Hitting the Bull’s AI: Artificial Intelligence-derived Imaging Features and their Association with Outcomes in CT-guided Lung Biopsy, a Retrospective Study
With the advancing integration of AI tools into radiological workflows, this study highlights AI's potential to provide pre-interventional risk stratification and outcome predictions for CT-guided lung biopsies, which are the gold standard for sampling peripheral lung lesions.
Authors
- Mark Oliver Wielpütz (ORCID: https://orcid.org/0000-0001-6962-037X)
- Annika Syperek (ORCID: https://orcid.org/0000-0002-8132-6912)
- Patrick M. Winter (ORCID: https://orcid.org/0000-0001-5975-5465)
- Susanne Schnell (ORCID: https://orcid.org/0000-0001-6009-4756)
- M Mühler
- Till Ittermann (ORCID: https://orcid.org/0000-0002-0154-7353)
- C. Roller
- Marie-Luise Kromrey
- Felix Schön
- Jens-Peter Kühn
- Sophia FU Blum
Institutions
- Universitätsmedizin Greifswald (DE)
- Universität Greifswald (DE)
- University Hospital Carl Gustav Carus (DE)
Publication Details
- Journal
- European Journal of Radiology
- Published
- 2025-12-31
- DOI
- https://doi.org/10.1016/j.ejrad.2025.112642
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00