Digital tomosynthesis for evaluating metastatic lung nodules: nodule visibility, learning curves, and reading times

Korean J Radiol. 2015 Mar-Apr;16(2):430-9. doi: 10.3348/kjr.2015.16.2.430. Epub 2015 Feb 27.

Abstract

Objective: To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT).

Materials and methods: We 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.

Results: Among 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 < 0.001). Area under the curve (AUC) values at the initial session were > 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.

Conclusion: Most 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.

Keywords: Learning curve; Pulmonary nodules; Tomography; X-ray.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Area Under Curve
  • Female
  • Humans
  • Learning Curve
  • Lung Neoplasms / diagnosis*
  • Lung Neoplasms / diagnostic imaging*
  • Lung Neoplasms / secondary
  • Male
  • Middle Aged
  • ROC Curve
  • Reading
  • Retrospective Studies
  • Software
  • Tomography, X-Ray Computed / methods*
  • Young Adult