Utility and Limitations of Metabolic Parameters in Head and Neck Cancer: Finding a Practical Segmentation Method

Overview

Journal Eur Arch Otorhinolaryngol

Specialty Otorhinolaryngology

Date 2022 May 2

PMID 35499622

Authors

Jefferson Rijo-Cedeno

Jorge Mucientes

Ithzel Maria Villarreal

Ana Royuela

Patricia Garcia Vicente

Jose Ramon Garcia-Berrocal

Affiliations

Soon will be listed here.

Abstract

Purpose: Although metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have shown good prognostic value in head and neck cancer (HNC), there are still many issues to resolve before their potential application in standard clinical practice. The purpose of this study was to compare the discrimination ability of two relevant segmentation methods in HNC and to evaluate the potential benefit of adding lymph nodes' metabolism (LNM) to the measurements.

Methods: We retrospectively analyzed a recently published database of 62 patients with HNC treated with chemoradiotherapy. MTV and TLG were measured using an absolute threshold of SUV2.5. Comparison analysis with previously published background-level threshold (BLT) results was done through Concordance index (C-index) in eight prognostic models.

Results: BLT obtained better C-index values in five out of the eight models. The addition of LNM improved C-index values in six of the prognostic models.

Conclusion: We found a potential benefit in adding LNM to the main tumor measurements, as well as in using a BLT for MTV segmentation compared to the most commonly used SUV2.5 threshold. Despite its limitations, this study suggests a practical and simple manner to use these parameters in standard clinical practice, aiming to help elaborate a general consensus.

Citing Articles

Performance Analysis of Six Semi-Automated Tumour Delineation Methods on [F] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) in Patients with Head and Neck Cancer.

Bianconi F, Salis R, Fravolini M, Khan M, Minestrini M, Filippi L Sensors (Basel). 2023; 23(18).

PMID: 37766009 PMC: 10537871. DOI: 10.3390/s23187952.

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