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

Abstract：

PURPOSE:To determine whether [18F]FDG PET/CT-derived radiomic features alone or in combination with clinical, laboratory and biological parameters are predictive of 2-year progression-free survival (PFS) in patients with mantle cell lymphoma (MCL), and whether they enable outcome prognostication. METHODS:Included in this retrospective study were 107 treatment-naive MCL patients scheduled to receive CD20 antibody-based immuno(chemo)therapy. Standardized uptake values (SUV), total lesion glycolysis, and 16 co-occurrence matrix radiomic features were extracted from metabolic tumour volumes on pretherapy [18F]FDG PET/CT scans. A multilayer perceptron neural network in combination with logistic regression analyses for feature selection was used for prediction of 2-year PFS. International prognostic indices for MCL (MIPI and MIPI-b) were calculated and combined with the radiomic data. Kaplan-Meier estimates with log-rank tests were used for PFS prognostication. RESULTS:SUVmean (OR 1.272, P = 0.013) and Entropy (heterogeneity of glucose metabolism; OR 1.131, P = 0.027) were significantly predictive of 2-year PFS: median areas under the curve were 0.72 based on the two radiomic features alone, and 0.82 with the addition of clinical/laboratory/biological data. Higher SUVmean in combination with higher Entropy (SUVmean >3.55 and entropy >3.5), reflecting high "metabolic risk", was associated with a poorer prognosis (median PFS 20.3 vs. 39.4 months, HR 2.285, P = 0.005). The best PFS prognostication was achieved using the MIPI-bm (MIPI-b and metabolic risk combined): median PFS 43.2, 38.2 and 20.3 months in the low-risk, intermediate-risk and high-risk groups respectively (P = 0.005). CONCLUSION:In MCL, the [18F]FDG PET/CT-derived radiomic features SUVmean and Entropy may improve prediction of 2-year PFS and PFS prognostication. The best results may be achieved using a combination of metabolic, clinical, laboratory and biological parameters.

journal_name

Eur J Nucl Med Mol Imaging

journal_title

European journal of nuclear medicine and molecular imaging

authors

Mayerhoefer ME,Riedl CC,Kumar A,Gibbs P,Weber M,Tal I,Schilksy J,Schöder H

doi

10.1007/s00259-019-04420-6

subject

Has Abstract

pub_date

2019-12-01 00:00:00

pages

2760-2769

issue

eissn

1619-7070

issn

1619-7089

pii

10.1007/s00259-019-04420-6

journal_volume

pub_type

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