Related Experiment Video
Updated: Nov 17, 2025
09:17
Point-of-Care Lung Ultrasound in Adults: Image Acquisition
Published on: March 3, 2023
7.0K
A Model for Predicting Malignant Sub-pleural Solid Masses Using Grayscale Ultrasound and Ultrasound Elastography
Wanbin Li1, Mengjun Shen2, Yi Zhang2
1Department of Ultrasonography, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China; Department of Intervention Radiology, Shanghai Fengxian District Central Hospital, Shanghai, China.
Ultrasound in Medicine & Biology
|February 12, 2021
Summary
This study developed a prediction model using ultrasound imaging to distinguish malignant from benign sub-pleural masses. The model significantly improved diagnostic accuracy, offering a valuable tool for healthcare professionals.
Area of Science:
- Medical Imaging
- Diagnostic Ultrasound
- Oncology
Background:
- Sub-pleural solid masses require accurate differentiation between malignant and benign conditions.
- Current diagnostic methods may have limitations in distinguishing these masses.
Purpose of the Study:
- To establish and evaluate a prediction model combining grayscale sonography and ultrasound elastography for malignant sub-pleural solid masses.
- To assess the diagnostic value of this integrated prediction model.
Main Methods:
- A retrospective study included 153 patients (89 malignant, 64 benign).
- Analysis of factors including age, air bronchogram, borderline characteristics, shape, and elasticity score.
- Development of a prediction model using logistic regression and assessment via receiver operating characteristic (ROC) curve analysis.
Main Results:
- Significant statistical differences (p < 0.05) were observed between malignant and benign groups in age, air bronchogram, borderline, shape, and elasticity score.
- Individual factors like age, elasticity score, and borderline characteristics showed predictive value (AUROC 0.70-0.73).
- The combined prediction model achieved a high diagnostic accuracy with an area under the ROC curve (AUROC) of 0.88 (95% CI 0.81-0.92).
Conclusions:
- The prediction model integrating grayscale sonography and ultrasound elastography effectively differentiates malignant sub-pleural solid masses.
- This model demonstrates improved diagnostic accuracy and serves as a potentially valuable auxiliary tool, particularly in resource-limited settings.
- The findings support the utility of advanced ultrasound techniques in improving the diagnosis of pleural abnormalities.
