title: A Preanalytic Validation Study of Automated Bone Scan Index: Effect on Accuracy and Reproducibility Due to the Procedural Variabilities in Bone Scan Image Acquisition.
abstract: The effect of the procedural variability in image acquisition on the quantitative assessment of bone scan is unknown. Here, we have developed and performed preanalytical studies to assess the impact of the variability in scanning speed and in vendor-specific γ-camera on reproducibility and accuracy of the automated bone scan index (BSI).
  
  
  METHODS
  Two separate preanalytical studies were performed: a patient study and a simulation study. In the patient study, to evaluate the effect on BSI reproducibility, repeated bone scans were prospectively obtained from metastatic prostate cancer patients enrolled in 3 groups (Grp). In Grp1, the repeated scan speed and the γ-camera vendor were the same as that of the original scan. In Grp2, the repeated scan was twice the speed of the original scan. In Grp3, the repeated scan used a different γ-camera vendor than that used in the original scan. In the simulation study, to evaluate the effect on BSI accuracy, bone scans of a virtual phantom with predefined skeletal tumor burden (phantom-BSI) were simulated against the range of image counts (0.2, 0.5, 1.0, and 1.5 million) and separately against the resolution settings of the γ-cameras. The automated BSI was measured with a computer-automated platform. Reproducibility was measured as the absolute difference between the repeated BSI values, and accuracy was measured as the absolute difference between the observed BSI and the phantom-BSI values. Descriptive statistics were used to compare the generated data.
  
  
  RESULTS
  In the patient study, 75 patients, 25 in each group, were enrolled. The reproducibility of Grp2 (mean ± SD, 0.35 ± 0.59) was observed to be significantly lower than that of Grp1 (mean ± SD, 0.10 ± 0.13; P < 0.0001) and that of Grp3 (mean ± SD, 0.09 ± 0.10; P < 0.0001). However, no significant difference was observed between the reproducibility of Grp3 and Grp1 (P = 0.388). In the simulation study, the accuracy at 0.5 million counts (mean ± SD, 0.57 ± 0.38) and at 0.2 million counts (mean ± SD, 4.67 ± 0.85) was significantly lower than that observed at 1.5 million counts (mean ± SD, 0.20 ± 0.26; P < 0.0001). No significant difference was observed in the accuracy data of the simulation study with vendor-specific γ-cameras (P = 0.266).
  
  
  CONCLUSIONS
  In this study, we observed that the automated BSI accuracy and reproducibility were dependent on scanning speed but not on the vendor-specific γ-cameras. Prospective BSI studies should standardize scanning speed of bone scans to obtain image counts at or above 1.5 million.
authors.affiliation: Division of Urological Cancers, Department of Translational Medicine, Malmö, Lund University, Lund, Sweden aseem.anand@med.lu.se.
authors.forename: Aseem
authors.initials: A
authors.lastname: Anand
authors.affiliation: Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.|Weil Cornell Medical College, New York, New York.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Morris
authors.affiliation: Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden.
authors.forename: Reza
authors.initials: R
authors.lastname: Kaboteh
authors.affiliation: Department of Clinical Physiology, Skåne University Hospital, Lund University, Malmö, Sweden.
authors.forename: Mariana
authors.initials: M
authors.lastname: Reza
authors.affiliation: Department of Clinical Physiology, Skåne University Hospital, Lund University, Malmö, Sweden.
authors.forename: Elin
authors.initials: E
authors.lastname: Trägårdh
authors.affiliation: Department of Radiology, Yamaguchi University Hospital, Yamaguchi, Japan.
authors.forename: Naofumi
authors.initials: N
authors.lastname: Matsunaga
authors.affiliation: Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden.|Department of Clinical Physiology, Skåne University Hospital, Lund University, Malmö, Sweden.
authors.forename: Lars
authors.initials: L
authors.lastname: Edenbrandt
authors.affiliation: Division of Urological Cancers, Department of Translational Medicine, Malmö, Lund University, Lund, Sweden.|Department of Urology, Lund University, Malmö, Sweden.
authors.forename: Anders
authors.initials: A
authors.lastname: Bjartell
authors.affiliation: Weil Cornell Medical College, New York, New York.|Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York; and.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Larson
authors.affiliation: Department of Radiation Physics, Skåne University Hospital, Malmö, Sweden.
authors.forename: David
authors.initials: D
authors.lastname: Minarik
mesh_terms: D001331:Automation; D001859:Bone Neoplasms / Q000000981:diagnostic imaging / Q000556:secondary; D001842:Bone and Bones / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008954:Models, Biological; D011877:Radionuclide Imaging / Q000295:instrumentation / Q000379:methods*; D015203:Reproducibility of Results
keywords: bone scan; bone scan index; imaging biomarker; metastatic prostate cancer; pre-analytical validation