Literature DB >> 30940529

Integrating Tumor and Nodal Imaging Characteristics at Baseline and Mid-Treatment Computed Tomography Scans to Predict Distant Metastasis in Oropharyngeal Cancer Treated With Concurrent Chemoradiotherapy.

Jia Wu1, Micheal F Gensheimer1, Nasha Zhang2, Fei Han3, Rachel Liang1, Yushen Qian1, Carrie Zhang1, Nancy Fischbein4, Erqi L Pollom1, Beth Beadle1, Quynh-Thu Le1, Ruijiang Li5.   

Abstract

PURPOSE: Prognostic biomarkers of disease relapse are needed for risk-adaptive therapy of oropharyngeal cancer (OPC). This work aims to identify an imaging signature to predict distant metastasis in OPC. METHODS AND MATERIALS: This single-institution retrospective study included 140 patients treated with definitive concurrent chemoradiotherapy, for whom both pre- and midtreatment contrast-enhanced computed tomography (CT) scans were available. Patients were divided into separate training and testing cohorts. Forty-five quantitative image features were extracted to characterize tumor and involved lymph nodes at both time points. By incorporating both imaging and clinicopathological features, a random survival forest (RSF) model was built to predict distant metastasis-free survival (DMFS). The model was optimized via repeated cross-validation in the training cohort and then independently validated in the testing cohort.
RESULTS: The most important features for predicting DMFS were the maximum distance among nodes, maximum distance between tumor and nodes at mid-treatment, and pretreatment tumor sphericity. In the testing cohort, the RSF model achieved good discriminability for DMFS (C-index = 0.73, P = .008), and further divided patients into 2 risk groups with different 2-year DMFS rates: 96.7% versus 67.6%. Similar trends were observed for patients with p16tumors and smoking ≤10 pack-years. The RSF model based on pretreatment CT features alone achieved lower performance (concordance index = 0.68, P = .03).
CONCLUSIONS: Integrating tumor and nodal imaging characteristics at baseline and mid-treatment CT allows prediction of distant metastasis in OPC. The proposed imaging signature requires prospective validation and, if successful, may help identify high-risk human papillomavirus-positive patients who should not be considered for deintensification therapy.
Copyright © 2019 Elsevier Inc. All rights reserved.

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Year:  2019        PMID: 30940529      PMCID: PMC6579673          DOI: 10.1016/j.ijrobp.2019.03.036

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  38 in total

1.  Human papillomavirus and survival of patients with oropharyngeal cancer.

Authors:  K Kian Ang; Jonathan Harris; Richard Wheeler; Randal Weber; David I Rosenthal; Phuc Felix Nguyen-Tân; William H Westra; Christine H Chung; Richard C Jordan; Charles Lu; Harold Kim; Rita Axelrod; C Craig Silverman; Kevin P Redmond; Maura L Gillison
Journal:  N Engl J Med       Date:  2010-06-07       Impact factor: 91.245

2.  Development and validation of a staging system for HPV-related oropharyngeal cancer by the International Collaboration on Oropharyngeal cancer Network for Staging (ICON-S): a multicentre cohort study.

Authors:  Brian O'Sullivan; Shao Hui Huang; Jie Su; Adam S Garden; Erich M Sturgis; Kristina Dahlstrom; Nancy Lee; Nadeem Riaz; Xin Pei; Shlomo A Koyfman; David Adelstein; Brian B Burkey; Jeppe Friborg; Claus A Kristensen; Anita B Gothelf; Frank Hoebers; Bernd Kremer; Ernst-Jan Speel; Daniel W Bowles; David Raben; Sana D Karam; Eugene Yu; Wei Xu
Journal:  Lancet Oncol       Date:  2016-02-27       Impact factor: 41.316

3.  Deintensification candidate subgroups in human papillomavirus-related oropharyngeal cancer according to minimal risk of distant metastasis.

Authors:  Brian O'Sullivan; Shao Hui Huang; Lillian L Siu; John Waldron; Helen Zhao; Bayardo Perez-Ordonez; Ilan Weinreb; John Kim; Jolie Ringash; Andrew Bayley; Laura A Dawson; Andrew Hope; John Cho; Jonathan Irish; Ralph Gilbert; Patrick Gullane; Angela Hui; Fei-Fei Liu; Eric Chen; Wei Xu
Journal:  J Clin Oncol       Date:  2013-01-07       Impact factor: 44.544

4.  CT imaging during treatment improves radiomic models for patients with locally advanced head and neck cancer.

Authors:  Stefan Leger; Alex Zwanenburg; Karoline Pilz; Sebastian Zschaeck; Klaus Zöphel; Jörg Kotzerke; Andreas Schreiber; Daniel Zips; Mechthild Krause; Michael Baumann; Esther G C Troost; Christian Richter; Steffen Löck
Journal:  Radiother Oncol       Date:  2018-08-04       Impact factor: 6.280

5.  External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma.

Authors:  Ralph T H Leijenaar; Sara Carvalho; Frank J P Hoebers; Hugo J W L Aerts; Wouter J C van Elmpt; Shao Hui Huang; Biu Chan; John N Waldron; Brian O'sullivan; Philippe Lambin
Journal:  Acta Oncol       Date:  2015-08-12       Impact factor: 4.089

6.  Improving the prediction of overall survival for head and neck cancer patients using image biomarkers in combination with clinical parameters.

Authors:  Tian-Tian Zhai; Lisanne V van Dijk; Bao-Tian Huang; Zhi-Xiong Lin; Cássia O Ribeiro; Charlotte L Brouwer; Sjoukje F Oosting; Gyorgy B Halmos; Max J H Witjes; Johannes A Langendijk; Roel J H M Steenbakkers; Nanna M Sijtsema
Journal:  Radiother Oncol       Date:  2017-07-29       Impact factor: 6.280

7.  Phase 2 Trial of De-intensified Chemoradiation Therapy for Favorable-Risk Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma.

Authors:  Bhishamjit S Chera; Robert J Amdur; Joel Tepper; Bahjat Qaqish; Rebecca Green; Shannon L Aumer; Neil Hayes; Jared Weiss; Juneko Grilley-Olson; Adam Zanation; Trevor Hackman; William Funkhouser; Nathan Sheets; Mark Weissler; William Mendenhall
Journal:  Int J Radiat Oncol Biol Phys       Date:  2015-08-22       Impact factor: 7.038

8.  Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer.

Authors:  Jia Wu; Xuejie Li; Xiaodong Teng; Daniel L Rubin; Sandy Napel; Bruce L Daniel; Ruijiang Li
Journal:  Breast Cancer Res       Date:  2018-09-03       Impact factor: 6.466

9.  Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach.

Authors:  Hugo J W L Aerts; Emmanuel Rios Velazquez; Ralph T H Leijenaar; Chintan Parmar; Patrick Grossmann; Sara Carvalho; Sara Cavalho; Johan Bussink; René Monshouwer; Benjamin Haibe-Kains; Derek Rietveld; Frank Hoebers; Michelle M Rietbergen; C René Leemans; Andre Dekker; John Quackenbush; Robert J Gillies; Philippe Lambin
Journal:  Nat Commun       Date:  2014-06-03       Impact factor: 14.919

10.  Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer.

Authors:  Chintan Parmar; Ralph T H Leijenaar; Patrick Grossmann; Emmanuel Rios Velazquez; Johan Bussink; Derek Rietveld; Michelle M Rietbergen; Benjamin Haibe-Kains; Philippe Lambin; Hugo J W L Aerts
Journal:  Sci Rep       Date:  2015-06-05       Impact factor: 4.379

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  8 in total

1.  Tumor Subregion Evolution-Based Imaging Features to Assess Early Response and Predict Prognosis in Oropharyngeal Cancer.

Authors:  Jia Wu; Michael F Gensheimer; Nasha Zhang; Meiying Guo; Rachel Liang; Carrie Zhang; Nancy Fischbein; Erqi L Pollom; Beth Beadle; Quynh-Thu Le; Ruijiang Li
Journal:  J Nucl Med       Date:  2019-08-16       Impact factor: 10.057

2.  Breast MRI radiomics for the pretreatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients.

Authors:  Karen Drukker; Alexandra Edwards; Christopher Doyle; John Papaioannou; Kirti Kulkarni; Maryellen L Giger
Journal:  J Med Imaging (Bellingham)       Date:  2019-09-30

Review 3.  Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy.

Authors:  Jia Wu; Aaron T Mayer; Ruijiang Li
Journal:  Semin Cancer Biol       Date:  2020-12-05       Impact factor: 17.012

4.  Radiomics features of the primary tumor fail to improve prediction of overall survival in large cohorts of CT- and PET-imaged head and neck cancer patients.

Authors:  Rachel B Ger; Shouhao Zhou; Baher Elgohari; Hesham Elhalawani; Dennis M Mackin; Joseph G Meier; Callistus M Nguyen; Brian M Anderson; Casey Gay; Jing Ning; Clifton D Fuller; Heng Li; Rebecca M Howell; Rick R Layman; Osama Mawlawi; R Jason Stafford; Hugo Aerts; Laurence E Court
Journal:  PLoS One       Date:  2019-09-19       Impact factor: 3.240

5.  Machine Learning for Head and Neck Cancer: A Safe Bet?-A Clinically Oriented Systematic Review for the Radiation Oncologist.

Authors:  Stefania Volpe; Matteo Pepa; Mattia Zaffaroni; Federica Bellerba; Riccardo Santamaria; Giulia Marvaso; Lars Johannes Isaksson; Sara Gandini; Anna Starzyńska; Maria Cristina Leonardi; Roberto Orecchia; Daniela Alterio; Barbara Alicja Jereczek-Fossa
Journal:  Front Oncol       Date:  2021-11-18       Impact factor: 6.244

6.  Artificial intelligence in oncologic imaging.

Authors:  Melissa M Chen; Admir Terzic; Anton S Becker; Jason M Johnson; Carol C Wu; Max Wintermark; Christoph Wald; Jia Wu
Journal:  Eur J Radiol Open       Date:  2022-09-29

7.  Precision association of lymphatic disease spread with radiation-associated toxicity in oropharyngeal squamous carcinomas.

Authors:  Andrew Wentzel; Timothy Luciani; Lisanne V van Dijk; Nicolette Taku; Baher Elgohari; Abdallah S R Mohamed; Guadalupe Canahuate; Clifton D Fuller; David M Vock; G Elisabeta Marai
Journal:  Radiother Oncol       Date:  2021-06-11       Impact factor: 6.901

8.  Early response evaluation using primary tumor and nodal imaging features to predict progression-free survival of locally advanced non-small cell lung cancer.

Authors:  Nasha Zhang; Rachel Liang; Michael F Gensheimer; Meiying Guo; Hui Zhu; Jinming Yu; Maximilian Diehn; Bill W Loo; Ruijiang Li; Jia Wu
Journal:  Theranostics       Date:  2020-09-23       Impact factor: 11.556

  8 in total

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