Esten Høyland Leonardsen

• de Lange, Ann-Marie Glasø; Leonardsen, Esten Høyland; Barth, Claudia; Schindler, Louise S.; Crestol, Arielle & Holm, Madelene Christin [Vis alle 10 forfattere av denne artikkelen] (2024). Parental status and markers of brain and cellular age: A 3D convolutional network and classification study. Psychoneuroendocrinology. ISSN 0306-4530. 165. doi: 10.1016/j.psyneuen.2024.107040.
• Beck, Dani; de Lange, Ann-Marie Glasø; Gurholt, Tiril Pedersen; Voldsbekk, Irene; Maximov, Ivan & Subramaniapillai, Sivaniya [Vis alle 19 forfattere av denne artikkelen] (2024). Dissecting unique and common variance across body and brain health indicators using age prediction. Human Brain Mapping. ISSN 1065-9471. 45(6). doi: 10.1002/hbm.26685.
• Leonardsen, Esten Høyland; Persson, Karin Ester Torun; Grødem, Edvard Olaf Sætersdal; Dinsdale, Nicola; SCHELLHORN, TILL & Roe, James Michael [Vis alle 16 forfattere av denne artikkelen] (2024). Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence. npj Digital Medicine. 7(1). doi: 10.1038/s41746-024-01123-7.
• Iakunchykova, Olena; Leonardsen, Esten Høyland & Wang, Yunpeng (2024). Genetic evidence for causal effects of immune dysfunction in psychiatric disorders: where are we? Translational Psychiatry. ISSN 2158-3188. 14(1), s. 1–11. doi: 10.1038/s41398-024-02778-2.
• Dahl, Andreas; Eilertsen, Espen Moen; Fernandez Rodriguez Cabello, Sara; Norbom, Linn B.; Tandberg, Anneli D. & Leonardsen, Esten [Vis alle 11 forfattere av denne artikkelen] (2024). Genetic and brain similarity independently predict childhood anthropometrics and neighborhood socioeconomic conditions. Developmental Cognitive Neuroscience. ISSN 1878-9293. 65, s. 1–11. doi: 10.1016/j.dcn.2023.101339. Fulltekst i vitenarkiv
• Persson, Karin Ester Torun; Leonardsen, Esten Høyland; Edwin, Trine Holt; Knapskog, Anne-Brita; Tangen, Gro Gujord & Selbæk, Geir [Vis alle 9 forfattere av denne artikkelen] (2023). Diagnostic accuracy of brain age prediction in a memory clinic population and comparison with clinically available volumetric measures. Scientific Reports. ISSN 2045-2322. 13. doi: 10.1038/s41598-023-42354-0. Fulltekst i vitenarkiv Vis sammendrag

  The aim of this study was to assess the diagnostic validity of a deep learning-based method estimating brain age based on magnetic resonance imaging (MRI) and to compare it with volumetrics obtained using NeuroQuant (NQ) in a clinical cohort. Brain age prediction was performed on minimally processed MRI data using deep convolutional neural networks and an independent training set. The brain age gap (difference between chronological and biological age) was calculated, and volumetrics were performed in 110 patients with dementia (Alzheimer’s disease, frontotemporal dementia (FTD), and dementia with Lewy bodies), and 122 with non-dementia (subjective and mild cognitive impairment). Area-under-the-curve (AUC) based on receiver operating characteristics and logistic regression analyses were performed. The mean age was 67.1 (9.5) years and 48.7% (113) were females. The dementia versus non-dementia sensitivity and specificity of the volumetric measures exceeded 80% and yielded higher AUCs compared to BAG. The explained variance of the prediction of diagnostic stage increased when BAG was added to the volumetrics. Further, BAG separated patients with FTD from other dementia etiologies with > 80% sensitivity and specificity. NQ volumetrics outperformed BAG in terms of diagnostic discriminatory power but the two methods provided complementary information, and BAG discriminated FTD from other dementia etiologies.

• Korbmacher, Max; Wang, Mengyun; Eikeland, Rune; Buchert, Ralph; Andreassen, Ole & Espeseth, Thomas [Vis alle 10 forfattere av denne artikkelen] (2023). Considerations on brain age predictions from repeatedly sampled data across time. Brain and Behavior. ISSN 2162-3279. doi: 10.1002/brb3.3219. Fulltekst i vitenarkiv
• Leonardsen, Esten Høyland; Vidal-Piñeiro, Didac; Roe, James Michael; Frei, Oleksandr; Shadrin, Alexey & Iakunchykova, Olena [Vis alle 14 forfattere av denne artikkelen] (2023). Genetic architecture of brain age and its casual relations with brain and mental disorders. Molecular Psychiatry. ISSN 1359-4184. doi: 10.1038/s41380-023-02087-y. Fulltekst i vitenarkiv
• Holm, Madelene Christin; Leonardsen, Esten Høyland; Beck, Dani; Dahl, Andreas; Kjelkenes, Rikka & de Lange, Ann-Marie Glasø [Vis alle 7 forfattere av denne artikkelen] (2023). Linking brain maturation and puberty during early adolescence using longitudinal brain age prediction in the ABCD cohort. Developmental Cognitive Neuroscience. ISSN 1878-9293. 60. doi: 10.1016/j.dcn.2023.101220. Fulltekst i vitenarkiv
• Leonardsen, Esten Høyland; Peng, Han; Kaufmann, Tobias; Agartz, Ingrid; Andreassen, Ole & Celius, Elisabeth Gulowsen [Vis alle 19 forfattere av denne artikkelen] (2022). Deep neural networks learn general and clinically relevant representations of the ageing brain. NeuroImage. ISSN 1053-8119. 256. doi: 10.1016/j.neuroimage.2022.119210. Fulltekst i vitenarkiv Vis sammendrag

  The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data — the brain age delta — has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into one of the largest and most diverse datasets assembled (n=53542), and trained convolutional neural networks (CNNs) to predict age. We achieved state-of-the-art performance on unseen data from unknown scanners (n=2553), and showed that higher brain age delta is associated with diabetes, alcohol intake and smoking. Using transfer learning, the intermediate representations learned by our model complemented and partly outperformed brain age delta in predicting common brain disorders. Our work shows we can achieve generalizable and biologically plausible brain age predictions using CNNs trained on heterogeneous datasets, and transfer them to clinical use cases.

• Vidal-Piñeiro, Didac; Wang, Yunpeng; Krogsrud, Stine Kleppe; Amlien, Inge; Baaré, William FC & Bartres-Faz, David [Vis alle 31 forfattere av denne artikkelen] (2021). Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change. eLIFE. ISSN 2050-084X. 10. doi: 10.7554/eLife.69995. Fulltekst i vitenarkiv

Se alle arbeider i Cristin

• Abdulkadir, Ahmed; Dvornek, Nicha C.; Habes, Mohamad; Leonardsen, Esten Høyland; Xiao, Yiming & Bathula, Deepti R. [Vis alle 9 forfattere av denne artikkelen] (2023). Preface. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 14312, s. v–vi.
• Roe, James Michael & Leonardsen, Esten Høyland (2023). Brain age as a marker of overall brain health: Phenotypic associations, genetic foundations and causal relationships.
• Korbmacher, Max; Wang, Meng-yun; Eikeland, Rune; Buchert, Ralph; Andreassen, Ole & Espeseth, Thomas [Vis alle 10 forfattere av denne artikkelen] (2023). Field strength and potentially scan quality influence brain age estimates. Fulltekst i vitenarkiv

Se alle arbeider i Cristin