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  11. Predicting Lymphovascular Invasion In N0 Stage Non-small Cell Lung Cancer: A Nomogram Based On Dual-energy Ct Imaging And Clinical Findings

Predicting lymphovascular invasion in N0 stage non-small cell lung cancer: A nomogram based on Dual-energy CT imaging and clinical findings

Liangna Deng1, Jingjing Yang1, Mingtao Zhang2

  • 1Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730000, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou 730000, China; Second Clinical School, Lanzhou University, Lanzhou 730000, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730000, China.

European Journal of Radiology
|August 8, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

This study developed a nomogram using dual-energy CT scans and clinical data to predict lymphovascular invasion in early-stage lung cancer. The tool accurately identifies patients with lymphovascular invasion (LVI) in non-small cell lung cancer (NSCLC).

Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Lymphovascular invasion (LVI) is a critical prognostic factor in non-small cell lung cancer (NSCLC).
  • Accurate prediction of LVI in early-stage (N0) NSCLC is essential for treatment planning and patient management.
  • Current methods for LVI detection may have limitations, necessitating improved predictive tools.

Purpose of the Study:

  • To develop and validate a predictive nomogram for lymphovascular invasion (LVI) in N0 stage non-small cell lung cancer (NSCLC).
  • To integrate dual-energy computed tomography (DECT) findings with clinical data for enhanced LVI prediction.
  • To provide a tool for improved risk stratification in early-stage NSCLC patients.

Main Methods:

  • Retrospective analysis of 135 N0 NSCLC patients who underwent DECT prior to surgery.
Keywords:
Lymphovascular invasionN0 stageNon-small cell lung cancerX-ray computed tomography

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  • Collection of clinical data (including lymphocyte count) and DECT-derived parameters (iodine concentration, effective atomic number, normalized iodine concentration, fractal dimension).
  • Construction and external validation of a nomogram using significant predictors of LVI.

    • Main Results:

    • Multivariable analysis identified lymphocyte count (LYMPH), arterial phase iodine concentration (ICa), venous phase normalized iodine concentration (NICv), and fractal dimension (FD) as independent predictors of LVI.
    • The constructed nomogram demonstrated robust predictive performance with AUCs of 0.819 in the development cohort and 0.844 in the validation cohort.
    • Excellent agreement was observed between predicted and actual LVI rates upon external validation, indicating strong calibration.

    Conclusions:

    • A nomogram combining clinical factors (LYMPH) and DECT imaging features (ICa, NICv, FD) effectively predicts LVI in N0 stage NSCLC.
    • This tool offers a non-invasive method to aid in the prediction of LVI, potentially improving treatment decisions.
    • The study highlights the value of DECT in conjunction with clinical data for risk stratification in NSCLC.