Li Sze Chow

Investigating direct detection of axon firing in the adult human optic nerve using MRI.

The aim of this study was to directly detect spectral components of the magnetic fields of ionic currents caused by firing of the axons in the optic nerve in response to visual strobe stimulation. The magnetic field parallel to the main B0 field can potentially alter the local phase and magnitude of the MR signal which can cause signal loss due to intravoxel dephasing. Measured frequency spectra showed evidence of the strobe stimulus localized to regions containing the optic nerve, not thought to be due to motion artifacts, in 30 out of 52 experiments in 5 adult human subjects. The effect was (0.15 +/- 0.05)% of the mean magnitude equilibrium signal from the voxel in the frequency range 0.7-3.3 Hz, corresponding to an estimated field of (1.2 +/- 0.4) nT, at an echo time of TE = 32.4 ms using a 1.5 T MRI scanner. Only 1 of 12 phase image experiments showed effects. These findings provide preliminary evidence for direct detection of axonal firing in the optic nerve.

Comparison of BOLD and direct‐MR neuronal detection (DND) in the human visual cortex at 3T

Direct‐MR neuronal detection (DND) of transient magnetic fields has recently been investigated as a novel imaging alternative to the conventional BOLD functional MRI (fMRI) technique. However, there remain controversial issues and debate surrounding this methodology, and this study attempts clarification by comparing BOLD responses in the human visual system with those of DND. BOLD relies on indirectly measuring blood oxygenation and flow changes as a result of neuronal activity, whereas the putative DND method is based on the hypothesis that the components of the in vivo neuronal magnetic fields, which lie parallel to the B0 field, can potentially modulate the MR signal, thus providing a means of direct detection of nerve impulses. Block paradigms of checkerboard patterns were used for visual stimulation in both DND and BOLD experiments, allowing detection based on different frequency responses. This study shows colocalization of some voxels with slow BOLD responses and putative fast DND responses using General Linear Model (GLM) analysis. Frequency spectra for the activated voxel cluster are also shown for both stimulated and control data. The mean percentage signal change for the DND responses is 0.2%, corresponding to a predicted neuronal field of 0.14 nT. Magn Reson Med 60:1147–1154, 2008.

Modelling of axonal fields in the optic nerve for direct MR detection studies

A number of studies have now shown that direct detection of neuronal firing by MRI may be possible. The optic nerve carries all visual information from the eye to the brain and is a particularly promising target for these measurements. However, it has been assumed that the effects of axonal firing may not be detectable, as a single firing event produces a bipolar waveform of around 1ms duration whose effects should cancel on MR. A simulation of the magnetic modulation which could feasibly be produced by the optic nerve over an extended period and with different firing rates has been developed. The Hodgkin-Huxley equations were calculated for an array of model ganglion cell axons which were assumed to act as voltage to pulse frequency converters. Dependence of the modulating waveform on relative action potential firing start time was investigated. Although the simulated waveforms were bipolar at the beginning, during the period of MR acquisition the different frequencies combine to produce a largely positive waveform. The simulation included only contrast luminance changes and not color, spatial correlations or other more sophisticated processing in the retina. A gradient echo sequence was used at 3T to create images for analysis by the ghost reconstructed alternating current estimation (GRACE) method from phantoms subject to current modulation by the actual modelled axonal waveforms. The optic nerve was also imaged using the same method during visual stimulus by a strobe light in adult human volunteers at 3T. Analysis of digitized video recordings of eye locations during strobe stimulation outside the magnet showed no correlation with the applied strobe frequency over the short duration of the scans. Images of the optic nerves at an echo time of TE=39ms had weak but significant first harmonic ghosts in locations consistent with the applied stimulus as calculated from GRACE theory in just two out of thirteen studies on 10 volunteers and a detection rate of only 15% providing no clear evidence for direct detection in these experiments.

Review of medical image quality assessment

Abstract Image Quality Assessment (IQA) plays an important role in assessing any new hardware, software, image acquisition techniques, image reconstruction or post-processing algorithms, etc. In the past decade, there have been various IQA methods designed to evaluate natural images. Some were used for the medical images but the use was limited. This paper reviews the recent advancement on IQA for medical images, mainly for Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and ultrasonic imaging. Thus far, there is no gold standard of IQA for medical images due to various difficulties in designing a suitable IQA for medical images, and there are many different image characteristics and contents across various imaging modalities. No reference-IQA (NR-IQA) is recommended for assessing medical images because there is no perfect reference image in the real world medical imaging. We will discuss and comment on some useful and interesting IQA methods, and then suggest several important factors to be considered in designing a new IQA method for medical images. There is still great potential for research in this area.

Investigation of axonal magnetic fields in the human corpus callosum using visual stimulation based on MR signal modulation

To investigate the possibility of detecting visually‐evoked axonal currents in the splenium of the human corpus callosum using a 3.0T MRI system.

Correlation between subjective and objective assessment of magnetic resonance (MR) images.

Medical Image Quality Assessment (IQA) plays an important role in assisting and evaluating the development of any new hardware, imaging sequences, pre-processing or post-processing algorithms. We have performed a quantitative analysis of the correlation between subjective and objective Full Reference - IQA (FR-IQA) on Magnetic Resonance (MR) images of the human brain, spine, knee and abdomen. We have created a MR image database that consists of 25 original reference images and 750 distorted images. The reference images were distorted with six types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur, DCT compression, JPEG compression and JPEG2000 compression, at various levels of distortion. Twenty eight subjects were chosen to evaluate the images resulting in a total of 21,700 human evaluations. The raw scores were then converted to Difference Mean Opinion Score (DMOS). Thirteen objective FR-IQA metrics were used to determine the validity of the subjective DMOS. The results indicate a high correlation between the subjective and objective assessment of the MR images. The Noise Quality Measurement (NQM) has the highest correlation with DMOS, where the mean Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are 0.936 and 0.938 respectively. The Universal Quality Index (UQI) has the lowest correlation with DMOS, where the mean PLCC and SROCC are 0.807 and 0.815 respectively. Students T-test was used to find the difference in performance of FR-IQA across different types of distortion. The superior IQAs tested statistically are UQI for Rician noise images, Visual Information Fidelity (VIF) for Gaussian blur images, NQM for both DCT and JPEG compressed images, Peak Signal-to-Noise Ratio (PSNR) for JPEG2000 compressed images.

Modified-BRISQUE as no reference image quality assessment for structural MR images

An effective and practical Image Quality Assessment (IQA) model is needed to assess the image quality produced from any new hardware or software in MRI. A highly competitive No Reference - IQA (NR - IQA) model called Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) initially designed for natural images were modified to evaluate structural MR images. The BRISQUE model measures the image quality by using the locally normalized luminance coefficients, which were used to calculate the image features. The modified-BRISQUE model trained a new regression model using MR image features and Difference Mean Opinion Score (DMOS) from 775 MR images. Two types of benchmarks: objective and subjective assessments were used as performance evaluators for both original and modified-BRISQUE models. There was a high correlation between the modified-BRISQUE with both benchmarks, and they were higher than those for the original BRISQUE. There was a significant percentage improvement in their correlation values. The modified-BRISQUE was statistically better than the original BRISQUE. The modified-BRISQUE model can accurately measure the image quality of MR images. It is a practical NR-IQA model for MR images without using reference images.

Direct detection of the magnetic fields of neuronal impulses using MRI

The neuronal (ionic) current caused by nerve firing induces subtle and transient magnetic flux density changes that potentially modulate the MR signal over successive gradient echo planar image frames. Frequency spectra derived from Fourier transformation of experimental data down these time frames show evidence of a strobe stimulus localized to regions containing the optic nerve and visual cortex, which suggests that direct detection of the magnetic fields emanating from these regions has been achieved.

Segmentation and interpolation of optic nerves in MR images

The measurement of human optic nerve is a difficult task because of its small structure. The goal of this work is to find the most suitable segmentation and interpolation models for the optic nerves in MR images, in order to improve the precision in the optic nerves area measurement. In this study, we have chosen Level Set Method (LSM) segmentation and Contrast-Guided (CG) interpolation models. We use the integrated LSM-CG model to produce distinct circular edge for the optic nerves prior the area measurement. It was found that the mean area of the optic nerve is 13.07 ± 1.29 mm2 from original images, and 12.20 ± 1.01 mm2 from the LSM-CG processed images, which are within the range of the reported literature values. These measurement were obtained from Proton Density (PD) images from five healthy volunteers on both 1.5T and 3.0T MRI scanners. The integrated LSM-CG model is suitable for processing optic nerve images to achieve higher resolution edges and allow more accurate area measurement.