Literature DB >> 18773240

Variability of semiautomated lung nodule volumetry on ultralow-dose CT: comparison with nodule volumetry on standard-dose CT.

Patrick A Hein1, Valentina C Romano, Patrik Rogalla, Christian Klessen, Alexander Lembcke, Lars Bornemann, Volker Dicken, Bernd Hamm, Hans-Christian Bauknecht.   

Abstract

The study investigates the effect of a substantial dose reduction on the variability of lung nodule volume measurements by assessing and comparing nodule volumes using a dedicated semiautomated segmentation software on ultralow-dose computed tomography (ULD-CT) and standard-dose computed tomography (SD-CT) data. In 20 patients, thin-slice chest CT datasets (1 mm slice thickness; 20% reconstruction overlap) were acquired at ultralow-dose (120 kV, 5 mAs) and at standard-dose (120 kV, 75 mAs), respectively, and analyzed using the segmentation software OncoTREAT (MeVis, Bremen, Germany; version 1.3). Interobserver variability of volume measurements of 202 solid pulmonary nodules (mean diameter 11 mm, range 3.2-44.5 mm) was calculated for SD-CT and ULD-CT. With respect to interobserver variability, the 95% confidence interval for the relative differences in nodule volume in the intrascan analysis was measured with -9.7% to 8.3% (mean difference -0.7%) for SD-CT and with -12.6% to 12.4% (mean difference -0.2%) for ULD-CT. In the interscan analysis, the 95% confidence intervals for the differences in nodule volume ranged with -25.1% to -23.4% and 26.2% to 28.9% (mean difference 1.4% to 2.1%) dependent on the combination of readers and scans. Intrascan interobserver variability of volume measurements was comparable for ULD-CT and SD-CT data. The calculated variability of volume measurements in the interscan analysis was similar to the data reported in the literature for CT data acquired with equal radiation dose. Thus, the evaluated segmentation software provides nodule volumetry that appears to be independent of the dose level with which the CT source dataset is acquired.

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Year:  2008        PMID: 18773240      PMCID: PMC3043750          DOI: 10.1007/s10278-008-9157-5

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  24 in total

1.  Spiral CT of pulmonary nodules: interobserver variation in assessment of lesion size.

Authors:  D Wormanns; S Diederich; M G Lentschig; F Winter; W Heindel
Journal:  Eur Radiol       Date:  2000       Impact factor: 5.315

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.  Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility.

Authors:  Dag Wormanns; Gerhard Kohl; Ernst Klotz; Anke Marheine; Florian Beyer; Walter Heindel; Stefan Diederich
Journal:  Eur Radiol       Date:  2003-11-13       Impact factor: 5.315

4.  Pulmonary nodule volume: effects of reconstruction parameters on automated measurements--a phantom study.

Authors:  James G Ravenel; William M Leue; Paul J Nietert; James V Miller; Katherine K Taylor; Gerard A Silvestri
Journal:  Radiology       Date:  2008-05       Impact factor: 11.105

5.  Screening for early lung cancer with low-dose spiral CT: prevalence in 817 asymptomatic smokers.

Authors:  Stefan Diederich; Dag Wormanns; Michael Semik; Michael Thomas; Horst Lenzen; Nikolaus Roos; Walter Heindel
Journal:  Radiology       Date:  2002-03       Impact factor: 11.105

6.  Lung cancer screening with CT: Mayo Clinic experience.

Authors:  Stephen J Swensen; James R Jett; Thomas E Hartman; David E Midthun; Jeff A Sloan; Anne-Marie Sykes; Gregory L Aughenbaugh; Medy A Clemens
Journal:  Radiology       Date:  2003-01-24       Impact factor: 11.105

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

8.  Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable?

Authors:  Marie-Pierre Revel; Alvine Bissery; Marie Bienvenu; Laetitia Aycard; Catherine Lefort; Guy Frija
Journal:  Radiology       Date:  2004-05       Impact factor: 11.105

9.  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

10.  Tumor response to chemotherapy: the validity and reproducibility of RECIST guidelines in NSCLC patients.

Authors:  Hirokazu Watanabe; Seiichiro Yamamoto; Hideo Kunitoh; Ikuo Sekine; Noboru Yamamoto; Yuichiro Ohe; Tomohide Tamura; Tetsuro Kodama; Kazuro Sugimura; Nagahiro Saijo
Journal:  Cancer Sci       Date:  2003-11       Impact factor: 6.716

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  14 in total

1.  Impact of a computer-aided detection (CAD) system integrated into a picture archiving and communication system (PACS) on reader sensitivity and efficiency for the detection of lung nodules in thoracic CT exams.

Authors:  Luca Bogoni; Jane P Ko; Jeffrey Alpert; Vikram Anand; John Fantauzzi; Charles H Florin; Chi Wan Koo; Derek Mason; William Rom; Maria Shiau; Marcos Salganicoff; David P Naidich
Journal:  J Digit Imaging       Date:  2012-12       Impact factor: 4.056

2.  Workflow-centred evaluation of an automatic lesion tracking software for chemotherapy monitoring by CT.

Authors:  Jan Hendrik Moltz; Melvin D'Anastasi; Andreas Kiessling; Daniel Pinto dos Santos; Christoph Schülke; Heinz-Otto Peitgen
Journal:  Eur Radiol       Date:  2012-06-29       Impact factor: 5.315

3.  Computer-aided diagnosis systems for lung cancer: challenges and methodologies.

Authors:  Ayman El-Baz; Garth M Beache; Georgy Gimel'farb; Kenji Suzuki; Kazunori Okada; Ahmed Elnakib; Ahmed Soliman; Behnoush Abdollahi
Journal:  Int J Biomed Imaging       Date:  2013-01-29

4.  Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods.

Authors:  Stefano Young; Hyun J Grace Kim; Moe Moe Ko; War War Ko; Carlos Flores; Michael F McNitt-Gray
Journal:  Med Phys       Date:  2015-05       Impact factor: 4.071

Review 5.  Volume versus diameter assessment of small pulmonary nodules in CT lung cancer screening.

Authors:  Daiwei Han; Marjolein A Heuvelmans; Matthijs Oudkerk
Journal:  Transl Lung Cancer Res       Date:  2017-02

6.  Pulmonary Nodules: growth rate assessment in patients by using serial CT and three-dimensional volumetry.

Authors:  Jane P Ko; Erika J Berman; Manmeen Kaur; James S Babb; Elan Bomsztyk; Alissa K Greenberg; David P Naidich; Henry Rusinek
Journal:  Radiology       Date:  2011-12-09       Impact factor: 11.105

7.  Evaluation of the 95% limits of agreement of the volumes of 5-year clinically stable solid nodules for the development of a follow-up system for indeterminate solid nodules in CT lung cancer screening.

Authors:  Ryutaro Kakinuma; Yukio Muramatsu; Junta Yamamichi; Shiho Gomi; Estanislao Oubel; Noriyuki Moriyama
Journal:  J Thorac Dis       Date:  2018-01       Impact factor: 2.895

8.  The Fate of Patients with Solitary Pulmonary Nodules: Clinical Management and Radiation Exposure Associated.

Authors:  Blanca Lumbreras; José Vilar; Isabel González-Álvarez; Noemí Gómez-Sáez; María L Domingo; María F Lorente; María Pastor-Valero; Ildefonso Hernández-Aguado
Journal:  PLoS One       Date:  2016-07-08       Impact factor: 3.240

9.  The effects of computed tomography with iterative reconstruction on solid pulmonary nodule volume quantification.

Authors:  Martin J Willemink; Jaap Borstlap; Richard A P Takx; Arnold M R Schilham; Tim Leiner; Ricardo P J Budde; Pim A de Jong
Journal:  PLoS One       Date:  2013-02-27       Impact factor: 3.240

10.  Diameter of the Solid Component in Subsolid Nodules on Low-Dose Unenhanced Chest Computed Tomography: Measurement Accuracy for the Prediction of Invasive Component in Lung Adenocarcinoma.

Authors:  Hyungwoo Ahn; Kyung Hee Lee; Jihang Kim; Jeongjae Kim; Junghoon Kim; Kyung Won Lee
Journal:  Korean J Radiol       Date:  2018-04-06       Impact factor: 3.500

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