BRAHMA: Population specific T1, T2, and FLAIR weighted brain templates and their impact in structural and functional imaging studies.

Differences in brain morphology across population groups necessitate creation of population-specific Magnetic Resonance Imaging (MRI) brain templates for interpretation of neuroimaging data. Variations in the neuroanatomy in a genetically heterogeneous population make the development of a population-specific brain template for the Indian subcontinent imperative. A dataset of high-resolution 3D T1, T2-weighted, and FLAIR images acquired from a group of 113 volunteers (M/F - 56/57, mean age-28.96 ±â€¯7.80 years) are used to construct T1, T2-weighted, and FLAIR templates, collectively referred to as Indian Brain Template, "BRAHMA". A processing pipeline is developed and implemented in a MATLAB based toolbox for template construction and generation of tissue probability maps and segmentation atlases, with additional labels for deep brain regions such as the Substantia Nigra generated from the T2-weighted and FLAIR templates. The use of BRAHMA template for analysis of structural and functional neuroimaging data obtained from Indian participants, provides improved accuracy with statistically significant results over that obtained using the ICBM-152 (International Consortium for Brain Mapping) template. Our results indicate that segmentations generated on structural images are closer in volume to those obtained from registration to the BRAHMA template than to the ICBM-152. Furthermore, functional MRI data obtained for Working Memory and Finger Tapping paradigms processed using the BRAHMA template show a significantly higher percentage of the activation area than ICBM-152 in relevant brain regions, i.e. the left middle frontal gyrus, and the left and right precentral gyri, respectively. The availability of different image contrasts, tissue maps, and segmentation atlases makes the BRAHMA template a comprehensive tool for multi-modal image analysis in laboratory and clinical settings.

Modelling, verification, and calibration of a photoacoustics based continuous non-invasive blood glucose monitoring system.

This paper examines the use of photoacoustic spectroscopy (PAS) at an excitation wavelength of 905 nm for making continuous non-invasive blood glucose measurements. The theoretical background of the measurement technique is verified through simulation. An apparatus is fabricated for performing photoacoustic measurements in vitro on glucose solutions and in vivo on human subjects. The amplitude of the photoacoustic signals measured from glucose solutions is observed to increase with the solution concentration, while photoacoustic amplitude obtained from in vivo measurements follows the blood glucose concentration of the subjects, indicating a direct proportionality between the two quantities. A linear calibration method is applied separately on measurements obtained from each individual in order to estimate the blood glucose concentration. The estimated glucose values are compared to reference glucose concentrations measured using a standard glucose meter. A plot of 196 measurement pairs taken over 30 normal subjects on a Clarke error grid gives a point distribution of 82.65% and 17.35% over zones A and B of the grid with a mean absolute relative deviation (MARD) of 11.78% and a mean absolute difference (MAD) of 15.27 mg/dl (0.85 mmol/l). The results obtained are better than or comparable to those obtained using photoacoustic spectroscopy based methods or other non-invasive measurement techniques available. The accuracy levels obtained are also comparable to commercially available continuous glucose monitoring systems.

NIR photoacoustic spectroscopy for non-invasive glucose measurement.

The use of near infra red (NIR) photoacoustic spectroscopy (PAS) for continuous non-invasive glucose measurement is outlined in the paper. A photoacoustic (PA) measurement apparatus was constructed and PA measurements were made on glucose solutions at multiple NIR excitation wavelengths. A variety of time and frequency domain features, including amplitude and area based features, were extracted from the PA measurements. These features were observed to be proportional to the glucose concentration of the sample. PA measurements from samples of whole blood at different glucose concentrations showed similar results. Subsequently, in vivo PA measurements made on a cohort of 30 volunteers were calibrated using a quadratic fit, and the results were compared to reference glucose concentrations made using a regular blood glucose meter. A comparison of 196 measurement pairs of predicted and reference glucose concentrations using a Clarke Error Grid gave a point distribution of 87.24% and 12.76% over zones A and B of the grid, with no measurement pairs falling in unacceptable zones C-E of the error grid. The predicted measurements had a mean absolute difference (MAD) of 12.57 ± 13.90 mg/dl and a mean absolute relative difference (MARD) of 9.61% ± 10.55%. This is an improvement over previous results obtained using PAS and other non-invasive techniques, validating the potential of PAS for continuous noninvasive glucose monitoring.