Prognostic value of pre-treatment 18F-FDG PET uptake for nasopharyngeal carcinoma

Neural Network-based Automated Classification of 18F-FDG PET/CT Lesions and Prognosis Prediction in Nasopharyngeal Carcinoma Without Distant Metastasis

PURPOSE

To evaluate the diagnostic performance of the PET Assisted Reporting System (PARS) in nasopharyngeal carcinoma (NPC) patients without distant metastasis, and to investigate the prognostic significance of the metabolic parameters.

PATIENTS AND METHODS

Eighty-three NPC patients who underwent pretreatment 18F-FDG PET/CT were retrospectively collected. First, the sensitivity, specificity, and accuracy of PARS for diagnosing malignant lesions were calculated, using histopathology as the gold standard. Next, metabolic parameters of the primary tumor were derived using both PARS and manual segmentation. The differences and consistency between the 2 methods were analyzed. Finally, the prognostic value of PET metabolic parameters was evaluated. Prognostic analysis of progression-free survival (PFS) and overall survival (OS) was conducted.

RESULTS

PARS demonstrated high patient-based accuracy (97.2%), sensitivity (88.9%), and specificity (97.4%), and 96.7%, 84.0%, and 96.9% based on lesions. Manual segmentation yielded higher metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than PARS. Metabolic parameters from both methods were highly correlated and consistent. ROC analysis showed metabolic parameters exhibited differences in prognostic prediction, but generally performed well in predicting 3-year PFS and OS overall. MTV and age were independent prognostic factors; Cox proportional-hazards models incorporating them showed significant predictive improvements when combined. Kaplan-Meier analysis confirmed better prognosis in the low-risk group based on combined indicators (χ² = 42.25, P < 0.001; χ² = 20.44, P < 0.001).

CONCLUSIONS

Preliminary validation of PARS in NPC patients without distant metastasis shows high diagnostic sensitivity and accuracy for lesion identification and classification, and metabolic parameters correlate well with manual. MTV reflects prognosis, and its combination with age enhances prognostic prediction and risk stratification.

Baseline SUVmax is correlated with tumor hypoxia and patient outcomes in nasopharyngeal carcinoma

To evaluate the prognostic significance of the maximum standardized uptake value (SUVmax) in nasopharyngeal carcinoma (NPC), establish a gene signature that correlates with SUVmax, and explore the underlying biological behaviors associated with these correlations for the prediction of clinical outcomes. A cohort of 726 patients with NPC was examined to identify correlations between SUVmax and various clinical variables. RNA sequencing was performed to identify genes related to SUVmax, and these genes were used to develop an SUV signature. Additionally, transcriptome enrichment analysis was conducted to investigate the potential biological behaviors underlying the observed correlations. Higher SUVmax was associated with an increased tumor burden and worse prognosis. The SUV signature, which consisted of 10 genes, was positively correlated with SUVmax, and it predicted worse survival outcomes. This signature was highly expressed in malignant epithelial cells and associated with hypoxia and resistance to radiotherapy. Additionally, the signature was negatively correlated with immune function. SUVmax is a valuable prognostic indicator in NPC, with higher values predicting worse outcomes. The SUV signature offers further prognostic insights, linking glucose metabolism to tumor aggressiveness, treatment resistance, and immune function, and it could represent a potential biomarker for NPC.

Prognostic value of pre-treatment FDG PET/CT SUVmax for metastatic lesions in de novo metastatic nasopharyngeal carcinoma following chemotherapy and locoregional radiotherapy

BACKGROUND

To explore the prognostic role of FDG PET/CT maximal standard uptake values of metastatic lesions (SUVmax-M) in patients with de novo metastatic nasopharyngeal carcinoma (mNPC) following palliative chemotherapy and locoregional radiotherapy (LRRT).

METHODS

We retrospectively collected the information of 86 eligible patients between Jan 2012 and Oct 2020. All the parameters involving SUVmax and serum lactate dehydrogenase (LDH) at diagnosis were evaluated and cutoff values were determined by the maximum log-rank statistic method. The multivariate analysis was performed using Cox proportional hazards regression to identify the independent prognostic factors associated with overall survival (OS). All estimated survival rates were conducted with Kaplan-Meier method.

RESULTS

Median survival and progression time in the cohort were 38.2 and 13.9 months, respectively. The univariable analysis showed that male, number of metastatic sites ≥ 4, presence of liver, serum LDH ≥ 229, SUVmax-M ≥ 10, SUVmax-M-sum ≥ 10, and SUVmax-M-mean ≥ 8.8 were significant prognostic factors. Five variables were identified after LASSO regression and entered into the multivariate analysis. Furthermore, liver involvement (P = 0.039), elevated LDH (≥ 229) (P = 0.05) and higher SUVmax-M (≥ 10) (P = 0.004) were significantly associated with worse OS.

CONCLUSION

The high SUVmax of metastatic lesions (≥ 10), liver involvement, and elevated serum LDH (≥ 229) at diagnosis could independently predict poor survival for de novo mNPC patients treated with palliative chemotherapy following LRRT.

Prognostic value of baseline [18F]-fluorodeoxyglucose positron emission tomography parameters MTV, TLG and asphericity in an international multicenter cohort of nasopharyngeal carcinoma patients

Purpose

[¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) parameters have shown prognostic value in nasopharyngeal carcinomas (NPC), mostly in monocenter studies. The aim of this study was to assess the prognostic impact of standard and novel PET parameters in a multicenter cohort of patients.

Methods

The established PET parameters metabolic tumor volume (MTV), total lesion glycolysis (TLG) and maximal standardized uptake value (SUV_max) as well as the novel parameter tumor asphericity (ASP) were evaluated in a retrospective multicenter cohort of 114 NPC patients with FDG-PET staging, treated with (chemo)radiation at 8 international institutions. Uni- and multivariable Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), event-free survival (EFS), distant metastases-free survival (FFDM), and locoregional control (LRC) was performed for clinical and PET parameters.

Results

When analyzing metric PET parameters, ASP showed a significant association with EFS (p = 0.035) and a trend for OS (p = 0.058). MTV was significantly associated with EFS (p = 0.026), OS (p = 0.008) and LRC (p = 0.012) and TLG with LRC (p = 0.019). TLG and MTV showed a very high correlation (Spearman’s rho = 0.95), therefore TLG was subesequently not further analysed. Optimal cutoff values for defining high and low risk groups were determined by maximization of the p-value in univariate Cox regression considering all possible cutoff values. Generation of stable cutoff values was feasible for MTV (p<0.001), ASP (p = 0.023) and combination of both (MTV+ASP = occurrence of one or both risk factors, p<0.001) for OS and for MTV regarding the endpoints OS (p<0.001) and LRC (p<0.001). In multivariable Cox (age >55 years + one binarized PET parameter), MTV >11.1ml (hazard ratio (HR): 3.57, p<0.001) and ASP > 14.4% (HR: 3.2, p = 0.031) remained prognostic for OS. MTV additionally remained prognostic for LRC (HR: 4.86 p<0.001) and EFS (HR: 2.51 p = 0.004). Bootstrapping analyses showed that a combination of high MTV and ASP improved prognostic value for OS compared to each single variable significantly (p = 0.005 and p = 0.04, respectively). When using the cohort from China (n = 57 patients) for establishment of prognostic parameters and all other patients for validation (n = 57 patients), MTV could be successfully validated as prognostic parameter regarding OS, EFS and LRC (all p-values <0.05 for both cohorts).

Conclusions

In this analysis, PET parameters were associated with outcome of NPC patients. MTV showed a robust association with OS, EFS and LRC. Our data suggest that combination of MTV and ASP may potentially further improve the risk stratification of NPC patients.

Radiomics Model to Predict Early Progression of Nonmetastatic Nasopharyngeal Carcinoma after Intensity Modulation Radiation Therapy: A Multicenter Study

Purpose

To examine the prognostic value of a machine learning model trained with pretreatment MRI radiomic features in the assessment of patients with nonmetastatic nasopharyngeal carcinoma (NPC) who are at risk for 3-year disease progression after intensity-modulated radiation therapy and to explain the radiomics features in the model.

Materials and Methods

A total of 277 patients with nonmetastatic NPC admitted between March 2008 and December 2014 at two imaging centers were retrospectively reviewed. Patients were allocated to a discovery or validation cohort based on where they underwent MRI (discovery cohort, n = 217; validation cohort, n = 60). A total of 525 radiomics features extracted from contrast material-enhanced T1- or T2-weighted MRI studies and five clinical features were subjected to radiomic machine learning modeling to predict 3-year disease progression. Feature selection was performed by analyzing robustness to resampling, reproducibility between observers, and redundancy. Features for the final model were selected with Kaplan-Meier analysis and the log-rank test. A support vector machine was used as the classifier for the model. To interpret the pattern learned from the model, Shapley additive explanations (SHAP) was applied.

Results

The final model yielded an area under the receiver operating characteristic curve of 0.80 in both the discovery (95% bootstrap confidence interval: 0.80, 0.81) and independent validation (95% bootstrap confidence interval: 0.73, 0.89) cohorts. Analysis with SHAP revealed that tumor shape sphericity, first-order mean absolute deviation, T stage, and overall stage were important factors in 3-year disease progression.

Conclusion

These results add to the growing evidence of the role of radiomics in the assessment of NPC. By using explanatory techniques, such as SHAP, the complex interaction of features learned by the model may be understood.© RSNA, 2019Supplemental material is available for this article.