Advertisement

Annals of Nuclear Medicine

, Volume 26, Issue 7, pp 586–593 | Cite as

Assessment of bone scans in advanced prostate carcinoma using fully automated and semi-automated bone scan index methods

  • Yoshiko Takahashi
  • Mana Yoshimura
  • Kunihito Suzuki
  • Tsuyoshi Hashimoto
  • Hideji Hirose
  • Kenji Uchida
  • Shingo Inoue
  • Kiyoshi Koizumi
  • Koichi Tokuuye
Original article

Abstract

Objective

As metastasis of prostate carcinoma occurs in approximately 80 % of terminal prostate carcinoma patients, the prognostic value of the prediction of prostate carcinoma by bone scintigraphy is important. We compared the automated and semi-automated bone scan index (BSI) system with extent of disease (EOD) grade if there is a possibility to substitute for EOD grading.

Materials and methods

We evaluated the bone scintigraphic images of 158 prostate carcinoma patients (mean age, 69.2 years old; range 50–97). Bone scans were obtained approximately 3 h after the intravenous injection of 740 MBq technetium-99 m-methylene diphosphonate. EOD grade was evaluated by 2 experienced radiologists using bone scintigraphy, magnetic resonance imaging, and computed tomography. We calculated the BSI using the Bonenavi® system (Fujifilm RI Pharma Co., Ltd.), utilizing data from a Japanese database. The semi-automated BSI of the patients was obtained by modifying the automated BSI independently by 3 radiologists (referred to as “observers” in this study) with 25, 10, and 4 years of experience. We then compared the EOD with the corresponding 4 independent BSIs for each patient. We used the Steel–Dwass test for multiple comparisons of the BSI among different EOD groups of patients. We analyzed the receiver-operating characteristics (ROC) curve to determine the cutoff values of sensitivity and specificity, which were both set at 95 %.

Results

There were significant correlations observed among the mean EOD and BSI scores as determined using the Bonenavi® system for every patient group for all observers and the automated method. There was also a statistically significant difference in the mean BSI among all EOD groups (grades 0, 1, or 2–4) for all observers and the automated method. Each ROC curve showed an ideal shape and was within the optimal cutoff range.

Conclusion

On the basis of the present results, BSI as calculated using the Bonenavi® system significantly correlated with EOD. Sensitivity and specificity as measured by the fully automated method were lower than those of semi-automated BSI with modification by radiologists. Therefore, semi-automated BSI is considered to have the possibility to substitute for EOD grading to predict the survival of prostate carcinoma patients with bone metastases, with only slight interobserver variation.

Keywords

Bone scan index Prostate carcinoma Bone metastasis 

Notes

Acknowledgments

We are indebted to Mr. Roderick J. Turner, Associate Professor Edward F. Barroga and Professor J. Patrick Barron, Chairman of the Department of International Medical Communications of Tokyo Medical University, for their editorial review of the English manuscript.

References

  1. 1.
    Namiki M, Akaza H, Lee SE, Song JM, Umbas R, Zhou L, et al. Prostate Cancer Working Group report. Jpn J Clin Oncol. 2010;40(Suppl 1):i70–5.PubMedCrossRefGoogle Scholar
  2. 2.
    Nakata S, Ohtake N, Yamanaka H. Epidemiology of prostate cancer in Japan. Nihon Rinsho. 2011;69 Suppl 5:181–186 (in Japanese).Google Scholar
  3. 3.
    Knudson G, Grinis G, Lopez-Majano V, Sansi P, Targonski P, Rubenstein M, et al. Bone scan as a stratification variable in advanced prostate cancer. Cancer. 1991;68:316–20.PubMedCrossRefGoogle Scholar
  4. 4.
    Amico S, Liehn JC, Desoize B, Larbre H, Deltour G, Valeyre J. Comparison of phosphatase isoenzymes PAP and PSA with bone scan in prostate carcinoma. J Clin Nucl Med. 1991;13:643–8.CrossRefGoogle Scholar
  5. 5.
    Soloway MS, Hardeman SW, Hickey D, Raymond J, Todd B, Soloway S, et al. Stratification of patients with metastatic prostate cancer based on extent of disease on initial bone scan. Cancer. 1988;61:195–202.PubMedCrossRefGoogle Scholar
  6. 6.
    Erdi YE, Humm JL, Imbriaco M, Yeung H, Larson SM. Quantitative bone metastases analysis based on image segmentation. J Nucl Med. 1997;38:1401–6.PubMedGoogle Scholar
  7. 7.
    Imbriaco M, Larson SM, Yeung HW, Mawlawi OR, Erdi Y, Venkatraman ES, et al. A new parameter for measuring metastatic bone involvement by prostate cancer: the bone scan index. Clin Cancer Res. 1998;4:1765–72.PubMedGoogle Scholar
  8. 8.
    International Commission on Radiation Protection. Publication 23: report of the task group on reference man. New York: Pergamon Press; 1992.Google Scholar
  9. 9.
    Sadik M, Jakobsson D, Olofsson F, Ohlsson M, Suukula M, Edenbrandt L. A new computer-based decision-support system for the interpretation of bone scans. Nucl Med Commun. 2006;27:417–23.PubMedCrossRefGoogle Scholar
  10. 10.
    Sadik M, Suurkula M, Höglund P, Järund A, Edenbrandt L. Quality of planar whole-body bone scan interpretations—a nationwide survey. Eur J Nucl Med Mol Imaging. 2008;35:1464–72.PubMedCrossRefGoogle Scholar
  11. 11.
    Sadik M, Hamadeh I, Nordblom P, Suurkula M, Höglund P, Ohlsson M, Edenbrandt L. Computer-assisted interpretation of planar whole-body bone scans. J Nucl Med. 2008;49:1958–65.PubMedCrossRefGoogle Scholar
  12. 12.
    Sadik M, Suurkula M, Höglund P, Järund A, Edenbrandt L. Improved classifications of planar whole-body bone scans using a computer-assisted diagnosis system: a multicenter, multiple-reader, multiple-case study. J Nucl Med. 2009;50:368–75.PubMedCrossRefGoogle Scholar

Copyright information

© The Japanese Society of Nuclear Medicine 2012

Authors and Affiliations

  • Yoshiko Takahashi
    • 1
  • Mana Yoshimura
    • 2
  • Kunihito Suzuki
    • 2
  • Tsuyoshi Hashimoto
    • 2
  • Hideji Hirose
    • 2
  • Kenji Uchida
    • 2
  • Shingo Inoue
    • 1
  • Kiyoshi Koizumi
    • 1
  • Koichi Tokuuye
    • 2
  1. 1.Department of RadiologyTokyo Medical University Hachioji Medical CenterTokyoJapan
  2. 2.Department of RadiologyTokyo Medical UniversityTokyoJapan

Personalised recommendations