The “digital biopsy” in non-small cell lung cancer (NSCLC): a pilot study to predict the PD-L1 status from radiomics features of [18F]FDG PET/CT

Monaco, Lavinia; Bernardi, Elisabetta De; Bono, F; Cortinovis, Diego; Crivellaro, Cinzia; Elisei, Federica; L’Imperio, Vincenzo; Landoni, Claudio; Mathoux, Gregory; Musarra, Monica; Pagni, Fabio; Turolla, E; Messa, Cristina; Guerra, Luca

doi:10.1007/s00259-022-05783-z

Cited by 24 publications

(20 citation statements)

References 15 publications

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“…Other metabolic parameters, such as mean standardized uptake value (SUVmean) and the ratio of metabolic to morphological lesion volumes (MMVR), have been reported to be correlated with PD-1 or PD-L1 expression (26,27). 18 F-FDG PET/CT radiomics have also been used to explore predictive models based on images and clinical information for PD-L1 expression (28)(29)(30). In addition, the correlation between 18 F-FDG PET/CT imaging and TIME in breast cancer, gastric cancer, colorectal cancer, bladder cancer, nasopharyngeal cancer, and oral squamous cell carcinoma has also been observed (Table 1).…”

Section: Characterization Of Timementioning

confidence: 99%

Section: Application Of 18 F-fdg Pet/ct Imaging In...mentioning

confidence: 99%

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PET/CT molecular imaging in the era of immune-checkpoint inhibitors therapy

Gao

Chen

et al. 2022

Front. Immunol.

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Cancer immunotherapy, especially immune-checkpoint inhibitors (ICIs), has paved a new way for the treatment of many types of malignancies, particularly advanced-stage cancers. Accumulating evidence suggests that as a molecular imaging modality, positron emission tomography/computed tomography (PET/CT) can play a vital role in the management of ICIs therapy by using different molecular probes and metabolic parameters. In this review, we will provide a comprehensive overview of the clinical data to support the importance of 18F-fluorodeoxyglucose PET/CT (18F-FDG PET/CT) imaging in the treatment of ICIs, including the evaluation of the tumor microenvironment, discovery of immune-related adverse events, evaluation of therapeutic efficacy, and prediction of therapeutic prognosis. We also discuss perspectives on the development direction of 18F-FDG PET/CT imaging, with a particular emphasis on possible challenges in the future. In addition, we summarize the researches on novel PET molecular probes that are expected to potentially promote the precise application of ICIs.

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Section: Characterization Of Timementioning

confidence: 99%

Section: Application Of 18 F-fdg Pet/ct Imaging In...mentioning

confidence: 99%

PET/CT molecular imaging in the era of immune-checkpoint inhibitors therapy

Gao

Chen

et al. 2022

Front. Immunol.

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“…The AUC of PD-L1 expression greater than 50% was predicted to be 0.84. 93 While exploring this issue, Jiang et al discussed the predictive performance of separate and combined modeling of PET and CT features. Twenty-four (PET and CT features) features related to PD-L1 expression were extracted from PET/CT.…”

Section: Application Of Pet/ct Radiomics In Pd-l1mentioning

confidence: 99%

“…Three radiomics features were screened for modeling. The AUC of PD‐L1 expression greater than 50% was predicted to be 0.84 93 …”

Section: Advantages Of Radiomics In Noninvasive and Real‐time Diagnosismentioning

confidence: 99%

What does radiomics do in PD‐L1 blockade therapy of NSCLC patients?

2022

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With the in-depth understanding of programmed cell death 1 ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC), PD-L1 has become a vital immunotherapy target and a significant biomarker. The clinical utility of detecting PD-L1 by immunohistochemistry or next-generation sequencing has been written into guidelines. However, the application of these methods is limited in some circumstances where the biopsy size is small or not accessible, or a dynamic monitor is needed. Radiomics can noninvasively, in real-time, and quantitatively analyze medical images to reflect deeper information about diseases. Since radiomics was proposed in 2012, it has been widely used in disease diagnosis and differential diagnosis, tumor staging and grading, gene and protein phenotype prediction, treatment plan decision-making, efficacy evaluation, and prognosis prediction. To explore the feasibility of the clinical application of radiomics in predicting PD-L1 expression, immunotherapy response, and long-term prognosis, we comprehensively reviewed and summarized recently published works in NSCLC. In conclusion, radiomics is expected to be a companion to the whole immunotherapy process.

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“…PD-1/PD-L1 pathway is an important immune checkpoint in lung adenocarcinoma, and abnormal expression of PD-L1 molecules would affect the tumor microenvironment and then change the overall morphology of the tumor, which can be captured by sophisticated imaging analysis. Several studies have focused on the noninvasive prediction of PD-L1 expression and have developed promising CT or PET/CT radiomic models; however, the sample size of these literatures was small, and most of the subjects were advanced NSCLC patients (24)(25)(26). So far, noninvasive prediction of PD-L1 expression in early-stage lung adenocarcinoma remains for further research.…”

Section: Introductionmentioning

confidence: 99%

Correlation between PD-L1 expression and radiomic features in early-stage lung adenocarcinomas manifesting as ground-glass nodules

Shi

Yang²,

Zhu³

et al. 2022

Front. Oncol.

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BackgroundImmunotherapy might be a promising auxiliary or alternative systemic treatment for early-stage lung adenocarcinomas manifesting as ground-glass nodules (GGNs). This study intended to investigate the PD-L1 expression in these patients, and to explore the non-invasive prediction model of PD-L1 expression based on radiomics.MethodsWe retrospectively analyzed the PD-L1 expression of patients with postoperative pathological diagnosis of lung adenocarcinomas and with imaging manifestation of GGNs, and divided patients into positive group and negative group according to whether PD-L1 expression ≥1%. Then, CT-based radiomic features were extracted semi-automatically, and feature dimensions were reduced by univariate analysis and LASSO in the randomly selected training cohort (70%). Finally, we used logistic regression algorithm to establish the radiomic models and the clinical-radiomic combined models for PD-L1 expression prediction, and evaluated the prediction efficiency of the models with the receiver operating characteristic (ROC) curves.ResultsA total of 839 “GGN-like lung adenocarcinoma” patients were included, of which 226 (26.9%) showed positive PD-L1 expression. 779 radiomic features were extracted, and 9 of them were found to be highly corelated with PD-L1 expression. The area under the curve (AUC) values of the radiomic models were 0.653 and 0.583 in the training cohort and test cohort respectively. After adding clinically significant and statistically significant clinical features, the efficacy of the combined model was slightly improved, and the AUC values were 0.693 and 0.598 respectively.ConclusionsGGN-like lung adenocarcinoma had a fairly high positive PD-L1 expression rate. Radiomics was a hopeful noninvasive method for predicting PD-L1 expression, with better predictive efficacy in combination with clinical features.

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The “digital biopsy” in non-small cell lung cancer (NSCLC): a pilot study to predict the PD-L1 status from radiomics features of [18F]FDG PET/CT

Cited by 24 publications

References 15 publications

PET/CT molecular imaging in the era of immune-checkpoint inhibitors therapy

PET/CT molecular imaging in the era of immune-checkpoint inhibitors therapy

What does radiomics do in PD‐L1 blockade therapy of NSCLC patients?

Correlation between PD-L1 expression and radiomic features in early-stage lung adenocarcinomas manifesting as ground-glass nodules

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