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Accurate FDG PET tumor segmentation using the peritumoral halo layer method: a study in patients with esophageal squamous cell carcinoma

Overview of attention for article published in Cancer Imaging, September 2018
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Title
Accurate FDG PET tumor segmentation using the peritumoral halo layer method: a study in patients with esophageal squamous cell carcinoma
Published in
Cancer Imaging, September 2018
DOI 10.1186/s40644-018-0169-1
Pubmed ID
Authors

Sungmin Jun, Jung Gu Park, Youngduk Seo

Abstract

In a previous study, FDG PET tumor segmentation (SegPHL) using the peritumoral halo layer (PHL) was more reliable than fixed threshold methods in patients with thyroid cancer. We performed this study to validate the reliability and accuracy of the PHL method in patients with esophageal squamous cell carcinomas (ESCCs), which can be larger and more heterogeneous than thyroid cancers. A total of 121 ESCC patients (FDG avid = 85 (70.2%); FDG non-avid = 36 (29.8%)) were enrolled in this study. In FDG avid ESCCs, metabolic tumor length (ML) using SegPHL (MLPHL), fixed SUV 2.5 threshold (ML2.5), and fixed 40% of maximum SUV (SUVmax) (ML40%) were measured. Regression and Bland-Altman analyses were performed to evaluate associations between ML, endoscopic tumor length (EL), and pathologic tumor length (PL). A comparison test was performed to evaluate the absolute difference between ML and PL. Correlation with tumor threshold determined by the PHL method (PHL tumor threshold) and SUVmax was evaluated. MLPHL, ML2.5, and ML40% correlated well with EL (R2 = 0.6464, 0.5789, 0.3321, respectively; p < 0.001) and PL (R2 = 0.8778, 0.8365, 0.6266, respectively; p < 0.001). However, ML2.5 and ML40% showed significant proportional error with regard to PL; there was no significant error between MLPHL and PL. MLPHL showed the smallest standard deviation on Bland-Altman analyses. The absolute differences between ML and PL were significantly smaller for MLPHL and ML40% than for ML2.5 (p < 0.0001). The PHL tumor threshold showed an inverse correlation with SUVmax (σ = - 0.923, p < 0.0001). SegPHL was more accurate than fixed threshold methods in ESCC. The PHL tumor threshold was adjusted according to SUVmax of ESCC.

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The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 21%
Unspecified 1 7%
Lecturer 1 7%
Student > Bachelor 1 7%
Student > Master 1 7%
Other 2 14%
Unknown 5 36%
Readers by discipline Count As %
Medicine and Dentistry 6 43%
Neuroscience 1 7%
Unspecified 1 7%
Unknown 6 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 September 2018.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from Cancer Imaging
#445
of 674 outputs
Outputs of similar age
#272,873
of 351,260 outputs
Outputs of similar age from Cancer Imaging
#8
of 14 outputs
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