Standardized methodology for assessing the presence, variants and area of the interthalamic adhesion using anatomical MRI (SNAP-IA): multicentric validation on 565 healthy individuals and multiple neurological disorders.

Overview

1. Centre de recherche Cerveau et Cognition (Cerco), UMR5549, CNRS – Université de Toulouse,Toulouse, France
2. Univ Toulouse, Inserm, ToNIC, Toulouse, France
3. Geroscience Center for Brain Health and Metabolism (GERO),Santiago, Chile
4. Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department – ICBM, Neuroscience and East Neuroscience Departments, Faculty of Medicine, University of Chile,Avenida Salvador 486, Providencia, Santiago, Chile
5. Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton,Southampton, UK
6. Center for Biomedical Imaging (CIBM), University of Lausanne,Lausanne, Switzerland
7. Radiology Department (CHUV), Lausanne University Hospital,Lausanne, Switzerland
8. Max Planck Institute for Biological Cybernetics,Tuebingen, Germany
9. Neuroimagerie diagnostique et thérapeutique, CHU de Bordeaux,33000 Bordeaux, France
10. Univ. Bordeaux, INSERM,Neurocentre Magendie, U1215, 3300 Bordeaux, France

Abstract

The interthalamic adhesion (IA) connects both thalami. Emerging research suggests it may support thalamo-cortical connectivity and could be involved in neurodevelopmental and neuropsychiatric conditions. However, inconsistent MRI evaluation hinders progress on this subject. We developed SNAP-IA, a standardized anatomical imaging protocol for consistent IA identification and quantification. This work leveraged the expertise from seven research teams (Toulouse, Santiago, Southampton, Lausanne, Tübingen, and Bordeaux). SNAP-IA includes three steps: (1) determination of IA presence/absence on T1-weighted MRI; (2) classification of IA variants (simple, broad, double, bilobar, and filiform); (3) segmentation-based area assessment. It was tested on 500 controls (20–69 yo) and patients (stroke, schizophrenia, bipolar disorder, and ADHD) with 0.6–1 mm isotropic T1-weighted MRI (3T to 9.4T). SNAP-IA application achieved high inter-dataset agreement (mean Dice ≈ 0.92), with an average identification time of 35 s. The IA was absent in 22.8% of controls. Simple and broad variants constituted 95% of identified IA while some variants (double, filiform) were observed less frequently. At 3T, females had a higher presence rate (84.4%) than males (69.8%) and a larger IA area. ANCOVA indicated that both age and gender were highly predictive of IA area, decreasing by 0.25 mm²/year. At 9.4T, absence rates were significantly higher (34.6%) than at 3T (18.1%, p = 0.002). Mean IA area did not differ significantly between 3T and 9.4T. Patients with neurodevelopmental or neuropsychiatric disorders had two times less IA presence, with significantly smaller IA. SNAP-IA provides a reliable, reproducible framework for anatomical IA assessment across populations and MRI sequences, enabling future research into its structural and functional roles and supporting automated, large-scale AI studies.

Supplementary Information: The online version contains supplementary material available at 10.1007/s00429-026-03097-6.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data and to no code of its authors: see the Data section.

Protocol summary and availability

This protocol is called SNAP (Standardized Neuroanatomical Assessment Protocol) and is applied to the IA (SNAP-IA). A schematic summary of SNAP-IA is represented in Fig. 2. A detailed video protocol outlining the IA characterization process is publicly available (https://github.com/Julievidal8/SNAP-IA-protocol).

Fig. 2 Schematic representation of SNAP-IA, illustrating the progression of the protocol from suggested parameters to specific assessment (highlighted in yellow diamonds). Step 1: presence or absence of the IA; Step 2: identification of IA anatomical variants; and Step 3: IA area

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

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Data

Datasets cited

• github.com/julievidal8](https:/github.com, at github.com; found in “Data availability”

Data availability

A detailed video protocol outlining the IA characterization process is publicly available ( [https://github.com/Julievidal8/SNAP-IA-protocol](https:/github.com/Julievidal8/SNAP-IA-protocol) ). Datasets, including IA segmentations and characterizations performed using SNAP-IA, are made publicly available or provided upon request ( [https://github.com/Julievidal8](https:/github.com/Julievidal8) ).

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 5 keywords, 13 MeSH terms, 1 funder, 55 references.

Cite

This paper

Vidal, J. P., Forno, G., Hornberger, M., Cuadra, M. B., Danet, L., Kumar, V. J., Péran, P., Tourdias, T., & Barbeau, E. J. (2026). Standardized methodology for assessing the presence, variants and area of the interthalamic adhesion using anatomical MRI (SNAP-IA): multicentric validation on 565 healthy individuals and multiple neurological disorders. Brain structure & function, 231(3), 42. https://doi.org/10.1007/s00429-026-03097-6

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