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High Image Matrix CT Reconstruction

High Image Matrix CT Reconstruction

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT02610465
Enrollment
148
Registered
2015-11-20
Start date
2015-11-09
Completion date
2020-03-27
Last updated
2026-09-14

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cardiac-Related Conditions, Healthy Subjects, Pulmonary-Related Conditions

Keywords

Computed Tomography, Image Reconstruction, Iterative Reconstruction, Natural History

Brief summary

Background: Computed Tomography (CT) scans make detailed pictures of the body in seconds. CT scans make pictures by passing x-rays through a person. CT scans are common. In 2011, around 85.3 million of them occurred in the United States. Researchers think CT images can be made better using new techniques. Higher resolution images can be derived from the original scan. Objective: To learn if new ways of obtaining and processing pictures of the body from a regular CT scan can produce images with higher resolution (pixels) and more information than standard methods. Eligibility: People ages 18 and older who are scheduled to have a CT scan and are not pregnant Design: Participants will be screened with a review of their medical records. Participants will have their scheduled CT scan. The CT scanner used in this study provides enhanced images of inside the body. Researchers may use the CT scanner in a research mode to test and improve the pictures. Images from the CT scan will be reviewed. Any clinical findings from the CT test will be shared with the participant s doctor. Participants will continue to receive their medical care from their regular doctor. The CT images will be entered into an NIH research database. In the future, they may be used for research purposes.

Detailed description

Computed Tomography (CT) images the body. Different methods of creating CT pictures are avilable on a research basis that enables higher resolution imaging using the same aquisition. The purpose of this research study is to learn wheteher these new high resolution images derived from the original CT scan provide similar or perhaps more information than the current standard clinical method.

Interventions

None listed

Sponsors

National Heart, Lung, and Blood Institute (NHLBI)
Lead SponsorNIH

Study design

Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 99 Years
Healthy volunteers
No

Inclusion criteria

* INCLUSION CRITERIA: * Clinical indication for CT * Age equal to or greater than 18 years * Able to understand and willing to sign the Informed Consent Form

Exclusion criteria

-Pregnancy

Design outcomes

Primary

MeasureTime frameDescription
Compare with respect to 7 image quality metrics the overall image quality from a higher resolution CT with traditional clinical standard CT from the same acquisition05/13/2016The primary analysis will compare the overall image quality across the 7 Likert scales between the clinical standard and the high resolution images. For each of the two readers, we will sum each subject s 7 Likert scores for the standard and high resolution images, respectively. Then we will average the two readers standard image cumulative scores, respectively, the two readers high resolution image cumulative scores. Thus for each subject, both the standard and high resolution images will have an average cumulative score between 7 and 34. For each subject, we will compute the difference between the standard image and high resolution image average cumulative scores. The primary analysis will report the mean and its 95% confidence interval for the standard image high resolution image difference. We will also report the median and 5th-95th percentiles of the differences.

Countries

United States

Contacts

PRINCIPAL_INVESTIGATORMarcus Y Chen, M.D.

National Heart, Lung, and Blood Institute (NHLBI)

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Sep 15, 2026