English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Background: Although there are many studies on the application of artificialintelligence (AI) models to medical imaging, there is no report of an AI modelthat determines the accumulation of ribs in bone metastases and trauma onlyusing the anterior image of thorax of bone scintigraphy. In recent years, amethod for visualizing diagnostic grounds called Gradient-weighted ClassActivation Mapping (Grad-CAM) has been proposed in the area of diagnosticimages using Deep Convolutional Neural Network (DCNN). As far as we haveinvestigated, there are no reports of visualization of the diagnostic basis inbone scintigraphy. Our aim is to visualize the area of interest of DCNN, inaddition to developing an algorithm to classify and diagnose whether RIaccumulation on the ribs is bone metastasis or trauma using only anterior bonescan view of thorax. Material and Methods: For this retrospective study, weused 838 patients who underwent bone scintigraphy to search for bone metastasesat our institution. A frontal chest image of bone scintigraphy was used tocreate the algorithm. We used 437 cases with bone metastases on the ribs and401 cases with abnormal RI accumulation due to trauma. Result: AI model wasable to detect bone metastasis lesion with a sensitivity of 90.00% and accuracyof 86.5%. And it was possible to visualize the part that the AI model focusedon with Grad-CAM.

Development of the algorithm for differentiating bone metastases and  trauma of the ribs in bone scintigraphy and demonstration of visual evidence  of the algorithm -- Using only anterior bone scan view of thorax