European Radiology

, Volume 25, Issue 2, pp 488–496 | Cite as

Detection and quantification of the solid component in pulmonary subsolid nodules by semiautomatic segmentation

  • Ernst Th. Scholten
  • Colin Jacobs
  • Bram van Ginneken
  • Sarah van Riel
  • Rozemarijn Vliegenthart
  • Matthijs Oudkerk
  • Harry J. de Koning
  • Nanda Horeweg
  • Mathias Prokop
  • Hester A. Gietema
  • Willem P. Th.M. Mali
  • Pim A. de Jong
Computed Tomography

Abstract

Objective

To determine whether semiautomatic volumetric software can differentiate part-solid from nonsolid pulmonary nodules and aid quantification of the solid component.

Methods

As per reference standard, 115 nodules were differentiated into nonsolid and part-solid by two radiologists; disagreements were adjudicated by a third radiologist. The diameters of solid components were measured manually. Semiautomatic volumetric measurements were used to identify and quantify a possible solid component, using different Hounsfield unit (HU) thresholds. The measurements were compared with the reference standard and manual measurements.

Results

The reference standard detected a solid component in 86 nodules. Diagnosis of a solid component by semiautomatic software depended on the threshold chosen. A threshold of −300 HU resulted in the detection of a solid component in 75 nodules with good sensitivity (90 %) and specificity (88 %). At a threshold of −130 HU, semiautomatic measurements of the diameter of the solid component (mean 2.4 mm, SD 2.7 mm) were comparable to manual measurements at the mediastinal window setting (mean 2.3 mm, SD 2.5 mm [p = 0.63]).

Conclusion

Semiautomatic segmentation of subsolid nodules could diagnose part-solid nodules and quantify the solid component similar to human observers. Performance depends on the attenuation segmentation thresholds. This method may prove useful in managing subsolid nodules.

Key Points

Semiautomatic segmentation can accurately differentiate nonsolid from part-solid pulmonary nodules

Semiautomatic segmentation can quantify the solid component similar to manual measurements

Semiautomatic segmentation may aid management of subsolid nodules following Fleischner Society recommendations

Performance for the segmentation of subsolid nodules depends on the chosen attenuation thresholds

Keywords

Subsolid pulmonary nodules Computer-aided diagnosis Computed tomography Lung cancer Screening 

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Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Ernst Th. Scholten
    • 1
    • 2
  • Colin Jacobs
    • 3
  • Bram van Ginneken
    • 3
    • 4
  • Sarah van Riel
    • 3
  • Rozemarijn Vliegenthart
    • 5
    • 6
  • Matthijs Oudkerk
    • 6
  • Harry J. de Koning
    • 7
  • Nanda Horeweg
    • 7
    • 8
  • Mathias Prokop
    • 9
  • Hester A. Gietema
    • 1
  • Willem P. Th.M. Mali
    • 1
  • Pim A. de Jong
    • 1
  1. 1.Department of RadiologyUniversity Medical CenterUtrechtThe Netherlands
  2. 2.Department of RadiologyKennemer GasthuisHaarlemThe Netherlands
  3. 3.Diagnostic Image Analysis GroupRadboud University Medical CenterNijmegenThe Netherlands
  4. 4.Fraunhofer MEVISBremenGermany
  5. 5.Department of RadiologyUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands
  6. 6.Center for Medical Imaging-North East NetherlandsUniversity of Groningen, University Medical Centre GroningenGroningenThe Netherlands
  7. 7.Department of Public HealthErasmus Medical CenterRotterdamThe Netherlands
  8. 8.Department of PulmonologyErasmus Medical CenterRotterdamThe Netherlands
  9. 9.Department of RadiologyRadboud University Medical CenterNijmegenThe Netherlands

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