Literature DB >> 25170645

Noninvasive risk stratification of lung adenocarcinoma using quantitative computed tomography.

Sushravya Raghunath1, Fabien Maldonado, Srinivasan Rajagopalan, Ronald A Karwoski, Zackary S DePew, Brian J Bartholmai, Tobias Peikert, Richard A Robb.   

Abstract

INTRODUCTION: Lung cancer remains the leading cause of cancer-related deaths in the United States and worldwide. Adenocarcinoma is the most common type of lung cancer and encompasses lesions with widely variable clinical outcomes. In the absence of noninvasive risk stratification, individualized patient management remains challenging. Consequently a subgroup of pulmonary nodules of the lung adenocarcinoma spectrum is likely treated more aggressively than necessary.
METHODS: Consecutive patients with surgically resected pulmonary nodules of the lung adenocarcinoma spectrum (lesion size ≤3 cm, 2006-2009) and available presurgical high-resolution computed tomography (HRCT) imaging were identified at Mayo Clinic Rochester. All cases were classified using an unbiased Computer-Aided Nodule Assessment and Risk Yield (CANARY) approach based on the quantification of presurgical HRCT characteristics. CANARY-based classification was independently correlated to postsurgical progression-free survival.
RESULTS: CANARY analysis of 264 consecutive patients identified three distinct subgroups. Independent comparisons of 5-year disease-free survival (DFS) between these subgroups demonstrated statistically significant differences in 5-year DFS, 100%, 72.7%, and 51.4%, respectively (p = 0.0005).
CONCLUSIONS: Noninvasive CANARY-based risk stratification identifies subgroups of patients with pulmonary nodules of the adenocarcinoma spectrum characterized by distinct clinical outcomes. This technique may ultimately improve the current expert opinion-based approach to the management of these lesions by facilitating individualized patient management.

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Year:  2014        PMID: 25170645      PMCID: PMC4254143          DOI: 10.1097/JTO.0000000000000319

Source DB:  PubMed          Journal:  J Thorac Oncol        ISSN: 1556-0864            Impact factor:   15.609


  40 in total

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2.  Stage classification and prediction of prognosis: difference between accountants and speculators.

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3.  Overdiagnosis in lung cancer screening with low-dose computed tomography.

Authors:  Yuichi Takiguchi; Ikuo Sekine; Shunichiro Iwasawa
Journal:  J Thorac Oncol       Date:  2013-11       Impact factor: 15.609

4.  Lung cancer-celebrating progress and acknowledging challenges.

Authors:  Alex A Adjei
Journal:  J Thorac Oncol       Date:  2013-11       Impact factor: 15.609

5.  Noninvasive characterization of the histopathologic features of pulmonary nodules of the lung adenocarcinoma spectrum using computer-aided nodule assessment and risk yield (CANARY)--a pilot study.

Authors:  Fabien Maldonado; Jennifer M Boland; Sushravya Raghunath; Marie Christine Aubry; Brian J Bartholmai; Mariza Deandrade; Thomas E Hartman; Ronald A Karwoski; Srinivasan Rajagopalan; Anne-Marie Sykes; Ping Yang; Eunhee S Yi; Richard A Robb; Tobias Peikert
Journal:  J Thorac Oncol       Date:  2013-04       Impact factor: 15.609

Review 6.  Benefits and harms of CT screening for lung cancer: a systematic review.

Authors:  Peter B Bach; Joshua N Mirkin; Thomas K Oliver; Christopher G Azzoli; Donald A Berry; Otis W Brawley; Tim Byers; Graham A Colditz; Michael K Gould; James R Jett; Anita L Sabichi; Rebecca Smith-Bindman; Douglas E Wood; Amir Qaseem; Frank C Detterbeck
Journal:  JAMA       Date:  2012-06-13       Impact factor: 56.272

7.  Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society.

Authors:  David P Naidich; Alexander A Bankier; Heber MacMahon; Cornelia M Schaefer-Prokop; Massimo Pistolesi; Jin Mo Goo; Paolo Macchiarini; James D Crapo; Christian J Herold; John H Austin; William D Travis
Journal:  Radiology       Date:  2012-10-15       Impact factor: 11.105

Review 8.  American Cancer Society lung cancer screening guidelines.

Authors:  Richard Wender; Elizabeth T H Fontham; Ermilo Barrera; Graham A Colditz; Timothy R Church; David S Ettinger; Ruth Etzioni; Christopher R Flowers; G Scott Gazelle; Douglas K Kelsey; Samuel J LaMonte; James S Michaelson; Kevin C Oeffinger; Ya-Chen Tina Shih; Daniel C Sullivan; William Travis; Louise Walter; Andrew M D Wolf; Otis W Brawley; Robert A Smith
Journal:  CA Cancer J Clin       Date:  2013-01-11       Impact factor: 508.702

9.  Estimating overdiagnosis in low-dose computed tomography screening for lung cancer: a cohort study.

Authors:  Giulia Veronesi; Patrick Maisonneuve; Massimo Bellomi; Cristiano Rampinelli; Iara Durli; Raffaella Bertolotti; Lorenzo Spaggiari
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10.  Natural history of pure ground-glass opacity lung nodules detected by low-dose CT scan.

Authors:  Boksoon Chang; Jung Hye Hwang; Yoon-Ho Choi; Man Pyo Chung; Hojoong Kim; O Jung Kwon; Ho Yun Lee; Kyung Soo Lee; Young Mog Shim; Joungho Han; Sang-Won Um
Journal:  Chest       Date:  2013-01       Impact factor: 9.410

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  19 in total

1.  Appreciating the shades of gray: a case for Computer-Aided Nodule Assessment and Risk Yield (CANARY)-based risk stratification of lung adenocarcinomas.

Authors:  Fabien Maldonado; Tobias Peikert; Brian J Bartholmai; Srinivasan Rajagopalan; Ronald A Karwoski
Journal:  J Thorac Dis       Date:  2016-10       Impact factor: 2.895

Review 2.  The Pursuit of Noninvasive Diagnosis of Lung Cancer.

Authors:  Thomas Atwater; Christine M Cook; Pierre P Massion
Journal:  Semin Respir Crit Care Med       Date:  2016-10-12       Impact factor: 3.119

3.  The bell tolls for indeterminant lung nodules: computer-aided nodule assessment and risk yield (CANARY) has the wrong tune.

Authors:  David O Wilson; Jiantao Pu
Journal:  J Thorac Dis       Date:  2016-08       Impact factor: 2.895

Review 4.  Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening.

Authors:  Chara E Rydzak; Samuel G Armato; Ricardo S Avila; James L Mulshine; David F Yankelevitz; David S Gierada
Journal:  Br J Radiol       Date:  2017-10-27       Impact factor: 3.039

5.  Morphologic characteristics of pulmonary adenocarcinomas manifesting as pure ground-glass nodules on CT.

Authors:  Benedikt H Heidinger; Kevin R Anderson; Ursula Nemec; Daniel B Costa; Sidhu P Gangadharan; Paul A VanderLaan; Alexander A Bankier
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6.  While size matters-advanced "Radiomics" remain promising for the clinical management of ground glass opacities.

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7.  Added Value of Computer-aided CT Image Features for Early Lung Cancer Diagnosis with Small Pulmonary Nodules: A Matched Case-Control Study.

Authors:  Peng Huang; Seyoun Park; Rongkai Yan; Junghoon Lee; Linda C Chu; Cheng T Lin; Amira Hussien; Joshua Rathmell; Brett Thomas; Chen Chen; Russell Hales; David S Ettinger; Malcolm Brock; Ping Hu; Elliot K Fishman; Edward Gabrielson; Stephen Lam
Journal:  Radiology       Date:  2017-09-05       Impact factor: 11.105

Review 8.  Computer Aided Nodule Analysis and Risk Yield (CANARY) characterization of adenocarcinoma: radiologic biopsy, risk stratification and future directions.

Authors:  Ryan Clay; Srinivasan Rajagopalan; Ronald Karwoski; Fabien Maldonado; Tobias Peikert; Brian Bartholmai
Journal:  Transl Lung Cancer Res       Date:  2018-06

9.  Noninvasive Computed Tomography-based Risk Stratification of Lung Adenocarcinomas in the National Lung Screening Trial.

Authors:  Fabien Maldonado; Fenghai Duan; Sushravya M Raghunath; Srinivasan Rajagopalan; Ronald A Karwoski; Kavita Garg; Erin Greco; Hrudaya Nath; Richard A Robb; Brian J Bartholmai; Tobias Peikert
Journal:  Am J Respir Crit Care Med       Date:  2015-09-15       Impact factor: 21.405

10.  Computer-Aided Nodule Assessment and Risk Yield Risk Management of Adenocarcinoma: The Future of Imaging?

Authors:  Finbar Foley; Srinivasan Rajagopalan; Sushravya M Raghunath; Jennifer M Boland; Ronald A Karwoski; Fabien Maldonado; Brian J Bartholmai; Tobias Peikert
Journal:  Semin Thorac Cardiovasc Surg       Date:  2016-01-08
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