Unravelling differences and hallmarks in suspected diffuse low-grade gliomas: a multicentre database study

Francesco Latini ¹, Markus Fahlström ², Alice Neimantaite ³

¹Department of Medical Sciences, Section of Neurosurgery Uppsala University Hospital, S-75185 Uppsala, Sweden.
²Department of Surgical Sciences, Molecular Imaging and Medical Physics, Uppsala University, S-75185 Uppsala, Sweden.
³Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden.
⁴Institute of Health and Care Sciences, Sahlgrenska Academy, University of Gothenburg, 40530 Gothenburg, Sweden.
⁵Department of Neurosurgery, Sahlgrenska University Hospital, 40530 Gothenburg, Sweden.
⁶Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, NTNU, 7491 Trondheim, Norway.
⁷Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, 7491 Trondheim, Norway.
⁸Department of Neurosurgery, Linköping University Hospital, 58185 Linköping, Sweden.
⁹Department of Biomedical and Clinical Sciences, Linköping University, 58185 Linköping, Sweden.
¹⁰Department of Neurosurgery, University Hospital of North Norway, 9038 Tromsø, Norway.
¹¹Department of Clinical Sciences, Neuroscience, Umeå University, 90187 Umeå, Sweden.
¹²Department of Neurosurgery, University Hospital of Northern Sweden, 90187 Umeå, Sweden.
¹³Department of Neurosurgery, Skåne University Hospital, 22185 Lund, Sweden.
¹⁴Department of Clinical Medicine, Faculty of Medicine, University of Bergen, 5020 Bergen, Norway.
¹⁵Department of Neurosurgery, Haukeland University Hospital, Bergen 5020, Norway.
¹⁶Department of Radiology, Sahlgrenska University Hospital, 40530 Gothenburg, Sweden.
¹⁷Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
¹⁸Department of Neurosurgery, Karolinska University Hospital, 17176 Stockholm, Sweden.
¹⁹Department of Neurosurgery, Copenhagen University Hospital Rigshospitalet, 2100 Copenhagen, Denmark.

⁰Department of Medical Sciences, Section of Neurosurgery Uppsala University Hospital, S-75185 Uppsala, Sweden.

Brain Communications +

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October 13, 2025

View abstract on PubMed

Summary

This study reveals distinct clinical and radiological phenotypes for diffuse low-grade glioma (DLGG) molecular subgroups. Integrating patient and tumor features aids in understanding DLGG progression and developing predictive models.

Area Of Science

Neuro-oncology
Radiology
Molecular Pathology

Background

Diffuse low-grade gliomas (DLGG) natural history is influenced by molecular status.
Preoperative clinical and radiological data integration may enhance understanding of DLGG.
Identifying distinct phenotypes for DLGG molecular subgroups is crucial for prognosis.

Purpose Of The Study

To systematically analyze clinical and radiological phenotypes of DLGG molecular subgroups at diagnosis.
To identify differences in age, tumor location, onset symptoms, and cognitive status among DLGG molecular subgroups.
To explore the utility of integrated clinico-radiological approaches for DLGG prediction models.

Main Methods

Analysis of 235 patients with World Health Organization (WHO) grade 2 gliomas from nine Scandinavian centers.
Inclusion of patients with known isocitrate dehydrogenase (IDH) status and 1p19q codeletion status.
Utilized MRI-based tumor volume segmentation, Brain-Grid (BG) system for invasiveness analysis, and regression analyses.

Main Results

Three molecular subgroups (IDH-mutated astrocytomas, oligodendrogliomas, IDH-wildtype astrocytomas) showed significant differences in age, location, onset, and cognitive status.
Seizure onset correlated with BG voxel count and specific locations (A3C2S2).
Cognitive deficits related to age, gender, and tumor volume, with specific white matter tract infiltrations predicting subgroups.

Conclusions

Integrated clinico-radiological analysis identified distinct phenotypes across DLGG molecular subgroups.
Patient-specific (age, onset) and tumor-specific (location, infiltration) features are relevant for preoperative DLGG understanding.
Combining clinical and radiological data offers potential for improved DLGG prediction models and understanding of onco-functional trajectory.

Keywords:

diffuse low-grade gliomas epilepsy molecular profile onco-functional trajectory white matter