Publications of Cornelia Schaefer-Prokop

2026

Papers in international journals

1. D. Peeters, B. Obreja, N. Antonissen, Z. Saghir, U. Pastorino, M. Silva, G. de Bock, H. Gietema, F. Gleeson, M. Heuvelmans, S. Lam, G. Litjens, F. Mohamed Hoesein, C. Schaefer-Prokop, E. Scholten, A. Snoeckx, E. van der Heijden, R. Vliegenthart, M. Prokop, C. Jacobs and O. behalf of the Consortium, "Benchmarking of AI and Radiologists for Indeterminate Lung Nodule Malignancy Risk Estimation on Screening CT: The LUNA25 Challenge", Radiology: Artificial Intelligence, 2026.
   Abstract DOI PMID
2. S. Bunk, E. Bennink, G. Sidorenkov, M. Heuvelmans, H. Groen, H. Gietema, M. Prokop, J. Aerts, C. Jacobs, G. de Bock, P. de Jong, R. Vliegenthart, F. Mohamed Hoesein, J. Aerts, R. Cornelissen, R. Stadhouders, J. van Rooij, L. Trap, M. Prokop, C. Schaefer-Prokop, C. Jacobs, G. de Bock, M. Heuvelmans, G. Sidorenkov, D. Zhong, H. Groen, R. Vliegenthart, P. de Jong, F. Mohamed Hoesein, S. Bunk and G. Downward, "CT-based body composition and its change through time in relation to outcomes in participants screened for lung cancer", eBioMedicine, 2026;127:106276.
   DOI PMID
3. S. Scharm, C. Schaefer-Prokop, A. Schreuder, J. Ehmig, A. Hunkemöller, J. Fuge, B. Seeliger, J. Schupp, F. Wacker and H. Shin, "Extent of alveolar collapse in expiratory CT as a prognostic marker in idiopathic pulmonary fibrosis", PLOS One, 2026;21:e0345308.
   Abstract DOI PMID
4. C. van den Berg, J. Dittrich, S. Scharm, C. Schaefer-Prokop, S. Dettmer, A. Hunkemoeller, J. Eckstein, J. Glandorf, F. Wacker, G. Pöhler and H. Shin, "CT-based lung ventilation metrics: reference ranges and pulmonary function test correlations in healthy individuals", European Radiology, 2026.
   Abstract DOI
5. A. Hunkemöller, T. Werncke, J. Dittrich, C. Schaefer-Prokop, F. Söbbeler, M. Avsar, J. Salman, A. Ruhparwar, R. Blasczyk, S. Besli, C. Figueiredo, A. Enzig-Strohm, F. Wacker and H. Shin, "Photon-counting CT for dynamic lung perfusion: validation of a low-dose protocol in a porcine lung transplantation model", European Radiology Experimental, 2026;10.
   Abstract DOI

Abstracts

1. R. Dinnessen, N. Antonissen, D. Peeters, H. Gietema, F. Mohamed Hoesein, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "Performance and generalisability of a screening-trained deep learning model for pulmonary nodule malignancy risk estimation on a multicentre dataset of incidental nodules", European Congress of Radiology, 2026.
   Abstract