FDG PET/CT for Primary Staging of Lung Cancer and Mesothelioma

Current and Future Perspective of PET/CT in Response Assessment of Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) is a rare but aggressive cancer characterized by its unique growth patterns, presenting substantial diagnostic challenges. With the shift toward immunotherapy for MPM treatment, assessing therapeutic responses has become increasingly complex. Recent studies indicate that FDG PET/CT may provide more effective response criteria compared to traditional CT-based methods. This review emphasizes the important role of PET/CT in offering deep insights into the disease state and monitoring treatment responses. It also addresses the challenges associated with current imaging criteria, particularly the nonspecificity of FDG uptake that may represent inflammatory responses following treatments or procedures rather than tumor activity. Furthermore, the review discusses the potential of emerging radiopharmaceuticals and advanced volumetric assessments, discussing their implications for improving diagnostic accuracy and treatment evaluation in MPM.

Prognostic Value of Tumor Dissemination (Dmax) Derived from Basal 18F-FDG Positron Emission Tomography/Computed Tomography in Patients with Advanced Non-Small-Cell Lung Cancer

Objectives: The aim of the present study was to test whether a parameter reflecting tumor dissemination (Dmax), derived from basal 18F-FDG PET/CT, may predict clinical outcome in patients with advanced non-small-cell lung cancer (NSCLC). Methods: A total of 78 patients (55 men, 23 women) with stage III and IV NSCLC who had undergone whole-body 18F-FDG PET/CT scan at diagnosis were included in this study. Imaging parameters of primary lung tumors along with total MTV (MTVTOT) and whole-body TLG (TLGWB) of all malignant lesions were determined. Moreover, the largest distance between two 18F-FDG avid lesions (Dmax) in each patient was measured. Univariate and multivariate analyses of clinical and imaging variables were performed followed by overall survival (OS) curves. Results: A total of 441 lesions were analyzed, including 78 primary tumors, 174 metastatic lymph nodes, and 189 distant metastases. In primary tumors, the average values of SUVmax, SUVmean, MTV, and TLG were 11.80 ± 5.73, 5.37 ± 2.09, 60.61 ± 102.57 mL, and 340.36 ± 558.40 g, respectively. The mean value of Dmax was 29.98 ± 20.98 cm, whereas the average values of MTVTOT and TLGWB were 155.90 ± 176.94 mL and 851.08 ± 1032.17 g, respectively. In the univariate analysis, OS was predicted by MTVTOT (p = 0.0145), TLGWB (p = 0.0518), Dmax (p = 0.0031), and stage (p = 0.0130), whereas in the multivariate analysis, only Dmax was retained in the model (χ2 = 7.3130, p = 0.0068). In particular, a high Dmax value indicates a worse prognosis. Moreover, the combination of Dmax with MTVTOT was able to improve the prognostic stratification of patients with advanced stages of NSCLC. Conclusions: Dmax, by reflecting tumor dissemination throughout the body, can predict overall survival in NSCLC patients.

Comparative benefits of Ki and SUV images in lesion detection during PET/CT imaging

BACKGROUND

Clinical application of the tracer net influx rate (Ki) imaging in PET/CT remains limited, due to a lack of evidence demonstrating the superiority of Ki images in lesion detection, and guidelines on when to utilize Ki images. This study aims to compare the benefits of Ki and standardized uptake value (SUV) images in lesion detection during PET/CT imaging. By analyzing the performance of both techniques in identifying tumor lesions, the study seeks to provide guidance for the clinical application of Ki images.

RESULTS

This retrospective study included 134 patients with 244 pathologically confirmed lesions (200 malignant and 44 benign). Patients with a histopathological diagnosis received a weight-based 18F-FDG injection and underwent 60-min total-body PET/CT dynamic imaging. SUV images were reconstructed using data collected from the last 10 min of the scans. Ki images were generated using the Patlak methods with data from minutes 12-60. The background SUVmax, SUVmean, SUVSD, Kimax, Kimean, and KiSD values were recorded. The signal-to-noise ratios of the SUV (SUVSNR) and Ki (KiSNR) images were calculated. The lesion detection rate and sensitivity of the SUV and Ki images were evaluated. The lesion-detection rates were 97.7% (214/219) and 99.5% (218/219) for the SUV and Ki images, respectively (p = .22). Five false-negative lesions on the SUV images were true-positive on the Ki images (3 hepatic malignancies and 2 metastatic lymph nodes). The sensitivity (94.0% vs. 96.0%, p = .22), specificity (41.9% vs. 41.9%, p > .99), accuracy (84.4% vs. 86.1%, p = .61), positive predictive value (87.9% vs. 88.1%, p = .94), negative predictive value (60.0% vs. 69.2%, p = .47), and the area under the curve [0.68 (95% confidence interval, 0.61-0.73) vs. 0.69 (95% confidence interval, 0.62-0.74)] were similar in the SUV and Ki images (all p ≥ .10).

CONCLUSION

Ki images exhibit benefits in lesion detection compared to SUV images, particularly in organs with high background such as liver. The enhanced contrast provided by Ki imaging is recommended to clinically improve detection rates in such cases.

68Ga-FAPI-04 PET/CT in Non-Small Cell Lung Cancer: Accurate Evaluation of Lymph Node Metastasis and Correlation with Fibroblast Activation Protein Expression

Fibroblast activation protein (FAP) is a promising diagnostic and therapeutic target in various solid tumors. This study aimed to assess the diagnostic efficiency of 68Ga-labeled FAP inhibitor (FAPI)-04 PET/CT for detecting lymph node metastasis in non-small cell lung cancer (NSCLC) and to investigate the correlation between tumor 68Ga-FAPI-04 uptake and FAP expression. Methods: We retrospectively enrolled 136 participants with suspected or biopsy-confirmed NSCLC who underwent 68Ga-FAPI-04 PET/CT for initial staging. The diagnostic performance of 68Ga-FAPI-04 for the detection of NSCLC was evaluated. The final histopathology or typical imaging features were used as the reference standard. The SUVmax and SUVmean, 68Ga-FAPI-avid tumor volume (FTV), and total lesion FAP expression (TLF) were measured and calculated. FAP immunostaining of tissue specimens was performed. The correlation between 68Ga-FAPI-04 uptake and FAP expression was assessed using the Spearman correlation coefficient. Results: Ninety-one participants (median age, 65 y [interquartile range, 58-70 y]; 69 men) with NSCLC were finally analyzed. In lesion-based analysis, the diagnostic sensitivity and positive predictive value of 68Ga-FAPI-04 PET/CT for detection of the primary tumor were 96.70% (88/91) and 100% (88/88), respectively. In station-based analysis, the diagnostic sensitivity, specificity, and accuracy for the detection of lymph node metastasis were 72.00% (18/25), 93.10% (108/116), and 89.36% (126/141), respectively. Tumor 68Ga-FAPI-04 uptake (SUVmax, SUVmean, FTV, and TLF) correlated positively with FAP expression (r = 0.470, 0.477, 0.582, and 0.608, respectively; all P ≤ 0.001). The volume parameters FTV and TLF correlated strongly with FAP expression in 31 surgical specimens (r = 0.700 and 0.770, respectively; both P < 0.001). Conclusion: 68Ga-FAPI-04 PET/CT had excellent diagnostic efficiency for detecting lymph node metastasis, and 68Ga-FAPI-04 uptake showed a close association with FAP expression in participants with NSCLC.

A cuproptosis score model and prognostic score model can evaluate clinical characteristics and immune microenvironment in NSCLC

BACKGROUND

Cuproptosis-related genes (CRGs) are associated with lung adenocarcinoma. However, the links between CRGs and non-small-cell lung cancer (NSCLC) are not clear. In this study, we aimed to develop two cuproptosis models and investigate their correlation with NSCLC in terms of clinical features and tumor microenvironment.

METHODS

CRG expression profiles and clinical data from NSCLC and normal tissues was obtained from GEO (GSE42127) and TCGA datasets. Molecular clusters were classified into three patterns based on CRGs and cuproptosis cluster-related specific differentially expressed genes (CRDEGs). Then, two clinical models were established. First, a prognostic score model based on CRDEGs was established using univariate/multivariate Cox analysis. Then, through principal component analysis, a cuproptosis score model was established based on prognosis-related genes acquired via univariate analysis of CRDEGs. NSCLC patients were divided into high/low risk groups.

RESULTS

Eighteen CRGs were acquired, all upregulated in tumor tissues, 15 of which significantly (P < 0.05). Among the three CRG clusters, cluster B had the best prognosis. In the CRDEG clusters, cluster C had the best survival. In the prognostic score model, the high-risk group had worse prognosis, higher tumor mutation load, and lower immune infiltration while in the cuproptosis score model, a high score represented better survival, lower tumor mutation load, and high-level immune infiltration.

CONCLUSIONS

The cuproptosis score model and prognostic score model may be associated with NSCLC prognosis and immune microenvironment. These novel findings on the progression and immune landscape of NSCLC may facilitate the provision of more personalized immunotherapy interventions for NSCLC patients.