Literature DB >> 23204495

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

Gary J R Cook1, Connie Yip, Muhammad Siddique, Vicky Goh, Sugama Chicklore, Arunabha Roy, Paul Marsden, Shahreen Ahmad, David Landau.   

Abstract

UNLABELLED: There is evidence in some solid tumors that textural features of tumoral uptake in (18)F-FDG PET images are associated with response to chemoradiotherapy and survival. We have investigated whether a similar relationship exists in non-small cell lung cancer (NSCLC).
METHODS: Fifty-three patients (mean age, 65.8 y; 31 men, 22 women) with NSCLC treated with chemoradiotherapy underwent pretreatment (18)F-FDG PET/CT scans. Response was assessed by CT Response Evaluation Criteria in Solid Tumors (RECIST) at 12 wk. Overall survival (OS), progression-free survival (PFS), and local PFS (LPFS) were recorded. Primary tumor texture was measured by the parameters coarseness, contrast, busyness, and complexity. The following parameters were also derived from the PET data: primary tumor standardized uptake values (SUVs) (mean SUV, maximum SUV, and peak SUV), metabolic tumor volume, and total lesion glycolysis.
RESULTS: Compared with nonresponders, RECIST responders showed lower coarseness (mean, 0.012 vs. 0.027; P = 0.004) and higher contrast (mean, 0.11 vs. 0.044; P = 0.002) and busyness (mean, 0.76 vs. 0.37; P = 0.027). Neither complexity nor any of the SUV parameters predicted RECIST response. By Kaplan-Meier analysis, OS, PFS, and LPFS were lower in patients with high primary tumor coarseness (median, 21.1 mo vs. not reached, P = 0.003; 12.6 vs. 25.8 mo, P = 0.002; and 12.9 vs. 20.5 mo, P = 0.016, respectively). Tumor coarseness was an independent predictor of OS on multivariable analysis. Contrast and busyness did not show significant associations with OS (P = 0.075 and 0.059, respectively), but PFS and LPFS were longer in patients with high levels of each (for contrast: median of 20.5 vs. 12.6 mo, P = 0.015, and median not reached vs. 24 mo, P = 0.02; and for busyness: median of 20.5 vs. 12.6 mo, P = 0.01, and median not reached vs. 24 mo, P = 0.006). Neither complexity nor any of the SUV parameters showed significant associations with the survival parameters.
CONCLUSION: In NSCLC, baseline (18)F-FDG PET scan uptake showing abnormal texture as measured by coarseness, contrast, and busyness is associated with nonresponse to chemoradiotherapy by RECIST and with poorer prognosis. Measurement of tumor metabolic heterogeneity with these parameters may provide indices that can be used to stratify patients in clinical trials for lung cancer chemoradiotherapy.

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Year:  2012        PMID: 23204495     DOI: 10.2967/jnumed.112.107375

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  183 in total

1.  Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards.

Authors:  Matthew J Nyflot; Fei Yang; Darrin Byrd; Stephen R Bowen; George A Sandison; Paul E Kinahan
Journal:  J Med Imaging (Bellingham)       Date:  2015-08-05

Review 2.  Computerized PET/CT image analysis in the evaluation of tumour response to therapy.

Authors:  W Lu; J Wang; H H Zhang
Journal:  Br J Radiol       Date:  2015-02-27       Impact factor: 3.039

3.  A Pilot Study of Texture Analysis of Primary Tumor [18F]FDG Uptake to Predict Recurrence in Surgically Treated Patients with Non-small Cell Lung Cancer.

Authors:  Masatoyo Nakajo; Megumi Jinguji; Tetsuya Shinaji; Masaya Aoki; Atsushi Tani; Yoshiaki Nakabeppu; Masayuki Nakajo; Masami Sato; Takashi Yoshiura
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

4.  [18]Fluorodeoxyglucose Positron Emission Tomography for the Textural Features of Cervical Cancer Associated with Lymph Node Metastasis and Histological Type.

Authors:  Wei-Chih Shen; Shang-Wen Chen; Ji-An Liang; Te-Chun Hsieh; Kuo-Yang Yen; Chia-Hung Kao
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-04-14       Impact factor: 9.236

5.  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

6.  Comprehensive Computed Tomography Radiomics Analysis of Lung Adenocarcinoma for Prognostication.

Authors:  Geewon Lee; Hyunjin Park; Insuk Sohn; Seung-Hak Lee; So Hee Song; Hyeseung Kim; Kyung Soo Lee; Young Mog Shim; Ho Yun Lee
Journal:  Oncologist       Date:  2018-04-05

7.  Treatment-related changes in neuroendocrine tumors as assessed by textural features derived from 68Ga-DOTATOC PET/MRI with simultaneous acquisition of apparent diffusion coefficient.

Authors:  Manuel Weber; Lukas Kessler; Benedikt Schaarschmidt; Wolfgang Peter Fendler; Harald Lahner; Gerald Antoch; Lale Umutlu; Ken Herrmann; Christoph Rischpler
Journal:  BMC Cancer       Date:  2020-04-16       Impact factor: 4.430

Review 8.  Clinical applications of textural analysis in non-small cell lung cancer.

Authors:  Iain Phillips; Mazhar Ajaz; Veni Ezhil; Vineet Prakash; Sheaka Alobaidli; Sarah J McQuaid; Christopher South; James Scuffham; Andrew Nisbet; Philip Evans
Journal:  Br J Radiol       Date:  2017-10-27       Impact factor: 3.039

9.  Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer.

Authors:  Sara Carvalho; Ralph T H Leijenaar; Emmanuel Rios Velazquez; Cary Oberije; Chintan Parmar; Wouter van Elmpt; Bart Reymen; Esther G C Troost; Michel Oellers; Andre Dekker; Robert Gillies; Hugo J W L Aerts; Philippe Lambin
Journal:  Acta Oncol       Date:  2013-09-09       Impact factor: 4.089

Review 10.  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

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