Optimization of CT image reconstruction algorithms for the Lung Tissue Research Consortium (LTRC)

Cynthia H McCollough, Jie Zhang, Michael Bruesewitz, Brian Jack Bartholmai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 × 3 × 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the spatial resolution bar patterns demonstrated that the BONE (GE) and B46f (Siemens) showed higher spatial resolution compared to the STANDARD (GE) or B30f (Siemens) reconstruction algorithms typically used for routine body CT imaging. Only the sharper images were deemed clinically acceptable for the evaluation of diffuse lung disease (e.g. emphysema). Quantitative analyses of the extent of emphysema in patient data showed the percent volumes above the -950 HU threshold as 9.4% for the BONE reconstruction, 5.9% for the STANDARD reconstruction, and 4.7% for the BONE filtered images. Contrary to the practice of using standard resolution CT images for the quantitation of diffuse lung disease, these data demonstrate that a single sharp reconstruction (BONE/B46f) should be used for both the qualitative and quantitative evaluation of diffuse lung disease. The sharper reconstruction images, which are required for diagnostic interpretation, provide accurate CT numbers over the range of-1000 to +900 HU and preserve the fidelity of small structures in the reconstructed images. A filtered version of the sharper images can be accurately substituted for images reconstructed with smoother kernels for comparison to previously published results.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6143 II
DOIs
StatePublished - 2006
EventMedical Imaging 2006: Physiology, Function, and Structure from Medical Images - San Diego, CA, United States
Duration: Feb 12 2006Feb 14 2006

Other

OtherMedical Imaging 2006: Physiology, Function, and Structure from Medical Images
CountryUnited States
CitySan Diego, CA
Period2/12/062/14/06

Fingerprint

Image reconstruction
Pulmonary diseases
Tissue
Median filters
Accreditation
Image quality
Blood
Imaging techniques

Keywords

  • Computed Tomography (CT)
  • Diffuse lung disease
  • Emphysema
  • Lung
  • Reconstruction algorithm

ASJC Scopus subject areas

  • Engineering(all)

Cite this

McCollough, C. H., Zhang, J., Bruesewitz, M., & Bartholmai, B. J. (2006). Optimization of CT image reconstruction algorithms for the Lung Tissue Research Consortium (LTRC). In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 6143 II). [614330] https://doi.org/10.1117/12.653290

Optimization of CT image reconstruction algorithms for the Lung Tissue Research Consortium (LTRC). / McCollough, Cynthia H; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian Jack.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6143 II 2006. 614330.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

McCollough, CH, Zhang, J, Bruesewitz, M & Bartholmai, BJ 2006, Optimization of CT image reconstruction algorithms for the Lung Tissue Research Consortium (LTRC). in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 6143 II, 614330, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, San Diego, CA, United States, 2/12/06. https://doi.org/10.1117/12.653290
McCollough CH, Zhang J, Bruesewitz M, Bartholmai BJ. Optimization of CT image reconstruction algorithms for the Lung Tissue Research Consortium (LTRC). In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6143 II. 2006. 614330 https://doi.org/10.1117/12.653290
McCollough, Cynthia H ; Zhang, Jie ; Bruesewitz, Michael ; Bartholmai, Brian Jack. / Optimization of CT image reconstruction algorithms for the Lung Tissue Research Consortium (LTRC). Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 6143 II 2006.
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