The development of the first quantitative in vivo water content brain atlas at 3T
22nd February 2022
N. Jon Shah, Zaheer Abbas, Dominik Ridder, Markus Zimmermann and Ana-Maria Oros-Peusquens
The use of brain atlases to compare healthy and diseased brains is commonly employed in clinical neuroscience for assessing and understanding a range of brain diseases and progression. However, despite novel quantitative MRI (qMRI) approaches gaining attention in recent years, the currently available, standard brain atlases are only able to provide qualitative comparisons. Compared to conventional (i.e. non-quantitative) MRI, qMRI uses specific sequences to quantify specific parameters of interest without influence from other factors, thus enabling the direct measurement of physical tissue properties. This is important because often, changes in tissue properties precede the structural changes visible with standard MRI, enabling the earlier diagnosis of a number of pathologies and more accurate treatment monitoring.
Within the framework of qMRI of the brain, this work reports on the development of the first quantitative brain atlas for tissue water content at 3T. The methodology used to create this quantitative atlas of in vivo brain water content was based on established methods for the fast and reliable measurement of absolute water content. Water content and T2* were mapped based on two different methods: an intermediate-TR, two-point method and a long-TR, single-scan method. Twenty healthy subjects (age 25.3 ± 2.5 years) were examined with these quantitative imaging protocols. The images were normalised to MNI stereotactic coordinates, and water content atlases were created for each method and compared. Regions of interest were generated with the help of a standard MNI template, and water content values averaged across the ROIs were compared to water content values from the literature.
The results show that, irrespective of the method used to acquire the individual water maps, global grey matter and white matter water content values agreed with each other to within 0.5 %.
Water content maps from patients with pathological changes in the brain due to stroke, tumour (glioblastoma) and multiple sclerosis were voxel-wise compared to the healthy brain water content atlases. In all cases, regions of pathologically increased water content were identified.
This demonstrates the power of quantitative methods and opens the way to detecting abnormal water content in the brains of patients based on a healthy brain water content atlas.
The first row (R1) in the figure below shows axial slices of the water content brain atlas acquired from twenty right-handed healthy male participants. The second row (R2) shows (i) axial slice of a water content atlas and (ii) a free water content map from a glioblastoma tumour patient co-registered to the atlas (i) using non-linear registration, (iii) along with the absolute differences between both maps and (iv) an estimation of brain oedema using a z-score (an overlaid map). The third (R3) and fourth rows (R4) show the same analysis between the water content atlas and the water content map acquired from a stroke patient and multiple sclerosis patient, respectively.
The combination of atlas-based features of water content, T1 and T2* mapping with clinical information has the potential to form the basis for a multidimensional analysis of characteristic disease properties, which could allow for a much more individualised diagnosis and the prediction of future disease burden. However, to realise this, well-organised and large multi-centre studies with large patient populations are necessary.
Future work will now concentrate on producing additional quantitative atlases to enable ‘multi-modal’ characterisation of other features seen in brain diseases. This further development could potentially shed light on patient cohorts, such as those with traumatic brain injury, idiopathic normal pressure hydrocephalus etc., where pathological changes are reflected by variations in relaxation times and/or tissue water content.
Link to the original publication: A Novel MRI-Based Quantitative Water Content Atlas of the Human Brain