Comparison of different automatic methods for the delineation of the total metabolic tumor volume in I–II stage Hodgkin Lymphoma
Total metabolic tumor volume (TMTV) is a promising quantitative biomarker for therapy assessment and prognosis in Hodgkin Lymphoma affected patients that allows prediction of patient outcome. The aim of this study was to evaluate the TMTV reproducibility between different sources of variability in t...
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Published in | Scientific reports Vol. 10; no. 1; pp. 12590 - 10 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
28.07.2020
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | Total metabolic tumor volume (TMTV) is a promising quantitative biomarker for therapy assessment and prognosis in Hodgkin Lymphoma affected patients that allows prediction of patient outcome. The aim of this study was to evaluate the TMTV reproducibility between different sources of variability in tumor delimitation such as SUV-based thresholds (2.5, 41% and 50%) and software tools (Beth Israel plugin (BI) and LIFEx). Effect of contouring procedure both including single and multiple regions of interest was also studied in patients with multiple lesions, and optimal cut-offs for each studied method were displayed to compare the effect on prognosis. Strong alikeness in TMTV was found for 2.5 under software choice
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Best accuracy in contouring compared to visual assessment of the disease was found for BI multiple ROI and LIFEx single ROI drawing. Similar cut-offs were found between both software for all considered thresholds, but best resemblance and highest cut-off due to an overestimation of the TMTV was found for 2.5 SUV. Our findings suggest that optimal reproducibility in TMTV is found for SUV > 2.5 threshold under choice of contouring methodology or software tool, meaning that overestimation of the TMTV threshold using 2.5 looks to be preferable than underestimation with 41% and 50%. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-020-69577-9 |