Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics.

Abstract

BACKGROUND:

Because shape or irregularity along the tumor perimeter can result from interactions between the tumor and the surrounding parenchyma, there could be a difference in tumor growth rate according to tumor margin or shape. However, no attempt has been made to evaluate the correlation between margin or shape features and tumor growth.

METHODS:

We evaluated 52 lung adenocarcinoma (ADC) patients who had at least two computed tomographic (CT) examinations before curative resection. Volume-based doubling times (DTs) were calculated based on CT scans, and patients were divided into two groups according to the growth pattern (GP) of their ADCs (gradually growing tumors [GP I] vs. growing tumors with a temporary decrease in DT [GP II]). CT radiomic features reflecting margin characteristics were extracted, and radiomic features reflective of tumor DT were selected.

RESULTS:

Among the 52 patients, 41 (78.8%) were assigned to GP I and 11 (21.2%) to GP II. Of the 94 radiomic features extracted, eccentricity, surface-to-volume ratio, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5) were ultimately selected for tumor DT prediction. Selected radiomic features in GP I were surface-to-volume ratio, contrast, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5), similar to those for total subjects, whereas the radiomic features in GP II were solidity, energy, and busyness.

CONCLUSIONS:

This study demonstrated the potential of margin-related radiomic features to predict tumor DT in lung ADCs.

KEY POINTS:

SIGNIFICANT FINDINGS OF THE STUDY: We found a relationship between margin-related radiomic features and tumor doubling time.

WHAT THIS STUDY ADDS:

Margin-related radiomic features can potentially be used as noninvasive biomarkers to predict tumor doubling time in lung adenocarcinoma and inform treatment strategies.

• Authors: Hyun Jung Yoon, Hyunjin Park, Ho Yun Lee, Insuk Sohn, Joonghyun Ahn, Seung-Hak Lee
• Journal: Thoracic cancer (Thorac Cancer) Vol. 11 Issue 9 Pg. 2600-2609 (09 2020) ISSN: 1759-7714 [Electronic] Singapore
• PMID: 32705793 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © 2020 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Topics

• Adenocarcinoma of Lung (pathology, radiotherapy)
• Female
• Humans
• Lung Neoplasms (pathology, radiotherapy)
• Male
• Middle Aged
• Radiometry (methods)