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

Abstract

Bone scintigraphy (BS) is one of the most frequently utilized diagnostic techniques in detecting cancer bone metastasis, and it occupies an enormous workload for nuclear medicine physicians. So, we aimed to architecture an automatic image interpreting system to assist physicians for diagnosis. We developed an artificial intelligence (AI) model based on a deep neural network with 12,222 cases of 99mTc-MDP bone scintigraphy and evaluated its diagnostic performance of bone metastasis. This AI model demonstrated considerable diagnostic performance, the 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 individually classifying bone metastasis. Further AI-consulted interpretation also improved human diagnostic sensitivity and accuracy. In total, this AI model performed a valuable benefit for nuclear medicine physicians in timely and accurate evaluation of cancer bone metastasis.

A Lightweight Convolutional Neural Network Architecture Applied for Bone Metastasis Classification in Nuclear Medicine: A Case Study on Prostate Cancer Patients

“…The great majority of the reported approaches employ CNN-based methodologies to implement the classification problem of BS detection. Being a gold standard in BS detection, CNNs have been used in various architectures [ 10 , 14 , 15 , 42 , 45 ] outperforming conventional ML models such as ANNs [ 11 ] or LR, DT and SVMs [ 16 ]. However, difficulties in comparing their efficacy of the different CNN architectures arise from the fact that each of the aforementioned techniques uses its own dataset that is not publicly available due to privacy reasons.…”

GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives

“…For this, it is fundamental to create algorithm connections on which system AI technologies need to run. It has been already reported by Carter et al that breast cancer care was always supported by AI applications since the 1970s, and now it is even more integrated in diagnostic systems [ 13 ], for example, in mammography implementation [ 12 , 14 ]. There are many single experiences of AI application in breast cancer care.…”

Extracellular Vesicles in Tumors: A Potential Mediator of Bone Metastasis

“…When breast tumors metastasize to bone, the balance between osteoblasts and osteoclasts is damaged. Osteoclasts are continuously activated, as manifested by higher osteoclast activity, resulting in osteolytic diseases with osteolysis and structural bone damage ( Zhao Z. et al, 2020 ). Multiple bone growth factors are activated and released during bone resorption and remodeling, which provide an appropriate microenvironment for tumor cell growth, invasion, and metastasis ( Zhao Z. et al, 2020 ).…”

“…Osteoclasts are continuously activated, as manifested by higher osteoclast activity, resulting in osteolytic diseases with osteolysis and structural bone damage ( Zhao Z. et al, 2020 ). Multiple bone growth factors are activated and released during bone resorption and remodeling, which provide an appropriate microenvironment for tumor cell growth, invasion, and metastasis ( Zhao Z. et al, 2020 ). Once breast cancer cells have migrated to bone, the unique bone microenvironment could help to exchange biological information from the tumor cells to osteoblasts and osteoclasts, breaking the balance between osteolysis or osteogenesis during bone remodeling, which further results in fractures and pain and finally leads to death ( Zhang D. et al, 2020 ; Pang et al, 2021 ).…”