Biology subjects

Scerri, K.

Publications and source records attributed to Scerri, K..

3 recordsLinked to original sources

bioRxiv2026

Testing diffusion-derived orientation priors for streamline modelling of the MRI-visible glioblastoma core: the BRIAN framework

Glioblastoma spreads diffusely beyond the abnormality visible on conventional magnetic resonance imaging, and because tumour cells migrate preferentially along white-matter pathways, growth models that assume isotropic spread may misrepresent the geometry of invasion relevant to radiotherapy planning. This work introduces and evaluates BRIAN, a diffusion-informed simulator that biases tumour propagation along directions derived from diffusion MRI. Patient tumour masks from the UPENN-GBM cohort are transferred onto healthy host brains from the Human Connectome Project through the MNI152 template as a proxy, diffusion orientation distribution functions (dODFs) are reconstructed on each host, and stochastic streamline propagation with the MRtrix3 iFOD2 algorithm yields volumetric occupancy maps. Propagation parameters are fitted per tumour under a three-stage curriculum that tightens a constrained five-metric objective. Across 30 unifocal tumours, each propagated onto 65 validation hosts (1 950 tumour-host pairings), the simulator reached a per-tumour median Dice coefficient of 0.748 (0.745 pooled across all pairings) and a median bounded Hausdorff agreement of 0.776. Because parameters are calibrated against each tumours own reference mask and the train/validation split is over hosts, these figures quantify reproduction and host-transfer of a known lesion; prediction of unseen tumours is outside their scope. On a purposively selected ten-tumour subset, controlled comparisons tested both the contribution of directional information and whether a richer angular reconstruction improved performance. Relative to a direction-blind isotropic null, orientation-informed tracking improved all five evaluated metrics (dz = 0.4-1.2), although only surface Dice remained significant after Holm correction. A second comparison replaced the multi-shell SHORE dODF with a single-tensor dODF while keeping the tracking framework unchanged. No statistically detectable differences were observed between the two directional models on this subset, providing no evidence that resolving crossing fibres improved agreement with the visible tumour envelope. Directional sampling improved agreement with the MRI-visible tumour core, but the selected subset provided no evidence that the SHORE dODF outperformed the tensor dODF.

neuroscience↗

bioRxiv2025

Testing the Vogt-Bailey Index using task-based fMRI across pulse sequence protocols

Local connectivity analyses in fMRI such as the Vogt-Bailey Index, investigate the prevalence of co-fluctuations in the time-series of adjacent voxels. While there have been in silico assessments of the VB Index, this technique has not yet been assessed in vivo. This study has two aims: first, to assess the VB Index using a task paradigm with well established a priori expectations on the brain region predominantly responsible for executing this task to determine whether the VB Index highlights this area. Second, we investigate if, and how, the spatial resolution of the sequence protocols employed, with their inherent effects on the signal-to-noise ratio, affect the resultant VB maps. A cohort of 10 research volunteers underwent fMRI acquisitions utilising a block design finger tapping experiment. Each volunteer was scanned with three sequence protocols, with all parameters equivalent except for the volume of the voxels. The resulting parametric maps derived using the VB Index were compared with those obtained from the conventional General Linear Model approach. Particular emphasis was placed on the identification of the hand portion of the motor homunculus. Across sequence protocols, the VB Index consistently identified elevated local connectivity in, qualitatively, the same portion of the motor cortex as that yielded by the General Linear Model based on the task paradigm. However, the VB Index also detected elevated local connectivity outside the motor cortex while the General Linear Model results were mostly restricted to the motor cortex. The consistently high VB Index, across sequence protocols, in the cortical region associated with an fMRI task paradigm, despite the approachs agnosticism to that task, provides support for the biological relevance of such local connectivity measures.

neuroscience↗

bioRxiv2022

The Vogt-Bailey index: a local gradient analysis

In this work, we take a closer look at the Vogt-Bailey (VB) index, proposed in Ref. [1] as a tool for studying local functional homogeneity in the human cortex. We interpret the VB index in terms of the minimum ratio cut, a parameter that indicates whether a network can easily be disconnected into two parts having a comparable number of nodes. In our case, the nodes of the network consist of a brain vertex/voxel and its nearest neighbours, and a given edge is weighted according to the affinity of the nodes it connects (as reflected by the modified Pearson correlation between their fMRI time series). Consequently, the minimum ratio cut quantifies the degree of small-scale similarity in brain activity: the greater the similarity, the heavier the edges and the more difficult it is to disconnect the network, hence the higher the value of the minimum ratio cut. We compare the performance of the VB index with that of the Regional Homogeneity (ReHo) algorithm, commonly used to assess whether voxels in close proximity have synchronised fMRI signals, and find that the VB index is uniquely placed to detect sharp changes in the (local) functional organization of the human cortex.

neuroscience↗