Comprehensive brain tumour characterization with VERDICT-MRI: evaluation of cellular and vascular measures validated by histology

The aim of this work is to extend the VERDICT-MRI framework for modelling brain tumours, enabling comprehensive characterization of both intra-tumoural and peri-tumoural areas with a particular focus on cellular and vascular features. Diffusion MRI data were acquired with multiple b-values (ranging from 50 to 3500 s/mm2), diffusion times and echo times, in 21 patients with brain tumours of different types and with a wide range of cellular and vascular features. We fitted a selection of diffusion models that resulted from the combination of different types of intracellular, extracellular, and vascular compartments to the signal. We compared the models using criteria for parsimony while aiming at a good characterization of all the key histological brain tumour components. Finally, we evaluated the parameters of the best-performing model in the differentiation of tumour histotypes, having ADC (apparent diffusion coefficient) as a clinical standard reference, and compared them to histopathology and relevant perfusion MRI metrics. The best-performing model for VERDICT in brain tumours was a three-compartment model accounting for anisotropically hindered and isotropically restricted diffusion and isotropic pseudo-diffusion. VERDICT metrics were compatible with the histological appearance of low-grade gliomas and metastases, and reflected differences found by histopathology between multiple biopsy samples within tumours. The comparison between histotypes showed that both the intracellular and the vascular fractions tend to be higher in tumours with high cellularity (glioblastoma and metastasis), and quantitative analysis showed a trend toward higher values of the intracellular fraction (fic) within the tumour core with increasing glioma grade. We also observed a trend towards higher free water fraction in vasogenic oedemas around metastases compared to infiltrative oedemas around glioblastomas and WHO 3 gliomas and the periphery of low-grade gliomas. In conclusion, we developed and evaluated a multi-compartment diffusion MRI model for brain tumours based on the VERDICT framework and showed agreement of non-invasive microstructural estimates with histology and encouraging trends for differentiation of tumour types and sub-regions

Comparison of Diffusion MRI Acquisition Protocols for the <i>In Vivo</i> Characterization of the Mouse Spinal Cord: Variability Analysis and Application to an Amyotrophic Lateral Sclerosis Model

<div><p>Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios and the mean value and variability of Diffusion Tensor metrics were evaluated in healthy controls. For the estimation of fractional anisotropy less variability was provided by protocols with more diffusion directions, for the estimation of mean, axial and radial diffusivity by protocols with fewer diffusion directions and higher diffusion weighting. Intermediate features (12 directions, b = 1200 s/mm²) provided the overall minimum inter- and intra-subject variability in most cases. In order to test the diagnostic sensitivity of the protocols, 7 G93A-SOD1 mice (model of amyotrophic lateral sclerosis) at 10 and 17 weeks of age were scanned and the derived diffusion parameters compared with those estimated in age-matched healthy animals. The protocols with an intermediate or high number of diffusion directions provided the best differentiation between the two groups at week 17, whereas only few local significant differences were highlighted at week 10. According to our results, a dMRI protocol with an intermediate number of diffusion gradient directions and a relatively high diffusion weighting is optimal for spinal cord imaging. Further work is needed to confirm these results and for a finer tuning of acquisition parameters. Nevertheless, our findings could be important for the optimization of acquisition protocols for preclinical and clinical dMRI studies on the spinal cord.</p></div

Toluidine staining and electron microscopy of lumbar spinal cord of WT-SOD1 and G93A-SOD1 mice.

<p>A) and B): macroscopic view of toluidine stained α-motor neurons (first row) and motor fibers (second row) in WT-SOD1 and G93A-SOD1 spinal cord at weeks 10 (A) and 17 (B). Scale bar = 50 μm. C) and D) Electron microscopy. The images show the presence of vacuoles (red arrows) in the soma (first row) and in the big axons (second row) of lumbar motoneurons of G93A-SOD1 mice at 10 (C) and 17 (D) weeks of age compared to age-matched WT-SOD1 mice. The images show also degenerated axons with disorganized myelin sheaths (blue asterisks) in G93A-SOD1 animals at 10 and 17 weeks of age compared to WT-SOD1 mice at the same age.</p

Differences in DTI parameters of WT-SOD1 mice between 10 and 17 weeks of age.

<p>Differences in DTI parameters of WT-SOD1 mice between 10 and 17 weeks of age.</p

Acquisition setup and ROI delineation.

<p>Left: T2-weighted sagittal view of the lumbar tract. The green boxes are the image slices and the purple grid shows the position of the saturation slices. Note that the examined lumbar spinal cord region is mostly straight and the imaging slices were placed perpendicular to the axis of the spine. Center: FA map of a single slice (framed in yellow on the left panel). Right: ROIs overlaid on a part of the FA map including the whole section of the spinal cord (in yellow on the central panel); ventral (vWM), dorsal (dWM), ventro-lateral (vlWM) and dorso-lateral (dlWM) white matter, ventral (vGM) and dorsal (dGM) gray matter.</p

Differences in DTI parameters of G93A-SOD1 mice between 10 and 17 weeks of age.

<p>Differences in DTI parameters of G93A-SOD1 mice between 10 and 17 weeks of age.</p

Inter-and intra-subject CV.

<p>Upper panel: The color in each ROI indicates the protocol with the lowest inter-subject coefficient of variation, thus the minimum variability of each DTI parameter (FA, MD, AD, RD) among animals at 10 and 17 weeks of age. Lower panel: The color in each ROI indicates the protocol with the lowest intra-subject coefficient of variation, thus the minimum variability of each DTI parameter (FA, MD, AD, RD) inside the ROI, averaged among animals at 10 and 17 weeks of age.</p

Differences in DTI parameters between G93A-SOD1 and WT-SOD1 at week 17.

<p>Differences in DTI parameters between G93A-SOD1 and WT-SOD1 at week 17.</p

Representative FA and AD maps for 17-week old mice.

<p>The images show representative FA (left) and AD maps (right) for WT-SOD1 and G93A-SOD1 mice at 17 weeks of age. Each row correspond to a different protocol. Please note that the same contrast was used for all the FA and for all the AD maps, so that different intensities reflect different values of the parameters.</p

Comparison of DTI parameters between G93A-SOD1 and WT-SOD1 mice.

<p>The bar graphs show representative MRI quantities estimated in 7 WT-SOD1 (white) and 7 G93A-SOD1 mice (gray) at 17 weeks of age by each protocol (Prt). Mean values (± standard deviation) are shown for ventral (left) and dorsal (right) WM in the first 4 rows, for ventral (left) and dorsal (right) GM in the last row. Significant differences (p < 0.05) between G93A-SOD1 and WT-SOD1 are labeled with asterisks.</p