PET/CT in Surgical Planning for Head and Neck Cancer

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.

Comparison of semi-automatic and manual segmentation methods for tumor delineation on head and neck squamous cell carcinoma (HNSCC) positron emission tomography (PET) images

Objective. Accurate and reproducible tumor delineation on positron emission tomography (PET) images is required to validate predictive and prognostic models based on PET radiomic features. Manual segmentation of tumors is time-consuming whereas semi-automatic methods are easily implementable and inexpensive. This study assessed the reliability of semi-automatic segmentation methods over manual segmentation for tumor delineation in head and neck squamous cell carcinoma (HNSCC) PET images.Approach. We employed manual and six semi-automatic segmentation methods (just enough interaction (JEI), watershed, grow from seeds (GfS), flood filling (FF), 30% SUVmax and 40%SUVmax threshold) using 3D slicer software to extract 128 radiomic features from FDG-PET images of 100 HNSCC patients independently by three operators. We assessed the distributional properties of all features and considered 92 log-transformed features for subsequent analysis. For each paired comparison of a feature, we fitted a separate linear mixed effect model using the method (two levels; manual versus one semi-automatic method) as a fixed effect and the subject and the operator as the random effects. We estimated different statistics-the intraclass correlation coefficient agreement (aICC), limits of agreement (LoA), total deviation index (TDI), coverage probability (CP) and coefficient of individual agreement (CIA)-to evaluate the agreement between the manual and semi-automatic methods.Main results. Accounting for all statistics across 92 features, the JEI method consistently demonstrated acceptable agreement with the manual method, with median values of aICC = 0.86, TDI = 0.94, CP = 0.66, and CIA = 0.91.Significance. This study demonstrated that JEI method is a reliable semi-automatic method for tumor delineation on HNSCC PET images.

Cost-Effectiveness Analysis of PET-CT Surveillance After Treatment of Human Papillomavirus-Positive Oropharyngeal Cancer

OBJECTIVE

To determine the cost-effectiveness of surveillance imaging with PET/CT scan among patients with human papillomavirus-positive oropharyngeal squamous cell carcinoma.

STUDY DESIGN

Cost-effectiveness analysis.

SETTING

Oncologic care centers in the United States with head and neck oncologic surgeons and physicians.

METHODS

We compared the cost-effectiveness of 2 posttreatment surveillance strategies: clinical surveillance with the addition of PET/CT scan versus clinical surveillance alone in human papillomavirus-positive oropharyngeal squamous cell carcinoma patients. We constructed a Markov decision model which was analyzed from a third-party payer's perspective using 1-year Markov cycles and a 30-year time horizon. Values for transition probabilities, costs, health care utilities, and their studied ranges were derived from the literature.

RESULTS

The incremental cost-effectiveness ratio for PET/CT with clinical surveillance versus clinical surveillance alone was $89,850 per quality-adjusted life year gained. Flexible fiberoptic scope exams during clinical surveillance would have to be over 51% sensitive or PET/CT scan cost would have to exceed $1678 for clinical surveillance alone to be more cost-effective. The willingness-to-pay threshold at which imaging surveillance was equally cost-effective to clinical surveillance was approximately $80,000/QALY.

CONCLUSION

Despite lower recurrence rates of human papillomavirus-positive oropharyngeal cancer, a single PET/CT scan within 6 months after primary treatment remains a cost-effective tool for routine surveillance when its cost does not exceed $1678. The cost-effectiveness of this strategy is also dependent on the clinical surveillance sensitivity (flexible fiberoptic pharyngoscopy), and willingness-to-pay thresholds which vary by country.

Efforts toward PET-Activatable Red-Shifted Silicon Rhodamines and Silicon Pyronine Dyes

Tracers for bimodal optical imaging and positron emission tomography unite multiple advantages in a single molecule. Their tumor-specific uptake can be visualized after their PET activation by radiofluorination via PET/CT or PET/MRI allowing for staging or therapy planning, while their non-radioactive moiety additionally facilitates the visualization of malignant tissue during intraoperative fluorescence-guided surgery or in histological assessments. The silicon-bridged xanthene core offers the opportunity for radiofluorination with SiFA isotope exchange to obtain a small-molecule, PET-activatable NIR dye that can be linked to different target vectors. Herein, we demonstrate for the first time the PET-activation of a fluorinated silicon pyronine, belonging to a class of low-molecular-weight fluorescence dyes with a large Stokes shift (up to 129 nm) and solvent-dependent NIR dye properties, with a successful radiochemical conversion of 70%. The non-fluorinated pyronine precursor is easily accessible by a three-step sequence from commercially starting material with a 12% overall yield. Moreover, a library of seven unusually functionalized (by approximately 15 nm), red-shifted silicon rhodamines were synthesized in three- to four-step sequences and the optical properties of the novel dyes were characterized. It was also shown that the synthesized silicon rhodamine dyes can be easily conjugated by amide bond formation or ‘click-reaction’ approaches.

Total lesion glycolysis as a predictor of clinical T3-4a laryngeal cancer with laryngectomy or nonlaryngectomy

The purpose of the present study is to investigate whether the 18F-fluorodeoxyglucose (18F-FDG) uptake parameter is related to survival outcomes for patients with clinical T3-T4a laryngeal cancer with various definitive treatments including total laryngectomy (TL). Parameters of 18F-FDG uptake in the primary tumors of 46 cases which were assessed by positron emission tomography with computed tomography were enrolled in the present observation study. Monovariate or multivariate survival analyses were performed with log-rank test or Cox regression model, with the hazard ratio (HR) and 95% confidence interval (CI), respectively. Cutoff values of the 18F-FDG uptake parameters were determined by the lowest P-value for monovariate overall survival. In the monovariate analysis, both metabolic tumor volume ≥13.1 and total lesion glycolysis (TLG) ≥46.5 were significantly associated with shorter overall survival, and TLG ≥46.5 was also related to a reduction in distant metastasis-free survival. In the multivariate analysis adjusting for clinical T classification (cT4/cT3) and treatment group (TL/non-TL), TLG (≥46.5/<46.5) was associated with both poorer overall (HR: 3.16, 95% CI: 1.10-9.49) and distant metastasis-free (HR: 8.91, 95% CI: 1.93-62.6) survival. In conclusion, TLG is a predictor for survival in laryngeal cancer.

A hidden Markov model for lymphatic tumor progression in the head and neck

Currently, elective clinical target volume (CTV-N) definition for head and neck squamous cell carcinoma (HNSCC) is mostly based on the prevalence of nodal involvement for a given tumor location. In this work, we propose a probabilistic model for lymphatic metastatic spread that can quantify the risk of microscopic involvement in lymph node levels (LNL) given the location of macroscopic metastases and T-category. This may allow for further personalized CTV-N definition based on an individual patient's state of disease. We model the patient's state of metastatic lymphatic progression as a collection of hidden binary random variables that indicate the involvement of LNLs. In addition, each LNL is associated with observed binary random variables that indicate whether macroscopic metastases are detected. A hidden Markov model (HMM) is used to compute the probabilities of transitions between states over time. The underlying graph of the HMM represents the anatomy of the lymphatic drainage system. Learning of the transition probabilities is done via Markov chain Monte Carlo sampling and is based on a dataset of HNSCC patients in whom involvement of individual LNLs was reported. The model is demonstrated for ipsilateral metastatic spread in oropharyngeal HNSCC patients. We demonstrate the model's capability to quantify the risk of microscopic involvement in levels III and IV, depending on whether macroscopic metastases are observed in the upstream levels II and III, and depending on T-category. In conclusion, the statistical model of lymphatic progression may inform future, more personalized, guidelines on which LNL to include in the elective CTV. However, larger multi-institutional datasets for model parameter learning are required for that.