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Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer

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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.

In: European Radiology, Vol. 29, No. 10, 01.10.2019, p. 5227-5235.

Research output: Contribution to journalArticle

Harvard

Prezzi, D, Owczarczyk, K, Bassett, P, Siddique, M, Breen, DJ, Cook, GJR & Goh, V 2019, 'Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer', European Radiology, vol. 29, no. 10, pp. 5227-5235. https://doi.org/10.1007/s00330-019-06073-3

APA

Prezzi, D., Owczarczyk, K., Bassett, P., Siddique, M., Breen, D. J., Cook, G. J. R., & Goh, V. (2019). Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer. European Radiology, 29(10), 5227-5235. https://doi.org/10.1007/s00330-019-06073-3

Vancouver

Prezzi D, Owczarczyk K, Bassett P, Siddique M, Breen DJ, Cook GJR et al. Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer. European Radiology. 2019 Oct 1;29(10):5227-5235. https://doi.org/10.1007/s00330-019-06073-3

Author

Prezzi, Davide ; Owczarczyk, Katarzyna ; Bassett, Paul ; Siddique, Muhammad ; Breen, David J. ; Cook, Gary J.R. ; Goh, Vicky. / Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer. In: European Radiology. 2019 ; Vol. 29, No. 10. pp. 5227-5235.

Bibtex Download

@article{68cb6595834d45dfbea2a484c442a7a8,
title = "Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer",
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.",
keywords = "Colorectal neoplasms, Computer-assisted, Fractals, Image processing, Multidetector computed tomography",
author = "Davide Prezzi and Katarzyna Owczarczyk and Paul Bassett and Muhammad Siddique and Breen, {David J.} and Cook, {Gary J.R.} and Vicky Goh",
year = "2019",
month = oct,
day = "1",
doi = "10.1007/s00330-019-06073-3",
language = "English",
volume = "29",
pages = "5227--5235",
journal = "European Radiology",
issn = "0938-7994",
publisher = "Springer Verlag",
number = "10",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer

AU - Prezzi, Davide

AU - Owczarczyk, Katarzyna

AU - Bassett, Paul

AU - Siddique, Muhammad

AU - Breen, David J.

AU - Cook, Gary J.R.

AU - Goh, Vicky

PY - 2019/10/1

Y1 - 2019/10/1

N2 - 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.

AB - 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.

KW - Colorectal neoplasms

KW - Computer-assisted

KW - Fractals

KW - Image processing

KW - Multidetector computed tomography

UR - http://www.scopus.com/inward/record.url?scp=85063214080&partnerID=8YFLogxK

U2 - 10.1007/s00330-019-06073-3

DO - 10.1007/s00330-019-06073-3

M3 - Article

C2 - 30887205

AN - SCOPUS:85063214080

VL - 29

SP - 5227

EP - 5235

JO - European Radiology

JF - European Radiology

SN - 0938-7994

IS - 10

ER -

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