Lesion Detection Assessment in the Liver: Standard vs Low Radiation Dose Using Varied Post-Processing Techniques
NCT ID: NCT03151564
Last Updated: 2025-09-08
Study Results
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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ACTIVE_NOT_RECRUITING
NA
146 participants
INTERVENTIONAL
2017-05-09
2027-04-30
Brief Summary
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Detailed Description
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To evaluate whether post-processing software Adaptive Statistical Iterative Reconstruction (ASIR), ASIR-V, Veo 3.0 (GE version of Model-based Iterative Reconstruction (MBIR), and Deep Learning Image Reconstruction (DLIR) is able to preserve lesion detection in the liver and other measures of image quality at reduced radiation doses for computed tomography (CT).
Secondary Objectives:
Assessment of whether post-processing software enhances lesion detection in the liver and other measures of image quality at standard and reduced radiation doses.
Assessment of whether DLIR and GSI DLIR reconstructions perform differently, both in terms of accuracy and image quality metrics such as noise reduction.
Conditions
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Study Design
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NON_RANDOMIZED
SINGLE_GROUP
DIAGNOSTIC
SINGLE
Study Groups
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Computed Tomography Scan - 50% Dose Reduction
Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 50% dose reduction.
Computed Tomography Scan - 50% Dose Reduction
Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 50% dose reduction.
Computed tomography Scan - 70% Dose Reduction
Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 70% dose reduction.
Computed Tomography Scan - 70% Dose Reduction
Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 70% dose reduction.
Deep Learning Image Reconstruction (DLIR)
DLIR is available in both single (SE) and dual/multi energy (DE) CT scanning modes. DLIR SECT and DLIR DECT reconstructions have yet to be compared.
Deep Learning Image Reconstruction (DLIR)
Participants to receive standard-of-care imaging without the artificial intelligence software and imaging technique.
Interventions
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Computed Tomography Scan - 50% Dose Reduction
Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 50% dose reduction.
Computed Tomography Scan - 70% Dose Reduction
Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 70% dose reduction.
Deep Learning Image Reconstruction (DLIR)
Participants to receive standard-of-care imaging without the artificial intelligence software and imaging technique.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
2. Men and non-pregnant women
3. Pathology proven diagnosis of colon or colorectal carcinoma
4. Liver metastases on most recent CT examination
5. Standard of care CT abdomen examination planned WITH IV contrast
Exclusion Criteria
2. Patients cannot undergo CT examination
18 Years
90 Years
ALL
No
Sponsors
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M.D. Anderson Cancer Center
OTHER
Responsible Party
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Principal Investigators
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Corey T. Jensen, MD
Role: PRINCIPAL_INVESTIGATOR
M.D. Anderson Cancer Center
Locations
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University of Texas MD Anderson Cancer Center
Houston, Texas, United States
Countries
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References
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Jensen CT, Gupta S, Saleh MM, Liu X, Wong VK, Salem U, Qiao W, Samei E, Wagner-Bartak NA. Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases. Radiology. 2022 Apr;303(1):90-98. doi: 10.1148/radiol.211838. Epub 2022 Jan 11.
Jensen CT, Wagner-Bartak NA, Vu LN, Liu X, Raval B, Martinez D, Wei W, Cheng Y, Samei E, Gupta S. Detection of Colorectal Hepatic Metastases Is Superior at Standard Radiation Dose CT versus Reduced Dose CT. Radiology. 2019 Feb;290(2):400-409. doi: 10.1148/radiol.2018181657. Epub 2018 Nov 27.
Related Links
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MD Anderson Cancer Center
Other Identifiers
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NCI-2018-01272
Identifier Type: OTHER
Identifier Source: secondary_id
2016-1135
Identifier Type: -
Identifier Source: org_study_id
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