TY - JOUR
T1 - Combatting the effect of image reconstruction settings on lymphoma [18F]FDG PET metabolic tumor volume assessment using various segmentation methods
AU - Ferrandez, Maria C.
AU - Eertink, Jakoba J.
AU - Golla, Sandeep S., V
AU - Wiegers, Sanne E.
AU - Zwezerijnen, Gerben J. C.
AU - Pieplenbosch, Simone
AU - Zijlstra, Josee M.
AU - Boellaard, Ronald
N1 - Funding Information: This work was financially supported by the Hanarth Fonds Fund and the Dutch Cancer Society. The sponsor had no role in gathering, analyzing or interpreting the data. The authors thank all the patients who participated in the trial. Funding Information: This work is financially supported by the Hanarth Fonds Fund and the Dutch Cancer Society (# VU 2018–11648). Publisher Copyright: © 2022, The Author(s).
PY - 2022/7/29
Y1 - 2022/7/29
N2 - 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.
AB - 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.
KW - Lymphoma
KW - Metabolic tumor volume
KW - Reconstruction
KW - Segmentation
KW - [F-18]FDG PET
UR - http://www.scopus.com/inward/record.url?scp=85135190880&partnerID=8YFLogxK
U2 - https://doi.org/10.1186/s13550-022-00916-9
DO - https://doi.org/10.1186/s13550-022-00916-9
M3 - Article
C2 - 35904645
SN - 2191-219X
VL - 12
JO - EJNMMI Research
JF - EJNMMI Research
IS - 1
M1 - 44
ER -