Evidence map›Paper›PMID 25932353›Full record

ArticleEJNMMI research2015

Metabolically active tumour volume segmentation from dynamic [(18)F]FLT PET studies in non-small cell lung cancer.

Lieke L Hoyng, Virginie Frings, Otto S Hoekstra, Laura M Kenny, Eric O Aboagye, Ronald Boellaard

Abstract read
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Article in EJNMMI research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. IntratumoralEJNMMI research · 2019
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Lieke L HoyngDepartment of Radiology & Nuclear Medicine, VU University Medical Center (VUmc), P.O. Box 7057, 1007 MB Amsterdam, The Netherlands.
Virginie FringsDepartment of Radiology & Nuclear Medicine, VU University Medical Center (VUmc), P.O. Box 7057, 1007 MB Amsterdam, The Netherlands.
Otto S HoekstraDepartment of Radiology & Nuclear Medicine, VU University Medical Center (VUmc), P.O. Box 7057, 1007 MB Amsterdam, The Netherlands.
Laura M KennyComprehensive Cancer Imaging Centre, Imperial College London, Hammersmith Hospital, W12 0NN London, UK.
Eric O AboagyeComprehensive Cancer Imaging Centre, Imperial College London, Hammersmith Hospital, W12 0NN London, UK.
Ronald BoellaardDepartment of Radiology & Nuclear Medicine, VU University Medical Center (VUmc), P.O. Box 7057, 1007 MB Amsterdam, The Netherlands.

Funding

Cancer Research UK 16584
6 · The paper itself

Abstract

backgroundPositron emission tomography (PET) with (18)F-3'-deoxy-3'-fluorothymidine ([(18)F]FLT) can be used to assess tumour proliferation. A kinetic-filtering (KF) classification algorithm has been suggested for segmentation of tumours in dynamic [(18)F]FLT PET data. The aim of the present study was to evaluate KF segmentation and its test-retest performance in [(18)F]FLT PET in non-small cell lung cancer (NSCLC) patients.

methodsNine NSCLC patients underwent two 60-min dynamic [(18)F]FLT PET scans within 7 days prior to treatment. Dynamic scans were reconstructed with filtered back projection (FBP) as well as with ordered subsets expectation maximisation (OSEM). Twenty-eight lesions were identified by an experienced physician. Segmentation was performed using KF applied to the dynamic data set and a source-to-background corrected 50% threshold (A50%) was applied to the sum image of the last three frames (45- to 60-min p.i.). Furthermore, several adaptations of KF were tested. Both for KF and A50% test-retest (TRT) variability of metabolically active tumour volume and standard uptake value (SUV) were evaluated.

resultsKF performed better on OSEM- than on FBP-reconstructed PET images. The original KF implementation segmented 15 out of 28 lesions, whereas A50% segmented each lesion. Adapted KF versions, however, were able to segment 26 out of 28 lesions. In the best performing adapted versions, metabolically active tumour volume and SUV TRT variability was similar to those of A50%. KF misclassified certain tumour areas as vertebrae or liver tissue, which was shown to be related to heterogeneous [(18)F]FLT uptake areas within the tumour.

conclusionsFor [(18)F]FLT PET studies in NSCLC patients, KF and A50% show comparable tumour volume segmentation performance. The KF method needs, however, a site-specific optimisation. The A50% is therefore a good alternative for tumour segmentation in NSCLC [(18)F]FLT PET studies in multicentre studies. Yet, it was observed that KF has the potential to subsegment lesions in high and low proliferative areas.

Indexed as

18F-FLTDynamicKinetic filteringNSCLCPETSegmentation

Identifiers

PMID25932353
PMCPMC4409618

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