Tetsuya Tsujikawa1, Tasmiah Rahman2, Makoto Yamamoto3, Shizuka Yamada3, Hideaki Tsuyoshi3, Yasushi Kiyono2, Hirohiko Kimura4, Yoshio Yoshida3, Hidehiko Okazawa2. 1. Biomedical Imaging Research Center, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui, 910-1193, Japan. awaji@u-fukui.ac.jp. 2. Biomedical Imaging Research Center, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui, 910-1193, Japan. 3. Department of Obstetrics and Gynecology, Faculty of Medical Sciences, University of Fukui, Fukui, Japan. 4. Department of Radiology, Faculty of Medical Sciences, University of Fukui, Fukui, Japan.
Abstract
OBJECTIVES: The aims of our study were to find the textural features on 18F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18F-FDG PET textural features in cervical cancer. METHODS: Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. RESULTS: Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. CONCLUSIONS: 18F-FDG PET textural features might reflect the differences in histological architecture between cervical cancer subtypes. PET radiomics approaches reveal the association between PET features and will be useful for finding a single feature or a combination of features leading to precise diagnoses, potential prognostic models, and effective therapeutic strategies.
OBJECTIVES: The aims of our study were to find the textural features on 18F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18F-FDG PET textural features in cervical cancer. METHODS: Eighty-three cervical cancerpatients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. RESULTS: Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. CONCLUSIONS: 18F-FDG PET textural features might reflect the differences in histological architecture between cervical cancer subtypes. PET radiomics approaches reveal the association between PET features and will be useful for finding a single feature or a combination of features leading to precise diagnoses, potential prognostic models, and effective therapeutic strategies.
Authors: A Sörensen; M Carles; H Bunea; L Majerus; C Stoykow; N H Nicolay; N E Wiedenmann; P Vaupel; P T Meyer; A L Grosu; M Mix Journal: Eur J Nucl Med Mol Imaging Date: 2019-11-26 Impact factor: 9.236
Authors: Angela Collarino; Giorgia Garganese; Simona M Fragomeni; Lenka M Pereira Arias-Bouda; Francesco P Ieria; Ronald Boellaard; Vittoria Rufini; Lioe-Fee de Geus-Oei; Giovanni Scambia; Renato A Valdés Olmos; Alessandro Giordano; Willem Grootjans; Floris H P van Velden Journal: J Nucl Med Date: 2018-07-20 Impact factor: 10.057
Authors: Marta Ferreira; Pierre Lovinfosse; Johanne Hermesse; Marjolein Decuypere; Caroline Rousseau; François Lucia; Ulrike Schick; Caroline Reinhold; Philippe Robin; Mathieu Hatt; Dimitris Visvikis; Claire Bernard; Ralph T H Leijenaar; Frédéric Kridelka; Philippe Lambin; Patrick E Meyer; Roland Hustinx Journal: Eur J Nucl Med Mol Imaging Date: 2021-03-26 Impact factor: 9.236