Daniele Piccolo, MD, BEng, PhD
Neurosurgeon · Clinician-Scientist · ex-founder & PE healthcare advisor
Consultant Neurosurgeon — Neurosurgery Department, Azienda Sanitaria Universitaria Friuli Centrale (Udine, Italy)
Consultant Neurosurgeon at the Department of Neurosurgery, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy. Clinical practice focuses on hydrocephalus (notably idiopathic Normal Pressure Hydrocephalus (iNPH) and LOVA), vascular neurosurgery and neuro-oncology, in both adult and paediatric patients. More than 1,000 neurosurgical procedures attended to date.
Research activity is developed jointly with the University of Pavia (PhD in Experimental Medicine, track: Experimental Surgery and Microsurgery) and the University of Udine, and applies quantitative neuroimaging, machine learning, radiomics and — in a translational research setting — quantum-inspired algorithms to improve preoperative stratification and surgical candidate selection. The publication record is available on ORCID, OpenAlex and PubMed.
Training combines an engineering background (BEng in Civil Engineering, University of Udine, 2011), Medicine and Surgery (MD, 110/110 cum laude, University of Udine, 2017) and Residency in Neurosurgery (110/110 cum laude, University of Padua, 2023). This clinical-academic profile is complemented by prior entrepreneurial experience as founder of a medtech start-up developing mixed-reality surgical guidance systems, and by previous advisory work in the healthcare sector with institutional investors.
Education
Current role & prior experience
Research lines
Active research areas, integrated with clinical neurosurgical practice.
- Idiopathic Normal Pressure Hydrocephalus (iNPH) and LOVA — quantitative neuroimaging, CSF dynamics, deep-learning cortical thickness, resting-state connectivity, CSF biomarkers.
- Neuro-oncology — glioblastoma (radiomics integrated with transcriptomic data), meningiomas (tumor microenvironment), posterior fossa paediatric tumors.
- Vascular neurosurgery — complex aneurysms, arteriovenous malformations and cavernomas, endovascular embolization, management of post flow-diverter recurrences.
- Functional neuromodulation — vagus nerve stimulation (VNS) for drug-resistant epilepsy, candidate selection, predictive models.
- Artificial intelligence, radiomics, multi-omics — applications of machine learning, deep learning and quantum algorithms to tumor classification, surgical selection and outcome prediction.
- Augmented and mixed reality in neurosurgery — preoperative planning and intraoperative guidance. Research line rooted in prior entrepreneurial experience (Nucleode SRL, 2017-2022).
Selected recent publications
- Piccolo D, Bagatto D, D'Agostini S, et al. Cortical thickness analysis combined with CSF dynamics improves diagnostic stratification in idiopathic normal pressure hydrocephalus. Neurosurgical Review, 2026.
- Piccolo D, Vindigni M. Radiomic Features of MRI Subcompartments Associate with Angiogenic and Inflammatory Transcriptomic Programs in Glioblastoma. Cancers, 2026; 18(8):1293. DOI
- Piccolo D, Cannizzo KM, Vindigni M, Sponza M, Gavrilovic V. Endovascular coil embolization through a previously implanted Contour intrasaccular device. J NeuroInterv Surg, 2025. DOI
- Belgrado E, Tuniz F, Piccolo D, et al. AQP4 levels in CSF correlate with clinical severity in iNPH patients. Journal of the Neurological Sciences, 2026.
- Piccolo D, Fabbro S, Tuniz F, et al. Clipping, Aneurysmotomy, and Thrombectomy of an Enlarged Thrombosed Giant PCA Aneurysm After Flow Diverter Treatment. Operative Neurosurgery, 2024. DOI
- Cobianchi L, Piccolo D, Dal Mas F, et al. Surgeons' perspectives on artificial intelligence to support clinical decision-making in trauma. World Journal of Emergency Surgery, 2023; 18(1). DOI
- Cobianchi L, Verde JM, Loftus TJ, et al. Artificial Intelligence and Surgery: Ethical Dilemmas and Open Issues. Journal of the American College of Surgeons, 2022; 235(2):268-275. DOI
Selected talks & congresses
Technical skills
Quantitative neuroimaging: processing of MRI, DTI and connectomics data for surgical planning and research — FSL, 3D Slicer, MRtrix3, FreeSurfer, FastSurfer, CAT12, DSI Studio, TrackVis, MRIcroGL, Horos, Surfice.
Data Science & Quantum Computing: multivariate statistical analysis, machine learning and quantum algorithms applied to clinical problems — R, Python, MATLAB.
Mixed Reality: development and coordination of mixed-reality surgical guidance systems (HoloLens) and digital-health projects.
Cloud architecture: design and supervision of cloud-native EHR-HIS systems.
Industry & advisory engagements
Open to selective clinical strategy advisory work with medtech, neurotech, healthcare VC & PE.
See advisory profile