Advertisement

Journal of Medical Systems

, Volume 30, Issue 2, pp 123–132 | Cite as

Enhancing the Utility of ProstaScint SPECT Scans for Patient Management

  • Marilyn E. Noz
  • Grace Chung
  • Benjamin Y. Lee
  • Gerald Q. MaguireJr.
  • J. Keith DeWyngaert
  • Jay V. Doshi
  • Elissa L. Kramer
  • Antoinette D. Murphy-Walcott
  • Michael P. Zeleznik
  • Noeun G. Kwak
Research Article

Abstract

This project investigated reducing the artifact content of In-111 ProstaScint SPECT scans for use in treatment planning and management. Forty-one patients who had undergone CT or MRI scans and simultaneous Tc-99m RBC/In-111 ProstaScint SPECT scans were included. SPECT volume sets, reconstructed using Ordered Set-Expectation Maximum (OS-EM) were compared against those reconstructed with standard Filtered Back projection (FBP). Bladder activity in Tc-99m scans was suppressed within an ellipsoidal volume. Tc-99m voxel values were subtracted from the corresponding In-111 after scaling based on peak activity within the descending aorta. The SPECT volume data sets were merged with the CT or MRI scans before and after processing. Volume merging, based both on visual assessment and statistical evaluation, was not affected. Thus iterative reconstruction together with bladder suppression and blood pool subtraction may improve the interpretation and utility of ProstaScint SPECT scans for patient management.

Keywords

Reconstruction algorithms ProstaScint SPECT artifact elimination Volume fusion Volume subtraction Prostate cancer treatment planning. 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Eubank, W. B., Mankoff, D. A., Schmiedl, U. P., Winter, T. C. III, Fisher, E. R., Olshen, A. B., Graham, M. M., and Eary, J. F. Imaging of oncologic patients: Benefit of combined CT and FDG PET in the diagnosis of malignancy. Am. J. Roentgenol. 171:1103–1110, 1998.Google Scholar
  2. 2.
    Mizowaki, T., Cohen, G. N., Fung, A. Y., and Zaider, M. Towards integrating functional imaging in the treatment of prostate cancer with radiation: The registration of the MR spectroscopy imaging to ultrasound/CT images and its implementation in treatment planning. Int. J. Radiat. Oncol. Biol. Phys. 54:1558–1564, 2002.CrossRefGoogle Scholar
  3. 3.
    Sannazzari, G. L., Ragona, R., Ruo Redda, M. G., Giglioli, F. R., Isolato, G., and Guarneri, A. CT-MRI image fusion for delineation of volumes in three-dimensional conformal radiation therapy in the treatment of localized prostate cancer. Br. J. Radiol. 75:603–607, 2002.Google Scholar
  4. 4.
    Wahl, R. L., Quint, L. E., Cieslak, R. D., Aisen, A. M., Koeppe, R. A., and Meyer, C. R. Anatometabolic tumor imaging: Fusion of FDG PET with CT or MRI to localize foci of increased activity. J. Nucl. Med. 34:1190–1197, 1993.Google Scholar
  5. 5.
    Wahl, R. L., Quint, L. E., Greenough, R., Meyer, C. R., White, R. I., and Orringer, M. B. Staging of mediastinum nonsmall cell lung cancer with FDG-PET, CT, and fusion images: Preliminary prospective evaluation. Radiology 191:371–377, 1994.Google Scholar
  6. 6.
    Kooy, H. M., Dunbar, S. F., Tarbell, N. J., Mannarino, E., Ferarro, N., Shusterman, S., Bellerive, M., Finn, L., McDonough, C. V., and Loeffler, J. S. Image fusion for stereotactic radiotherapy and radiosurgery treatment planning. Int. J. Radiat. Oncol. Biol. Phys. 28:1229–1234, 1994.Google Scholar
  7. 7.
    Schad, L. R., Boesecke, R., Schlegel, W., Hartmann, G. H., Sturm, V., Strauss, L. G., and Lorenz, W. J. Three-dimensional image correlation of CT, MR, and PET studies in radiotherapy treatment planning of brain tumors. J. Comput. Assist. Tomogr. 11:948–954, 1987.Google Scholar
  8. 8.
    Small, E. J. Advances in prostate cancer. Curr. Opin. Oncol. 11:226–235, 1999.CrossRefGoogle Scholar
  9. 9.
    Murphy, G. P., Elgamal, A. A., Troychak, M. J., and Kenny, G. M. Follow-up ProstaScint scans verify detection of occult soft-tissue recurrence after failure of primary prostate cancer therapy. Prostate 42:315–317, 2000.CrossRefGoogle Scholar
  10. 10.
    Petronis, J. D., Regan, F., and Lin, K. Indium-111 Capromab Pendetide (Prostascint) imaging to detect recurrent and metastatic prostate cancer. Clin. Nucl. Med. 23:672–677, 1998.CrossRefGoogle Scholar
  11. 11.
    Hinkle, G. H., Burgers, J. K., Neal, C. E., Texter, J. H., Kahn, D., Williams, R. D., Maguire, R., Rogers, B., Olsen, J. O., and Badalament, R. A. Multicenter radioimmunoscintigraphic evaluation of patients with prostate carcinoma using Indium-111 Capromab Pendetide. Cancer 83:739–747, 1998.CrossRefGoogle Scholar
  12. 12.
    Manyak, M. J. Capromab Pendetide immunoscintigraphy: Connecting the dots for prostate cancer imaging. Cancer Biother. Radiopharm. 15:127–130, 2000.CrossRefGoogle Scholar
  13. 13.
    Manyak, M. J., Hinkle, G. H., Olsen, J. O., Chiaccherini, R. P., Partin, A. W., Piantadosi, S., Burgers, J. K., Texter, J. H., Neal, C. E., Libertino, J. A., Wright, G. L. Jr., and Maguire, R. T. Immunoscintigraphy with Indium-111-Capromab Pendetide: Evaluation before definitive therapy in patients with prostate cancer. Urology 54:1058–1063, 1999.CrossRefGoogle Scholar
  14. 14.
    Raj, G. V., Partin, A. W., and Polascik, T. J. Clinical utility of Indium 111-Capromab Pendetide immunoscintigraphy in the detection of early recurrent prostate carcinoma after radical prostatectomy. Cancer 94:987–996, 2002.CrossRefGoogle Scholar
  15. 15.
    Rini, B. I., and Small, E. J. Prostate cancer update. Curr. Opin. Oncol. 14:288–291, 2002.CrossRefGoogle Scholar
  16. 16.
    Cooperberg, M. R., Broering, J. M., Litwin, M. S., Lubeck, D. P., Mehta, S. S., Henning, J. M., Carroll, P. R., and CaPSURE Investigators. The Contemporary Management of prostate cancer in the United States: Lessons from the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE), a National Disease Registry. J. Urol. 171:1393–1401, 2004.CrossRefGoogle Scholar
  17. 17.
    Quintana, J. C., and Blend, M. J. The dual-isotope prostascint imaging procedure: Clinical experience and staging results in 145 patients. Clin. Nucl. Med. 25:33–46, 200.Google Scholar
  18. 18.
    Long, D. T., King, M. A., and Sheehan, J. Comparative evaluation of image segmentation methods for volume quantization in SPECT. Med. Phys. 19:483–489, 1992.CrossRefGoogle Scholar
  19. 19.
    King, M. A., Long, D. T., and Brill, A. B. SPECT volume quantization: Influence of spatial resolution, source size and shape, and voxel size. Med. Phys. 18:1016–1024, 1991.CrossRefGoogle Scholar
  20. 20.
    Hamilton, R. J., Blend, M. J., Pelizzari, C. A., Milliken, B. D., and Vijayakumar, S. Using vascular structure for CT-SPECT registration in the pelvis. J. Nucl. Med. 40:347–351, 1999.Google Scholar
  21. 21.
    Thomas, C. T., Bradshaw, P. T., Pollock, B. H., Montie, J. E., Taylor, J. M. G., Thames, H. D., McLaughlin, P. W., deBiose, D. A., Hussey, D. H., and Wahl, R. L. Indium-111-Capromab Pendetide radioimmunoscintigraphy and prognosis for durable biochemical response to salvage radiation therapy in men after failed prostatectomy. J. Clin. Oncol. 21:1715–1721, 2003.CrossRefGoogle Scholar
  22. 22.
    Schettino, C. J., Kramer, E. L., Noz, M. E., Taneja, S., Padmanabhan, P., and Lepor, H. Impact of fusion of Indium-111 Capromab Pendetide volume data sets with those from MRI or CT in patients with recurrent prostate cancer. Am. J. Roentgenol. 183:519–524, 2004.Google Scholar
  23. 23.
    Ellis, R. J., Kim, E. Y., Conant, R., Sodee, D. B., Spirnak, J. P., Dinchman, K. H., Beddar, S., Wessels, B., Resnick, M. I., and Kinsella, T. J. Radioimmunoguided imaging of prostate cancer foci with histopathological correlation. Int. J. Radiat. Oncol. Biol. Phys. 49:1281–1286, 2001.CrossRefGoogle Scholar
  24. 24.
    Sodee, D. B., Ellis, R. J., Samuels, M. A., Spirnak, J. P., Poole, W. F., Riester, C., Martanovic, D. M., Stonecipher, R., and Bellon, E. M. Prostate cancer and prostate bed SPECT imaging with Prostascint: Semiquantitative correlation with prostatic biopsy results. Prostate 37:140–148, 1998.CrossRefGoogle Scholar
  25. 25.
    Ellis, R. J., Sodee, D. B., Spirnak, J. P., Dinchman, K. H., O’Leary, A. W., Samuels, M. A., Resnick, M. I., and Kinsella, T. J. Feasibility and acute toxicities of radioimmunoguided prostate brachytherapy. Int. J. Radiat. Oncol. Biol. Phys. 48:683–687, 2000.CrossRefGoogle Scholar
  26. 26.
    Duchesne, G. M. Radiation for prostate cancer. Lancet Oncol. 2:73–81, 2001.CrossRefGoogle Scholar
  27. 27.
    Bruyant, P. B. Analytic and iterative reconstruction algorithms in SPECT. J. Nucl. Med. 43:1343–1358, 2002.Google Scholar
  28. 28.
    Riddell, C., Carson, R. E., Carrasquillo, J. A., Libutti, S. K., Danforth, D. N., Whatley, M., and Bacharach, S. L. Noise reduction in oncology DFG PET images by iterative reconstruction: A quantitative assessment. J. Nucl. Med. 42:1316–1323, 2001.Google Scholar
  29. 29.
    deJonge, F. A. A., and Blokland, K. A. K. Statistical tomographic reconstruction: How many more iterations to go? Eur. J. Nucl. Med. Mol. Imaging 26:1247–1250, 1999.CrossRefGoogle Scholar
  30. 30.
    Lee, B. Y., deWyngaert, J. K., Noz, M. E., Maguire, G. Q. Jr., Murphy-Walcott, A., and Kramer, E. L. Unmasking true signal/tumor information from ProstaScint scans. Proc. SPIE Med. Imaging SPIE—Int. Soc. Opt. Eng. 5370:1980–1990, 2004.Google Scholar
  31. 31.
    Reddy, D. P., Maguire, G. Q. Jr., Noz, M. E., and Kenny, R. Automating image format conversion —Twelve years and twenty-five formats later. In Lemke, H. U., Inamura, K., Jaffee, C. C., and Felix, R. (eds.), Computer-Assisted Radiology – CAR’93, Springer-Verlag, Berlin, pp. 253–258, 1993.Google Scholar
  32. 32.
    Noz, M. E., Maguire, G. Q. Jr., Zeleznik, M. P., Kramer, E. L., Mahmoud, F., and Crafoord, J. A versatile functional-anatomic image fusion method for volume data sets. J. Med. Syst. 25:297–307, 2001.CrossRefGoogle Scholar
  33. 33.
    Gorniak, R. J., Kramer, E. L., Maguire, G. Q. Jr., Noz, M. E., Schettino, C. J., and Zeleznik, M. P. Evaluation of a semiautomatic 3D fusion technique applied to molecular imaging and MRI brain/frame volume data sets. J. Med. Syst. 27:141–156, 2003.CrossRefGoogle Scholar
  34. 34.
    deWyngaert, J. K., Noz, M. E., Ellerin, B., Kramer, E. L., Maguire, G. Q. Jr., and Zeleznik, M. P. Procedure for unmasking localization information from ProstaScint scans for prostate radiation therapy treatment. Int. J. Radiat. Oncol. Biol. Phys. 60:654–662, 2004.CrossRefGoogle Scholar
  35. 35.
    Maguire, G. Q. Jr., Noz, M. E., Rusinek, H., Jaeger, J., Kramer, E. L., Sanger, J. J., and Smith, G. Graphics applied to image registration. IEEE Comput. Graphics Appl. 11:20–29, 1991.CrossRefGoogle Scholar
  36. 36.
    Cohen, J., Statistical Power Analysis for the Behavioral Sciences, 2nd edn., Erlbaum, Hillside, NJ, 1988.MATHGoogle Scholar
  37. 37.
    vandenberghe, S., D’Asseler, Y., van de Walle, R., et al. Iterative reconstruction algorithms in nuclear medicine. Comput. Med. Imaging Graphics 25:105–111, 2001.CrossRefGoogle Scholar
  38. 38.
    Erdi, Y. E., Wessels, B. W., Loew, M. H., and Erdi, A. K. Threshold estimation in single emission computed tomography and planar imaging for clinical radioimmunotherapy. Cancer Res. 55(Suppl.):5823–5826, 1995.Google Scholar

Copyright information

© Springer Science + Business Media, Inc. 2006

Authors and Affiliations

  • Marilyn E. Noz
    • 1
  • Grace Chung
    • 1
  • Benjamin Y. Lee
    • 1
  • Gerald Q. MaguireJr.
    • 2
  • J. Keith DeWyngaert
    • 3
  • Jay V. Doshi
    • 1
  • Elissa L. Kramer
    • 1
  • Antoinette D. Murphy-Walcott
    • 1
  • Michael P. Zeleznik
    • 4
  • Noeun G. Kwak
    • 5
  1. 1.Department of RadiologyNYU School of MedicineNew York
  2. 2.School of Information and Communication TechnologyKistaSweden
  3. 3.Department of Radiation OncologyNYU School of MedicineNew York
  4. 4.RAHD Oncology ProductsSt. Louis
  5. 5.UMDNJ – Robert Wood Johnson Medical SchoolPiscataway

Personalised recommendations