Literature DB >> 19332844

Noncalcified lung nodules: volumetric assessment with thoracic CT.

Marios A Gavrielides1, Lisa M Kinnard, Kyle J Myers, Nicholas Petrick.   

Abstract

Lung nodule volumetry is used for nodule diagnosis, as well as for monitoring tumor response to therapy. Volume measurement precision and accuracy depend on a number of factors, including image-acquisition and reconstruction parameters, nodule characteristics, and the performance of algorithms for nodule segmentation and volume estimation. The purpose of this article is to provide a review of published studies relevant to the computed tomographic (CT) volumetric analysis of lung nodules. A number of underexamined areas of research regarding volumetric accuracy are identified, including the measurement of nonsolid nodules, the effects of pitch and section overlap, and the effect of respiratory motion. The need for public databases of phantom scans, as well as of clinical data, is discussed. The review points to the need for continued research to examine volumetric accuracy as a function of a multitude of interrelated variables involved in the assessment of lung nodules. Understanding and quantifying the sources of volumetric measurement error in the assessment of lung nodules with CT would be a first step toward the development of methods to minimize that error through system improvements and to correctly account for any remaining error.

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Year:  2009        PMID: 19332844      PMCID: PMC2663581          DOI: 10.1148/radiol.2511071897

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


  52 in total

1.  Method for quantifying volumetric lesion change in interval liver CT examinations.

Authors:  Chuck Meyer; Hyunjin Park; James M Balter; Peyton H Bland
Journal:  IEEE Trans Med Imaging       Date:  2003-06       Impact factor: 10.048

2.  Small pulmonary nodules: volume measurement at chest CT--phantom study.

Authors:  Jane P Ko; Henry Rusinek; Erika L Jacobs; James S Babb; Margrit Betke; Georgeann McGuinness; David P Naidich
Journal:  Radiology       Date:  2003-09       Impact factor: 11.105

3.  Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images.

Authors:  William J Kostis; Anthony P Reeves; David F Yankelevitz; Claudia I Henschke
Journal:  IEEE Trans Med Imaging       Date:  2003-10       Impact factor: 10.048

4.  Characterization of small nodules by automatic segmentation of X-ray computed tomography images.

Authors:  Peng Tao; Friederike Griess; Yelena Lvov; Mikhail Mineyev; Binsheng Zhao; David Levin; Leon Kaufman
Journal:  J Comput Assist Tomogr       Date:  2004 May-Jun       Impact factor: 1.826

5.  Growth rate of small lung cancers detected on mass CT screening.

Authors:  M Hasegawa; S Sone; S Takashima; F Li; Z G Yang; Y Maruyama; T Watanabe
Journal:  Br J Radiol       Date:  2000-12       Impact factor: 3.039

6.  CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules.

Authors:  Claudia I Henschke; David F Yankelevitz; Rosna Mirtcheva; Georgeann McGuinness; Dorothy McCauley; Olli S Miettinen
Journal:  AJR Am J Roentgenol       Date:  2002-05       Impact factor: 3.959

7.  Effect of varying CT section width on volumetric measurement of lung tumors and application of compensatory equations.

Authors:  Helen T Winer-Muram; S Gregory Jennings; Cristopher A Meyer; Yun Liang; Alex M Aisen; Robert D Tarver; Ronald C McGarry
Journal:  Radiology       Date:  2003-10       Impact factor: 11.105

Review 8.  Assessment methodologies and statistical issues for computer-aided diagnosis of lung nodules in computed tomography: contemporary research topics relevant to the lung image database consortium.

Authors:  Lori E Dodd; Robert F Wagner; Samuel G Armato; Michael F McNitt-Gray; Sergey Beiden; Heang-Ping Chan; David Gur; Geoffrey McLennan; Charles E Metz; Nicholas Petrick; Berkman Sahiner; Jim Sayre
Journal:  Acad Radiol       Date:  2004-04       Impact factor: 3.173

9.  Pulmonary nodules: Interscan variability of semiautomated volume measurements with multisection CT-- influence of inspiration level, nodule size, and segmentation performance.

Authors:  Hester A Gietema; Cornelia M Schaefer-Prokop; Willem P T M Mali; Gerard Groenewegen; Mathias Prokop
Journal:  Radiology       Date:  2007-10-08       Impact factor: 11.105

10.  Interobserver and intraobserver variability in measurement of non-small-cell carcinoma lung lesions: implications for assessment of tumor response.

Authors:  Jeremy J Erasmus; Gregory W Gladish; Lyle Broemeling; Bradley S Sabloff; Mylene T Truong; Roy S Herbst; Reginald F Munden
Journal:  J Clin Oncol       Date:  2003-07-01       Impact factor: 44.544

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  57 in total

Review 1.  Imaging of lung cancer in the era of molecular medicine.

Authors:  Mizuki Nishino; David M Jackman; Hiroto Hatabu; Pasi A Jänne; Bruce E Johnson; Annick D Van den Abbeele
Journal:  Acad Radiol       Date:  2011-01-28       Impact factor: 3.173

Review 2.  The use of tumour volumetrics to assess response to therapy in anticancer clinical trials.

Authors:  Gregory V Goldmacher; James Conklin
Journal:  Br J Clin Pharmacol       Date:  2012-06       Impact factor: 4.335

3.  Volumetric difference evaluation of registered three-dimensional pre-operative and post-operative CT dental data.

Authors:  T L Economopoulos; P A Asvestas; G K Matsopoulos; B Molnár; P Windisch
Journal:  Dentomaxillofac Radiol       Date:  2012-01-12       Impact factor: 2.419

4.  Application of CT-PSF-based computer-simulated lung nodules for evaluating the accuracy of computer-aided volumetry.

Authors:  Ayumu Funaki; Masaki Ohkubo; Shinichi Wada; Kohei Murao; Toru Matsumoto; Shinji Niizuma
Journal:  Radiol Phys Technol       Date:  2012-03-25

Review 5.  Imaging-based tumor treatment response evaluation: review of conventional, new, and emerging concepts.

Authors:  Hee Kang; Ho Yun Lee; Kyung Soo Lee; Jae-Hun Kim
Journal:  Korean J Radiol       Date:  2012-06-18       Impact factor: 3.500

6.  Special computer-aided computed tomography (CT) volume measurement and comparison method for pulmonary tuberculosis (TB).

Authors:  Jingming Liu; Zhaogang Sun; Ruming Xie; Mengqiu Gao; Chuanyou Li
Journal:  Int J Clin Exp Med       Date:  2015-09-15

7.  Volume estimation of multidensity nodules with thoracic computed tomography.

Authors:  Marios A Gavrielides; Qin Li; Rongping Zeng; Kyle J Myers; Berkman Sahiner; Nicholas Petrick
Journal:  J Med Imaging (Bellingham)       Date:  2016-01-29

8.  Contrast agents for quantitative microCT of lung tumors in mice.

Authors:  Kush Lalwani; Anand Giddabasappa; Danan Li; Peter Olson; Brett Simmons; Farbod Shojaei; Todd Van Arsdale; James Christensen; Amy Jackson-Fisher; Anthony Wong; Patrick B Lappin; Jeetendra Eswaraka
Journal:  Comp Med       Date:  2013       Impact factor: 0.982

9.  3D shape analysis to reduce false positives for lung nodule detection systems.

Authors:  Antonio Oseas de Carvalho Filho; Aristófanes Corrêa Silva; Anselmo Cardoso de Paiva; Rodolfo Acatauassú Nunes; Marcelo Gattass
Journal:  Med Biol Eng Comput       Date:  2016-10-17       Impact factor: 2.602

10.  Computed tomography assessment of response to therapy: tumor volume change measurement, truth data, and error.

Authors:  Michael F McNitt-Gray; Luc M Bidaut; Samuel G Armato; Charles R Meyer; Marios A Gavrielides; Charles Fenimore; Geoffrey McLennan; Nicholas Petrick; Binsheng Zhao; Anthony P Reeves; Reinhard Beichel; Hyun-Jung Grace Kim; Lisa Kinnard
Journal:  Transl Oncol       Date:  2009-12       Impact factor: 4.243

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