Correlation between PD-L1 Expression of Non-Small Cell Lung Cancer and Data from IVIM-DWI Acquired during Magnetic Resonance of the Thorax: Preliminary Results

Author:

Bortolotto ChandraORCID,Stella Giulia MariaORCID,Messana GaiaORCID,Lo Tito Antonio,Podrecca ChiaraORCID,Nicora Giovanna,Bellazzi Riccardo,Gerbasi AlessiaORCID,Agustoni Francesco,Grimm RobertORCID,Zacà Domenico,Filippi Andrea RiccardoORCID,Bottinelli Olivia Maria,Preda LorenzoORCID

Abstract

This study aims to investigate the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in magnetic resonance imaging (MRI) and programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC). Twenty-one patients diagnosed with stage III NSCLC from April 2021 to April 2022 were included. The tumors were distinguished into two groups: no PD-L1 expression (<1%), and positive PD-L1 expression (≥1%). Conventional MRI and IVIM-DWI sequences were acquired with a 1.5-T system. Both fixed-size ROIs and freehand segmentations of the tumors were evaluated, and the data were analyzed through a software using four different algorithms. The diffusion (D), pseudodiffusion (D*), and perfusion fraction (pf) were obtained. The correlation between IVIM parameters and PD-L1 expression was studied with Pearson correlation coefficient. The Wilcoxon–Mann–Whitney test was used to study IVIM parameter distributions in the two groups. Twelve patients (57%) had PD-L1 ≥1%, and 9 (43%) <1%. There was a statistically significant correlation between D* values and PD-L1 expression in images analyzed with algorithm 0, for fixed-size ROIs (189.2 ± 65.709 µm²/s × 104 in no PD-L1 expression vs. 122.0 ± 31.306 µm²/s × 104 in positive PD-L1 expression, p = 0.008). The values obtained with algorithms 1, 2, and 3 were not significantly different between the groups. The IVIM-DWI MRI parameter D* can reflect PD-L1 expression in NSCLC.

Funder

Fondazione IRCCS Policlinico San Matteo

Publisher

MDPI AG

Subject

Cancer Research,Oncology

Reference34 articles.

1. Global Burden of Disease Cancer Collaboration, Fitzmaurice, C., Abate, D., Abbasi, N., Abbastabar, H., Abd-Allah, F., Ab-del-Rahman, O., Abdelalim, A., Abdoli, A., and Abdollahpour, I. (2019). Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017: A Systematic Analysis for the Global Burden of Disease Study. JAMA Oncol., 5, 1749–1768.

2. 2021 WHO Classification of Lung Cancer: A Globally Applicable and Molecular Biomarker-Relevant Classification;J. Thorac. Oncol.,2022

3. de Castro, G., Kudaba, I., Wu, Y.-L., Lopes, G., Kowalski, D.M., Turna, H.Z., Caglevic, C., Zhang, L., Karaszewska, B., and Laktionov, K.K. (2022). Five-Year Outcomes With Pembrolizumab Versus Chemotherapy as First-Line Therapy in Patients With Non-Small-Cell Lung Cancer and Programmed Death Ligand-1 Tumor Proportion Score ≥ 1% in the KEYNOTE-042 Study. J. Clin. Oncol., JCO2102885.

4. 973MO KEYNOTE-189 5-year update: First-line pembrolizumab (pembro) + pemetrexed (pem) and platinum vs placebo (pbo) + pem and platinum for metastatic nonsquamous NSCLC;Ann. Oncol.,2022

5. 5-year update from KEYNOTE-407: Pembrolizumab plus chemotherapy in squamous non-small cell lung cancer (NSCLC);Ann. Oncol.,2022

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