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Derivation of a nuclear heterogeneity image index to grade DCIS.

Publication ,  Journal Article
Hayward, M-K; Louise Jones, J; Hall, A; King, L; Ironside, AJ; Nelson, AC; Shelley Hwang, E; Weaver, VM
Published in: Comput Struct Biotechnol J
2020

Abnormalities in cell nuclear morphology are a hallmark of cancer. Histological assessment of cell nuclear morphology is frequently used by pathologists to grade ductal carcinoma in situ (DCIS). Objective methods that allow standardization and reproducibility of cell nuclear morphology assessment have potential to improve the criteria needed to predict DCIS progression and recurrence. Aggressive cancers are highly heterogeneous. We asked whether cell nuclear morphology heterogeneity could be incorporated into a metric to classify DCIS. We developed a nuclear heterogeneity image index to objectively, and quantitatively grade DCIS. A whole-tissue cell nuclear morphological analysis, that classified tumors by the worst ten percent in a duct-by-duct manner, identified nuclear size ranges associated with each DCIS grade. Digital image analysis further revealed increasing heterogeneity within ducts or between ducts in tissues of worsening DCIS grade. The findings illustrate how digital image analysis comprises a supplemental tool for pathologists to objectively classify DCIS and in the future, may provide a method to predict patient outcome through analysis of nuclear heterogeneity.

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Published In

Comput Struct Biotechnol J

DOI

ISSN

2001-0370

Publication Date

2020

Volume

18

Start / End Page

4063 / 4070

Location

Netherlands

Related Subject Headings

  • 4601 Applied computing
  • 3101 Biochemistry and cell biology
  • 0802 Computation Theory and Mathematics
  • 0103 Numerical and Computational Mathematics
 

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Hayward, M.-K., Louise Jones, J., Hall, A., King, L., Ironside, A. J., Nelson, A. C., … Weaver, V. M. (2020). Derivation of a nuclear heterogeneity image index to grade DCIS. Comput Struct Biotechnol J, 18, 4063–4070. https://doi.org/10.1016/j.csbj.2020.11.040
Hayward, Mary-Kate, J. Louise Jones, Allison Hall, Lorraine King, Alastair J. Ironside, Andrew C. Nelson, E. Shelley Hwang, and Valerie M. Weaver. “Derivation of a nuclear heterogeneity image index to grade DCIS.Comput Struct Biotechnol J 18 (2020): 4063–70. https://doi.org/10.1016/j.csbj.2020.11.040.
Hayward M-K, Louise Jones J, Hall A, King L, Ironside AJ, Nelson AC, et al. Derivation of a nuclear heterogeneity image index to grade DCIS. Comput Struct Biotechnol J. 2020;18:4063–70.
Hayward, Mary-Kate, et al. “Derivation of a nuclear heterogeneity image index to grade DCIS.Comput Struct Biotechnol J, vol. 18, 2020, pp. 4063–70. Pubmed, doi:10.1016/j.csbj.2020.11.040.
Hayward M-K, Louise Jones J, Hall A, King L, Ironside AJ, Nelson AC, Shelley Hwang E, Weaver VM. Derivation of a nuclear heterogeneity image index to grade DCIS. Comput Struct Biotechnol J. 2020;18:4063–4070.
Journal cover image

Published In

Comput Struct Biotechnol J

DOI

ISSN

2001-0370

Publication Date

2020

Volume

18

Start / End Page

4063 / 4070

Location

Netherlands

Related Subject Headings

  • 4601 Applied computing
  • 3101 Biochemistry and cell biology
  • 0802 Computation Theory and Mathematics
  • 0103 Numerical and Computational Mathematics