavir triple therapy [ATV/r 300/100mg+2NRTIs]. A chromatographic method coupled with tandem mass spectrometry was applied to analyze ATV plasma concentrations in a pharmacokinetic sub-study from the MODAt trial. Mixed linear models were used to examine the ATV plasma concentration trend during follow-up and to assess the association between ATV plasma concentrations trajectories with the study arm or the occurrence of treatment failure or drug-related adverse events or the grading of baseline total bilirubin (<3 vs ≥3). The analyses were performed using SAS Software, release 9.4 (SAS Institute, Cary, NC, USA). Overall, ATV plasma Ctrough concentration did not vary during follow-up (slope: +0.75 ng/mL/week, 95%CI: -0.97 to 2.47, p=0.387); trajectories did not differ between study arms 2 (p=0.527). The unadjusted model-based means (95%CI) of ATV Ctrough during follow-up were 835 (95%CI: 657-1012) ng/ml in the ATV/r monotherapy arm as compared to 911 (95%CI: 740-1082) ng/mL in the ATV/r triple therapy arm (p=0.621). Mean ATV Ctrough was similar in subjects with or without adverse events (AEs). Subjects treated with ATV/r monotherapy showed significantly higher ATV concentrations as compared to subjects without adverse events or treated with ATV/r triple therapy. ATV concentrations were associated with the grading of baseline total bilirubin and the occurrence of drug-related AEs but not with HCV infection. Our findings showed a lack of association between ATV concentrations and treatment failure both in ATV/r monotherapy and triple therapy. Conversely, these data emphasized that ATV concentrations are associated with the development of side-effects in both subjects treated with ATV/r monotherapy and subjects treated with ATV/r triple therapy
Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI.
No full textPreterm birth is a major public health concern, with the severity and occurrence of adverse outcome increasing with earlier delivery. Being born preterm disrupts a time of rapid brain development: in addition to volumetric growth, the cortex folds, myelination is occurring and there are changes on the cellular level. These neurological events have been imaged non-invasively using diffusion-weighted (DW) MRI. In this population, there has been a focus on examining diffusion in the white matter, but the grey matter is also critically important for neurological health. We acquired multi-shell high-resolution diffusion data on 12 infants born at ≤28weeks of gestational age at two time-points: once when stable after birth, and again at term-equivalent age. We used the Neurite Orientation Dispersion and Density Imaging model (NODDI) (Zhang et al., 2012) to analyse the changes in the cerebral cortex and the thalamus, both grey matter regions. We showed region-dependent changes in NODDI parameters over the preterm period, highlighting underlying changes specific to the microstructure. This work is the first time that NODDI parameters have been evaluated in both the cortical and the thalamic grey matter as a function of age in preterm infants, offering a unique insight into neuro-development in this at-risk population
Geodesic Information Flows: Spatially-Variant Graphs and Their Application to Segmentation and Fusion
No full textClinical annotations, such as voxel-wise binary or probabilistic tissue segmentations, structural parcellations, pathological regionsof- interest and anatomical landmarks are key to many clinical studies. However, due to the time consuming nature of manually generating these annotations, they tend to be scarce and limited to small subsets of data. This work explores a novel framework to propagate voxel-wise annotations between morphologically dissimilar images by diffusing and mapping the available examples through intermediate steps. A spatially-variant graph structure connecting morphologically similar subjects is introduced over a database of images, enabling the gradual diffusion of information to all the subjects, even in the presence of large-scale morphological variability. We illustrate the utility of the proposed framework on two example applications: brain parcellation using categorical labels and tissue segmentation using probabilistic features. The application of the proposed method to categorical label fusion showed highly statistically significant improvements when compared to state-of-the-art methodologies. Significant improvements were also observed when applying the proposed framework to probabilistic tissue segmentation of both synthetic and real data, mainly in the presence of large morphological variability
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