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Defining the optimal method for measuring baseline metabolic tumour volume in diffuse large B cell lymphoma

Overview of attention for article published in European Journal of Nuclear Medicine and Molecular Imaging, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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Title
Defining the optimal method for measuring baseline metabolic tumour volume in diffuse large B cell lymphoma
Published in
European Journal of Nuclear Medicine and Molecular Imaging, February 2018
DOI 10.1007/s00259-018-3953-z
Pubmed ID
Authors

Hajira Ilyas, N. George Mikhaeel, Joel T. Dunn, Fareen Rahman, Henrik Møller, Daniel Smith, Sally F. Barrington

Abstract

Metabolic tumour volume (MTV) is a promising prognostic indicator in diffuse large B cell lymphoma (DLBCL). Optimal thresholds to divide patients into 'low' versus 'high' MTV groups depend on clinical characteristics and the measurement method. The aim of this study was to compare in consecutive unselected patients with DLBCL, different software algorithms and published methods of MTV measurement using FDG PET. Pretreatment MTV was measured on 147 patients treated at Guy's and St Thomas' Hospital. We compared 3 methods: SUV ≥2.5, SUV ≥41% of maximum SUV and SUV ≥ mean liver uptake (PERCIST) and compared 2 software programs for measuring SUV ≥2.5; in-house 'PETTRA' software and Hermes commercial software. There was strong correlation between MTV using the 4 methods, although derived thresholds were very different for the 41% method. Optimal cut-offs for predicting PFS ranged from 166-400cm3. All methods predicted survival with similar accuracy. 5y-PFS was 83-87% vs. 42-44% and 5y-OS was 85-89% vs. 55-58% for the low- and high-MTV groups, respectively. Interobserver variation in 50 patients showed excellent agreement, though variation was lowest using the SUV ≥ 2.5 method. The 41% method was the most complex and took the longest time. All methods predicted PFS and OS with similar accuracy, but the derived cut-off separating good from poor prognosis varied markedly depending on the method. The choice of the optimal method should rely primarily on prognostic value, but for clinical use needs to take account of ease of use and reproducibility. In this study, all methods predicted prognosis, but SUV ≥ 2.5 had the best inter-observer agreement and was easiest to apply.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 19%
Researcher 10 19%
Other 7 13%
Student > Master 5 9%
Student > Postgraduate 2 4%
Other 5 9%
Unknown 15 28%
Readers by discipline Count As %
Medicine and Dentistry 30 56%
Physics and Astronomy 4 7%
Engineering 2 4%
Computer Science 1 2%
Mathematics 1 2%
Other 2 4%
Unknown 14 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 October 2022.
All research outputs
#3,830,058
of 23,806,312 outputs
Outputs from European Journal of Nuclear Medicine and Molecular Imaging
#432
of 3,083 outputs
Outputs of similar age
#73,974
of 332,353 outputs
Outputs of similar age from European Journal of Nuclear Medicine and Molecular Imaging
#2
of 44 outputs
Altmetric has tracked 23,806,312 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,083 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 332,353 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.