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Purpose <p>The aim of this study was to assess the predictive value of magnetic resonance imaging (MRI)–derived ventilation defect percent (VDP) for International Association for the Study of Lung Cancer (IASLC) grading of lung adenocarcinoma (LUAD), and to compare its performance with computed tomography (CT)–derived low-attenuation area percentage (LAA%) and pulmonary function tests (PFTs).</p> Methods <p>In this prospective study, 71 patients at high risk for lung cancer who underwent chest CT, MRI, and PFTs within a one-week interval were included. VDP and LAA% were quantitatively derived, and histologic grading according to IASLC criteria was used as the reference standard. Patients with confirmed LUAD were classified into low-to-intermediate-grade (<i>n</i> = 50) and high-grade (<i>n</i> = 21) groups based on IASLC criteria. Diagnostic performance was assessed using receiver operating characteristic analysis, and independent predictors were identified using multivariable logistic regression.</p> Results <p>The high-grade group demonstrated significantly higher VDP (24.2% ± 6.2 vs. 17.5% ± 4.3; <i>p</i> &lt; 0.001) and LAA% (16.8% ± 8.9 vs. 8.4% ± 6.7; <i>p</i> = 0.003) compared with the low-/intermediate-grade group. VDP was moderately negatively correlated with FEV1% predicted (<i>r</i> = − 0.54, <i>p</i> &lt; 0.001). After adjustment for pathologic T stage, consolidation-to-tumor ratio (CTR), and other potential confounders, multivariable analysis identified VDP (OR = 1.09; 95% CI: 1.01–1.17; <i>p</i> = 0.03) and LAA% (OR = 1.06; 95% CI: 1.02–1.13; <i>p</i> = 0.04) as independent predictors of high-grade LUAD. VDP achieved an area under the curve (AUC) of 0.761, and LAA% achieved an AUC of 0.737; while the combined model demonstrated significantly improved discrimination (AUC = 0.851, <i>p</i> &lt; 0.05).</p> Conclusion <p>MRI-derived VDP shows promise as a noninvasive functional imaging marker for identifying high-grade LUAD within the IASLC grading framework. By characterizing regional ventilation abnormalities that are not fully captured by CT morphology or global pulmonary function tests, VDP may complement conventional preoperative risk assessment in high-risk patients.</p>

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Predictive value of MRI ventilation defect percent and CT-derived LAA% for IASLC grading of lung adenocarcinoma in high-risk populations

  • 期刊论文

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  • 发表日期：

    2026年8月3日

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  • Meng-Ting Duan,
  • Hui Liu,
  • Li-Jia Wang,
  • Xiao-Jia Cai,
  • Si-Xue Xie,
  • Gao-Feng Shi,
  • Hui Feng

摘要

Purpose

The aim of this study was to assess the predictive value of magnetic resonance imaging (MRI)–derived ventilation defect percent (VDP) for International Association for the Study of Lung Cancer (IASLC) grading of lung adenocarcinoma (LUAD), and to compare its performance with computed tomography (CT)–derived low-attenuation area percentage (LAA%) and pulmonary function tests (PFTs).

Methods

In this prospective study, 71 patients at high risk for lung cancer who underwent chest CT, MRI, and PFTs within a one-week interval were included. VDP and LAA% were quantitatively derived, and histologic grading according to IASLC criteria was used as the reference standard. Patients with confirmed LUAD were classified into low-to-intermediate-grade (n = 50) and high-grade (n = 21) groups based on IASLC criteria. Diagnostic performance was assessed using receiver operating characteristic analysis, and independent predictors were identified using multivariable logistic regression.

Results

The high-grade group demonstrated significantly higher VDP (24.2% ± 6.2 vs. 17.5% ± 4.3; p < 0.001) and LAA% (16.8% ± 8.9 vs. 8.4% ± 6.7; p = 0.003) compared with the low-/intermediate-grade group. VDP was moderately negatively correlated with FEV1% predicted (r = − 0.54, p < 0.001). After adjustment for pathologic T stage, consolidation-to-tumor ratio (CTR), and other potential confounders, multivariable analysis identified VDP (OR = 1.09; 95% CI: 1.01–1.17; p = 0.03) and LAA% (OR = 1.06; 95% CI: 1.02–1.13; p = 0.04) as independent predictors of high-grade LUAD. VDP achieved an area under the curve (AUC) of 0.761, and LAA% achieved an AUC of 0.737; while the combined model demonstrated significantly improved discrimination (AUC = 0.851, p < 0.05).

Conclusion

MRI-derived VDP shows promise as a noninvasive functional imaging marker for identifying high-grade LUAD within the IASLC grading framework. By characterizing regional ventilation abnormalities that are not fully captured by CT morphology or global pulmonary function tests, VDP may complement conventional preoperative risk assessment in high-risk patients.