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Current Radiopharmaceuticals

Author(s): Habib E. Ashoor*

DOI: 10.2174/1874471015666220107101305

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Critical Review of the Simple Theoretical Models in Dynamic Imaging: Up-Slope Method and Graphical Analysis

Page: [174 - 183] Pages: 10

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Abstract

Clinical imaging equipment technological advancements offer insight into the evolution of mathematical techniques used to estimate parameters necessary to characterize the microvasculature and, thus, differentiate normal tissues from abnormal ones. These parameters are blood flow (F), capillary endothelial permeability surface area product (PS), vascular fraction (vp), and extravascular extracellular space size (EES,ve). There are a number of well-established approaches that exist in the literature; however, their analysis is restricted by complexity and is heavily influenced by noise. On the other hand, these characteristics can also be calculated using simpler and straightforward approaches such as Up-Slope Method (USM) and Graphical Analysis (GA). The review looks into the theoretical background and clinical uses of these methodologies, as well as the applicability of these techniques in various sections of the human body.

Keywords: Angiogenesis, microvasculature, Up-Slope model, graphical analysis, unidirectional model, bidirectional model.

Graphical Abstract

[1]
Hyder, F. Dynamic imaging of brain function. Methods Mol. Biol., 2009, 489, 3-21.
[http://dx.doi.org/10.1007/978-1-59745-543-5_1] [PMID: 18839085]
[2]
Marcus, C.D.; Ladam-Marcus, V.; Cucu, C.; Bouche, O.; Lucas, L.; Hoeffel, C. Imaging techniques to evaluate the response to treatment in oncology: Current standards and perspectives. Crit. Rev. Oncol. Hematol., 2009, 72(3), 217-238.
[PMID: 18760935]
[3]
Callewaert, B.; Jones, E.A.V.; Himmelreich, U.; Gsell, W. Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations; Diagnostics Basel; , 2021, Vol. 11, .
[4]
Chan, H. P.; Chang, C. C.; Hu, C.; Wang, W. H.; Peng, N. J.; Tyan, Y. C.; Yang, M. H. The evaluation of left ventricle ischemic extent in patients with significantly suspicious cardiovascular disease by (99m)Tc-sestamibi dynamic SPECT/CT and myocardial perfusion imaging: A head-to-head comparison Diagnostics (Basel), 2021, 11(6), 1101.
[5]
Larsson, H.B.; Stubgaard, M.; Frederiksen, J.L.; Jensen, M.; Henriksen, O.; Paulson, O.B. Quantitation of blood-brain barrier defect by magnetic resonance imaging and gadolinium-DTPA in patients with multiple sclerosis and brain tumors. Magn. Reson. Med., 1990, 16(1), 117-131.
[http://dx.doi.org/10.1002/mrm.1910160111] [PMID: 2255233]
[6]
Tofts, P.S. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J. Magn. Reson. Imaging, 1997, 7(1), 91-101.
[http://dx.doi.org/10.1002/jmri.1880070113] [PMID: 9039598]
[7]
Tofts, P.S.; Kermode, A.G. Blood brain barrier permeability in multiple sclerosis using labelled DTPA with PET, CT and MRI. J. Neurol. Neurosurg. Psychiatry, 1989, 52(8), 1019-1020.
[http://dx.doi.org/10.1136/jnnp.52.8.1019] [PMID: 2507745]
[8]
Wiender, N. Tumor angiogenesis and metastasis in invasive breast carcinoma. Engl. J. Med., 1995, 324, 1-8.
[9]
Carmeliet, P.; Jain, R.K. Angiogenesis in cancer and other diseases. Nature, 2000, 407(6801), 249-257.
[http://dx.doi.org/10.1038/35025220] [PMID: 11001068]
[10]
Cuenod, C.A.; Fournier, L.; Balvay, D.; Guinebretière, J.M. Tumor angiogenesis: pathophysiology and implications for contrast-enhanced MRI and CT assessment. Abdom. Imaging, 2006, 31(2), 188-193.
[http://dx.doi.org/10.1007/s00261-005-0386-5] [PMID: 16447089]
[11]
Folkman, J. What is the evidence that tumors are angiogenesis dependent? J. Natl. Cancer Inst., 1990, 82(1), 4-6.
[http://dx.doi.org/10.1093/jnci/82.1.4] [PMID: 1688381]
[12]
Sun, H.; Xu, Y.; Xu, Q.; Duan, J.; Zhang, H.; Liu, T.; Li, L.; Chan, Q.; Xie, S.; Wang, W. Correlation between intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging parameters in rectal cancer. Acad. Radiol., 2019, 26(7), e134-e140.
[http://dx.doi.org/10.1016/j.acra.2018.08.012] [PMID: 30268719]
[13]
Jackson, A. Quantitative characterization of tumour micro-vasculator using dynamic contrast-enhanced MRI. Medicamundi, 2003, 47, 40-47.
[14]
Ahmadian, N.; van Baarsen, K.M.; Robe, P.A.J.T.; Hoving, E.W. Association between cerebral perfusion and paediatric postoperative cerebellar mutism syndrome after posterior fossa surgery-a systematic review. Childs Nerv. Syst., 2021, 37(9), 2743-2751.
[http://dx.doi.org/10.1007/s00381-021-05225-5] [PMID: 34155533]
[15]
Gribbestad, I.S.; Gjesdal, K.I.; Nilsen, G.; Landgren, S.; Hjelstuen, M.H.B. An introduction to dynamic contrast-enhanced MRI in oncology In: Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Oncology, Medical Rediology: Diagnostic Imaging and Radiation Oncology; Jackson, A.; Buckley, D.L.; Parker, G.J., Eds.; Springer,, 2005, , pp. 3-37.
[http://dx.doi.org/10.1007/3-540-26420-5_1]
[16]
Padhani, A.R.; Husband, J.E. Dynamic contrast-enhanced MRI studies in oncology with an emphasis on quantification, validation and human studies. Clin. Radiol., 2001, 56(8), 607-620.
[http://dx.doi.org/10.1053/crad.2001.0762] [PMID: 11467863]
[17]
Kargozar, S.; Baino, F.; Hamzehlou, S.; Hamblin, M.R.; Mozafari, M. Nanotechnology for angiogenesis: Opportunities and challenges. Chem. Soc. Rev., 2020, 49(14), 5008-5057.
[http://dx.doi.org/10.1039/C8CS01021H] [PMID: 32538379]
[18]
Jain, R.; Ellika, S.K.; Scarpace, L.; Schultz, L.R.; Rock, J.P.; Gutierrez, J.; Patel, S.C.; Ewing, J.; Mikkelsen, T. Quantitative estimation of permeability surface-area product in astroglial brain tumors using perfusion CT and correlation with histopathologic grade. AJNR Am. J. Neuroradiol., 2008, 29(4), 694-700.
[http://dx.doi.org/10.3174/ajnr.A0899] [PMID: 18202239]
[19]
Harvey, C.; Dooher, A.; Morgan, J.; Blomley, M.; Dawson, P. Imaging of tumour therapy responses by dynamic CT. Eur. J. Radiol., 1999, 30(3), 221-226.
[http://dx.doi.org/10.1016/S0720-048X(99)00015-7] [PMID: 10452721]
[20]
Ishii, A.; Korogi, Y.; Nishimura, R.; Kawanaka, K.; Yamura, M.; Ikushima, I.; Hirai, T.; Yamashita, Y.; Shinohara, M. Intraarterial infusion chemotherapy for head and neck cancers: evaluation of tumor perfusion with intraarterial CT during carotid arteriography. Radiat. Med., 2004, 22(4), 254-259.
[PMID: 15468946]
[21]
Millar, A.W.; Lynch, K.P. Rethinking clinical trials for cytostatic drugs. Nat. Rev. Cancer, 2003, 3(7), 540-545.
[http://dx.doi.org/10.1038/nrc1124] [PMID: 12835674]
[22]
Xie, X.; Zhang, Y.; Li, F.; Lv, T.; Li, Z.; Chen, H.; Jia, L.; Gao, Y. Challenges and opportunities from basic cancer biology for nanomedicine for targeted drug delivery. Curr. Cancer Drug Targets, 2019, 19(4), 257-276.
[http://dx.doi.org/10.2174/1568009618666180628160211] [PMID: 29956629]
[23]
Geranpayehvaghei, M.; Dabirmanesh, B.; Khaledi, M.; Atabakhshi-Kashi, M.; Gao, C.; Taleb, M.; Zhang, Y.; Khajeh, K.; Nie, G. Cancer-associated-platelet-inspired nanomedicines for cancer therapy. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol., 2021, 13(5), e1702.
[http://dx.doi.org/10.1002/wnan.1702] [PMID: 33538125]
[24]
Koenig, M.; Klotz, E.; Luka, B.; Venderink, D.J.; Spittler, J.F.; Heuser, L. Perfusion CT of the brain: diagnostic approach for early detection of ischemic stroke. Radiology, 1998, 209(1), 85-93.
[http://dx.doi.org/10.1148/radiology.209.1.9769817] [PMID: 9769817]
[25]
Lee, T.Y.; Ellis, R.J.; Dunscombe, P.B.; McClarty, B.; Hodson, D.I.; Kroeker, M.A.; Bews, J. Quantitative computed tomography of the brain with xenon enhancement: a phantom study with the GE9800 scanner. Phys. Med. Biol., 1990, 35(7), 925-935.
[http://dx.doi.org/10.1088/0031-9155/35/7/008] [PMID: 2385623]
[26]
Miles, K.A. Measurement of tissue perfusion by dynamic computed tomography. Br. J. Radiol., 1991, 64(761), 409-412.
[http://dx.doi.org/10.1259/0007-1285-64-761-409] [PMID: 2036562]
[27]
Miles, K.A.; Leggett, D.A.; Bennett, G.A. CT derived Patlak images of the human kidney. Br. J. Radiol., 1999, 72(854), 153-158.
[http://dx.doi.org/10.1259/bjr.72.854.10365065] [PMID: 10365065]
[28]
Mungai, F.; Verrone, G.B.; Bonasera, L.; Bicci, E.; Pietragalla, M.; Nardi, C.; Berti, V.; Mazzoni, L.N.; Miele, V. Imaging biomarkers in the diagnosis of salivary gland tumors: the value of lesion/parenchyma ratio of perfusion-MR pharmacokinetic parameters. Radiol. Med. (Torino), 2021, 126(10), 1345-1355.
[http://dx.doi.org/10.1007/s11547-021-01376-2] [PMID: 34181206]
[29]
Montet, X.; Ivancevic, M.K.; Belenger, J.; Jorge-Costa, M.; Pochon, S.; Pechère, A.; Terrier, F.; Vallée, J.P. Noninvasive measurement of absolute renal perfusion by contrast medium-enhanced magnetic resonance imaging. Invest. Radiol., 2003, 38(9), 584-592.
[http://dx.doi.org/10.1097/01.RLI.0000077127.11949.8c] [PMID: 12960528]
[30]
Brix, G.; Bahner, M.L.; Hoffmann, U.; Horvath, A.; Schreiber, W. Regional blood flow, capillary permeability, and compartmental volumes: measurement with dynamic CT-initial experience. Radiology, 1999, 210(1), 269-276.
[http://dx.doi.org/10.1148/radiology.210.1.r99ja46269] [PMID: 9885619]
[31]
Coolens, C.; Gwilliam, M.N.; Alcaide-Leon, P.; de Freitas Faria, I.M.; Ynoe de Moraes, F. Transformational role of medical imaging in (radiation) oncology. Cancers (Basel), 2021, 13(11), 2557.
[http://dx.doi.org/10.3390/cancers13112557] [PMID: 34070984]
[32]
Hindel, S.; Heuchel, L.; Ludemann, L. Fractional calculus tracer kinetic compartment model for quantification of microvascular perfusion, In: Physiol Meas; , 2021; p. 42.
[33]
St Lawrence, K.S.; Lee, T.Y. An adiabatic approximation to the tissue homogeneity model for water exchange in the brain: II. Experimental validation. J. Cereb. Blood Flow Metab., 1998, 18(12), 1378-1385.
[http://dx.doi.org/10.1097/00004647-199812000-00012] [PMID: 9850150]
[34]
Li, K.L.; Zhu, X.P.; Checkley, D.R.; Tessier, J.J.; Hillier, V.F.; Waterton, J.C.; Jackson, A. Simultaneous mapping of blood volume and endothelial permeability surface area product in gliomas using iterative analysis of first-pass dynamic contrast enhanced MRI data. Br. J. Radiol., 2003, 76(901), 39-50.
[http://dx.doi.org/10.1259/bjr/31662734] [PMID: 12595324]
[35]
Li, K.L.; Jackson, A. New hybrid technique for accurate and reproducible quantitation of dynamic contrast-enhanced MRI data. Magn. Reson. Med., 2003, 50(6), 1286-1295.
[http://dx.doi.org/10.1002/mrm.10652] [PMID: 14648577]
[36]
Mullani, N.A.; Gould, K.L. First-pass measurements of regional blood flow with external detectors. J. Nucl. Med., 1983, 24(7), 577-581.
[PMID: 6602868]
[37]
Logan, J. Graphical analysis of PET data applied to reversible and irreversible tracers. Nucl. Med. Biol., 2000, 27(7), 661-670.
[http://dx.doi.org/10.1016/S0969-8051(00)00137-2] [PMID: 11091109]
[38]
Logan, J. A review of graphical methods for tracer studies and strategies to reduce bias. Nucl. Med. Biol., 2003, 30(8), 833-844.
[http://dx.doi.org/10.1016/S0969-8051(03)00114-8] [PMID: 14698787]
[39]
Marin, A.; Murchison, J.T.; Skwarski, K.M.; Tavares, A.A.S.; Fletcher, A.; Wallace, W.A.; Salapura, V.; van Beek, E.J.R.; Mirsadraee, S. Can dynamic imaging, using 18F-FDG PET/CT and CT perfusion differentiate between benign and malignant pulmonary nodules? Radiol. Oncol., 2021, 55(3), 259-267.
[http://dx.doi.org/10.2478/raon-2021-0024] [PMID: 34051709]
[40]
Krishnamoorthy, M.; Lenehan, J.G.; Maleki Vareki, S. Neoadjuvant immunotherapy for high-risk, resectable malignancies: Scientific rationale and clinical challenges. J. Natl. Cancer Inst., 2021, 113(7), 823-832.
[http://dx.doi.org/10.1093/jnci/djaa216] [PMID: 33432320]
[41]
Logan, J.; Fowler, J.S.; Volkow, N.D.; Wolf, A.P.; Dewey, S.L.; Schlyer, D.J.; MacGregor, R.R.; Hitzemann, R.; Bendriem, B.; Gatley, S.J. 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., 1990, 10(5), 740-747.
[http://dx.doi.org/10.1038/jcbfm.1990.127] [PMID: 2384545]
[42]
Ewing, J.R.; Brown, S.L.; Nagaraja, T.N.; Bagher-Ebadian, H.; Paudyal, R.; Panda, S.; Knight, R.A.; Ding, G.; Jiang, Q.; Lu, M.; Fenstermacher, J.D. MRI measurement of change in vascular parameters in the 9L rat cerebral tumor after dexamethasone administration. J. Magn. Reson. Imaging, 2008, 27(6), 1430-1438.
[http://dx.doi.org/10.1002/jmri.21356] [PMID: 18504732]
[43]
Ewing, J.R.; Brown, S.L.; Lu, M.; Panda, S.; Ding, G.; Knight, R.A.; Cao, Y.; Jiang, Q.; Nagaraja, T.N.; Churchman, J.L.; Fenstermacher, J.D. Model selection in magnetic resonance imaging measurements of vascular permeability: Gadomer in a 9L model of rat cerebral tumor. J. Cereb. Blood Flow Metab., 2006, 26(3), 310-320.
[http://dx.doi.org/10.1038/sj.jcbfm.9600189] [PMID: 16079791]
[44]
Patlak, C.S.; Blasberg, R.G. Graphical evaluation of blood -to-brain transfer constants from multiple-time uptake data. Generalizations. J. Cereb. Blood Flow Metab., 1985, 5(4), 584-590.
[http://dx.doi.org/10.1038/jcbfm.1985.87] [PMID: 4055928]
[45]
Patankar, T.F.; Haroon, H.A.; Mills, S.J.; Balériaux, D.; Buckley, D.L.; Parker, G.J.; Jackson, A. Is volume transfer coefficient (K(trans)) related to histologic grade in human gliomas? AJNR Am. J. Neuroradiol., 2005, 26(10), 2455-2465.
[PMID: 16286385]
[46]
Ellika, S.K.; Jain, R.; Patel, S.C.; Scarpace, L.; Schultz, L.R.; Rock, J.P.; Mikkelsen, T. Role of perfusion CT in glioma grading and comparison with conventional MR imaging features. AJNR Am. J. Neuroradiol., 2007, 28(10), 1981-1987.
[http://dx.doi.org/10.3174/ajnr.A0688] [PMID: 17893216]
[47]
Ashoor, H. Optimal time frame required to accurately estimate Ktrans, vp and veusing graphical method: Simulation Study 2019.
[http://dx.doi.org/10.1109/ICMSAO.2019.8880290]
[48]
Ashoor, H.E. DCE-CT perfusion parametric coloured image using steepest gradient approach based on time frame. EAI Endorsed Transac. Energ. Web, 2020, 6, 13.
[49]
Parker, G.J.; Padhani, A.R. T1-Weighted Dynamic Contrast-enhanced MRI. Quantitative MRI of the Brain; ; Tofts, P., Ed.; Wiley & Sons,. , 2003, pp. 341-364.
[http://dx.doi.org/10.1002/0470869526.ch10]
[50]
Kety, S.S. The theory and applications of the exchange of inert gas at the lungs and tissues. Pharmacol. Rev., 1951, 3(1), 1-41.
[PMID: 14833874]
[51]
Petralia, G.; Summers, P.E.; Agostini, A.; Ambrosini, R.; Cianci, R.; Cristel, G.; Calistri, L.; Colagrande, S. Dynamic contrast-enhanced MRI in oncology: How we do it. Radiol. Med. (Torino), 2020, 125(12), 1288-1300.
[http://dx.doi.org/10.1007/s11547-020-01220-z] [PMID: 32415476]
[52]
Crone, C. The permeability of capillaries in various organs as determined by use of the ‘indicator diffusion’ method. Acta Physiol. Scand., 1963, 58, 292-305.
[http://dx.doi.org/10.1111/j.1748-1716.1963.tb02652.x] [PMID: 14078649]
[53]
Henderson, E.; Sykes, J.; Drost, D.; Weinmann, H.J.; Rutt, B.K.; Lee, T.Y. Simultaneous MRI measurement of blood flow, blood volume, and capillary permeability in mammary tumors using two different contrast agents. J. Magn. Reson. Imaging, 2000, 12(6), 991-1003.
[http://dx.doi.org/10.1002/1522-2586(200012)12:6<991::AID-JMRI26>3.0.CO;2-1] [PMID: 11105041]
[54]
Tomandl, B.F.; Klotz, E.; Handschu, R.; Stemper, B.; Reinhardt, F.; Huk, W.J.; Eberhardt, K.E.; Fateh-Moghadam, S. Comprehensive imaging of ischemic stroke with multisection CT. Radiographics, 2003, 23(3), 565-592.
[http://dx.doi.org/10.1148/rg.233025036] [PMID: 12740462]
[55]
Kety, S.S. Theory of blood-tissue exchange and its application to measurement of blood flow. Methods Med. Res., 1960, 8, 223-227.
[56]
Li, L.; Lin, X.; Brown, M.B.; Gupta, S.; Lee, K.H. A population pharmacokinetic model with time-dependent covariates measured with errors. Biometrics, 2004, 60(2), 451-460.
[http://dx.doi.org/10.1111/j.0006-341X.2004.00190.x] [PMID: 15180671]
[57]
Vallée, J.P.; Lazeyras, F.; Khan, H.G.; Terrier, F. Absolute renal blood flow quantification by dynamic MRI and Gd-DTPA. Eur. Radiol., 2000, 10(8), 1245-1252.
[http://dx.doi.org/10.1007/s003300000434] [PMID: 10939483]
[58]
Kim, J.H.; Lee, J.W.; Park, K.; Ahn, M.J.; Moon, J.W.; Ham, S.Y.; Yi, C.A. Dynamic contrast-enhanced MRI for response evaluation of non-small cell lung cancer in therapy with epidermal growth factor receptor tyrosine kinase inhibitors: a pilot study. Ann. Palliat. Med., 2021, 10(2), 1589-1598.
[http://dx.doi.org/10.21037/apm-19-622] [PMID: 33302635]
[59]
Roberts, T.P. Physiologic measurements by contrast-enhanced MR imaging: expectations and limitations. J. Magn. Reson. Imaging, 1997, 7(1), 82-90.
[http://dx.doi.org/10.1002/jmri.1880070112] [PMID: 9039597]
[60]
Tofts, P.S.; Brix, G.; Buckley, D.L.; Evelhoch, J.L.; Henderson, E.; Knopp, M.V.; Larsson, H.B.; Lee, T.Y.; Mayr, N.A.; Parker, G.J.; Port, R.E.; Taylor, J.; Weisskoff, R.M. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J. Magn. Reson. Imaging, 1999, 10(3), 223-232.
[http://dx.doi.org/10.1002/(SICI)1522-2586(199909)10:3<223::AID-JMRI2>3.0.CO;2-S] [PMID: 10508281]
[61]
Parker, G.J.; Buckley, D.L. Tracer Kinetic Modelling for T1-Weighting DCE-MRI.Dynamic Contract-Enhanced Magnetic Resonance Imaging in Oncology; ; Jackson, A.; Buckley, D.L.; Parker, G.J., Eds.; Springer: Germany,. , 2005, pp. pp.81-92.
[http://dx.doi.org/10.1007/3-540-26420-5_6]
[62]
Henderson, E.; Rutt, B.K.; Lee, T.Y. Temporal sampling requirements for the tracer kinetics modeling of breast disease. Magn. Reson. Imaging, 1998, 16(9), 1057-1073.
[http://dx.doi.org/10.1016/S0730-725X(98)00130-1] [PMID: 9839990]
[63]
Buckley, D.L.; Kerslake, R.W.; Blackband, S.J.; Horsman, A. Quantitative analysis of multi-slice Gd-DTPA enhanced dynamic MR images using an automated simplex minimization procedure. Magn. Reson. Med., 1994, 32(5), 646-651.
[http://dx.doi.org/10.1002/mrm.1910320514] [PMID: 7808266]
[64]
Brix, G.; Semmler, W.; Port, R.; Schad, L.R.; Layer, G.; Lorenz, W.J. Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imaging. J. Comput. Assist. Tomogr., 1991, 15(4), 621-628.
[http://dx.doi.org/10.1097/00004728-199107000-00018] [PMID: 2061479]
[65]
Pekar, J.; Jezzard, P.; Roberts, D.A.; Leigh, J.S.J., Jr; Frank, J.A.; McLaughlin, A.C. Perfusion imaging with compensation for asymmetric magnetization transfer effects. Magn. Reson. Med., 1996, 35(1), 70-79.
[http://dx.doi.org/10.1002/mrm.1910350110] [PMID: 8771024]
[66]
Tofts, P.S.; Berkowitz, B.A. Measurement of capillary permeability from the Gd enhancement curve: a comparison of bolus and constant infusion injection methods. Magn. Reson. Imaging, 1994, 12(1), 81-91.
[http://dx.doi.org/10.1016/0730-725X(94)92355-8] [PMID: 8295511]
[67]
Patlak, C.S.; Blasberg, R.G.; Fenstermacher, J.D. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J. Cereb. Blood Flow Metab., 1983, 3(1), 1-7.
[http://dx.doi.org/10.1038/jcbfm.1983.1] [PMID: 6822610]
[68]
Wintermark, M.; Maeder, P.; Thiran, J.P.; Schnyder, P.; Meuli, R. Quantitative assessment of regional cerebral blood flows by perfusion CT studies at low injection rates: a critical review of the underlying theoretical models. Eur. Radiol., 2001, 11(7), 1220-1230.
[http://dx.doi.org/10.1007/s003300000707] [PMID: 11471616]
[69]
Tsushima, F.S.; Aoki J, Y; Sanada, S; Endo, K Quantitative perfusion map of malignant liver tumours, created from dynamic computed tomography data. Acad. Radiol., 2004, 11, 215-223.
[http://dx.doi.org/10.1016/S1076-6332(03)00578-6] [PMID: 14974597]
[70]
Blomley, M.J.; McBride, A.; Mohammedtagi, S.; Albrecht, T.; Harvey, C.J.; Jäger, R.; Standfield, N.J.; Dawson, P. Functional renal perfusion imaging with colour mapping: is it a useful adjunct to spiral CT of in the assessment of abdominal aortic aneurysm (AAA)? Eur. J. Radiol., 1999, 30(3), 214-220.
[http://dx.doi.org/10.1016/S0720-048X(99)00014-5] [PMID: 10452720]
[71]
Miles, K.A. Brain perfusion: computed tomography applications. Neuroradiology, 2004, 46(Suppl. 2), s194-s200.
[http://dx.doi.org/10.1007/s00234-004-1333-9] [PMID: 15645152]
[72]
Bruehlmeier, M.; Roelcke, U.; Bläuenstein, P.; Missimer, J.; Schubiger, P.A.; Locher, J.T.; Pellikka, R.; Ametamey, S.M. Measurement of the extracellular space in brain tumors using 76Br-bromide and PET. J. Nucl. Med., 2003, 44(8), 1210-1218.
[PMID: 12902409]
[73]
Kawatsu, S.; Kato, T.; Nagano-Saito, A.; Hatano, K.; Ito, K.; Ishigaki, T. New insight into the analysis of 6-[18F]fluoro-L-DOPA PET dynamic data in brain tissue without an irreversible compartment: comparative study of the Patlak and Logan analyses. Radiat. Med., 2003, 21(1), 47-54.
[PMID: 12801143]
[74]
Ikoma, Y.; Yasuno, F.; Ito, H.; Suhara, T.; Ota, M.; Toyama, H.; Fujimura, Y.; Takano, A.; Maeda, J.; Zhang, M.R.; Nakao, R.; Suzuki, K. Quantitative analysis for estimating binding potential of the peripheral benzodiazepine receptor with [(11)C]DAA1106. J. Cereb. Blood Flow Metab., 2007, 27(1), 173-184.
[http://dx.doi.org/10.1038/sj.jcbfm.9600325] [PMID: 16685259]
[75]
Tsuchida, T.; Sadato, N.; Yonekura, Y.; Yamamoto, K.; Waki, A.; Sugimoto, K.; Yang, J.T.; Ishizu, K.; Hayashi, N.; Ishii, Y. Quantification of regional cerebral blood flow with continuous infusion of technetium-99m-ethyl cysteinate dimer. J. Nucl. Med., 1997, 38(11), 1699-1702.
[PMID: 9374336]
[76]
Mertens, N.; Maguire, R.P.; Serdons, K.; Lacroix, B.; Mercier, J.; Sciberras, D.; Van Laere, K.; Koole, M. Validation of parametric methods for [11C]UCB-J PET imaging using subcortical white matter as reference tissue. Mol. Imaging Biol., 2020, 22(2), 444-452.
[http://dx.doi.org/10.1007/s11307-019-01387-6] [PMID: 31209780]
[77]
Logan, J.; Fowler, J.S.; Volkow, N.D.; Ding, Y.S.; Wang, G.J.; Alexoff, D.L. A strategy for removing the bias in the graphical analysis method. J. Cereb. Blood Flow Metab., 2001, 21(3), 307-320.
[http://dx.doi.org/10.1097/00004647-200103000-00014] [PMID: 11295885]
[78]
Slifstein, M.; Laruelle, M. Effects of statistical noise on graphic analysis of PET neuroreceptor studies. J. Nucl. Med., 2000, 41(12), 2083-2088.
[PMID: 11138696]
[79]
Ichise, M.; Toyama, H.; Innis, R.B.; Carson, R.E. Strategies to improve neuroreceptor parameter estimation by linear regression analysis. J. Cereb. Blood Flow Metab., 2002, 22(10), 1271-1281.
[http://dx.doi.org/10.1097/01.WCB.0000038000.34930.4E] [PMID: 12368666]