The automated method for analysis of anterior and posterior whole-body bone scan images has been described previously [16 (link)]. Each individual hot spot was classified as metastasis or no metastasis by an artificial neural network. The BSI was calculated as the percentage of the sum of all hot spots classified as bone metastases by the artificial neural network values. For calculation of the BSI, we used BONENAVI version 2 (Fujifilm RI Pharma, Co. Ltd., Tokyo, Japan; Exini Bone, Exini Diagnostics, Lund, Sweden) [17 (link)].
Bonenavi version 2
Manufactured by Fujifilm
Sourced in Japan
BONENAVI version 2 is a lab equipment product from Fujifilm. It is designed for bone analysis applications. The core function of BONENAVI version 2 is to provide advanced imaging and analysis capabilities for evaluating bone structure and density.
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Lab products found in correlation
2 protocols using bonenavi version 2
1
Automated Bone Scan Image Analysis
2
Bone Scintigraphy Protocol for Calculating ANN and BSI
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Bone scintigraphy was performed by intravenously administering 99m Tc-MDP (Fujifilm RI Pharma Co., Tokyo, Japan) 370-925 MBq; 3 hours later, horizontal images (anterior and posterior) were taken using a scintillation camera (ECAM and GX7200, Toshiba Corp., Tokyo, Japan). The ECAM imaging rate was 18 cm/min and the image matrix size was 256 × 1024. The GX7200 imaging rate was 17.5 cm/min and image matrix was 256 × 1024. Both devices used a parallel multihole collimator. The data acquisition window was 10% of both ends of the 140 KeV gamma ray emitted by 99m Tc-MDP.
Both BONENAVI version 1 (Fujifilm RI Pharma) and BONENAVI version 2 (Fujifilm RI Pharma) were used to calculate artificial neural networks (ANN), bone scan index (BSI), and hot-spot values from the bone scintigraphy data (Fig. 1). F1 Fig. 1: Method case selection.
Both BONENAVI version 1 (Fujifilm RI Pharma) and BONENAVI version 2 (Fujifilm RI Pharma) were used to calculate artificial neural networks (ANN), bone scan index (BSI), and hot-spot values from the bone scintigraphy data (Fig. 1). F1 Fig. 1: Method case selection.
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