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Classification of follicular lymphoma: the effect of computer aid on pathologists grading

BACKGROUND: Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL cases are stratified into three histological grades based on the average centroblast count per high power field (HPF). The centroblast count is performed manually by the pathologist using an...

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Autores principales: Fauzi, Mohammad Faizal Ahmad, Pennell, Michael, Sahiner, Berkman, Chen, Weijie, Shana’ah, Arwa, Hemminger, Jessica, Gru, Alejandro, Kurt, Habibe, Losos, Michael, Joehlin-Price, Amy, Kavran, Christina, Smith, Stephen M., Nowacki, Nicholas, Mansor, Sharmeen, Lozanski, Gerard, Gurcan, Metin N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4696238/
https://www.ncbi.nlm.nih.gov/pubmed/26715518
http://dx.doi.org/10.1186/s12911-015-0235-6
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author Fauzi, Mohammad Faizal Ahmad
Pennell, Michael
Sahiner, Berkman
Chen, Weijie
Shana’ah, Arwa
Hemminger, Jessica
Gru, Alejandro
Kurt, Habibe
Losos, Michael
Joehlin-Price, Amy
Kavran, Christina
Smith, Stephen M.
Nowacki, Nicholas
Mansor, Sharmeen
Lozanski, Gerard
Gurcan, Metin N.
author_facet Fauzi, Mohammad Faizal Ahmad
Pennell, Michael
Sahiner, Berkman
Chen, Weijie
Shana’ah, Arwa
Hemminger, Jessica
Gru, Alejandro
Kurt, Habibe
Losos, Michael
Joehlin-Price, Amy
Kavran, Christina
Smith, Stephen M.
Nowacki, Nicholas
Mansor, Sharmeen
Lozanski, Gerard
Gurcan, Metin N.
author_sort Fauzi, Mohammad Faizal Ahmad
collection PubMed
description BACKGROUND: Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL cases are stratified into three histological grades based on the average centroblast count per high power field (HPF). The centroblast count is performed manually by the pathologist using an optical microscope and hematoxylin and eosin (H&E) stained tissue section. Although this is the current clinical practice, it suffers from high inter- and intra-observer variability and is vulnerable to sampling bias. METHODS: In this paper, we present a system, called Follicular Lymphoma Grading System (FLAGS), to assist the pathologist in grading FL cases. We also assess the effect of FLAGS on accuracy of expert and inexperienced readers. FLAGS automatically identifies possible HPFs for examination by analyzing H&E and CD20 stains, before classifying them into low or high risk categories. The pathologist is first asked to review the slides according to the current routine clinical practice, before being presented with FLAGS classification via color-coded map. The accuracy of the readers with and without FLAGS assistance is measured. RESULTS: FLAGS was used by four experts (board-certified hematopathologists) and seven pathology residents on 20 FL slides. Access to FLAGS improved overall reader accuracy with the biggest improvement seen among residents. An average AUC value of 0.75 was observed which generally indicates “acceptable” diagnostic performance. CONCLUSIONS: The results of this study show that FLAGS can be useful in increasing the pathologists’ accuracy in grading the tissue. To the best of our knowledge, this study measure, for the first time, the effect of computerized image analysis on pathologists’ grading of follicular lymphoma. When fully developed, such systems have the potential to reduce sampling bias by examining an increased proportion of HPFs within follicle regions, as well as to reduce inter- and intra-reader variability. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-015-0235-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-46962382015-12-31 Classification of follicular lymphoma: the effect of computer aid on pathologists grading Fauzi, Mohammad Faizal Ahmad Pennell, Michael Sahiner, Berkman Chen, Weijie Shana’ah, Arwa Hemminger, Jessica Gru, Alejandro Kurt, Habibe Losos, Michael Joehlin-Price, Amy Kavran, Christina Smith, Stephen M. Nowacki, Nicholas Mansor, Sharmeen Lozanski, Gerard Gurcan, Metin N. BMC Med Inform Decis Mak Research Article BACKGROUND: Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL cases are stratified into three histological grades based on the average centroblast count per high power field (HPF). The centroblast count is performed manually by the pathologist using an optical microscope and hematoxylin and eosin (H&E) stained tissue section. Although this is the current clinical practice, it suffers from high inter- and intra-observer variability and is vulnerable to sampling bias. METHODS: In this paper, we present a system, called Follicular Lymphoma Grading System (FLAGS), to assist the pathologist in grading FL cases. We also assess the effect of FLAGS on accuracy of expert and inexperienced readers. FLAGS automatically identifies possible HPFs for examination by analyzing H&E and CD20 stains, before classifying them into low or high risk categories. The pathologist is first asked to review the slides according to the current routine clinical practice, before being presented with FLAGS classification via color-coded map. The accuracy of the readers with and without FLAGS assistance is measured. RESULTS: FLAGS was used by four experts (board-certified hematopathologists) and seven pathology residents on 20 FL slides. Access to FLAGS improved overall reader accuracy with the biggest improvement seen among residents. An average AUC value of 0.75 was observed which generally indicates “acceptable” diagnostic performance. CONCLUSIONS: The results of this study show that FLAGS can be useful in increasing the pathologists’ accuracy in grading the tissue. To the best of our knowledge, this study measure, for the first time, the effect of computerized image analysis on pathologists’ grading of follicular lymphoma. When fully developed, such systems have the potential to reduce sampling bias by examining an increased proportion of HPFs within follicle regions, as well as to reduce inter- and intra-reader variability. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-015-0235-6) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-30 /pmc/articles/PMC4696238/ /pubmed/26715518 http://dx.doi.org/10.1186/s12911-015-0235-6 Text en © Fauzi et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Fauzi, Mohammad Faizal Ahmad
Pennell, Michael
Sahiner, Berkman
Chen, Weijie
Shana’ah, Arwa
Hemminger, Jessica
Gru, Alejandro
Kurt, Habibe
Losos, Michael
Joehlin-Price, Amy
Kavran, Christina
Smith, Stephen M.
Nowacki, Nicholas
Mansor, Sharmeen
Lozanski, Gerard
Gurcan, Metin N.
Classification of follicular lymphoma: the effect of computer aid on pathologists grading
title Classification of follicular lymphoma: the effect of computer aid on pathologists grading
title_full Classification of follicular lymphoma: the effect of computer aid on pathologists grading
title_fullStr Classification of follicular lymphoma: the effect of computer aid on pathologists grading
title_full_unstemmed Classification of follicular lymphoma: the effect of computer aid on pathologists grading
title_short Classification of follicular lymphoma: the effect of computer aid on pathologists grading
title_sort classification of follicular lymphoma: the effect of computer aid on pathologists grading
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4696238/
https://www.ncbi.nlm.nih.gov/pubmed/26715518
http://dx.doi.org/10.1186/s12911-015-0235-6
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