Affiliations: [a] Department of Nuclear Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| [b] Department of Medical Imaging and Radiology, Shu-Zen Junior College of Medicine and Management, Kaohsiung, Taiwan
| [c] Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| [d] Department of Chemistry, R.O.C Military Academy, Taiwan
| [e] Center of General Education, Shu-Zen Junior College of Medicine and Management, Kaohsiung, Taiwan
Correspondence:
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Corresponding author: Chien-Yi Ting, Ph.D., Department of Medical Imaging and Radiology, Shu-Zen Junior College of Medicine and Management, No.452, Huanqiu Rd. Luzhu Dist., Kaohsiung City 82144, Taiwan (R.O.C.). Tel.: +886 7 6979333 # 1107; E-mail: chienyi@ms.szmc.edu.tw.
Abstract: The Tc-99m methylene diphosphonate (MDP) whole body bone scan (WBBS) has been widely accepted as a method of choice for the initial diagnosis of bone and joint changes in patients with oncologic diseases. The WBBS has shown high sensitivity but relatively low specificity due to bone variation. This study aims to use the self-developing irregular flux viewer (IFV) system to predict possible bone lesions in planar WBBS. The study uses gradient vector flow (GVF) and self-organizing map (SOM) methods to analyze the blood fluid-dynamics and evaluate hot points. The evaluation includes a selection of 368 patients with bone metastasis from prostate cancer, lung cancer and breast cancer. Finally, we compare IFV values with BONENAVI version data. BONENAVI is a computer-assisted diagnosis system that analyzes bone scintigraphy automatically. The analysis shows that the IFV system achieves sensitivities of 93% for prostate cancer, 91% for breast cancer, and 83% for lung cancer, respectively. On the other hand, our proposed approach achieves a higher sensitivity than the results of BONEVAVI version 2.0.5 for prostate cancer (88%), breast cancer (86%) and lung cancer (82%), respectively. The study results demonstrate that the high sensitivity and specificity of the IFV system can provide assistance for image interpretation and generate prediction values for WBBS.
Keywords: Tc-99m MDP, irregular flux viewer (IFV), computer-aided diagnosis (CAD), whole body bone scan (WBBS), machine learning (ML)
