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Prospective Pilot Evaluation of Radiologists and Computer-aided Pulmonary Nodule Detection on Ultra–low-Dose CT With Tin Filtration

Takahashi, Edwin A., MD*; Koo, Chi Wan, MD*; White, Darin B., MD*; Lindell, Rebecca M., MD*; Sykes, Anne-Marie G., MD*; Levin, David L., MD*; Kuzo, Ronald S., MD*; Wolf, Matthias, PhD; Bogoni, Luca, PhD; Carter, Rickey E., PhD*,‡; McCollough, Cynthia H., PhD*,§; Fletcher, Joel G., MD*

doi: 10.1097/RTI.0000000000000348
Lung Nodules/Pulmonary Neoplasm

Purpose: The aim of this study was to evaluate the ability of computer-aided detection (CAD) and human readers to detect pulmonary nodules ≥5 mm using 100 kV ultra–low-dose computed tomography (ULDCT) utilizing a tin filter.

Materials and Methods: After informed consent, 55 patients prospectively underwent standard-dose chest CT (SDCT) using 120 kV followed by ULDCT using 100 kV/tin. Reference nodules ≥5 mm were identified by a thoracic radiologist using SDCT. Four thoracic radiologists marked detected nodules on SDCT and ULDCT examinations using a dedicated computer workstation. After a 6-month memory extinction, readers were shown the same ULDCT cases with all CAD markings as well as their original detections, and characterized CAD detections as true positive or false positive.

Results: Volume CT Dose index (CTDIvol) for SDCT and ULDCT were 5.3±2 and 0.4±0.2 mGy (P<0.0001), respectively. Forty-five reference nodules were detected in 30 patients. Reader sensitivity varied widely but similarly for SDCT (ranging from 45% to 87%) and ULDCT (45% to 83%). CAD sensitivity was 76% (34/45) for SDCT and 71% (32/45) for ULDCT. After CAD, reader sensitivity substantially improved by 19% and 18% for 2 readers, and remained nearly unchanged for the other 2 readers (0% and 2%), despite reader perception that many more nodules were identified with CAD. There was a mean of 2 false-positive CAD detections/case.

Conclusions: ULDCT with 100 kV/tin reduced patient dose by over 90% without compromising pulmonary nodule detection sensitivity. CAD can substantially improve nodule detection sensitivity at ULDCT for some readers, maintaining interobserver performance.

Departments of *Radiology

Biostatistics

§Biomedical Engineering and Medical Physics, Mayo Clinic, Rochester, MN

Seimens Medical Solutions, Malvern, PA

E.A.T. and C.W.K. are co-first authors.

C.H.M. and J.G.F. receive research grant from Siemens AG. M.W. and L.B. are employees of Siemens. The remaining authors declare no conflicts of interest.

Correspondence to: Chi Wan Koo, MD, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 (e-mail: koo.chiwan@mayo.edu).

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