Combatting the effect of image reconstruction settings on lymphoma [18F]FDG PET metabolic tumor volume assessment using various segmentation methods

Abstract

Background: [¹⁸F]FDG PET-based metabolic tumor volume (MTV) is a promising prognostic marker for lymphoma patients. The aim of this study is to assess the sensitivity of several MTV segmentation methods to variations in image reconstruction methods and the ability of ComBat to improve MTV reproducibility.

Methods: Fifty-six lesions were segmented from baseline [¹⁸F]FDG PET scans of 19 lymphoma patients. For each scan, EARL1 and EARL2 standards and locally clinically preferred reconstruction protocols were applied. Lesions were delineated using 9 semiautomatic segmentation methods: fixed threshold based on standardized uptake value (SUV), (SUV = 4, SUV = 2.5), relative threshold (41% of SUVmax [41M], 50% of SUVpeak [A50P]), majority vote-based methods that select voxels detected by at least 2 (MV2) and 3 (MV3) out of the latter 4 methods, Nestle thresholding, and methods that identify the optimal method based on SUVmax (L2A, L2B). MTVs from EARL2 and locally clinically preferred reconstructions were compared to those from EARL1. Finally, different versions of ComBat were explored to harmonize the data.

Results: MTVs from the SUV4.0 method were least sensitive to the use of different reconstructions (MTV ratio: median = 1.01, interquartile range = [0.96-1.10]). After ComBat harmonization, an improved agreement of MTVs among different reconstructions was found for most segmentation methods. The regular implementation of ComBat ('Regular ComBat') using non-transformed distributions resulted in less accurate and precise MTV alignments than a version using log-transformed datasets ('Log-transformed ComBat').

Conclusion: MTV depends on both segmentation method and reconstruction methods. ComBat reduces reconstruction dependent MTV variability, especially when log-transformation is used to account for the non-normal distribution of MTVs.

Keywords: Lymphoma; Metabolic tumor volume; Reconstruction; Segmentation; [18F]FDG PET.

Fig. 1

MTV ratios across segmentation methods. Each boxplot illustrates the set of MTV ratios obtained with a particular segmentation method: 41M, A50P, L2A, L2B, MV2, MV3, NESTLE, SUV2.5 or SUV4.0. MTV ratios are given for a EARL2 reconstructions and b HR reconstructions. * Implies few outliers not displayed

Fig. 2

MTVs obtained using 41M segmentation across 3 different reconstructions: EARL1, EARL2 and HR. a MTVs before ComBat harmonization. b MTVs after ComBat using non-transformed distribution (Regular ComBat). c MTVs after ComBat using log-transformed distribution (Log-transformed ComBat). Regular ComBat leads to negative volume values for the clinical reconstruction unlike Log-transformed ComBat which led to positive-only volumes

Fig. 3

MTV ratio across 9 segmentation methods. MTV ratio calculated by comparing MTVs of EARL2 to those of EARL1, with EARL1 as the denominator for a particular segmentation method: 41M, A50P, L2A, L2B, MV2, MV3, NESTLE, SUV2.5 or SUV4.0. For each segmentation method, 2 boxplots are shown. The light blue boxplot represents data without ComBat harmonization, while the dark blue boxplot is obtained after ComBat harmonization. MTV ratio equal to 1 indicates a perfect alignment between reconstructions. a MTV ratio before and after ComBat using non-transformed distribution (Regular ComBat) b MTV ratio before and after ComBat using log-transformed distribution (Log-transformed ComBat)