Effect of Reconstruction Filters on Detectability of Pulmonary Nodules in Chest Phantoms by Low-Dose Computed Tomography in Simulated Lung Cancer Screening
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- YAMAGUCHI Isao
- Faculty of Health Sciences, Butsuryo College of Osaka
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- MURAMATSU Yoshihisa
- National Cancer Center Hospital East
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- HANAI Kozo
- Fukujuji Hospital, Japan Anti-Tuberculosis Association
Bibliographic Information
- Other Title
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- 低線量肺がんCT検診の腫瘤検出能に対するフィルタ関数の影響
- テイセンリョウ ハイ ガン CT ケンシン ノ シュリュウケンシュツノウ ニ タイスル フィルタ カンスウ ノ エイキョウ
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Abstract
Low-dose lung cancer screening by computed tomography (CT) contributes to reduction of the mortality rate. However, the use of low-dose CT screening for lung cancer has not become widely implemented in Japan. The objective of this study was to compare the sensitivity and specificity for the detection of lung nodules on low-dose CT screening images by using reconstruction filters. Nine lung cancer CT screening-certified radiological technologists read the low-dose screening CT images of 48 chest phantoms. On CT images with slice thicknesses of 2 or 5 mm, there were 18 lung nodules that were 8 mm in diameter. The reconstruction filters used for reading were FC13, FC52, and FC84. The differences in the mean sensitivities for detection of the nodules between FC13 and FC52 and between FC52 and FC84 were statistically significant. The mean sensitivities of FC13, FC52, and FC84 were 96.3%, 64.8%, and 98.1%, respectively. The differences in the mean specificities for detection of the nodules between FC13, FC52, and FC84 were not statistically significant. The mean specificities of FC13, FC52, and FC84 were 88.9%, 94.4%, and 100%, respectively. Low-dose lung cancer CT screening improved the detectability of simulated pulmonary nodules by using reconstruction filters to control image noise.
Journal
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- Bulletin of Butsuryo College of Osaka
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Bulletin of Butsuryo College of Osaka 4 (0), 9-14, 2016
Butsuryo College of Osaka
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Keywords
Details 詳細情報について
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- CRID
- 1390564238079923200
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- NII Article ID
- 110010016122
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- NII Book ID
- AA12619042
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- ISSN
- 24334758
- 21876517
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- NDL BIB ID
- 027333153
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed