A virtual clinical trial using projection-based nodule insertion to determine radiologist reader performance in lung cancer screening CT
| Autor: | Lifeng Yu, Megan J. Hora, Cynthia H. McCollough, Shuai Leng, Edwin A. Takahashi, Chi Wan Koo, Baiyu Chen, Shane Dirks, Qiyuan Hu, David L. Levin, Tucker F. Johnson, Joel G. Fletcher, Kyle McMillan |
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| Rok vydání: | 2017 |
| Předmět: |
Protocol (science)
medicine.medical_specialty medicine.diagnostic_test Image quality Computer science Radiation dose Nodule (medicine) Computed tomography medicine.disease Article 030218 nuclear medicine & medical imaging Task (project management) Lesion Clinical trial 03 medical and health sciences 0302 clinical medicine 030220 oncology & carcinogenesis medicine Medical physics Radiology medicine.symptom Projection (set theory) Lung cancer Lung cancer screening |
| Zdroj: | Medical Imaging 2017: Physics of Medical Imaging. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.2255593 |
| Popis: | Task-based image quality assessment using model observers is promising to provide an efficient, quantitative, and objective approach to CT dose optimization. Before this approach can be reliably used in practice, its correlation with radiologist performance for the same clinical task needs to be established. Determining human observer performance for a well-defined clinical task, however, has always been a challenge due to the tremendous amount of efforts needed to collect a large number of positive cases. To overcome this challenge, we developed an accurate projection-based insertion technique. In this study, we present a virtual clinical trial using this tool and a low-dose simulation tool to determine radiologist performance on lung-nodule detection as a function of radiation dose, nodule type, nodule size, and reconstruction methods. The lesion insertion and low-dose simulation tools together were demonstrated to provide flexibility to generate realistically-appearing clinical cases under well-defined conditions. The reader performance data obtained in this virtual clinical trial can be used as the basis to develop model observers for lung nodule detection, as well as for dose and protocol optimization in lung cancer screening CT. |
| Databáze: | OpenAIRE |
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