Koichi Okuda1, Hisahiro Saito2, Shozo Yamashita3, Haruki Yamamoto3, Hajime Ichikawa4, Toyohiro Kato4, Kunihiko Yokoyama5, Mariko Doai6, Mitsumasa Hashimoto7, Munetaka Matoba6. 1. Department of Physics, Kanazawa Medical University, 1-1 Daigaku, Uchinada, Kahoku, Ishikawa, 920-0293, Japan. okuda@kanazawa-med.ac.jp. 2. Department of Radiological Technology, Kanazawa Medical University Hospital, Uchinada, Kahoku, Japan. 3. Division of Radiology, Public Central Hospital of Matto Ishikawa, Hakusan, Japan. 4. Department of Radiology, Toyohashi Municipal Hospital, Toyohashi, Japan. 5. PET Imaging Center, Public Central Hospital of Matto Ishikawa, Hakusan, Japan. 6. Department of Radiology, Kanazawa Medical University Hospital, Uchinada, Kahoku, Japan. 7. Department of Physics, Kanazawa Medical University, 1-1 Daigaku, Uchinada, Kahoku, Ishikawa, 920-0293, Japan.
Abstract
PURPOSE: This study aimed to develop a dedicated phantom using acrylic beads for texture analysis and to represent heterogeneous 18F-fluorodeoxyglucose (FDG) distributions in various acquisition periods. METHODS: Images of acrylic spherical beads with or without diameters of 5- and 10-mm representing heterogeneous and homogeneous 18F-FDG distribution in phantoms, respectively, were collected for 20 min in list mode. Phantom data were reconstructed using three-dimensional ordered subset expectation maximization with attenuation and scatter corrections, and the time-of-flight algorithm. The beads phantom images were acquired twice to evaluate the robustness of texture features. Thirty-one texture features were extracted, and the robustness of texture feature values was evaluated by calculating the percentage of coefficient of variation (%COV) and intraclass coefficient of correlation (ICC). Cross-correlation coefficients among texture feature values were clustered to classify the characteristics of these features. RESULTS: Heterogeneous 18F-FDG distribution was represented by the beads phantom images. The agreements of %COV between two measurements were acceptable (ICC ≥ 0.71). All texture features were classified into four groups. Among 31 texture features, 24 exhibited significant different values between phantoms with and without beads in 1-, 2-, 3-, 4-, 5-, 20-min image acquisitions. Whereas, the homogeneous and heterogeneous 18F-FDG distribution could not be discriminated by seven texture features: low gray-level run emphasis, high gray-level run emphasis, short-run low gray-level emphasis, low gray-level zone emphasis, high gray-level zone emphasis, short-zone low gray-level emphasis, and coarseness. CONCLUSIONS: We have developed the acrylic beads phantom for texture analysis that could represent heterogeneous 18F-FDG distributions in various acquisition periods. Most texture features could discriminate homogeneous and heterogeneous 18F-FDG distributions in the beads phantom images.
PURPOSE: This study aimed to develop a dedicated phantom using acrylic beads for texture analysis and to represent heterogeneous 18F-fluorodeoxyglucose (FDG) distributions in various acquisition periods. METHODS: Images of acrylic spherical beads with or without diameters of 5- and 10-mm representing heterogeneous and homogeneous 18F-FDG distribution in phantoms, respectively, were collected for 20 min in list mode. Phantom data were reconstructed using three-dimensional ordered subset expectation maximization with attenuation and scatter corrections, and the time-of-flight algorithm. The beads phantom images were acquired twice to evaluate the robustness of texture features. Thirty-one texture features were extracted, and the robustness of texture feature values was evaluated by calculating the percentage of coefficient of variation (%COV) and intraclass coefficient of correlation (ICC). Cross-correlation coefficients among texture feature values were clustered to classify the characteristics of these features. RESULTS: Heterogeneous 18F-FDG distribution was represented by the beads phantom images. The agreements of %COV between two measurements were acceptable (ICC ≥ 0.71). All texture features were classified into four groups. Among 31 texture features, 24 exhibited significant different values between phantoms with and without beads in 1-, 2-, 3-, 4-, 5-, 20-min image acquisitions. Whereas, the homogeneous and heterogeneous 18F-FDG distribution could not be discriminated by seven texture features: low gray-level run emphasis, high gray-level run emphasis, short-run low gray-level emphasis, low gray-level zone emphasis, high gray-level zone emphasis, short-zone low gray-level emphasis, and coarseness. CONCLUSIONS: We have developed the acrylic beads phantom for texture analysis that could represent heterogeneous 18F-FDG distributions in various acquisition periods. Most texture features could discriminate homogeneous and heterogeneous 18F-FDG distributions in the beads phantom images.
Authors: Jianhua Yan; Jason Lim Chu-Shern; Hoi Yin Loi; Lih Kin Khor; Arvind K Sinha; Swee Tian Quek; Ivan W K Tham; David Townsend Journal: J Nucl Med Date: 2015-07-30 Impact factor: 10.057
Authors: Steven M. Larson; Yusuf Erdi; Timothy Akhurst; Madhu Mazumdar; Homer A. Macapinlac; Ronald D. Finn; Cecille Casilla; Melissa Fazzari; Neil Srivastava; Henry W.D. Yeung; John L. Humm; Jose Guillem; Robert Downey; Martin Karpeh; Alfred E. Cohen; Robert Ginsberg Journal: Clin Positron Imaging Date: 1999-05
Authors: Percy Lee; Dilani K Weerasuriya; Philip W Lavori; Andrew Quon; Wendy Hara; Peter G Maxim; Quynh-Thu Le; Heather A Wakelee; Jessica S Donington; Edward E Graves; Billy W Loo Journal: Int J Radiat Oncol Biol Phys Date: 2007-10-01 Impact factor: 7.038