Literature DB >> 18653927

Assessment of tumour response with (18)F-fluorodeoxyglucose positron emission tomography using three-dimensional measures compared to SUVmax--a phantom study.

J A Boucek1, R J Francis, C G Jones, N Khan, B A Turlach, A J Green.   

Abstract

SUVmax is currently the most common semi-quantitative method of response assessment on FDG PET. By defining the tumour volume of interest (VOI), a measure of total glycolytic volume (TGV) may be obtained. We aimed to comprehensively examine, in a phantom setting, the accuracy of TGV in reflecting actual lesion activity and to compare TGV with SUVmax for response assessment. The algorithms for VOI generation from which TGV was derived included fixed threshold techniques at 50% of maximum (MAX50), 70% of maximum (MAX70), an adaptive threshold of 50% of (maximum + background)/2 (BM50) and a semi-automated iterative region-growing algorithm, GRAB. Comparison with both actual lesion activity and response scenarios was performed. SUVmax correlated poorly with actual lesion activity (r = 0.651) and change in lesion activity (r = 0.605). In a response matrix scenario SUVmax performed poorly when all scenarios were considered, but performed well when only clinically likely scenarios were included. The TGV derived using MAX50 and MAX70 algorithms performed poorly in evaluation of lesion change. The TGV derived from BM50 and GRAB algorithms however performed extremely well in correlation with actual lesion activity (r = 0.993 and r = 0.982, respectively), change in lesion activity (r = 0.972 and r = 0.963, respectively) and in the response scenario matrix. TGV(GRAB) demonstrated narrow confidence bands when modelled with actual lesion activity. Measures of TGV generated by iterative algorithms such as GRAB show potential for increased sensitivity of metabolic response monitoring compared to SUVmax, which may have important implications for improved patient care.

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Year:  2008        PMID: 18653927     DOI: 10.1088/0031-9155/53/16/001

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  12 in total

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4.  Correlation of Primary Tumor FDG Uptake with Histopathologic Features of Advanced Gastric Cancer.

Authors:  Hae Won Kim; Kyoung Sook Won; Bong-Il Song; Yu Na Kang
Journal:  Nucl Med Mol Imaging       Date:  2015-02-25

5.  Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18F-FDG uptake patterns.

Authors:  Shan Tan; Hao Zhang; Yongxue Zhang; Wengen Chen; Warren D D'Souza; Wei Lu
Journal:  Med Phys       Date:  2013-10       Impact factor: 4.071

6.  Disease volumes as a marker for patient response in malignant pleural mesothelioma.

Authors:  Z E Labby; A K Nowak; J J Dignam; C Straus; H L Kindler; S G Armato
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7.  CT-based quantitative SPECT for the radionuclide ²⁰¹Tl: experimental validation and a standardized uptake value for brain tumour patients.

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Journal:  Cancer Imaging       Date:  2012       Impact factor: 3.909

8.  Post-radioembolization yttrium-90 PET/CT - part 2: dose-response and tumor predictive dosimetry for resin microspheres.

Authors:  Yung-Hsiang Kao; Jeffrey D Steinberg; Young-Soon Tay; Gabriel Ky Lim; Jianhua Yan; David W Townsend; Charley A Budgeon; Jan A Boucek; Roslyn J Francis; Timothy St Cheo; Mark C Burgmans; Farah G Irani; Richard Hg Lo; Kiang-Hiong Tay; Bien-Soo Tan; Pierce Kh Chow; Somanesan Satchithanantham; Andrew Eh Tan; David Ce Ng; Anthony Sw Goh
Journal:  EJNMMI Res       Date:  2013-07-25       Impact factor: 3.138

Review 9.  Tumor quantification in clinical positron emission tomography.

Authors:  Bing Bai; James Bading; Peter S Conti
Journal:  Theranostics       Date:  2013-10-07       Impact factor: 11.556

10.  Prognostic and predictive role of [18 F]fluorodeoxyglucose positron emission tomography (FDG-PET) in patients with unresectable malignant pleural mesothelioma (MPM) treated with up-front pemetrexed-based chemotherapy.

Authors:  Paolo Andrea Zucali; Egesta Lopci; Giovanni Luca Ceresoli; Laura Giordano; Matteo Perrino; Gianluigi Ciocia; Letizia Gianoncelli; Elena Lorenzi; Matteo Simonelli; Fabio De Vincenzo; Lucia Rebecca Setti; Cristiana Bonifacio; Maria Bonomi; Emilio Bombardieri; Arturo Chiti; Armando Santoro
Journal:  Cancer Med       Date:  2017-09-21       Impact factor: 4.452

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