Literature DB >> 26830299

FDG PET/CT texture analysis for predicting the outcome of lung cancer treated by stereotactic body radiation therapy.

Pierre Lovinfosse1, Zsolt Levente Janvary2, Philippe Coucke2, Sébastien Jodogne3, Claire Bernard4, Mathieu Hatt5, Dimitris Visvikis5, Nicolas Jansen2, Bernard Duysinx6, Roland Hustinx4.   

Abstract

INTRODUCTION: With (18)F-FDG PET/CT, tumor uptake intensity and heterogeneity have been associated with outcome in several cancers. This study aimed at investigating whether (18)F-FDG uptake intensity, volume or heterogeneity could predict the outcome in patients with non-small cell lung cancers (NSCLC) treated by stereotactic body radiation therapy (SBRT).
METHODS: Sixty-three patients with NSCLC treated by SBRT underwent a (18)F-FDG PET/CT before treatment. Maximum and mean standard uptake value (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), as well as 13 global, local and regional textural features were analysed. The predictive value of these parameters, along with clinical features, was assessed using univariate and multivariate analysis for overall survival (OS), disease-specific survival (DSS) and disease-free survival (DFS). Cutoff values were obtained using logistic regression analysis, and survivals were compared using Kaplan-Meier analysis.
RESULTS: The median follow-up period was 27.1 months for the entire cohort and 32.1 months for the surviving patients. At the end of the study, 25 patients had local and/or distant recurrence including 12 who died because of the cancer progression. None of the clinical variables was predictive of the outcome, except age, which was associated with DFS (HR 1.1, P = 0.002). None of the (18)F-FDG PET/CT or clinical parameters, except gender, were associated with OS. The univariate analysis showed that only dissimilarity (D) was associated with DSS (HR = 0.822, P = 0.037), and that several metabolic measurements were associated with DFS. In multivariate analysis, only dissimilarity was significantly associated with DSS (HR = 0.822, P = 0.037) and with DFS (HR = 0.834, P < 0.01).
CONCLUSION: The textural feature dissimilarity measured on the baseline (18)F-FDG PET/CT appears to be a strong independent predictor of the outcome in patients with NSCLC treated by SBRT. This may help selecting patients who may benefit from closer monitoring and therapeutic optimization.

Entities:  

Keywords:  18F-FDG PET/CT; Heterogeneity; Non-small cell lung cancer; Prognostic factor; Stereotactic body radiation therapy; Textural analysis

Mesh:

Substances:

Year:  2016        PMID: 26830299     DOI: 10.1007/s00259-016-3314-8

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


  40 in total

1.  Volume-based parameters measured by using FDG PET/CT in patients with stage I NSCLC treated with stereotactic body radiation therapy: prognostic value.

Authors:  Yoko Satoh; Hiroshi Onishi; Atsushi Nambu; Tsutomu Araki
Journal:  Radiology       Date:  2013-10-28       Impact factor: 11.105

2.  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

3.  Tumor Treatment Response Based on Visual and Quantitative Changes in Global Tumor Glycolysis Using PET-FDG Imaging. The Visual Response Score and the Change in Total Lesion Glycolysis.

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

4.  Stereotactic radiotherapy with real-time tumor tracking for non-small cell lung cancer: clinical outcome.

Authors:  Noëlle C van der Voort van Zyp; Jean-Briac Prévost; Mischa S Hoogeman; John Praag; Bronno van der Holt; Peter C Levendag; Robertus J van Klaveren; Peter Pattynama; Joost J Nuyttens
Journal:  Radiother Oncol       Date:  2009-03-16       Impact factor: 6.280

5.  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

6.  Outcomes after stereotactic lung radiotherapy or wedge resection for stage I non-small-cell lung cancer.

Authors:  Inga S Grills; Victor S Mangona; Robert Welsh; Gary Chmielewski; Erika McInerney; Shannon Martin; Jennifer Wloch; Hong Ye; Larry L Kestin
Journal:  J Clin Oncol       Date:  2010-01-11       Impact factor: 44.544

7.  Prognostic value of metabolic tumor volume and total lesion glycolysis from ¹⁸F-FDG PET/CT in patients undergoing stereotactic body radiation therapy for stage I non-small-cell lung cancer.

Authors:  Charles C Vu; Robert Matthews; Bong Kim; Dinko Franceschi; Thomas V Bilfinger; William H Moore
Journal:  Nucl Med Commun       Date:  2013-10       Impact factor: 1.690

Review 8.  Noninvasive staging of non-small cell lung cancer: a review of the current evidence.

Authors:  Eric M Toloza; Linda Harpole; Douglas C McCrory
Journal:  Chest       Date:  2003-01       Impact factor: 9.410

9.  Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012.

Authors:  Jacques Ferlay; Isabelle Soerjomataram; Rajesh Dikshit; Sultan Eser; Colin Mathers; Marise Rebelo; Donald Maxwell Parkin; David Forman; Freddie Bray
Journal:  Int J Cancer       Date:  2014-10-09       Impact factor: 7.396

10.  Pretreatment SUVmax predicts progression-free survival in early-stage non-small cell lung cancer treated with stereotactic body radiation therapy.

Authors:  Zachary D Horne; David A Clump; John A Vargo; Samir Shah; Sushil Beriwal; Steven A Burton; Annette E Quinn; Matthew J Schuchert; Rodney J Landreneau; Neil A Christie; James D Luketich; Dwight E Heron
Journal:  Radiat Oncol       Date:  2014-01-30       Impact factor: 3.481

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  51 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.  Prognostic value of 18F-FDG PET/CT with texture analysis in patients with rectal cancer treated by surgery.

Authors:  Masatoshi Hotta; Ryogo Minamimoto; Yoshimasa Gohda; Kenta Miwa; Kensuke Otani; Tomomichi Kiyomatsu; Hideaki Yano
Journal:  Ann Nucl Med       Date:  2021-05-04       Impact factor: 2.668

3.  A pilot study using kernelled support tensor machine for distant failure prediction in lung SBRT.

Authors:  Shulong Li; Ning Yang; Bin Li; Zhiguo Zhou; Hongxia Hao; Michael R Folkert; Puneeth Iyengar; Kenneth Westover; Hak Choy; Robert Timmerman; Steve Jiang; Jing Wang
Journal:  Med Image Anal       Date:  2018-09-15       Impact factor: 8.545

4.  Early PET-CT After Stereotactic Radiotherapy for Stage 1 Non-small Cell Lung Carcinoma Is Predictive of Local Control.

Authors:  Marguerite Tyran; Nathalie Charrier; Julien Darreon; Anne Madroszyk; Agnes Tallet; Naji Salem
Journal:  In Vivo       Date:  2018 Jan-Feb       Impact factor: 2.155

Review 5.  Radiomics in Oncological PET/CT: Clinical Applications.

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

Review 6.  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

7.  18F-FDG PET/CT heterogeneity quantification through textural features in the era of harmonisation programs: a focus on lung cancer.

Authors:  Charline Lasnon; Mohamed Majdoub; Brice Lavigne; Pascal Do; Jeannick Madelaine; Dimitris Visvikis; Mathieu Hatt; Nicolas Aide
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-06-21       Impact factor: 9.236

8.  Robustness versus disease differentiation when varying parameter settings in radiomics features: application to nasopharyngeal PET/CT.

Authors:  Wenbing Lv; Qingyu Yuan; Quanshi Wang; Jianhua Ma; Jun Jiang; Wei Yang; Qianjin Feng; Wufan Chen; Arman Rahmim; Lijun Lu
Journal:  Eur Radiol       Date:  2018-03-08       Impact factor: 5.315

9.  Unsupervised machine learning of radiomic features for predicting treatment response and overall survival of early stage non-small cell lung cancer patients treated with stereotactic body radiation therapy.

Authors:  Hongming Li; Maya Galperin-Aizenberg; Daniel Pryma; Charles B Simone; Yong Fan
Journal:  Radiother Oncol       Date:  2018-07-04       Impact factor: 6.280

Review 10.  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

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