Literature DB >> 10811683

Evaluation of tumor measurements in oncology: use of film-based and electronic techniques.

L H Schwartz1, M S Ginsberg, D DeCorato, L N Rothenberg, S Einstein, P Kijewski, D M Panicek.   

Abstract

PURPOSE: To evaluate the variability in bidimensional computed tomography (CT) measurements obtained of actual tumors and of tumor phantoms by use of three measurement techniques: hand-held calipers on film, electronic calipers on a workstation, and an autocontour technique on a workstation.
MATERIALS AND METHODS: Three radiologists measured 45 actual tumors (in the lung, liver, and lymph nodes) on CT images, using each of the three techniques. Bidimensional measurements were recorded, and their cross-products calculated. The coefficient of variation was calculated to assess interobserver variability. CT images of 48 phantoms were measured by three radiologists with each of the techniques. In addition to the coefficient of variation, the differences between the cross-product measurements of tumor phantoms themselves and the measurements obtained with each of the techniques were calculated.
RESULTS: The differences between the coefficients of variation were statistically significantly different for the autocontour technique, compared with the other techniques, both for actual tumors and for tumor phantoms. There was no statistically significant difference in the coefficient of variation between measurements obtained with hand-held calipers and electronic calipers. The cross-products for tumor phantoms were 12% less than the actual cross-product when calipers on film were used, 11% less using electronic calipers, and 1% greater using the autocontour technique.
CONCLUSION: Tumor size is obtained more accurately and consistently between readers using an automated autocontour technique than between those using hand-held or electronic calipers. This finding has substantial implications for monitoring tumor therapy in an individual patient, as well as for evaluating the effectiveness of new therapies under development.

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Year:  2000        PMID: 10811683     DOI: 10.1200/JCO.2000.18.10.2179

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  29 in total

1.  Reproducibility of linear tumor measurements using PACS: comparison of caliper method with edge-tracing method.

Authors:  Wayne L Monsky; Vassilios Raptopoulos; Mary T Keogan; David Doty; Ihab Kamel; Chun Sam Yam; Bernard J Ransil
Journal:  Eur Radiol       Date:  2003-12-05       Impact factor: 5.315

2.  The influence of initial outlines on manual segmentation.

Authors:  William F Sensakovic; Adam Starkey; Rachael Roberts; Christopher Straus; Philip Caligiuri; Masha Kocherginsky; Samuel G Armato
Journal:  Med Phys       Date:  2010-05       Impact factor: 4.071

3.  Evaluation of a method of computer-aided detection (CAD) of pulmonary nodules with computed tomography.

Authors:  G Foti; N Faccioli; M D'Onofrio; A Contro; T Milazzo; R Pozzi Mucelli
Journal:  Radiol Med       Date:  2010-06-23       Impact factor: 3.469

4.  Effect of blood vessels on measurement of nodule volume in a chest phantom.

Authors:  Jane P Ko; Rachel Marcus; Elan Bomsztyk; James S Babb; Cornel Stefanescu; Manmeen Kaur; David P Naidich; Henry Rusinek
Journal:  Radiology       Date:  2006-04       Impact factor: 11.105

5.  Evaluation of lung MDCT nodule annotation across radiologists and methods.

Authors:  Charles R Meyer; Timothy D Johnson; Geoffrey McLennan; Denise R Aberle; Ella A Kazerooni; Heber Macmahon; Brian F Mullan; David F Yankelevitz; Edwin J R van Beek; Samuel G Armato; Michael F McNitt-Gray; Anthony P Reeves; David Gur; Claudia I Henschke; Eric A Hoffman; Peyton H Bland; Gary Laderach; Richie Pais; David Qing; Chris Piker; Junfeng Guo; Adam Starkey; Daniel Max; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2006-10       Impact factor: 3.173

6.  The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation.

Authors:  Michael F McNitt-Gray; Samuel G Armato; Charles R Meyer; Anthony P Reeves; Geoffrey McLennan; Richie C Pais; John Freymann; Matthew S Brown; Roger M Engelmann; Peyton H Bland; Gary E Laderach; Chris Piker; Junfeng Guo; Zaid Towfic; David P-Y Qing; David F Yankelevitz; Denise R Aberle; Edwin J R van Beek; Heber MacMahon; Ella A Kazerooni; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-12       Impact factor: 3.173

7.  The Lung Image Database Consortium (LIDC): a comparison of different size metrics for pulmonary nodule measurements.

Authors:  Anthony P Reeves; Alberto M Biancardi; Tatiyana V Apanasovich; Charles R Meyer; Heber MacMahon; Edwin J R van Beek; Ella A Kazerooni; David Yankelevitz; Michael F McNitt-Gray; Geoffrey McLennan; Samuel G Armato; Claudia I Henschke; Denise R Aberle; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-12       Impact factor: 3.173

8.  Computer input devices: neutral party or source of significant error in manual lesion segmentation?

Authors:  James Y Chen; F Jacob Seagull; Paul Nagy; Paras Lakhani; Elias R Melhem; Eliot L Siegel; Nabile M Safdar
Journal:  J Digit Imaging       Date:  2011-02       Impact factor: 4.056

9.  Discrete-space versus continuous-space lesion boundary and area definitions.

Authors:  William F Sensakovic; Adam Starkey; Rachael Y Roberts; Samuel G Armato
Journal:  Med Phys       Date:  2008-09       Impact factor: 4.071

10.  Evaluating variability in tumor measurements from same-day repeat CT scans of patients with non-small cell lung cancer.

Authors:  Binsheng Zhao; Leonard P James; Chaya S Moskowitz; Pingzhen Guo; Michelle S Ginsberg; Robert A Lefkowitz; Yilin Qin; Gregory J Riely; Mark G Kris; Lawrence H Schwartz
Journal:  Radiology       Date:  2009-07       Impact factor: 11.105

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