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Annals of Nuclear Medicine
Published in: Annals of Nuclear Medicine 11/2020

01-11-2020 | Prostate Cancer | Original Article

Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy

Authors: Nikolaos Papandrianos, Elpiniki I. Papageorgiou, Athanasios Anagnostis

Published in: Annals of Nuclear Medicine | Issue 11/2020

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Abstract

Objective

The main aim of this work is to build a robust Convolutional Neural Network (CNN) algorithm that efficiently and quickly classifies bone scintigraphy images, by determining the presence or absence of prostate cancer metastasis.

Methods

CNN, widely applied in medical image classification, was used for bone scintigraphy image classification. The retrospective study included 778 sequential male patients who underwent whole-body bone scans. A nuclear medicine physician classified all the cases into 3 categories: (1) normal, (2) malignant, and (3) degenerative, which were used as the gold standard.

Results

An efficient CNN architecture was built, based on CNN exploration performance, achieving high prediction accuracy. The results showed that the method is sufficiently precise when it comes to differentiating a bone metastasis from other either degenerative changes or normal tissue (overall classification accuracy = 91.42% ± 1.64%). To strengthen the outcomes of this study the authors further compared the best performing CNN method to other popular CNN architectures for medical imaging, like ResNet50, VGG16 and GoogleNet, as reported in the literature.

Conclusions

The prediction results reveal the efficacy of the proposed CNN-based approach and its ability for an easier and more precise interpretation of whole-body images in bone metastasis diagnosis for prostate cancer patients in nuclear medicine. This leads to marked effects on the diagnostic accuracy and decision-making regarding the treatment to be applied.
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Metadata
Title
Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy
Authors
Nikolaos Papandrianos
Elpiniki I. Papageorgiou
Athanasios Anagnostis
Publication date
01-11-2020
Publisher
Springer Singapore
Published in
Annals of Nuclear Medicine / Issue 11/2020
Print ISSN: 0914-7187
Electronic ISSN: 1864-6433
DOI
https://doi.org/10.1007/s12149-020-01510-6

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