Quantification of 18F-fluorodeoxyglucose uptake to detect residual nodal disease in locally advanced head and neck squamous cell carcinoma after chemoradiotherapy: results from the ECLYPS study

Role of 18F-FDG PET/CT in Head and Neck Squamous Cell Carcinoma: Current Evidence and Innovative Applications

This article provides an overview of the use of 18F-FDG PET/CT in various clinical scenarios of head-neck squamous cell carcinoma, ranging from initial staging to treatment-response assessment, and post-therapy follow-up, with a focus on the current evidence, debated issues, and innovative applications. Methodological aspects and the most frequent pitfalls in head-neck imaging interpretation are described. In the initial work-up, 18F-FDG PET/CT is recommended in patients with metastatic cervical lymphadenectomy and occult primary tumor; moreover, it is a well-established imaging tool for detecting cervical nodal involvement, distant metastases, and synchronous primary tumors. Various 18F-FDG pre-treatment parameters show prognostic value in terms of disease progression and overall survival. In this scenario, an emerging role is played by radiomics and machine learning. For radiation-treatment planning, 18F-FDG PET/CT provides an accurate delineation of target volumes and treatment adaptation. Due to its high negative predictive value, 18F-FDG PET/CT, performed at least 12 weeks after the completion of chemoradiotherapy, can prevent unnecessary neck dissections. In addition to radiomics and machine learning, emerging applications include PET/MRI, which combines the high soft-tissue contrast of MRI with the metabolic information of PET, and the use of PET radiopharmaceuticals other than 18F-FDG, which can answer specific clinical needs.

Impact of 18F-FDG PET Intensity Normalization on Radiomic Features of Oropharyngeal Squamous Cell Carcinomas and Machine Learning-Generated Biomarkers

We aimed to investigate the effects of 18F-FDG PET voxel intensity normalization on radiomic features of oropharyngeal squamous cell carcinoma (OPSCC) and machine learning-generated radiomic biomarkers. Methods: We extracted 1,037 18F-FDG PET radiomic features quantifying the shape, intensity, and texture of 430 OPSCC primary tumors. The reproducibility of individual features across 3 intensity-normalized images (body-weight SUV, reference tissue activity ratio to lentiform nucleus of brain and cerebellum) and the raw PET data was assessed using an intraclass correlation coefficient (ICC). We investigated the effects of intensity normalization on the features' utility in predicting the human papillomavirus (HPV) status of OPSCCs in univariate logistic regression, receiver-operating-characteristic analysis, and extreme-gradient-boosting (XGBoost) machine-learning classifiers. Results: Of 1,037 features, a high (ICC ≥ 0.90), medium (0.90 > ICC ≥ 0.75), and low (ICC < 0.75) degree of reproducibility across normalization methods was attained in 356 (34.3%), 608 (58.6%), and 73 (7%) features, respectively. In univariate analysis, features from the PET normalized to the lentiform nucleus had the strongest association with HPV status, with 865 of 1,037 (83.4%) significant features after multiple testing corrections and a median area under the receiver-operating-characteristic curve (AUC) of 0.65 (interquartile range, 0.62-0.68). Similar tendencies were observed in XGBoost models, with the lentiform nucleus-normalized model achieving the numerically highest average AUC of 0.72 (SD, 0.07) in the cross validation within the training cohort. The model generalized well to the validation cohorts, attaining an AUC of 0.73 (95% CI, 0.60-0.85) in independent validation and 0.76 (95% CI, 0.58-0.95) in external validation. The AUCs of the XGBoost models were not significantly different. Conclusion: Only one third of the features demonstrated a high degree of reproducibility across intensity-normalization techniques, making uniform normalization a prerequisite for interindividual comparability of radiomic markers. The choice of normalization technique may affect the radiomic features' predictive value with respect to HPV. Our results show trends that normalization to the lentiform nucleus may improve model performance, although more evidence is needed to draw a firm conclusion.

Optimized 18F-FDG PET-CT Method to Improve Accuracy of Diagnosis of Metastatic Cancer

The diagnosis of cancer by FDG PET-CT is often inaccurate owing to subjectivity of interpretation. We compared the accuracy of a novel normalized (standardized) method of interpretation with conventional non-normalized SUV. Patients (n = 393) with various malignancies were studied with FDG PET/CT to determine the presence or absence of cancer. Target lesions were assessed by two methods: (1) conventional SUV_max (conSUV_max) and (2) a novel method that combined multiple factors to optimize SUV (optSUVmax), including the patient's normal liver SUV_max, a liver constant (k) derived from a review of the literature, and use of site-specific thresholds for malignancy. The two methods were compared to pathology findings in 154 patients being evaluated for mediastinal and/or hilar lymph node (MHLNs) metastases, 143 evaluated for extra-thoracic lymph node (ETLNs) metastases, and 96 evaluated for liver metastases. OptSUV_max was superior to conSUV_max for all patient groups. For MHLNs, sensitivity was 83.8% vs. 80.7% and specificity 88.7% vs. 9.6%, respectively; for ETLNs, sensitivity was 92.1% vs. 77.8% and specificity 80.1% vs. 27.6%, respectively; and for lesions in the liver parenchyma, sensitivity was 96.1% vs. 82.3% and specificity 88.8% vs. 23.0%, respectively. Optimized SUV_max increased diagnostic accuracy of FDG PET-CT for cancer when compared with conventional SUV_max interpretation.

18F-FDG PET/CT Prediction of Treatment Outcomes in Human Papillomavirus-Positive, Locally Advanced Oropharyngeal Cancer Patients Receiving Deintensified Therapy: Results from NRG-HN002

The purpose of this study was to determine the negative predictive value (NPV) of a 12- to 14-wk posttreatment PET/CT for 2-y progression-free survival (PFS) and locoregional control (LRC) in patients with p16-positive locoregionally advanced oropharyngeal cancer (LA-OPC). Study was a secondary endpoint in NRG-HN002, a noncomparative phase II trial in p16-positive LA-OPC, stage T1-T2, N1-N2b or T3, N0-N2b, and ≤10 pack-year smoking. Patients were randomized in a 1:1 ratio to reduced-dose intensity-modulated radiotherapy (IMRT) with or without cisplatin. Methods: PET/CT scans were reviewed centrally. Tumor response evaluations for the primary site, right neck, and left neck were performed using a 5-point ordinal scale (Hopkins criteria). Overall scores were then assigned as negative, positive, or indeterminate. Patients with a negative score for all 3 evaluation sites were given an overall score of negative. The hypotheses were NPV for PFS and LRC at 2-y posttreatment ≤ 90% versus >90% (1-sided P value, 0.10). Results: A total of 316 patients were enrolled, of whom 306 were randomized and eligible. Of these, 131 (42.8%) patients consented to a posttherapy PET/CT, and 117 (89.3%) patients were eligible for PET/CT analysis. The median time from the end of treatment to PET/CT scan was 94 d (range, 52-139 d). Estimated 2-y PFS and LRC rates in the analysis subgroup were 91.3% (95% CI, 84.6, 95.8%) and 93.8% (95% CI, 87.6, 97.5%), respectively. Posttreatment scans were negative for residual tumor for 115 patients (98.3%) and positive for 2 patients (1.7%). NPV for 2-y PFS was 92.0% (90% lower confidence bound [LCB] 87.7%; P = 0.30) and for LRC was 94.5% (90% LCB 90.6%; P = 0.07). Conclusion: In the context of deintensification with reduced-dose radiation, the NPV of a 12- to 14-wk posttherapy PET/CT for 2-y LRC is estimated to be >90%, similar to that reported for patients receiving standard chemoradiation. However, there is insufficient evidence to conclude that the NPV is >90% for PFS.

Dual time point imaging in locally advanced head and neck cancer to assess residual nodal disease after chemoradiotherapy

Background

FDG-PET/CT has a high negative predictive value to detect residual nodal disease in patients with locally advanced squamous cell head and neck cancer after completing concurrent chemoradiotherapy (CCRT). However, the positive predictive value remains suboptimal due to inflammation after radiotherapy, generating unnecessary further investigations and possibly even surgery. We report the results of a preplanned secondary end point of the ECLYPS study regarding the potential advantages of dual time point FDG-PET/CT imaging (DTPI) in this setting. Standardized dedicated head and neck FDG-PET/CT images were obtained 12 weeks after CCRT at 60 and 120 min after tracer administration. We performed a semiquantitative assessment of lymph nodes, and the retention index (RI) was explored to optimize diagnostic performance. The reference standard was histology, negative FDG-PET/CT at 1 year, or > 2 years of clinical follow-up. The time-dependent area under the receiver operator characteristics (AUROC) curves was calculated.

Results

In total, 102 subjects were eligible for analysis. SUV values increased in malignant nodes (median SUV₁ = 2.6 vs. SUV₂ = 2.7; P = 0.04) but not in benign nodes (median SUV₁ = 1.8 vs. SUV₂ = 1.7; P = 0.28). In benign nodes, RI was negative although highly variable (median RI = − 2.6; IQR 21.2), while in malignant nodes RI was positive (median RI = 12.3; IQR 37.2) and significantly higher (P = 0.018) compared to benign nodes. A combined threshold (SUV₁ ≥ 2.2 + RI ≥ 3%) significantly reduced the amount of false-positive cases by 53% (P = 0.02) resulting in an increased specificity (90.8% vs. 80.5%) and PPV (52.9% vs. 37.0%), while sensitivity (60.0% vs. 66.7%) and NPV remained comparably high (92.9% vs. 93.3%). However, AUROC, as overall measure of benefit in diagnostic accuracy, did not significantly improve (P = 0.62). In HPV-related disease (n = 32), there was no significant difference between SUV₁, SUV₂, and RI in malignant and benign nodes, yet this subgroup was small.

Conclusions

DTPI did not improve the overall diagnostic accuracy of FDG-PET/CT to detect residual disease 12 weeks after chemoradiation. Due to differences in tracer kinetics between malignant and benign nodes, DTPI improved the specificity, but at the expense of a loss in sensitivity, albeit minimal. Since false negatives at the 12 weeks PET/CT are mainly due to minimal residual disease, DTPI is not able to significantly improve sensitivity, but repeat scanning at a later time (e.g. after 12 months) could possibly solve this problem. Further study is required in HPV-associated disease.

Risk Stratification Using 18F-FDG PET/CT and Artificial Neural Networks in Head and Neck Cancer Patients Undergoing Radiotherapy

This study retrospectively analyzed the performance of artificial neural networks (ANN) to predict overall survival (OS) or locoregional failure (LRF) in HNSCC patients undergoing radiotherapy, based on 2-[¹⁸F]FDG PET/CT and clinical covariates. We compared predictions relying on three different sets of features, extracted from 230 patients. Specifically, (i) an automated feature selection method independent of expert rating was compared with (ii) clinical variables with proven influence on OS or LRF and (iii) clinical data plus expert-selected SUV metrics. The three sets were given as input to an artificial neural network for outcome prediction, evaluated by Harrell’s concordance index (HCI) and by testing stratification capability. For OS and LRF, the best performance was achieved with expert-based PET-features (0.71 HCI) and clinical variables (0.70 HCI), respectively. For OS stratification, all three feature sets were significant, whereas for LRF only expert-based PET-features successfully classified low vs. high-risk patients. Based on 2-[¹⁸F]FDG PET/CT features, stratification into risk groups using ANN for OS and LRF is possible. Differences in the results for different feature sets confirm the relevance of feature selection, and the key importance of expert knowledge vs. automated selection.

Quality Assessment in FDG-PET/CT Imaging of Head-and-Neck Cancer: One Home Run Is Better Than Two Doubles

2-deoxy-2-[¹⁸F]fluoro-D-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) is indicated in head-and-neck cancer for the initial workup when clinically indicated (e. g., large tumors, clinically positive neck, cervical adenopathy from an unknown primary, etc.), for the assessment of treatment response 12 weeks after completion of (chemo)radiotherapy, and during follow-up when there is suspicion of relapse. The successful implementation of FDG-PET/CT in routine clinical practice requires an in-depth understanding of the recent advances in physics and engineering that have significantly improved the imaging capabilities of PET/CT scanners (e.g., digital silicon photomultipliers, point-spread function modeling, and time-of-flight, and Bayesian penalized likelihood reconstruction). Moreover, a coordinated harmonization effort from professional societies (e.g., EANM) and international bodies (e.g., IAEA) has resulted in the creation of quality assurance frameworks (e.g., QUANUM, EARL, GMP) and guidelines that collectively cover the entire spectrum from tracer production, hardware calibration, patient preparation, and scan acquisition, to image interpretation (e.g., PERCIST, Hopkins criteria). The ultimate goal is to standardize the PET/CT technique and to guarantee accurate and reproducible imaging results for every patient. This review summarizes the recent technical breakthroughs in PET/CT scan design and describes the existing quality assessment frameworks with a focus on applications in head-and-neck cancer. Strict adherence to these harmonization efforts will enable leveraging the full potential of PET/CT and translate the proven benefits of this technique into tangible improvements in outcome for patients with head-and-neck cancer in routine clinical care.

Head and neck tumors angiogenesis imaging with 68Ga-NODAGA-RGD in comparison to 18F-FDG PET/CT: a pilot study

Background

Angiogenesis plays an important role in head and neck squamous cell carcinoma (HNSCC) progression. This pilot study was designed to compare the distribution of ⁶⁸Ga-NODAGA-RGD PET/CT for imaging α_vβ₃ integrins involved in tumor angiogenesis to ¹⁸F-FDG PET/CT in patients with HNSCC.

Material and methods

Ten patients (aged 58.4 ± 8.3 years [range, 44–73 years], 6 males, 4 females) with a total of 11 HNSCC were prospectively enrolled. Activity mapping and standard uptake values (SUV) from both ⁶⁸Ga-NODAGA-RGD and ¹⁸F-FDG PET/CT scans were recorded for primary tumor and compared with the Wilcoxon signed-rank test. The relation between the SUV of both tracers was assessed using the Spearman correlation.

Results

All HNSCC tumors were visible with both tracers. Quantitative analysis showed higher ¹⁸F-FDG SUV_max in comparison to ⁶⁸Ga-NODAGA-RGD (14.0 ± 6.1 versus 3.9 ± 1.1 g/mL, p = 0.0017) and SUV_mean (8.2 ± 3.1 versus 2.0 ± 0.8 g/mL, p = 0.0017). Both ¹⁸F-FDG and ⁶⁸Ga-NODAGA-RGD uptakes were neither correlated with grade, HPV status nor p16 protein expression (p ≥ 0.17).

Conclusion

All HNSCC tumors were detected with both tracers with higher uptake with ¹⁸F-FDG, however. ⁶⁸Ga-NODAGA-RGD has a different spatial distribution than ¹⁸F-FDG bringing different tumor information.

Trial registration

NCT, NCT02666547. Registered 12.8.2012.