Literature DB >> 27904837

Positron emission tomography/computerized tomography for tumor response assessment-a review of clinical practices and radiomics studies.

Wei Lu1, Wengen Chen2.   

Abstract

Even with recent advances in cancer diagnosis and therapy, treatment outcomes for many cancers remain dismal. Patients often show different response to the same therapy regimen, supporting the development of personalized medicine. 18F-FDG PET/CT has been used routinely in the assessment of tumor response, in prediction of outcomes, and in guiding personalized treatment. These assessments are mainly based on physician's subjective or semi-quantitative evaluation. Recent development in Radiomics provides a promising objective way for tumor response assessment, which uses computerized tools to extract a large number of image features that capture additional information not currently used in clinic that has prognostic value. In this review, we summarized the clinical use of PET/CT and the PET/CT Radiomics studies for tumor response assessment. Finally, we discussed some challenges and future perspectives.

Entities:  

Keywords:  18F-FDG PET/CT; Radiomics; image analysis; tumor response

Year:  2016        PMID: 27904837      PMCID: PMC5124903          DOI: 10.21037/tcr.2016.07.12

Source DB:  PubMed          Journal:  Transl Cancer Res        ISSN: 2218-676X            Impact factor:   1.241


  45 in total

1.  A novel fuzzy C-means algorithm for unsupervised heterogeneous tumor quantification in PET.

Authors:  Saoussen Belhassen; Habib Zaidi
Journal:  Med Phys       Date:  2010-03       Impact factor: 4.071

2.  Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification.

Authors:  Bruce D Cheson; Richard I Fisher; Sally F Barrington; Franco Cavalli; Lawrence H Schwartz; Emanuele Zucca; T Andrew Lister
Journal:  J Clin Oncol       Date:  2014-09-20       Impact factor: 44.544

3.  Tumor Treatment Response Based on Visual and Quantitative Changes in Global Tumor Glycolysis Using PET-FDG Imaging. The Visual Response Score and the Change in Total Lesion Glycolysis.

Authors:  Steven M. Larson; Yusuf Erdi; Timothy Akhurst; Madhu Mazumdar; Homer A. Macapinlac; Ronald D. Finn; Cecille Casilla; Melissa Fazzari; Neil Srivastava; Henry W.D. Yeung; John L. Humm; Jose Guillem; Robert Downey; Martin Karpeh; Alfred E. Cohen; Robert Ginsberg
Journal:  Clin Positron Imaging       Date:  1999-05

4.  Spatial heterogeneity in sarcoma 18F-FDG uptake as a predictor of patient outcome.

Authors:  Janet F Eary; Finbarr O'Sullivan; Janet O'Sullivan; Ernest U Conrad
Journal:  J Nucl Med       Date:  2008-11-07       Impact factor: 10.057

Review 5.  Tumor heterogeneity: causes and consequences.

Authors:  Andriy Marusyk; Kornelia Polyak
Journal:  Biochim Biophys Acta       Date:  2009-11-18

6.  Metabolic monitoring of breast cancer chemohormonotherapy using positron emission tomography: initial evaluation.

Authors:  R L Wahl; K Zasadny; M Helvie; G D Hutchins; B Weber; R Cody
Journal:  J Clin Oncol       Date:  1993-11       Impact factor: 44.544

7.  Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy?

Authors:  Gary J R Cook; Connie Yip; Muhammad Siddique; Vicky Goh; Sugama Chicklore; Arunabha Roy; Paul Marsden; Shahreen Ahmad; David Landau
Journal:  J Nucl Med       Date:  2012-11-30       Impact factor: 10.057

8.  Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study.

Authors:  Ronald Boellaard; Nanda C Krak; Otto S Hoekstra; Adriaan A Lammertsma
Journal:  J Nucl Med       Date:  2004-09       Impact factor: 10.057

9.  Modeling pathologic response of esophageal cancer to chemoradiation therapy using spatial-temporal 18F-FDG PET features, clinical parameters, and demographics.

Authors:  Hao Zhang; Shan Tan; Wengen Chen; Seth Kligerman; Grace Kim; Warren D D'Souza; Mohan Suntharalingam; Wei Lu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2013-11-01       Impact factor: 7.038

10.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

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  4 in total

Review 1.  Towards precision medicine: from quantitative imaging to radiomics.

Authors:  U Rajendra Acharya; Yuki Hagiwara; Vidya K Sudarshan; Wai Yee Chan; Kwan Hoong Ng
Journal:  J Zhejiang Univ Sci B       Date:  2018 Jan.       Impact factor: 3.066

2.  Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer.

Authors:  Wookjin Choi; Jung Hun Oh; Sadegh Riyahi; Chia-Ju Liu; Feng Jiang; Wengen Chen; Charles White; Andreas Rimner; James G Mechalakos; Joseph O Deasy; Wei Lu
Journal:  Med Phys       Date:  2018-03-12       Impact factor: 4.071

3.  Computed-Tomography-Based Radiomics Model for Predicting the Malignant Potential of Gastrointestinal Stromal Tumors Preoperatively: A Multi-Classifier and Multicenter Study.

Authors:  Minhong Wang; Zhan Feng; Lixiang Zhou; Liang Zhang; Xiaojun Hao; Jian Zhai
Journal:  Front Oncol       Date:  2021-04-22       Impact factor: 6.244

Review 4.  Radiomics for Response and Outcome Assessment for Non-Small Cell Lung Cancer.

Authors:  Liting Shi; Yaoyao He; Zilong Yuan; Stanley Benedict; Richard Valicenti; Jianfeng Qiu; Yi Rong
Journal:  Technol Cancer Res Treat       Date:  2018-01-01
  4 in total

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