Low-dose pelvic CT using adaptive iterative dose reduction 3D: a phantom study.

Kockelkoren, R. (Remko) (2013) Low-dose pelvic CT using adaptive iterative dose reduction 3D: a phantom study. thesis, Medicine.

Text KockelkorenR.pdf Restricted to Registered users only Download (1MB)

Abstract

Purpose: It is predicted that 1.5–2.0% of all U.S. population cancers may be caused by CT radiation exposure. To address the growing concerns of medical radiation exposure, improvements have been made to CT scanners to lower the radiation dose. In this study we evaluate a new image reconstruction algorithm from Toshiba, Adaptive Iterative Dose Reduction 3D (AIDR3D), by evaluating image quality at low-dose settings and comparing it to standard Filtered Back Projection (FBP). Method and materials: An anthropomorphic phantom and a Catphan phantom containing low-contrast objects were scanned with a 320-detector row CT scanner at eight tube current levels (25-500 mA) at 80 kV and 120 kV, respectively. Standard FBP images and AIDR3D images were reconstructed for each setting and were compared. For the quantitative evaluation, image noise and contrast to noise ratio (CNR) were calculated. For the qualitative evaluation, image noise, image artifacts, delineation of the organs and overall image quality of the anthropomorphic phantom were assessed by two experienced radiologists. The detectability of the low-contrast objects of the Catphan phantom was also evaluated using a receiver operator characteristic (ROC) analysis. Results: In the quantitative evaluation, AIDR3D resulted in a substantial noise reduction (55%) compared to FBP and revealed higher CNR’s than FBP. In the subjective evaluation, the image noise, image artifact such as photon starvation and overall image quality improved with AIDR3D. ROC analysis showed comparable results between AIDR3D and FBP. Conclusion: Our results of the phantom study show that the AIDR3D technique may allow approximately 50% radiation dose reduction compared to FBP technique in pelvic CT examinations maintaining the image quality and the diagnostic performance.

Item Type:	Thesis (Thesis)
Supervisor name:	Boomsma, Dr. M.
Supervisor name:	Kim, Dr. Tonsok and Osaka University Graduate School of Medicine
Faculty:	Medical Sciences
Date Deposited:	25 Jun 2020 11:02
Last Modified:	25 Jun 2020 11:02
URI:	https://umcg.studenttheses.ub.rug.nl/id/eprint/2240

Actions (login required)

View Item