Related Experiment Video
Updated: Feb 12, 2026

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer
Published on: May 20, 2016
Predictive factors for treatment response using dual-energy computed tomography in patients with advanced lung
Sae Rom Hong1, Jin Hur1, Yong Wha Moon2
1Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea, Korea.
Purpose:
This study aimed to investigate whether the quantitative parameters of dual-energy computed tomography (DECT) can predict the effects of chemotherapy in advanced adenocarcinoma based on the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines.
Materials And Methods:
A total of 90 patients (59 males, 31 females, age 61.4 ± 12.3 (23-85)) with unresectable lung adenocarcinoma (TNM stage IIIB or IV) who underwent DECT before chemotherapy were prospectively included in this study. By comparing baseline studies with the best response achieved during 1 st line chemotherapy, patients were divided into two groups according to RECIST (version 1.1) guidelines as follows; responders (CR or PR) and non-responders (SD or PD). Quantitative measurements were performed on baseline DECT, and a logistic regression model was used to evaluate predictive factors for a response to chemotherapy.
Results:
Among 90 patients, 38 were categorized as responders, while 52 patients were non-responders. The mean iodine concentration measurements were significantly higher in responders compared with non-responders (1.81 ± 0.51 vs 1.33 ± 0.76 mg/ml, p < 0.001). On multivariate analysis, EGFR mutation (odds ratio (OR): 3.116, 95% confidential interval (CI):1.182-8.213, p = .019) and iodine concentration (OR: 1.112, 95% CI:1.034-1.196, p = .006) were found to be significant for predicting a treatment response.
Conclusions:
Dual-energy CT using a quantitative analytic method based on iodine concentration measurements can be used to predict the effects of chemotherapy in patients with advanced adenocarcinoma.
More Related Videos
13:18Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
Published on: March 3, 2023
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
Related Concept Videos
Computed Tomography
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Imaging Studies III: Computed Tomography
Factors Affecting Protein-Drug Binding: Patient-Related Factors
Age stands as a key determinant in protein-drug binding. Neonates, characterized by low albumin content, experience heightened concentrations of unbound drugs such as phenytoin and...
Factors Affecting Drug Response: Overview
What is Energy?
Predicting Molecular Geometry