Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma

Mehrsima Abdoli,Habib Zaidi,Carolina Llina Fuentes,Issam M El Naqa

doi:10.1007/s00259-011-2053-0

Abstract

PurposeSeveral methods have been proposed for the segmentation of 18F-FDG uptake in PET. In this study, we assessed the performance of four categories of 18F-FDG PET image segmentation techniques in pharyngolaryngeal squamous cell carcinoma using clinical studies where the surgical specimen served as the benchmark.MethodsNine PET image segmentation techniques were compared including: five thresholding methods; the level set technique (active contour); the stochastic expectation-maximization approach; fuzzy clustering-based segmentation (FCM); and a variant of FCM, the spatial wavelet-based algorithm (FCM-SW) which incorporates spatial information during the segmentation process, thus allowing the handling of uptake in heterogeneous lesions. These algorithms were evaluated using clinical studies in which the segmentation results were compared to the 3-D biological tumour volume (BTV) defined by histology in PET images of seven patients with T3–T4 laryngeal squamous cell carcinoma who underwent a total laryngectomy. The macroscopic tumour specimens were collected “en bloc”, frozen and cut into 1.7- to 2-mm thick slices, then digitized for use as reference.ResultsThe clinical results suggested that four of the thresholding methods and expectation-maximization overestimated the average tumour volume, while a contrast-oriented thresholding method, the level set technique and the FCM-SW algorithm underestimated it, with the FCM-SW algorithm providing relatively the highest accuracy in terms of volume determination (−5.9 ± 11.9%) and overlap index. The mean overlap index varied between 0.27 and 0.54 for the different image segmentation techniques. The FCM-SW segmentation technique showed the best compromise in terms of 3-D overlap index and statistical analysis results with values of 0.54 (0.26–0.72) for the overlap index.ConclusionThe BTVs delineated using the FCM-SW segmentation technique were seemingly the most accurate and approximated closely the 3-D BTVs defined using the surgical specimens. Adaptive thresholding techniques need to be calibrated for each PET scanner and acquisition/processing protocol, and should not be used without optimization.

Highlights

Image-guided adaptive radiation therapy using modern technology has emerged as a promising approach to dose escalation in pharyngolaryngeal squamous cell carcinoma [1]
We present here an assessment of the performance of four categories of 18F-FDG PET image segmentation techniques for pharyngolaryngeal squamous cell carcinoma in clinical studies, where the 3-D contour defined on the surgical specimen served as the reference
Where PCE refers to the positive classification errors (CE), including voxels of the background that are classified as belonging to the tumour, and NCE refers to negative CEs, including voxels of Figure 2 shows example clinical imaging of a pharyngolaryngeal squamous cell carcinoma comparing the target volume definitions obtained using the different segmentation methods with the histology serving as reference

Summary

Introduction

Image-guided adaptive radiation therapy using modern technology has emerged as a promising approach to dose escalation in pharyngolaryngeal squamous cell carcinoma [1]. In many studies the findings of anatomical and molecular imaging modalities have disagreed, and the addition of PET has been shown to result in modification of the treatment plans in a substantial number of clinical studies [3]. Another important consideration is the reduction in inter- and intraobserver variability achieved with PET for delineation of the biological tumour volume (BTV) compared to anatomical imaging techniques [4]

Methods

Results

Discussion

Conclusion