[논문]Digital Tomosynthesis for Evaluating Metastatic Lung Nodules: Nodule Visibility, Learning Curves, and Reading Times

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyungjin; Song, Yong Sub; Hwang, Eui Jin

doi:10.3348/kjr.2015.16.2.430

Digital Tomosynthesis for Evaluating Metastatic Lung Nodules: Nodule Visibility, Learning Curves, and Reading Times 원문보기

Korean journal of radiology : official journal of the Korean Radiological Society, v.16 no.2, 2015년, pp.430 - 439

Lee, Kyung Hee (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 110-744, Korea.) , Goo, Jin Mo (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 110-744, Korea.) , Lee, Sang Min (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 110-744, Korea.) , Park, Chang Min (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 110-744, Korea.) , Bahn, Young Eun (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 110-744, Korea.) , Kim, Hyungjin (Department of Radiology, Seoul National University College of Medicine, and Inst) , Song, Yong Sub , Hwang, Eui Jin

Abstract ▼ AI-Helper

ObjectiveTo evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT).Materials and MethodsWe included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined.ResultsAmong 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, ≤ 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed.ConclusionMost malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

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Digital Tomosynthesis for Evaluating Metastatic Lung Nodules: Nodule Visibility, Learning Curves, and Reading Times 원문보기

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