Literature DB >> 30929200

Prognostic role of baseline 18F-FDG PET/CT metabolic parameters in mantle cell lymphoma.

Domenico Albano1, Giovanni Bosio2, Nicola Bianchetti3, Chiara Pagani3, Alessandro Re3, Alessandra Tucci3, Raffaele Giubbini4, Francesco Bertagna4.   

Abstract

OBJECTIVE: Mantle cell lymphoma (MCL) is an aggressive lymphoma sub-type with poor prognosis and high 18F-FDG avidity at PET/CT; nowadays, no validated criteria for PET/CT in treatment response evaluation and prediction of outcome are present. The aim of study was to investigate whether the metabolic PET/CT features may predict treatment evaluation and prognosis in MCL.
METHODS: We retrospectively enrolled 87 patients who underwent baseline 18F-FDG PET/CT and 85 end-of-treatment (eot) PET/CT. The baseline PET images were analyzed visually and semi-quantitatively by measuring the maximum standardized uptake value body weight (SUVbw), lean body mass (SUVlbm), body surface area (SUVbsa), lesion-to-liver SUVmax ratio (L-L SUV R), lesion-to-blood pool SUVmax ratio (L-BP SUV R), metabolic tumor volume (MTV) and total lesion glycolysis (TLG). EotPET/CT was visually interpreted according to the criteria of the Deauville 5-point scale (DC). Survival curves were plotted according to the Kaplan-Meier method.
RESULTS: At a median follow-up of 40 months, relapse/progression occurred in 47 and death in 23 patients. Median PFS and OS were 30 and 41 months. Baseline MTV and TLG were significantly higher in patients with progressive metabolic response compared to complete/partial response group. EotPET/CT results using DC significantly correlated with PFS, not with OS. MTV and TLG were demonstrated to be independent prognostic factors for PFS; instead the other metabolic parameters were not related to outcome survival. Considering OS, no variable was significantly associated.
CONCLUSIONS: EotPET/CT results (using DC), MTV and TLG were significantly correlated with response to treatment and PFS.

Entities:  

Keywords:  18F-FDG PET/CT; MTV; Mantle cell lymphoma; Prognosis; TLG

Year:  2019        PMID: 30929200     DOI: 10.1007/s12149-019-01354-9

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN: 0914-7187            Impact factor:   2.668


  17 in total

1.  Prognostic value of FDG-PET in patients with mantle cell lymphoma: results from the LyMa-PET Project.

Authors:  Clément Bailly; Thomas Carlier; Alina Berriolo-Riedinger; Olivier Casasnovas; Emmanuel Gyan; Michel Meignan; Anne Moreau; Barbara Burroni; Loïc Djaileb; Remy Gressin; Anne Devillers; Thierry Lamy; Catherine Thieblemont; Olivier Hermine; Françoise Kraeber-Bodéré; Steven Le Gouill; Caroline Bodet-Milin
Journal:  Haematologica       Date:  2019-08-01       Impact factor: 9.941

2.  Lesion-Based Radiomics Signature in Pretherapy 18F-FDG PET Predicts Treatment Response to Ibrutinib in Lymphoma.

Authors:  Jorge E Jimenez; Dong Dai; Guofan Xu; Ruiyang Zhao; Tengfei Li; Tinsu Pan; Linghua Wang; Yingyan Lin; Zhangyang Wang; David Jaffray; John D Hazle; Homer A Macapinlac; Jia Wu; Yang Lu
Journal:  Clin Nucl Med       Date:  2022-03-01       Impact factor: 7.794

3.  Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDG-PET/CT for total metabolic tumour volume prediction using a convolutional neural network.

Authors:  Paul Blanc-Durand; Simon Jégou; Salim Kanoun; Alina Berriolo-Riedinger; Caroline Bodet-Milin; Françoise Kraeber-Bodéré; Thomas Carlier; Steven Le Gouill; René-Olivier Casasnovas; Michel Meignan; Emmanuel Itti
Journal:  Eur J Nucl Med Mol Imaging       Date:  2020-10-24       Impact factor: 9.236

4.  The Incremental Prognostic Value of Baseline 18F-FDG PET/CT Imaging in Angioimmunoblastic T-Cell Lymphoma.

Authors:  Hui Wang; Wenjing Yu; Tao Wu; Yangyang Xue; Dan Zhang; Huiqin Xu
Journal:  Biomed Res Int       Date:  2020-06-06       Impact factor: 3.411

5.  Radiomic features of glucose metabolism enable prediction of outcome in mantle cell lymphoma.

Authors:  Marius E Mayerhoefer; Christopher C Riedl; Anita Kumar; Peter Gibbs; Michael Weber; Ilan Tal; Juliana Schilksy; Heiko Schöder
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-07-08       Impact factor: 9.236

6.  The Role of 18F-FDG PET/CT in Staging and Prognostication of Mantle Cell Lymphoma: An Italian Multicentric Study.

Authors:  Domenico Albano; Riccardo Laudicella; Paola Ferro; Michela Allocca; Elisabetta Abenavoli; Ambra Buschiazzo; Alessia Castellino; Agostino Chiaravalloti; Annarosa Cuccaro; Lea Cuppari; Rexhep Durmo; Laura Evangelista; Viviana Frantellizzi; Sofya Kovalchuk; Flavia Linguanti; Giulia Santo; Matteo Bauckneht; Salvatore Annunziata
Journal:  Cancers (Basel)       Date:  2019-11-21       Impact factor: 6.639

7.  Early Interim Chemotherapy Response Evaluation by F-18 FDG PET/CT in Diffuse Large B Cell Lymphoma.

Authors:  Hye Lim Park; Eun Ji Han; Joo Hyun O; Byung-Ock Choi; Gyeongsin Park; Seung-Eun Jung; Seung-Ah Yahng; Ki-Seong Eom; Seok-Goo Cho
Journal:  Diagnostics (Basel)       Date:  2020-11-24

8.  Evaluation of an Automatic Classification Algorithm Using Convolutional Neural Networks in Oncological Positron Emission Tomography.

Authors:  Pierre Pinochet; Florian Eude; Stéphanie Becker; Vijay Shah; Ludovic Sibille; Mathieu Nessim Toledano; Romain Modzelewski; Pierre Vera; Pierre Decazes
Journal:  Front Med (Lausanne)       Date:  2021-02-26

9.  Prognostic value of baseline metabolic tumor volume in children and adolescents with intermediate-risk Hodgkin lymphoma treated with chemo-radiation therapy: FDG-PET parameter analysis in a subgroup from COG AHOD0031.

Authors:  Sarah A Milgrom; Jihyun Kim; Alin Chirindel; Jongho Kim; Qinglin Pei; Lu Chen; Allen Buxton; Sandy Kessel; Jeffrey Leal; Kathleen M McCarten; Bradford S Hoppe; Suzanne L Wolden; Cindy L Schwartz; Debra L Friedman; Kara M Kelly; Steve Y Cho
Journal:  Pediatr Blood Cancer       Date:  2021-07-10       Impact factor: 3.838

10.  Tumor metabolic volume by 18F-FDG-PET as a prognostic predictor of first-line pembrolizumab for NSCLC patients with PD-L1 ≥ 50.

Authors:  Ou Yamaguchi; Kyoichi Kaira; Kosuke Hashimoto; Atsuto Mouri; Ayako Shiono; Yu Miura; Yoshitake Murayama; Kunihiko Kobayashi; Hiroshi Kagamu; Ichiei Kuji
Journal:  Sci Rep       Date:  2020-09-14       Impact factor: 4.379

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