Related Experiment Video
Updated: Mar 15, 2026
Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Multicenter external validation of two malignancy risk prediction models in patients undergoing 18F-FDG-PET for
Simone Perandini1, G A Soardi2, A R Larici3
1UOC Radiologia, Ospedale Maggiore di Borgo Trento, Azienda Ospedaliera Universitaria Integrata di Verona, Piazzale Stefani 1, Verona, 37124, Italy. mail@simoneperandini.com.
Objectives:
To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models.
Methods:
Two hundred and fifty-nine solitary pulmonary nodules (SPNs) collected from four major hospitals which underwent 18-FDG-PET characterization were included in this multicentre retrospective study. The Herder model was tested on all available lesions (group A). A subgroup of 180 SPNs (group B) was used to provide unbiased comparison between the Herder and BIMC models. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to assess diagnostic accuracy. Decision analysis was performed by adopting the risk threshold stated in British Thoracic Society (BTS) guidelines.
Results:
Unbiased comparison performed In Group B showed a ROC AUC for the Herder model of 0.807 (95 % CI 0.742-0.862) and for the BIMC model of 0.822 (95 % CI 0.758-0.875).
Conclusions:
Both the Herder and the BIMC models were proven to accurately predict the risk of malignancy when tested on a large multicentre external case series. The BIMC model seems advantageous on the basis of a more favourable decision analysis.
Key Points:
• The Herder model showed a ROC AUC of 0.807 on 180 SPNs. • The BIMC model showed a ROC AUC of 0.822 on 180 SPNs. • Decision analysis is more favourable to the BIMC model.
