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Multiparametric MRI for evaluation of pathological response to the neoadjuvant chemo-immunotherapy in resectable non-small-cell lung cancer

  • Magnetic Resonance
  • Published:
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Abstract

Objectives

This study aimed to explore the predictive value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion kurtosis imaging (DKI) quantitative parameters for the response to neoadjuvant chemo-immunotherapy (NCIT) in resectable non-small-cell lung cancer (NSCLC) patients, so as to provide a basis for clinical individualized precision treatment.

Methods

Treatment naive locally advanced NSCLC patients who enrolled in 3 prospective, open-label, and single-arm clinical trials and received NCIT were retrospectively analyzed in this study. Functional MRI imaging was performed at baseline and following 3 weeks of treatment as an exploratory endpoint to evaluate treatment efficacy. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCIT response. Prediction models were built with statistically significant quantitative parameters and their combinations.

Results

In total of 32 patients, 13 were classified as complete pathological response (pCR) and 19 were non-pCR. Post-NCIT ADC, ΔADC, and ΔD values in the pCR group were significantly higher than those in the non-pCR group, while the pre-NCIT D, post-NCIT Kapp, and ΔKapp were significantly lower than those in non-pCR group. Multivariate logistic regression analysis demonstrated that pre-NCIT D and post-NCIT Kapp values were independent predictors for NCIT response. The combined predictive model, which consisted of IVIM-DWI and DKI, showed the best prediction performance with AUC of 0.889.

Conclusions

The pre-NCIT D, post-NCIT parameters (ADC and Kapp) and Δ parameters (ΔADC, ΔD, and ΔKapp) were effective biomarkers for predicting pathologic response, and pre-NCIT D and post-NCIT Kapp values were independent predictors of NCIT response for NSCLC patients.

Clinical relevance statement

This exploratory study indicated that IVIM-DWI and DKI MRI imaging would predict pathologic response of neoadjuvant chemo-immunotherapy in locally advanced NSCLC patients at initial state and early treatment, which could help make clinical individualized treatment strategies.

Key Points

• Effective NCIT treatment resulted in increased ADC and D values for NSCLC patients.

• The residual tumors in non-pCR group tend to have higher microstructural complexity and heterogeneity, as measured by Kapp.

• Pre-NCIT D and post-NCIT Kapp values were independent predictors of NCIT response.

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Abbreviations

ADC:

Apparent diffusion coefficients

AUC:

Area under curve

DKI:

Diffusion kurtosis imaging

IVIM:

Intravoxel incoherent motion

K app :

Apparent diffusion kurtosis

MPR:

Major pathologic response

NCIT:

Neoadjuvant chemo-immunotherapy

NSCLC:

Non-small-cell lung cancer

pCR:

Complete pathological response

ROC:

Receiver operating characteristic curve

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Author notes

  1. Xiao Bao, Dongliang Bian, and Xing Yang contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China

    Xiao Bao, Xing Yang, Zheming Wang, Mingdong Shang & Jingyun Shi

  2. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China

    Dongliang Bian & Gening Jiang

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Correspondence to Gening Jiang or Jingyun Shi.

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The scientific guarantor of this publication is Jingyun Shi.

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The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Siyang Wang kindly provided statistical advice for this manuscript.

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The informed consents were obtained from all patients and the studies were approved by the local independent ethic committee (ID: 19218XW, 19216XW, 19217XW).

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Bao, X., Bian, D., Yang, X. et al. Multiparametric MRI for evaluation of pathological response to the neoadjuvant chemo-immunotherapy in resectable non-small-cell lung cancer. Eur Radiol 33, 9182–9193 (2023). https://doi.org/10.1007/s00330-023-09813-8

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