Correlation Between Dual-Time-Point FDG PET and Tumor Microenvironment Immune Types in Non-Small Cell Lung Cancer

The value of dual time-point fluorine-18 fluorodeoxyglucose PET/computed tomography imaging in predicting lymph node metastasis in non-small cell lung cancer patients

OBJECTIVE

The purpose of this study was to analyze the correlation between specified dual time-point fluorine-18 fluorodeoxyglucose (18F-FDG) PET/computed tomography (CT) imaging parameters and pathological characteristics in non-small cell lung cancer (NSCLC) patients.

METHODS

This study retrospectively analyzed 47 patients with NSCLC. All patients underwent dual time-point 18F-FDG PET/CT imaging. We obtained the metabolic parameters, standardized uptake value (SUV) maximum, SUVmean, delayed standardized uptake value (DSUV) maximum, DSUVmean, delay index standardized uptake value (DISUV) maximum, and DISUVmean, of the primary tumor. The tumor size was measured by CT. All lymph nodes had a definite pathological diagnosis. We next evaluated the status of the lymph node metastases (LNM) and the correlations between metabolic parameters and clinical characteristics. Receiver operating characteristic curves were drawn for the prediction of LNM.

RESULTS

We found that the DSUVmax, DISUVmax, DSUVmean, and tumor size were significantly related to LNM (P = 0.036, 0.009, and 0.049, respectively). Multivariate analysis revealed that tumor size and DISUVmax were independent risk factors for LNM in lung cancer patients. According to the receiver operating characteristic curve analysis, the optimal cutoff values for DISUVmax and tumor size were 0.33 and 2.8 cm, respectively. When these two parameters were combined, the area under the curve for predicting LNM in NSCLC was 0.768, and the sensitivity was 95.7% for predicting LNM in lung cancer patients. We further allocated the patients to three groups: the high-risk group (tumor size ≥ 2.8 cm, DISUVmax ≥ 0.33), the moderate-risk group (tumor size ≥ 2.8 cm, DISUVmax < 0.33, or tumor size < 2.8 cm, DISUVmax ≥ 0.33), and the low-risk group (tumor size < 2.8 cm, DISUVmax < 0.33). The rates of LNM were 70, 50, and 0%, respectively.

CONCLUSION

Tumor size and DISUVmax are risk factors for predicting LNM, and they are more useful in combination. Compared with standard PET/CT imaging, dual time-point PET/CT imaging has added value in predicting LNM in NSCLC patients.

Intraepithelial tumor-infiltrating lymphocytes shape loco-regional PET/CT spread of locally advanced cervical cancer

BACKGROUND

Data suggest an association between positron emission tomography/CT (PET/CT) metabolic metrics and tumor microenvironment in several malignancies, and a potential role of PET/CT to monitor response to immunotherapy.

OBJECTIVE

To evaluate the correlation between tumor loco-regional extension and tumor-infiltrating lymphocyte infiltration in locally advanced cervical cancer prior to concurrent chemo-radiotherapy.The secondary objective was to assess the association between tumor-infiltrating lymphocytes and PET/CT metabolic metrics.

METHODS

Patients with locally advanced cervical cancer and negative para-aortic extensions on PET/CT were included. Two senior nuclear medicine physicians specializing in gynecologic oncology reviewed all PET/CT exams, and extracted tumor maximum standardized uptake value, metabolic tumor volume, and total lesion glycolysis, as well as pelvic lymph node involvement. One senior gynecologic oncology pathologist assessed intraepithelial tumor-infiltrating lymphocytes and stromal tumor-infiltrating lymphocytes. Intraepithelial tumor-infiltrating lymphocytes were categorized following previous studies as <1% and >1%. The cut-off for stromal tumor-infiltrating lymphocytes was chosen empirically: intermediate <60% and high >60%.

RESULTS

86 patients were included. Intraepithelial tumor-infiltrating lymphocytes were not significantly associated with tumor metabolic metrics. Intraepithelial tumor-infiltrating lymphocytes were not significantly associated with maximum standard uptake value (p=0.16), or metabolic tumor volume (p=0.19). Tumors with <1% intraepithelial tumor-infiltrating lymphocytes score were associated with a higher MRI tumor size (≥ median) (63.3% vs 39.3%, p=0.04). Patients with pelvic lymph node uptake were significantly more frequent in patients with high stromal tumor-infiltrating lymphocytes score (≥60%) (61.5% vs 31.7%, p=0.009).

CONCLUSIONS

Poor or absent intraepithelial tumor-infiltrating lymphocytes were associated with more advanced disease at diagnosis and larger tumor size. Tumor-infiltrating lymphocytes were not associated with tumor metabolic activity. Intraepithelial and stroma tumor-infiltrating lymphocytes are not redundant and should be assessed separately. Further work is needed to evaluate the association between tumor metabolic profile and immune populations, including different T-cell subtypes for patient selection for immunotherapy strategies.

Role of multiple dual-phase 18F-FDG PET/CT metabolic parameters in differentiating adenocarcinomas from squamous cell carcinomas of the lung

Purpose

To evaluate the ability of multiple dual-phase 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters to distinguish the histological subtypes of non-small cell lung cancer (NSCLC).

Methods

Data from 127 patients with non-small cell lung cancer who underwent preoperative dual-phase 18F-FDG PET/CT scanning at the PET-CT center of our hospital from December 2020 to October 2021 were collected, and the metabolic parameters of their primary lesions were measured and analyzed retrospectively. Intraclass correlation coefficients (ICC) were calculated for consistency between readers. Metabolic parameters in the early (SUVpeak, SUVmean, SUVmin, SUVmax, MTV, and TLG) and delayed phases (dpSUVpeak, dpSUVmean, dpSUVmin, dpSUVmax, dpMTV, and dpTLG) were calculated. We drew receiver operating characteristic (ROC) curves to compare the differences in different metabolic parameters between the adenocarcinoma (AC) and squamous cell carcinoma (SCC) groups and evaluated the ability of different metabolic parameters to distinguish AC from SCC.

Results

Inter-reader agreement, as assessed by the intraclass correlation coefficient (ICC), was good (ICC = 0.71, 95% CI:0.60-0.79). The mean MTV, SUVmax, TLG, SUVpeak, SUVmean, dpSUVmax, dpTLG, dpSUVpeak, dpSUVmean, and dpSUVmin of the tumors were significantly higher in SCC lesions than in AC lesions (P = 0.049, < 0.001, 0.016, < 0.001, 0.001, < 0.001, 0.018, < 0.001, 0.001, and 0.001, respectively). The diagnostic efficacy of the metabolic parameters in 18F-FDG PET/CT for differentiating adenocarcinoma from squamous cell carcinoma ranged from high to low as follows: SUVpeak (AUC = 0.727), SUVmax (AUC = 0.708), dpSUVmax (AUC = 0.699), dpSUVpeak (AUC = 0.698), TLG (AUC = 0.695), and dpTLG (AUC = 0.692), SUVmean (AUC = 0.690), dpSUVmean (AUC = 0.687), dpSUVmin (AUC = 0.680), SUVmin (AUC = 0.676), and MTV (AUC = 0.657).

Conclusions

Squamous cell carcinoma of the lung had higher mean MTV, SUVmax, TLG, SUVpeak, SUVmean, SUVmin, dpSUVpeak, dpSUVmean, dpSUVmin, dpSUVmax, and dpTLG than AC, which can be helpful tools in differentiating between the two. The metabolic parameters of the delayed phase (2 h after injection) 18F-FDG PET/CT did not improve the diagnostic efficacy in distinguishing lung AC from SCC. Conventional dual-phase 18F-FDG PET/CT is not recommended.

Application of radiomics-based multiomics combinations in the tumor microenvironment and cancer prognosis

The advent of immunotherapy, a groundbreaking advancement in cancer treatment, has given rise to the prominence of the tumor microenvironment (TME) as a critical area of research. The clinical implications of an improved understanding of the TME are significant and far-reaching. Radiomics has been increasingly utilized in the comprehensive assessment of the TME and cancer prognosis. Similarly, the advancement of pathomics, which is based on pathological images, can offer additional insights into the panoramic view and microscopic information of tumors. The combination of pathomics and radiomics has revolutionized the concept of a "digital biopsy". As genomics and transcriptomics continue to evolve, integrating radiomics with genomic and transcriptomic datasets can offer further insights into tumor and microenvironment heterogeneity and establish correlations with biological significance. Therefore, the synergistic analysis of digital image features (radiomics, pathomics) and genetic phenotypes (genomics) can comprehensively decode and characterize the heterogeneity of the TME as well as predict cancer prognosis. This review presents a comprehensive summary of the research on important radiomics biomarkers for predicting the TME, emphasizing the interplay between radiomics, genomics, transcriptomics, and pathomics, as well as the application of multiomics in decoding the TME and predicting cancer prognosis. Finally, we discuss the challenges and opportunities in multiomics research. In conclusion, this review highlights the crucial role of radiomics and multiomics associations in the assessment of the TME and cancer prognosis. The combined analysis of radiomics, pathomics, genomics, and transcriptomics is a promising research direction with substantial research significance and value for comprehensive TME evaluation and cancer prognosis assessment.

Prognostic Significance of Volumetric Parameters Based on FDG PET/CT in Patients with Lung Adenocarcinoma Undergoing Curative Surgery

INTRODUCTION

FDG PET/CT is a robust imaging modality to diagnose and stratify prognoses for non-small cell lung carcinoma. However, the role of FDG PET/CT in operable lung adenocarcinoma patients has not been previously investigated in a large cohort with varying pathological stages. The prognostic value of volumetric parameters based on FDG PET/CT was investigated in patients with stage I-III lung adenocarcinoma receiving curative surgery.

METHODS

This retrospective study included 432 patients with lung adenocarcinoma undergoing preoperative FDG PET/CT between January 2016 and December 2017. Clinicopathologic variables, conventional image parameters, such as the maximum standardized uptake value (SUVmax) and mean SUV (SUVmean) of the primary tumor, and volumetric parameters, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), were included in Cox regression analysis. Subgroup analysis was conducted to compare hazard ratios (HRs) based on MTV in each pathological stage. A new staging system including volumetric parameters was suggested.

RESULTS

A total of 432 patients (median age: 62 years; interquartile range: 56-70 years; 225 males) were evaluated. Sex, age, presence of EGFR mutation, pathological stage, MTV, and TLG of the primary tumor were selected as statistically significant prognostic factors for overall survival irrespective of other variables (OS; p < 0.05 for all). Pathological stage, MTV, and TLG of the primary tumor were selected as statistically significant prognostic factors for disease-free survival irrespective of other variables (p < 0.05 for all). The suggested new staging system including MTV as an additional criterion showed better discrimination and prediction for OS than the conventional pathological staging system despite statistical insignificance (concordance index: 0.698 vs. 0.673).

CONCLUSIONS

The volumetric parameters of the primary tumor based on preoperative FDG PET/CT were independent prognostic factors in addition to pathological stage in patients with operable lung adenocarcinoma. The suggested new staging system considering MTV predicted the prognoses better than the conventional pathological staging system.

Tumor infiltrating lymphocytes and radiological picture of the tumor

Tumor microenvironment (TME) is a complex entity that includes besides the tumor cells also a whole range of immune cells. Among various populations of immune cells infiltrating the tumor, tumor infiltrating lymphocytes (TILs) are a population of lymphocytes characterized by high reactivity against the tumor component. As, TILs play a key role in mediating responses to several types of therapy and significantly improve patient outcomes in some cancer types including for instance breast cancer and lung cancer, their assessment has become a good predictive tool in the evaluation of potential treatment efficacy. Currently, the evaluation of the density of TILs infiltration is performed by histopathological. However, recent studies have shed light on potential utility of several imaging methods, including ultrasonography, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), and radiomics, in the assessment of TILs levels. The greatest attention concerning the utility of radiology methods is directed to breast and lung cancers, nevertheless imaging methods of TILs are constantly being developed also for other malignancies. Here, we focus on reviewing the radiological methods used to assess the level of TILs in different cancer types and on the extraction of the most favorable radiological features assessed by each method.

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

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.

Radiomic Signatures Associated with CD8+ Tumour-Infiltrating Lymphocytes: A Systematic Review and Quality Assessment Study

The tumour immune microenvironment influences the efficacy of immune checkpoint inhibitors. Within this microenvironment are CD8-expressing tumour-infiltrating lymphocytes (CD8+ TILs), which are an important mediator and marker of anti-tumour response. In practice, the assessment of CD8+ TILs via tissue sampling involves logistical challenges. Radiomics, the high-throughput extraction of features from medical images, may offer a novel and non-invasive alternative. We performed a systematic review of the available literature reporting radiomic signatures associated with CD8+ TILs. We also aimed to evaluate the methodological quality of the identified studies using the Radiomics Quality Score (RQS) tool, and the risk of bias and applicability with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Articles were searched from inception until 31 December 2021, in three electronic databases, and screened against eligibility criteria. Twenty-seven articles were included. A wide variety of cancers have been studied. The reported radiomic signatures were heterogeneous, with very limited reproducibility between studies of the same cancer group. The overall quality of studies was found to be less than desirable (mean RQS = 33.3%), indicating a need for technical maturation. Some potential avenues for further investigation are also discussed.

Radiogenomic analysis of primary breast cancer reveals [18F]-fluorodeoxglucose dynamic flux-constants are positively associated with immune pathways and outperform static uptake measures in associating with glucose metabolism

BACKGROUND

PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers.

METHODS

Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging.

RESULTS

A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis ('GLYC-GLUC') which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance.

CONCLUSIONS

In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K, but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.

A Novel Approach Using FDG-PET/CT-Based Radiomics to Assess Tumor Immune Phenotypes in Patients With Non-Small Cell Lung Cancer

PURPOSE

Tumor microenvironment immune types (TMITs) are closely related to the efficacy of immunotherapy. We aimed to assess the predictive ability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT)-based radiomics of TMITs in treatment-naive patients with non-small cell lung cancer (NSCLC).

METHODS

A retrospective analysis was performed in 103 patients with NSCLC who underwent 18F-FDG PET/CT scans. The patients were randomly assigned into a training set (n = 71) and a validation set (n = 32). Tumor specimens were analyzed by immunohistochemistry for the expression of programmed death-ligand 1 (PD-L1), programmed death-1 (PD-1), and CD8+ tumor-infiltrating lymphocytes (TILs) and categorized into four TMITs according to their expression of PD-L1 and CD8+ TILs. LIFEx package was used to extract radiomic features. The optimal features were selected using the least absolute shrinkage and selection operator (LASSO) algorithm, and a radiomics signature score (rad-score) was developed. We constructed a combined model based on the clinical variables and radiomics signature and compared the predictive performance of models using receiver operating characteristic (ROC) curves.

RESULTS

Four radiomic features (GLRLM_LRHGE, GLZLM_SZE, SUVmax, NGLDM_Contrast) were selected to build the rad-score. The rad-score showed a significant ability to discriminate between TMITs in both sets (p < 0.001, p < 0.019), with an area under the ROC curve (AUC) of 0.800 [95% CI (0.688-0.885)] in the training set and that of 0.794 [95% CI (0.615-0.916)] in the validation set, while the AUC values of clinical variables were 0.738 and 0.699, respectively. When clinical variables and radiomics signature were combined, the complex model showed better performance in predicting TMIT-I tumors, with the AUC values increased to 0.838 [95% CI (0.731-0.914)] in the training set and 0.811 [95% CI (0.634-0.927)] in the validation set.

CONCLUSION

The FDG-PET/CT-based radiomic features showed good performance in predicting TMIT-I tumors in NSCLC, providing a promising approach for the choice of immunotherapy in a clinical setting.