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Open Access 01-12-2022 | Prostate Cancer | Research

The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study

Authors: Maíra Suzuka Kudo, Vinicius Meneguette Gomes de Souza, Carmen Liane Neubarth Estivallet, Henrique Alves de Amorim, Fernando J. Kim, Katia Ramos Moreira Leite, Matheus Cardoso Moraes

Published in: Patient Safety in Surgery | Issue 1/2022

Abstract

Background

The Gleason grading system is an important clinical practice for diagnosing prostate cancer in pathology images. However, this analysis results in significant variability among pathologists, hence creating possible negative clinical impacts. Artificial intelligence methods can be an important support for the pathologist, improving Gleason grade classifications. Consequently, our purpose is to construct and evaluate the potential of a Convolutional Neural Network (CNN) to classify Gleason patterns.

Methods

The methodology included 6982 image patches with cancer, extracted from radical prostatectomy specimens previously analyzed by an expert uropathologist. A CNN was constructed to accurately classify the corresponding Gleason. The evaluation was carried out by computing the corresponding 3 classes confusion matrix; thus, calculating the percentage of precision, sensitivity, and specificity, as well as the overall accuracy. Additionally, k-fold three-way cross-validation was performed to enhance evaluation, allowing better interpretation and avoiding possible bias.

Results

The overall accuracy reached 98% for the training and validation stage, and 94% for the test phase. Considering the test samples, the true positive ratio between pathologist and computer method was 85%, 93%, and 96% for specific Gleason patterns. Finally, precision, sensitivity, and specificity reached values up to 97%.

Conclusion

The CNN model presented and evaluated has shown high accuracy for specifically pattern neighbors and critical Gleason patterns. The outcomes are in line and complement others in the literature. The promising results surpassed current inter-pathologist congruence in classical reports, evidencing the potential of this novel technology in daily clinical aspects.

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Title: The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study
Authors: Maíra Suzuka Kudo
Vinicius Meneguette Gomes de Souza
Carmen Liane Neubarth Estivallet
Henrique Alves de Amorim
Fernando J. Kim
Katia Ramos Moreira Leite
Matheus Cardoso Moraes
Publication date: 01-12-2022
Publisher: BioMed Central
Keywords: Prostate Cancer
Artificial Intelligence
Prostate Cancer
Confusion
Prostatectomy
Pathology
Prostatectomy
Published in: Patient Safety in Surgery / Issue 1/2022
Electronic ISSN: 1754-9493
DOI: https://doi.org/10.1186/s13037-022-00345-6

Keynote webinar | Spotlight on medication adherence

Springer Medicine

The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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