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Impact of physiological noise correction on detecting blood oxygenation level-dependent contrast in the breast.

Published version
Peer-reviewed

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Authors

Wallace, TE 
Graves, MJ 
Patterson, AJ 
Gilbert, FJ 

Abstract

Physiological fluctuations are expected to be a dominant source of noise in blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) experiments to assess tumour oxygenation and angiogenesis. This work investigates the impact of various physiological noise regressors: retrospective image correction (RETROICOR), heart rate (HR) and respiratory volume per unit time (RVT), on signal variance and the detection of BOLD contrast in the breast in response to a modulated respiratory stimulus. BOLD MRI was performed at 3 T in ten volunteers at rest and during cycles of oxygen and carbogen gas breathing. RETROICOR was optimized using F-tests to determine which cardiac and respiratory phase terms accounted for a significant amount of signal variance. A nested regression analysis was performed to assess the effect of RETROICOR, HR and RVT on the model fit residuals, temporal signal-to-noise ratio, and BOLD activation parameters. The optimized RETROICOR model accounted for the largest amount of signal variance ([Formula: see text]  =  3.3  ±  2.1%) and improved the detection of BOLD activation (P  =  0.002). Inclusion of HR and RVT regressors explained additional signal variance, but had a negative impact on activation parameter estimation (P  <  0.001). Fluctuations in HR and RVT appeared to be correlated with the stimulus and may contribute to apparent BOLD signal reactivity.

Description

Keywords

Adult, Artifacts, Breast, Female, Heart Rate, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Oxygen, Regression Analysis, Respiration, Retrospective Studies, Signal-To-Noise Ratio, Young Adult

Journal Title

Phys Med Biol

Conference Name

Journal ISSN

0031-9155
1361-6560

Volume Title

62

Publisher

IOP Publishing
Sponsorship
Cambridge University Hospitals NHS Foundation Trust (CUH) (unknown)
Cancer Research Uk (None)
This work was supported by the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre and the CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester (C197/A16465 and C8742/A18097).