Literature DB >> 29866335

Quantifying the robustness of [18F]FDG-PET/CT radiomic features with respect to tumor delineation in head and neck and pancreatic cancer patients.

Maria Luisa Belli1, Martina Mori1, Sara Broggi1, Giovanni Mauro Cattaneo1, Valentino Bettinardi2, Italo Dell'Oca3, Federico Fallanca2, Paolo Passoni3, Emilia Giovanna Vanoli2, Riccardo Calandrino1, Nadia Di Muzio3, Maria Picchio2, Claudio Fiorino4.   

Abstract

PURPOSE: To investigate the robustness of PET radiomic features (RF) against tumour delineation uncertainty in two clinically relevant situations.
METHODS: Twenty-five head-and-neck (HN) and 25 pancreatic cancer patients previously treated with 18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based planning optimization were considered. Seven FDG-based contours were delineated for tumour (T) and positive lymph nodes (N, for HN patients only) following manual (2 observers), semi-automatic (based on SUV maximum gradient: PET_Edge) and automatic (40%, 50%, 60%, 70% SUV_max thresholds) methods. Seventy-three RF (14 of first order and 59 of higher order) were extracted using the CGITA software (v.1.4). The impact of delineation on volume agreement and RF was assessed by DICE and Intra-class Correlation Coefficients (ICC).
RESULTS: A large disagreement between manual and SUV_max method was found for thresholds  ≥50%. Inter-observer variability showed median DICE values between 0.81 (HN-T) and 0.73 (pancreas). Volumes defined by PET_Edge were better consistent with the manual ones compared to SUV40%. Regarding RF, 19%/19%/47% of the features showed ICC < 0.80 between observers for HN-N/HN-T/pancreas, mostly in the Voxel-alignment matrix and in the intensity-size zone matrix families. RFs with ICC < 0.80 against manual delineation (taking the worst value) increased to 44%/36%/61% for PET_Edge and to 69%/53%/75% for SUV40%.
CONCLUSIONS: About 80%/50% of 72 RF were consistent between observers for HN/pancreas patients. PET_edge was sufficiently robust against manual delineation while SUV40% showed a worse performance. This result suggests the possibility to replace manual with semi-automatic delineation of HN and pancreas tumours in studies including PET radiomic analyses.
Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Head-and-neck cancer; PET; Pancreas cancer; Radiomic; Texture analysis

Mesh:

Substances:

Year:  2018        PMID: 29866335     DOI: 10.1016/j.ejmp.2018.05.013

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   2.685


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