title: Evaluation of a computer-assisted diagnosis system, BONENAVI version 2, for bone scintigraphy in cancer patients in a routine clinical setting.
abstract: OBJECTIVE
  To evaluate a computer-assisted diagnosis system, BONEVAVI version 2 for bone scintigraphy, this study examined the performance of the software in patients with and without skeletal metastasis.
  
  
  METHODS
  Bone scans of various patients were analyzed by BONENAVI version 2. Patients with skeletal metastasis from prostate cancer, lung cancer, breast cancer, and other cancers were included in the study as true positive cases. Patients with normal bone scans, consecutive patients with several days of no skeletal metastasis (regardless of hot spots), and patients with abnormal bone scans but no skeletal metastasis were included as negative cases. Patient artificial neural network (ANN) values equal to or above 0.5 were regarded as positive, and those below 0.5 as negative. This study also analyzed cases according to primary cancer factors, osseous metastasis type, and bone tumor burden.
  
  
  RESULTS
  The sensitivity of patient ANN values was 121/142 (85 %) for all cancers, 25/29 (86 %) for prostate cancer, 35/40 (88 %) for lung cancer, 37/45 (82 %) for breast cancer, and 24/28 (86 %) for other cancers. The specificity of ANN values was 40/49 (82 %) for normal bone scans, 99/122 (81 %) for consecutive patients with several days of no skeletal metastasis, and 44/81 (54 %) for patients with abnormal bone scans but no skeletal metastasis. Patients showing false negatives included: 10 patients with small lesions (6 of whom showed positive lesion ANN values), 4 patients with osteolytic lesions, 5 patients with intertrabecular osseous metastasis, and 1 patient with a metastatic lesion adjacent to the urinary bladder. The correlation between manually counted lesion numbers and Bone Scan Index was excellent for prostate cancer, and was good for lung cancer, breast cancer, and other cancers.
  
  
  CONCLUSIONS
  BONENAVI version 2 is an effective computer-assisted diagnosis system for bone scanning, but the drawbacks of bone scanning remain unresolved.
authors.affiliation: Department of Nuclear Medicine, Cancer Institute Hospital, 3-8-31 Ariake, Koto-ku, Tokyo, 135-8550, Japan, mitsuru@jfcr.or.jp.
authors.forename: Mitsuru
authors.initials: M
authors.lastname: Koizumi
authors.forename: Kei
authors.initials: K
authors.lastname: Wagatsuma
authors.forename: Noriaki
authors.initials: N
authors.lastname: Miyaji
authors.forename: Taisuke
authors.initials: T
authors.lastname: Murata
authors.forename: Kenta
authors.initials: K
authors.lastname: Miwa
authors.forename: Tomohiro
authors.initials: T
authors.lastname: Takiguchi
authors.forename: Tomoko
authors.initials: T
authors.lastname: Makino
authors.forename: Masamichi
authors.initials: M
authors.lastname: Koyama
mesh_terms: D001859:Bone Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000556:secondary; D001842:Bone and Bones / Q000000981:diagnostic imaging* / Q000473:pathology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005188:False Negative Reactions; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D011877:Radionuclide Imaging; D014057:Tomography, X-Ray Computed; D047368:Tumor Burden