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

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 (ΔRadj2  =  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.

[1]  Tess E Wallace,et al.  Detecting gas‐induced vasomotor changes via blood oxygenation level‐dependent contrast in healthy breast parenchyma and breast carcinoma , 2016, Journal of magnetic resonance imaging : JMRI.

[2]  Roderick W McColl,et al.  Blood oxygenation level‐dependent (BOLD) contrast magnetic resonance imaging (MRI) for prediction of breast cancer chemotherapy response: A pilot study , 2013, Journal of magnetic resonance imaging : JMRI.

[3]  Dafna Ben Bashat,et al.  Hemodynamic Response Imaging: A Potential Tool for the Assessment of Angiogenesis in Brain Tumors , 2012, PloS one.

[4]  Irene Tracey,et al.  Assessment of physiological noise modelling methods for functional imaging of the spinal cord , 2012, NeuroImage.

[5]  Oliver Speck,et al.  The impact of physiological noise correction on fMRI at 7 T , 2011, NeuroImage.

[6]  Arno Klein,et al.  A reproducible evaluation of ANTs similarity metric performance in brain image registration , 2011, NeuroImage.

[7]  Bruce Daniel,et al.  Detecting blood oxygen level‐dependent (BOLD) contrast in the breast , 2010, Journal of magnetic resonance imaging : JMRI.

[8]  Brian W Pogue,et al.  Inspired gas-induced vascular change in tumors with magnetic-resonance-guided near-infrared imaging: human breast pilot study. , 2010, Journal of biomedical optics.

[9]  K D Paulsen,et al.  Monitoring of hemodynamic changes induced in the healthy breast through inspired gas stimuli with MR-guided diffuse optical imaging. , 2010, Medical physics.

[10]  D J Collins,et al.  Carbogen breathing increases prostate cancer oxygenation: a translational MRI study in murine xenografts and humans , 2009, British Journal of Cancer.

[11]  Catie Chang,et al.  Influence of heart rate on the BOLD signal: The cardiac response function , 2009, NeuroImage.

[12]  Stephen D. Mayhew,et al.  Brainstem functional magnetic resonance imaging: Disentangling signal from physiological noise , 2008, Journal of magnetic resonance imaging : JMRI.

[13]  Peter A. Bandettini,et al.  Integration of motion correction and physiological noise regression in fMRI , 2008, NeuroImage.

[14]  Jeff H. Duyn,et al.  Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal , 2007, NeuroImage.

[15]  Kevin Murphy,et al.  How long to scan? The relationship between fMRI temporal signal to noise ratio and necessary scan duration , 2007, NeuroImage.

[16]  Jeff H. Duyn,et al.  An adaptive filter for suppression of cardiac and respiratory noise in MRI time series data , 2006, NeuroImage.

[17]  Sonya Bells,et al.  Vasomodulation of skeletal muscle BOLD signal , 2006, Journal of magnetic resonance imaging : JMRI.

[18]  Peter A. Bandettini,et al.  Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI , 2006, NeuroImage.

[19]  Thomas E. Nichols,et al.  Non-white noise in fMRI: Does modelling have an impact? , 2006, NeuroImage.

[20]  M. Neeman,et al.  Functional and molecular mapping of uncoupling between vascular permeability and loss of vascular maturation in ovarian carcinoma xenografts: The role of stroma cells in tumor angiogenesis , 2005, International journal of cancer.

[21]  Egill Rostrup,et al.  Motion or activity: their role in intra- and inter-subject variation in fMRI , 2005, NeuroImage.

[22]  Irene Tracey,et al.  Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal , 2004, NeuroImage.

[23]  Mark Rijpkema,et al.  Effects of breathing a hyperoxic hypercapnic gas mixture on blood oxygenation and vascularity of head-and-neck tumors as measured by magnetic resonance imaging. , 2002, International journal of radiation oncology, biology, physics.

[24]  J. Karemaker,et al.  Influence of chemoreflexes on respiratory variability in healthy subjects. , 2002, American journal of respiratory and critical care medicine.

[25]  G. Glover,et al.  Physiological noise in oxygenation‐sensitive magnetic resonance imaging , 2001, Magnetic resonance in medicine.

[26]  J R Griffiths,et al.  BOLD MRI of human tumor oxygenation during carbogen breathing , 2001, Journal of magnetic resonance imaging : JMRI.

[27]  M. Dewhirst,et al.  In vivo BOLD contrast MRI mapping of subcutaneous vascular function and maturation: Validation by intravital microscopy , 2001, Magnetic resonance in medicine.

[28]  G H Glover,et al.  Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR , 2000, Magnetic resonance in medicine.

[29]  J. Haxby,et al.  Localization of Cardiac-Induced Signal Change in fMRI , 1999, NeuroImage.

[30]  J. Saunders,et al.  k‐space detection and correction of physiological artifacts in fMRI , 1997, Magnetic resonance in medicine.

[31]  J R Griffiths,et al.  The response of human tumors to carbogen breathing, monitored by Gradient-Recalled Echo Magnetic Resonance Imaging. , 1997, International journal of radiation oncology, biology, physics.

[32]  X Hu,et al.  Retrospective estimation and correction of physiological artifacts in fMRI by direct extraction of physiological activity from MR data , 1996, Magnetic resonance in medicine.

[33]  X Hu,et al.  Retrospective estimation and correction of physiological fluctuation in functional MRI , 1995, Magnetic resonance in medicine.

[34]  Adrian T. Lee,et al.  Discrimination of Large Venous Vessels in Time‐Course Spiral Blood‐Oxygen‐Level‐Dependent Magnetic‐Resonance Functional Neuroimaging , 1995, Magnetic resonance in medicine.

[35]  Daniel Hershey,et al.  Blood Oxygenation , 1970, Springer US.