Comparison of CT Dose Reduction Algorithms in a Porcine Model

Mohammed Nazir Khan,Blair Henderson,Idris Elbakri,Jeffrey Mottola,Azeez Omotayo

doi:10.4236/act.2015.44008

Abstract

The present study utilized a porcine model for qualitative and quantitative assessment of the diagnostic quality of non-contrast abdominal computed tomography (CT) images generated by Adaptive Statistical Iterative Reconstruction (ASIR, GE Healthcare, Waukesha, Wisconsin, USA), Model-Based Iterative Reconstruction (GE company name VEO), and conventional Filtered back projection (FBP) technique. Methods: Multiple CT whole-body scans of a freshly euthanized pig carcass were performed on a 64-slice GE CT scanner at varying noise indices (5, 10, 15, 20, 30, 37, 40, 45), and with three different algorithms (VEO, FBP, and ASIR at 30%, 50%, and 70% levels of ASIR-FBP blending). Abdominal CT images were reviewed and scored in a blinded and randomized manner by two board-certified abdominal radiologists. The task was to evaluate the clarity of the images according to a rubric involving edge sharpness, presence of artifact, anatomical clarity (assessed at four regions), and perceived diagnostic acceptability. This amounted to seven criteria, each of which was graded on a scale of 1 to 5. A weighted formula was used to calculate a composite score for each scan. Results: VEO outperforms ASIR and FBP by an average of 0.5 points per the scoring system used (p < 0.05). Above a threshold noise index of 30, diagnostic acceptability is lost by all algorithms, and there is no diagnostic advantage to increasing the dose beyond a noise index of 10. Between a noise index of 25 - 30, VEO retains diagnostic acceptability, as opposed to ASIR and FBP which lose acceptability above noise index of 25. Conclusion: Model-based iterative reconstruction provides superior image quality and anatomical clarity at reduced radiation dosages, supporting the routine use of this technology, particularly in pediatric abdominal CT scans.

Highlights

Healthcare in recent years has witnessed a dramatic rise in the number of computed tomography (CT) scans, which has greatly contributed to increased exposure to medical radiation
VEO images had the highest contrast-to-noise ration (CNR), which increases at a lower rate with respect to dose increment
At the highest doses, VEO produced lower CNR values compared to ASIR50 and ASIR70

Summary

Introduction

Healthcare in recent years has witnessed a dramatic rise in the number of computed tomography (CT) scans, which has greatly contributed to increased exposure to medical radiation. Given the evidence linking radiation exposure with carcinogenesis [1], numerous strategies to reduce radiation have been explored, including lowering tube current (mA) and potential (kVp), increased scanning pitch, the use of automated tube current modulation, and improving implementation of guidelines for avoiding unnecessary imaging. The greatest challenge with reducing CT dosage is the concomitant deterioration of image quality at lower dose levels due to increased image noise and artifacts. The development of alternative reconstruction algorithms promises to achieve lower radiation dosage while preserving acceptable image quality. Alternative algorithms, involving iterative reconstruction, generate the radiological image through a mathematical model of the data acquisition process, thereby reducing image noise that is unlikely to represent true anatomy

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Discussion

Conclusion