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

• Published in: European radiology 2023-12, Vol.33 (12), p.9182-9193
• Main Authors: Bao, Xiao, Bian, Dongliang, Yang, Xing, Wang, Zheming, Shang, Mingdong, Jiang, Gening, Shi, Jingyun
• Format: Article
• Language: English
• Subjects: Biomarkers; Clinical trials; Diagnostic Radiology; Functional magnetic resonance imaging; Heterogeneity; Imaging; Immunotherapy; Internal Medicine; Interventional Radiology; Kurtosis; Lung cancer; Magnetic Resonance; Magnetic resonance imaging; Mathematical models; Medical imaging; Medicine; Medicine & Public Health; Multivariate analysis; Neuroradiology; Non-small cell lung carcinoma; Parameter identification; Patients; Prediction models; Predictions; Radiology; Regression analysis; Small cell lung carcinoma; Statistical analysis; Tumors; Ultrasound
• ISSN: 1432-1084; 0938-7994; 1432-1084
• DOI: 10.1007/s00330-023-09813-8

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 K app , and Δ K app were significantly lower than those in non-pCR group. Multivariate logistic regression analysis demonstrated that pre-NCIT D and post-NCIT K app 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 K app ) and Δ parameters (ΔADC, ΔD, and Δ K app ) were effective biomarkers for predicting pathologic response, and pre-NCIT D and post-NCIT K app 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 K app . • Pre-NCIT D and post-NCIT K app values were independent predictors of NCIT response.