Effects of MRI protocols on brain FDG uptake in simultaneous PET/MR imaging.

PURPOSE: To investigate the potential effects of MRI protocols on brain FDG uptake in simultaneous PET/MR imaging. METHODS: Seventy healthy subjects and ten patients with temporal lobe epilepsy were enrolled. Healthy subjects were divided to three groups to undergo different PET/MR scan protocols: "continuous MRI" with MRI stimulation presented during the whole scan, "late MRI" with MRI stimulation started after 40 min glucose uptake, and "no MRI" without MRI stimulation at all. Region-wise and voxel-wise differences in FDG uptake among the three protocols were compared. All epilepsy patients were scanned with the "continuous MRI" scan protocol. The effects of MRI protocol stimulation on pathological interpretation were evaluated. RESULTS: Highest global averaged metabolism was found in the normal dataset with continuous MRI scan protocol (P < 0.05). Specifically, we observed higher FDG uptake in the primary auditory cortex, putamen, and lower FDG uptake in the occipital lobe and cerebellum during the "continuous MRI" scan protocol. However, MRI protocol stimulation after 40 min glucose uptake did not cause any significant differences in FDG uptake. Respectively compared to the normal dataset, patients with epilepsy showed consistent hypometabolism in the temporal lobe. Besides, significant metabolism changes in the primary auditory cortex, vermis, and occipital lobe were found in the "late MRI" protocol. CONCLUSION: The effects of MRI protocol on brain FDG uptake were varied. The effects, including from other practical setting, were conspicuous for scans where MRI protocol started immediately after glucose uptake, but would dramatically decrease to negligible 40 min later. Hence, it would be necessary for pathology studies to collect data from a normal control group using the same scan protocol for unbiased evaluation.

Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference.

OBJECTIVE: Respiration is recognized as a systematic physiological interference in functional near-infrared spectroscopy (fNIRS). However, it remains unanswered as to whether it is possible to estimate the respiratory rate (RR) from such interference. Undoubtedly, RR estimation from fNIRS can provide complementary information that can be used alongside the cerebral activity analysis, e.g., sport studies. Thus, the objective of this paper is to propose a method for RR estimation from fNIRS. Our primary presumption is that changes in the baseline wander of oxygenated hemoglobin concentration (O2Hb) signal are related to RR. METHODS: fNIRS and respiratory signals were concurrently collected from subjects during controlled breathing tasks at a constant rate from 0.1 Hz to 0.4 Hz. Firstly, the signal quality index algorithm is employed to select the best O2Hb signal, and then a band-pass filter with cut-off frequencies from 0.05 to 2 Hz is used to remove very low- and high-frequency artifacts. Secondly, troughs of the filtered O2Hb signal are localized for synthesizing the baseline wander (S1) using cubic spline interpolation. Finally, the fast Fourier transform of the S1 signal is computed, and its dominant frequency is considered as RR. In this paper, two different datasets were employed, where the first one was used for the parameter adjustment of the proposed method, and the second one was solely used for testing. RESULTS: The low mean absolute error between the reference and estimated RRs for the first and second datasets (2.6 and 1.3 breaths per minute, respectively) indicates the feasibility of the proposed method for RR estimation from fNIRS. SIGNIFICANCE: This paper provides a novel view on the respiration interference as a source of complementary information in fNIRS.

Physiological interference reduction for near infrared spectroscopy brain activity measurement based on recursive least squares adaptive filtering and least squares support vector machines.

Near infrared spectroscopy is the promising and noninvasive technique that can be used to detect the brain functional activation by monitoring the concentration alternations in the haemodynamic concentration. The acquired NIRS signals are commonly contaminated by physiological interference caused by breathing and cardiac contraction. Though the adaptive filtering method with least mean squares algorithm or recursive least squares algorithm based on multidistance probe configuration could improve the quality of evoked brain activity response, both methods can only remove the physiological interference occurred in superficial layers of the head tissue. To overcome the shortcoming, we combined the recursive least squares adaptive filtering method with the least squares support vector machine to suppress physiological interference both in the superficial layers and deeper layers of the head tissue. The quantified results based on performance measures suggest that the estimation performances of the proposed method for the evoked haemodynamic changes are better than the traditional recursive least squares method.

Suppressing Systemic Interference in fNIRS Monitoring of the Hemodynamic Cortical Response to Motor Execution and Imagery.

Hemodynamic response to motor execution (ME) and motor imagery (MI) was investigated using functional near-infrared spectroscopy (fNIRS). We used a 31 channel fNIRS system which allows non-invasive monitoring of cerebral oxygenation changes induced by cortical activation. Sixteen healthy subjects (mean-age 24.5 yeas) were recruited and the changes in concentration of hemoglobin were examined during right and left hand finger tapping tasks and kinesthetic MI. To suppress the systemic physiological interference, we developed a preprocessing procedure which prevents over-activated reporting in NIRS-SPM. In the condition of ME, more activation was observed in the anterior part of the motor cortex including the pre-motor and supplementary motor area (pre-motor and SMA), primary motor cortex (M1) and somatosensory motor cortex (SMC; t(15) > 2.27), however, in the condition of MI, more activation was found in the posterior part of motor cortex including SMC (t(15) > 1.81), which is in line with previous observations with functional magnetic resonance imaging (fMRI).