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Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images.

Publication ,  Journal Article
Dov, D; Kovalsky, SZ; Feng, Q; Assaad, S; Cohen, J; Bell, J; Henao, R; Carin, L; Range, DE
Published in: Arch Pathol Lab Med
July 1, 2022

CONTEXT.—: The use of whole slide images (WSIs) in diagnostic pathology presents special challenges for the cytopathologist. Informative areas on a direct smear from a thyroid fine-needle aspiration biopsy (FNAB) smear may be spread across a large area comprising blood and dead space. Manually navigating through these areas makes screening and evaluation of FNA smears on a digital platform time-consuming and laborious. We designed a machine learning algorithm that can identify regions of interest (ROIs) on thyroid fine-needle aspiration biopsy WSIs. OBJECTIVE.—: To evaluate the ability of the machine learning algorithm and screening software to identify and screen for a subset of informative ROIs on a thyroid FNA WSI that can be used for final diagnosis. DESIGN.—: A representative slide from each of 109 consecutive thyroid fine-needle aspiration biopsies was scanned. A cytopathologist reviewed each WSI and recorded a diagnosis. The machine learning algorithm screened and selected a subset of 100 ROIs from each WSI to present as an image gallery to the same cytopathologist after a washout period of 117 days. RESULTS.—: Concordance between the diagnoses using WSIs and those using the machine learning algorithm-generated ROI image gallery was evaluated using pairwise weighted κ statistics. Almost perfect concordance was seen between the 2 methods with a κ score of 0.924. CONCLUSIONS.—: Our results show the potential of the screening software as an effective screening tool with the potential to reduce cytopathologist workloads.

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Published In

Arch Pathol Lab Med

DOI

EISSN

1543-2165

Publication Date

July 1, 2022

Volume

146

Issue

7

Start / End Page

872 / 878

Location

United States

Related Subject Headings

  • Thyroid Gland
  • Software
  • Pathology
  • Machine Learning
  • Humans
  • Biopsy, Fine-Needle
  • Algorithms
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

APA
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ICMJE
MLA
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Dov, D., Kovalsky, S. Z., Feng, Q., Assaad, S., Cohen, J., Bell, J., … Range, D. E. (2022). Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images. Arch Pathol Lab Med, 146(7), 872–878. https://doi.org/10.5858/arpa.2020-0712-OA
Dov, David, Shahar Z. Kovalsky, Qizhang Feng, Serge Assaad, Jonathan Cohen, Jonathan Bell, Ricardo Henao, Lawrence Carin, and Danielle Elliott Range. “Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images.Arch Pathol Lab Med 146, no. 7 (July 1, 2022): 872–78. https://doi.org/10.5858/arpa.2020-0712-OA.
Dov D, Kovalsky SZ, Feng Q, Assaad S, Cohen J, Bell J, et al. Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images. Arch Pathol Lab Med. 2022 Jul 1;146(7):872–8.
Dov, David, et al. “Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images.Arch Pathol Lab Med, vol. 146, no. 7, July 2022, pp. 872–78. Pubmed, doi:10.5858/arpa.2020-0712-OA.
Dov D, Kovalsky SZ, Feng Q, Assaad S, Cohen J, Bell J, Henao R, Carin L, Range DE. Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images. Arch Pathol Lab Med. 2022 Jul 1;146(7):872–878.

Published In

Arch Pathol Lab Med

DOI

EISSN

1543-2165

Publication Date

July 1, 2022

Volume

146

Issue

7

Start / End Page

872 / 878

Location

United States

Related Subject Headings

  • Thyroid Gland
  • Software
  • Pathology
  • Machine Learning
  • Humans
  • Biopsy, Fine-Needle
  • Algorithms
  • 3202 Clinical sciences
  • 1103 Clinical Sciences