Abstract

Purpose:The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans.Methods:A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts.Results:Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach.Conclusions:Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in clinical oncology decision-making. The properties of the authors approach make it well suited for applications in image-guided radiation oncology, response assessment, or treatment outcome prediction.

Highlights

  • FDG PET/CT has become an essential tool for clinical management of head and neck (H&N) squamous cell carcinoma (SCC).1 This disease typically originates from the normal squamous mucosa that lines the open air spaces in the H&N region

  • The provided 95% confidence intervals (CIs) show that intra- and interoperator standard deviations are significantly lower for the semiautomated method compared to the manual segmentation approach

  • This can be seen by the example provided in Fig. 12; the manual segmentation approach leads to considerable variation in segmentations produced by the same user as well as across users, whereas little variation is observed between the segmentations produced with the semiautomated method

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Summary

Introduction

FDG PET/CT has become an essential tool for clinical management of head and neck (H&N) squamous cell carcinoma (SCC). This disease typically originates from the normal squamous mucosa that lines the open air spaces in the H&N region. FDG PET/CT has become an essential tool for clinical management of head and neck (H&N) squamous cell carcinoma (SCC).1 This disease typically originates from the normal squamous mucosa that lines the open air spaces in the H&N region. Cancers are most often caused by irritants and carcinogens from cigarette smoke, alcohol, and chewing tobacco more recent studies show a role for human papilloma virus (HPV).2,3 Once cancerous, these mucosal neoplasms have access to associated lymphatic drainage, leading to local/regional spread of the disease to neck lymph nodes. These mucosal neoplasms have access to associated lymphatic drainage, leading to local/regional spread of the disease to neck lymph nodes Staging for these cancers is defined by the size and invasion pattern of the primary site cancer (T stage) as well as the presence, size, and location of regional nodes (N stage).. Staging for these cancers is defined by the size and invasion pattern of the primary site cancer (T stage) as well as the presence, size, and location of regional nodes (N stage). More rarely these cancers spread to regions beyond the H&N region, which can be defined as metastases (M stage)

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