Literature DB >> 32259852

Textural features in FDG-PET/CT can predict outcome in melanoma patients to treatment with Vemurafenib and Ipililumab.

Daniela Dittrich1, Thomas Pyka1,2, Klemens Scheidhauer1, Susanne Lütje3, Markus Essler3, Ralph A Bundschuh3.   

Abstract

AIM: Recently, textural parameters assessed in FDG-PET/CT as surrogate marker for tumor heterogeneity have been shown to provide prognostic power. Therefore, we investigated the use of such parameters in FDG-PET/CT examinations before the start of immunotherapy with vemurafenib or ipilimumab in patients with malignant melanoma.
METHODS: In this retrospective analysis 26 patients with histologically proven advanced melanoma were included. FGD-PET/CT was performed before the start of treatment either with vemurafenib (n = 9) or ipilimumab (n = 17) and tumors were analyzed for textural parameters as well as conventional PET features. Lesions were classified as responding or not responding following PERCIST criteria. ROC analysis was performed to analyze the predictive power and cut-off values. In addition, the change of maximum SUV of the lesions between pretherapeutic PET/CT and another PET/CT performed about 12 weeks after start of treatment was evaluated and correlated with the pretreatment parameters.
RESULTS: In both groups, six textural parameters showed statistically significant predictive power as well as the metabolic tumor volume. In the group treated with vemurafenib eight additional textural parameters as well as the maximum and mean SUV and the TLG showed significance. A statistically significant correlation between the change of maximum SUV in the course of treatment and the pretherapeutic parameters was found in both treatment groups for three textural features.
CONCLUSION: In patients with malignant melanoma textural parameters in pretherapeutic FDG-PET/CT examinations seem to have prognostic power for treatment response of immunotherapy with vemurafenib and ipilimumab. This can be an important step towards personalized tumor therapy. © Georg Thieme Verlag KG Stuttgart · New York.

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Year:  2020        PMID: 32259852     DOI: 10.1055/a-1140-5458

Source DB:  PubMed          Journal:  Nuklearmedizin        ISSN: 0029-5566            Impact factor:   1.379


  7 in total

1.  FDG PET biomarkers for prediction of survival in metastatic melanoma prior to anti-PD1 immunotherapy.

Authors:  A Flaus; V Habouzit; N De Leiris; J P Vuillez; M T Leccia; J L Perrot; N Prevot; F Cachin
Journal:  Sci Rep       Date:  2021-09-22       Impact factor: 4.379

2.  Prognostic Value of Metabolic, Volumetric and Textural Parameters of Baseline [18F]FDG PET/CT in Early Triple-Negative Breast Cancer.

Authors:  Clément Bouron; Clara Mathie; Valérie Seegers; Olivier Morel; Pascal Jézéquel; Hamza Lasla; Camille Guillerminet; Sylvie Girault; Marie Lacombe; Avigaelle Sher; Franck Lacoeuille; Anne Patsouris; Aude Testard
Journal:  Cancers (Basel)       Date:  2022-01-27       Impact factor: 6.639

3.  Outcome Prediction at Patient Level Derived from Pre-Treatment 18F-FDG PET Due to Machine Learning in Metastatic Melanoma Treated with Anti-PD1 Treatment.

Authors:  Anthime Flaus; Vincent Habouzit; Nicolas de Leiris; Jean-Philippe Vuillez; Marie-Thérèse Leccia; Mathilde Simonson; Jean-Luc Perrot; Florent Cachin; Nathalie Prevot
Journal:  Diagnostics (Basel)       Date:  2022-02-02

Review 4.  Artificial intelligence and radiomics: fundamentals, applications, and challenges in immunotherapy.

Authors:  Laurent Dercle; Jeremy McGale; Shawn Sun; Aurelien Marabelle; Randy Yeh; Eric Deutsch; Fatima-Zohra Mokrane; Michael Farwell; Samy Ammari; Heiko Schoder; Binsheng Zhao; Lawrence H Schwartz
Journal:  J Immunother Cancer       Date:  2022-09       Impact factor: 12.469

5.  Malignancy Rate of Indeterminate Findings on FDG-PET/CT in Cutaneous Melanoma Patients.

Authors:  Ken Kudura; Florentia Dimitriou; Daniela Mihic-Probst; Urs J Muehlematter; Tim Kutzker; Lucas Basler; Robert Förster; Reinhard Dummer; Joanna Mangana; Lars Husmann; Irene A Burger; Michael Christoph Kreissl
Journal:  Diagnostics (Basel)       Date:  2021-05-15

6.  Prediction of Early Response to Immune Checkpoint Inhibition Using FDG-PET/CT in Melanoma Patients.

Authors:  Ken Kudura; Florentia Dimitriou; Lucas Basler; Robert Förster; Daniela Mihic-Probst; Tim Kutzker; Reinhard Dummer; Joanna Mangana; Irene A Burger; Michael C Kreissl
Journal:  Cancers (Basel)       Date:  2021-07-29       Impact factor: 6.575

7.  A Novel Radiomics-Based Tumor Volume Segmentation Algorithm for Lung Tumors in FDG-PET/CT after 3D Motion Correction-A Technical Feasibility and Stability Study.

Authors:  Lena Bundschuh; Vesna Prokic; Matthias Guckenberger; Stephanie Tanadini-Lang; Markus Essler; Ralph A Bundschuh
Journal:  Diagnostics (Basel)       Date:  2022-02-23
  7 in total

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