NCT03033615

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

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

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 20 (estimated)
• Sponsor: AlgoMedica, Inc. · Industry
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

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.

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.

Conditions

• Cancer, Lung
• Cancer Liver
• X-rays; Effects

Interventions

Type	Name	Description
DEVICE	PixelShine	Machine learning algorithm
DEVICE	Conventional processing	Iterative reconstruction software

Timeline

• Start date: 2017-08-01
• Primary completion: 2017-10-01
• Completion: 2017-12-01
• First posted: 2017-01-27
• Last updated: 2017-06-28

Regulatory

• FDA-regulated device study