PixelShine vs. Iterative Reconstruction (IR) Processing of CT Images

June 26, 2017 updated by: AlgoMedica, Inc.

Prospective Review of CT Imaging Data Comparing Quality of Low-Radiation-Dose Images Post-Processed With Iterative Reconstruction Software vs. Machine Learning (AlgoMedica PixelShine) Software

This study will compare the quality of CT images acquired with very low-dose radiation and processed with commercially available software vs. PixelShine processed images. It would potentially allow imaging facilities to acquire CT scans using lower doses of radiation without sacrificing clarity of CT images. Acquiring high quality CT images with low-dose radiation has the potential to enhance patient safety and has significant implications in imaging practices.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Detailed Description

Patients receiving CT scans as part of their standard treatment will be asked to consent to an additional 5 minutes of imaging using very low-dose radiation prior to the conventional-dose CT scan. The prospective review will be performed in two cohorts: Chest CT scans and abdominal CT scans.

Anonymized images will be processed by conventional CT software and compared to the same images processed with machine-learning-based PixelShine. A board-certified radiologist will assess the noise and visual quality of the imaging data.

Study patients will receive approximately 10% more dose than a standard CT scan by participating in the study. There are no known short-term safety issues associated with this study. The study-related very low dose radiation is at a level far below that used for conventional x-ray imaging. The study has been approved by the Radiation Safety Committee as part of the review process.

Study Type

Interventional

Enrollment (Anticipated)

20

Phase

  • Not Applicable

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • Patients must be 18 years of age or older
  • Patients must be able and willing to consent to participate in this project
  • Patients will be scheduled for a standard of care CT scan

Exclusion Criteria:

  • This study does not investigate either a specific disease or a specific patient population-it only examines and compares images obtained at low radiation exposure post-processed with Algomedica's PixelShine software with conventionally processed images
  • All other patients will be excluded

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Non-Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: Chest CT
Conventional processing vs. PixelShine processing
Device: PixelShine
Machine learning algorithm
Device: Conventional processing
Iterative reconstruction software
Active Comparator: Abdominal CT
Conventional processing vs. PixelShine processing
Device: PixelShine
Machine learning algorithm
Device: Conventional processing
Iterative reconstruction software

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Visual Image Quality as Assessed by Image Noise Reduction
Time Frame: Through study completion, an average of 1 month
Comparison of image noise
Through study completion, an average of 1 month

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Image Resolution as Assessed by Size of Detected Lesions
Time Frame: Through study completion, an average of 1 month
Determine smallest size of detectable objects
Through study completion, an average of 1 month

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

AlgoMedica, Inc.

Collaborators

Cedars-Sinai Medical Center

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

August 1, 2017

Primary Completion (Anticipated)

October 1, 2017

Study Completion (Anticipated)

December 1, 2017

Study Registration Dates

First Submitted

November 5, 2016

First Submitted That Met QC Criteria

January 24, 2017

First Posted (Estimate)

January 27, 2017

Study Record Updates

Last Update Posted (Actual)

June 28, 2017

Last Update Submitted That Met QC Criteria

June 26, 2017

Last Verified

June 1, 2017

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • ALG-002

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

Yes

product manufactured in and exported from the U.S.

Yes

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Cancer, Lung

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Australia

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

3
Subscribe