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Importance of Quantification for the Analysis of PET Data in Oncology: Review of Current Methods and Trends for the Future

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Abstract

In oncology, positron emission tomography (PET) is an important tool for tumour diagnosis and staging, assessment of response to treatment and evaluation of the pharmacokinetic properties and efficacy of new drugs. Despite its quantitative potential, however, in daily clinical practice PET is used almost exclusively with 2-deoxy-2-[18F]fluoro-d-glucose ([18F]FDG) and, in addition, [18F]FDG data are normally assessed visually or using simple indices as the standardised uptake value (SUV). After explaining why more sophisticated quantification methods can be useful in oncology, the paper reviews the approaches that are commonly used and those available but not routinely employed. Particular emphasis is addressed to the SUV, for its importance in clinical practice. Issues specific to PET quantification in oncology and related examples are then discussed. Finally, some ideas for the development of new quantitative methods for analysing PET data in oncology and for the application of approaches already existing but not commonly employed are presented.

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References

  1. Nanni C, Fantini L, Nicolini S, Fanti S (2010) Non FDG PET. Clin Radiol 65(7):536–548. doi:10.1016/j.crad.2010.03.012

    PubMed  CAS  Google Scholar 

  2. Weber WA (2006) Positron emission tomography as an imaging biomarker. J Clin Oncol 24(20):3282–3292. doi:10.1200/JCO.2006.06.6068

    PubMed  CAS  Google Scholar 

  3. Aboagye EO, Price PM (2003) Use of positron emission tomography in anticancer drug development. Invest New Drugs 21(2):169–181

    PubMed  CAS  Google Scholar 

  4. Ido TWC, Casella V (1978) Labeled 2-dexoy-d-glucose analogs: 18Flabeled 2-deoxy-2-fluoro-d-glucose, 2-deoxy-2-fluoro-d-mannose and 14C-2-deoxy-2-fluoro-d-glucose. J Labelled Comp Radiopharm 14:175–183

    CAS  Google Scholar 

  5. Fletcher JW, Djulbegovic B, Soares HP, Siegel BA, Lowe VJ, Lyman GH, Coleman RE, Wahl R, Paschold JC, Avril N, Einhorn LH, Suh WW, Samson D, Delbeke D, Gorman M, Shields AF (2008) Recommendations on the use of 18F-FDG PET in oncology. J Nucl Med 49(3):480–508. doi:10.2967/jnumed.107.047787

    PubMed  Google Scholar 

  6. Boellaard R (2009) Standards for PET image acquisition and quantitative data analysis. J Nucl Med 50(Suppl 1):11S–20S. doi:10.2967/jnumed.108.057182

    PubMed  CAS  Google Scholar 

  7. Lin C, Itti E, Haioun C, Petegnief Y, Luciani A, Dupuis J, Paone G, Talbot JN, Rahmouni A, Meignan M (2007) Early 18F-FDG PET for prediction of prognosis in patients with diffuse large B-cell lymphoma: SUV-based assessment versus visual analysis. J Nucl Med 48(10):1626–1632. doi:10.2967/jnumed.107.042093

    PubMed  Google Scholar 

  8. Weber WA (2010) Monitoring tumor response to therapy with 18F-FLT PET. J Nucl Med 51(6):841–844. doi:10.2967/jnumed.109.071217

    PubMed  Google Scholar 

  9. DuBois DDE (1916) A formula to estimate the approximate surface area if height and weight are known. Arch Intern Medicine 17:863–871

    CAS  Google Scholar 

  10. Zasadny KR, Wahl RL (1993) Standardized uptake values of normal tissues at PET with 2-[fluorine-18]-fluoro-2-deoxy-d-glucose: variations with body weight and a method for correction. Radiology 189(3):847–850

    PubMed  CAS  Google Scholar 

  11. Lindholm P, Minn H, Leskinen-Kallio S, Bergman J, Ruotsalainen U, Joensuu H (1993) Influence of the blood glucose concentration on FDG uptake in cancer—a PET study. J Nucl Med 34(1):1–6

    PubMed  CAS  Google Scholar 

  12. Weber WA (2005) Use of PET for monitoring cancer therapy and for predicting outcome. J Nucl Med 46(6):983–995

    PubMed  CAS  Google Scholar 

  13. Hoekstra CJ, Hoekstra OS, Stroobants SG, Vansteenkiste J, Nuyts J, Smit EF, Boers M, Twisk JW, Lammertsma AA (2002) Methods to monitor response to chemotherapy in non-small cell lung cancer with 18F-FDG PET. J Nucl Med 43(10):1304–1309

    PubMed  CAS  Google Scholar 

  14. Krak NC, van der Hoeven J, Hoekstra OS, Twisk JW, van der Wall E, Lammertsma AA (2003) Measuring [(18)F]FDG uptake in breast cancer during chemotherapy: comparison of analytical methods. Eur J Nucl Med Mol Imaging 30:674–681

    PubMed  CAS  Google Scholar 

  15. Kroep JRVGC, Cuesta MA, Craanen ME, Hoekstra OS, Comans EF, Bloemena E, Hoekstra CJ, Golding RP, Twisk JW, Peters GJ, Pinedo HM, Lammertsma AA (2003) Positron emission tomography using 2-deoxy-2-[18F]-fluoro-d-glucose for response monitoring in locally advanced gastroesophageal cancer; a comparison of different analytical methods. Mol Imaging Biol 5(5):337–346

    PubMed  Google Scholar 

  16. Cazaentre T, Morschhauser F, Vermandel M, Betrouni N, Prangere T, Steinling M, Huglo D Pre-therapy 18F-FDG PET quantitative parameters help in predicting the response to radioimmunotherapy in non-Hodgkin lymphoma. Eur J Nucl Med Mol Imaging 37 (3):494–504. doi:10.1007/s00259-009-1275-x

  17. Kenny L, Coombes RC, Vigushin DM, Al-Nahhas A, Shousha S, Aboagye EO (2007) Imaging early changes in proliferation at 1 week post chemotherapy: a pilot study in breast cancer patients with 3′-deoxy-3′-[18F]fluorothymidine positron emission tomography. Eur J Nucl Med Mol Imaging 34(9):1339–1347. doi:10.1007/s00259-007-0379-4

    PubMed  Google Scholar 

  18. Prevost S, Boucher L, Larivee P, Boileau R, Benard F (2006) Bone marrow hypermetabolism on 18F-FDG PET as a survival prognostic factor in non-small cell lung cancer. J Nucl Med 47(4):559–565

    PubMed  Google Scholar 

  19. Cicone F, Loose D, Deron P, Vermeersch H, Signore A, Van de Vyvere F, Scopinaro F, Van de Wiele C (2008) Prognostic value of FDG uptake by the bone marrow in squamous cell carcinoma of the head and neck. Nucl Med Commun 29(5):431–435. doi:10.1097/MNM.0b013e3282f5d2ce

    PubMed  CAS  Google Scholar 

  20. Teo BK, Badiee S, Hadi M, Lam T, Johnson L, Seo Y, Bacharach SL, Hasegawa BH, Franc BL (2008) Correcting tumour SUV for enhanced bone marrow uptake: retrospective 18F-FDG PET/CT studies. Nucl Med Commun 29(4):359–366. doi:10.1097/MNM.0b013e3282f44f99

    PubMed  Google Scholar 

  21. Watabe H, Ikoma Y, Kimura Y, Naganawa M, Shidahara M (2006) PET kinetic analysis–compartmental model. Ann Nucl Med 20(9):583–588

    PubMed  CAS  Google Scholar 

  22. Gunn RN, Gunn SR, Cunningham VJ (2001) Positron emission tomography compartmental models. J Cereb Blood Flow Metab 21(6):635–652. doi:10.1097/00004647-200106000-00002

    PubMed  CAS  Google Scholar 

  23. Kety SS, Schmidt CF (1948) The nitrous oxide method for the quantitative determination of cerebral blood flow in man; theory, procedure and normal values. J Clin Invest 27(4):476–483

    Google Scholar 

  24. Sokoloff L, Reivich M, Kennedy C, Des Rosiers MH, Patlak CS, Pettigrew KD, Sakurada O, Shinohara M (1977) The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J Neurochem 28(5):897–916

    PubMed  CAS  Google Scholar 

  25. Mintun MA, Raichle ME, Kilbourn MR, Wooten GF, Welch MJ (1984) A quantitative model for the in vivo assessment of drug binding sites with positron emission tomography. Ann Neurol 15(3):217–227. doi:10.1002/ana.410150302

    PubMed  CAS  Google Scholar 

  26. Strauss LG, Koczan D, Klippel S, Pan L, Cheng C, Haberkorn U, Willis S, Dimitrakopoulou-Strauss A Impact of cell-proliferation-associated gene expression on 2-deoxy-2-[(18)F]fluoro-d-glucose (FDG) kinetics as measured by dynamic positron emission tomography (dPET) in colorectal tumors. Mol Imaging Biol. doi:10.1007/s11307-010-0465-z

  27. Cook GLM, Marsden P, Dynes A, Fogelman I (1989) Non-invasive assessment of skeletal kinetics using fluorine-18 fluoride positron emission tomography: evaluation of image and population-derived arterial input functions. Eur J Nucl Med 26:1424–1429

    Google Scholar 

  28. Lammertsma AA, Hume SP (1996) Simplified reference tissue model for PET receptor studies. Neuroimage 4(3 Pt 1):153–158. doi:10.1006/nimg.1996.0066

    PubMed  CAS  Google Scholar 

  29. Strauss LG, Dimitrakopoulou-Strauss A, Haberkorn U (2003) Shortened PET data acquisition protocol for the quantification of 18F-FDG kinetics. J Nucl Med 44(12):1933–1939

    PubMed  CAS  Google Scholar 

  30. Strauss LG, Pan L, Cheng C, Haberkorn U, Dimitrakopoulou-Strauss A Shortened acquisition protocols for the quantitative assessment of the 2-tissue-compartment model using dynamic PET/CT 18F-FDG studies. J Nucl Med 52 (3):379–385. doi:10.2967/jnumed.110.079798

  31. Logan J (2000) Graphical analysis of PET data applied to reversible and irreversible tracers. Nucl Med Biol 27(7):661–670

    PubMed  CAS  Google Scholar 

  32. Patlak CS, Blasberg RG, Fenstermacher JD (1983) Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 3(1):1–7

    PubMed  CAS  Google Scholar 

  33. Wu HM, Bergsneider M, Glenn TC, Yeh E, Hovda DA, Phelps ME, Huang SC (2003) Measurement of the global lumped constant for 2-deoxy-2-[18F]fluoro-d-glucose in normal human brain using [15O]water and 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography imaging. A method with validation based on multiple methodologies. Mol Imaging Biol 5(1):32–41

    PubMed  Google Scholar 

  34. Logan J, Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, MacGregor RR, Hitzemann R, Bendriem B, Gatley SJ et al (1990) Graphical analysis of reversible radioligand binding from time-activity measurements applied to [N-11C-methyl]-(−)-cocaine PET studies in human subjects. J Cereb Blood Flow Metab 10(5):740–747

    PubMed  CAS  Google Scholar 

  35. Ichise M, Toyama H, Innis RB, Carson RE (2002) Strategies to improve neuroreceptor parameter estimation by linear regression analysis. J Cereb Blood Flow Metab 22(10):1271–1281. doi:10.1097/00004647-200210000-00015

    PubMed  Google Scholar 

  36. Logan J, Fowler JS, Volkow ND, Wang GJ, Ding YS, Alexoff DL (1996) Distribution volume ratios without blood sampling from graphical analysis of PET data. J Cereb Blood Flow Metab 16(5):834–840. doi:10.1097/00004647-199609000-00008

    PubMed  CAS  Google Scholar 

  37. Cunningham VJ, Jones T (1993) Spectral analysis of dynamic PET studies. J Cereb Blood Flow Metab 13(1):15–23

    PubMed  CAS  Google Scholar 

  38. Turkheimer F, Moresco RM, Lucignani G, Sokoloff L, Fazio F, Schmidt K (1994) The use of spectral analysis to determine regional cerebral glucose utilization with positron emission tomography and [18F]fluorodeoxyglucose: theory, implementation, and optimization procedures. J Cereb Blood Flow Metab 14(3):406–422

    PubMed  CAS  Google Scholar 

  39. Rosso L, Brock CS, Gallo JM, Saleem A, Price PM, Turkheimer FE, Aboagye EO (2009) A new model for prediction of drug distribution in tumor and normal tissues: pharmacokinetics of temozolomide in glioma patients. Cancer Res 69(1):120–127. doi:10.1158/0008-5472.CAN-08-2356

    PubMed  CAS  Google Scholar 

  40. Zhang X, Xiong Z, Wu Y, Cai W, Tseng JR, Gambhir SS, Chen X (2006) Quantitative PET imaging of tumor integrin alphavbeta3 expression with 18F-FRGD2. J Nucl Med 47(1):113–121

    PubMed  CAS  Google Scholar 

  41. Flores LG, Bertolini S, Yeh HH, Young D, Mukhopadhyay U, Pal A, Ying Y, Volgin A, Shavrin A, Soghomonyan S, Tong W, Bornmann W, Alauddin MM, Logsdon C, Gelovani JG (2009) Detection of pancreatic carcinomas by imaging lactose-binding protein expression in peritumoral pancreas using [18F]fluoroethyl-deoxylactose PET/CT. PLoS One 4(11):e7977. doi:10.1371/journal.pone.0007977

    PubMed  Google Scholar 

  42. Lammertsma AA, Hoekstra CJ, Giaccone G, Hoekstra OS (2006) How should we analyse FDG PET studies for monitoring tumour response? Eur J Nucl Med Mol Imaging 33(Suppl 1):16–21. doi:10.1007/s00259-006-0131-5

    PubMed  Google Scholar 

  43. Weber WA, Ziegler SI, Thodtmann R, Hanauske AR, Schwaiger M (1999) Reproducibility of metabolic measurements in malignant tumors using FDG PET. J Nucl Med 40(11):1771–1777

    PubMed  CAS  Google Scholar 

  44. Nahmias C, Wahl LM (2008) Reproducibility of standardized uptake value measurements determined by 18F-FDG PET in malignant tumors. J Nucl Med 49(11):1804–1808. doi:10.2967/jnumed.108.054239

    PubMed  Google Scholar 

  45. Velasquez LM, Boellaard R, Kollia G, Hayes W, Hoekstra OS, Lammertsma AA, Galbraith SM (2009) Repeatability of 18F-FDG PET in a multicenter phase I study of patients with advanced gastrointestinal malignancies. J Nucl Med 50(10):1646–1654. doi:10.2967/jnumed.109.063347

    PubMed  CAS  Google Scholar 

  46. Buck AK, Halter G, Schirrmeister H, Kotzerke J, Wurziger I, Glatting G, Mattfeldt T, Neumaier B, Reske SN, Hetzel M (2003) Imaging proliferation in lung tumors with PET: 18F-FLT versus 18F-FDG. J Nucl Med 44(9):1426–1431

    PubMed  CAS  Google Scholar 

  47. Pio BS, Park CK, Pietras R, Hsueh WA, Satyamurthy N, Pegram MD, Czernin J, Phelps ME, Silverman DH (2006) Usefulness of 3′-[F-18]fluoro-3′-deoxythymidine with positron emission tomography in predicting breast cancer response to therapy. Mol Imaging Biol 8(1):36–42. doi:10.1007/s11307-005-0029-9

    PubMed  Google Scholar 

  48. de Langen AJ, Klabbers B, Lubberink M, Boellaard R, Spreeuwenberg MD, Slotman BJ, de Bree R, Smit EF, Hoekstra OS, Lammertsma AA (2009) Reproducibility of quantitative 18F-3′-deoxy-3′-fluorothymidine measurements using positron emission tomography. Eur J Nucl Med Mol Imaging 36(3):389–395. doi:10.1007/s00259-008-0960-5

    PubMed  Google Scholar 

  49. Shields AF, Lawhorn-Crews JM, Briston DA, Zalzala S, Gadgeel S, Douglas KA, Mangner TJ, Heilbrun LK, Muzik O (2008) Analysis and reproducibility of 3′-Deoxy-3′-[18F]fluorothymidine positron emission tomography imaging in patients with non-small cell lung cancer. Clin Cancer Res 14(14):4463–4468. doi:10.1158/1078-0432.CCR-07-5243

    PubMed  CAS  Google Scholar 

  50. de Langen AJ, Lubberink M, Boellaard R, Spreeuwenberg MD, Smit EF, Hoekstra OS, Lammertsma AA (2008) Reproducibility of tumor perfusion measurements using 15O-labeled water and PET. J Nucl Med 49(11):1763–1768. doi:10.2967/jnumed.108.053454

    PubMed  Google Scholar 

  51. Lodge MA, Jacene HA, Pili R, Wahl RL (2008) Reproducibility of tumor blood flow quantification with 15O-water PET. J Nucl Med 49(10):1620–1627. doi:10.2967/jnumed.108.052076

    PubMed  Google Scholar 

  52. Sohn HJ, Yang YJ, Ryu JS, Oh SJ, Im KC, Moon DH, Lee DH, Suh C, Lee JS, Kim SW (2008) [18F]Fluorothymidine positron emission tomography before and 7 days after gefitinib treatment predicts response in patients with advanced adenocarcinoma of the lung. Clin Cancer Res 14(22):7423–7429. doi:10.1158/1078-0432.CCR-08-0312

    PubMed  CAS  Google Scholar 

  53. Herrmann K, Wieder HA, Buck AK, Schoffel M, Krause BJ, Fend F, Schuster T, Meyer zum Buschenfelde C, Wester HJ, Duyster J, Peschel C, Schwaiger M, Dechow T (2007) Early response assessment using 3′-deoxy-3′-[18F]fluorothymidine-positron emission tomography in high-grade non-Hodgkin’s lymphoma. Clin Cancer Res 13(12):3552–3558. doi:10.1158/1078-0432.CCR-06-3025

    PubMed  CAS  Google Scholar 

  54. Muijs CT, Beukema JC, Widder J, van den Bergh AC, Havenga K, Pruim J, Langendijk JA (18)F-FLT-PET for detection of rectal cancer. Radiother Oncol. doi:10.1016/j.radonc.2010.12.008

  55. Tomasi G, Bertoldo A, Cobelli C, Pavese N, Tai YF, Hammers A, Turkheimer FE (2010) Global-two-stage filtering of clinical PET parametric maps: application to [(11)C]-(R)-PK11195. Neuroimage. doi:10.1016/j.neuroimage.2010.12.056

  56. Mankoff DA, Shields AF, Graham MM, Link JM, Krohn KA (1996) A graphical analysis method to estimate blood-to-tissue transfer constants for tracers with labeled metabolites. J Nucl Med 37(12):2049–2057

    PubMed  CAS  Google Scholar 

  57. Mankoff DA, Shields AF, Graham MM, Link JM, Eary JF, Krohn KA (1998) Kinetic analysis of 2-[carbon-11]thymidine PET imaging studies: compartmental model and mathematical analysis. J Nucl Med 39(6):1043–1055

    PubMed  CAS  Google Scholar 

  58. Mankoff DA, Shields AF, Link JM, Graham MM, Muzi M, Peterson LM, Eary JF, Krohn KA (1999) Kinetic analysis of 2-[11C]thymidine PET imaging studies: validation studies. J Nucl Med 40(4):614–624

    PubMed  CAS  Google Scholar 

  59. Gunn RN, Yap JT, Wells P, Osman S, Price P, Jones T, Cunningham VJ (2000) A general method to correct PET data for tissue metabolites using a dual-scan approach. J Nucl Med 41(4):706–711

    PubMed  CAS  Google Scholar 

  60. Hatt M, Cheze-Le Rest C, Aboagye EO, Kenny LM, Rosso L, Turkheimer FE, Albarghach NM, Metges JP, Pradier O, Visvikis D Reproducibility of 18F-FDG and 3′-deoxy-3′-18F-fluorothymidine PET tumor volume measurements. J Nucl Med 51 (9):1368–1376. doi:10.2967/jnumed.110.078501

  61. Avril N, Bense S, Ziegler SI, Dose J, Weber W, Laubenbacher C, Romer W, Janicke F, Schwaiger M (1997) Breast imaging with fluorine-18-FDG PET: quantitative image analysis. J Nucl Med 38(8):1186–1191

    PubMed  CAS  Google Scholar 

  62. Schelling M, Avril N, Nahrig J, Kuhn W, Romer W, Sattler D, Werner M, Dose J, Janicke F, Graeff H, Schwaiger M (2000) Positron emission tomography using [(18)F]Fluorodeoxyglucose for monitoring primary chemotherapy in breast cancer. J Clin Oncol 18(8):1689–1695

    PubMed  CAS  Google Scholar 

  63. Lee JR, Madsen MT, Bushnel D, Menda Y (2000) A threshold method to improve standardized uptake value reproducibility. Nucl Med Commun 21(7):685–690

    PubMed  CAS  Google Scholar 

  64. Hatt M, Cheze le Rest C, Turzo A, Roux C, Visvikis D (2009) A fuzzy locally adaptive Bayesian segmentation approach for volume determination in PET. IEEE Trans Med Imaging 28(6):881–893. doi:10.1109/TMI.2008.2012036

    PubMed  Google Scholar 

  65. Krak NC, Boellaard R, Hoekstra OS, Twisk JW, Hoekstra CJ, Lammertsma AA (2005) Effects of ROI definition and reconstruction method on quantitative outcome and applicability in a response monitoring trial. Eur J Nucl Med Mol Imaging 32(3):294–301. doi:10.1007/s00259-004-1566-1

    PubMed  Google Scholar 

  66. Soret M, Bacharach SL, Buvat I (2007) Partial-volume effect in PET tumor imaging. J Nucl Med 48(6):932–945. doi:10.2967/jnumed.106.035774

    PubMed  Google Scholar 

  67. Soret MRC, Hapdey S, Buvat I (2002) Biases affecting the measurements of tumor-to-background activity ratio in PET. IEEE Trans Nucl Science 49:2112–2118

    Google Scholar 

  68. O’Sullivan F, Muzi M, Spence AM, Mankoff DM, O’Sullivan JN, Fitzgerald N, Newman GC, Krohn KA (2009) Nonparametric residue analysis of dynamic PET data with application to cerebral FDG studies in normals. J Am Stat Assoc 104(486):556–571. doi:10.1198/jasa.2009.0021

    PubMed  Google Scholar 

  69. Nehmeh SA, Erdi YE, Ling CC, Rosenzweig KE, Squire OD, Braban LE, Ford E, Sidhu K, Mageras GS, Larson SM, Humm JL (2002) Effect of respiratory gating on reducing lung motion artifacts in PET imaging of lung cancer. Med Phys 29(3):366–371

    PubMed  CAS  Google Scholar 

  70. Nye JA, Esteves F, Votaw JR (2007) Minimizing artifacts resulting from respiratory and cardiac motion by optimization of the transmission scan in cardiac PET/CT. Med Phys 34(6):1901–1906

    PubMed  Google Scholar 

  71. Gray KR, Contractor KB, Kenny LM, Al-Nahhas A, Shousha S, Stebbing J, Wasan HS, Coombes RC, Aboagye EO, Turkheimer FE, Rosso L (2010) Kinetic filtering of [(18)F]Fluorothymidine in positron emission tomography studies. Phys Med Biol 55(3):695–709. doi:10.1088/0031-9155/55/3/010

    PubMed  CAS  Google Scholar 

  72. Turkheimer FE, Edison P, Pavese N, Roncaroli F, Anderson AN, Hammers A, Gerhard A, Hinz R, Tai YF, Brooks DJ (2007) Reference and target region modeling of [11C]-(R)-PK11195 brain studies. J Nucl Med 48(1):158–167

    PubMed  Google Scholar 

  73. Tixier F, Le Rest CC, Hatt M, Albarghach N, Pradier O, Metges JP, Corcos L, Visvikis D Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med 52 (3):369–378. doi:10.2967/jnumed.110.082404

  74. El Naqa I, Grigsby P, Apte A, Kidd E, Donnelly E, Khullar D, Chaudhari S, Yang D, Schmitt M, Laforest R, Thorstad W, Deasy JO (2009) Exploring feature-based approaches in PET images for predicting cancer treatment outcomes. Pattern Recognit 42(6):1162–1171. doi:10.1016/j.patcog.2008.08.011

    PubMed  Google Scholar 

  75. Eary JF, O’Sullivan F, O’Sullivan J, Conrad EU (2008) Spatial heterogeneity in sarcoma 18F-FDG uptake as a predictor of patient outcome. J Nucl Med 49(12):1973–1979. doi:10.2967/jnumed.108.053397

    PubMed  Google Scholar 

  76. Dimitrakopoulou-Strauss A, Hoffmann M, Bergner R, Uppenkamp M, Eisenhut M, Pan L, Haberkorn U, Strauss LG (2007) Prediction of short-term survival in patients with advanced nonsmall cell lung cancer following chemotherapy based on 2-deoxy-2-[F-18]fluoro-d-glucose-positron emission tomography: a feasibility study. Mol Imaging Biol 9(5):308–317. doi:10.1007/s11307-007-0103-6

    PubMed  Google Scholar 

  77. Dimitrakopoulou-Strauss A, Hoffmann M, Bergner R, Uppenkamp M, Haberkorn U, Strauss LG (2009) Prediction of progression-free survival in patients with multiple myeloma following anthracycline-based chemotherapy based on dynamic FDG-PET. Clin Nucl Med 34(9):576–584. doi:10.1097/RLU.0b013e3181b06bc5

    PubMed  Google Scholar 

  78. Hatt M, Visvikis D, Albarghach NM, Tixier F, Pradier O, Cheze-le Rest C Prognostic value of (18)F-FDG PET image-based parameters in oesophageal cancer and impact of tumour delineation methodology. Eur J Nucl Med Mol Imaging 38 (7):1191–1202. doi:10.1007/s00259-011-1755-7

  79. Byrne HM Dissecting cancer through mathematics: from the cell to the animal model. Nat Rev Cancer 10 (3):221–230. doi:10.1038/nrc2808

  80. Sanga S, Frieboes HB, Zheng X, Gatenby R, Bearer EL, Cristini V (2007) Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth. Neuroimage 37(Suppl 1):S120–S134. doi:10.1016/j.neuroimage.2007.05.043

    PubMed  Google Scholar 

  81. Kelly CJ, Brady M (2006) A model to simulate tumour oxygenation and dynamic [18F]-Fmiso PET data. Phys Med Biol 51(22):5859–5873. doi:10.1088/0031-9155/51/22/009

    PubMed  CAS  Google Scholar 

  82. Zheng X, Wise SM, Cristini V (2005) Nonlinear simulation of tumor necrosis, neo-vascularization and tissue invasion via an adaptive finite-element/level-set method. Bull Math Biol 67(2):211–259. doi:10.1016/j.bulm.2004.08.001

    PubMed  CAS  Google Scholar 

  83. Flux GD, Guy MJ, Beddows R, Pryor M, Flower MA (2002) Estimation and implications of random errors in whole-body dosimetry for targeted radionuclide therapy. Phys Med Biol 47(17):3211–3223

    PubMed  Google Scholar 

  84. Gear JI, Charles-Edwards E, Partridge M, Flux GD (2007) A quality-control method for SPECT-based dosimetry in targeted radionuclide therapy. Cancer Biother Radiopharm 22(1):166–174. doi:10.1089/cbr.2007.305

    PubMed  CAS  Google Scholar 

  85. Divoli A, Chiavassa S, Ferrer L, Barbet J, Flux GD, Bardies M (2009) Effect of patient morphology on dosimetric calculations for internal irradiation as assessed by comparisons of Monte Carlo versus conventional methodologies. J Nucl Med 50(2):316–323. doi:10.2967/jnumed.108.056705

    PubMed  Google Scholar 

  86. Wu HM, Huang SC, Choi Y, Hoh CK, Hawkins RA (1995) A modeling method to improve quantitation of fluorodeoxyglucose uptake in heterogeneous tumor tissue. J Nucl Med 36(2):297–306

    PubMed  CAS  Google Scholar 

  87. Minn H, Zasadny KR, Quint LE, Wahl RL (1995) Lung cancer: reproducibility of quantitative measurements for evaluating 2-[F-18]-fluoro-2-deoxy-d-glucose uptake at PET. Radiology 196(1):167–173

    PubMed  CAS  Google Scholar 

  88. Torizuka T, Zasadny KR, Recker B, Wahl RL (1998) Untreated primary lung and breast cancers: correlation between F-18 FDG kinetic rate constants and findings of in vitro studies. Radiology 207(3):767–774

    PubMed  CAS  Google Scholar 

  89. Sugawara Y, Zasadny KR, Grossman HB, Francis IR, Clarke MF, Wahl RL (1999) Germ cell tumor: differentiation of viable tumor, mature teratoma, and necrotic tissue with FDG PET and kinetic modeling. Radiology 211(1):249–256

    PubMed  CAS  Google Scholar 

  90. Dimitrakopoulou-Strauss A, Strauss LG, Schwarzbach M, Burger C, Heichel T, Willeke F, Mechtersheimer G, Lehnert T (2001) Dynamic PET 18F-FDG studies in patients with primary and recurrent soft-tissue sarcomas: impact on diagnosis and correlation with grading. J Nucl Med 42(5):713–720

    PubMed  CAS  Google Scholar 

  91. Dimitrakopoulou-Strauss A, Strauss LG, Burger C, Ruhl A, Irngartinger G, Stremmel W, Rudi J (2004) Prognostic aspects of 18F-FDG PET kinetics in patients with metastatic colorectal carcinoma receiving FOLFOX chemotherapy. J Nucl Med 45(9):1480–1487

    PubMed  CAS  Google Scholar 

  92. Dimitrakopoulou-Strauss A, Strauss L (2006) Quantitative studies using positron emission tomography (PET) for the diagnosis and therapy planning of oncological patients. Hell J Nucl Med 9(1):10–21

    PubMed  Google Scholar 

  93. Dimitrakopoulou-Strauss A, Strauss LG, Egerer G, Vasamiliette J, Mechtersheimer G, Schmitt T, Lehner B, Haberkorn U, Stroebel P, Kasper B Impact of dynamic 18F-FDG PET on the early prediction of therapy outcome in patients with high-risk soft-tissue sarcomas after neoadjuvant chemotherapy: a feasibility study. J Nucl Med 51 (4):551–558. doi:10.2967/jnumed.109.070862

  94. Roe K, Aleksandersen TB, Kristian A, Nilsen LB, Seierstad T, Qu H, Ree AH, Olsen DR, Malinen E Preclinical dynamic 18F-FDG PET—tumor characterization and radiotherapy response assessment by kinetic compartment analysis. Acta Oncol 49 (7):914–921. doi:10.3109/0284186X.2010.498831

  95. Dunnwald LK, Doot RK, Specht JM, Gralow JR, Ellis GK, Livingston RB, Linden HM, Gadi VK, Kurland BF, Schubert EK, Muzi M, Mankoff DA PET Tumor Metabolism in Locally Advanced Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy: Value of Static versus Kinetic Measures of Fluorodeoxyglucose Uptake. Clin Cancer Res 17 (8):2400–2409. doi:10.1158/1078-0432.CCR-10-2649

  96. Kenny L, Vigushin D, Al-Nahhas A, Osman S, Luthra S, Coombes C, Aboagye E (2005) Quantification of cellular proliferation in tumor and normal tissues of patients with breast cancer by [18F]fluorothymidine-positron emission tomography imaging: evaluation of analytical methods. Cancer Res 65(21)

  97. Muzi M, Vesselle H, Grierson JR, Mankoff DA, Schmidt RA, Peterson L, Wells JM, Krohn KA (2005) Kinetic analysis of 3′-deoxy-3′-fluorothymidine PET studies: validation studies in patients with lung cancer. J Nucl Med 46(2):274–282

    PubMed  CAS  Google Scholar 

  98. Jacobs AH, Thomas A, Kracht LW, Li H, Dittmar C, Garlip G, Galldiks N, Klein JC, Sobesky J, Hilker R, Vollmar S, Herholz K, Wienhard K, Heiss WD (2005) 18F-fluoro-l-thymidine and 11C-methylmethionine as markers of increased transport and proliferation in brain tumors. J Nucl Med 46(12):1948–1958

    PubMed  CAS  Google Scholar 

  99. Muzi M, Spence AM, O’Sullivan F, Mankoff DA, Wells JM, Grierson JR, Link JM, Krohn KA (2006) Kinetic analysis of 3′-deoxy-3′-18F-fluorothymidine in patients with gliomas. J Nucl Med 47(10):1612–1621

    PubMed  CAS  Google Scholar 

  100. Ullrich R, Backes H, Li H, Kracht L, Miletic H, Kesper K, Neumaier B, Heiss WD, Wienhard K, Jacobs AH (2008) Glioma proliferation as assessed by 3′-fluoro-3′-deoxy-l-thymidine positron emission tomography in patients with newly diagnosed high-grade glioma. Clin Cancer Res 14(7):2049–2055. doi:10.1158/1078-0432.CCR-07-1553

    PubMed  CAS  Google Scholar 

  101. Pan MH, Huang SC, Liao YP, Schaue D, Wang CC, Stout DB, Barrio JR, McBride WH (2008) FLT-PET imaging of radiation responses in murine tumors. Mol Imaging Biol 10(6):325–334. doi:10.1007/s11307-008-0158-z

    PubMed  CAS  Google Scholar 

  102. Kim SJ, Lee JS, Im KC, Kim SY, Park SA, Lee SJ, Oh SJ, Lee DS, Moon DH (2008) Kinetic modeling of 3′-deoxy-3′-18F-fluorothymidine for quantitative cell proliferation imaging in subcutaneous tumor models in mice. J Nucl Med 49(12):2057–2066. doi:10.2967/jnumed.108.053215

    PubMed  Google Scholar 

  103. Eary JF, Mankoff DA, Spence AM, Berger MS, Olshen A, Link JM, O’Sullivan F, Krohn KA (1999) 2-[C-11]thymidine imaging of malignant brain tumors. Cancer Res 59(3):615–621

    PubMed  CAS  Google Scholar 

  104. Wells P, Gunn RN, Alison M, Steel C, Golding M, Ranicar AS, Brady F, Osman S, Jones T, Price P (2002) Assessment of proliferation in vivo using 2-[(11)C]thymidine positron emission tomography in advanced intra-abdominal malignancies. Cancer Res 62(20):5698–5702

    PubMed  CAS  Google Scholar 

  105. Kissel J, Brix G, Bellemann ME, Strauss LG, Dimitrakopoulou-Strauss A, Port R, Haberkorn U, Lorenz WJ (1997) Pharmacokinetic analysis of 5-[18F]fluorouracil tissue concentrations measured with positron emission tomography in patients with liver metastases from colorectal adenocarcinoma. Cancer Res 57(16):3415–3423

    PubMed  CAS  Google Scholar 

  106. Meikle SR, Matthews JC, Brock CS, Wells P, Harte RJ, Cunningham VJ, Jones T, Price P (1998) Pharmacokinetic assessment of novel anti-cancer drugs using spectral analysis and positron emission tomography: a feasibility study. Cancer Chemother Pharmacol 42(3):183–193

    PubMed  CAS  Google Scholar 

  107. Bading JR, Alauddin MM, Fissekis JD, Shahinian AH, Joung J, Spector T, Conti PS (2000) Blocking catabolism with eniluracil enhances PET studies of 5-[18F]fluorouracil pharmacokinetics. J Nucl Med 41(10):1714–1724

    PubMed  CAS  Google Scholar 

  108. Bading JR, Yoo PB, Fissekis JD, Alauddin MM, D’Argenio DZ, Conti PS (2003) Kinetic modeling of 5-fluorouracil anabolism in colorectal adenocarcinoma: a positron emission tomography study in rats. Cancer Res 63(13):3667–3674

    PubMed  CAS  Google Scholar 

  109. Dimitrakopoulou-Strauss A, Strauss LG, Gutzler F, Irngartinger G, Kontaxakis G, Kim DK, Oberdorfer F, van Kaick G (1999) Pharmacokinetic imaging of 11C ethanol with PET in eight patients with hepatocellular carcinomas who were scheduled for treatment with percutaneous ethanol injection. Radiology 211(3):681–686

    PubMed  CAS  Google Scholar 

  110. Dimitrakopoulou-Strauss A, Strauss LG, Burger C (2001) Quantitative PET studies in pretreated melanoma patients: a comparison of 6-[18F]fluoro-l-dopa with 18F-FDG and (15)O-water using compartment and noncompartment analysis. J Nucl Med 42(2):248–256

    PubMed  CAS  Google Scholar 

  111. Chen S, Ho C, Feng D, Chi Z (2004) Tracer kinetic modeling of 11C-acetate applied in the liver with positron emission tomography. IEEE Trans Med Imaging 23(4):426–432. doi:10.1109/TMI.2004.824229

    PubMed  Google Scholar 

  112. Chen JC, Chang SM, Hsu FY, Wang HE, Liu RS (2004) MicroPET-based pharmacokinetic analysis of the radiolabeled boron compound [18F]FBPA-F in rats with F98 glioma. Appl Radiat Isot 61(5):887–891. doi:10.1016/j.apradiso.2004.05.056

    PubMed  CAS  Google Scholar 

  113. Henze M, Dimitrakopoulou-Strauss A, Milker-Zabel S, Schuhmacher J, Strauss LG, Doll J, Macke HR, Eisenhut M, Debus J, Haberkorn U (2005) Characterization of 68 Ga-DOTA-d-Phe1-Tyr3-octreotide kinetics in patients with meningiomas. J Nucl Med 46(5):763–769

    PubMed  CAS  Google Scholar 

  114. Dimitrakopoulou-Strauss A, Georgoulias V, Eisenhut M, Herth F, Koukouraki S, Macke HR, Haberkorn U, Strauss LG (2006) Quantitative assessment of SSTR2 expression in patients with non-small cell lung cancer using(68)Ga-DOTATOC PET and comparison with (18)F-FDG PET. Eur J Nucl Med Mol Imaging 33(7):823–830. doi:10.1007/s00259-005-0063-5

    PubMed  Google Scholar 

  115. Beer AJ, Grosu AL, Carlsen J, Kolk A, Sarbia M, Stangier I, Watzlowik P, Wester HJ, Haubner R, Schwaiger M (2007) [18F]galacto-RGD positron emission tomography for imaging of alphavbeta3 expression on the neovasculature in patients with squamous cell carcinoma of the head and neck. Clin Cancer Res 13(22 Pt 1):6610–6616. doi:10.1158/1078-0432.CCR-07-0528

    PubMed  CAS  Google Scholar 

  116. Doot RK, Muzi M, Peterson LM, Schubert EK, Gralow JR, Specht JM, Mankoff DA Kinetic analysis of 18F-fluoride PET images of breast cancer bone metastases. J Nucl Med 51 (4):521–527. doi:10.2967/jnumed.109.070052

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Tomasi, G., Turkheimer, F. & Aboagye, E. Importance of Quantification for the Analysis of PET Data in Oncology: Review of Current Methods and Trends for the Future. Mol Imaging Biol 14, 131–146 (2012). https://doi.org/10.1007/s11307-011-0514-2

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