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EJNMMI Research
Published in: EJNMMI Research 1/2018

Open Access 01-12-2018 | Original research

A semi-automatic technique to quantify complex tuberculous lung lesions on 18F-fluorodeoxyglucose positron emission tomography/computerised tomography images

Authors: Stephanus T. Malherbe, Patrick Dupont, Ilse Kant, Petri Ahlers, Magdalena Kriel, André G. Loxton, Ray Y. Chen, Laura E. Via, Friedrich Thienemann, Robert J. Wilkinson, Clifton E. Barry III, Stephanie Griffith-Richards, Annare Ellman, Katharina Ronacher, Jill Winter, Gerhard Walzl, James M. Warwick, the Catalysis Biomarker Consortium

Published in: EJNMMI Research | Issue 1/2018

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Abstract

Background

There is a growing interest in the use of 18F-FDG PET-CT to monitor tuberculosis (TB) treatment response. However, TB causes complex and widespread pathology, which is challenging to segment and quantify in a reproducible manner.
To address this, we developed a technique to standardise uptake (Z-score), segment and quantify tuberculous lung lesions on PET and CT concurrently, in order to track changes over time. We used open source tools and created a MATLAB script. The technique was optimised on a training set of five pulmonary tuberculosis (PTB) cases after standard TB therapy and 15 control patients with lesion-free lungs.

Results

We compared the proposed method to a fixed threshold (SUV > 1) and manual segmentation by two readers and piloted the technique successfully on scans of five control patients and five PTB cases (four cured and one failed treatment case), at diagnosis and after 1 and 6 months of treatment. There was a better correlation between the Z-score-based segmentation and manual segmentation than SUV > 1 and manual segmentation in terms of overall spatial overlap (measured in Dice similarity coefficient) and specificity (1 minus false positive volume fraction). However, SUV > 1 segmentation appeared more sensitive. Both the Z-score and SUV > 1 showed very low variability when measuring change over time. In addition, total glycolytic activity, calculated using segmentation by Z-score and lesion-to-background ratio, correlated well with traditional total glycolytic activity calculations. The technique quantified various PET and CT parameters, including the total glycolytic activity index, metabolic lesion volume, lesion volumes at different CT densities and combined PET and CT parameters. The quantified metrics showed a marked decrease in the cured cases, with changes already apparent at month one, but remained largely unchanged in the failed treatment case.

Conclusions

Our technique is promising to segment and quantify the lung scans of pulmonary tuberculosis patients in a semi-automatic manner, appropriate for measuring treatment response. Further validation is required in larger cohorts.
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Metadata
Title
A semi-automatic technique to quantify complex tuberculous lung lesions on 18F-fluorodeoxyglucose positron emission tomography/computerised tomography images
Authors
Stephanus T. Malherbe
Patrick Dupont
Ilse Kant
Petri Ahlers
Magdalena Kriel
André G. Loxton
Ray Y. Chen
Laura E. Via
Friedrich Thienemann
Robert J. Wilkinson
Clifton E. Barry III
Stephanie Griffith-Richards
Annare Ellman
Katharina Ronacher
Jill Winter
Gerhard Walzl
James M. Warwick
the Catalysis Biomarker Consortium
Publication date
01-12-2018
Publisher
Springer Berlin Heidelberg
Published in
EJNMMI Research / Issue 1/2018
Electronic ISSN: 2191-219X
DOI
https://doi.org/10.1186/s13550-018-0411-7

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