OtherClinical Investigations (Human)
Open Access
Deep learning FDG uptake classification enables total metabolic tumor volume estimation in diffuse large B-cell lymphoma
Nicolò Capobianco, Michel A. Meignan, Anne-Segolene Cottereau, Laetitia Vercellino, Ludovic Sibille, Bruce Spottiswoode, Sven Zuehlsdorff, Olivier Casasnovas, Catherine Thieblemont and Irene Buvat
Journal of Nuclear Medicine June 2020, jnumed.120.242412; DOI: https://doi.org/10.2967/jnumed.120.242412
Nicolò Capobianco
1 Siemens Healthcare GmbH, Germany;
Michel A. Meignan
2 Lysa Imaging, Henri Mondor University Hospitals, AP-HP, University Paris East, France;
Anne-Segolene Cottereau
3 Department of Nuclear Medicine, Cochin Hospital, AP-HP, France;
Laetitia Vercellino
4 Department of Nuclear Medicine, Saint-Louis Hospital, AP-HP, France;
Ludovic Sibille
5 Siemens Medical Solutions USA, Inc., United States;
Bruce Spottiswoode
5 Siemens Medical Solutions USA, Inc., United States;
Sven Zuehlsdorff
5 Siemens Medical Solutions USA, Inc., United States;
Olivier Casasnovas
6 Department of Hematology, University Hospital of Dijon, France;
Catherine Thieblemont
7 Department of Hematology, Saint Louis Hospital, AP-HP, France;
Irene Buvat
8 Laboratoire d'Imagerie Translationnelle en Oncologie, Inserm, Institut Curie, Université Paris Saclay, France

Article Figures & Data
Additional Files
Supplemental Data
Files in this Data Supplement:
In this issue
Journal of Nuclear Medicine
Vol. 66, Issue 5
May 1, 2025
Deep learning FDG uptake classification enables total metabolic tumor volume estimation in diffuse large B-cell lymphoma
Nicolò Capobianco, Michel A. Meignan, Anne-Segolene Cottereau, Laetitia Vercellino, Ludovic Sibille, Bruce Spottiswoode, Sven Zuehlsdorff, Olivier Casasnovas, Catherine Thieblemont, Irene Buvat
Journal of Nuclear Medicine Jun 2020, jnumed.120.242412; DOI: 10.2967/jnumed.120.242412
Deep learning FDG uptake classification enables total metabolic tumor volume estimation in diffuse large B-cell lymphoma
Nicolò Capobianco, Michel A. Meignan, Anne-Segolene Cottereau, Laetitia Vercellino, Ludovic Sibille, Bruce Spottiswoode, Sven Zuehlsdorff, Olivier Casasnovas, Catherine Thieblemont, Irene Buvat
Journal of Nuclear Medicine Jun 2020, jnumed.120.242412; DOI: 10.2967/jnumed.120.242412
Jump to section
Related Articles
Cited By...
- Total metabolic tumor volume on 18F-FDG PET/CT is a game-changer for patients with metastatic lung cancer treated with immunotherapy
- Technologist-Based Implementation of Total Metabolic Tumor Volume into Clinical Practice
- 18F-FDG PET Maximum-Intensity Projections and Artificial Intelligence: A Win-Win Combination to Easily Measure Prognostic Biomarkers in DLBCL Patients
- Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development
- Quantification of Metastatic Prostate Cancer Whole-Body Tumor Burden with 18F-FDG PET Parameters and Associations with Overall Survival After First-Line Abiraterone or Enzalutamide: A Single-Center Retrospective Cohort Study