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Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT.
Godoy, Myrna C B; Kim, Tae Jung; White, Charles S; Bogoni, Luca; de Groot, Patricia; Florin, Charles; Obuchowski, Nancy; Babb, James S; Salganicoff, Marcos; Naidich, David P; Anand, Vikram; Park, Sangmin; Vlahos, Ioannis; Ko, Jane P.
Afiliação
  • Godoy MC; Department of Radiology, New York University Langone Medical Center, 560 First Ave, IRM 236, New York, NY 10016, USA.
AJR Am J Roentgenol ; 200(1): 74-83, 2013 Jan.
Article em En | MEDLINE | ID: mdl-23255744
ABSTRACT

OBJECTIVE:

The objective of our study was to evaluate the impact of computer-aided detection (CAD) on the identification of subsolid and solid lung nodules on thin- and thick-section CT. MATERIALS AND

METHODS:

For 46 chest CT examinations with ground-glass opacity (GGO) nodules, CAD marks computed using thin data were evaluated in two phases. First, four chest radiologists reviewed thin sections (reader(thin)) for nodules and subsequently CAD marks (reader(thin) + CAD(thin)). After 4 months, the same cases were reviewed on thick sections (reader(thick)) and subsequently with CAD marks (reader(thick) + CAD(thick)). Sensitivities were evaluated. Additionally, reader(thick) sensitivity with assessment of CAD marks on thin sections was estimated (reader(thick) + CAD(thin)).

RESULTS:

For 155 nodules (mean, 5.5 mm; range, 4.0-27.5 mm)-74 solid nodules, 22 part-solid (part-solid nodules), and 59 GGO nodules-CAD stand-alone sensitivity was 80%, 95%, and 71%, respectively, with three false-positives on average (0-12) per CT study. Reader(thin) + CAD(thin) sensitivities were higher than reader(thin) for solid nodules (82% vs 57%, p < 0.001), part-solid nodules (97% vs 81%, p = 0.0027), and GGO nodules (82% vs 69%, p < 0.001) for all readers (p < 0.001). Respective sensitivities for reader(thick), reader(thick) + CAD(thick), reader(thick) + CAD(thin) were 40%, 58% (p < 0.001), and 77% (p < 0.001) for solid nodules; 72%, 73% (p = 0.322), and 94% (p < 0.001) for part-solid nodules; and 53%, 58% (p = 0.008), and 79% (p < 0.001) for GGO nodules. For reader(thin), false-positives increased from 0.64 per case to 0.90 with CAD(thin) (p < 0.001) but not for reader(thick); false-positive rates were 1.17, 1.19, and 1.26 per case for reader(thick), reader(thick) + CAD(thick), and reader(thick) + CAD(thin), respectively.

CONCLUSION:

Detection of GGO nodules and solid nodules is significantly improved with CAD. When interpretation is performed on thick sections, the benefit is greater when CAD marks are reviewed on thin rather than thick sections.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Radiográfica Assistida por Computador / Tomografia Computadorizada por Raios X / Nódulo Pulmonar Solitário / Nódulos Pulmonares Múltiplos / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: AJR Am J Roentgenol Ano de publicação: 2013 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Radiográfica Assistida por Computador / Tomografia Computadorizada por Raios X / Nódulo Pulmonar Solitário / Nódulos Pulmonares Múltiplos / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: AJR Am J Roentgenol Ano de publicação: 2013 Tipo de documento: Article País de afiliação: Estados Unidos