ArticleCureus2026
Evaluating the Impact of Sex-Specific Artificial Intelligence on Bone Metastasis Detection: VSBONE Bone Scan Index (BSI) Version 2.1 Versus Version 3.0.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
OBJECTIVE(S): The present study compared the diagnostic accuracy of two different versions of an AI-assisted computer-aided diagnosis (CAD) software (VSBONE versions 2.1 and 3.0, Nihon Medi-Physics, Tokyo, Japan) for detecting bone metastases using bone scintigraphy images, with a focus on evaluating the impact of the new sex-specific analysis feature in version 3.0 on the overall performance and diagnostic accuracy in clinical decision-making.
methodsThis retrospective study analyzed 1,421 bone scintigraphy images from 1,119 patients at Nagasaki University Hospital. Patients were initially classified into metastatic and non-metastatic groups based on expert visual interpretation of planar images. Final classifications were made after single-photon emission computed tomography (SPECT)/CT and clinical review, resulting in metastatic, non-metastatic, and initially missed metastases groups. Bone Scan Index (BSI) and Hotspot number (HSn) were quantified using VSBONE BSI versions 2.1 and 3.0.
resultsOverall diagnostic performance improved with version 3.0 compared to version 2.1. In male patients, specificity increased (from 83.9% to 86.4%), with a slight decrease in sensitivity (from 82.0% to 79.7%), in the Youden index remained similar (from 0.660 to 0.662). In female patients, diagnostic accuracy improved, with notable increases in sensitivity (from 77.3% to 79.1%) and specificity (from 73.9% to 86.7%), and a marked increase in the Youden index (from 0.512 to 0.658).
conclusionThe present study showed that version 3.0 improved diagnostic quality and accuracy, particularly in the sex-specific analysis (female patients). These findings support the integration of sex-specific AI in CAD software to enhance diagnostic accuracy, reduce interpretation errors, and promote more equitable patient care.
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