Ultra-High-Resolution Computed Tomography of the Lung: Image Quality of a Prototype Scanner

PLoS One. 2015 Sep 9;10(9):e0137165. doi: 10.1371/journal.pone.0137165. eCollection 2015.

Abstract

Purpose: The image noise and image quality of a prototype ultra-high-resolution computed tomography (U-HRCT) scanner was evaluated and compared with those of conventional high-resolution CT (C-HRCT) scanners.

Materials and methods: This study was approved by the institutional review board. A U-HRCT scanner prototype with 0.25 mm x 4 rows and operating at 120 mAs was used. The C-HRCT images were obtained using a 0.5 mm x 16 or 0.5 mm x 64 detector-row CT scanner operating at 150 mAs. Images from both scanners were reconstructed at 0.1-mm intervals; the slice thickness was 0.25 mm for the U-HRCT scanner and 0.5 mm for the C-HRCT scanners. For both scanners, the display field of view was 80 mm. The image noise of each scanner was evaluated using a phantom. U-HRCT and C-HRCT images of 53 images selected from 37 lung nodules were then observed and graded using a 5-point score by 10 board-certified thoracic radiologists. The images were presented to the observers randomly and in a blinded manner.

Results: The image noise for U-HRCT (100.87 ± 0.51 Hounsfield units [HU]) was greater than that for C-HRCT (40.41 ± 0.52 HU; P < .0001). The image quality of U-HRCT was graded as superior to that of C-HRCT (P < .0001) for all of the following parameters that were examined: margins of subsolid and solid nodules, edges of solid components and pulmonary vessels in subsolid nodules, air bronchograms, pleural indentations, margins of pulmonary vessels, edges of bronchi, and interlobar fissures.

Conclusion: Despite a larger image noise, the prototype U-HRCT scanner had a significantly better image quality than the C-HRCT scanners.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adenocarcinoma / diagnostic imaging
  • Adenocarcinoma of Lung
  • Humans
  • Image Processing, Computer-Assisted*
  • Lung / diagnostic imaging*
  • Lung / pathology
  • Lung Neoplasms / diagnostic imaging
  • Observer Variation
  • Phantoms, Imaging
  • Tomography, X-Ray Computed / methods*

Grants and funding

This research was supported in part by a Grant-in-Aid from the Third-term Comprehensive Cancer Control Strategy sponsored by the Ministry of Health, Labour and Welfare (http://www.mhlw.go.jp/english/), Tokyo, Japan (19-1, 22-019), by the Program for Promotion of Fundamental Studies in Health Science of the National Institute of Biomedical Innovation, and by the National Cancer Center (http://www.ncc.go.jp/en/index.html) Research and Development Fund (48-A-12). Toshiba Medical Systems Corporation provided support in the form of salaries for authors NS, ST, YS & MK, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.