Literature DB >> 24904113

Visual versus quantitative assessment of intratumor 18F-FDG PET uptake heterogeneity: prognostic value in non-small cell lung cancer.

Florent Tixier1, Mathieu Hatt2, Clemence Valla3, Vincent Fleury3, Corinne Lamour4, Safaa Ezzouhri3, Pierre Ingrand5, Remy Perdrisot3, Dimitris Visvikis6, Catherine Cheze Le Rest3.   

Abstract

UNLABELLED: The goal of this study was to compare visual assessment of intratumor (18)F-FDG PET uptake distribution with a textural-features (TF) automated quantification and to establish their respective prognostic value in non-small cell lung cancer (NSCLC).
METHODS: The study retrospectively included 102 consecutive patients. Only primary tumors were considered. Intratumor heterogeneity was visually scored (3-level scale [Hvisu]) by 2 nuclear medicine physicians. Tumor volumes were automatically delineated, and heterogeneity was quantified with TF. Mean and maximum standardized uptake value were also included. Visual interobserver agreement and correlations with quantitative assessment were evaluated using the κ test and Spearman rank (ρ) coefficient, respectively. Association with overall survival and recurrence-free survival was investigated using the Kaplan-Meier method and Cox regression models.
RESULTS: Moderate correlations (0.4 < ρ < 0.6) between TF parameters and Hvisu were observed. Interobserver agreement for Hvisu was moderate (κ = 0.64, discrepancies in 27% of the cases). High standardized uptake value, large metabolic volumes, and high heterogeneity according to TF were associated with poorer overall survival and recurrence-free survival and remained an independent prognostic factor of overall survival with respect to clinical variables.
CONCLUSION: Quantification of (18)F-FDG uptake heterogeneity in NSCLC through TF was correlated with visual assessment by experts. However, TF also constitutes an objective heterogeneity quantification, with reduced interobserver variability, and independent prognostic value potentially useful for patient stratification and management.
© 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Entities:  

Keywords:  18FDG-PET/CT; NSCLC; heterogeneity; prognosis; textural features

Mesh:

Substances:

Year:  2014        PMID: 24904113     DOI: 10.2967/jnumed.113.133389

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  57 in total

1.  A Pilot Study of Texture Analysis of Primary Tumor [18F]FDG Uptake to Predict Recurrence in Surgically Treated Patients with Non-small Cell Lung Cancer.

Authors:  Masatoyo Nakajo; Megumi Jinguji; Tetsuya Shinaji; Masaya Aoki; Atsushi Tani; Yoshiaki Nakabeppu; Masayuki Nakajo; Masami Sato; Takashi Yoshiura
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

2.  Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non-Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235.

Authors:  Nitin Ohri; Fenghai Duan; Bradley S Snyder; Bo Wei; Mitchell Machtay; Abass Alavi; Barry A Siegel; Douglas W Johnson; Jeffrey D Bradley; Albert DeNittis; Maria Werner-Wasik; Issam El Naqa
Journal:  J Nucl Med       Date:  2016-02-11       Impact factor: 10.057

Review 3.  Towards precision medicine: from quantitative imaging to radiomics.

Authors:  U Rajendra Acharya; Yuki Hagiwara; Vidya K Sudarshan; Wai Yee Chan; Kwan Hoong Ng
Journal:  J Zhejiang Univ Sci B       Date:  2018 Jan.       Impact factor: 3.066

4.  Stage III Non-Small Cell Lung Cancer: Prognostic Value of FDG PET Quantitative Imaging Features Combined with Clinical Prognostic Factors.

Authors:  David V Fried; Osama Mawlawi; Lifei Zhang; Xenia Fave; Shouhao Zhou; Geoffrey Ibbott; Zhongxing Liao; Laurence E Court
Journal:  Radiology       Date:  2015-07-15       Impact factor: 11.105

5.  Heterogeneity in Metastatic Breast Cancer 18F-Fluoroestradiol Uptake: Clinically Actionable, Biologically Illuminating?

Authors:  Brenda F Kurland; Steffi Oesterreich
Journal:  J Nucl Med       Date:  2018-06-14       Impact factor: 10.057

Review 6.  Radiomics in Oncological PET/CT: Clinical Applications.

Authors:  Jeong Won Lee; Sang Mi Lee
Journal:  Nucl Med Mol Imaging       Date:  2017-10-20

Review 7.  Characterization of PET/CT images using texture analysis: the past, the present… any future?

Authors:  Mathieu Hatt; Florent Tixier; Larry Pierce; Paul E Kinahan; Catherine Cheze Le Rest; Dimitris Visvikis
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-06-06       Impact factor: 9.236

8.  Robustness of Radiomic Features in [11C]Choline and [18F]FDG PET/CT Imaging of Nasopharyngeal Carcinoma: Impact of Segmentation and Discretization.

Authors:  Lijun Lu; Wenbing Lv; Jun Jiang; Jianhua Ma; Qianjin Feng; Arman Rahmim; Wufan Chen
Journal:  Mol Imaging Biol       Date:  2016-12       Impact factor: 3.488

Review 9.  Clinical applications of textural analysis in non-small cell lung cancer.

Authors:  Iain Phillips; Mazhar Ajaz; Veni Ezhil; Vineet Prakash; Sheaka Alobaidli; Sarah J McQuaid; Christopher South; James Scuffham; Andrew Nisbet; Philip Evans
Journal:  Br J Radiol       Date:  2017-10-27       Impact factor: 3.039

Review 10.  PET in the management of locally advanced and metastatic NSCLC.

Authors:  Willem Grootjans; Lioe-Fee de Geus-Oei; Esther G C Troost; Eric P Visser; Wim J G Oyen; Johan Bussink
Journal:  Nat Rev Clin Oncol       Date:  2015-04-28       Impact factor: 66.675

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