Dr. Tugba Akinci D'Antonoli

Albano, D., Mallardi, C., Afat, S., Agnollitto, P. M., Caruso, D., Cannella, R., Carriero, S., Chupetlovska, K., Clauser, P., D’Angelo, T., De Santis, D., Dioguardi Burgio, M., Dumic-Cule, I., Fanni, S. C., Fusco, S., Gatti, M., Gitto, S., Jankovic, S., Karagechev, T., et al. (2024). How young radiologists use contrast media and manage adverse reactions: an international survey [Journal-article]. Insights into Imaging, 15(1). https://doi.org/10.1186/s13244-024-01658-z

Kocak, B., Akinci D’Antonoli, T., Mercaldo, N., Alberich-Bayarri, A., Baessler, B., Ambrosini, I., Andreychenko, A. E., Bakas, S., Beets-Tan, R. G. H., Bressem, K., Buvat, I., Cannella, R., Cappellini, L. A., Cavallo, A. U., Chepelev, L. L., Chu, L. C. H., Demircioglu, A., deSouza, N. M., Dietzel, M., et al. (2024). METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII. Insights into Imaging, 15(1). https://doi.org/10.1186/s13244-023-01572-w

Akinci D’Antonoli, T., & Rudie, J. D. (2024). Achieving More with Less: Combining Strong and Weak Labels for Intracranial Hemorrhage Detection [Journal-article]. Radiology: Artificial Intelligence, 6(6). https://doi.org/10.1148/ryai.240670

Santinha, J., Pinto dos Santos, D., Laqua, F., Visser, J. J., Groot Lipman, K. B. W., Dietzel, M., Klontzas, M. E., Cuocolo, R., Gitto, S., & Akinci D’Antonoli, T. (2024). ESR Essentials: radiomics—practice recommendations by the European Society of Medical Imaging Informatics [Journal-article]. European Radiology. https://doi.org/10.1007/s00330-024-11093-9

Woźnicki, Piotr, Laqua, Caroline, Fiku, Ina, Hekalo, Amar, Truhn, Daniel, Engelhardt, Sandy, Kather, Jakob, Foersch, Sebastian, D’Antonoli, Tugba Akinci, Pinto dos Santos, Daniel, Baeßler, Bettina, & Laqua, Fabian Christopher. (2024). Automatic structuring of radiology reports with on-premise open-source large language models [Journal-article]. European Radiology. https://doi.org/10.1007/s00330-024-11074-y

Akinci D’Antonoli, T., & Bluethgen, C. (2024). A New Era of Text Mining in Radiology with Privacy-Preserving LLMs [Journal-article]. Radiology: Artificial Intelligence, 6(4). https://doi.org/10.1148/ryai.240261

Kocak, Burak, Borgheresi, Alessandra, Ponsiglione, Andrea, Andreychenko, Anna E., Cavallo, Armando Ugo, Stanzione, Arnaldo, Doniselli, Fabio M., Vernuccio, Federica, Triantafyllou, Matthaios, Cannella, Roberto, Trotta, Romina, Ghezzo, Samuele, Akinci D’Antonoli, Tugba, & Cuocolo, Renato. (2024). Explanation and Elaboration with Examples for CLEAR (CLEAR-E3): an EuSoMII Radiomics Auditing Group Initiative [Journal-article]. European Radiology Experimental, 8(1). https://doi.org/10.1186/s41747-024-00471-z

Burak Koçak, Tugba Akinci D’Antonoli, & Renato Cuocolo. (2024). Exploring radiomics research quality scoring tools: a comparative analysis of METRICS and RQS. Diagnostic and Interventional Radiology . https://doi.org/10.4274/dir.2024.242793

Akinci D’Antonoli T., Cuocolo R., Baessler B., & Pinto dos Santos D. (2024). Towards reproducible radiomics research: introduction of a database for radiomics studies. European Radiology, 34(1), 436–443. https://doi.org/10.1007/s00330-023-10095-3

Akinci D’Antonoli, T., & Mercaldo, N. D. (2024). Reply to Letter to the Editor: “Obsolescence of nomograms in radiomics research”. European Radiology. https://doi.org/10.1007/s00330-023-10570-x

Doniselli, F. M., Pascuzzo, R., Mazzi, F., Padelli, F., Moscatelli, M., Akinci D’Antonoli, T., Cuocolo, R., Aquino, D., Cuccarini, V., & Sconfienza, L. M. (2024). Quality assessment of the MRI-radiomics studies for MGMT promoter methylation prediction in glioma: a systematic review and meta-analysis [Journal-article]. European Radiology. https://doi.org/10.1007/s00330-024-10594-x

Kocak, B., Akinci D’Antonoli, T., Ates Kus, E., Keles, A., Kala, A., Kose, F., Kadioglu, M., Solak, S., Sunman, S., & Temiz, Z. H. (2024). Self-reported checklists and quality scoring tools in radiomics: a meta-research [Journal-article]. European Radiology. https://doi.org/10.1007/s00330-023-10487-5

Merel Huisman, & Tugba Akinci D’Antonoli. (2024). What a Radiologist Needs to Know About Radiomics, Standardization, and Reproducibility. Radiology. https://doi.org/10.1148/radiol.232459

Akinci D’Antonoli T, Stanzione A, Bluethgen C, Vernuccio F, Ugga L, Klontzas ME, Cuocolo R, Cannella R, & Koçak B. (2023). Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions. Diagnostic and Interventional Radiology (Ankara, Turkey). https://doi.org/10.4274/dir.2023.232417

Kocak B, Keles A, & Akinci D’Antonoli T. (2023). Self-reporting with checklists in artificial intelligence research on medical imaging: a systematic review based on citations of CLAIM. European Radiology. https://doi.org/10.1007/s00330-023-10243-9

Akinci D’Antonoli T, Cavallo AU, Vernuccio F, Stanzione A, Klontzas ME, Cannella R, Ugga L, Baran A, Fanni SC, Petrash E, Ambrosini I, Cappellini LA, van Ooijen P, Kotter E, Pinto Dos Santos D, Cuocolo R, & EuSoMII Radiomics Auditing Group. (2023). Reproducibility of radiomics quality score: an intra- and inter-rater reliability study. European Radiology. https://doi.org/10.1007/s00330-023-10217-x

Akinci D’Antonoli T, & Mercaldo ND. (2023, May 11). Obsolescence of nomograms in radiomics research. https://doi.org/10.1007/s00330-023-09728-4

Gaia Spadarella, Arnaldo Stanzione, Tugba Akinci D’Antonoli, Anna Andreychenko, Salvatore Claudio Fanni, Lorenzo Ugga, Elmar Kotter, & Renato Cuocolo. (2023). Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative. European Radiology, 33(3), 1884–1894. https://doi.org/10.1007/s00330-022-09187-3

D’Antonoli, Tugba Akinci, Todea, Ramona-Alexandra, Leu, Nora, Datta, Alexandre N., Stieltjes, Bram, Pruefer, Friederike, & Wasserthal, Jakob. (2023). Development and Evaluation of Deep Learning Models for Automated Estimation of Myelin Maturation Using Pediatric Brain MRI Scans. Radiology: Artificial Intelligence, 5. https://doi.org/10.1148/ryai.220292

Sexauer R, Stieltjes B, Bremerich J, D’Antonoli TA, & Schmidt N. (2022). Considerations on Baseline Generation for Imaging AI Studies Illustrated on the CT-Based Prediction of Empyema and Outcome Assessment. Journal of Imaging, 8(3). https://doi.org/10.3390/jimaging8030050

Tugba Akinci D’Antonoli. (2022). Ethical and Legal Risks of Artificial Intelligence in Radiology. In Springer (Ed.), Integrity of Scientific Research (pp. 113–122). Springer International Publishing. https://doi.org/10.1007/978-3-030-99680-2_12

Zettinig D, D’Antonoli TA, Wilder-Smith A, Bremerich J, Roth JA, & Sexauer R. (2021). Diagnostic Accuracy of Imaging Findings in Pleural Empyema: Systematic Review and Meta-Analysis. Journal of Imaging, 8(1). https://doi.org/10.3390/jimaging8010003

Weidensteiner, Claudia, Madoerin, Philipp, Deligianni, Xeni, Haas, Tanja, Bieri, Oliver, Akinci D’Antonoli, Tugba, Bracht-Schweizer, Katrin, Romkes, Jacqueline, De Pieri, Enrico, Santini, Francesco, Rutz, Erich, Brunner, Reinald, & Garcia, Meritxell. (2021). Quantification and Monitoring of the Effect of Botulinum Toxin A on Paretic Calf Muscles of Children With Cerebral Palsy With MRI: A Preliminary Study [Journal-article]. Frontiers in Neurology, 12. https://doi.org/10.3389/fneur.2021.630435

Weidensteiner C, Madoerin P, Deligianni X, Haas T, Bieri O, Akinci D’Antonoli T, Bracht-Schweizer K, Romkes J, De Pieri E, Santini F, Rutz E, Brunner R, & Garcia M. (2021). Quantification and Monitoring of the Effect of Botulinum Toxin A on Paretic Calf Muscles of Children With Cerebral Palsy With MRI: A Preliminary Study. Frontiers in Neurology, 12, 630435. https://doi.org/10.3389/fneur.2021.630435

Akinci D’Antonoli T, Santini F, Deligianni X, Garcia Alzamora M, Rutz E, Bieri O, Brunner R, & Weidensteiner C. (2021). Combination of Quantitative MRI Fat Fraction and Texture Analysis to Evaluate Spastic Muscles of Children With Cerebral Palsy. Frontiers in Neurology, 12, 633808. https://doi.org/10.3389/fneur.2021.633808

Anastasopoulos, Constantin, Yang, Shan, Pradella, Maurice, Akinci D’Antonoli, Tugba, Knecht, Sven, Cyriac, Joshy, Reisert, Marco, Kellner, Elias, Achermann, Rita, Haaf, Philip, Stieltjes, Bram, Sauter, Alexander W., Bremerich, Jens, Sommer, Gregor, & Abdulkadir, Ahmed. (2021). Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium. Journal of Cardiovascular Magnetic Resonance (JCMR)e Society for Cardiovascular Magnetic Resonance, 23(1), 133. https://doi.org/10.1186/s12968-021-00791-8

Akinci D’Antonoli T. (2020). Ethical considerations for artificial intelligence: An overview of the current radiology landscape. Diagnostic and Interventional Radiology, 26(5), 504–511. https://doi.org/10.5152/dir.2020.19279

Akinci D’Antonoli T, Farchione A, Lenkowicz J, Chiappetta M, Cicchetti G, Martino A, Ottavianelli A, Manfredi R, Margaritora S, Bonomo L, Valentini V, & Larici AR. (2020). CT Radiomics Signature of Tumor and Peritumoral Lung Parenchyma to Predict Nonsmall Cell Lung Cancer Postsurgical Recurrence Risk. Academic Radiology, 27(4), 497–507. https://doi.org/10.1016/j.acra.2019.05.019

Triadyaksa P, Kuijpers D, Akinci D’Antonoli T, Overbosch J, Rook M, van Swieten JM, Oudkerk M, & Sijens PE. (2020). Early detection of heart function abnormality by native T1: a comparison of two T1 quantification methods. European Radiology, 30(1), 652–662. https://doi.org/10.1007/s00330-019-06364-9

Weikert T, Akinci D’Antonoli T, Bremerich J, Stieltjes B, Sommer G, & Sauter AW. (2019). Evaluation of an AI-powered lung nodule algorithm for detection and 3D segmentation of primary lung tumors. Contrast Media and Molecular Imaging, 2019, 1545747. https://doi.org/10.1155/2019/1545747

Guler GB, Can MM, Guler E, Akinci T, Sogukpinar O, Hatipoglu S, Kilicaslan F, & Serebruany VL. (2016). Asymptomatic Pulmonary Embolism after Ablation. Cardiology, 134(4), 426–432. https://doi.org/10.1159/000444440

Karadag D, Ozdol NC, Beriat K, & Akinci T. (2011). CT evaluation of the bony nasal pyramid dimensions in Anatolian people. Dento Maxillo Facial Radiology, 40(3), 160–164. https://doi.org/10.1259/dmfr/35578628

Karadag D., Beriat G.K., Akinci T., & Yinanc M.A. (2011). Nasolabial cyst: MRI findings: Case report Nasolabial cyst: MRI findings. Turkiye Klinikleri Journal of Medical Sciences, 31(3), 731–734. https://doi.org/10.5336/medsci.2009-13142