ArticleJournal of neuro-oncology2026
Longitudinal connectomics-based tractometry for characterizing white matter reorganization following brain tumor surgery: a proof-of-concept case series.
Article in Journal of neuro-oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeConnectomics-based neurosurgery enables patient-specific characterization of white matter architecture and may provide novel insights into network adaptation following brain tumor treatment. Quantitative tractometry allows longitudinal measurement of white matter microstructural integrity, yet its application in neurosurgical oncology remains limited. We evaluated the utility of combining tract-level asymmetry metrics with exploratory network-level analyses to characterize white matter reorganization following tumor resection.
methodsWe retrospectively analyzed serial connectome imaging obtained at several clinical timepoints, including before and after surgery or radiation therapy in three patients undergoing brain tumor resection. Fractional anisotropy (FA) values were extracted from six bilateral white matter tracts. Hemispheric asymmetry was quantified using asymmetry index (AI) and percentage asymmetry (%Asym) metrics. A novel global asymmetry burden (GAB) metric was introduced to summarize cumulative hemispheric lateralization across tracts. To explore coordinated longitudinal tract remodeling, patient-specific structural covariance networks were constructed from pairwise correlations of tract FA values across imaging timepoints. Network strength was summarized as the mean absolute correlation between tract pairs and evaluated using permutation testing.
resultsDistinct longitudinal asymmetry patterns were observed across patients. GAB demonstrated heterogeneous trajectories over time, while tract-level ranking identified the arcuate fasciculus and superior longitudinal fasciculus as the most variable pathways. Exploratory structural covariance analysis showed one patient exhibited greater temporal coordination of tract remodeling than expected under the applied permutation framework (network strength = 0.648; p = 0.045), whereas the others did not.
conclusionLongitudinal connectomics-based tractometry is a useful framework for characterizing patient-specific white matter reorganization following brain tumor surgery.
Indexed as
Identifiers
42552291What Socratic holds
Registered trials
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 Socratic graph.