Literature DB >> 33718144

Positron Emission Tomography-Based Short-Term Efficacy Evaluation and Prediction in Patients With Non-Small Cell Lung Cancer Treated With Hypo-Fractionated Radiotherapy.

Yi-Qing Jiang1, Qin Gao1, Han Chen1, Xiang-Xiang Shi1, Jing-Bo Wu1, Yue Chen2, Yan Zhang2, Hao-Wen Pang1, Sheng Lin1,2.   

Abstract

BACKGROUND: Positron emission tomography is known to provide more accurate estimates than computed tomography when staging non-small cell lung cancer. The aims of this prospective study were to contrast the short-term efficacy of the two imaging methods while evaluating the effects of hypo-fractionated radiotherapy in non-small cell lung cancer, and to establish a short-term efficacy prediction model based on the radiomics features of positron emission tomography.
METHODS: This nonrandomized-controlled trial was conducted from March 2015 to June 2019. Thirty-one lesions of 30 patients underwent the delineation of the regions of interest on positron emission tomography and computed tomography 1 month before, and 3 months after hypo-fractionated radiotherapy. Each patient was evaluated for the differences in local objective response rate between the two images. The Kaplan Meier method was used to analyze the local objective response and subsequent survival duration of the two imaging methods. The 3D Slicer was used to extract the radiomics features based on positron emission tomography. Least absolute shrinkage and selection operator regression was used to eliminate redundant features, and logistic regression analysis was used to develop the curative-effect-predicting model, which was displayed through a radiomics nomogram. Receiver operating characteristic curve and decision curve were used to evaluate the accuracy and clinical usefulness of the prediction model.
RESULTS: Positron emission tomography-based local objective response rate was significantly higher than that based on computed tomography [70.97% (22/31) and 12.90% (4/31), respectively (p<0.001)]. The mean survival time of responders and non-responders assessed by positron emission tomography was 28.6 months vs. 11.4 months (p=0.29), whereas that assessed by computed tomography was 24.5 months vs. 26 months (p=0.66), respectively. Three radiomics features were screened to establish a personalized prediction nomogram with high area under curve (0.94, 95% CI 0.85-0.99, p<0.001). The decision curve showed a high clinical value of the radiomics nomogram.
CONCLUSIONS: We recommend positron emission tomography for evaluating the short-term efficacy of hypo-fractionated radiotherapy in non-small cell lung cancer, and that the radiomics nomogram could be an important technique for the prediction of short-term efficacy, which might enable an improved and precise treatment. REGISTRATION NUMBER/URL: ChiCTR1900027768/http://www.chictr.org.cn/showprojen.aspx?proj=46057.
Copyright © 2021 Jiang, Gao, Chen, Shi, Wu, Chen, Zhang, Pang and Lin.

Entities:  

Keywords:  computed tomography; hypo-fractionated radiotherapy; non-small-cell lung cancer; positron emission tomography; radiomics

Year:  2021        PMID: 33718144      PMCID: PMC7947869          DOI: 10.3389/fonc.2021.590836

Source DB:  PubMed          Journal:  Front Oncol        ISSN: 2234-943X            Impact factor:   6.244


  39 in total

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Authors:  Jeffrey Bradley; Kyounghwa Bae; Noah Choi; Ken Forster; Barry A Siegel; Jacqueline Brunetti; James Purdy; Sergio Faria; Toni Vu; Wade Thorstad; Hak Choy
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-11-13       Impact factor: 7.038

2.  Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non-Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235.

Authors:  Nitin Ohri; Fenghai Duan; Bradley S Snyder; Bo Wei; Mitchell Machtay; Abass Alavi; Barry A Siegel; Douglas W Johnson; Jeffrey D Bradley; Albert DeNittis; Maria Werner-Wasik; Issam El Naqa
Journal:  J Nucl Med       Date:  2016-02-11       Impact factor: 10.057

3.  Pre-treatment 18F-FDG PET-based radiomics predict survival in resected non-small cell lung cancer.

Authors:  H K Ahn; H Lee; S G Kim; S H Hyun
Journal:  Clin Radiol       Date:  2019-03-18       Impact factor: 2.350

4.  FDG-PET as a "metabolic biopsy" tool in non-lung lesions with indeterminate biopsy.

Authors:  A D Beggs; S F Hain; K M Curran; M J O'Doherty
Journal:  Eur J Nucl Med Mol Imaging       Date:  2002-02-27       Impact factor: 9.236

5.  Computed tomography-based anatomic assessment overestimates local tumor recurrence in patients with mass-like consolidation after stereotactic body radiotherapy for early-stage non-small cell lung cancer.

Authors:  Neal E Dunlap; Wensha Yang; Alyson McIntosh; Ke Sheng; Stanley H Benedict; Paul W Read; James M Larner
Journal:  Int J Radiat Oncol Biol Phys       Date:  2012-08-14       Impact factor: 7.038

6.  Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group.

Authors:  H Young; R Baum; U Cremerius; K Herholz; O Hoekstra; A A Lammertsma; J Pruim; P Price
Journal:  Eur J Cancer       Date:  1999-12       Impact factor: 9.162

7.  Tumor hypoxia imaging with [F-18] fluoromisonidazole positron emission tomography in head and neck cancer.

Authors:  Joseph G Rajendran; David L Schwartz; Janet O'Sullivan; Lanell M Peterson; Patrick Ng; Jeffrey Scharnhorst; John R Grierson; Kenneth A Krohn
Journal:  Clin Cancer Res       Date:  2006-09-15       Impact factor: 12.531

8.  Assessing the usefulness of 18F-fluorodeoxyglucose PET-CT scan after stereotactic body radiotherapy for early-stage non-small cell lung cancer.

Authors:  Nicholas J Pastis; Travis J Greer; Nichole T Tanner; Amy E Wahlquist; Leonie L Gordon; Anand K Sharma; Nicholas C Koch; Gerard A Silvestri
Journal:  Chest       Date:  2014-08       Impact factor: 9.410

9.  Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer.

Authors:  Wen Yu; Chad Tang; Brian P Hobbs; Xiao Li; Eugene J Koay; Ignacio I Wistuba; Boris Sepesi; Carmen Behrens; Jaime Rodriguez Canales; Edwin Roger Parra Cuentas; Jeremy J Erasmus; Laurence E Court; Joe Y Chang
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-11-15       Impact factor: 7.038

10.  Deep segmentation networks predict survival of non-small cell lung cancer.

Authors:  Stephen Baek; Yusen He; Bryan G Allen; John M Buatti; Brian J Smith; Ling Tong; Zhiyu Sun; Jia Wu; Maximilian Diehn; Billy W Loo; Kristin A Plichta; Steven N Seyedin; Maggie Gannon; Katherine R Cabel; Yusung Kim; Xiaodong Wu
Journal:  Sci Rep       Date:  2019-11-21       Impact factor: 4.379

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  1 in total

1.  Dynamic PET Imaging Using Dual Texture Features.

Authors:  Zhanglei Ouyang; Shujun Zhao; Zhaoping Cheng; Yanhua Duan; Zixiang Chen; Na Zhang; Dong Liang; Zhanli Hu
Journal:  Front Comput Neurosci       Date:  2022-01-07       Impact factor: 2.380

  1 in total

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