Biology subjects

Raniga, P.

Publications and source records attributed to Raniga, P..

3 recordsLinked to original sources

bioRxiv2021

Multi T1-weighted contrast imaging and T1 mapping with Compressed sensing FLAWS at 3T

The Fluid And White matter Suppression (FLAWS) MRI sequence allows for the acquisition of multiple T1-weighted contrasts in a single sequence acquisition. However, its acquisition time is prohibitive for use in clinical practice when the k-space is linearly downsampled and reconstructed using the Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) technique. This study proposes a FLAWS sequence optimization tailored to allow for the acquisition of FLAWS images with a Cartesian phyllotaxis k-space undersampling and compressed sensing (CS) reconstruction at 3T. The CS FLAWS sequence parameters were determined using a method previously employed to optimize FLAWS imaging at 1.5T and 7T. In-vivo experiments show that the proposed CS FLAWS optimization allows to reduce the FLAWS sequence acquisition time from 8 mins to 6 mins without decreasing the FLAWS image quality. In addition, this study demonstrates for the first time that T1-weighted imaging with low B1 sensitivity and T1 mapping can be performed with the FLAWS sequence at 3T for both GRAPPA and CS reconstructions. The FLAWS T1 mapping was validated using in-silico, in-vitro and in-vivo experiments with comparison against the inversion recovery turbo spin echo and MP2RAGE T1 mappings. These new results suggest that the recent advances in FLAWS imaging allow to combine the MP2RAGE imaging benefits (T1-weigthed imaging with low B1 sensitivity and T1 mapping) and with the previous version of FLAWS imaging benefits (multi T1-weighted contrast imaging) in a single 6 mins sequence acquisition. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

neuroscience↗

bioRxiv2017

Combining images and anatomical knowledge to improve automated vein segmentation in MRI

PurposeTo improve the accuracy of automated vein segmentation by combining susceptibility-weighted images (SWI), quantitative susceptibility maps (QSM), and a vein atlas to produce a resultant image called a composite vein image (CV image).\n\nMethodAn atlas was constructed in common space from 1072 manually traced 2D-slices. The composite vein image was derived for each subject as a weighted sum of three inputs; a SWI image, a QSM image and the vein atlas. The weights for each input and each anatomical location, called template priors, were derived by assessing the accuracy of each input over an independent data set. The accuracy of venograms derived automatically from each of the CV image, SWI, and QSM image sets was assessed by comparison with manual tracings. Three different automated vein segmentation techniques were used, and ten performance metrics evaluated.\n\nResultsVein segmentations using the CV image were comprehensively better than those derived from SWI or QSM images (mean Cohens d = 1.1). Sixty permutations of performance metric and automated segmentation technique were evaluated. Vein identification improvements that were both large and significant (Cohens d>0.80, p<0.05) were found in 77% of the permutations, compared to no improvement in 5%.\n\nConclusionThe accuracy of automated venograms derived from the composite vein image was overwhelmingly superior to venograms derived from SWI or QSM alone.

neuroscience↗

bioRxiv2016

Resting state functional coupling between the ascending synchronising system, limbic system and the default mode network via theta oscillations

In order to better understand dysfunction in dementia and psychiatric illnesses, the underlying neuronal systems that give rise to normal memory and cognitive processes need to be better understood. Based on electrophysiological recordings in animals, theta oscillations have been proposed as an intrinsic mechanism for the orchestration of memory functions, especially episodic and autobiographical memory. Theta oscillations are controlled by the ascending synchronising system, a set of nucleui in the pontine tegmentum and basal forebrain. At a network level, the default mode network has been shown to be responsible for episodic and autobiographical.\n\nUsing resting state fMRI data, we show using an ICA approach, seed based connectivity and dynamic causal modelling that the ascending synchronising system is coupled to the medial temporal lobe nodes including the hippocampus and parahippocampal gyrus and with the default mode network. Our results provide thus support the role of theta oscillations in memory function and coordination at a network level.\n\nHighlightsO_LIResting state functional coupling between the DMN, MTL and ascending synchronising system.\nC_LIO_LITheta oscillations may be the basis of this coupling given the role of these structures in control of theta.\nC_LIO_LITheta oscillations have been implicated in memory, cognition and predictive coding.\nC_LIO_LIDMN, MTL and ASS are implicated in Alzheimers disease.\nC_LI\n\nAbbreviations

neuroscience↗