Accuracy Evaluation of SIS Software-based Visualization of New Anatomical Brain Structure

NCT ID: NCT04814277

Last Updated: 2023-11-22

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

34 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-10-26

Study Completion Date

2021-01-11

Brief Summary

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SIS has developed a software technology, based on machine learning and image processing, designed to enhance standard clinical images for the visualization of anatomical structures.

Detailed Description

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A cohort of 34 subjects will be scanned on a clinical MRI scanner as well as on a 7 Tesla (7T) scanner. Images acquired on the 7T allow to visualize anatomical structures that are not easily identified on standard clinical images.

SIS software will be used to visualize selected anatomical features on the clinical image and the results will be compared with the images in the same subject obtained from the 7T MRI.

Conditions

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Software Evaluation for Visualizing Anatomical Structures Not Typically Identified on Clinical MR Images

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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MRI Data Collection

A group of 34 subjects will be scanned on a 3Tesla (3T) and on a 7T MRI scanner. The images will be compared.

No interventions assigned to this group

Eligibility Criteria

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Exclusion Criteria

2. Pregnant women.
3. Subject under the age of 18.
Minimum Eligible Age

18 Years

Maximum Eligible Age

85 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Surgical Information Sciences Inc.

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Surgical Information Sciences

Plymouth, Minnesota, United States

Site Status

Countries

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United States

Other Identifiers

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DOC-0055

Identifier Type: -

Identifier Source: org_study_id