Insular gliomas and tractographic visualization of the connectome

In this video, the authors present a connectome-guided surgical resection of an insular glioma in a 39-year-old woman. Preoperative study with constrained spherical deconvolution (CSD)–based tractography revealed the surrounding brain connectome architecture around the tumor relevant for safe surgical resection. Connectomic information provided detailed maps of the surrounding language and salience networks, including eloquent white matter fibers and cortical regions, which were visualized intraoperatively with image guidance and artificial intelligence (AI)–based brain mapping software. Microsurgical dissection is presented with detailed discussion of the safe boundaries and angles of resection when entering the insular operculum defined by connectomic information. The video can be found here: https://stream.cadmore.media/r10.3171/2021.10.FOCVID21194

An atlas of white matter anatomy, its variability, and reproducibility based on Constrained Spherical Deconvolution of diffusion MRI

Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the first segment of the superior longitudinal fasciculus, fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a highly reproducible parcellation-based dissection protocol, as well as being an educational resource for applied neuroimaging and clinical professionals.

Constrained-Spherical Deconvolution Tractography in the Evaluation of the Corticospinal Tract in Glioma Surgery

Introduction: Tractography has demonstrated utility for surgical resection in the setting of primary brain tumors involving eloquent white matter (WM) pathways.Methods: Twelve patients with glioma in or near eloquent motor areas were analyzed. The motor status was recorded before and after surgery. Two different tractography approaches were used to generate the motor corticospinal tract (CST): Constrained spherical deconvolution probabilistic tractography (CSD-Prob) and single tensor deterministic tractography (Tens-DET). To define the degree of disruption of the CST after surgical resection of the tumor, we calculated the percentage of the CST affected by surgical resection, which was then correlated with the postoperative motor status. Moreover, the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of the CST generated by the CSD-Prob and the Tens-DET was measured and compared between the ipsilesional and contralesional side.Results: The CST was identified in all patients and its trajectory was displaced by the tumor. Only the CSD-Prob approach showed the CST with the characteristic fan-like projections from the precentral gyrus to the brainstem. Disruption of the CST was identified in 6/6 with postoperative motor deficit by CSD-Prob approach and in 5/6 in the Tens-DET. The degree of disruption was significantly associated with the motor deficit with the CSD-Prob approach (rho = −0.88, p = 0.021). However, with the Tens-DET approach the CST disruption did not show significant association with the motor function (rho = −0.27, p = 0.6). There was a significant decrease in FA (p = 0.006) and a significant increase in MD (p = 0.0004) and RD (p = 0.005) on the ipsilesional CST compared with the contralesional CST only with the CSD-Prob approach.Conclusion: CSD-Prob accurately represented the known anatomy of the CST and provided a meaningful estimate of microstructural changes of the CST affected by the tumor and its macrostructural damage after surgery. Newer surgical planning stations should include advanced models and algorithms of tractography in order to obtain more meaningful reconstructions of the WM pathways during glioma surgery.

Subdivision of Superior Longitudinal Fasciculus in Human Neonatal Brain

The superior longitudinal fasciculus (SLF) is a complex associative tract comprising of three distinct subdivisions in the fronto-parietal cortex, each presenting different anatomical connectivity and different functional roles. However, the subdivision of SLF was hampered by limitations of data quality and tractography methods, and many studies on white matter development often consider the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonatal period remain poorly understood. In this work, we investigated the morphological characteristics and maturation degree of SLF each branch using the diffusion MRI (dMRI) data of 40 healthy term neonates from the Developing Human Connectome Project (dHCP) database. An advanced single shell 3-tissue constrained spherical deconvolution (SS3T-CSD) algorithm was used to ensure the successful separation of the SLF three branches (SLF I, SLF II and SLF III). In addition, diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters values of the three subcomponents of SLF were measured quantitatively. The fiber morphology and connectivity of SLF sub-bundles in neonatal brain were nicely revealed in our study. Furthermore, the comparison results of parameters values supported that the maturation of SLF three segments was heterochronic. Further multiple comparison results indicated that the dorsal SLF II was less mature than the ventral SLF III and the former may involve in higher-level cognitive functions. Our findings can provide new anatomical basis for early diagnosis and treatment of related diseases caused by aberrant development of SLF.

Enabling constrained spherical deconvolution and diffusional variance decomposition with tensor-valued diffusion MRI

Diffusion tensor imaging (DTI) is widely used to extract valuable tissue measurements and white matter (WM) fiber orientations, even though its lack of specificity is now well-known, especially for WM fiber crossings. Models such as constrained spherical deconvolution (CSD) take advantage of HARDI data to compute fiber orientation distribution functions (fODF) and tackle the orientational part of the DTI limitations. Furthermore, the recent introduction of tensor-valued diffusion MRI allows for diffusional variance decomposition (DIVIDE), opening the door to the computation of measures more specific to microstructure than DTI measures, such as microscopic fractional anisotropy (μFA). However, tensor-valued diffusion MRI data is not compatible with latest versions of CSD and the impacts of such atypical data on fODF reconstruction with CSD are yet to be studied. In this work, we lay down the mathematical and computational foundations of a tensor-valued CSD and use simulated data to explore the effects of various combinations of diffusion encodings on the angular resolution of extracted fOFDs. We also compare the combinations with regards to their performance at producing accurate and precise μFA with DIVIDE, and present an optimised protocol for both methods. We show that our proposed protocol enables the reconstruction of both fODFs and μFA on in vivo data.

Magnetic resonance tractography based on the constrained spherical deconvolution in patients with gliomas of the optic pathway

Background: The use of magnetic resonance (MR) tractography in neurosurgery is becoming an increasingly common practice for noninvasive imaging of white matter pathways. The most common method of tract reconstruction is the deterministic algorithm of diffusion tensor magnetic resonance imaging (MRI). However, this method of reconstructing pathways has a number of significant limitations. The most important of them are the lack of the possibility of visualizing the intersecting fibers, the complexity of building tracts in the area of perifocal edema and in the immediate vicinity of the tumor borders. The method of MR tractography, based on obtaining a diffusion image with a high angular resolution (High Angular Resolution Diffusion Imaging, HARDI), using the constrained spherical deconvolution (CSD) algorithm for post-processing of data, makes it possible to avoid these disadvantages. Relatively recently, a new algorithm, Single-Shell 3-Tissue CSD (SS3TCSD), has been proposed for processing HARDI data, which has the potential to improve the reconstructing of pathways in the area of perifocal edema or edema-infiltration.Aim: To evaluate the potential of the new SS3TCSD algorithm compared to ST-CSD (Single-Tissue CSD) in the imaging of the optic radiation and visual tracts in patients with gliomas.Materials and methods: Diffusion and routine brain MRI was performed in 10 patients with newly diagnosed cerebral gliomas, followed by reconstruction of the optic radiation and visual tracts. We compared new algorithms for postprocessing MR tractography (ST-CSD and SS3TCSD) in imaging of the optic tract and visual radiation in patients with brain gliomas affecting various parts of the visual system.Results: The SS3T-CSD method showed a lower mean percentage of false positive tracts compared to the ST-CSD method: 19.75% for the SS3T-CSD method and 80.32% for the ST-CSD method in cases of proximity of the tumor to the tracts, 5.27% for the SS3T-CSD method and 25.27% for the STCSD method in cases of reconstructing tracts in healthy white matter.Conclusion: The SS3T-CSD method has a number of advantages over ST-CSD and allows for successful imaging of the optic pathways that have a complex structure and repeatedly change direction along their course.

Avoiding Data Loss: Synthetic MRIs Generated from Diffusion Imaging Can Replace Corrupted Structural Acquisitions For Freesurfer-Seeded Tractography

1AbstractMagnetic Resonance Imaging (MRI) motion artefacts frequently complicate structural and diffusion MRI analyses. While diffusion imaging is easily ‘scrubbed’ of motion affected volumes, the same is not true for structural images. Structural images are critical to most diffusion-imaging pipelines thus their corruption can lead to disproportionate data loss. To enable diffusion-image processing when structural images have been corrupted, we propose a means by which synthetic structural images can be generated from diffusion MRI. This technique combines multi-tissue constrained spherical deconvolution, which is central to many existing diffusion analyses, with the Bloch equations which allow simulation of MRI intensities given scanner parameters and magnetic resonance (MR) tissue properties. We applied this technique to 32 scans, including those acquired on different scanners, with different protocols and with pathology present. The resulting synthetic T1w and T2w images were visually convincing and exhibited similar tissue contrast to acquired structural images. These were also of sufficient quality to drive a Freesurfer-based tractographic analysis. In this analysis, probabilistic tractography connecting the thalamus to the primary sensorimotor cortex was delineated with Freesurfer, using either real or synthetic structural images. Tractography for real and synthetic conditions was largely identical in terms of both voxels encountered (Dice 0.88 – 0.95) and mean fractional anisotropy (intrasubject absolute difference 0.00 – 0.02). We provide executables for the proposed technique in the hope that these may aid the community in analysing datasets where structural image corruption is common, such as studies of children or cognitively impaired persons.HighlightsWe propose a simple means of synthesizing T1w and T2w images from diffusion dataThe proposed method worked well for a variety of acquisitionsSynthetic images showed tissue contrast akin to acquired imagesSynthetic images were high enough quality to be used for Freesurfer seeded diffusion tractographyThis method enables analysis of datasets where motion has corrupted acquired structural MRIs