Stereology and computer-based image analysis quantifies heterogeneity and improves reproducibility for grading reticulin in myeloproliferative neoplasms

Mohamed Salama, Erik Hagendorn, Sherrie L. Perkins, Jeff L. Kutok, A. Etman, Josef T. Prchal, Steven J. Potts

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Evaluation of bone marrow fibrosis in myeloproliferative neoplasms (MPN) is subject to interobserver inconsistency, and cutpoints for determination of therapy are dependent on manual pathologist grading of reticulin. To provide a more consistent approach to cutpoint determination, we developed a stereology-based method of calculating length fiber density (the length of the fiber network divided by the volume of bone marrow hematopoietic tissue). Forty-eight thin needle core bone marrow biopsy samples from patients with MPN were obtained from the University of Utah archives after institutional review board approval and stained for reticulin and then scanned using whole slide imaging. To determine interpathologist concordance, the blinded cases were scored according to the European consensus system by four pathologists. Two pathologists scored twice with a 1-month washout period to determine intrapathologist concordance. Using systematic uniform random sampling and line counting, two techniques adapted from the stereology field, the length density of the reticulin network was measured as well as a measure of heterogeneity across the bone marrow sample. Image analysis was used to measure the area of the reticulin fiber as a two-dimensional profile. To build a model for predicting scoring by stereology, 16 samples were chosen randomly and a linear regression relationship determined. This score was then rounded to 0, 1, 2, or 3, and concordance rates between pathologists and between pathologist and the computer stereology score determined.: In the 48 patient cohort, stereology assessment was well correlated with the average of manual pathologist scoring (linear regression, 2=0.7038). While the European consensus scoring system ranges from 0 to 3, the cutpoint between 0/1 and 2/3 is generally used for guiding therapeutic decision as myelofibrosis. In 7 of the 48 cases (15 %), pathologists had differing scores across this cutpoint, meaning that the ultimate therapeutic outcome would have been impacted. The stereology score differed with the average of the pathologist scores in only 5 of the 48 cases across this cutpoint (10 %). Precision rates for the stereology analysis were 92 %, compared with interpathologist concordance ranging from 54.2 to 65.2 % and intrapathologist at 60.9 %. Computer-based stereology proved to be more reproducible at predicting therapeutic cutpoint than manual scoring. The new technique can be run using standard histochemistry and provides both a nonbiased systematic measure of reticulin and a new measure of reticulin heterogeneity.

Original languageEnglish (US)
Title of host publicationMolecular Histopathology and Tissue Biomarkers in Drug and Diagnostic Development
PublisherSpringer New York
Pages117-126
Number of pages10
ISBN (Electronic)9781493926817
ISBN (Print)9781493926800
DOIs
StatePublished - Jun 15 2015
Externally publishedYes

Fingerprint

Reticulin
Neoplasms
Primary Myelofibrosis
Bone Marrow
Linear Models
Pathologists
Research Ethics Committees
Therapeutics
Needles
Biopsy

Keywords

  • Bone marrow fibrosis
  • Digital imaging
  • Myelofibrosis
  • Myeloproliferative neoplasms
  • Reticulin scoring

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Salama, M., Hagendorn, E., Perkins, S. L., Kutok, J. L., Etman, A., Prchal, J. T., & Potts, S. J. (2015). Stereology and computer-based image analysis quantifies heterogeneity and improves reproducibility for grading reticulin in myeloproliferative neoplasms. In Molecular Histopathology and Tissue Biomarkers in Drug and Diagnostic Development (pp. 117-126). Springer New York. https://doi.org/10.1007/7653_2014_36

Stereology and computer-based image analysis quantifies heterogeneity and improves reproducibility for grading reticulin in myeloproliferative neoplasms. / Salama, Mohamed; Hagendorn, Erik; Perkins, Sherrie L.; Kutok, Jeff L.; Etman, A.; Prchal, Josef T.; Potts, Steven J.

Molecular Histopathology and Tissue Biomarkers in Drug and Diagnostic Development. Springer New York, 2015. p. 117-126.

Research output: Chapter in Book/Report/Conference proceedingChapter

Salama, M, Hagendorn, E, Perkins, SL, Kutok, JL, Etman, A, Prchal, JT & Potts, SJ 2015, Stereology and computer-based image analysis quantifies heterogeneity and improves reproducibility for grading reticulin in myeloproliferative neoplasms. in Molecular Histopathology and Tissue Biomarkers in Drug and Diagnostic Development. Springer New York, pp. 117-126. https://doi.org/10.1007/7653_2014_36
Salama M, Hagendorn E, Perkins SL, Kutok JL, Etman A, Prchal JT et al. Stereology and computer-based image analysis quantifies heterogeneity and improves reproducibility for grading reticulin in myeloproliferative neoplasms. In Molecular Histopathology and Tissue Biomarkers in Drug and Diagnostic Development. Springer New York. 2015. p. 117-126 https://doi.org/10.1007/7653_2014_36
Salama, Mohamed ; Hagendorn, Erik ; Perkins, Sherrie L. ; Kutok, Jeff L. ; Etman, A. ; Prchal, Josef T. ; Potts, Steven J. / Stereology and computer-based image analysis quantifies heterogeneity and improves reproducibility for grading reticulin in myeloproliferative neoplasms. Molecular Histopathology and Tissue Biomarkers in Drug and Diagnostic Development. Springer New York, 2015. pp. 117-126
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abstract = "Evaluation of bone marrow fibrosis in myeloproliferative neoplasms (MPN) is subject to interobserver inconsistency, and cutpoints for determination of therapy are dependent on manual pathologist grading of reticulin. To provide a more consistent approach to cutpoint determination, we developed a stereology-based method of calculating length fiber density (the length of the fiber network divided by the volume of bone marrow hematopoietic tissue). Forty-eight thin needle core bone marrow biopsy samples from patients with MPN were obtained from the University of Utah archives after institutional review board approval and stained for reticulin and then scanned using whole slide imaging. To determine interpathologist concordance, the blinded cases were scored according to the European consensus system by four pathologists. Two pathologists scored twice with a 1-month washout period to determine intrapathologist concordance. Using systematic uniform random sampling and line counting, two techniques adapted from the stereology field, the length density of the reticulin network was measured as well as a measure of heterogeneity across the bone marrow sample. Image analysis was used to measure the area of the reticulin fiber as a two-dimensional profile. To build a model for predicting scoring by stereology, 16 samples were chosen randomly and a linear regression relationship determined. This score was then rounded to 0, 1, 2, or 3, and concordance rates between pathologists and between pathologist and the computer stereology score determined.: In the 48 patient cohort, stereology assessment was well correlated with the average of manual pathologist scoring (linear regression, 2=0.7038). While the European consensus scoring system ranges from 0 to 3, the cutpoint between 0/1 and 2/3 is generally used for guiding therapeutic decision as myelofibrosis. In 7 of the 48 cases (15 {\%}), pathologists had differing scores across this cutpoint, meaning that the ultimate therapeutic outcome would have been impacted. The stereology score differed with the average of the pathologist scores in only 5 of the 48 cases across this cutpoint (10 {\%}). Precision rates for the stereology analysis were 92 {\%}, compared with interpathologist concordance ranging from 54.2 to 65.2 {\%} and intrapathologist at 60.9 {\%}. Computer-based stereology proved to be more reproducible at predicting therapeutic cutpoint than manual scoring. The new technique can be run using standard histochemistry and provides both a nonbiased systematic measure of reticulin and a new measure of reticulin heterogeneity.",
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