Prognostic value of 18F-FDG-PET/CT in patients with nasopharyngeal carcinoma: a systematic review and meta-analysis

Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using 18F-FDG PET-CT parameters

PURPOSE

The objective of this study is to assess the prognostic efficacy of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (ML) prognostic model for NPC patients based on these 18F-FDG PET/CT parameters and clinical variables.

METHOD

A cohort of 678 patients diagnosed with NPC between 2016 and 2020 was analyzed in this study. The model was constructed using four advanced ML algorithms, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Least Absolute Shrinkage and Selection Operator (LASSO), and multifactor COX step-up regression. Statistical significance of the models was assessed using Kaplan-Meier (K-M) curves, with a significance level established at P < 0.05. The prognostic efficacy of the models was evaluated through the analysis of receiver operating characteristic (ROC) curves, with the area under the ROC curve (AUC) serving as a criterion for model selection. The decision curve analysis (DCA) and concordance index (C-index) were employed to assess the precision of the optimal model.

RESULTS

Multivariate analysis revealed age, T stage, and metabolic tumor volume (MTV) for the primary nasopharyngeal tumor (MTVT) as significant independent prognostic factors for overall survival (OS) in NPC patients. Additionally, the LASSO model identified six key variables, including peak standardized uptake value (SUV-peak) for the primary nasopharyngeal tumor (SUV-peak(T)), MTVT, heterogeneity index for neck lymph nodes (HIN), age, pathological type, and T stage. Remarkably, the LASSO model demonstrated superior performance with a 5-year AUC of 0.849 compared to other models. Further assessment using the C-index and DCA confirmed the accuracy of the LASSO model. Subgroup analysis revealed notable risk factors, such as a high heterogeneity index (HI) for the primary nasopharyngeal tumor (HIT), MTV values for neck lymph nodes (MTVN), and HIN.

CONCLUSIONS

We developed a novel prognostic machine learning model that integrates 18F-FDG PET-CT parameters and clinical characteristics, significantly enhancing prognosis prediction in NPC.

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

PURPOSE

To evaluate the prognostic value of maximal standardized uptake values (SUVmax) from serial fluor-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in patients with nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

Fifty-two patients with NPC who underwent 18F-FDG PET/CT scan before radiotherapy with/without chemotherapy were reviewed retrospectively. Twenty-seven patients (52%) were applied 3-D conformal radiotherapy and 25 patients (48%) applied intensity-modulated radiotherapy (IMRT). Fourteen (27%) patients were given neoadjuvant chemotherapy and forty-four (84.6%) patients were given concomitant and adjuvant chemotherapy.

RESULTS

Median follow-up time was 34 months (range 5.6-66.4 months). Forty-four (84.6%) patients were alive at last follow-up and eight (15.4%) had died. The best cut-off value of the SUVmax for the primary tumor site (SUVmax-PT) was 13 and 9 for the lymph nodes (SUVmax-LN). Patients with SUVmax-PT ≥ 13.0 and SUVmax-LN ≥ 9 had a significantly higher risk for the development of the distant metastases (p = 0.044 and p = 0.038). DFS was affected in patients with SUVmax-PT ≥ 13 (log rank χ 2 = 2.54, p = 0.017) and was significantly lower in patients with SUVmax-LN ≥ 9 for the lymph nodes (log rank χ 2 = 5.81, p = 0.013). OS was not affected by SUV levels. A multivariate Cox proportional hazard model of DFS included age (≥ 40), SUVmax-LN (< 9), T stage (T1-2) and neoadjuvant chemotherapy are significantly better prognosis for the DFS.

CONCLUSION

18F-FDG PET/CT uptake before treatment, as determined by SUVmax, may be a valuable tool to evaluate prognosis in NPC patients.

Metabolic reprogramming in the pathogenesis and progression of nasopharyngeal carcinoma: molecular mechanisms and therapeutic implications

Nasopharyngeal carcinoma (NPC) is a unique head and neck cancer with a complex etiology involving genetic predispositions, environmental factors, and Epstein-Barr virus (EBV) infection. Despite progress in radiotherapy and chemotherapy, the prognosis for advanced NPC is still unfavorable, prompting the need for innovative therapeutic approaches. Metabolic reprogramming plays a crucial role in the development and progression of NPC, marked by substantial changes in glycolysis, lipid, and amino acid metabolism. These alterations aid tumor cell proliferation, survival under stress, and immune evasion, with features such as enhanced aerobic glycolysis (Warburg effect) and shifts in lipid and amino acid pathways. Oncogenic drivers like MYC, RAS, EGFR, and the loss of tumor suppressors such as TP53 and PTEN, along with key signaling pathways including mTOR, AMPK, and HIF-1α, orchestrate these metabolic changes. This review discusses the molecular mechanisms of metabolic reprogramming in NPC and outlines potential therapeutic targets within these pathways. Advances in metabolic imaging and biomarker discovery are also enhancing the precision of diagnostics and treatment monitoring, fostering personalized medicine in NPC treatment. This manuscript aims to provide a detailed overview of the current research and its implications for improving NPC management and patient outcomes through targeted metabolic therapies.

Predictive significance of pretreatment 18F-FDG PET volumetric parameters on survival outcomes in pediatric patients with locally advanced undifferentiated nasopharyngeal carcinoma

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a rare pediatric cancer. Most children are first diagnosed with advanced locoregional disease. Identification of patients at higher risk of treatment failure is crucial as they may benefit from more aggressive initial treatment approaches. 18Fluorine-labeled fluoro-2-deoxyglucose positron emission tomography (18F-FDG PET) has shown promise as a prognostic tool for predicting outcomes.

METHODS

Retrospective study of pediatric patients with locally advanced undifferentiated NPC who underwent 18F-FDG PET/CT prior to intial treatment. Predictive significance of metabolic PET parameters on survival outcomes were estimated.

RESULTS

Thirty-two children were included, age range was 7.1-18 years at the time of diagnosis. The median follow-up duration was 46.1 months. Three patients (9.4%) were classified as AJCC stage IIb, 13 patients (40.6%) as stage IIIa, eight patients (25%) as stage IIIb, and eight patients (25%) as stage IVa. Our findings revealed that high whole-body metabolic tumor volume at the threshold of hepatic reference SUVmean (WB-MTV-HR) (>135 mL) was associated with significantly lower event-free survival (EFS) compared to the low WB-MTV-HR group (≤135 mL) (3-year EFS: 50% ± 18% vs. 82% ± 8%; p = .015). Additionally, the 3-year overall survival (OS) rates differed significantly between the high whole-body metabolic tumor volume at the threshold of an SUV of 2.5 isocontour (WB-MTV-2.5) group (MTV >74 mL) and the low WB-MTV-2.5 group (MTV ≤74 mL) (63% ± 18% vs. 100%; p = .021).

CONCLUSION

Our study suggests that WB-MTV parameters could serve as significant prognostic factors for disease progression in pediatric patients with locally advanced undifferentiated NPC. However, further prospective studies with larger sample sizes are needed to validate these findings.

Comparison of Magnetic Resonance Imaging-Based Radiomics Features with Nomogram for Prediction of Prostate Cancer Invasion

Objective

To explore the value of the magnetic resonance imaging (MRI) radiomics model in predicting prostate cancer (PCa) invasion.

Methods

Clinical data of 86 pathologically confirmed PCa patients in our hospital were collected, including 44 cases in the invasive group and 42 cases in the non-invasive group. All patients underwent MRI examinations, and the same parameters were used. The lesion area was manually delineated and the radiomics features were extracted from T2WI. The radiomics signature based on LASSO regression was established. Besides, logistic regression was used to identify independent clinical predictors, and a combined model incorporating the radiomics signature and independent clinical risk factor was constructed. Finally, the receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA) was performed to compare the prediction efficiency and clinical benefit of each model.

Results

A total of 867 radiomics features were obtained, and six of them were incorporated into the radiomics model. Multivariate logistic regression analysis exhibited the Gleason score as an independent clinical risk factor for PCa invasion. ROC results showed that the performance of the radiomics model was comparable to that of the clinical-radiomics model in predicting PCa invasion, and it was better than that of the single Gleason score. DCA also confirmed the considerable clinical application value of the radiomics and the clinical-radiomics models.

Conclusion

As a simple, non-invasive, and efficient method, the radiomics model has important predictive value for PCa invasion.

The prognostic value of radiomic features from pre- and post-treatment 18F-FDG PET imaging in patients with nasopharyngeal carcinoma

Positron emission tomography/computed tomography (PET/CT) with ¹⁸F-fluorodeoxyglucose (FDG) is widely used for management of nasopharyngeal carcinoma (NPC). Combining the radiomic features of pre- and post-treatment FDG PET images may improve tumor characterization and prognostic predication. We investigated prognostic value of radiomic features from pre- and post-radiotherapy FDG PET images in patients with NPC. Quantitative radiomic features of primary tumors were extracted from the FDG PET images of 145 NPC patients and the delta values were also calculated. The study population was divided randomly into two groups, the training and test sets (7:3). A random survival forest (RSF) model was adopted to perform analyses of progression-free survival (PFS) and overall survival (OS). There were 37 (25.5%) cases of recurrence and 16 (11.0%) cases of death during a median follow-up period of 54.5 months. Both RSF models with clinical variables and radiomic PET features for PFS and OS showed comparable predictive performance to RSF models with clinical variables and conventional PET parameters. Tumoral radiomic features of pre- and post-treatment FDG PET and the corresponding delta values may predict PFS and OS in patients with NPC.

The Efficacy of Pretreatment 18F-FDG PET-CT-Based Deep Learning Network Structure to Predict Survival in Nasopharyngeal Carcinoma

Background

Previous studies have shown that the 5-year survival rates of patients with nasopharyngeal carcinoma (NPC) were still not ideal despite great improvement in NPC treatments. To achieve individualized treatment of NPC, we have been looking for novel models to predict the prognosis of patients with NPC. The objective of this study was to use a novel deep learning network structural model to predict the prognosis of patients with NPC and to compare it with the traditional PET-CT model combining metabolic parameters and clinical factors.

Methods

A total of 173 patients were admitted to 2 institutions between July 2014 and April 2020 for the retrospective study; each received a PET-CT scan before treatment. The least absolute shrinkage and selection operator (LASSO) was employed to select some features, including SUVpeak-P, T3, age, stage II, MTV-P, N1, stage III and pathological type, which were associated with overall survival (OS) of patients. We constructed 2 survival prediction models: an improved optimized adaptive multimodal task (a 3D Coordinate Attention Convolutional Autoencoder and an uncertainty-based jointly Optimizing Cox Model, CACA-UOCM for short) and a clinical model. The predictive power of these models was assessed using the Harrell Consistency Index (C index). Overall survival of patients with NPC was compared by Kaplan-Meier and Log-rank tests.

Results

The results showed that CACA-UOCM model could estimate OS (C index, 0.779 for training, 0.774 for validation, and 0.819 for testing) and divide patients into low and high mortality risk groups, which were significantly associated with OS (P < .001). However, the C-index of the model based only on clinical variables was only 0.42.

Conclusions

The deep learning network model based on ¹⁸F-FDG PET/CT can serve as a reliable and powerful predictive tool for NPC and provide therapeutic strategies for individual treatment.

Focal Nasopharyngeal Activity Detected on [18F]FDG PET/CT: Clinical Implications and Comparison of Metabolic Parameters for Prediction of Malignancy

Purpose

We aimed to investigate the incidence and clinical significance of incidental focal nasopharyngeal uptake on [18F]FDG PET/CT and to evaluate the diagnostic performance of various metabolic parameters to differentiate between benign and malignant nasopharyngeal lesions.

Methods

A total of 63 consecutive patients with incidental focal nasopharyngeal uptake on [18F]FDG PET/CT and subsequent nasopharyngeal biopsy were retrospectively enrolled. In addition, baseline pretherapeutic [18F]FDG PET/CT images of 59 patients with newly diagnosed pathologically proven nasopharyngeal carcinoma (NPC) were reviewed. Maximum standardized uptake value (SUVmax), mean SUV (SUVmean), nasopharynx-to-palatine tonsil ratio (NPR), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the nasopharyngeal lesions were determined. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the metabolic parameters.

Results

Incidental focal nasopharyngeal uptake in two patients (3.2%, 2/63) was pathologically confirmed to be NPC. All the metabolic parameters (SUVmax, SUVmean, NPR, MTV, and TLG) demonstrated significantly greater values in patients with NPC compared with patients with benign or physiological nasopharyngeal uptake (p < 0.001). Among the metabolic parameters, NPR demonstrated the greatest area under the curve of 0.992 (p < 0.05), with a sensitivity of 96.7% and a specificity of 93.4% when a cut-off of 1.1 was used. Similar results were seen in nasopharyngeal lesions without morphological abnormality.

Conclusion

NPC is an infrequent but important cause of incidental focal nasopharyngeal uptake on [18F]FDG PET/CT. Metabolic parameters were shown to be useful to differentiate between benign and malignant nasopharyngeal lesions, and NPR showed the best diagnostic performance.

Pretreatment [18F]FDG PET/CT and MRI in the prognosis of nasopharyngeal carcinoma

OBJECTIVE

The present study aimed to assess the prognostic interest of metabolic and anatomic parameters derived from 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography/computed tomography ([¹⁸F]FDG PET/CT) and head and neck magnetic resonance imaging (HN-MRI) for better management of nasopharyngeal carcinoma (NPC).

METHODS

In this study, pre-treatment [¹⁸F]FDG PET/CT and HN-MRI parameters of NPC patients diagnosed between January 2017 and December 2018, were prospectively investigated. Correlation between those parameters and 4-year patient's survival outcomes was evaluated using Kaplan-Meier and Cox-regression analyses.

RESULTS

Our results revealed a significant association between pre-treatment nodal-maximum standardized uptake value (N-SUV max) and N categories (p = 0.01), between pre-treatment node-to-tumor SUV ratio (NTR) and both tumor size (p = 0.01) and N categories (p = 0.009), as well as between metabolic tumor volume (MTV) and both tumor size and NPC overall stage (p < 0.000). In multivariate analyses, pre-treatment N-SUV max, NTR and MTV were significant independent predictors of overall survival, distant metastasis-free survival, and progression-free survival (PFS) (p < 0.05). N-SUV max and MTV were also found to be significant independent predictors of loco-regional recurrence-free survival (p < 0.05), whereas HN-MRI detection of skull-base bone invasion was an independent factor associated with worse PFS in NPC (p = 0.03).

CONCLUSIONS

The present study highlights N-SUV max, NTR and MTV derived from [¹⁸F]FDG PET/CT, and skull-base bone invasion defined by HN-MRI, as promising metabolic and anatomic prognosis biomarkers for NPC.

Nasopharyngeal Carcinoma Radiomic Evaluation with Serial PET/CT: Exploring Features Predictive of Survival in Patients with Long-Term Follow-Up

PURPOSE

We aim determine the value of PET and CT radiomic parameters on survival with serial follow-up PET/CT in patients with nasopharyngeal carcinoma (NPC) for which curative intent therapy is undertaken.

METHODS

Patients with NPC and available pre-treatment as well as follow up PET/CT were included from 2005 to 2006 and were followed to 2021. Baseline demographic, radiological and outcome data were collected. Univariable Cox proportional hazard models were used to evaluate features from baseline and follow-up time points, and landmark analyses were performed for each time point.

RESULTS

Sixty patients were enrolled, and two-hundred and seventy-eight (278) PET/CT were at baseline and during follow-up. Thirty-eight percent (38%) were female, and sixty-two patients were male. All patients underwent curative radiation or chemoradiation therapy. The median follow-up was 11.72 years (1.26-14.86). Five-year and ten-year overall survivals (OSs) were 80.0% and 66.2%, and progression-free survival (PFS) was 90.0% and 74.4%. Time-dependent modelling suggested that, among others, PET gray-level zone length matrix (GLZLM) gray-level non-uniformity (GLNU) (HR 2.74 95% CI 1.06, 7.05) was significantly associated with OS. Landmark analyses suggested that CT parameters were most predictive at 15 month, whereas PET parameters were most predictive at time points 3, 6, 9 and 15 month.

CONCLUSIONS

This study with long-term follow up data on NPC suggests that mainly PET-derived radiomic features are predictive for OS but not PFS in a time-dependent evaluation. Furthermore, CT radiomic measures may predict OS and PFS best at initial and long-term follow-up time points and PET measures may be more predictive in the interval. These modalities are commonly used in NPC surveillance, and prospective validation should be considered.

18F-FDOPA PET/CT SUV-Derived Indices and Volumetric Parameters Correlation in Patients with Primary Brain Tumors

Simple Summary

This paper aims to improve the knowledge regarding 18F-FDOPA PET/CT parameters that may influence both the interpretation of PET data and the management of primary brain tumors. The evaluation of volumetric parameters in 18F-FDOPA imaging is uncommon, and we aim to increase the scientific interest on the potential role of volumetric parameters in the clinical practice. The standardized uptake value (SUV)-derived indices as SUV max, SUV mean, SUV max ratio, and SUV mean ratio are widely used but the exact methodology to elaborate SUV ratio is not well established. Therefore, this study aims to assess the correlation between SUV-derived indices and volumetric uptake parameters.

Abstract

Novel parameters in PET imaging, such as volumetric parameters, are gaining interest in the scientific literature, but the role of dopaminergic tumor volume (DTV) and total lesion F-DOPA activity (TLDA) and the correlation between volumetric and SUV-derived parameters are not well defined yet. One hundred and thirty-three patients that underwent 18F-FDOPA imaging for primary brain tumors were included in this retrospective study. SUV-derived indices were calculated (the occipital region was chosen to generate ratios of tumor SUV) and compared with volumetric parameters. Regression models were applied in univariate analysis and lnSUVmax was positively associated with lnDTV (beta 0.42, p = 0.007), the lnSUVmax ratio was positively associated with lnDTV (beta 0.80, p = 0.011), lnSUVmax was positively associated with lnTLDA (beta 1.27, p < 0.0001), and the lnSUVmax ratio was positively associated with lnTLDA (beta 1.87, p < 0.0001). Our study demonstrates that volumetric uptake parameters in 18F-FDOPA PET/CT are easier to assess in primary brain tumors with higher SUV max and SUV max ratios, and supports the emerging role of volumetric parameters in the data interpretation.

Subregional Radiomics Analysis of PET/CT Imaging with Intratumor Partitioning: Application to Prognosis for Nasopharyngeal Carcinoma

PURPOSE

This work aims to identify intratumoral habitats with distinct heterogeneity based on 2-deoxy-2-[¹⁸F]fluro-D-glucose positron emission tomography (PET)/X-ray computed tomography (CT) imaging, and to develop a subregional radiomics approach to predict progression-free survival (PFS) in patients with nasopharyngeal carcinoma (NPC).

PROCEDURES

In total, 128 NPC patients (85 vs. 43 for primary vs. validation cohorts) who underwent pre-treatment PET/CT scan were enrolled retrospectively. Each tumor was partitioned into several phenotypically consistent subregions based on individual- and population-level clustering. For each subregion, 202 radiomics features were extracted to construct imaging biomarker for prognosis via Cox's proportional hazard model combined with forward stepwise feature selection. Relevance of imaging biomarkers and clinicopathological factors were assessed by multivariate Cox regression analysis and Spearman's correlation analysis. To investigate whether imaging biomarkers could provide complementary prognosis information beyond existing predictors, a scoring system was further developed for risk stratification and compared with AJCC staging system.

RESULTS

Three subregions (denoted as S1, S2, and S3) were discovered with distinct PET/CT imaging characteristics in the two cohorts. The prognostic performance of imaging biomarker S3 outperformed the whole tumor (C-index, 0.69 vs. 0.58; log-rank test, p < 0.001 vs. p = 0.552). Imaging biomarker S3 and AJCC stage were identified as independent predictors (p = 0.011 and 0.042, respectively) after adjusting for clinicopathological factors. The scoring system outperformed the traditional AJCC staging system (log-rank test, p < 0.0001 vs. p = 0.0002 in primary cohort and p = 0.0021 vs. p = 0.0277 in validation cohort, respectively).

CONCLUSIONS

Subregional radiomics analysis of PET/CT imaging has the potential to predict PFS in patients with NPC, which also provides complementary prognostic information for traditional predictors.

A subregion-based positron emission tomography/computed tomography (PET/CT) radiomics model for the classification of non-small cell lung cancer histopathological subtypes

Background

This study classifies lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using subregion-based radiomics features extracted from positron emission tomography/computed tomography (PET/CT) images.

Methods

In this study, the standard ¹⁸F-fluorodeoxyglucose (FDG) PET/CT images of 150 patients with lung ADC and 100 patients with SCC were retrospectively collected from the PET Center of the First Affiliated Hospital, College of Medicine, Zhejiang University. First, the 3D feature vector of each tumor voxel (whose basis is PET value, CT value, and CT local dominant orientation) was extracted. Using K-means individual clustering and population clustering, each tumor was divided into 4 subregions that reflect intratumoral regional heterogeneity. Next, based on each subregion, 385 radiomics features were extracted. Clinical features including age, gender, and smoking history were included. Thus, there were a total of 1,543 features extracted from PET/CT images and clinical reports. Statistical tests were then used to eliminate irrelevant and redundant features, and the recursive feature elimination (RFE) algorithm was used to select the best feature subset to classify SCC and ADC. Finally, 7 types of classifiers were tested to achieve the optimized model for the classification: support vector machine (SVM) with linear kernel, SVM with radial basis function kernel (SVM-RBF), random forest, logistic regression, Gaussian process classifier, linear discriminant analysis, and the AdaBoost classifier. Furthermore, 5-fold cross-validation was applied to obtain the sensitivity, specificity, accuracy, and area under the curve (AUC) for performance evaluation.

Results

Our model exhibited the best performance with the subregion radiomics features and SVM-RBF classifier, with a 5-fold cross-validation sensitivity, specificity, accuracy, and AUC of 0.8538, 0.8758, 0.8623, and 0.9155, respectively. The interquartile range feature from subregion 2 of CT and the gender feature from the clinical reports are the 2 optimized features that achieved the highest comprehensive score.

Conclusions

Our proposed model showed that SCC and ADC could be classified successfully using PET/CT images, which could be a promising tool to assist radiologists or medical physicists during diagnosis. The subregion-based method illustrated that non-small cell lung cancer (NSCLC) depicts intratumoral regional heterogeneity on both CT and PET images. By defining these heterogeneities through a subregion-based method, the diagnostic performance was improved. The 3D feature vector (whose basis is PET value, CT value, and CT local dominant orientation) showed superiority in reflecting NSCLC intratumoral regional heterogeneity.

Optimal management of oligometastatic nasopharyngeal carcinoma

PURPOSE

Oligometastatic nasopharyngeal carcinoma (NPC) is a distinctive subset of metastatic NPC. Imaging examinations and biomarkers can screen out NPC patients with limited number of sites showing metastasis. Past studies have demonstrated the survival advantages of oligometastatic NPC over multiple metastatic NPC. The treatment strategies of de-novo oligometastatic NPC differ owing to the heterogeneity of this disease. This study aims to systematically review the characteristics and treatments of oligometastatic NPC.

METHODS

PubMed, EMBASE, the Web of Science, and the Cochrane Library were used to search for publications with an emphasis on oligometastatic NPC.

RESULTS

We have presented the current advances on the management of oligometastatic NPC, including the definition, diagnosis, biomarkers, classification, prognosis, subtype, especially systematic therapy, locoregional radiotherapy to the primary tumor, and treatments of the metastatic lesions.

CONCLUSIONS

More well-designed prospective clinical trials that are exclusive for oligometastatic NPC are warranted to determine the best treatment paradigm.

Cell-free DNA concentration and fragment size fraction correlate with FDG PET/CT-derived parameters in NSCLC patients

PURPOSE

The aim of our study was to investigate the correlation between cfDNA concentration and fragment size fraction with FDG PET/CT- and CT-derived parameters in untreated NSCLC patient.

METHODS

Fifty-three patients diagnosed of locally advanced or metastatic NSCLC who had undergone FDG PET/CT, CT and cfDNA analysis prior to any treatment were included in this retrospective study. CfDNA concentration was measured by fluorometry and fragment size fractions were determined by microchip electrophoresis. [¹⁸F]F-FDG PET/CT was performed and standardised uptake values (SUV), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were calculated for primary, extrapulmonary and total disease. CT scans were evaluated according to RECIST 1.1 criteria.

RESULTS

CfDNA concentration showed a positive correlation with extrapulmonary MTV (r² = 0.36, P = 0.009), and extrapulmonary TLG (r² = 0.35, P = 0.009) and their whole-body (wb) ratios. Higher concentrations of total cfDNA were found in patients with liver lesions. Short fragments of cfDNA (100-250 bp) showed a positive correlation with extrapulmonary MTV (r² = 0.49, P = 0.0005) and extrapulmonary TLG (r² = 0.39, P = 0.006) and their respective wb ratios, and a negative correlation with SUVmean (r² = -0.31, P = 0.03) and SUVmean/SUVmax ratio (r² = -0.34, P = 0.02). A higher fraction of short cfDNA fragments was found in patients with liver and pleural lesions.

CONCLUSIONS

This study supports the hypothesis that cfDNA concentration and short cfDNA fragment size fraction reflect the tumour burden as well as metabolic activity in advanced NSCLC patients. This suggests their suitability as complementary tests for a more accurate diagnosis of tumour metabolic behaviour and to allow personalised therapies.

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.

Metastatic disease in head & neck oncology

The head and neck district represents one of the most frequent sites of cancer, and the percentage of metastases is very high in both loco-regional and distant areas. Prognosis refers to several factors: a) stage of disease; b) loco-regional relapses; c) distant metastasis. At diagnosis, distant metastases of head and neck cancers are present in about 10% of cases with an additional 20-30% developing metastases during the course of their disease. Diagnosis of distant metastases is associated with unfavorable prognosis, with a median survival of about 10 months. The aim of the present review is to provide an update on distant metastasis in head and neck oncology. Recent achievements in molecular profiling, interaction between neoplastic tissue and the tumor microenvironment, oligometastatic disease concepts, and the role of immunotherapy have all deeply changed the therapeutic approach and disease control. Firstly, we approach topics such as natural history, epidemiology of distant metastases and relevant pathological and radiological aspects. Focus is then placed on the most relevant clinical aspects; particular attention is reserved to tumours with distant metastasis and positive for EBV and HPV, and the oligometastatic concept. A substantial part of the review is dedicated to different therapeutic approaches. We highlight the role of immunotherapy and the potential effects of innovative technologies. Lastly, we present ethical and clinical perspectives related to frailty in oncological patients and emerging difficulties in sustainable socio-economical governance.

Novel Quantitative PET Imaging Techniques in Tuberculosis

The role of fluorodeoxyglucose (FDG)-PET/computed tomography (CT) in tuberculosis (TB) continues to expand in disease detection, assessment of the extent of the disease, and treatment response monitoring. This article reviews available data regarding the use of FDG-PET/CT in patients with TB. A new method of quantification for patients with TB is introduced. This method produces robust parameters that represent the total disease burden.

The Prognostic Role of Programmed Death-Ligand 1 in Nasopharyngeal Carcinoma

OBJECTIVES

Programmed death-ligand 1 (PD-L1) is an immune checkpoint protein that may be a useful prognostic biomarker in nasopharyngeal cancer (NPC). The purpose of this systematic review and meta-analysis was to investigate the relationship between PD-L1 expression and survival in NPC.

METHODS

PubMed, Cochrane, Embase, Scopus, and Web of Science were searched from inception to present. A predefined inclusion and exclusion criteria were used to select articles. Hazard ratios (HRs) and 95% confidence intervals (CIs) were pooled for overall survival (OS), disease-free survival (DFS), and disease metastasis-free survival (DMFS).

RESULTS

Eleven studies published from 2014 to 2018 were included, with 1,356 total participants. PD-L1 expression was not associated with OS (HR = 1.10, 95% CI: 0.79-1.55), DFS (HR = 1.66, 95% CI: 0.68-4.03), or DMFS (HR = 1.18, 95% CI: 0.44-3.20).

CONCLUSIONS

The prognostic role of PD-L1 in NPC remains unsubstantiated. Future research is needed. Laryngoscope, 130:2598-2606, 2020.

Comparison of 18FBPA uptake with 18FDG uptake in cancer patients

For the patients who underwent ¹⁸fluorinated para-boronophenylalanine (¹⁸FBPA) positron emission tomography (PET) and ¹⁸fluorodeoxyglucose (¹⁸FDG) PET within a period of 2 weeks, maximum standardized uptake value (SUVmax), tumor-to-normal tissue ratio (TNR), and tumor-to-blood ratio (TBR) for ¹⁸FBPA were compared with SUVmax for ¹⁸FDG. A total of 30 patients were selected for comparison. SUVmax for ¹⁸FBPA was correlated the best with SUVmax for ¹⁸FDG. Subsequently, the SUVmax correlation between ¹⁸FBPA and ¹⁸FDG were verified among 82 patients. The correlation factor was 0.4825.

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.

Tumor volume/metabolic information can improve the prognostication of anatomy based staging system for nasopharyngeal cancer? Evaluation of the 8th edition of the AJCC/UICC staging system for nasopharyngeal cancer

Purpose

We evaluated prognostic value of the 8th edition of the American Joint Committee on Cancer/International Union for Cancer Control (AJCC/UICC) staging system for nasopharyngeal cancer and investigated whether tumor volume/metabolic information refined prognostication of anatomy based staging system.

Materials and Methods

One hundred thirty-three patients with nasopharyngeal cancer who were staged with magnetic resonance imaging (MRI) and treated with intensity-modulated radiotherapy (IMRT) between 2004 and 2013 were reviewed. Multivariate analyses were performed to evaluate prognostic value of the 8th edition of the AJCC/UICC staging system and other factors including gross tumor volume and maximum standardized uptake value of primary tumor (GTV-T and SUV-T).

Results

Median follow-up period was 63 months. In multivariate analysis for overall survival (OS), stage group (stage I-II vs. III-IVA) was the only significant prognostic factor. However, 5-year OS rates were not significantly different between stage I and II (100% vs. 96.2%), and between stage III and IVA (80.1% vs. 71.7%). Although SUV-T and GTV-T were not significant prognostic factors in multivariate analysis, those improved prognostication of stage group. The 5-year OS rates were significantly different between stage I-II, III-IV (SUV-T ≤ 16), and III-IV (SUV-T > 16) (97.2% vs. 78% vs. 53.8%), and between stage I, II-IV (GTV-T ≤ 33 mL), and II-IV (GTV-T > 33 mL) (100% vs. 87.3% vs. 66.7%).

Conclusion

Current anatomy based staging system has limitations on prognostication for nasopharyngeal cancer despite the most accurate assessment of tumor extent by MRI. Tumor volume/metabolic information seem to improve prognostication of current anatomy based staging system, and further studies are needed to confirm its clinical significance.

Prognostic value of preoperative fluorodeoxyglucose positron emission tomography/computed tomography in patients with potentially resectable pancreatic cancer

PURPOSE

To evaluate the prognostic value of preoperative 18-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in patients with potentially resectable pancreatic cancer.

METHODS

The study included 103 consecutive patients with potentially resectable pancreatic cancer who underwent preoperative FDG-PET/CT. Age, sex, blood glucose level, tumor marker levels (carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9)), PET-related parameters (maximum standardized uptake value (SUVmax)), and contrast-enhanced CT-related factors (tumor size, location, enhancement pattern, and CT-based T and N factors by tumor nodes metastasis (TNM) classification) were assessed for their ability to independently predict postoperative tumor recurrence using Cox proportional hazards model.

RESULTS

Median follow-up was 23.1 months. Univariate analyses revealed that SUVmax (P = 0.0004), tumor size (P = 0.0002), T factor (P = 0.0102), N factor (P = 0.0049), and CA19-9 levels (P = 0.0059) were significantly associated with disease-free survival (DFS). In multivariate analysis, SUVmax (P = 0.0163) and CA19-9 levels (P = 0.0364) independently predicted DFS. Kaplan-Meier analysis revealed that patients with low (< 2.5) SUVmax had a significantly better prognosis than those with higher SUVmax (P = 0.0006). The DFS in patients with SUVmax < 2.5 (n = 23) and SUVmax ≥ 2.5 (n = 80) was 61.9% and 9.7%, respectively, 3 years postoperatively.

CONCLUSIONS

SUVmax can predict DFS in patients with resectable pancreatic cancer. A SUVmax < 2.5 heralds a better prognosis.

Parameters of metabolic quantification in clinical practice. Is it now time to include them in reports?

Qualitative techniques have traditionally been the standard for the diagnostic assessment with ¹⁸F-FDG PET studies. Since the introduction of the technique, quantitative parameters have been sought, more accurate and with better diagnostic precision, that may offer relevant information of the behavior, aggressiveness or prognosis of tumors. Nowadays, more and more studies with high quality evidence show the utility of other metabolic parameters different from the SUV maximum, which despite being widely used in clinical practice is controversial and many physicians still do not know its real meaning. The objective of this paper has been to review the key concepts of these metabolic parameters that could be relevant in normal practice in the future. It has been seen that there is more evidence in the complete evaluation of the metabolism of a lesion, through volumetric parameters that more adequately reflect the patient's tumor burden. Basically, these parameters calculate the volume of tumor that fulfills certain characteristics. A software available in the majority of the workstations has been used for this purpose and it has allowed to calculate these volumes using more or less complex criteria. The simplest threshold-based segmentation methods are available in most equipments, they are easy to calculate and they have been shown in many studies to have an important prognostic significance.

Prognostic value of nodal SUVmax of 18F-FDG PET/CT in nasopharyngeal carcinoma treated with intensity-modulated radiotherapy

Purpose

To investigate the predictive role of maximum standardized uptake value (SUV_max) of 2-[¹⁸F]fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) in nasopharyngeal cancer patients treated with intensity-modulated radiotherapy (IMRT).

Materials and Methods

Between October 2006 and April 2016, 53 patients were treated with IMRT in two institutions and their PET/CT at the time of diagnosis was reviewed. The SUV_max of their nasopharyngeal lesions and metastatic lymph nodes (LN) was recorded. IMRT was delivered using helical tomotherapy. All patients except for one were treated with concurrent chemoradiation therapy (CCRT). Correlations between SUV_max and patients’ survival and recurrence were analyzed.

Results

At a median follow-up time of 31.5 months (range, 3.4 to 98.7 months), the 3-year overall survival (OS) and disease-free survival (DFS) rates were 83.2% and 77.5%, respectively. In univariate analysis, patients with a higher nodal pre-treatment SUV_max (≥ 13.4) demonstrated significantly lower 3-year OS (93.1% vs. 55.5%; p = 0.003), DFS (92.7% vs. 38.5%; p < 0.001), locoregional recurrence-free survival (100% vs. 50.5%; p < 0.001), and distant metastasis-free survival (100% vs. 69.2%; p = 0.004), respectively. In multivariate analysis, high pre-treatment nodal SUV_max (≥ 13.4) was a negative prognostic factor for OS (hazard ratio [HR], 7.799; 95% confidence interval [CI], 1.506–40.397; p = 0.014) and DFS (HR, 9.392; 95% CI, 1.989–44.339; p = 0.005).

conclusions

High pre-treatment nodal SUV_max was an independent prognosticator of survival and disease progression in nasopharyngeal carcinoma patients treated with IMRT in our cohort. Therefore, nodal SUV_max may provide important information for identifying patients who require more aggressive treatment.

Cervical nodal volume for prognostication and risk stratification of patients with nasopharyngeal carcinoma, and implications on the TNM-staging system

We aim to evaluate the quantitative parameters of ¹⁸F-FDG PET/CT (metabolic parameters) and MRI (morphologic parameters) for prognostication and risk stratification in nasopharyngeal carcinoma (NPC). 200 (147 males, aged 50 ± 13 years-old, mean ± S.D.) newly diagnosed patients with NPC (T_xN_xM₀) were prospectively recruited. Primary tumor and nodal lesions were identified and segmented for both morphologic (volume, VOL) and metabolic (SUV and MTV) quantification. Independent predictive factors for recurrence free survival (RFS) and overall survival (OS) were morphologic nodal volume (VOL_N, p < 0.001), TNM-stage (p = 0.022), N-Stage (p = 0.024) for RFS, and VOL_N (p = 0.014) for OS. Using Classification and Regression Tree (CART) analysis, three risk-layers were identified for RFS: Stage I/II with VOL_N < 18cc (HR = 1), stage III /IV with VOL_N < 18cc (HR = 2.93), VOL_N ≥ 18cc (HR = 7.84) regardless of disease stage (p < 0.001). For OS, two risk layers were identified: VOL_N < 18cc (HR = 1), VOL_N ≥ 18cc (HR = 4.23) (p = 0.001). The 18cc threshold for morphologic nodal volume was validated by an independent cohort (n = 105). Based on the above risk-classification, 35 patients (17.5%) would have a higher risk than suggested by the TNM-staging system. Thus, morphologic nodal volume is an important factor in prognostication and risk stratification in NPC, and should be incorporated into the staging system, while PET parameters have no advantage for this purpose in our cohort.

Tumor Metabolic Features Identified by 18F-FDG PET Correlate with Gene Networks of Immune Cell Microenvironment in Head and Neck Cancer

The importance of ¹⁸F-FDG PET in imaging head and neck squamous cell carcinoma (HNSCC) has grown in recent decades. Because PET has prognostic values, and provides functional and molecular information in HNSCC, the genetic and biologic backgrounds associated with PET parameters are of great interest. Here, as a systems biology approach, we aimed to investigate gene networks associated with tumor metabolism and their biologic function using RNA sequence and ¹⁸F-FDG PET data. Methods: Using RNA sequence data of HNSCC downloaded from The Cancer Genome Atlas data portal, we constructed a gene coexpression network. PET parameters including lesion-to-blood-pool ratio, metabolic tumor volume, and tumor lesion glycolysis were calculated. The Pearson correlation test was performed between module eigengene-the first principal component of modules' expression profile-and the PET parameters. The significantly correlated module was functionally annotated with gene ontology terms, and its hub genes were identified. Survival analysis of the significantly correlated module was performed. Results: We identified 9 coexpression network modules from the preprocessed RNA sequence data. A network module was significantly correlated with total lesion glycolysis as well as maximum and mean ¹⁸F-FDG uptake. The expression profiles of hub genes of the network were inversely correlated with ¹⁸F-FDG uptake. The significantly annotated gene ontology terms of the module were associated with immune cell activation and aggregation. The module demonstrated significant association with overall survival, and the group with higher module eigengene showed better survival than the other groups with statistical significance (P = 0.022). Conclusion: We showed that a gene network that accounts for immune cell microenvironment was associated with ¹⁸F-FDG uptake as well as prognosis in HNSCC. Our result supports the idea that competition for glucose between cancer cell and immune cell plays an important role in cancer progression associated with hypermetabolic features. In the future, PET parameters could be used as a surrogate marker of HNSCC for estimating molecular status of immune cell microenvironment.