Daniel Gogola

Project selection:

International projects

SP4LIFE – Smart Patch for Life Support Systems
Inteligentná náplasť pre systémy na udržanie života
Program: NATO
Duration: 10.3.2021 – 10.3.2024
Project leader: doc. Ing. Tyšler Milan, CSc.
Annotation: Wearable real-time systems collecting and smartly analysing information on respiration, heartbeat, SpO2, blood pressure and body temperature could help medical personnel adopting most suitable countermeasure in case of highly stressful situations in military and civil scenarios as a result of terrorist attacks, IEDs’ or rescue operations. The system gives an alert if the health status of a person is changed to prevent overlook of critical health changes. We propose design and development of a patch-like device prototypes and methodology enabling continuous evaluation of personnel or victims’ vital parameters, using Artificial Intelligence to create software capable of real-time diagnostics and rapid countermeasures’ selection.
Project website:

National projects

FERINO – Advanced diagnostics of neurodegenerative disorders using magnetic resonance techniques and artificial intelligence
Pokročilá diagnostika neurodegenerat ívnych ochorení pomocou techník magnetickej rezonancie a umelej inteligencie
Program: SRDA
Duration: 1.7.2023 – 30.6.2027
Project leader: Ing. Gogola Daniel, PhD.
Annotation: Neurodegenerative diseases (ND) are becoming a severe problem in developed countries. Since we currently haveno effective therapies available, early diagnosis is critical to ensure a good quality of life for ND patients. ND arecharacterized by iron accumulation and magnetite mineralization in brain tissue, with ferritin as a precursor. Due toits low relaxivity, physiological ferritin is at the edge of visibility using magnetic resonance imaging (MRI)techniques. On the contrary, "pathological" ferritin causes a significant shortening of MRI relaxation times. Thiscreates hypointense artifacts, which theoretically allow the distinguishability of both proteins. Since ironaccumulation precedes the clinical symptoms of the disease, MRI has the potential to become a non -invasivediagnostic method for the early stages of ND. At present, however, this is limited by the insufficient characterizationof the relaxation properties of biogenic iron and the uncertainty in the interpretation of clinical data. Therefore, ourbasic goal (application output) is the development of a comprehensive methodology (FERINO software tool) for theunequivocal diagnosis of the early stages of ND. To reach our goal, we will use a combination of several diagnostictechniques and artificial intelligence tools. The diagnostic techniques include in-vitro, in-silico, and in-vivocharacteristics of ferritin relaxation, structural MRI, magnetic resonance spectroscopy (MRS), neurological tests,and clinical biochemistry biomarkers. The cornerstone of the methodology will be the FerroQuant software tool,which was proposed by the principal investigator within the APVV 2012. It enables the analysis and quantificationof iron-related clinical MRI data but lacks new findings in iron MRI (false-positive artifacts, ferritin\’s mineral phases).FerroQuant also does not use artificial intelligence and does not combine different diagnostic data, whic h, however,will be an integral part of the FERINO tool.
MRCartilage – Automatic data evaluation tool from the longitudinal quantitative MRI studies of articular cartilage
Automatický softvérový nástroj na výhodnocovanie kvantitatívnych MRI štúdií artikulárných chrupaviek v čase
Program: SRDA
Duration: 1.7.2022 – 30.6.2026
Project leader: Ing. Dr. Szomolányi Pavol, (PhD.)
Annotation: The aim of the project is to design a comprehensive tool for automatic evaluation of human articular cartilage data from quantitative MRI. Data obtained from the Osteoarthritis Initiative database, and measured at Institute of Measurement Science and Medical University of Vienna will be segmented using an automated segmentation tool based on convolutional neural networks. The annotated data will then be registered on quantitative MRI data that will be available from the database (T2 and T1rho mapping, gagCEST, sodium MR) using automated or semiautomated tools developed within this project. The data obtained will be evaluated at multiple time points according to MR measurements that will be available. In addition to quantitative MR data, this will include volumetric data, cartilage thickness, and texture analysis of quantitative maps. Patient evaluation will be based on risk factor groups (transverse ligament rupture, meniscus rupture and menisectomy). The expected number of patients is approximately 4000 divided into individual groups in the ratio 40/30/30. The output of the project will be a compiled version of an automatic cartilage evaluation tool that will be available in a public source (such as website of Institute of Measurement).