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Ki67 proliferation index in medullary thyroid carcinoma: a comparative study of multiple counting methods and validation of image analysis and deep learning platforms.

Saad NadeemMatthew G HannaKartik ViswanathanJoseph MarinoMahsa S AhadiBayan AlzumailiMohamed-Amine BaniFederico ChiarucciAngela ChouAntonio De LeoTalia L FuchsDaniel J LubinCatherine LuxfordKelly MaglioccaGermán MartinezQiuying ShiStan SidhuAbir Al GhuzlanAnthony J GillGiovanni TalliniRonald GhosseinRonald A Ghossein
Published in: Histopathology (2023)
We herein validate a machine learning-based deep-learning platform and an image analysis software with internal thresholding to generate accurate automatic Ki67 proliferation indices in medullary thyroid carcinoma. Manual Ki67 count remains useful when facing a tumour with a borderline Ki67 proliferation index of 3-7%. In daily practice, validation of alternative evaluation methods for the Ki67 index in MTC is required prior to implementation.
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