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| ID | Type | Description | Link |
|---|---|---|---|
| NCI-2018-01272 | Other Identifier | NCI-CTRP Clinical Trials Reporting Registry |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Computed Tomography Scan - 50% Dose Reduction | Experimental | Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 50% dose reduction. |
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| Computed tomography Scan - 70% Dose Reduction | Experimental | Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 70% dose reduction. |
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| Deep Learning Image Reconstruction (DLIR) | Experimental | 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. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Computed Tomography Scan - 50% Dose Reduction | Diagnostic Test | Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 50% dose reduction. |
| Measure | Description | Time Frame |
|---|---|---|
| Metastasis Detection Accuracy | Primary endpoint is metastasis detection accuracy status of each patient, where the standard of care scan reviewed by ''truth readers'' (independent to the blinded radiologists) serve as the gold standard. If any lesion of a patient is diagnosed as metastasis by "truth readers" or blinded readers' consensus, that patient will be considered true positive and diagnosis positive, respectively. The expected accuracy of standard CT is 95%, and a low dose CT detection be considered non-inferior if its accuracy is 85% or higher. | 1 day |
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Inclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Corey T. Jensen, MD | M.D. Anderson Cancer Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Texas MD Anderson Cancer Center | Houston | Texas | 77030 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35014900 | Derived | 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. | |
| 30480489 | Derived | 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. |
| Label | URL |
|---|---|
| MD Anderson Cancer Center | View source |
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| Computed Tomography Scan - 70% Dose Reduction | Diagnostic Test | Participants undergo routine standard of care CT examination for colon carcinoma restaging, then have an additional scan of the liver at 70% dose reduction. |
|
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| Deep Learning Image Reconstruction (DLIR) | Diagnostic Test | Participants to receive standard-of-care imaging without the artificial intelligence software and imaging technique. |
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| ID | Term |
|---|---|
| D004066 | Digestive System Diseases |
| D003110 | Colonic Neoplasms |
| D015179 | Colorectal Neoplasms |
| ID | Term |
|---|---|
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |
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| ID | Term |
|---|---|
| D014057 | Tomography, X-Ray Computed |
| ID | Term |
|---|---|
| D007090 | Image Interpretation, Computer-Assisted |
| D003952 | Diagnostic Imaging |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D011856 | Radiographic Image Enhancement |
| D007089 | Image Enhancement |
| D010781 | Photography |
| D011859 | Radiography |
| D014056 | Tomography, X-Ray |
| D014054 | Tomography |
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