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


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.




  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.
  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.