ORIGINAL RESEARCH article
Front. Oncol.
Sec. Hematologic Malignancies
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1567152
Development of a model to predict Ki-67 expression status in non-Hodgkin's lymphoma based on PET radiomics
Provisionally accepted
- 1Medical Imaging Department, Air Force Medical Center, Air Force Medical University, PLA, Beijing, China
- 2The Third People’s Hospital of Henan Province, Zhengzhou, China
- 3Department of Nuclear Medicine, Henan Medical Key Laboratory of Molecular Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- 4Zhengzhou University, Zhengzhou, Henan Province, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Introduction: This study aims to evaluate the effectiveness of conventional metabolic parameters and radiomic features from 18F-deoxyglucose(FDG) PET in predicting Ki-67 expression status in patients with non-Hodgkin’s lymphoma.Methods: We analyzed clinical, immunohistochemical(IHC), and 18F-FDG PET/CT data from 197 patients diagnosed with non-Hodgkin’s lymphoma at our institution between May 2018 and July 2023. Patients were randomly assigned to a training set (60%) and a validation set (40%) to develop PET image-based radiomics, clinical, and combined models. The models' predictive abilities were evaluated using receiver operating characteristic (ROC) curves and a nomogram was created to estimate high Ki-67 expression probabilities.Results: Among the patients, 70 exhibited low Ki-67 expression while 127 had high Ki-67 expression (113 males, 84 females, aged 5-85 years). The high Ki-67 group showed a higher proportion of fever(75.9% vs. 24.1%, P < 0.05) and tumor SUV max value／mediastinal SUV max value (T/MB) (P < 0.01). Five radiomic features formed the radiomics score (AUC: training 0.827; validation 0.883). The combined model showed the highest AUC(training 0.921; validation 0.916), indicating strong predictive capability.Conclusion: The radiomics model derived from 18F-FDG PET demonstrates superior predictive performance for Ki-67 expression status compared to T/MB. The combined model further improves prediction accuracy, highlighting its potential clinical applicability.
Keywords: PET/CT, Ki-67, non-Hodgkin lymphoma, invasive, Metabolic parameter, Radiomics
Received: 26 Jan 2025; Accepted: 29 May 2025.
Copyright: © 2025 Tian, Tong, Wu, Azhar, Fang, Xu and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ruihua Wang, Department of Nuclear Medicine, Henan Medical Key Laboratory of Molecular Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.