LAUSR

Purpose Bone scintigraphy (BS) of disseminated skeletal metastasis is sometimes misinterpreted as normal. The use of computer-assisted diagnosis (CAD) may resolve this problem. We investigated the performance of a CAD system, BONENAVI, in the diagnosis of disseminated skeletal metastasis. Methods Cases of disseminated skeletal metastasis were selected from a BS log. These patients’ BSs were analyzed by BONENAVI to obtain an artificial neural network (ANN) and bone scan index (BSI). Clinical features (type of primary cancer, CT type, and BS type) were compared with the BONENAVI (ANN and BSI) results. The BS findings (diffuse increased axial skeleton uptake, inhomogeneity of uptake, proximal extremity contrast, and degree of renal uptake) and ANN or BSI were evaluated. Then, negative ANN patients were presented. Results Fifty-four patients were diagnosed as having disseminated skeletal metastasis. Regarding the primary cancers, 12 had prostate cancer, 16 gastric cancers, 16 breast cancers, and 10 miscellaneous cancers. Total sensitivity of ANN (≥ 0.5) was 76% (41/54). ANN values correlated with the BS type among clinical features. Diffuse increased axial skeleton uptake was mostly correlated with ANN of the BS findings. Conclusion The BONENAVI CAD system was partially helpful in diagnosing disseminated skeletal metastasis, but the sensitivity of BONENAVI was not sufficient and underestimated the disseminated skeletal metastasis. Further improvement of this CAD system is necessary to improve the detectability of disseminated skeletal metastasis.