Literature DB >> 25455879

An update on novel quantitative techniques in the context of evolving whole-body PET imaging.

Sina Houshmand1, Ali Salavati1, Søren Hess2, Thomas J Werner1, Abass Alavi1, Habib Zaidi3.   

Abstract

Since its foundation PET has established itself as one of the standard imaging modalities enabling the quantitative assessment of molecular targets in vivo. In the past two decades, quantitative PET has become a necessity in clinical oncology. Despite introduction of various measures for quantification and correction of PET parameters, there is debate on the selection of the appropriate methodology in specific diseases and conditions. In this review, we have focused on these techniques with special attention to topics such as static and dynamic whole body PET imaging, tracer kinetic modeling, global disease burden, texture analysis and radiomics, dual time point imaging and partial volume correction.
Copyright © 2015 Elsevier Inc. All rights reserved.

Keywords:  Glucose metabolism; Kinetic modeling; Quantification; Segmentation

Mesh:

Substances:

Year:  2014        PMID: 25455879     DOI: 10.1016/j.cpet.2014.09.004

Source DB:  PubMed          Journal:  PET Clin        ISSN: 1556-8598


  16 in total

1.  FDG-PET imaging to detect and characterize infectious disorders; an unavoidable path for the foreseeable future.

Authors:  Abass Alavi; Thomas J Werner
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-03       Impact factor: 9.236

Review 2.  Characterization of PET/CT images using texture analysis: the past, the present… any future?

Authors:  Mathieu Hatt; Florent Tixier; Larry Pierce; Paul E Kinahan; Catherine Cheze Le Rest; Dimitris Visvikis
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-06-06       Impact factor: 9.236

Review 3.  Towards enhanced PET quantification in clinical oncology.

Authors:  Habib Zaidi; Nicolas Karakatsanis
Journal:  Br J Radiol       Date:  2017-11-22       Impact factor: 3.039

4.  Correction for Partial Volume Effect Is a Must, Not a Luxury, to Fully Exploit the Potential of Quantitative PET Imaging in Clinical Oncology.

Authors:  Abass Alavi; Thomas J Werner; Poul Flemming Høilund-Carlsen; Habib Zaidi
Journal:  Mol Imaging Biol       Date:  2018-02       Impact factor: 3.488

5.  An update on the unparalleled impact of FDG-PET imaging on the day-to-day practice of medicine with emphasis on management of infectious/inflammatory disorders.

Authors:  Abass Alavi; Søren Hess; Thomas J Werner; Poul Flemming Høilund-Carlsen
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-09-04       Impact factor: 9.236

6.  Optimal FDG PET/CT volumetric parameters for risk stratification in patients with locally advanced non-small cell lung cancer: results from the ACRIN 6668/RTOG 0235 trial.

Authors:  Ali Salavati; Fenghai Duan; Bradley S Snyder; Bo Wei; Sina Houshmand; Benjapa Khiewvan; Adam Opanowski; Charles B Simone; Barry A Siegel; Mitchell Machtay; Abass Alavi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-07-08       Impact factor: 9.236

Review 7.  PET in the management of locally advanced and metastatic NSCLC.

Authors:  Willem Grootjans; Lioe-Fee de Geus-Oei; Esther G C Troost; Eric P Visser; Wim J G Oyen; Johan Bussink
Journal:  Nat Rev Clin Oncol       Date:  2015-04-28       Impact factor: 66.675

8.  Incremental value of FDG-PET/CT to monitor treatment response in infectious spondylodiscitis.

Authors:  Elda Righi; Alessia Carnelutti; Daniele Muser; Fernando Di Gregorio; Barbara Cadeo; Giulia Melchioretto; Maria Merelli; Abass Alavi; Matteo Bassetti
Journal:  Skeletal Radiol       Date:  2020-01-04       Impact factor: 2.199

9.  A prospective study of the feasibility of FDG-PET/CT imaging to quantify radiation-induced lung inflammation in locally advanced non-small cell lung cancer patients receiving proton or photon radiotherapy.

Authors:  Pegah Jahangiri; Kamyar Pournazari; Drew A Torigian; Thomas J Werner; Samuel Swisher-McClure; Charles B Simone; Abass Alavi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-09-18       Impact factor: 9.236

10.  Identify. Quantify. Predict. Why Immunologists Should Widely Use Molecular Imaging for Coronavirus Disease 2019.

Authors:  Freimut D Juengling; Antonio Maldonado; Frank Wuest; Thomas H Schindler
Journal:  Front Immunol       Date:  2021-05-13       Impact factor: 7.561

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