Literature DB >> 19969253

The use of volumetric CT as an imaging biomarker in lung cancer.

Andrew J Buckler1, James L Mulshine, Ronald Gottlieb, Binsheng Zhao, P David Mozley, Lawrence Schwartz.   

Abstract

RATIONALE AND
OBJECTIVES: Lung cancer is the leading cause of cancer death in the United States. Mortality outcomes have improved only modestly over the past 30 years. There is intense focus on the development of better treatments for lung cancer. Major issues include the cost and time duration of the clinical trials required to establish the utility of a drug so that it can be formally approved by regulatory agencies. In clinical settings, biomarkers that accelerate assessments of responses to treatment could benefit patients by providing earlier diagnoses of progressive disease, particularly when there are multiple options for treatment, and the effects of toxicity from one treatment tend to limit the ability to administer the next line of therapy.
MATERIALS AND METHODS: Quantifying longitudinal changes in tumor volumes using computed tomography could eventually become a more useful surrogate endpoint for assessing tumor responses or progression events than simple unidimensional measurements.
RESULTS: The authors review the historical development of response measurements in lung cancer, set out the medical context for specifying volumetric imaging requirements and goals, compare volumetric technique to conventional methods, and identify the imaging profiles being pursued.
CONCLUSION: The Quantitative Imaging Biomarkers Alliance is investigating volumetric computed tomographic acquisition and analytic methods to increase the analytic power per subject enrolled in clinical trials to reduce the number of total subjects needed or shorten the length of time an individual needs to be followed to reliably establish drug response.

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Year:  2010        PMID: 19969253     DOI: 10.1016/j.acra.2009.07.030

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  16 in total

1.  A mathematical simulation to assess variability in lung nodule size measurement associated with nodule-slice position.

Authors:  Krishna Juluru; Noor Al Khori; Sha He; Amy Kuceyeski; John Eng
Journal:  J Digit Imaging       Date:  2015-06       Impact factor: 4.056

Review 2.  Can oncology recapitulate paleontology? Lessons from species extinctions.

Authors:  Viola Walther; Crispin T Hiley; Darryl Shibata; Charles Swanton; Paul E Turner; Carlo C Maley
Journal:  Nat Rev Clin Oncol       Date:  2015-02-17       Impact factor: 66.675

Review 3.  A novel knowledge representation framework for the statistical validation of quantitative imaging biomarkers.

Authors:  Andrew J Buckler; David Paik; Matt Ouellette; Jovanna Danagoulian; Gary Wernsing; Baris E Suzek
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

Review 4.  Drug development and clinical trials--the path to an approved cancer drug.

Authors:  Eric H Rubin; D Gary Gilliland
Journal:  Nat Rev Clin Oncol       Date:  2012-02-28       Impact factor: 66.675

5.  Measurement of tumor volumes improves RECIST-based response assessments in advanced lung cancer.

Authors:  P David Mozley; Claus Bendtsen; Binsheng Zhao; Lawrence H Schwartz; Matthias Thorn; Yuanxin Rong; Luduan Zhang; Andrea Perrone; René Korn; Andrew J Buckler
Journal:  Transl Oncol       Date:  2012-02-01       Impact factor: 4.243

6.  Lung Cancer Workshop XI: Tobacco-Induced Disease: Advances in Policy, Early Detection and Management.

Authors:  James L Mulshine; Rick Avila; David Yankelevitz; Thomas M Baer; Raul San Jose Estépar; Laurie Fenton Ambrose; Carolyn R Aldigé
Journal:  J Thorac Oncol       Date:  2015-05       Impact factor: 15.609

7.  Three-dimensional Radiologic Assessment of Chemotherapy Response in Ewing Sarcoma Can Be Used to Predict Clinical Outcome.

Authors:  Maryam Aghighi; Justin Boe; Jarrett Rosenberg; Rie Von Eyben; Rakhee S Gawande; Philippe Petit; Tarsheen K Sethi; Jeremy Sharib; Neyssa M Marina; Steven G DuBois; Heike E Daldrup-Link
Journal:  Radiology       Date:  2016-03-16       Impact factor: 11.105

Review 8.  Clinical utility of quantitative imaging.

Authors:  Andrew B Rosenkrantz; Mishal Mendiratta-Lala; Brian J Bartholmai; Dhakshinamoorthy Ganeshan; Richard G Abramson; Kirsteen R Burton; John-Paul J Yu; Ernest M Scalzetti; Thomas E Yankeelov; Rathan M Subramaniam; Leon Lenchik
Journal:  Acad Radiol       Date:  2014-10-22       Impact factor: 3.173

9.  Quantitative CT characterization of pediatric lung development using routine clinical imaging.

Authors:  Jill M Stein; Laura L Walkup; Alan S Brody; Robert J Fleck; Jason C Woods
Journal:  Pediatr Radiol       Date:  2016-08-30

10.  Quantifying the margin sharpness of lesions on radiological images for content-based image retrieval.

Authors:  Jiajing Xu; Sandy Napel; Hayit Greenspan; Christopher F Beaulieu; Neeraj Agrawal; Daniel Rubin
Journal:  Med Phys       Date:  2012-09       Impact factor: 4.071

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