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

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

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
JournalJournal of Thoracic Imaging
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Tin
Tomography
Thorax
Lung
Radiologists
Aptitude
Cone-Beam Computed Tomography
Informed Consent

Keywords

  • CAD
  • detection
  • nodule
  • pulmonary
  • ultra-low

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Pulmonary and Respiratory Medicine

Cite this

Prospective Pilot Evaluation of Radiologists and Computer-aided Pulmonary Nodule Detection on Ultra-low-Dose CT with Tin Filtration. / Takahashi, Edwin A.; Koo, Chi Wan; White, Darin B.; Lindell, Rebecca M.; Sykes, Anne-Marie Gisele; Levin, David L.; Kuzo, Ronald S; Wolf, Matthias; Bogoni, Luca; Carter, Rickey E.; McCollough, Cynthia H; Fletcher, Joel Garland.

In: Journal of Thoracic Imaging, 01.01.2018.

Research output: Contribution to journalArticle

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abstract = "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.",
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AU - Takahashi, Edwin A.

AU - Koo, Chi Wan

AU - White, Darin B.

AU - Lindell, Rebecca M.

AU - Sykes, Anne-Marie Gisele

AU - Levin, David L.

AU - Kuzo, Ronald S

AU - Wolf, Matthias

AU - Bogoni, Luca

AU - Carter, Rickey E.

AU - McCollough, Cynthia H

AU - Fletcher, Joel Garland

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N2 - 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.

AB - 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.

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KW - ultra-low

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