Profile photo Stefano Mandija

Stefano Mandija

Assistant Professor

Strategic program(s):

Biography

Stefano is currently employed as assistant professor at the radiotherapy department of the University Medical Center Utrecht (The Netherlands). His research topics range from fundamental and methodological research to clinical development of quantitative MRI methods and MRI biomarkers for diagnostic and radiotherapy treatment response prediction and monitoring. In particular, he works on the characterization of tissue electrical properties for radiotherapy treatments efficacy assessment using MRI (NWO recipient VENI grant 2020), MRI-guided cardiac radio-ablation using stereotactic radiotherapy (STOPSTORM.eu consortium), MRI-based guidance of spinal cord stimulation (RESTORE and Prep2GO consortia), and he also supports the development and translation of quantitative MRI methods in clinical settings (MR-STAT).

Background

Stefano was born in Camposampiero, Padua (Italy) in September 1988. He was educated as a bioengineer at the University of Padua, 2007-2013. Afterwards, he moved to The Netherlands where he received his Ph.D. in the field of non-invasive characterization of tissue electrical properties with MRI at the University Medical Center Utrecht (The Netherlands) in 2018. Subsequently, he was offered a Post-Doc position at the Radiology and Radiotherapy departments of the University Medical Center Utrecht. Because of his passion for MRI and his positive attitude, which makes him looking at research challenges as new opportunities to expand his knowledge and to establish new collaborations, he also recently started investigating MRI-based guidance of cardiac ablation using stereotactic radiotherapy at the radiotherapy department of the University Medical Center Utrecht within the European STOPSTORM consortium.

Strategic program(s):

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Research groups

Computational Imaging Group for MRI Therapy & Diagnostics

Research aim

The Computational Imaging Group develops and apply new MR image acquisition, reconstruction and processing techniques for MRI-guided radiotherapy and diagnostic applications. The group is headed by Prof. Nico van den Berg and dr. Alessandro Sbrizzi.

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Recent publications

Deep learning-based relaxometry from conventional brain MRI: applications to a large-scale, clinically heterogeneous dataset Jelmer van Lune, Stefano Mandija, Oscar van der Heide, Matteo Maspero, Martin Schilder, Cornelis van den Berg, Alessandro Sbrizzi
2026
Clinical Applications of Electrical Conductivity Imaging Using MRI Stefano Mandija, Khin Khin Tha, Nitish Katoch, Cihan Göksu, Ulrich Katscher, Rosalind Sadleir, Kyu Jin Jung, Jierong Luo, Ilias I. Giannakopoulos, Dong Hyun Kim, Karin Shmueli, Riccardo Lattanzi, Yusuf Ziya Ider, Axel Thielscher, Cornelis van den Berg
Journal of Magnetic Resonance Imaging, 2026, vol. 63, p.1224-1245
Characterization of a deformable beating cardiac phantom with real-time dosimetric capabilities for validation of MRI-guided heart radiotherapy Manon M N Aubert, Prescilla Uijtewaal, Kalin I Penev, Yoan LeChasseur, Nick Hartman, Laurie J M de Vries, Paris Tzitzimpasis, Pim T S Borman, Stefano Mandija, Martin F Fast, Astrid L H M W van Lier
Medical physics, 2026, vol. 53
Standardization of MR Electrical Properties Tomography Stefano Mandija, Alessandro Arduino, Chuanjiang Cui, Patrick Fuchs, Ilias I Giannakopoulos, Yusuf Ziya Ider, Kyu-Jin Jung, Nitish Katoch, Ulrich Katscher, Dong-Hyun Kim, Riccardo Lattanzi, Thierry Meerbothe, Freddy Odille, Karin Shmueli, Paul Soullié, Khin Khin Tha, Luca Zilberti, Cornelis A T van den Berg
Journal of Magnetic Resonance Imaging, 2026, vol. 63, p.1204-1207
Retrospective relaxometry from conventional contrasts by physics-informed deep learning: A pilot on Tumor, MS, Stroke and Epilepsy patients Jelmer van Lune, Stefano Mandija, Martin Schilder, Luuk Jacobs, Jordi Kleinloog, Matteo Maspero, Sarah Jacobs, Cornelis van den Berg, Alessandro Sbrizzi
2025
Detecting dopaminergic degeneration in clinically uncertain parkinsonian syndrome patients using fast MR-STAT relaxometry Martin Schilder, Elon Wallert, Stefano Mandija, Oscar van der Heide, Hanna Liu, Miha Fuderer, Jan Booij, Rob de Bie, Martijn Beudel, Henk Berendse, Tom van Mierlo, Jeroen Blankevoort, Cornelis van den Berg, Elsmarieke van de Giessen, Alessandro Sbrizzi
2025

Fellowships & Awards

Grants:

NWO VIDI Grant: MRI-TARGET (2025): MR-based Imaging of Tissue conductivity and quAntitative paRameters for Guidance of cancEr Therapy.

EU-Metrology EURAMET Grant (2025): Trustworthy and quality-assured quantitative MRI.

Health-Holland TKI-LSH Grant (2024): Cardiac GPS: Gaussian Process safety navigation system for cardiac pacemaker lead placement.

EWUU AI for Preventive Care Grant (2023): Trustworthy AI for MRI safety and conductivity mapping.

Hannarth Fonds Grant (2023): Physics-informed Neural networks to standardize brain MRI: boosting AI applications in gliomas and meningiomas.

NWO Open Technology Grant (2022): MRI-Enhanced and Guided Adaptive Heart RadioTherapy.

NWO VENI Grant (2020): MR-based measurements of ‘Tissue ElectroMagnetic Properties in radiation Oncology (TEMPO)’: A predictive tool for early-stage assessment of radiotherapy treatments.

EU-Horizon Grant (2020): A prospective European Validation Cohort for Stereotactic Therapy of Reentrant Tachycardia.

Personal Awards:

Junior Fellow of the International Society for Magnetic Resonance in Medicine, ISMRM (2020)

Trainee Educational Stipend of the International Society for Magnetic Resonance in Medicine, ISMRM (2014, 2015, 2016)