Literature DB >> 15895571

Quantitation of the reconstruction quality of a four-dimensional computed tomography process for lung cancer patients.

Wei Lu1, Parag J Parikh, Issam M El Naqa, Michelle M Nystrom, James P Hubenschmidt, Sasha H Wahab, Sasa Mutic, Anurag K Singh, Gary E Christensen, Jeffrey D Bradley, Daniel A Low.   

Abstract

We have developed a four-dimensional computed tomography (4D CT) technique for mapping breathing motion in radiotherapy treatment planning. A multislice CT scanner (1.5 mm slices) operated in ciné mode was used to acquire 12 contiguous slices in each couch position for 15 consecutive scans (0.5 s rotation, 0.25 s between scans) while the patient underwent simultaneous quantitative spirometry measurements to provide a sorting metric. The spirometry-sorted scans were used to reconstruct a 4D data set. A critical factor for 4D CT is quantifying the reconstructed data set quality which we measure by correlating the metric used relative to internal-object motion. For this study, the internal air content within the lung was used as a surrogate for internal motion measurements. Thresholding and image morphological operations were applied to delineate the air-containing tissues (lungs, trachea) from each CT slice. The Hounsfield values were converted to the internal air content (V). The relationship between the air content and spirometer-measured tidal volume (v) was found to be quite linear throughout the lungs and was used to estimate the overall accuracy and precision of tidal volume-sorted 4D CT. Inspection of the CT-scan air content as a function of tidal volume showed excellent correlations (typically r>0.99) throughout the lung volume. Because of the discovered linear relationship, the ratio of internal air content to tidal volume was indicative of the fraction of air change in each couch position. Theoretically, due to air density differences within the lung and in room, the sum of these ratios would equal 1.11. For 12 patients, the mean value was 1.08 +/- 0.06, indicating the high quality of spirometry-based image sorting. The residual of a first-order fit between v and V was used to estimate the process precision. For all patients, the precision was better than 8%, with a mean value of 5.1% +/- 1.9%. This quantitative analysis highlights the value of using spirometry as the metric in sorting CT scans. The 4D reconstruction provides the CT data required to measure the three-dimensional trajectory of tumor and lung tissue during free breathing.

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Year:  2005        PMID: 15895571     DOI: 10.1118/1.1870152

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  24 in total

1.  Biomechanical interpretation of a free-breathing lung motion model.

Authors:  Tianyu Zhao; Benjamin White; Kevin L Moore; James Lamb; Deshan Yang; Wei Lu; Sasa Mutic; Daniel A Low
Journal:  Phys Med Biol       Date:  2011-11-11       Impact factor: 3.609

2.  Reconstruction of four-dimensional computed tomography lung images by applying spatial and temporal anatomical constraints using a Bayesian model.

Authors:  Tiancheng He; Zhong Xue; Bin S Teh; Stephen T Wong
Journal:  J Med Imaging (Bellingham)       Date:  2015-05-13

3.  Iterative sorting for four-dimensional CT images based on internal anatomy motion.

Authors:  Rongping Zeng; Jeffrey A Fessler; James M Balter; Peter A Balter
Journal:  Med Phys       Date:  2008-03       Impact factor: 4.071

4.  Reduction of acquisition time in the intersection profile method for four-dimensional magnetic resonance imaging reconstruction of thoracoabdominal organs.

Authors:  Windra Swastika; Yoshitada Masuda; Takashi Ohnishi; Hideaki Haneishi
Journal:  J Med Imaging (Bellingham)       Date:  2015-06-03

5.  Characterization and identification of spatial artifacts during 4D-CT imaging.

Authors:  Dongfeng Han; John Bayouth; Sudershan Bhatia; Milan Sonka; Xiaodong Wu
Journal:  Med Phys       Date:  2011-04       Impact factor: 4.071

6.  Technical note: development of a tidal volume surrogate that replaces spirometry for physiological breathing monitoring in 4D CT.

Authors:  René Werner; Benjamin White; Heinz Handels; Wei Lu; Daniel A Low
Journal:  Med Phys       Date:  2010-02       Impact factor: 4.071

7.  Novel spirometry based on optical surface imaging.

Authors:  Guang Li; Hailiang Huang; Jie Wei; Diana G Li; Qing Chen; Carl P Gaebler; James Sullivan; Joan Zatcky; Andreas Rimner; James Mechalakos
Journal:  Med Phys       Date:  2015-04       Impact factor: 4.071

8.  Simulating Developmental Cardiac Morphology in Virtual Reality Using a Deformable Image Registration Approach.

Authors:  Arash Abiri; Yichen Ding; Parinaz Abiri; René R Sevag Packard; Vijay Vedula; Alison Marsden; C-C Jay Kuo; Tzung K Hsiai
Journal:  Ann Biomed Eng       Date:  2018-08-15       Impact factor: 3.934

9.  Characterization of free breathing patterns with 5D lung motion model.

Authors:  Tianyu Zhao; Wei Lu; Deshan Yang; Sasa Mutic; Camille E Noel; Parag J Parikh; Jeffrey D Bradley; Daniel A Low
Journal:  Med Phys       Date:  2009-11       Impact factor: 4.071

Review 10.  [Computed tomography of the lungs. A step into the fourth dimension].

Authors:  J Dinkel; C Hintze; N Rochet; C Thieke; J Biederer
Journal:  Radiologe       Date:  2009-08       Impact factor: 0.635

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