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Evaluation of metabolic tumor volume using different image reconstruction on 18F-FDG PET/CT fusion image

18F-FDG PET/CT 융합영상에서 영상 재구성 차이에 의한 MTV (Metabolic tumor volume) 평가

  • Yoon, Seok Hwan (Department of Nuclear Medicine, Seoul National University Hospital)
  • 윤석환 (서울대학교병원 핵의학과)
  • Received : 2017.11.26
  • Accepted : 2018.01.20
  • Published : 2018.01.28

Abstract

Recently, MTV(metabolic tumor volume) has been used as indices of the whole tumor FDG uptake on FDG PET image but it is influenced by image reconstruction. The purpose of this study was to evaluate the correlation between actual volume and metabolic tumor volume applying different SUVmax threshold for different reconstruction algorithm on phantom study. Measurement were performed on a Siemens Biograph mCT40 using a NEMA IEC body phantom containing different size six spheres filled with F18-FDG applying four SBRs (4:1, 8:1, 10:1, 20:1). Images reconstructed four algorithms (OSEM3D, OSEM3D+PSF, OSEM3D +TOF, OSEM3D+TOF+PSF) and MTV were measured with different SUVmax threshold. Overall, the use of increasing thresholds result in decreasing MTV. and increasing the signal to background ratio decreased MTV by applying same SUVmax threshold. The 40% SUVmax threshold gave the best concordance between measured and actual volume in PSF and PSF+TOF reconstruction image. and the 45% threshold had the best correlation between the volume measured and actual volume in OSEM3D and TOF reconstruction image. we believe that this study will be used when the measurement of MTV applying various reconstruction image.

FDG PET 영상에서 MTV는 종양의 전체 대사정도를 반영하여 종양의 체적을 나타낸다. 하지만 MTV는 영상재구성의 영향을 받게 된다. 본 연구의 목적은 팬텀실험을 통하여 영상재구성에 따라 SUVmax의 역치 값을 달리하여 실제 체적과 MTV의 상관관계를 평가해보고자 하였다. NEMA IEC Body 팬텀에 $^{18}F-FDG$를 구와 배후 방사능의 비율(4:1, 8:1, 10:1, 20:1)이 되도록 주입 후 영상을 획득하였다. 획득한 영상에 4가지 방법(OSEM3D, OSEM3D+PSF, OSEM3D+TOF, OSEM3D+TOF+PSF)으로 영상을 재구성한 후 다양한 SUVmax 역치 값을 적용하여 MTV의 변화를 비교해 보았다. 전반적으로 SUVmax 역치 값이 증가 할수록 MTV가 감소하였으며, 구와 배후방사능 비율이 증가할수록 동일한 SUVmax 역치 값에서 MTV가 감소하였다. PSF와 TOF+PSF재구성영상에서 40% 역치 값, OSEM3D와 TOF 재구성 영상에서는 45% 역치 값을 적용하였을 때 팬텀의 실제체적과 MTV의 높은 상관관계를 보였다. 이번 연구결과를 통하여 영상재구성에 따라 MTV 측정에 기초적인 자료로 제공되어 질 것으로 사료된다.

Keywords

References

  1. Ben-Haim S, Ell P. 18F-FDG PET and PET/CT in the evaluation of cancer treatment response. J Nucl Med. Vol. 50, No. 1, pp. 88-99, 2009. https://doi.org/10.2967/jnumed.108.054205
  2. Israel O, Kuten A, Early detection of cancer recurrence: 18F-FDG PET/CT can make a difference in diagnosis and patient care. J Nucl Med. Vol. 48, No. 1, pp. 28-35, 2007.
  3. G. J. Kim, M. C. Jeon, M. S. Han, S. Y. Seo, N. S. Kim, W. G. Bae. In the examination of PET/CT, Breast-tool production and availability of using FRP to check for breast disease. Journal of the Korea Convergence Society, Vol. 8. No. 9, pp. 175-181, 2017. https://doi.org/10.15207/JKCS.2017.8.9.175
  4. Thie JA. Understanding the standardized uptake value, its methods and implications for usage. J Nucl Med. Vol. 45, No. 9, pp. 1431-1464, 2004.
  5. Higashi K, Ueda Y, Arisaka Y, Sakuma T, Nambu Y, Oguchi M, et al. 18F-FDG uptake as a biologic prognostic factor for recurrence in patients with surgically resected non-small cell lung cacer. J Nucl Med. Vol. 43, No. 1, pp. 39-45, 2004.
  6. Wahl RL, Jacene H, Kasamon Y, Lodge MA. From RECIST to PRECIST: Evolving considerations for PET response criteria in solid tumors. J Nucl Med. Vol. 50, no. Suppl 1 122S-150S, 2009. https://doi.org/10.2967/jnumed.108.057307
  7. Tomoka Kitao, Kenji Hirata, Katsumi Shima, Takashi Hayashi, Mitsunori Sekizawa, Toshiki Takei, Wataru Ichimura, Masao Harada, Keishi Kondo, and Nagara Tamaki. Reproducibility and uptake time dependency of volume-based parameters on FDG-PET for lung cancer. BMC Cancer. Vol.16, pp. 576, 2016. https://doi.org/10.1186/s12885-016-2624-3
  8. Sridhar P1, Mercier G, Tan J, Truong MT, Daly B, Subramaniam RM. FDG PET Metabolic Tumor Volume Segmentation and Pathologic Volume of Primary Human Solid Tumors. AJR Am J Roentgenol. Vol. 202, No. 5, pp. 1114-1119, 2014. https://doi.org/10.2214/AJR.13.11456
  9. Liao S, Penney BC, Zhang H, Suzuki K, Pu Y. Prognostic value of the quantitative metabolic volumetric measurement on 18 F-FDG PET/CT in Stage IV nonsurgical small-cell lung cancer. Acad Radiol. Vol. 19, No. 1, pp. 69-77, 2012. https://doi.org/10.1016/j.acra.2011.08.020
  10. Chen HH, Chiu NT, Su WC, Guo HR, Lee BF. Prognostic value of whole-body total lesion glycolysis at pretreatment FDG PET/CT in non-small cell lung cancer. Radiology. Vol. 264, No. 2, pp. 559-566, 2012. https://doi.org/10.1148/radiol.12111148
  11. Ryu IS, Kim JS, Roh JL, Lee JH, Cho KJ, Choi SH, et al. Prognostic value of preoperative metabolic tumor volume and total lesion glycolysis measured by 18F-FDG PET/CT in salivary gland carcinomas. J Nucl Med. Vol. 54, No. 7, pp. 1032-1038, 2013. https://doi.org/10.2967/jnumed.112.116053
  12. Prieto E, Dominguez-Prado I, Garcia-Velloso MJ, Penuelas I, Richter JA, Marti-Climent JM. Impact of time-of-flight and point-spread-function in SUV quantification for oncological PET. Clin Nucl Med. Vol. 38, No. 2, pp. 103-109, 2013. https://doi.org/10.1097/RLU.0b013e318279b9df
  13. Knausl B, Hirtl A, Dobrozemsky G, Bergmann H, Kletter K, Dudczak R, et al. PET based volume segmentation with emphasis on the iterative TrueX algorithm. Z Med Phys. Vol. 22, No. 1, pp. 29-39, 2012. https://doi.org/10.1016/j.zemedi.2010.12.003
  14. Knäusl B, Rausch IF, Bergmann H, Dudczak R, Hirtl A, Georg D. Influence of PET reconstruction parameters on the TrueX algorithm. A combined phantom and patient study. Nuklearmedizin. Vol. 52, No. 1, pp. 28-35, 2013. https://doi.org/10.3413/Nukmed-0523-12-07
  15. Julian MM Rogasch, frank Hofheinz, Alexandr Lougovski, Christian Furth, Juri Ruf, Oliver Sgrober, Konrad Mohnike, Peter Hass, Mathias Walke, Holger Amthauer, Ingo G steffen. The influence of different signal to background ratios on spatial resolution and F18-FDG-PET quantification using point spread function and time of flight reconstruction. EJNMMI Physics. Vol. 1, No. 1, pp. 12, 2014. https://doi.org/10.1186/2197-7364-1-12
  16. Hoetjes NJ, van Velden FH, Hoekstra OS, et al. Partial volume correction strategies for quantitative FDG PET in oncology. Eur J Nucl Med Mol Imaging. Vol. 37, No. 9, pp. 1679-1687, 2010. https://doi.org/10.1007/s00259-010-1472-7
  17. Soret M, Bacharach SL, Buvat I. Partial volume effect in PET tumor imaging. J Nucl Med. Vol. 48, No. 6, pp. 932-945, 2007. https://doi.org/10.2967/jnumed.106.035774
  18. M. Meignan, M. Sasanelli, E. Itti. Metabolic tumor volumes measured at staging in lymphoma: methodological evaluation on phantom experiments and patients. Eur J Nucl Med. Vol. 41, No. 6, pp. 1113-1122, 2014. https://doi.org/10.1007/s00259-014-2705-y