Literature DB >> 29182373

Texture analysis of 18F-FDG PET/CT for grading thymic epithelial tumours: usefulness of combining SUV and texture parameters.

Masatoyo Nakajo1, Megumi Jinguji1, Tetsuya Shinaji2, Masayuki Nakajo3, Masaya Aoki4, Atsushi Tani1, Masami Sato4, Takashi Yoshiura1.   

Abstract

OBJECTIVE: To retrospectively investigate the standardized uptake value (SUV)-related and heterogeneous texture parameters individually and in combination for differentiating between low- and high-risk 18Fluorone-fludeoxyglucose (18F-FDG)-avid thymic epithelial tumours (TETs) with positron emission tomography (PET)/CT.
METHODS: SUV-related and 6 texture parameters (entropy, homogeneity, dissimilarity, intensity variability, size-zone variability and zone percentage) were compared between 11 low-risk and 23 high-risk TETs (metabolic tumour volume >10.0 cm3 and SUV ≥2.5). Diagnostic performance was evaluated by receiver operating characteristic analysis. The diagnostic value of combining SUV and texture parameters was examined by a scoring system.
RESULTS: High-risk TETs were significantly higher in SUVmax (p = 0.022), entropy (p = 0.038), intensity variability (p = 0.041) and size-zone variability (p = 0.045) than low-risk TETs. Diagnostic accuracies of these 4 parameters, dissimilarity and zone percentage which also showed significance in receiver operating characteristic analysis ranged between 64.7 and 73.5% without significant differences in AUC (range; 0.71 to 0.75) (p ≥ 0.05 each). Each parameter was scored as 0 (negative for high-risk) or 1 (positive for high-risk) according to each threshold criterion, then scores were summed [0 or 1 for low-risk TETs (median; 1); ≥2 for high-risk TETs (median; 4)]. The sensitivity, specificity and accuracy of detecting high-risk TETs were 100, 81.8 and 94.1%, respectively, with an AUC of 0.99.
CONCLUSION: The diagnostic performances of individual SUVmax and texture parameters were relatively low. However, combining these parameters can significantly increase diagnostic performance when differentiating between relatively large low- and high-risk 18F-FDG-avid TETs. Advances in knowledge: Combined use of SUVmax and texture parameters can significantly increase the diagnostic performance when differentiating between low- and high-risk TETs.

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Year:  2018        PMID: 29182373      PMCID: PMC5965478          DOI: 10.1259/bjr.20170546

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  40 in total

1.  Texture analysis of FDG PET/CT for differentiating between FDG-avid benign and metastatic adrenal tumors: efficacy of combining SUV and texture parameters.

Authors:  Masatoyo Nakajo; Megumi Jinguji; Masayuki Nakajo; Tetsuya Shinaji; Yoshiaki Nakabeppu; Yoshihiko Fukukura; Takashi Yoshiura
Journal:  Abdom Radiol (NY)       Date:  2017-12

2.  MR imaging of thymic epithelial tumors: correlation with World Health Organization classification.

Authors:  Atsuo Inoue; Noriyuki Tomiyama; Kiminori Fujimoto; Junko Sadohara; Itsuko Nakamichi; Yasuhiko Tomita; Katsuyuki Aozasa; Mitsuko Tsubamoto; Sachiko Murai; Javzandulam Natsag; Hiromitsu Sumikawa; Naoki Mihara; Osamu Honda; Seiki Hamada; Takeshi Johkoh; Hironobu Nakamura
Journal:  Radiat Med       Date:  2006-04

3.  Zone-size nonuniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer.

Authors:  Nai-Ming Cheng; Yu-Hua Dean Fang; Li-yu Lee; Joseph Tung-Chieh Chang; Din-Li Tsan; Shu-Hang Ng; Hung-Ming Wang; Chun-Ta Liao; Lan-Yan Yang; Ching-Han Hsu; Tzu-Chen Yen
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-10-23       Impact factor: 9.236

4.  ¹⁸FDG PET for grading malignancy in thymic epithelial tumors: significant differences in ¹⁸FDG uptake and expression of glucose transporter-1 and hexokinase II between low and high-risk tumors: preliminary study.

Authors:  Masatoyo Nakajo; Yoriko Kajiya; Atsushi Tani; Satoshi Yoneda; Hiroshi Shirahama; Michiyo Higashi; Masayuki Nakajo
Journal:  Eur J Radiol       Date:  2010-08-31       Impact factor: 3.528

5.  18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort.

Authors:  Mathieu Hatt; Mohamed Majdoub; Martin Vallières; Florent Tixier; Catherine Cheze Le Rest; David Groheux; Elif Hindié; Antoine Martineau; Olivier Pradier; Roland Hustinx; Remy Perdrisot; Remy Guillevin; Issam El Naqa; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2014-12-11       Impact factor: 10.057

6.  New WHO histologic classification predicts prognosis of thymic epithelial tumors: a clinicopathologic study of 200 thymoma cases from China.

Authors:  Gang Chen; Alexander Marx; Wen-Hu Chen; Jiang Yong; Bernhard Puppe; Philipp Stroebel; Hans Konrad Mueller-Hermelink
Journal:  Cancer       Date:  2002-07-15       Impact factor: 6.860

Review 7.  Thymoma and thymic carcinoma.

Authors:  Federico Venuta; Marco Anile; Daniele Diso; Domenico Vitolo; Erino A Rendina; Tiziano De Giacomo; Federico Francioni; Giorgio Furio Coloni
Journal:  Eur J Cardiothorac Surg       Date:  2009-07-16       Impact factor: 4.191

8.  Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy?

Authors:  Gary J R Cook; Connie Yip; Muhammad Siddique; Vicky Goh; Sugama Chicklore; Arunabha Roy; Paul Marsden; Shahreen Ahmad; David Landau
Journal:  J Nucl Med       Date:  2012-11-30       Impact factor: 10.057

9.  Does CT of thymic epithelial tumors enable us to differentiate histologic subtypes and predict prognosis?

Authors:  Yeon Joo Jeong; Kyung Soo Lee; Jhingook Kim; Young Mok Shim; Jungho Han; O Jung Kwon
Journal:  AJR Am J Roentgenol       Date:  2004-08       Impact factor: 3.959

10.  Utility of 18FDG-PET for differentiating the grade of malignancy in thymic epithelial tumors.

Authors:  Masahiro Endo; Kazuo Nakagawa; Yasuhisa Ohde; Takehiro Okumura; Haruhiko Kondo; Satoshi Igawa; Yukiko Nakamura; Asuka Tsuya; Haruyasu Murakami; Toshiaki Takahashi; Nobuyuki Yamamoto; Ichiro Ito; Toru Kameya
Journal:  Lung Cancer       Date:  2008-03-04       Impact factor: 5.705

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  9 in total

1.  Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM staging.

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Review 2.  Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.

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3.  The role of MRI-based texture analysis to predict the severity of brain injury in neonates with perinatal asphyxia.

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Journal:  Br J Radiol       Date:  2022-01-27       Impact factor: 3.629

4.  Predicting pathological subtypes and stages of thymic epithelial tumors using DWI: value of combining ADC and texture parameters.

Authors:  Bo Li; Yong-Kang Xin; Gang Xiao; Gang-Feng Li; Shi-Jun Duan; Yu Han; Xiu-Long Feng; Wei-Qiang Yan; Wei-Cheng Rong; Shu-Mei Wang; Yu-Chuan Hu; Guang-Bin Cui
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5.  Computed tomography radiomics for the prediction of thymic epithelial tumor histology, TNM stage and myasthenia gravis.

Authors:  Christian Blüthgen; Miriam Patella; André Euler; Bettina Baessler; Katharina Martini; Jochen von Spiczak; Didier Schneiter; Isabelle Opitz; Thomas Frauenfelder
Journal:  PLoS One       Date:  2021-12-20       Impact factor: 3.240

6.  18F-FDG texture analysis predicts the pathological Fuhrman nuclear grade of clear cell renal cell carcinoma.

Authors:  Linhan Zhang; Hongyue Zhao; Huijie Jiang; Hong Zhao; Wei Han; Mengjiao Wang; Peng Fu
Journal:  Abdom Radiol (NY)       Date:  2021-08-28

Review 7.  Current Roles of PET/CT in Thymic Epithelial Tumours: Which Evidences and Which Prospects? A Pictorial Review.

Authors:  Filippo Lococo; Marco Chiappetta; Elizabeth Katherine Anna Triumbari; Jessica Evangelista; Maria Teresa Congedo; Daniele Antonio Pizzuto; Debora Brascia; Giuseppe Marulli; Salvatore Annunziata; Stefano Margaritora
Journal:  Cancers (Basel)       Date:  2021-12-03       Impact factor: 6.639

8.  The impact of radiomics in predicting oncologic behavior of thymic epithelial tumors.

Authors:  Yoshiyuki Ozawa; Masaki Hara; Yuta Shibamoto
Journal:  Mediastinum       Date:  2019-06-21

9.  Synergistic impact of motion and acquisition/reconstruction parameters on 18 F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

Authors:  Seyyed Ali Hosseini; Isaac Shiri; Ghasem Hajianfar; Bahador Bahadorzadeh; Pardis Ghafarian; Habib Zaidi; Mohammad Reza Ay
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