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      Optimal method for metabolic tumour volume assessment of cervical cancers with inter-observer agreement on [18F]-fluoro-deoxy-glucose positron emission tomography with computed tomography

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          Abstract

          Purpose

          Cervical cancer metabolic tumour volume (MTV) derived from [18F]-FDG PET/CT has a role in prognostication and therapy planning. There is no standard method of outlining MTV on [18F]-FDG PET/CT. The aim of this study was to assess the optimal method to outline primary cervical tumours on [18F]-FDG PET/CT using MRI-derived tumour volumes as the reference standard.

          Methods

          81 consecutive cervical cancer patients with pre-treatment staging MRI and [18F]-FDG PET/CT imaging were included. MRI volumes were compared with different PET segmentation methods. Method 1 measured MTVs at different SUV max thresholds ranging from 20 to 60% (MTV 20-MTV 60) with bladder masking and manual adjustment when required. Method 2 created an isocontour around the tumour prior to different SUV max thresholds being applied. Method 3 used an automated gradient method. Inter-observer agreement of MTV, following manual adjustment when required, was recorded.

          Results

          For method 1, the MTV 25 and MTV 30 were closest to the MRI volumes for both readers (mean percentage change from MRI volume of 2.9% and 13.4% for MTV 25 and − 13.1% and − 2.0% for MTV 30 for readers 1 and 2). 70% of lesions required manual adjustment at MTV 25 compared with 45% at MTV 30. There was excellent inter-observer agreement between MTV 30 to MTV 60 (ICC ranged from 0.898–0.976 with narrow 95% confidence intervals (CIs)) and moderate agreement at lower thresholds (ICC estimates of 0.534 and 0.617, respectively for the MTV 20 and MTV 25 with wide 95% CIs). Bladder masking was performed in 86% of cases overall. For method 2, excellent correlation was demonstrated at MTV 25 and MTV 30 (mean % change from MRI volume of −3.9% and − 8.6% for MTV 25 and − 16.9% and 19% for MTV 30 for readers 1 and 2, respectively). This method also demonstrated excellent ICC across all thresholds with no manual adjustment. Method 3 demonstrated excellent ICC of 0.96 (95% CI 0.94–0.97) but had a mean percentage difference from the MRI volume of − 19.1 and − 18.2% for readers 1 and 2, respectively. 21% required manual adjustment for both readers.

          Conclusion

          MTV 30 provides the optimal correlation with MRI volume taking into consideration the excellent inter-reader agreement and less requirement for manual adjustment.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00259-020-05136-8.

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          Most cited references47

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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                Author and article information

                Contributors
                mubarik@doctors.org.uk
                Journal
                Eur J Nucl Med Mol Imaging
                Eur J Nucl Med Mol Imaging
                European Journal of Nuclear Medicine and Molecular Imaging
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1619-7070
                1619-7089
                11 December 2020
                11 December 2020
                2021
                : 48
                : 6
                : 2009-2023
                Affiliations
                [1 ]GRID grid.413629.b, ISNI 0000 0001 0705 4923, Departments of Radiology and Nuclear Medicine, , Hammersmith Hospital, Imperial College Healthcare NHS Trust, ; Du Cane Road, London, W12 0HS UK
                [2 ]GRID grid.413629.b, ISNI 0000 0001 0705 4923, Department of Clinical Oncology, , Hammersmith Hospital, Imperial College Healthcare NHS Trust, ; Du Cane Road, London, W12 0HS UK
                [3 ]GRID grid.413629.b, ISNI 0000 0001 0705 4923, Department of Surgery & Cancer, , Hammersmith Hospital, Imperial College London Cancer Imaging Centre, ; Du Cane Road, London, W12 0NN UK
                Author information
                http://orcid.org/0000-0002-7086-6112
                Article
                5136
                10.1007/s00259-020-05136-8
                8113292
                33313962
                750663bb-43bd-4a3e-af6c-7129b8be917e
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 July 2020
                : 24 November 2020
                Funding
                Funded by: Imperial College London
                Categories
                Original Article
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2021

                Radiology & Imaging
                cervix,fdg,pet/ct,mtv,tumour segmentation
                Radiology & Imaging
                cervix, fdg, pet/ct, mtv, tumour segmentation

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