Literature DB >> 33353180

FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation.

Philipp Lohmann1,2, Mai A Elahmadawy1,3, Robin Gutsche1,4, Jan-Michael Werner5, Elena K Bauer5, Garry Ceccon5, Martin Kocher1,2,6, Christoph W Lerche1, Marion Rapp7, Gereon R Fink1,5, Nadim J Shah1,8,9, Karl-Josef Langen1,10,11, Norbert Galldiks1,5,6.   

Abstract

Currently, a reliable diagnostic test for differentiating pseudoprogression from early tumor progression is lacking. We explored the potential of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) radiomics for this clinically important task. Thirty-four patients (isocitrate dehydrogenase (IDH)-wildtype glioblastoma, 94%) with progressive magnetic resonance imaging (MRI) changes according to the Response Assessment in Neuro-Oncology (RANO) criteria within the first 12 weeks after completing temozolomide chemoradiation underwent a dynamic FET PET scan. Static and dynamic FET PET parameters were calculated. For radiomics analysis, the number of datasets was increased to 102 using data augmentation. After randomly assigning patients to a training and test dataset, 944 features were calculated on unfiltered and filtered images. The number of features for model generation was limited to four to avoid data overfitting. Eighteen patients were diagnosed with early tumor progression, and 16 patients had pseudoprogression. The FET PET radiomics model correctly diagnosed pseudoprogression in all test cohort patients (sensitivity, 100%; negative predictive value, 100%). In contrast, the diagnostic performance of the best FET PET parameter (TBRmax) was lower (sensitivity, 81%; negative predictive value, 80%). The results suggest that FET PET radiomics helps diagnose patients with pseudoprogression with a high diagnostic performance. Given the clinical significance, further studies are warranted.

Entities:  

Keywords:  amino acid PET; artificial intelligence; machine learning; textural features

Year:  2020        PMID: 33353180      PMCID: PMC7766151          DOI: 10.3390/cancers12123835

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  19 in total

1.  Radiomics Can Distinguish Pediatric Supratentorial Embryonal Tumors, High-Grade Gliomas, and Ependymomas.

Authors:  M Zhang; L Tam; J Wright; M Mohammadzadeh; M Han; E Chen; M Wagner; J Nemalka; H Lai; A Eghbal; C Y Ho; R M Lober; S H Cheshier; N A Vitanza; G A Grant; L M Prolo; K W Yeom; A Jaju
Journal:  AJNR Am J Neuroradiol       Date:  2022-03-31       Impact factor: 3.825

2.  Machine Assist for Pediatric Posterior Fossa Tumor Diagnosis: A Multinational Study.

Authors:  Michael Zhang; Samuel W Wong; Jason N Wright; Sebastian Toescu; Maryam Mohammadzadeh; Michelle Han; Seth Lummus; Matthias W Wagner; Derek Yecies; Hollie Lai; Azam Eghbal; Alireza Radmanesh; Jordan Nemelka; Stephen Harward; Michael Malinzak; Suzanne Laughlin; Sebastien Perreault; Kristina R M Braun; Arastoo Vossough; Tina Poussaint; Robert Goetti; Birgit Ertl-Wagner; Chang Y Ho; Ozgur Oztekin; Vijay Ramaswamy; Kshitij Mankad; Nicholas A Vitanza; Samuel H Cheshier; Mourad Said; Kristian Aquilina; Eric Thompson; Alok Jaju; Gerald A Grant; Robert M Lober; Kristen W Yeom
Journal:  Neurosurgery       Date:  2021-10-13       Impact factor: 5.315

Review 3.  Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.

Authors:  David Morland; Elizabeth Katherine Anna Triumbari; Luca Boldrini; Roberto Gatta; Daniele Pizzuto; Salvatore Annunziata
Journal:  Diagnostics (Basel)       Date:  2022-05-27

Review 4.  Standard clinical approaches and emerging modalities for glioblastoma imaging.

Authors:  Joshua D Bernstock; Sam E Gary; Neil Klinger; Pablo A Valdes; Walid Ibn Essayed; Hannah E Olsen; Gustavo Chagoya; Galal Elsayed; Daisuke Yamashita; Patrick Schuss; Florian A Gessler; Pier Paolo Peruzzi; Asim K Bag; Gregory K Friedman
Journal:  Neurooncol Adv       Date:  2022-05-26

Review 5.  Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma.

Authors:  Sanjeev Chawla; Sultan Bukhari; Omar M Afridi; Sumei Wang; Santosh K Yadav; Hamed Akbari; Gaurav Verma; Kavindra Nath; Mohammad Haris; Stephen Bagley; Christos Davatzikos; Laurie A Loevner; Suyash Mohan
Journal:  NMR Biomed       Date:  2022-03-15       Impact factor: 4.478

6.  TERT-Promoter Mutational Status in Glioblastoma - Is There an Association With Amino Acid Uptake on Dynamic 18F-FET PET?

Authors:  Marcus Unterrainer; Viktoria Ruf; Katharina von Rohr; Bogdana Suchorska; Lena Maria Mittlmeier; Leonie Beyer; Matthias Brendel; Vera Wenter; Wolfgang G Kunz; Peter Bartenstein; Jochen Herms; Maximilian Niyazi; Jörg C Tonn; Nathalie Lisa Albert
Journal:  Front Oncol       Date:  2021-04-27       Impact factor: 6.244

7.  Evaluation of FET PET Radiomics Feature Repeatability in Glioma Patients.

Authors:  Robin Gutsche; Jürgen Scheins; Martin Kocher; Khaled Bousabarah; Gereon R Fink; Nadim J Shah; Karl-Josef Langen; Norbert Galldiks; Philipp Lohmann
Journal:  Cancers (Basel)       Date:  2021-02-05       Impact factor: 6.639

8.  World Cancer Day 2021 - Perspectives in Pediatric and Adult Neuro-Oncology.

Authors:  Erik P Sulman; David D Eisenstat
Journal:  Front Oncol       Date:  2021-05-10       Impact factor: 6.244

9.  Diagnostic Accuracy of PET for Differentiating True Glioma Progression From Post Treatment-Related Changes: A Systematic Review and Meta-Analysis.

Authors:  Meng Cui; Rocío Isabel Zorrilla-Veloz; Jian Hu; Bing Guan; Xiaodong Ma
Journal:  Front Neurol       Date:  2021-05-20       Impact factor: 4.003

Review 10.  Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.

Authors:  Andra V Krauze; Kevin Camphausen
Journal:  Int J Mol Sci       Date:  2021-12-10       Impact factor: 5.923

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