Sofia Behndig

I’m a medical doctor, employed as a PhD-Student at the department of diagnostics and intervention. My reaserch utilize PET and MRI for diagnostics of normal pressure hydrocephalus.

Contact

sofia.behndig@umu.se

Works as

Doctoral student (on leave) at Department of Diagnostics and Intervention Section: Doctoral students

5A, Målpunkt H62, Norrlands universitetssjukhus Umeå universitet, 901 85 Umeå

I’m a medical doctor and PhD-student and work to develop methods to analyze the flow of cerebrospinal fluid with the aid of PET and MRI. My current research manly includes patients with normal pressure hydrocephalus. Previously I have also done some research regarding diagnostics of familiar amyloidosis with polyneuropathy

Relaxivity of gadobutrol and gadoteric acid in cerebrospinal fluid at 3T

Magnetic Resonance in Medicine, John Wiley & Sons 2026, Vol. 95, (6) : 3409-3415

Behndig, Sofia; Garpebring, Anders; Dahlgren Lindström, Daniel; et al.

Quantitative assessment of flow between cerebrospinal and interstitial fluid compartments in humans

Proceedings of the National Academy of Sciences of the United States of America, Proceedings of the National Academy of Sciences (PNAS) 2026, Vol. 123, (18)

Wåhlin, Anders; Behndig, Sofia; Eriksson De Ryst, Johan; et al.

qDESH: a method to quantify disproportionately enlarged subarachnoid space hydrocephalus

Fluids and Barriers of the CNS, Vol. 22, (1)

Behndig, Sofia; Lalou, Afroditi D.; Axelsson, Jan; et al.

Quantification of cardiac amyloid with [¹⁸F]Flutemetamol in patients with V30M hereditary transthyretin amyloidosis

Amyloid: Journal of Protein Folding Disorders, Taylor & Francis 2020, Vol. 27, (3) : 191-199

Möckelind, Sofia; Axelsson, Jan; Pilebro, Björn; et al.

Diffusion and bulk flow in cerebrospinal fluid along the major cerebral arteries

Björnfot, Cecilia; Behndig, Sofia; Eriksson De Ryst, Johan; et al.

Automated computation of a quantitative DESH score in Brain MRI for reproducible radiological assessment of hydrocephalus

Mogensen, Klara; Behndig, Sofia; Lalou, Afroditi D.; et al.

Can AI applied on MRI reliably predict shunt response in INPH?: a comprehensive exploration of deep learning and radiomics approaches using preoperative MRI

Mogensen, Klara; Guarrasi, Valerio; Behndig, Sofia; et al.

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