Evidence map›Paper›PMID 42519527›Full record

ArticleFrontiers in neuroimaging2026

A rapid streamline-based extension of Tractfinder for white matter tract segmentation.

Dana Kanel, Fiona Young, Kiran K Seunarine, Chris A Clark, Kristian Aquilina, Jonathan D Clayden

Abstract read
In one paragraph

Article in Frontiers in neuroimaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Dana KanelDevelopmental Imaging and Biophysics Section, UCL GOS Institute of Child Health, London, United Kingdom.
Fiona YoungSoftware Engineering and Artificial Intelligence Science Technology Platform, The Francis Crick Institute, London, United Kingdom.
Kiran K SeunarineDevelopmental Imaging and Biophysics Section, UCL GOS Institute of Child Health, London, United Kingdom.
Chris A ClarkDevelopmental Imaging and Biophysics Section, UCL GOS Institute of Child Health, London, United Kingdom.
Kristian AquilinaDepartment of Neurosurgery, Great Ormond Street Hospital for Children, London, United Kingdom.
Jonathan D ClaydenDevelopmental Imaging and Biophysics Section, UCL GOS Institute of Child Health, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

dMRIpaediatric brain tumourspre-operativetractographytract segmentation

Identifiers

PMID42519527
PMCPMC13381243

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.