Literature DB >> 30933647

Tumor Heterogeneity on FDG PET/CT and Immunotherapy: An Imaging Biomarker for Predicting Treatment Response in Patients With Metastatic Melanoma.

Y Sanli1, J Leake1, A Odu1, Y Xi1, R M Subramaniam1,2,3.   

Abstract

OBJECTIVE: The purpose of this study is to evaluate the ability of quantitative 18F-FDG PET parameters to predict outcomes of patients with malignant melanoma who have been treated with immune modulation therapy.
MATERIALS AND METHODS: We retrospectively investigated 34 patients with malignant melanoma. Twenty-three patients received immunotherapy as first-line therapy, and 11 patients received it as second-line therapy. The maximum standardized uptake value (SUVmax), metabolic tumor volume, tumor lesion glycolysis, and intratumoral metabolic heterogeneity (as measured by the tumor heterogeneity [TH] index) were measured for the primary tumors and metastatic sites associated with up to five of the most FDG-avid lesions per patient. The TH index was calculated as the AUC value of a cumulative SUV volume histogram curve for all patients. The median follow-up was 29.5 months (range, 3-288 months). Outcome endpoints were progression-free survival and overall survival. Kaplan-Meier survival plots were used, and Cox regression analysis was performed for predictors of survival.
RESULTS: A total of 101 lesions were analyzed. Five lesions were analyzed in 12 patients, four lesions in three patients, three lesions in three patients, two lesions in four patients, and one lesion in 12 patients. Of the 34 patients included in the study, 15 (44.1%) had disease progression and 11 (32.3%) had died by the time the last follow-up occurred. The mean (± SD) SUVmax, peak SUV, metabolic tumor volume, tumor lesion glycolysis, and TH values for all lesions were 9.68 ± 6.6, 7.82 ± 5.83, 81.96 ± 146.87 mL, 543.65 ± 1022.92 g, and 5841.36 ± 1249.85, respectively. TH had a negative correlation with SUVmax, peak SUV, and tumor lesion glycolysis (p < 0.0001 for all).
CONCLUSION: The TH index is significantly associated with overall survival in patients with metastatic melanoma treated with immune modulation therapy as first-line or second-line therapy.

Entities:  

Keywords:  F-FDG PET/CT; immunotherapy; metastatic melanoma; tumor heterogeneity

Year:  2019        PMID: 30933647     DOI: 10.2214/AJR.18.19796

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  6 in total

Review 1.  Precision Nuclear Medicine: The Evolving Role of PET in Melanoma.

Authors:  Chadwick L Wright; Eric D Miller; Carlo Contreras; Michael V Knopp
Journal:  Radiol Clin North Am       Date:  2021-09       Impact factor: 1.947

2.  The prognostic value of 18F-FDG PET/CT intra-tumoural metabolic heterogeneity in pretreatment neuroblastoma patients.

Authors:  Jun Liu; Yukun Si; Ziang Zhou; Xu Yang; Cuicui Li; Luodan Qian; Li Juan Feng; Mingyu Zhang; Shu Xin Zhang; Jie Liu; Ying Kan; Jianhua Gong; Jigang Yang
Journal:  Cancer Imaging       Date:  2022-07-05       Impact factor: 5.605

3.  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

4.  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 5.  The Role and Potential of 18F-FDG PET/CT in Malignant Melanoma: Prognostication, Monitoring Response to Targeted and Immunotherapy, and Radiomics.

Authors:  Luca Filippi; Francesco Bianconi; Orazio Schillaci; Angela Spanu; Barbara Palumbo
Journal:  Diagnostics (Basel)       Date:  2022-04-08

Review 6.  Anti-angiogenic Agents in Combination With Immune Checkpoint Inhibitors: A Promising Strategy for Cancer Treatment.

Authors:  Yuxiao Song; Yang Fu; Qi Xie; Bo Zhu; Jun Wang; Bicheng Zhang
Journal:  Front Immunol       Date:  2020-08-25       Impact factor: 7.561

  6 in total

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