Tobias Granberg

Tobias Granberg

Adjunct Professor | Docent
Visiting address: , Stockholm
Postal address: K8 Klinisk neurovetenskap, K8 Neuro Granberg, 171 77 Stockholm
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About me

  • I am an Adjunct Professor of Neuroradiology and Research Group Leader for Neuroradiology focusing on Neurodegenerative and Neuroinflammatory disorders and also serve as the Scientific Director of KI MRI Center Core Facility. 

    After graduating from medical school at Karolinska Institutet (KI) in 2012, I undertook a two-year clinical internship at Västerås Regional Hospital. Thereafter, I completed my residency in Radiology at Karolinska University Hospital between 2014-2019. This was followed by a fellowship in Neuroradiology 2019-2022.  

    Academically, I started conducting MRI research in 2009, writing my medical thesis on MRI detection of Cerebral microbleeds in Alzheimer's disease using Susceptibility-Weighted Imaging. My PhD focused on Neuroradiological aspects of Multiple Sclerosis (MS), which I defended in 2015. I thereafter conducted a post-doctoral research fellowship at Massachusetts General Hospital and Harvard Medical School. My post-doctoral work focused on MS diagnostics using a combination of 7 Tesla MRI, 11C-PBR28 (2nd generation TSPO marker for microglia) PET-MR and Human Connectom Scanner with 300 mT/m gradients (compared to typical 40-80 mT/m clinical gradients). I also continued developing and validating myelin quantification techniques.  

    Upon my return to Karolinska Institutet, I established our research group at the Clinical Neuroscience department at KI, where we continue to focus on Quantitative imaging techniques and their applications to improve the diagnostics, prognostics and treatment evaluation in pathologies such as MS, dementia disorders, movement disorders and ALS.  

Articles

All other publications

Grants

  • Swedish Research Council
    1 January 2026 - 31 December 2029
    Dementia with Lewy bodies (DLB) is a common cause of dementia, but it is severely under-diagnosed and has no cure. The main reason for this is the lack of clinically available biomarkers for Lewy body pathology. ´FindDLB’ is a leading international project to tackle these problems.The purpose of ‘FindDLB’ is to intensify DLB research in Sweden, with a strong focus on novel biomarkers to advance our current understanding of brain pathology, neurodegeneration, and treatment in DLB. ‘FindDLB’ has four specific aims: to (1) Implement in clinical routine a novel ultra-sensitive cerebrospinal fluid biomarker for Lewy body pathology, and develop new blood biomarkers for Lewy body pathology and related processes
    (2) Elucidate the role of cholinergic degeneration in DLB
    (3) Characterize the earliest stages of neurodegeneration and subsequent disease progression in DLB
    and (4) Implement project findings into precision medicine models, with a focus on identifying best candidate patients for specific treatments
    simulating next generation clinical trials
    and preparing a trial ready cohort in Sweden. ‘FindDLB’ generates and uses a unique and unprecedented large-scale multi-cohort dataset of more than 100 000 individuals.‘FindDLB’ strives to transform the way we currently treat DLB. It will improve management and care of our DLB patients, and will increase social awareness about the disease. Project’s findings will set the ground for precision medicine-based diagnostics and therapies.
  • SCAPIS-2 Brain: Neuroradiology and new technology in interplay to evaluate cerebrovascular disease from a population perspective
    Region Stockholm (ALF Medicin)
    1 January 2025 - 31 December 2026
  • Cerebral small vessel disease in SCAPIS-2 Brain
    Swedish Stroke Association
    1 January 2025 - 31 December 2026
  • Cerebral small vessel disease in SCAPIS-2 - radiology, comorbidities, biomarkers and risk
    Swedish Stroke Association
    1 January 2024 - 31 December 2024
  • Swedish Research Council
    1 January 2024 - 31 December 2027
    Background: Amyotrophic lateral sclerosis (ALS) is a fatal disorder with heterogeneous clinical expression. While overt morphological findings are often preceded by hypometabolism in ALS, FDG-PET is sparsely used in routine clinical practice due to costs and a somewhat uncertain diagnostic/predictive value. Meanwhile, GlucoCEST MRI is a novel radiation-free method for imaging metabolism that has yet to be applied in ALS.Aim: To evaluate the feasibility and accuracy of GlucoCEST MRI for assessing brain metabolism in ALS and study its diagnostic and predictive value.Methods: A prospective study with 120 persons with ALS and 60 matched controls will be conducted at Karolinska University Hospital using a second-generation clinical 7 Tesla MRI scanner. GlucoCEST will be processed and analyzed using advanced post-processing techniques and compared to the gold-standard, FDG-PET imaging, in patients. Patients will be longitudinally followed comprehensively over up to 4 years.Significance: GlucoCEST can integrate metabolic and structural information from a single scan to detect early neurodegeneration at a lower cost and with less patient risk and -burden than FDG-PET. As a radiation-free technique, the method is especially suitable for precision medicine approaches since it can track disease progression over time to advance our understanding of neurodegenerative disease processes and monitor the efficacy of emerging disease-modifying treatments in clinical trials.
  • Swedish Research Council
    1 December 2023 - 30 November 2027
    This translational project explores mechanisms and pathophysiology, prevention and outcomes related to long-term neurocognitive decline and risk for dementia after major surgery. The ultimate goal is to provide novel prognostic and therapeutic strategies and patient-centered guidelines for safer perioperative care. We hypothesize that adverse immune response signatures to surgical trauma with impaired periphery-to-brain communication leads to unresolved systemic and neuroinflammation with risk for neurocognitive decline and dementia. Using comprehensive clinical and experimental platforms in man, animals and cells, we will in standardized surgical cohorts in Part A define a longitudinal in-depth immunological, transcriptional, and soluble atlas with a periphery-to-brain axis coupled to hard adverse brain outcomes related to neuroinflammation, neurodegeneration and risk for dementia. Key findings from this effort will in Part B be mechanistically explored in established animal models and in vitro systems to provide in-depth knowledge on targets for prognostic and possibly therapeutic strategies. Information from preclinical and clinical investigations (Part A-B) on precision-based immune signatures will be prospectively validated in broader surgical populations to search at-risk patients (part C). This knowledge will ultimately serve as base for novel perioperative guidelines and therapeutic strategies to prevent neurocognitive decline or dementia after surgery.
  • Swedish Research Council
    1 January 2023 - 31 December 2026
    Understanding how the brain changes at different stages of neurodegenerative diseases can give important information for improving their early detection and diagnosis. A promising tool for that purpose is brain connectomics, whose aim is to study the connectivity among different areas of the brain. Structural connectivity estimates the degree of connectivity among regions in the cortex by analyzing the distribution of neural fibers in the white matter (WM) computed from diffusion MRI (dMRI) data. The current tools for connectomic analyses are not accurate enough for clinical use. In this project, we aim at closing this gap by proposing new advanced artificial intelligence (AI)-based tools for performing brain connectivity analysis. We will test their effectiveness in Alzheimer’s disease (AD) and multiple sclerosis (MS). Applying AI to dMRI data is challenging and requires advanced AI methods. The specific objectives of the project are to:Develop AI-based tractography and tractogram filtering methods that are reliable for performing structural connectivity analysisAdapt generative AI architectures for creating synthetic dMRI data to improve tractography and brain connectivity analyses.Combine mechanical properties of brain tissue and microstructure parameters of WM with tractography for improving structural connectivity analyses.
  • Swedish Research Council
    1 January 2023 - 31 December 2025
  • Swedish Heart-Lung Foundation
    1 January 2021 - 31 December 2021
  • Swedish Research Council
    1 January 2018 - 31 December 2020

Employments

  • Adjunct Professor, Department of Clinical Neuroscience, Karolinska Institutet, 2025-2029
  • Senior Research Specialist, Department of Clinical Neuroscience, Karolinska Institutet, 2020-2025

Degrees and Education

  • Docent, Karolinska Institutet, 2021
  • Degree Of Doctor Of Philosophy, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 2015
  • University Medical Degree, Karolinska Institutet, 2012

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