Lesion Detection Assessment in the Liver: Standard vs Low Radiation Dose Using Varied Post-Processing Techniques
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- STATUS
- Recruiting
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- End date
- Jun 30, 2023
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- participants needed
- 140
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- sponsor
- M.D. Anderson Cancer Center
Summary
To compare 2 different image creation/processing techniques during a standard CT scan in order to "see" problems in the liver and learn which method provides better image quality. The techniques use new artificial intelligence software to decrease image noise, which helps the radiologist to evaluate.
Description
Primary Objective:
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.
Details
| Condition | Diseases of Liver, Colon Carcinoma, Colorectal Carcinoma, Liver Metastases |
|---|---|
| Treatment | Computed Tomography Scan - 50% Dose Reduction, Computed Tomography Scan - 70% Dose Reduction, Deep Learning Image Reconstruction (DLIR) |
| Clinical Study Identifier | NCT03151564 |
| Sponsor | M.D. Anderson Cancer Center |
| Last Modified on | 4 October 2022 |
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