Reconstructing Virtual Large Slides Can Improve the Accuracy and Consistency of Tumor Bed Evaluation for Breast Cancer After Neoadjuvant Therapy

Overview

Journal Diagn Pathol

Publisher Biomed Central

Specialty Pathology

Date 2022 Apr 28

PMID 35484579

Authors

Dandan Han

Jun Liao

Meng Zhang

Chenchen Qin

Mengxue Han

Chun Wu

Jinze Li

Jianhua Yao

Yueping Liu

Affiliations

Soon will be listed here.

Abstract

Background: To explore whether the "WSI Stitcher", a program we developed for reconstructing virtual large slide through whole slide imaging fragments stitching, can improve the efficiency and consistency of pathologists in evaluating the tumor bed after neoadjuvant treatment of breast cancer compared with the conventional methods through stack splicing of physical slides.

Methods: This study analyzed the advantages of using software-assisted methods to evaluate the tumor bed after neoadjuvant treatment of breast cancer. This new method is to use "WSI Stitcher" to stitch all the WSI fragments together to reconstruct a virtual large slide and evaluate the tumor bed with the help of the built-in ruler and tumor proportion calculation functions.

Results: Compared with the conventional method, the evaluation time of the software-assisted method was shortened by 35%(P < 0.001). In the process of tumor bed assessment after neoadjuvant treatment of breast cancer, the software-assisted method has higher intraclass correlation coefficient when measuring the length (0.994 versus 0.934), width (0.992 versus 0.927), percentage of residual tumor cells (0.947 versus 0.878), percentage of carcinoma in situ (0.983 versus 0.881) and RCB index(0.997 versus 0.772). The software-assisted method has higher kappa values when evaluating tumor staging(0.901 versus 0.687) and RCB grading (0.963 versus 0.857).

Conclusion: The "WSI Stitcher" is an effective tool to help pathologists with the assessment of breast cancer after neoadjuvant treatment.

Citing Articles

Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments.

Schouten D, van der Laak J, van Ginneken B, Litjens G Sci Rep. 2024; 14(1):1497.

PMID: 38233535 PMC: 10794243. DOI: 10.1038/s41598-024-52007-5.

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