Literature DB >> 27046074

Early-Stage Non-Small Cell Lung Cancer: Quantitative Imaging Characteristics of (18)F Fluorodeoxyglucose PET/CT Allow Prediction of Distant Metastasis.

Jia Wu1, Todd Aguilera1, David Shultz1, Madhu Gudur1, Daniel L Rubin1, Billy W Loo1, Maximilian Diehn1, Ruijiang Li1.   

Abstract

Purpose To identify quantitative imaging biomarkers at fluorine 18 ((18)F) positron emission tomography (PET) for predicting distant metastasis in patients with early-stage non-small cell lung cancer (NSCLC). Materials and Methods In this institutional review board-approved HIPAA-compliant retrospective study, the pretreatment (18)F fluorodeoxyglucose PET images in 101 patients treated with stereotactic ablative radiation therapy from 2005 to 2013 were analyzed. Data for 70 patients who were treated before 2011 were used for discovery purposes, while data from the remaining 31 patients were used for independent validation. Quantitative PET imaging characteristics including statistical, histogram-related, morphologic, and texture features were analyzed, from which 35 nonredundant and robust features were further evaluated. Cox proportional hazards regression model coupled with the least absolute shrinkage and selection operator was used to predict distant metastasis. Whether histologic type provided complementary value to imaging by combining both in a single prognostic model was also assessed. Results The optimal prognostic model included two image features that allowed quantification of intratumor heterogeneity and peak standardized uptake value. In the independent validation cohort, this model showed a concordance index of 0.71, which was higher than those of the maximum standardized uptake value and tumor volume, with concordance indexes of 0.67 and 0.64, respectively. The prognostic model also allowed separation of groups with low and high risk for developing distant metastasis (hazard ratio, 4.8; P = .0498, log-rank test), which compared favorably with maximum standardized uptake value and tumor volume (hazard ratio, 1.5 and 2.0, respectively; P = .73 and 0.54, log-rank test, respectively). When combined with histologic types, the prognostic power was further improved (hazard ratio, 6.9; P = .0289, log-rank test; and concordance index, 0.80). Conclusion PET imaging characteristics associated with distant metastasis that could potentially help practitioners to tailor appropriate therapy for individual patients with early-stage NSCLC were identified. (©) RSNA, 2016 Online supplemental material is available for this article.

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Year:  2016        PMID: 27046074      PMCID: PMC5047129          DOI: 10.1148/radiol.2016151829

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  34 in total

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Authors:  Robert Timmerman; Rebecca Paulus; James Galvin; Jeffrey Michalski; William Straube; Jeffrey Bradley; Achilles Fakiris; Andrea Bezjak; Gregory Videtic; David Johnstone; Jack Fowler; Elizabeth Gore; Hak Choy
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2.  Prognostic value of metabolic tumor burden on 18F-FDG PET in nonsurgical patients with non-small cell lung cancer.

Authors:  Shengri Liao; Bill C Penney; Kristen Wroblewski; Hao Zhang; Cassie A Simon; Rony Kampalath; Ming-Chi Shih; Naoko Shimada; Sheng Chen; Ravi Salgia; Daniel E Appelbaum; Kenji Suzuki; Chin-Tu Chen; Yonglin Pu
Journal:  Eur J Nucl Med Mol Imaging       Date:  2011-09-23       Impact factor: 9.236

3.  Pretreatment [18F]-fluoro-2-deoxy-glucose positron emission tomography maximum standardized uptake value as predictor of distant metastasis in early-stage non-small cell lung cancer treated with definitive radiation therapy: rethinking the role of positron emission tomography in personalizing treatment based on risk status.

Authors:  Vimoj J Nair; Robert MacRae; Abby Sirisegaram; Jason R Pantarotto
Journal:  Int J Radiat Oncol Biol Phys       Date:  2014-02-01       Impact factor: 7.038

4.  Four-dimensional (4D) PET/CT imaging of the thorax.

Authors:  S A Nehmeh; Y E Erdi; T Pan; A Pevsner; K E Rosenzweig; E Yorke; G S Mageras; H Schoder; Phil Vernon; O Squire; H Mostafavi; S M Larson; J L Humm
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5.  Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival.

Authors:  Balaji Ganeshan; Elleny Panayiotou; Kate Burnand; Sabina Dizdarevic; Ken Miles
Journal:  Eur Radiol       Date:  2011-11-17       Impact factor: 5.315

6.  Prognostic PET 18F-FDG uptake imaging features are associated with major oncogenomic alterations in patients with resected non-small cell lung cancer.

Authors:  Viswam S Nair; Olivier Gevaert; Guido Davidzon; Sandy Napel; Edward E Graves; Chuong D Hoang; Joseph B Shrager; Andrew Quon; Daniel L Rubin; Sylvia K Plevritis
Journal:  Cancer Res       Date:  2012-06-18       Impact factor: 12.701

7.  Regularization Paths for Generalized Linear Models via Coordinate Descent.

Authors:  Jerome Friedman; Trevor Hastie; Rob Tibshirani
Journal:  J Stat Softw       Date:  2010       Impact factor: 6.440

8.  18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort.

Authors:  Mathieu Hatt; Mohamed Majdoub; Martin Vallières; Florent Tixier; Catherine Cheze Le Rest; David Groheux; Elif Hindié; Antoine Martineau; Olivier Pradier; Roland Hustinx; Remy Perdrisot; Remy Guillevin; Issam El Naqa; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2014-12-11       Impact factor: 10.057

9.  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

10.  Glucose metabolism in NSCLC is histology-specific and diverges the prognostic potential of 18FDG-PET for adenocarcinoma and squamous cell carcinoma.

Authors:  Olga C J Schuurbiers; Tineke W H Meijer; Johannes H A M Kaanders; Monika G Looijen-Salamon; Lioe-Fee de Geus-Oei; Miep A van der Drift; Erik H F M van der Heijden; Wim J Oyen; Eric P Visser; Paul N Span; Johan Bussink
Journal:  J Thorac Oncol       Date:  2014-10       Impact factor: 15.609

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  71 in total

1.  External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy.

Authors:  François Lucia; Dimitris Visvikis; Martin Vallières; Marie-Charlotte Desseroit; Omar Miranda; Philippe Robin; Pietro Andrea Bonaffini; Joanne Alfieri; Ingrid Masson; Augustin Mervoyer; Caroline Reinhold; Olivier Pradier; Mathieu Hatt; Ulrike Schick
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-12-07       Impact factor: 9.236

2.  Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis.

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Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-06-25       Impact factor: 9.236

3.  A pilot study using kernelled support tensor machine for distant failure prediction in lung SBRT.

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Journal:  Nucl Med Mol Imaging       Date:  2017-10-20

Review 5.  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

6.  Predictive Role of Temporal Changes in Intratumoral Metabolic Heterogeneity During Palliative Chemotherapy in Patients with Advanced Pancreatic Cancer: A Prospective Cohort Study.

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Journal:  J Nucl Med       Date:  2019-06-14       Impact factor: 10.057

7.  Multi-objective radiomics model for predicting distant failure in lung SBRT.

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8.  Non-invasive radiomics approach potentially predicts non-functioning pituitary adenomas subtypes before surgery.

Authors:  Shuaitong Zhang; Guidong Song; Yali Zang; Jian Jia; Chao Wang; Chuzhong Li; Jie Tian; Di Dong; Yazhuo Zhang
Journal:  Eur Radiol       Date:  2018-03-23       Impact factor: 5.315

Review 9.  Radiomics: from qualitative to quantitative imaging.

Authors:  William Rogers; Sithin Thulasi Seetha; Turkey A G Refaee; Relinde I Y Lieverse; Renée W Y Granzier; Abdalla Ibrahim; Simon A Keek; Sebastian Sanduleanu; Sergey P Primakov; Manon P L Beuque; Damiënne Marcus; Alexander M A van der Wiel; Fadila Zerka; Cary J G Oberije; Janita E van Timmeren; Henry C Woodruff; Philippe Lambin
Journal:  Br J Radiol       Date:  2020-02-26       Impact factor: 3.039

10.  Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.

Authors:  Jia Wu; Guanghua Gong; Yi Cui; Ruijiang Li
Journal:  J Magn Reson Imaging       Date:  2016-04-15       Impact factor: 4.813

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