Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images.
Kovalsky, Shahar Z
Range, Danielle Elliott
Online Publication Date2021-10-20
Print Publication Date2021-10-20
Permanent link to this recordhttp://hdl.handle.net/10754/672961
MetadataShow full item record
AbstractThe 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. 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. 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. 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. Our results show the potential of the screening software as an effective screening tool with the potential to reduce cytopathologist workloads.
CitationDov, D., Kovalsky, S. Z., Feng, Q., Assaad, S., Cohen, J., Bell, J., … Range, D. E. (2021). Use of Machine Learning–Based Software for the Screening of Thyroid Cytopathology Whole Slide Images. Archives of Pathology & Laboratory Medicine. doi:10.5858/arpa.2020-0712-oa
- Application of a machine learning algorithm to predict malignancy in thyroid cytopathology.
- Authors: Elliott Range DD, Dov D, Kovalsky SZ, Henao R, Carin L, Cohen J
- Issue date: 2020 Apr
- Comparison of glass slides and various digital-slide modalities for cytopathology screening and interpretation.
- Authors: Hanna MG, Monaco SE, Cuda J, Xing J, Ahmed I, Pantanowitz L
- Issue date: 2017 Sep
- Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies.
- Authors: Chen Y, Zee J, Smith A, Jayapandian C, Hodgin J, Howell D, Palmer M, Thomas D, Cassol C, Farris AB 3rd, Perkinson K, Madabhushi A, Barisoni L, Janowczyk A
- Issue date: 2021 Mar
- Evaluation of whole slide image immunohistochemistry interpretation in challenging prostate needle biopsies.
- Authors: Fine JL, Grzybicki DM, Silowash R, Ho J, Gilbertson JR, Anthony L, Wilson R, Parwani AV, Bastacky SI, Epstein JI, Jukic DM
- Issue date: 2008 Apr
- Assessment of malignancy for atypia of undetermined significance in thyroid fine-needle aspiration biopsy evaluated by whole-slide image analysis.
- Authors: Collins BT, Collins LE
- Issue date: 2013 Jun