Deep neural network based artificial intelligence assisted diagnosis of bone scintigraphy for cancer bone metastasis

Autor:	Yongzhao Xiang, Lin Li, Xiao Zhong, Ke Zhou, Yuhao Li, Jianan Wei, Huawei Cai, Pi Yong, Wenjie Zhang, Zhen Zhao, Zhang Yi, Lisha Jiang, Pei Yang
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Adult Male Mathematics and computing lcsh:Medicine Bone Neoplasms Sensitivity and Specificity Bone and Bones Article 030218 nuclear medicine & medical imaging Metastasis 03 medical and health sciences Prostate cancer 0302 clinical medicine Breast cancer Artificial Intelligence medicine Image Processing Computer-Assisted Humans Diagnosis Computer-Assisted Lung cancer Radionuclide Imaging lcsh:Science Aged Cancer Multidisciplinary Artificial neural network medicine.diagnostic_test Receiver operating characteristic business.industry lcsh:R Bone metastasis Middle Aged medicine.disease Bone scintigraphy 030220 oncology & carcinogenesis Female lcsh:Q Artificial intelligence Neural Networks Computer business
Zdroj:	Scientific Reports, Vol 10, Iss 1, Pp 1-9 (2020) Scientific Reports
ISSN:	2045-2322
DOI:	10.1038/s41598-020-74135-4
Popis:	Background: Bone scintigraphy (BS) is one of the most frequently utilized diagnostic techniques in detection of cancer bone metastasis, and it occupies great workload for nuclear physicians. So we aim to architecture an automatic image interpreting system to assist physicians for diagnosis.Methods: We developed an artificial intelligence (AI) model based on a deep neural network with 12222 cases of 99mTc-MDP bone scintigraphy, and evaluated its diagnostic performance of bone metastases.Results: This AI model demonstrated diagnostic performance by areas under the curve (AUC) of receiver operating characteristic (ROC) was 0.988 for breast cancer, 0.955 for prostate cancer, 0.957 for lung cancer, and 0.971 for other cancers. Applying this AI model to a new dataset of 400 BS cases, it represented comparable performance to that of human physicians in individually classifying bone metastasis. Further AI-consulting interpretation also improved human diagnostic sensitivity and accuracy.Conclusion: In total, this AI model performed valuable benefit for nuclear physicians in timely and accurate evaluation of cancer bone metastases.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6373d7474a4123eb0650a90167d81fab http://link.springer.com/article/10.1038/s41598-020-74135-4 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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