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    Digital pathology has been increasingly implemented for primary surgical pathology diagnosis. In our institution, digital pathology was recently deployed in the gynecologic (GYN) pathology practice. A notable challenge encountered in the digital evaluation of GYN specimens was high rates of scanning failure of specimens with fragmented as well as scant tissue. To improve tissue detection failure rates, we implemented a novel use of the collodion bag cell block preparation method. In this study, we reviewed 108 endocervical curettage (ECC) specimens, representing specimens processed with and without the collodion bag cell block method (n = 56 without collodion bag, n = 52 with collodion bag). Tissue detection failure rates were reduced from 77% (43/56) in noncollodion bag cases to 23/52 (44%) of collodion bag cases, representing a 42% reduction. The median total area of tissue detection failure per level was 0.35 mm2 (interquartile range [IQR]: 0.14, 0.70 mm2) for noncollodion bag cases and 0.08 mm2 (IQR: 0.03, 0.20 mm2) for collodion bag cases. This represents a greater than fourfold reduction in the total area of tissue detection failure per level (P < 0.001). In addition, there were no out-of-focus levels among collodion bag cases, compared to 6/56 (11%) of noncollodion bag cases (median total area = 4.9 mm2). The collodion bag method significantly improved the digital image quality of fragmented/scant GYN curettage specimens, increased efficiency and accuracy of diagnostic evaluation, and enhanced identification of tissue contamination during processing. The logistical challenges and labor cost of deploying the collodion bag protocol are important considerations for feasibility assessment at an institutional level. Copyright: © 2021 Journal of Pathology Informatics.

    Citation

    Iny Jhun, David Levy, Harumi Lim, Quintina Herrera, Erika Dobo, Dominique Burns, William Hetherington, Ronald Macasaet, April J Young, Christina S Kong, Ann K Folkins, Eric Joon Yang. Implementation of Collodion Bag Protocol to Improve Whole-slide Imaging of Scant Gynecologic Curettage Specimens. Journal of pathology informatics. 2021;12:2


    PMID: 34012706

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