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Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer.
Prezzi, Davide; Owczarczyk, Katarzyna; Bassett, Paul; Siddique, Muhammad; Breen, David J; Cook, Gary J R; Goh, Vicky.
Afiliación
  • Prezzi D; School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, Lambeth Wing, St Thomas' Hospital, London, SE1 7EH, UK. davide.prezzi@kcl.ac.uk.
  • Owczarczyk K; Department of Radiology, Guy's and St Thomas' NHS Foundation Trust, Lambeth Wing, St Thomas' Hospital, London, SE1 7EH, UK. davide.prezzi@kcl.ac.uk.
  • Bassett P; School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, Lambeth Wing, St Thomas' Hospital, London, SE1 7EH, UK.
  • Siddique M; Department of Clinical Oncology, Guy's and St Thomas' NHS Foundation Trust, Lambeth Wing, St Thomas' Hospital, London, SE1 7EH, UK.
  • Breen DJ; Statsconsultancy Ltd., 40 Longwood Lane, Amersham, Bucks, HP7 9EN, UK.
  • Cook GJR; School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, Lambeth Wing, St Thomas' Hospital, London, SE1 7EH, UK.
  • Goh V; University Hospital Southampton NHS Foundation Trust, Tremona Road, Southampton, SO16 6YD, UK.
Eur Radiol ; 29(10): 5227-5235, 2019 Oct.
Article en En | MEDLINE | ID: mdl-30887205
ABSTRACT

OBJECTIVES:

To investigate whether adaptive statistical iterative reconstruction (ASIR), a hybrid iterative CT image reconstruction algorithm, affects radiomics feature quantification in primary colorectal cancer compared to filtered back projection. Additionally, to establish whether radiomics from single-slice analysis undergo greater change than those from multi-slice analysis.

METHODS:

Following review board approval, contrast-enhanced CT studies from 32 prospective primary colorectal cancer patients were reconstructed with 20% ASIR level increments, from 0 to 100%. Radiomics analysis was applied to single-slice and multi-slice regions of interest outlining the tumour 70 features, including statistical (first-, second- and high-order) and fractal radiomics, were generated per dataset. The effect of ASIR was calculated by means of multilevel linear regression.

RESULTS:

Twenty-eight CT datasets were suitable for analysis. Incremental ASIR levels determined a significant change (p < 0.001) in most statistical radiomics features, best described by a simple linear relationship. First-order statistical features, including mean, standard deviation, skewness, kurtosis, energy and entropy, underwent a relatively small change in both single-slice and multi-slice analysis (median standardised effect size B = 0.08). Second-order statistical features, including grey-level co-occurrence and difference matrices, underwent a greater change in single-slice analysis (median B = 0.36) than in multi-slice analysis (median B = 0.13). Fractal features underwent a significant change only in single-slice analysis (median B = 0.49).

CONCLUSIONS:

Incremental levels of ASIR affect significantly CT radiomics quantification in primary colorectal cancer. Second-order statistical and fractal features derived from single-slice analysis undergo greater change than those from multi-slice analysis. KEY POINTS • Incremental levels of ASIR determine a significant change in most statistical (first-, second- and high-order) CT radiomics features measured in primary colorectal cancer, best described by a linear relationship. • First-order statistical features undergo a small change, both from single-slice and multi-slice radiomics analyses. • Most second-order statistical features undergo a greater change in single-slice analysis than in multi-slice analysis. Fractal features are only affected in single-slice analysis.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias Colorrectales Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias Colorrectales Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido