Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening.
Rationale and Objectives: This study aimed to evaluate the effects of iterative reconstruction (IR) algorithms on computer-assisted detection (CAD) software for lung nodules in ultra-low-dose computed tomography (ULD-CT) for lung cancer screening.Materials and Methods: We selected 85 subjects who un...
| Published in: | Academic Radiology Vol. 24; no. 2; pp. 124 - 131 |
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| Main Authors: | , , , , , , , , |
| Format: | research Journal Article |
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Elsevier B.V.
Feb2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=120654748&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 120654748 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10766332 T4X jtl: Academic Radiology issn: 10766332 maglogo: N pubinfo: dt: Feb2017 vid: 24 iid: 2 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 120654748 120654748 NLM27986507 120654748 10.1016/j.acra.2016.09.023 NLM27986507 120654748 ppf: 124 ppct: 7 formats: tig: atl: Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening. aug: au: Nomura, Yukihiro Higaki, Toru Fujita, Masayo Miki, Soichiro Awaya, Yoshikazu Nakanishi, Toshio Yoshikawa, Takeharu Hayashi, Naoto Awai, Kazuo affil: Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan sug: subj: Algorithms Lung Neoplasms Software Early Detection of Cancer Methods Tomography, X-Ray Computed Methods Female Human Radionuclide Imaging Radiographic Image Interpretation, Computer-Assisted Methods Tomography, X-Ray Computed Aged Radiation Dosage Middle Age Male Validation Studies Comparative Studies Evaluation Research Multicenter Studies Aged: 65+ years Middle Aged: 45-64 years Female Male ab: Rationale and Objectives: This study aimed to evaluate the effects of iterative reconstruction (IR) algorithms on computer-assisted detection (CAD) software for lung nodules in ultra-low-dose computed tomography (ULD-CT) for lung cancer screening.Materials and Methods: We selected 85 subjects who underwent both a low-dose CT (LD-CT) scan and an additional ULD-CT scan in our lung cancer screening program for high-risk populations. The LD-CT scans were reconstructed with filtered back projection (FBP; LD-FBP). The ULD-CT scans were reconstructed with FBP (ULD-FBP), adaptive iterative dose reduction 3D (AIDR 3D; ULD-AIDR 3D), and forward projected model-based IR solution (FIRST; ULD-FIRST). CAD software for lung nodules was applied to each image dataset, and the performance of the CAD software was compared among the different IR algorithms.Results: The mean volume CT dose indexes were 3.02 mGy (LD-CT) and 0.30 mGy (ULD-CT). For overall nodules, the sensitivities of CAD software at 3.0 false positives per case were 78.7% (LD-FBP), 9.3% (ULD-FBP), 69.4% (ULD-AIDR 3D), and 77.8% (ULD-FIRST). Statistical analysis showed that the sensitivities of ULD-AIDR 3D and ULD-FIRST were significantly higher than that of ULD-FBP (P < .001).Conclusions: The performance of CAD software in ULD-CT was improved by using IR algorithms. In particular, the performance of CAD in ULD-FIRST was almost equivalent to that in LD-FBP. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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