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Dataset results
1,053 results for “Computed Tomography”
Multislice Computed Tomography Assessment of PCSK9 Inhibition on Coronary Perfusion
ClinicalTrials.gov study NCT03851263. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Follow-up of Coronary Artery Bypass Graft Patency by Multislice Computed Tomography
ClinicalTrials.gov study NCT00712153. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Role of Screening With Coronary Computed Tomography Angiography in Primary Prevention of Coronary Heart Disease
ClinicalTrials.gov study NCT05431309. IPD Sharing: NO. Countries: 0. Publications: 0.
Ventricular Size and Value Calcification Measures by Computed Tomography - Ancillary to MESA
ClinicalTrials.gov study NCT00065780. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Automatic Versus Semiautomatic Registration of Digital Dental Cast to Cone Beam Computed Tomography Image
ClinicalTrials.gov study NCT04563117. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Computed Tomography Laser Mammography Breast Imaging Device
ClinicalTrials.gov study NCT00589043. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Relationship Between Computed Tomography Manifestation and Histopathological Classification of Thymic Epithelial Tumors
ClinicalTrials.gov study NCT03288662. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Computed Tomography-guided Brachytherapy Plus Chemotherapy for Locally Recurrent Rectum Cancer
ClinicalTrials.gov study NCT02423226. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Dual-Energy Computed Tomography for Improving Imaging Assessment of Multiple Myeloma
ClinicalTrials.gov study NCT05353907. IPD Sharing: Not stated. Countries: 0. Publications: 0.
18F-2-fluoro-2-deoxy-D-glucose in Positron Emission Tomography Computed Tomography
ClinicalTrials.gov study NCT04615156. IPD Sharing: NO. Countries: 0. Publications: 0.
Computed Tomography-derived Fractional Flow Reserve vs. Angiographic Quantitative Flow Ratio in Management of Patients With Coronary Artery Disease
ClinicalTrials.gov study NCT07308496. IPD Sharing: NO. Countries: 0. Publications: 0.
Cone Beam Computed Tomography Versus Intraoral Digital Radiography in Detection and Measurements of Simulated Periodontal Bone Defects
ClinicalTrials.gov study NCT03729843. IPD Sharing: Not stated. Countries: 0. Publications: 0.
SnowEx20 Grand Mesa IOP Computed Tomography Snow Microstructure V001
This data set characterizes snow microstructure for 6 snow pits from the SnowEx 2020 Grand Mesa Intensive Observation Period (February 2020) using microcomputed tomography (micro-CT). Included with this data set are two- and three-dimensional microstructural analysis of DMP/DEP casted and un-casted snow samples, available as .xlsx and .txt file, and visual representations of the three-dimensional snow structure, available is .bmp image files. Containers of snow were collected at 6 snow pits in approximately 17 cm intervals. There were approximately 5-8 discrete containers per pit and each container had an ~2 cm overlap with the sample below. A 6-cm section of snow was dissected from each container of snow, which were analyzed in ~2 cm sub-sections. Each sub-section was scanned in three intervals using a micro-CT instrument. The three interval scans comprise multiple slices, and were combined into the reconstructed final scan used for calculating the snow microstructural data.
37-Day microgravity exposure in 16-Week female C57BL/6J mice during the NASA Rodent Research 1 mission is associated with bone loss specific to weight-bearing skeletal sites (femur and vertebrae, micro computed tomography)
Exposure to weightlessness in microgravity and elevated space radiation are associated with rapid bone loss in mammals, but questions remain about their mechanisms of action and relative importance. In this study, we tested the hypothesis that bone loss during spaceflight in Low Earth Orbit is primarily associated with site-specific microgravity unloading of weight-bearing sites in the skeleton. Microcomputed tomography and histological analyses of bones from mice space flown on ISS for 37 days in the NASA Rodent Research-1 experiment show significant site-specific cancellous and cortical bone loss occurring in the femur, but not in L2 vertebrae. The lack of bone degenerative effects in the spine in combination with same-animal paired losses in the femur suggests that space radiation levels in Low Earth Orbit or other systemic stresses are not likely to significantly contribute to the observed bone loss. Remarkably, spaceflight is also associated with accelerated progression of femoral head endochondral ossification. This suggests the microgravity environment promotes premature progression of secondary ossification during late stages of skeletal maturation at 21 weeks. Furthermore, mice housed in the NASA ISS Rodent Habitat during 1g ground controls maintained or gained bone relative to mice housed in standard vivarium cages that showed significant bone mass declines. These findings suggest that housing in the Rodent Habitat with greater topological enrichment from 3D wire-mesh surfaces may promote increased mechanical loading of weight-bearing bones and maintenance of bone mass. In summary, our results indicate that in female mice approaching skeletal maturity, mechanical unloading of weight-bearing sites is the major cause of bone loss in microgravity, while sites loaded predominantly by muscle activity, such as the spine, appear unaffected. Additionally, we identified early-onset of femoral head epiphyseal plate secondary ossification as a novel spaceflight skeletal unloading effect that may lead to premature long bone growth arrest in microgravity. This study derives results from femur and vertebrae using the micro computed tomography assay.
Dataset related to article "Predicting survival and local control after radiochemotherapy in locally advanced head and neck cancer by means of computed tomography based radiomics."
<p>PURPOSE:</p> <p>To appraise the ability of a radiomics signature to predict clinical outcome after definitive radiochemotherapy (RCT) of stage III-IV head and neck cancer.</p> <p>METHODS:</p> <p>A cohort of 110 patients was included in a retrospective analysis. Radiomics texture features were extracted from the gross tumor volumes contoured on planning computed tomography (CT) images. The cohort of patients was randomly divided into a training (70 patients) and a validation (40 patients) cohorts. Textural features were correlated to survival and control data to build predictive models. All the significant predictors of the univariate analysis were included in a multivariate model. The quality of the models was appraised by means of the concordance index (CI).</p> <p>RESULTS:</p> <p>A signature with 3 features was identified as predictive of overall survival (OS) with CI = 0.88 and 0.90 for the training and validation cohorts, respectively. A signature with 2 features was identified for progression-free survival (PFS; CI = 0.72 and 0.80); 2 features also characterized the signature for local control (LC; CI = 0.72 and 0.82). In all cases, the stratification in high- and low-risk groups for the training and validation cohorts led to significant differences in the actuarial curves. In the validation cohort the mean OS times (in months) were 78.9 ± 2.1 vs 67.4 ± 6.0 in the low- and high-risk groups, respectively, the PFS was 73.1 ± 3.7 and 50.7 ± 7.2, while the LC was 78.7 ± 2.1 and 63.9 ± 6.5.</p> <p>CONCLUSION:</p> <p>CT-based radiomic signatures that correlate with survival and control after RCT were identified and allow low- and high-risk groups of patients to be identified.</p>
Dataset related to article "Computed tomography (CT)-derived radiomic features differentiate prevascular mediastinum masses as thymic neoplasms versus lymphomas"
<p>This record contains raw data related to article "Computed tomography (CT)-derived radiomic features differentiate prevascular mediastinum masses as thymic neoplasms versus lymphomas"</p> <p><strong>Objectives: </strong>We aimed to assess the ability of radiomics, applied to not-enhanced computed tomography (CT), to differentiate mediastinal masses as thymic neoplasms vs lymphomas.</p> <p><strong>Methods: </strong>The present study was an observational retrospective trial. Inclusion criteria were pathology-proven thymic neoplasia or lymphoma with mediastinal localization, availability of CT. Exclusion criteria were age < 16 years and mediastinal lymphoma lesion < 4 cm. We selected 108 patients (M:F = 47:61, median age 48 years, range 17-79) and divided them into a training and a validation group. Radiomic features were used as predictors in linear discriminant analysis. We built different radiomic models considering segmentation software and resampling setting. Clinical variables were used as predictors to build a clinical model. Scoring metrics included sensitivity, specificity, accuracy and area under the curve (AUC). Wilcoxon paired test was used to compare the AUCs.</p> <p><strong>Results: </strong>Fifty-five patients were affected by thymic neoplasia and 53 by lymphoma. In the validation analysis, the best radiomics model sensitivity, specificity, accuracy and AUC resulted 76.2 ± 7.0, 77.8 ± 5.5, 76.9 ± 6.0 and 0.84 ± 0.06, respectively. In the validation analysis of the clinical model, the same metrics resulted 95.2 ± 7.0, 88.9 ± 8.9, 92.3 ± 8.5 and 0.98 ± 0.07, respectively. The AUCs of the best radiomic and the clinical model not differed.</p> <p><strong>Conclusions: </strong>We developed and validated a CT-based radiomic model able to differentiate mediastinal masses on non-contrast-enhanced images, as thymic neoplasms or lymphoma. The proposed method was not affected by image postprocessing. Therefore, the present image-derived method has the potential to noninvasively support diagnosis in patients with prevascular mediastinal masses with major impact on management of asymptomatic cases.</p> <p> </p>
Reconstruction software: 4D imaging of two-phase flow in porous media using laboratory-based micro-Computed Tomography
<p>This repository contains the dataset and the computed tomography (CT) reconstruction software used in the journal article "4D imaging of two-phase flow in porous media using laboratory-based micro-Computed Tomography". </p>
Incidental findings from cone-beam computed tomographies in children and adolescents: a systematic review
<p>Dataset with all data for the systematic review.</p> <p>Dataset will be initially made available to editor and peer reviewers only and to everyone without any restrictions after journal acceptance.</p>
Figure 2 in Trigonotarbus johnsoni Pocock, 1911, revealed by X-ray computed tomography, with a cladistic analysis of the extinct trigonotarbid arachnids
Figure 2. Hand specimens of Trigonotarbus johnsoni from the NHMUK collections. Scale bars = 1 mm.
Comparing Single Photon Emission Computed Tomography (SPECT) and Liver Biopsy to Evaluate the Liver in Patients With HIV and Hepatitis C Virus
ClinicalTrials.gov study NCT00006643. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.