Literature DB >> 26219871

Textural analysis of pre-therapeutic [18F]-FET-PET and its correlation with tumor grade and patient survival in high-grade gliomas.

Thomas Pyka1, Jens Gempt2, Daniela Hiob3, Florian Ringel2, Jürgen Schlegel4, Stefanie Bette5, Hans-Jürgen Wester3, Bernhard Meyer2, Stefan Förster3,6.   

Abstract

PURPOSE: Amino acid positron emission tomography (PET) with [18F]-fluoroethyl-L-tyrosine (FET) is well established in the diagnostic work-up of malignant brain tumors. Analysis of FET-PET data using tumor-to-background ratios (TBR) has been shown to be highly valuable for the detection of viable hypermetabolic brain tumor tissue; however, it has not proven equally useful for tumor grading. Recently, textural features in 18-fluorodeoxyglucose-PET have been proposed as a method to quantify the heterogeneity of glucose metabolism in a variety of tumor entities. Herein we evaluate whether textural FET-PET features are of utility for grading and prognostication in patients with high-grade gliomas.
METHODS: One hundred thirteen patients (70 men, 43 women) with histologically proven high-grade gliomas were included in this retrospective study. All patients received static FET-PET scans prior to first-line therapy. TBR (max and mean), volumetric parameters and textural parameters based on gray-level neighborhood difference matrices were derived from static FET-PET images. Receiver operating characteristic (ROC) and discriminant function analyses were used to assess the value for tumor grading. Kaplan-Meier curves and univariate and multivariate Cox regression were employed for analysis of progression-free and overall survival.
RESULTS: All FET-PET textural parameters showed the ability to differentiate between World Health Organization (WHO) grade III and IV tumors (p < 0.001; AUC 0.775). Further improvement in discriminatory power was possible through a combination of texture and metabolic tumor volume, classifying 85 % of tumors correctly (AUC 0.830). TBR and volumetric parameters alone were correlated with tumor grade, but showed lower AUC values (0.644 and 0.710, respectively). Furthermore, a correlation of FET-PET texture but not TBR was shown with patient PFS and OS, proving significant in multivariate analysis as well. Volumetric parameters were predictive for OS, but this correlation did not hold in multivariate analysis.
CONCLUSIONS: Determination of uptake heterogeneity in pre-therapeutic FET-PET using textural features proved valuable for the (sub-)grading of high-grade glioma as well as prediction of tumor progression and patient survival, and showed improved performance compared to standard parameters such as TBR and tumor volume. Our results underscore the importance of intratumoral heterogeneity in the biology of high-grade glial cell tumors and may contribute to individual therapy planning in the future, although they must be confirmed in prospective studies before incorporation into clinical routine.

Entities:  

Keywords:  FET-PET; HGG; Textural analysis

Mesh:

Substances:

Year:  2015        PMID: 26219871     DOI: 10.1007/s00259-015-3140-4

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


  28 in total

1.  MRI-suspected low-grade glioma: is there a need to perform dynamic FET PET?

Authors:  Nathalie L Jansen; Vera Graute; Lena Armbruster; Bogdana Suchorska; Juergen Lutz; Sabina Eigenbrod; Paul Cumming; Peter Bartenstein; Jörg-Christian Tonn; Friedrich Wilhelm Kreth; Christian la Fougère
Journal:  Eur J Nucl Med Mol Imaging       Date:  2012-04-11       Impact factor: 9.236

2.  Prediction of glioma recurrence using dynamic ¹⁸F-fluoroethyltyrosine PET.

Authors:  T Pyka; J Gempt; F Ringel; S Hüttinger; S van Marwick; S Nekolla; H-J Wester; M Schwaiger; S Förster
Journal:  AJNR Am J Neuroradiol       Date:  2014-06-12       Impact factor: 3.825

3.  Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.

Authors:  Balaji Ganeshan; Vicky Goh; Henry C Mandeville; Quan Sing Ng; Peter J Hoskin; Kenneth A Miles
Journal:  Radiology       Date:  2012-11-20       Impact factor: 11.105

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

Authors:  Florent Tixier; Mathieu Hatt; Clemence Valla; Vincent Fleury; Corinne Lamour; Safaa Ezzouhri; Pierre Ingrand; Remy Perdrisot; Dimitris Visvikis; Catherine Cheze Le Rest
Journal:  J Nucl Med       Date:  2014-06-05       Impact factor: 10.057

5.  Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer.

Authors:  Florent Tixier; Catherine Cheze Le Rest; Mathieu Hatt; Nidal Albarghach; Olivier Pradier; Jean-Philippe Metges; Laurent Corcos; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2011-02-14       Impact factor: 10.057

6.  FET PET for the evaluation of untreated gliomas: correlation of FET uptake and uptake kinetics with tumour grading.

Authors:  Gabriele Pöpperl; Friedrich W Kreth; Jan H Mehrkens; Jochen Herms; Klaus Seelos; Walter Koch; Franz J Gildehaus; Hans A Kretzschmar; Jörg C Tonn; Klaus Tatsch
Journal:  Eur J Nucl Med Mol Imaging       Date:  2007-09-01       Impact factor: 9.236

7.  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

Review 8.  Chemotherapy in low-grade gliomas.

Authors:  Aurélien Viaccoz; Alain Lekoubou; François Ducray
Journal:  Curr Opin Oncol       Date:  2012-11       Impact factor: 3.645

9.  MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set.

Authors:  David A Gutman; Lee A D Cooper; Scott N Hwang; Chad A Holder; Jingjing Gao; Tarun D Aurora; William D Dunn; Lisa Scarpace; Tom Mikkelsen; Rajan Jain; Max Wintermark; Manal Jilwan; Prashant Raghavan; Erich Huang; Robert J Clifford; Pattanasak Mongkolwat; Vladimir Kleper; John Freymann; Justin Kirby; Pascal O Zinn; Carlos S Moreno; Carl Jaffe; Rivka Colen; Daniel L Rubin; Joel Saltz; Adam Flanders; Daniel J Brat
Journal:  Radiology       Date:  2013-02-07       Impact factor: 11.105

Review 10.  The 2007 WHO classification of tumours of the central nervous system.

Authors:  David N Louis; Hiroko Ohgaki; Otmar D Wiestler; Webster K Cavenee; Peter C Burger; Anne Jouvet; Bernd W Scheithauer; Paul Kleihues
Journal:  Acta Neuropathol       Date:  2007-07-06       Impact factor: 17.088

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  27 in total

1.  Integrated analysis of dynamic FET PET/CT parameters, histology, and methylation profiling of 44 gliomas.

Authors:  Manuel Röhrich; Kristin Huang; Daniel Schrimpf; Nathalie L Albert; Thomas Hielscher; Andreas von Deimling; Ulrich Schüller; Antonia Dimitrakopoulou-Strauss; Uwe Haberkorn
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-05-07       Impact factor: 9.236

Review 2.  "Radio-oncomics" : The potential of radiomics in radiation oncology.

Authors:  Jan Caspar Peeken; Fridtjof Nüsslin; Stephanie E Combs
Journal:  Strahlenther Onkol       Date:  2017-07-07       Impact factor: 3.621

Review 3.  Radiomics in Oncological PET/CT: Clinical Applications.

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

Review 4.  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

Review 5.  Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

Authors:  Faiq Shaikh; Benjamin Franc; Erastus Allen; Evis Sala; Omer Awan; Kenneth Hendrata; Safwan Halabi; Sohaib Mohiuddin; Sana Malik; Dexter Hadley; Rasu Shrestha
Journal:  J Am Coll Radiol       Date:  2018-02-01       Impact factor: 5.532

6.  Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase 18F-FET PET accuracy without dynamic scans.

Authors:  Philipp Lohmann; Gabriele Stoffels; Garry Ceccon; Marion Rapp; Michael Sabel; Christian P Filss; Marcel A Kamp; Carina Stegmayr; Bernd Neumaier; Nadim J Shah; Karl-Josef Langen; Norbert Galldiks
Journal:  Eur Radiol       Date:  2016-11-16       Impact factor: 5.315

7.  FDG PET/CT radiomics for predicting the outcome of locally advanced rectal cancer.

Authors:  Pierre Lovinfosse; Marc Polus; Daniel Van Daele; Philippe Martinive; Frédéric Daenen; Mathieu Hatt; Dimitris Visvikis; Benjamin Koopmansch; Frédéric Lambert; Carla Coimbra; Laurence Seidel; Adelin Albert; Philippe Delvenne; Roland Hustinx
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-10-18       Impact factor: 9.236

8.  Assessment of tumor heterogeneity in treatment-naïve adrenocortical cancer patients using (18)F-FDG positron emission tomography.

Authors:  Rudolf A Werner; Matthias Kroiss; Masatoyo Nakajo; Dirk O Mügge; Stefanie Hahner; Martin Fassnacht; Andreas Schirbel; Christina Bluemel; Takahiro Higuchi; Laszló Papp; Norbert Zsótér; Andreas K Buck; Ralph A Bundschuh; Constantin Lapa
Journal:  Endocrine       Date:  2016-05-02       Impact factor: 3.633

9.  Heterogeneous parameters based on 18F-FET PET imaging can non-invasively predict tumor grade and isocitrate dehydrogenase gene 1 mutation in untreated gliomas.

Authors:  Tao Hua; Weiyan Zhou; Zhirui Zhou; Yihui Guan; Ming Li
Journal:  Quant Imaging Med Surg       Date:  2021-01

10.  Brain Tumor Imaging: Applications of Artificial Intelligence.

Authors:  Muhammad Afridi; Abhi Jain; Mariam Aboian; Seyedmehdi Payabvash
Journal:  Semin Ultrasound CT MR       Date:  2022-02-11       Impact factor: 1.875

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