Accurate delineation of white matter tracts is critical in the pre-operative assessment of paediatric brain tumour patients, where preservation of eloquent pathways directly influences surgical planning and functional outcomes. Tractfinder is a recently introduced automated method for white matter tract segmentation in tumour patients, but its voxel-based (mask) outputs limit compatibility with streamline-based tractography tools, visualisation workflows, and downstream analytical frameworks. Here we introduce Tractfinder-constrained Tractography (TcT), a streamline-based extension that constrains probabilistic tractography to the probability maps produced by Tractfinder, generating streamline representations while preserving the speed and automation that make Tractfinder clinically appealing. We evaluated TcT in ten pre-operative paediatric patients with supratentorial tumours, targeting three clinically relevant tracts – the corticospinal tract, arcuate fasciculus, and optic radiation. Spatial agreement between TcT and conventional tractography was assessed using Bundle Adjacency (BA). Mean BA scores across all three tracts ranged from 2.1 to 2.6 mm, comparing favourably against published inter-protocol benchmarks for conventional probabilistic tractography (4.3 mm), and approaching within-protocol variability. The TcT pipeline was fully automated, required no manual region-of-interest placement, and completed in approximately 5–15 min per subject compared to 1–2 h for conventional tractography. These results demonstrate that TcT produces streamline-based tract segmentations with good spatial agreement to conventional tractography, while offering substantially reduced processing time and operator burden.
A rapid streamline-based extension of Tractfinder for white matter tract segmentation
Jonathan D. Clayden

