Using delta radiomic features to construct a model for predicting growth and prognosis of persistent pulmonary subsolid nodules.
Principal Investigator
Name
Linyu Wu
Degrees
Dr.
Institution
The First Affiliated Hospital of Zhejiang Chinese Medical University
Position Title
Attending physician
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-987
Initial CDAS Request Approval
Nov 30, 2022
Title
Using delta radiomic features to construct a model for predicting growth and prognosis of persistent pulmonary subsolid nodules.
Summary
We hypothesize the application of delta radiomic features extracted from pulmonary subsolid nodules could help predict the growth. Therefore, we aim to develop a model to predict the growth of persistent pulmonary subsolid nodules using our center population and validate the model from NLST study population. Radiomic features from baseline and follow-up CT images will be extracted and delta radiomic features will be calculated. Moreover, the volume doubling time (VDT) of malignant subsolid nodules will be also calculated. The association between VDT, delta radiomic features and prognosis of malignant nodules will be analyzed.
Aims
(1)A model combining clinical features and delta radiomic features for predicting subsolid nodules growth will be developed and validated. The performance of radiomic model and combined model will be evaluated.
(2) The association between VDT, delta radiomic features and prognosis of malignant subsolid nodules will be analyzed.
Collaborators
Chen Gao, the First Affiliated Hospital of Zhejiang Chinese Medical University
Ting Wu, the First school of of Clinical Medicine of Zhejiang Chinese Medical University