Literature DB >> 31084772

PET-Derived Quantitative Metrics for Response and Prognosis in Lymphoma.

Lale Kostakoglu1, Stéphane Chauvie2.   

Abstract

Lymphoma is a potentially curable disease; however, the clinical challenge lies in further improvement of outcomes. PET with fludeoxyglucose is an effective imaging tool. PET-derived quantitative metrics have raised significant interest to be used as a prognostic factor to complement clinical parameters for treatment decisions. The most optimized use of these quantitative PET metrics, however, will be possible with the standardization of imaging procedures. In this article, we review the technical and methodological considerations related to PET-derived quantitative metrics, and the relevant published data to emphasize the potential value of these metrics in patient prognosis and treatment response in lymphoma.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  FDG-PET; Lymphoma; Prognosis; Quantitative metrics; Response

Mesh：

Substances：

Year:  2019        PMID： 31084772     DOI： 10.1016/j.cpet.2019.03.002

Source DB:  PubMed          Journal:  PET Clin        ISSN： 1556-8598


  7 in total

Review 1.  Artificial Intelligence in Lymphoma PET Imaging:: A Scoping Review (Current Trends and Future Directions).

Authors:  Navid Hasani; Sriram S Paravastu; Faraz Farhadi; Fereshteh Yousefirizi; Michael A Morris; Arman Rahmim; Mark Roschewski; Ronald M Summers; Babak Saboury
Journal:  PET Clin       Date:  2022-01

2.  Two-Year Event-Free Survival Prediction in DLBCL Patients Based on In Vivo Radiomics and Clinical Parameters.

Authors:  Zsombor Ritter; László Papp; Katalin Zámbó; Zoltán Tóth; Dániel Dezső; Dániel Sándor Veres; Domokos Máthé; Ferenc Budán; Éva Karádi; Anett Balikó; László Pajor; Árpád Szomor; Erzsébet Schmidt; Hussain Alizadeh
Journal:  Front Oncol       Date:  2022-06-08       Impact factor: 5.738

3.  FDG PET/CT and Dosimetric Studies of 177Lu-Lilotomab Satetraxetan in a First-in-Human Trial for Relapsed Indolent non-Hodgkin Lymphoma-Are We Hitting the Target?

Authors:  Ayca Løndalen; Johan Blakkisrud; Mona-Elisabeth Revheim; Jostein Dahle; Arne Kolstad; Caroline Stokke
Journal:  Mol Imaging Biol       Date:  2022-04-29       Impact factor: 3.484

4.  A prognostic model integrating PET-derived metrics and image texture analyses with clinical risk factors from GOYA.

Authors:  Lale Kostakoglu; Federico Dalmasso; Paola Berchialla; Larry A Pierce; Umberto Vitolo; Maurizio Martelli; Laurie H Sehn; Marek Trněný; Tina G Nielsen; Christopher R Bolen; Deniz Sahin; Calvin Lee; Tarec Christoffer El-Galaly; Federico Mattiello; Paul E Kinahan; Stephane Chauvie
Journal:  EJHaem       Date:  2022-03-24

5.  Intraperitoneal Glucose Transport to Micrometastasis: A Multimodal In Vivo Imaging Investigation in a Mouse Lymphoma Model.

Authors:  Zsombor Ritter; Katalin Zámbó; Xinkai Jia; Dávid Szöllősi; Dániel Dezső; Hussain Alizadeh; Ildikó Horváth; Nikolett Hegedűs; David Tuch; Kunal Vyas; Péter Balogh; Domokos Máthé; Erzsébet Schmidt
Journal:  Int J Mol Sci       Date:  2021-04-23       Impact factor: 5.923

6.  In situ lymphoma imaging in a spontaneous mouse model using the Cerenkov Luminescence of F-18 and Ga-67 isotopes.

Authors:  Zsombor Ritter; Katalin Zámbó; Péter Balogh; Dávid Szöllősi; Xinkai Jia; Ákos Balázs; Gabriella Taba; Dániel Dezső; Ildikó Horváth; Hussain Alizadeh; David Tuch; Kunal Vyas; Nikolett Hegedűs; Tibor Kovács; Krisztián Szigeti; Domokos Máthé; Erzsébet Schmidt
Journal:  Sci Rep       Date:  2021-12-14       Impact factor: 4.379

7.  Convolutional Neural Networks for Automated PET/CT Detection of Diseased Lymph Node Burden in Patients with Lymphoma.

Authors:  Amy J Weisman; Minnie W Kieler; Scott B Perlman; Martin Hutchings; Robert Jeraj; Lale Kostakoglu; Tyler J Bradshaw
Journal:  Radiol Artif Intell       Date:  2020-09-02
  7 in total

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