Title of article :
Influence of the Different Primary Cancers and Different Types of Bone Metastasis on the Lesionbased Artificial Neural Network Value Calculated by a Computeraided Diagnostic System,BONENAVI, on Bone Scintigraphy Images
Author/Authors :
ISODA ، TAKURO Department of Diagnostic Radiology Sapporo Medical University , BABA ، SINGO Department of Clinical Radiology Graduated School of Medical Sciences Kyushul University , MARUOKA ، YASUHIRO Department of Clinical Radiology Graduated School of Medical Sciences Kyushu University , KITAMURA ، YOSHIYUKI Department of Clinical Radiology Graduated School of Medical Sciences Kyushu University , TAHARA ، KEIICHIRO Department of Clinical Radiology Graduated School of Medical Sciences Kyushu University , SASAKI ، MASAYUKI Department of Health Sciences Graduate School of Medical Sciences Kyushu University , Hatakenaka ، Masamitsu Department of Diagnostic Radiology Sapporo Medical University , HONDA ، HIROSHI Department of Clinical Radiology Graduate School of Medical Sciences Kyushu University
Abstract :
Objective(s): BONENAVI, a computeraided diagnostic system, is used in bone scintigraphy. This system provides the artificial neural network (ANN) and bone scan index (BSI) values. ANN is associated with the possibility of bone metastasis, while BSI is related to the amount of bone metastasis. The degree of uptake on bone scintigraphy can be affected by the type of bone metastasis. Therefore, the ANN value provided by BONENAVI may be influenced by the characteristics of bone metastasis. In this study, we aimed to assess the relationship between ANN value and characteristics of bone metastasis. Methods: We analyzed 50 patients (36 males, 14 females; age range: 42–87 yrs, median age: 72.5 yrs) with prostate, breast, or lung cancer who had undergone bone scintigraphy and were diagnosed with bone metastasis (32 cases of prostate cancer, nine cases of breast cancer, and nine cases of lung cancer). Those who had received systematic therapy over the past years were excluded. Bone metastases were diagnosed clinically, and the type of bone metastasis (osteoblastic, mildly osteoblastic,osteolytic, and mixed components) was decided visually by the agreement of two radiologists. We compared the ANN values (casebased and lesionbased) among the three primary cancers and four types of bone metastasis.Results: There was no significant difference in casebased ANN values among prostate, breast, and lung cancers. However, the lesionbased ANN values were the highest in cases with prostate cancer and the lowest in cases of lung cancer (median values: prostate cancer, 0.980; breast cancer, 0.909; and lung cancer, 0.864). Mildly osteoblastic lesions showed significantly lower ANN values than the other three types of bone metastasis (median values: osteoblastic, 0.939; mildly osteoblastic, 0.788; mixed type, 0.991; and osteolytic, 0.969). The possibility of a lesionbased ANN value below 0.5 was 10.9% for bone metastasis in prostate cancer, 12.9% for breast cancer, and 37.2% for lung cancer. The corresponding possibility were 14.7% for osteoblastic metastases, 23.9% for mildly osteoblastic metastases, 7.14% for mixedtype metastases, and 16.0% for osteolytic metastases.Conclusion: The lesionbased ANN values calculated by BONENAVI can be influenced by the type of primary cancer and bone metastasis.
Keywords :
Bone scintigraphy , Bone metastasis , computeraided diagnosis , BONENAVI