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Technical Note: Proof of concept for radiomics-based quality assurance for computed tomography.
Branco, Luciano R F; Ger, Rachel B; Mackin, Dennis S; Zhou, Shouhao; Court, Laurence E; Layman, Rick R.
Afiliação
  • Branco LRF; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Ger RB; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Mackin DS; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
  • Zhou S; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Court LE; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
  • Layman RR; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.
J Appl Clin Med Phys ; 20(11): 199-205, 2019 Nov.
Article em En | MEDLINE | ID: mdl-31609076
ABSTRACT

PURPOSE:

Routine quality assurance (QA) testing to identify malfunctions in medical imaging devices is a standard practice and plays an important role in meeting quality standards. However, current daily computed tomography (CT) QA techniques have proven to be inadequate for the detection of subtle artifacts on scans. Therefore, we investigated the ability of a radiomics phantom to detect subtle artifacts not detected in conventional daily QA.

METHODS:

An updated credence cartridge radiomics phantom was used in this study, with a focus on two of the cartridges (rubber and cork) in the phantom. The phantom was scanned using a Siemens Definition Flash CT scanner, which was reported to produce a subtle line pattern artifact. Images were then imported into the IBEX software program, and 49 features were extracted from the two cartridges using four different preprocessing techniques. Each feature was then compared with features for the same scanner several months previously and with features from controlled CT scans obtained using 100 scanners.

RESULTS:

Of 196 total features for the test scanner, 79 (40%) from the rubber cartridge and 70 (36%) from the cork cartridge were three or more standard deviations away from the mean of the controlled scan population data. Feature values for the artifact-producing scanner were closer to the population mean when features were preprocessed with Butterworth smoothing. The feature most sensitive to the artifact was co-occurrence matrix maximum probability. The deviation from the mean for this feature was more than seven times greater when the scanner was malfunctioning (7.56 versus 1.01).

CONCLUSIONS:

Radiomics features extracted from a texture phantom were able to identify an artifact-producing scanner as an outlier among 100 CT scanners. This preliminary analysis demonstrated the potential of radiomics in CT QA to identify subtle artifacts not detected using the currently employed daily QA techniques.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Garantia da Qualidade dos Cuidados de Saúde / Processamento de Imagem Assistida por Computador / Tomografia Computadorizada por Raios X / Tomógrafos Computadorizados / Imagens de Fantasmas / Linfoma Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: J Appl Clin Med Phys Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Garantia da Qualidade dos Cuidados de Saúde / Processamento de Imagem Assistida por Computador / Tomografia Computadorizada por Raios X / Tomógrafos Computadorizados / Imagens de Fantasmas / Linfoma Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: J Appl Clin Med Phys Ano de publicação: 2019 Tipo de documento: Article