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Computer-Aided Detection of Pulmonary Nodules in Computed Tomography Using ClearReadCT

  • Anne-Kathrin Wagner
  • Arno Hapich
  • Marios Nikos Psychogios
  • Ulf Teichgräber
  • Ansgar Malich
  • Ismini PapageorgiouEmail author
Image & Signal Processing
  • 23 Downloads
Part of the following topical collections:
  1. Image & Signal Processing

Abstract

This study evaluates the accuracy of a computer-aided detection (CAD) application for pulmonary nodular lesions (PNL) in computed tomography (CT) scans, the ClearReadCT (Riverain Technologies). The study was retrospective for 106 biopsied PNLs from 100 patients. Seventy-five scans were Contrast-Enhanced (CECT) and 25 received no enhancer (NECT). Axial reconstructions in soft-tissue and lung kernel were applied at three different slice thicknesses, 0.75 mm (CECT/NECT n = 25/6), 1.5 mm (n = 18/9) and 3.0 mm (n = 43/18). We questioned the effect of (1) enhancer, (2) kernel and (3) slice thickness on the CAD performance. Our main findings are: (1) Vessel suppression is effective and specific in both NECT and CECT. (2) Contrast enhancement significantly increased the CAD sensitivity from 60% in NECT to 80% in CECT, P = 0.025 Fischer’s exact test. (3) The CAD sensitivity was 84% in 3 mm slices compared to 68% in 0.75 mm slices, P > 0.2 Fischer’s exact test. (4) Small lesions of low attenuation were detected with higher sensitivity. (5) Lung kernel reconstructions increased the false positive rate without affecting the sensitivity (P > 0.05 McNemar’s test). In conclusion, ClearReadCT showed an optimized sensitivity of 84% and a positive predictive value of 67% in enhanced lung scans with thick, soft kernel reconstructions. NECT, thin slices and lung kernel reconstruction were associated with inferior performance.

Keywords

nodule classification segmentation vessel suppression background elimination lung cancer 

Abbreviations

16xDEF

Somatom definition AS 16-row CT scanner

16xEMO

Somatom emotion 16-row CT scanner

64xDEF

Somatom definition AS 64-row CT scanner

CAD

Computer-aided detection

CECT

Contrast-enhanced computed tomography

CT

Computed tomography

FN

False negative

FP

False positive

HU

Hounsfield Units

NECT

Non-enhanced computed tomography

PACS

Picture archiving and communication system

PNL

Pulmonary nodular lesions

PPV

Positive predictive value

TN

True negative

TP

True positive

TPR

True positive rate (sensitivity)

V1

CAD version 1

V2

CAD version 2

Notes

Compliance with the ethical standards

The study was approved by the Ethics Committee of the University Hospital of Jena and was performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its amendments, the European Regulation 536/2014 as well as with the good clinical and scientific practice protocols of the University of Jena. For this type of study a formal consent was not required.

Supplementary material

10916_2019_1180_MOESM1_ESM.pdf (58 kb)
ESM 1 (PDF 57 kb)
10916_2019_1180_MOESM2_ESM.pdf (51 kb)
ESM 2 (PDF 51 kb)
10916_2019_1180_MOESM3_ESM.pdf (109 kb)
ESM 3 (PDF 109 kb)
10916_2019_1180_MOESM4_ESM.xlsx (70 kb)
ESM 4 (XLSX 70 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Diagnostic and Interventional RadiologyUniversity Hospital JenaJenaGermany
  2. 2.Institute of RadiologySüdharz Hospital NordhausenNordhausenGermany
  3. 3.Department of Thoracic SurgerySüdharz Hospital NordhausenNordhausenGermany
  4. 4.Institute of Diagnostic and Interventional NeuroradiologyUniversity Medicine GöttingenGöttingenGermany

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