Contacts
Intranet
SK
Daniel Gogola
National projects
| DUOFLUOR – Dual‑tuned ¹H/¹⁹F RF coil for preclinical MRI | |
| Duálne ladená ¹H/¹⁹F RF cievka pre predklinické MRI | |
| Program: | SRDA |
| Duration: | 1.9.2026 – 31.8.2030 |
| Project leader: | Ing. Gogola Daniel, PhD. |
| Annotation: | The project focuses on the design, optimization, and experimental verification of a dual‑tuned ¹H/¹⁹F radiofrequency (RF) coil intended for preclinical MRI. Combined ¹H/¹⁹F imaging represents a promising technology enabling simultaneousanatomical (¹H) and quantitative functional measurements (¹⁹F), particularly in studies involving the biodistribution offluorinated compounds, cell‑tracking applications, inflammatory processes, and functional lung imaging. The absence of endogenous ¹⁹F signal in biological tissues allows absolute quantification without background reconstruction, which increases the accuracy and interpretability of measurements. Despite its potential, only a limited number of solutions optimized for small‑animal imaging currently exist, and available systems often do not achieve the required sensitivity and B₁ homogeneity for fluorine MRI.The project includes the development of detailed FEM/FDTD models of various coil geometries, their optimization for bothresonance frequencies, and the subsequent construction of a physical prototype. The experimental phase will involveS‑parameter and Q‑factor measurements, B₁ field mapping, and testing of tuning stability. The functional performance ofthe coil will be evaluated using phantoms with defined fluorine content and, in the final stage, through preclinical measurements in small animals. The project also includes the development of a software tool that enables the calculationand optimization of RF coil parameters for different dimensions and frequencies.The outcome of the project will be an experimentally validated dual‑tuned ¹H/¹⁹F RF coil and a complete methodology forits design, applicable in preclinical research, pharmacological studies, and the development of fluorinated markers. Theproject will contribute to the advancement of preclinical MRI technologies in Slovakia and create a foundation for furtherinterdisciplinary applications in biomedical imaging. |
| TRACE-DC – Non-invasive measurement and metrological traceability of DC component in modern networks with battery storage | |
| Neinvazívne meranie a metrologická sledovateľnosť jednosmernej zložky v moderných sieťach s batériovými úložiskami | |
| Program: | SRDA |
| Duration: | 1.9.2026 – 28.2.2029 |
| Project leader: | Ing. Gogola Daniel, PhD. |
| Annotation: | In the context of Slovakia\’s energy transformation, the share of renewable energy sources and battery storage systems integrated into the electricity grid is increasing. These devices operate with direct current (DC) but connect to alternating current (AC) networks, requiring metrologically reliable on-site measurement of DC power and energy. The first objective is to test and characterize a non-invasive DC sensor for measuring high currents (up to 1200 A) with 0.1% accuracy, suitable for battery storage, photovoltaic systems, and electric mobility. The second objective is to establish a reference standard for DC power and energy traceable to national standards. Additionally, connecting DC sources without transformers injectsDC components into AC networks, causing overheating, increased losses, and reduced power quality. The project therefore investigates the impact of DC components on AC electricity meters, with results serving as a basis for updating legislative requirements. The project supports the development of smart energy grids and contributes to effective electricity flow management in Slovakia\’s economy. |
| FERINO – Advanced diagnostics of neurodegenerative disorders using magnetic resonance techniques and artificial intelligence | |
| Pokročilá diagnostika neurodegeneratívnych 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. |
| QuantMR – Optimization and Standardization of Quantitative Magnetic Resonance Imaging Methods. Suppression of Metallic Artifacts on low-field MR Scanners | |
| Optimalizácia a štandardizácia kvantitatívnych metód zobrazovania magnetickou rezonanciou. Potlačenie kovových artefaktov na nízkopolových MR skeneroch | |
| Program: | Plán obnovy EÚ |
| Duration: | 1.9.2024 – 31.8.2026 |
| Project leader: | Ing. Gogola Daniel, PhD. |
| 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). |