Korean J Radiol.  2013 Feb;14(1):1-12. 10.3348/kjr.2013.14.1.1.

Prognostic Significance of Volume-Based PET Parameters in Cancer Patients

• Moon SH
• Hyun SH
• Choi JY

• KMID: 1430038
• DOI: http://doi.org/10.3348/kjr.2013.14.1.1

Abstract

Accurate prediction of cancer prognosis before the start of treatment is important since these predictions often affect the choice of treatment. Prognosis is usually based on anatomical staging and other clinical factors. However, the conventional system is not sufficient to accurately and reliably determine prognosis. Metabolic parameters measured by 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) have the potential to provide valuable information regarding prognosis and treatment response evaluation in cancer patients. Among these parameters, volume-based PET parameters such as metabolic tumor volume and total lesion glycolysis are especially promising. However, the measurement of these parameters is significantly affected by the imaging methodology and specific image characteristics, and a standard method for these parameters has not been established. This review introduces volume-based PET parameters as potential prognostic indicators, and highlights methodological considerations for measurement, potential implications, and prospects for further studies.

Keyword

Positron emission tomography; 18F-fluorodeoxyglucose; Metabolic tumor volume; Total lesion glycolysis; Prognosisrinogenesis

MeSH Terms

Fluorodeoxyglucose F18/diagnostic use
Glycolysis
Humans
Neoplasm Staging
Neoplasms/pathology/*radionuclide imaging
*Positron-Emission Tomography
Predictive Value of Tests
Prognosis
Radiopharmaceuticals/diagnostic use
Tumor Burden

Figure

• 

  Fig. 1 Measurement of metabolic tumor volume in patients with esophageal cancer. 18F-fluorodeoxyglucose PET/CT images of 53-year-old male patient with esophageal cancer demonstrating measurement of metabolic tumor volume. Boundary of metabolically active tumor was automatically delineated using isocontour, defined as percentage of maximum SUV in tumor (40% in this image). VOI = volume of interest, SUV = standardized uptake values

• 

  Fig. 2 Kaplan-Meier survival curves for overall survival using MTV (A), TLG (B), and SUVmax (C) in 69 patients with squamous cell carcinoma of tonsil. MTV = metabolic tumor volume, TLG = total lesion glycolysis, SUVmax = maximum standardized uptake value

Reference

1. Takes RP, Rinaldo A, Silver CE, Piccirillo JF, Haigentz M Jr, Suárez C, et al. Future of the TNM classification and staging system in head and neck cancer. Head Neck. 2010. 32:1693–1711.

2. Lee P, Weerasuriya DK, Lavori PW, Quon A, Hara W, Maxim PG, et al. Metabolic tumor burden predicts for disease progression and death in lung cancer. Int J Radiat Oncol Biol Phys. 2007. 69:328–333.

3. Mirsadraee S, Oswal D, Alizadeh Y, Caulo A, van Beek E Jr. The 7th lung cancer TNM classification and staging system: Review of the changes and implications. World J Radiol. 2012. 4:128–134.

4. Walters TK, Zuckerman J, Nisbet-Smith A, Hudson E, Chia Y, Burke M. Fine needle aspiration biopsy in the diagnosis and management of fibroadenoma of the breast. Br J Surg. 1990. 77:1215–1217.

5. Chun YH, Kim SU, Park JY, Kim do Y, Han KH, Chon CY, et al. Prognostic value of the 7th edition of the AJCC staging system as a clinical staging system in patients with hepatocellular carcinoma. Eur J Cancer. 2011. 47:2568–2575.

6. Soret M, Bacharach SL, Buvat I. Partial-volume effect in PET tumor imaging. J Nucl Med. 2007. 48:932–945.

7. Vanderhoek M, Perlman SB, Jeraj R. Impact of the definition of peak standardized uptake value on quantification of treatment response. J Nucl Med. 2012. 53:4–11.

8. Larson SM, Erdi Y, Akhurst T, Mazumdar M, Macapinlac HA, Finn RD, et al. Tumor Treatment Response Based on Visual and Quantitative Changes in Global Tumor Glycolysis Using PET-FDG Imaging. The Visual Response Score and the Change in Total Lesion Glycolysis. Clin Positron Imaging. 1999. 2:159–171.

9. Moon SH, Choi JY, Lee HJ, Son YI, Baek CH, Ahn YC, et al. Prognostic value of ¹⁸F-FDG PET/CT in patients with squamous cell carcinoma of the tonsil: Comparisons of volume-based metabolic parameters. Head Neck. 2012. [Epub ahead of print].

10. Geets X, Lee JA, Bol A, Lonneux M, Grégoire V. A gradient-based method for segmenting FDG-PET images: methodology and validation. Eur J Nucl Med Mol Imaging. 2007. 34:1427–1438.

11. Schaefer A, Kremp S, Hellwig D, Rübe C, Kirsch CM, Nestle U. A contrast-oriented algorithm for FDG-PET-based delineation of tumour volumes for the radiotherapy of lung cancer: derivation from phantom measurements and validation in patient data. Eur J Nucl Med Mol Imaging. 2008. 35:1989–1999.

12. van Dalen JA, Hoffmann AL, Dicken V, Vogel WV, Wiering B, Ruers TJ, et al. A novel iterative method for lesion delineation and volumetric quantification with FDG PET. Nucl Med Commun. 2007. 28:485–493.

13. Boellaard R, Krak NC, Hoekstra OS, Lammertsma AA. Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study. J Nucl Med. 2004. 45:1519–1527.

14. Paulino AC, Koshy M, Howell R, Schuster D, Davis LW. Comparison of CT- and FDG-PET-defined gross tumor volume in intensity-modulated radiotherapy for head-and-neck cancer. Int J Radiat Oncol Biol Phys. 2005. 61:1385–1392.

15. MacManus M, Nestle U, Rosenzweig KE, Carrio I, Messa C, Belohlavek O, et al. Use of PET and PET/CT for radiation therapy planning: IAEA expert report 2006-2007. Radiother Oncol. 2009. 91:85–94.

16. Zhong X, Yu J, Zhang B, Mu D, Zhang W, Li D, et al. Using ¹⁸F-fluorodeoxyglucose positron emission tomography to estimate the length of gross tumor in patients with squamous cell carcinoma of the esophagus. Int J Radiat Oncol Biol Phys. 2009. 73:136–141.

17. Hyun SH, Choi JY, Shim YM, Kim K, Lee SJ, Cho YS, et al. Prognostic value of metabolic tumor volume measured by ¹⁸F-fluorodeoxyglucose positron emission tomography in patients with esophageal carcinoma. Ann Surg Oncol. 2010. 17:115–122.

18. Cheebsumon P, Yaqub M, van Velden FH, Hoekstra OS, Lammertsma AA, Boellaard R. Impact of [¹⁸F]FDG PET imaging parameters on automatic tumour delineation: need for improved tumour delineation methodology. Eur J Nucl Med Mol Imaging. 2011. 38:2136–2144.

19. Meng X, Sun X, Mu D, Xing L, Ma L, Zhang B, et al. Noninvasive evaluation of microscopic tumor extensions using standardized uptake value and metabolic tumor volume in non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2012. 82:960–966.

20. Juweid ME, Stroobants S, Hoekstra OS, Mottaghy FM, Dietlein M, Guermazi A, et al. Use of positron emission tomography for response assessment of lymphoma: consensus of the Imaging Subcommittee of International Harmonization Project in Lymphoma. J Clin Oncol. 2007. 25:571–578.

21. Le Roux PY, Gastinne T, Le Gouill S, Nowak E, Bodet-Milin C, Querellou S, et al. Prognostic value of interim FDG PET/CT in Hodgkin's lymphoma patients treated with interim response-adapted strategy: comparison of International Harmonization Project (IHP), Gallamini and London criteria. Eur J Nucl Med Mol Imaging. 2011. 38:1064–1071.

22. de Jong PA, van Ufford HM, Baarslag HJ, de Haas MJ, Wittebol SH, Quekel LG, et al. CT and ¹⁸F-FDG PET for noninvasive detection of splenic involvement in patients with malignant lymphoma. AJR Am J Roentgenol. 2009. 192:745–753.

23. Hatt M, Visvikis D, Albarghach NM, Tixier F, Pradier O, Cheze-le Rest C. Prognostic value of ¹⁸F-FDG PET image-based parameters in oesophageal cancer and impact of tumour delineation methodology. Eur J Nucl Med Mol Imaging. 2011. 38:1191–1202.

24. Cheebsumon P, van Velden FH, Yaqub M, Frings V, de Langen AJ, Hoekstra OS, et al. Effects of image characteristics on performance of tumor delineation methods: a test-retest assessment. J Nucl Med. 2011. 52:1550–1558.

25. Kim K, Kim SJ, Kim IJ, Kim YS, Pak K, Kim H. Prognostic value of volumetric parameters measured by F-18 FDG PET/CT in surgically resected non-small-cell lung cancer. Nucl Med Commun. 2012. 33:613–620.

26. Daisne JF, Sibomana M, Bol A, Doumont T, Lonneux M, Grégoire V. Tri-dimensional automatic segmentation of PET volumes based on measured source-to-background ratios: influence of reconstruction algorithms. Radiother Oncol. 2003. 69:247–250.

27. Hatt M, Le Pogam A, Visvikis D, Pradier O, Cheze Le Rest C. Impact of partial-volume effect correction on the predictive and prognostic value of baseline ¹⁸F-FDG PET images in esophageal cancer. J Nucl Med. 2012. 53:12–20.

28. Nehmeh SA, Erdi YE, Ling CC, Rosenzweig KE, Schoder H, Larson SM, et al. Effect of respiratory gating on quantifying PET images of lung cancer. J Nucl Med. 2002. 43:876–881.

29. Cheebsumon P, van Velden FH, Yaqub M, Hoekstra CJ, Velasquez LM, Hayes W, et al. Measurement of metabolic tumor volume: static versus dynamic FDG scans. EJNMMI Res. 2011. 1:35.

30. Arslan N, Tuncel M, Kuzhan O, Alagoz E, Budakoglu B, Ozet A, et al. Evaluation of outcome prediction and disease extension by quantitative 2-deoxy-2-¹⁸F fluoro-D-glucose with positron emission tomography in patients with small cell lung cancer. Ann Nucl Med. 2011. 25:406–413.

31. Liao S, Penney BC, Wroblewski K, Zhang H, Simon CA, Kampalath R, et al. Prognostic value of metabolic tumor burden on ¹⁸F-FDG PET in nonsurgical patients with non-small cell lung cancer. Eur J Nucl Med Mol Imaging. 2012. 39:27–38.

32. Chan SC, Chang JT, Lin CY, Ng SH, Wang HM, Liao CT, et al. Clinical utility of ¹⁸F-FDG PET parameters in patients with advanced nasopharyngeal carcinoma: predictive role for different survival endpoints and impact on prognostic stratification. Nucl Med Commun. 2011. 32:989–996.

33. Chu KP, Murphy JD, La TH, Krakow TE, Iagaru A, Graves EE, et al. Prognostic value of metabolic tumor volume and velocity in predicting head-and-neck cancer outcomes. Int J Radiat Oncol Biol Phys. 2012. 83:1521–1527.

34. La TH, Filion EJ, Turnbull BB, Chu JN, Lee P, Nguyen K, et al. Metabolic tumor volume predicts for recurrence and death in head-and-neck cancer. Int J Radiat Oncol Biol Phys. 2009. 74:1335–1341.

35. Xie P, Yue JB, Zhao HX, Sun XD, Kong L, Fu Z, et al. Prognostic value of ¹⁸F-FDG PET-CT metabolic index for nasopharyngeal carcinoma. J Cancer Res Clin Oncol. 2010. 136:883–889.

36. Choi KH, Yoo IR, Han EJ, Kim YS, et al. Prognostic Value of Metabolic Tumor Volume Measured by ¹⁸F-FDG PET/CT in Locally Advanced Head and Neck Squamous Cell Carcinomas Treated by Surgery. Nucl Med Mol Imaging. 2011. 45:43–51.

37. Guillem JG, Moore HG, Akhurst T, Klimstra DS, Ruo L, Mazumdar M, et al. Sequential preoperative fluorodeoxyglucose-positron emission tomography assessment of response to preoperative chemoradiation: a means for determining longterm outcomes of rectal cancer. J Am Coll Surg. 2004. 199:1–7.

38. Gulec SA, Suthar RR, Barot TC, Pennington K. The prognostic value of functional tumor volume and total lesion glycolysis in patients with colorectal cancer liver metastases undergoing ⁹⁰Y selective internal radiation therapy plus chemotherapy. Eur J Nucl Med Mol Imaging. 2011. 38:1289–1295.

39. Chung HH, Kwon HW, Kang KW, Park NH, Song YS, Chung JK, et al. Prognostic value of preoperative metabolic tumor volume and total lesion glycolysis in patients with epithelial ovarian cancer. Ann Surg Oncol. 2012. 19:1966–1972.

40. Kim BS, Kim IJ, Kim SJ, Nam NH, Park KJ, Kim K, et al. The Prognostic value of the metabolic tumor volume in FIGO stage IA to IIB cervical cancer for tumor recurrence: measured by F-18 FDG PET/CT. Nucl Med Mol Imaging. 2011. 45:36–42.

41. Schaefer NG, Veit-Haibach P, Soyka JD, Steinert HC, Stahel RA. Continued pemetrexed and platin-based chemotherapy in patients with malignant pleural mesothelioma (MPM): value of ¹⁸F-FDG-PET/CT. Eur J Radiol. 2012. 81:e19–e25.

42. Costelloe CM, Macapinlac HA, Madewell JE, Fitzgerald NE, Mawlawi OR, Rohren EM, et al. ¹⁸F-FDG PET/CT as an indicator of progression-free and overall survival in osteosarcoma. J Nucl Med. 2009. 50:340–347.

43. Yoo J, Choi JY, Lee KT, Heo JS, Park SB, Moon SH, et al. Prognostic significance of volume-based metabolic parameters by ¹⁸F-FDG PET/CT in gallbladder carcinoma. Nucl Med Mol Imaging. 2012. 46:201–206.

44. Lee HY, Hyun SH, Lee KS, Kim BT, Kim J, Shim YM, et al. Volume-based parameter of ¹⁸F-FDG PET/CT in malignant pleural mesothelioma: prediction of therapeutic response and prognostic implications. Ann Surg Oncol. 2010. 17:2787–2794.

45. Kang H, Lee HY, Lee KS, Kim JH. Imaging-based tumor treatment response evaluation: review of conventional, new, and emerging concepts. Korean J Radiol. 2012. 13:371–390.

46. Kiyohara S, Nagamachi S, Wakamatsu H, Nishii R, Fujita S, Futami S, et al. [Usefulness of metabolic volume and total lesion glycolysis for predicting therapeutic response in cancer therapy by ¹⁸F-FDG PET/CT]. Kaku Igaku. 2010. 47:453–461.

47. Brepoels L, De Saint-Hubert M, Stroobants S, Verhoef G, Balzarini J, Mortelmans L, et al. Dose-response relationship in cyclophosphamide-treated B-cell lymphoma xenografts monitored with [¹⁸F]FDG PET. Eur J Nucl Med Mol Imaging. 2010. 37:1688–1695.

48. Melton GB, Lavely WC, Jacene HA, Schulick RD, Choti MA, Wahl RL, et al. Efficacy of preoperative combined 18-fluorodeoxyglucose positron emission tomography and computed tomography for assessing primary rectal cancer response to neoadjuvant therapy. J Gastrointest Surg. 2007. 11:961–969. discussion 969.

49. Im HJ, Kim TS, Park SY, Min HS, Kim JH, Kang HG, et al. Prediction of tumour necrosis fractions using metabolic and volumetric ¹⁸F-FDG PET/CT indices, after one course and at the completion of neoadjuvant chemotherapy, in children and young adults with osteosarcoma. Eur J Nucl Med Mol Imaging. 2012. 39:39–49.

50. Roedl JB, Colen RR, Holalkere NS, Fischman AJ, Choi NC, Blake MA. Adenocarcinomas of the esophagus: response to chemoradiotherapy is associated with decrease of metabolic tumor volume as measured on PET-CT. Comparison to histopathologic and clinical response evaluation. Radiother Oncol. 2008. 89:278–286.

51. Arslan N, Miller TR, Dehdashti F, Battafarano RJ, Siegel BA. Evaluation of response to neoadjuvant therapy by quantitative 2-deoxy-2-[¹⁸F]fluoro-D-glucose with positron emission tomography in patients with esophageal cancer. Mol Imaging Biol. 2002. 4:301–310.

52. Ruby JA, Leibold T, Akhurst TJ, Shia J, Saltz LB, Mazumdar M, et al. FDG-PET assessment of rectal cancer response to neoadjuvant chemoradiotherapy is not associated with long-term prognosis: a prospective evaluation. Dis Colon Rectum. 2012. 55:378–386.

53. Edet-Sanson A, Dubray B, Doyeux K, Back A, Hapdey S, Modzelewski R, et al. Serial assessment of FDG-PET FDG uptake and functional volume during radiotherapy (RT) in patients with non-small cell lung cancer (NSCLC). Radiother Oncol. 2012. 102:251–257.

54. Akhurst T, Ng V V, Larson SM, O'Donoghue JA, O'Neel J, Erdi Y, et al. Tumor Burden Assessment with Positron Emission Tomography with. Clin Positron Imaging. 2000. 3:57–65.

55. O'BRIEN RM. A caution regarding rules of thumb for variance inflation factors. Qual Quant. 2007. 41:673–690.

56. Chan WK, Mak HK, Huang B, Yeung DW, Kwong DL, Khong PL. Nasopharyngeal carcinoma: relationship between ¹⁸F-FDG PET-CT maximum standardized uptake value, metabolic tumour volume and total lesion glycolysis and TNM classification. Nucl Med Commun. 2010. 31:206–210.

57. Chang KP, Tsang NM, Liao CT, Hsu CL, Chung MJ, Lo CW, et al. Prognostic significance of ¹⁸F-FDG PET parameters and plasma Epstein-Barr virus DNA load in patients with nasopharyngeal carcinoma. J Nucl Med. 2012. 53:21–28.

58. Gu J, Khong PL, Wang S, Chan Q, Law W, Zhang J. Quantitative assessment of diffusion-weighted MR imaging in patients with primary rectal cancer: correlation with FDG-PET/CT. Mol Imaging Biol. 2011. 13:1020–1028.

59. Jansen JF, Schöder H, Lee NY, Stambuk HE, Wang Y, Fury MG, et al. Tumor metabolism and perfusion in head and neck squamous cell carcinoma: pretreatment multimodality imaging with 1H magnetic resonance spectroscopy, dynamic contrast-enhanced MRI, and [¹⁸F]FDG-PET. Int J Radiat Oncol Biol Phys. 2012. 82:299–307.

60. Aboagye EO, Bhujwalla ZM. Malignant transformation alters membrane choline phospholipid metabolism of human mammary epithelial cells. Cancer Res. 1999. 59:80–84.

61. Oh JR, Seo JH, Chong A, Min JJ, Song HC, Kim YC, et al. Whole-body metabolic tumour volume of ¹⁸F-FDG PET/CT improves the prediction of prognosis in small cell lung cancer. Eur J Nucl Med Mol Imaging. 2012. 39:925–935.

62. Zhu D, Ma T, Niu Z, Zheng J, Han A, Zhao S, et al. Prognostic significance of metabolic parameters measured by ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography in patients with small cell lung cancer. Lung Cancer. 2011. 73:332–337.