Skip to main content Accessibility help
×
Hostname: page-component-7479d7b7d-wxhwt Total loading time: 0 Render date: 2024-07-15T22:49:26.890Z Has data issue: false hasContentIssue false

9 - IMAGING BIOMARKERS IN DRUG DEVELOPMENT: CASE STUDIES

Published online by Cambridge University Press:  04 April 2011

Johannes T. Tauscher
Affiliation:
Lilly Research Laboratories
Adam J. Schwarz
Affiliation:
Lilly Research Laboratories
Bruce H. Littman
Affiliation:
Translational Medicine Associates
Rajesh Krishna
Affiliation:
Merck Research Laboratories
Get access

Summary

Introduction

The discovery and development of novel treatments is a lengthy and costly endeavor: for drug candidates entering clinical trials between 1989 and 2002, the estimated cost per new drug varied from approximately 500 million to more than 2 billion U.S. dollars. Biomarkers – objective and measurable responses to a putative drug candidate – have been heralded as one potential solution to the ever-increasing expenditure of developing new medicines, and anatomical or functional medical imaging can be one tool in the armamentarium of biomarkers. Conceptually, the utility of imaging biomarkers for facilitating drug development, especially go/no go decisions in early development, includes the following:

  • confirming the presence of a drug target in a (sub)population entering a clinical trial (e.g., accumulation of β-amyloid, as measured with positron emission tomography [PET] and a specific ligand for β-amyloid in the brain of patients entering a clinical trial for a novel Alzheimer's drug candidate);

  • assessing target engagement of a novel drug candidate (e.g., confirmation of dopamine-2 [D2]) receptor antagonism of antipsychotics using PET imaging of [C]-raclopride displacement);

  • demonstrating a functional effect of a drug on a mechanism- or disease-relevant biological parameter (e.g., blockade of ketamine-induced functional magnetic resonance imaging [fMRI] signal in the central nervous system [CNS] by antipsychotics or glutamate-normalizing compounds);

  • […]

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adams, CP, & Brantner, VV. (2006). Estimating the cost of new drug development: Is it really 802 million dollars? Health Aff. (Millwood). 25(2), 420–428.CrossRefGoogle ScholarPubMed
Klunk, WE, Engler, H, Nordberg, A, Wang, Y, Blomqvist, G, Holt, DP, et al. (2004). Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann. Neurol. 55(3), 306–319.CrossRefGoogle ScholarPubMed
Farde, L, Hall, H, Ehrin, E, & Sedvall, G. (1986). Quantitative analysis of D2 dopamine receptor binding in the living human brain by PET. Science. 231(4735), 258–261.CrossRefGoogle ScholarPubMed
Deakin, JF, Lees, J, McKie, S, Hallak, JE, Williams, SR, & Dursun, SM. (2008). Glutamate and the neural basis of the subjective effects of ketamine: A pharmaco-magnetic resonance imaging study. Arch. Gen. Psychiatry. 65(2), 154–164.CrossRefGoogle ScholarPubMed
Tauscher, J, Kielbasa, W, Iyengar, S, Vandenhende, F, Peng, X, Mozley, D, et al. (2009). Development of the 2nd generation neurokinin-1 receptor antagonist LY686017 for social anxiety disorder. Eur. Neuropsychopharmacol. 20, 80–87.CrossRefGoogle ScholarPubMed
Galbraith, SM. (2006). MR in oncology drug development. NMR Biomed. 19(6), 681–689.CrossRefGoogle ScholarPubMed
Steiger, P. (2009). Use of imaging biomarkers for regulatory studies. J. Bone Joint Surg. 91(Suppl 1), 132–136.CrossRefGoogle ScholarPubMed
Eisenhauer, EA, Therasse, P, Bogaerts, J, Schwartz, LH, Sargent, D, Ford, R, et al. (2009). New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur. J. Cancer. 45(2), 228–247.CrossRefGoogle ScholarPubMed
Olson, S, Robinson, S, & Giffin, R. (2009). Accelerating the Development of Biomarkers for Drug Safety: Workshop Summary. Washington, DC: The National Academies Press.Google Scholar
Woodcock, J, & Woosley, R. (2008). The FDA critical path initiative and its influence on new drug development. Ann. Rev. Med. 59, 1–12.CrossRefGoogle ScholarPubMed
Kapur, S, Remington, G, Jones, C, Wilson, A, DaSilva, J, Houle S, , et al. (1996). High levels of dopamine D2 receptor occupancy with low-dose haloperidol treatment: A PET study. Am. J. Psychiatry. 153(7), 948–950.Google ScholarPubMed
Farde, L, Nordstrom, AL, Wiesel, FA, Pauli, S, Halldin, C, & Sedvall, G. (1992). Positron emission tomographic analysis of central D1 and D2 dopamine receptor occupancy in patients treated with classical neuroleptics and clozapine. Relation to extrapyramidal side effects. Arch. Gen. Psychiatry. 49(7), 538–544.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Kapur, S, Zipursky, R, Jones, C, Remington, G, & Houle, S. (2000). Relationship between dopamine D(2) occupancy, clinical response, and side effects: A double-blind PET study of first-episode schizophrenia. Am. J. Psychiatry. 157(4), 514–520.CrossRefGoogle ScholarPubMed
Tauscher, J, & Kapur, S. (2001). Choosing the right dose of antipsychotics in schizophrenia: Lessons from neuroimaging studies. CNS Drugs. 15(9), 671–678.CrossRefGoogle ScholarPubMed
Grunder, G, Yokoi, F, Offord, SJ, Ravert, HT, Dannals, RF, Salzmann, JK, et al. (1997). Time course of 5-HT2A receptor occupancy in the human brain after a single oral dose of the putative antipsychotic drug MDL 100,907 measured by positron emission tomography. Neuropsychopharmacology. 17(3), 175–185.CrossRefGoogle ScholarPubMed
Tauscher, J, Jones, C, Remington, G, Zipursky, RB, & Kapur, S. (2002). Significant dissociation of brain and plasma kinetics with antipsychotics. Mol. Psychiatry. 7(3), 317–321.CrossRefGoogle ScholarPubMed
Tauscher, J, Pirker, W, Zwaan, M, Asenbaum, S, Brucke, T, & Kasper, S. (1999). In vivo visualization of serotonin transporters in the human brain during fluoxetine treatment. Eur. Neuropsychopharmacol. 9(1–2), 177–179.CrossRefGoogle ScholarPubMed
Meyer, JH. (2007). Imaging the serotonin transporter during major depressive disorder and antidepressant treatment. J. Psychiatry Neurosci. 32(2), 86–102.Google ScholarPubMed
Meyer, JH, Wilson, AA, Ginovart, N, Goulding, V, Hussey, D, Hood, K, et al. (2001). Occupancy of serotonin transporters by paroxetine and citalopram during treatment of depression: A [(11)C]DASB PET imaging study. Am. J. Psychiatry. 158(11), 1843–1849.CrossRefGoogle Scholar
Meyer, JH, Wilson, AA, Sagrati, S, Hussey, D, Carella, A, Potter, WZ, et al. (2004). Serotonin transporter occupancy of five selective serotonin reuptake inhibitors at different doses: An [11C]DASB positron emission tomography study. Am. J. Psychiatry. 161(5), 826–835.CrossRefGoogle Scholar
Suhara, T, Takano, A, Sudo, Y, Ichimiya, T, Inoue, M, Yasuno, F, et al. (2003). High levels of serotonin transporter occupancy with low-dose clomipramine in comparative occupancy study with fluvoxamine using positron emission tomography. Arch. Gen. Psychiatry. 60(4), 386–391.CrossRefGoogle ScholarPubMed
Raichle, ME. (1998). Imaging the mind. Semin. Nucl. Med. 28(4), 278–289.CrossRefGoogle ScholarPubMed
Raichle, ME. (2009). A brief history of human brain mapping. Trends Neurosci. 32(2), 118–126.CrossRefGoogle ScholarPubMed
Ogawa, S, Lee, TM, Kay, AR, & Tank, DW. (1990). Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl. Acad. Sci. U. S. A. 87(24), 9868–9872.CrossRefGoogle ScholarPubMed
Bandettini, PA, Wong, EC, Hinks, RS, Tikofsky, RS, & Hyde, JS. (1992). Time course EPI of human brain function during task activation. Magn. Reson. Med. 25(2), 390–397.CrossRefGoogle ScholarPubMed
Blamire, AM, Ogawa, S, Ugurbil, K, Rothman, D, McCarthy, G, Ellermann, JM, et al. (1992). Dynamic mapping of the human visual cortex by high-speed magnetic resonance imaging. Proc. Natl. Acad. Sci. U. S. A. 89(22), 11069–11073.CrossRefGoogle ScholarPubMed
Frahm, J, Bruhn, H, Merboldt, KD, & Hanicke, W. (1992). Dynamic MR imaging of human brain oxygenation during rest and photic stimulation. J. Magn. Reson. Imaging. 2(5), 501–505.CrossRefGoogle ScholarPubMed
Kwong, KK, Belliveau, JW, Chesler, DA, Goldberg, IE, Weisskoff, RM, Poncelet, BP, et al. (1992). Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc. Natl. Acad. Sci. U. S. A. 89(12), 5675–5679.CrossRefGoogle ScholarPubMed
Honey, G, & Bullmore, E. (2004). Human pharmacological MRI. Trends. Pharmacol. Sci. 25(7), 366–374.CrossRefGoogle ScholarPubMed
Schweinhardt, P, Bountra, C, & Tracey, I. (2006). Pharmacological fMRI in the development of new analgesic compounds. NMR Biomed. 19(6), 702–711.CrossRefGoogle ScholarPubMed
Abel, KM, Allin, MP, Kucharska-Pietura, K, David, A, Andrew, C, Williams, S, et al. (2003). Ketamine alters neural processing of facial emotion recognition in healthy men: An fMRI study. Neuroreport. 14(3), 387–391.CrossRefGoogle ScholarPubMed
Anderson, IM, Del-Ben, CM, McKie, S, Richardson, P, Williams, SR, Elliott, R, et al. (2007). Citalopram modulation of neuronal responses to aversive face emotions: A functional MRI study. Neuroreport. 18(13), 1351–1355.CrossRefGoogle ScholarPubMed
Anderson, IM, McKie, S, Elliott, R, Williams, SR, & Deakin, JF. (2008). Assessing human 5-HT function in vivo with pharmaco MRI. Neuropharmacol. 55(6), 1029–1037.CrossRefGoogle Scholar
Apud, JA, Mattay, V, Chen, J, Kolachana, BS, Callicott, JH, Rasetti, R, et al. (2007). Tolcapone improves cognition and cortical information processing in normal human subjects. Neuropsychopharmacol. 32(5), 1011–1020.CrossRefGoogle ScholarPubMed
Becerra, L, Harter, K, Gonzalez, RG, & Borsook, D. (2006). Functional magnetic resonance imaging measures of the effects of morphine on central nervous system circuitry in opioid-naive healthy volunteers. Anesth. Analg. 103(1), 208–216.CrossRefGoogle ScholarPubMed
Borsook, D, Becerra, L, & Hargreaves, R. (2006). A role for fMRI in optimizing CNS drug development. Nat. Rev. Drug Discov. 5(5), 411–424.CrossRefGoogle ScholarPubMed
Fu, CH, Williams, SC, Brammer, MJ, Suckling, J, Kim, J, Cleare, AJ, et al. (2007). Neural responses to happy facial expressions in major depression following antidepressant treatment. Am. J. Psychiatry. 164(4), 599–607.CrossRefGoogle ScholarPubMed
Fu, CH, Williams, SC, Cleare, AJ, Brammer, MJ, Walsh, ND, Kim, J, et al. (2004). Attenuation of the neural response to sad faces in major depression by antidepressant treatment: A prospective, event-related functional magnetic resonance imaging study. Arch. Gen. Psychiatry. 61(9), 877–889.CrossRefGoogle ScholarPubMed
Goekoop, R, Barkhof, F, Duschek, EJ, Netelenbos, C, Knol, DL, Scheltens, P, et al. (2006). Raloxifene treatment enhances brain activation during recognition of familiar items: A pharmacological fMRI study in healthy elderly males. Neuropsychopharmacol. 31(7), 1508–1518.CrossRefGoogle ScholarPubMed
Honey, GD, Suckling, J, Zelaya, F, Long, C, Routledge, C, Jackson, S, et al. (2003). Dopaminergic drug effects on physiological connectivity in a human cortico-striato-thalamic system. Brain. 126(Pt 8), 1767–1781.CrossRefGoogle Scholar
Honey, RA, Honey, GD, O'Loughlin, C, Sharar, SR, Kumaran, D, Bullmore, ET, et al. (2004). Acute ketamine administration alters the brain responses to executive demands in a verbal working memory task: An fMRI study. Neuropsychopharmacol. 29(6), 1203–1214.CrossRefGoogle Scholar
Lorenz, IH, Egger, K, Schubert, H, Schnurer, C, Tiefenthaler, W, Hohlrieder, M, et al. (2008). Lornoxicam characteristically modulates cerebral pain-processing in human volunteers: A functional magnetic resonance imaging study. Br. J. Anaesth. 100(6), 827–833.CrossRefGoogle ScholarPubMed
Sheline, YI, Barch, DM, Donnelly, JM, Ollinger, JM, Snyder, AZ, & Mintun, MA. (2001). Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: An fMRI study. Biol. Psychiatry. 50(9), 651–658.CrossRefGoogle ScholarPubMed
Stein, EA, Pankiewicz, J, Harsch, HH, Cho, JK, Fuller, SA, Hoffmann, RG, et al. (1998). Nicotine-induced limbic cortical activation in the human brain: A functional MRI study. Am. J. Psychiatry. 155(8), 1009–1015.CrossRefGoogle ScholarPubMed
Thiel, CM, Henson, RN, & Dolan, RJ. (2002). Scopolamine but not lorazepam modulates face repetition priming: A psychopharmacological fMRI study. Neuropsychopharmacol. 27(2), 282–292.CrossRefGoogle Scholar
Wise, RG, Rogers, R, Painter, D, Bantick, S, Ploghaus, A, Williams, P, et al. (2002). Combining fMRI with a pharmacokinetic model to determine which brain areas activated by painful stimulation are specifically modulated by remifentanil. Neuroimage. 16(4), 999–1014.CrossRefGoogle ScholarPubMed
Borsook, D, Bleakman, D, Hargreaves, R, Upadhyay, J, Schmidt, KF, & Becerra, L. (2008). A ‘BOLD’ experiment in defining the utility of fMRI in drug development. Neuroimage. 42(2), 461–466.CrossRefGoogle ScholarPubMed
Logothetis, NK. (2008). What we can do and what we cannot do with fMRI. Nature. 453(7197), 869–878.CrossRefGoogle Scholar
Breiter, HC, Gollub, RL, Weisskoff, RM, Kennedy, DN, Makris, N, Berke, JD, et al. (1997). Acute effects of cocaine on human brain activity and emotion. Neuron. 19(3), 591–611.CrossRefGoogle ScholarPubMed
Kufahl, PR, Li, Z, Risinger, RC, Rainey, CJ, Wu, G, Bloom, AS, et al. (2005). Neural responses to acute cocaine administration in the human brain detected by fMRI. Neuroimage. 28(4), 904–914.CrossRefGoogle ScholarPubMed
Kufahl, P, Li, Z, Risinger, R, Rainey, C, Piacentine, L, Wu, G, et al. (2008). Expectation modulates human brain responses to acute cocaine: A functional magnetic resonance imaging study. Biol. Psychiatry. 63(2), 222–230.CrossRefGoogle ScholarPubMed
Leppa, M, Korvenoja, A, Carlson, S, Timonen, P, Martinkauppi, S, Ahonen, J, et al. (2006). Acute opioid effects on human brain as revealed by functional magnetic resonance imaging. Neuroimage. 31(2), 661–669.CrossRefGoogle ScholarPubMed
Chen, YI, Choi, JK, & Jenkins, BG. (2005). Mapping interactions between dopamine and adenosine A2a receptors using pharmacologic MRI. Synapse. 55(2), 80–88.CrossRefGoogle ScholarPubMed
Chen, YC, Galpern, WR, Brownell, AL, Matthews, RT, Bogdanov, M, Isacson, O, et al. (1997). Detection of dopaminergic neurotransmitter activity using pharmacologic MRI: Correlation with PET, microdialysis, and behavioral data. Magn. Reson. Med. 38(3), 389–398.CrossRefGoogle ScholarPubMed
Chen, YC, Choi, JK, Andersen, SL, Rosen, BR, & Jenkins, BG. (2005). Mapping dopamine D2/D3 receptor function using pharmacological magnetic resonance imaging. Psychopharmacol. (Berl). 180(4), 705–715.CrossRefGoogle ScholarPubMed
Reese, T, Bjelke, B, Porszasz, R, Baumann, D, Bochelen, D, Sauter, A, et al. (2000). Regional brain activation by bicuculline visualized by functional magnetic resonance imaging. Time-resolved assessment of bicuculline-induced changes in local cerebral blood volume using an intravascular contrast agent. NMR Biomed. 13(1), 43–49.3.0.CO;2-S>CrossRefGoogle ScholarPubMed
Schwarz, A, Gozzi, A, Reese, T, Bertani, S, Crestan, V, Hagan, J, et al. (2004). Selective dopamine D(3) receptor antagonist SB-277011—A potentiates phMRI response to acute amphetamine challenge in the rat brain. Synapse. 54(1), 1–10.CrossRefGoogle ScholarPubMed
Gozzi, A, Schwarz, A, Reese, T, Bertani, S, Crestan, V, & Bifone, A. (2006). Region-specific effects of nicotine on brain activity: A pharmacological MRI study in the drug-naive rat. Neuropsychopharmacol. 31(8), 1690–1703.CrossRefGoogle ScholarPubMed
Gozzi, A, Large, CH, Schwarz, A, Bertani, S, Crestan, V, & Bifone, A. (2008). Differential effects of antipsychotic and glutamatergic agents on the phMRI response to phencyclidine. Neuropsychopharmacol. 33(7), 1690–1703.CrossRefGoogle ScholarPubMed
Ireland, MD, Lowe, AS, Reavill, C, James, MF, Leslie, RA, & Williams, SC. (2005). Mapping the effects of the selective dopamine D2/D3 receptor agonist quinelorane using pharmacological magnetic resonance imaging. Neuroscience. 133(1), 315–326.CrossRefGoogle ScholarPubMed
Skoubis, PD, Hradil, V, Chin, CL, Luo, Y, Fox, GB, & McGaraughty, S. (2006). Mapping brain activity following administration of a nicotinic acetylcholine receptor agonist, ABT-594, using functional magnetic resonance imaging in awake rats. Neuroscience. 137(2), 583–591.CrossRefGoogle ScholarPubMed
Xu, H, Li, SJ, Bodurka, J, Zhao, X, Xi, ZX, & Stein, EA. (2000). Heroin-induced neuronal activation in rat brain assessed by functional MRI. Neuroreport. 11(5), 1085–1092.CrossRefGoogle ScholarPubMed
Detre, JA, & Wang, J. (2002). Technical aspects and utility of fMRI using BOLD and ASL. Clin. Neurophysiol. 113(5), 621–634.CrossRefGoogle ScholarPubMed
Williams, DS. (2006). Quantitative perfusion imaging using arterial spin labeling. Methods Mol. Med. 124, 151–73.Google ScholarPubMed
O'Gorman, RL, Mehta, MA, Asherson, P, Zelaya, FO, Brookes, KJ, Toone, BK, et al. (2008). Increased cerebral perfusion in adult attention deficit hyperactivity disorder is normalised by stimulant treatment: A non-invasive MRI pilot study. Neuroimage. 42(1), 36–41.CrossRefGoogle ScholarPubMed
Jenkins, BG, Sanchez-Pernaute, R, Brownell, AL, Chen, YC, & Isacson, O. (2004). Mapping dopamine function in primates using pharmacologic magnetic resonance imaging. J. Neurosci. 24(43), 9553–9560.CrossRefGoogle ScholarPubMed
Andersen, AH, Zhang, Z, Barber, T, Rayens, WS, , Zhang J, Grondin, R, et al. (2002). Functional MRI studies in awake rhesus monkeys: Methodological and analytical strategies. J. Neurosci. Methods. 118(2), 141–152.CrossRefGoogle ScholarPubMed
Bingel, U, Quante, M, Knab, R, Bromm, B, Weiller, C, & Buchel, C. (2003). Single trial fMRI reveals significant contralateral bias in responses to laser pain within thalamus and somatosensory cortices. Neuroimage. 18(3), 740–748.CrossRefGoogle ScholarPubMed
Borras, MC, Becerra, L, Ploghaus, A, Gostic, JM, DaSilva, A, Gonzalez, RG, et al. (2004). fMRI measurement of CNS responses to naloxone infusion and subsequent mild noxious thermal stimuli in healthy volunteers. J. Neurophysiol. 91(6), 2723–2733.CrossRefGoogle ScholarPubMed
Wise, RG, Williams, P, & Tracey, I. (2004). Using fMRI to quantify the time dependence of remifentanil analgesia in the human brain. Neuropsychopharmacol. 29(3), 626–635.CrossRefGoogle ScholarPubMed
Borsook, D, & Becerra, LR. (2006). Breaking down the barriers: fMRI applications in pain, analgesia and analgesics. Mol. Pain. 2, 30.CrossRefGoogle ScholarPubMed
Oertel, BG, Preibisch, C, Wallenhorst, T, Hummel, T, Geisslinger, G, Lanfermann, H, et al. (2008). Differential opioid action on sensory and affective cerebral pain processing. Clin. Pharmacol. Ther. 83(4), 577–588.CrossRefGoogle ScholarPubMed
Iannetti, GD, Zambreanu, L, Wise, RG, Buchanan, TJ, Huggins, JP, Smart, TS, et al. (2005). Pharmacological modulation of pain-related brain activity during normal and central sensitization states in humans. Proc. Natl. Acad. Sci. U. S. A. 102(50), 18195–18200.CrossRefGoogle ScholarPubMed
Nahas, Z, George, MS, Horner, MD, Markowitz, JS, Li, X, Lorberbaum, JP, et al. (2003). Augmenting atypical antipsychotics with a cognitive enhancer (donepezil) improves regional brain activity in schizophrenia patients: A pilot double-blind placebo controlled BOLD fMRI study. Neurocase. 9(3), 274–282.Google ScholarPubMed
Del-Ben, CM, Deakin, JF, McKie, S, Delvai, NA, Williams, SR, Elliott, R, et al. (2005). The effect of citalopram pretreatment on neuronal responses to neuropsychological tasks in normal volunteers: An FMRI study. Neuropsychopharmacol. 30(9), 1724–1734.CrossRefGoogle ScholarPubMed
Muller, U, Suckling, J, Zelaya, F, Honey, G, Faessel, H, Williams, SC, et al. (2005). Plasma level-dependent effects of methylphenidate on task-related functional magnetic resonance imaging signal changes. Psychopharmacology (Berl). 180(4), 624–633.CrossRefGoogle ScholarPubMed
Yahata, N, Takahashi, H, & Okubo, Y. (2005). Pharmacological modulations in human cognitive processes: An fMRI study. J. Nippon Med. Sch. 72(1), 2–3.CrossRefGoogle Scholar
Biswal, B, Yetkin, FZ, Haughton, VM, & Hyde, JS. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34(4), 537–541.CrossRefGoogle ScholarPubMed
Fox, MD, Snyder, AZ, Vincent, JL, Corbetta, M, Van Essen, DC, & Raichle, ME. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U. S. A. 102(27), 9673–9678.CrossRefGoogle ScholarPubMed
Shehzad, Z, Kelly, AM, Reiss, PT, Gee, DG, Gotimer, K, Uddin, LQ, et al. (2009). The resting brain: Unconstrained yet reliable. Cereb. Cortex. 19(10), 2209–2229.CrossRefGoogle ScholarPubMed
Damoiseaux, JS, Rombouts, SA, Barkhof, F, Scheltens, P, Stam, CJ, Smith, SM, et al. (2006). Consistent resting-state networks across healthy subjects. Proc. Natl. Acad. Sci. U. S. A. 103(37), 13848–13853.CrossRefGoogle ScholarPubMed
Achard, S, & Bullmore, E. (2007). Efficiency and cost of economical brain functional networks. PloS Comput. Biol. 3(2), e17.CrossRefGoogle ScholarPubMed
Anand, A, Li, Y, Wang, Y, Wu, J, Gao, S, Bukhari, L, et al. (2005). Antidepressant effect on connectivity of the mood-regulating circuit: An FMRI study. Neuropsychopharmacol. 30(7), 1334–1344.CrossRefGoogle ScholarPubMed
Kelly, C, Zubicaray, G, Di Martino, A, Copland, DA, Reiss, PT, Klein, DF, et al. (2009). L-dopa modulates functional connectivity in striatal cognitive and motor networks: A double-blind placebo-controlled study. J. Neurosci. 29(22), 7364–7378.CrossRefGoogle ScholarPubMed
Greicius, M. (2008). Resting-state functional connectivity in neuropsychiatric disorders. Curr. Opin. Neurol. 21(4), 424–430.CrossRefGoogle ScholarPubMed
Verma, A, Declercq, R, Coimbra, A, & Achten, E. (2009). Incorporating functional MRI into clinical pharmacology trials. In: Imaging in CNS Drug Discovery and Development, edited by Borsook D. Springer, New York.Google Scholar
Large, CH. (2007). Do NMDA receptor antagonist models of schizophrenia predict the clinical efficacy of antipsychotic drugs? J. Psychopharmacol. 21(3), 283–301.CrossRefGoogle ScholarPubMed
Littlewood, CL, Cash, D, Dixon, AL, Dix, SL, White, CT, O'Neill, MJ, et al. (2006). Using the BOLD MR signal to differentiate the stereoisomers of ketamine in the rat. Neuroimage. 32(4), 1733–1746.CrossRefGoogle ScholarPubMed
Littlewood, CL, Jones, N, O'Neill, MJ, Mitchell, SN, Tricklebank, M, & Williams, SC. (2006). Mapping the central effects of ketamine in the rat using pharmacological MRI. Psychopharmacol. (Berl). 186(1), 64–81.CrossRefGoogle ScholarPubMed
Gozzi, A, Schwarz, A, Crestan, V, & Bifone, A. (2008). Drug-anaesthetic interaction in phMRI: The case of the psychotomimetic agent phencyclidine. Magn. Reson. Imaging. 26(7), 999–1006.CrossRefGoogle ScholarPubMed
Gozzi, A, Herdon, H, Schwarz, A, Bertani, S, Crestan, V, Turrini, G, et al. (2008). Pharmacological stimulation of NMDA receptors via co-agonist site suppresses fMRI response to phencyclidine in the rat. Psychopharmacol. (Berl). 201(2), 273–284.CrossRefGoogle ScholarPubMed
Duncan, GE, Leipzig, JN, Mailman, RB, & Lieberman, JA. (1998). Differential effects of clozapine and haloperidol on ketamine-induced brain metabolic activation. Brain Res. 812(1–2), 65–75.CrossRefGoogle ScholarPubMed
Duncan, GE, Miyamoto, S, Leipzig, JN, & Lieberman, JA. (2000). Comparison of the effects of clozapine, risperidone, and olanzapine on ketamine-induced alterations in regional brain metabolism. J. Pharmacol. Exp. Ther. 293(1), 8–14.Google ScholarPubMed
Langsjo, JW, Kaisti, KK, Aalto, S, Hinkka, S, Aantaa, R, Oikonen, V, et al. (2003). Effects of subanesthetic doses of ketamine on regional cerebral blood flow, oxygen consumption, and blood volume in humans. Anesthesiology. 99(3), 614–623.CrossRefGoogle ScholarPubMed
Langsjo, JW, Maksimow, A, Salmi, E, Kaisti, K, Aalto, S, Oikonen, V, et al. (2005). S-ketamine anesthesia increases cerebral blood flow in excess of the metabolic needs in humans. Anesthesiology. 103(2), 258–268.CrossRefGoogle ScholarPubMed
Langsjo, JW, Salmi, E, Kaisti, KK, Aalto, S, Hinkka, S, Aantaa, R, et al. (2004). Effects of subanesthetic ketamine on regional cerebral glucose metabolism in humans. Anesthesiology. 100(5), 1065–1071.CrossRefGoogle ScholarPubMed
Apkarian, AV, Bushnell, MC, Treede, RD, & Zubieta, JK. (2005). Human brain mechanisms of pain perception and regulation in health and disease. Eur. J. Pain. 9(4), 463–484.CrossRefGoogle ScholarPubMed
Cole, LJ, Farrell, MJ, Duff, EP, Barber, JB, Egan, GF, & Gibson, SJ. (2006). Pain sensitivity and fMRI pain-related brain activity in Alzheimer's disease. Brain. 129(Pt 11), 2957–2965.CrossRefGoogle ScholarPubMed
Davis, KD, Kwan, CL, Crawley, AP, & Mikulis, DJ. (1998). Event-related fMRI of pain: Entering a new era in imaging pain. Neuroreport. 9(13), 3019–3023.CrossRefGoogle ScholarPubMed
Peyron, R, Laurent, B, & Garcia-Larrea, L. (2000). Functional imaging of brain responses to pain. A review and meta-analysis. Neurophysiol. Clin. 30(5), 263–288.CrossRefGoogle Scholar
Owen, DG, Bureau, Y, Thomas, AW, Prato, FS, & St. Lawrence, KS. (2008). Quantification of pain-induced changes in cerebral blood flow by perfusion MRI. Pain. 136(1–2), 85–96.CrossRefGoogle ScholarPubMed
Geha, PY, & Apkarian, AV.Brain imaging findings in neuropathic pain. (2005). Curr. Pain Headache Rep. 9(3), 184–188.CrossRefGoogle ScholarPubMed
Moisset, X, & Bouhassira, D. (2007). Brain imaging of neuropathic pain. Neuroimage. 37(Suppl 1), S80–S88.CrossRefGoogle ScholarPubMed
Meyer-Lindenberg, A, & Weinberger, DR. (2006). Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat. Rev. Neurosci. 7(10), 818–827.CrossRefGoogle ScholarPubMed
Meyer-Lindenberg, A, & Zink, CF. (2007). Imaging genetics for neuropsychiatric disorders. Child Adolesc. Psychiatr. Clin. N. Am. 16(3), 581–597.CrossRefGoogle ScholarPubMed
Hariri, AR, Drabant, EM, Munoz, KE, Kolachana, BS, Mattay, VS, Egan, MF, et al. (2005). A susceptibility gene for affective disorders and the response of the human amygdala. Arch. Gen. Psychiatry. 62(2), 146–152.CrossRefGoogle ScholarPubMed
Hariri, AR, Mattay, VS, Tessitore, A, Kolachana, B, Fera, F, Goldman, D, et al. (2002). Serotonin transporter genetic variation and the response of the human amygdala. Science. 297(5580), 400–403.CrossRefGoogle ScholarPubMed
Hariri, AR, & Weinberger, DR. (2003). Functional neuroimaging of genetic variation in serotonergic neurotransmission. Genes Brain Behav. 2(6), 341–349.CrossRefGoogle ScholarPubMed
Roiser, JP, Martino, B, Tan, GC, Kumaran, D, Seymour, B, Wood, NW, et al. (2009). A genetically mediated bias in decision making driven by failure of amygdala control. J. Neurosci. 29(18), 5985–5991.CrossRefGoogle ScholarPubMed
Dannlowski, U, Ohrmann, P, Bauer, J, Kugel, H, Baune, BT, Hohoff, C, et al. (2007). Serotonergic genes modulate amygdala activity in major depression. Genes Brain Behav. 6(7), 672–676.CrossRefGoogle ScholarPubMed
Munafo, MR, Brown, SM, & Hariri, AR. (2008). Serotonin transporter (5-HTTLPR) genotype and amygdala activation: A meta-analysis. Biol. Psychiatry. 63(9), 852–857.CrossRefGoogle ScholarPubMed
Surguladze, SA, Elkin, A, Ecker, C, Kalidindi, S, Corsico, A, Giampietro, V, et al. (2008). Genetic variation in the serotonin transporter modulates neural system-wide response to fearful faces. Genes Brain Behav. 7(5), 543–551.CrossRefGoogle ScholarPubMed
Meyer-Lindenberg, A, Nichols, T, Callicott, JH, Ding, J, Kolachana, B, Buckholtz, J, et al. (2006). Impact of complex genetic variation in COMT on human brain function. Mol. Psychiatry. 11(9), 867–877, 797.CrossRefGoogle ScholarPubMed
Tan, HY, Chen, Q, Goldberg, TE, Mattay, VS, Meyer-Lindenberg, A, Weinberger, DR, et al. (2007). Catechol-O-methyltransferase Val158Met modulation of prefrontal-parietal-striatal brain systems during arithmetic and temporal transformations in working memory. J. Neurosci. 27(49), 13393–13401.CrossRefGoogle ScholarPubMed
Egan, MF, Goldberg, TE, Kolachana, BS, Callicott, JH, Mazzanti, CM, Straub, RE, et al. (2001). Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc. Natl. Acad. Sci. U. S. A. 98(12), 6917–6922.CrossRefGoogle ScholarPubMed
Mattay, VS, Goldberg, TE, Fera, F, Hariri, AR, Tessitore, A, Egan, MF, et al. (2003). Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine. Proc. Natl. Acad. Sci. U. S. A. 100(10), 6186–6191.CrossRefGoogle ScholarPubMed
Blasi, G, Mattay, VS, Bertolino, A, Elvevag, B, Callicott, JH, Das, S, et al. (2005). Effect of catechol-O-methyltransferase val158met genotype on attentional control. J. Neurosci. 25(20), 5038–5045.CrossRefGoogle ScholarPubMed
Tan, HY, Chen, Q, Sust, S, Buckholtz, JW, Meyers, JD, Egan, MF, et al. (2007). Epistasis between catechol-O-methyltransferase and type II metabotropic glutamate receptor 3 genes on working memory brain function. Proc. Natl. Acad. Sci. U. S. A. 104(30), 12536–12541.CrossRefGoogle ScholarPubMed
Buckholtz, JW, Sust, S, Tan, HY, Mattay, VS, Straub, RE, Meyer-Lindenberg, A, et al. (2007). fMRI evidence for functional epistasis between COMT and RGS4. Mol. Psychiatry. 12(10), 893–895, 885.CrossRefGoogle ScholarPubMed
Tan, HY, Nicodemus, KK, Chen, Q, Li, Z, Brooke, JK, Honea, R, et al. (2008). Genetic variation in AKT1 is linked to dopamine-associated prefrontal cortical structure and function in humans. J. Clin. Invest. 118(6), 2200–2208.Google ScholarPubMed
Bertolino, A, Caforio, G, Blasi, G, Candia, M, Latorre, V, Petruzzella, V, et al. (2004). Interaction of COMT (Val(108/158)Met) genotype and olanzapine treatment on prefrontal cortical function in patients with schizophrenia. Am. J. Psychiatry. 161(10), 1798–1805.CrossRefGoogle Scholar
Glahn, DC, Ragland, JD, Abramoff, A, Barrett, J, Laird, AR, Bearden, CE, et al. (2005). Beyond hypofrontality: A quantitative meta-analysis of functional neuroimaging studies of working memory in schizophrenia. Hum. Brain Mapping. 25(1), 60–69.CrossRefGoogle Scholar
Davidson, RJ, Irwin, W, Anderle, MJ, & Kalin, NH. (2003). The neural substrates of affective processing in depressed patients treated with venlafaxine. Am. J. Psychiatry. 160(1), 64–75.CrossRefGoogle ScholarPubMed
Surguladze, S, Brammer, MJ, Keedwell, P, Giampietro, V, Young, AW, Travis, MJ, et al. (2005). A differential pattern of neural response toward sad versus happy facial expressions in major depressive disorder. Biol. Psychiatry. 57(3), 201–209.CrossRefGoogle ScholarPubMed
Chen, CH, Lennox, B, Jacob, R, Calder, A, Lupson, V, Bisbrown-Chippendale, R, et al. (2006). Explicit and implicit facial affect recognition in manic and depressed states of bipolar disorder: A functional magnetic resonance imaging study. Biol. Psychiatry. 59(1), 31–39.CrossRefGoogle ScholarPubMed
Ford, JM, Roach, BJ, Jorgensen, KW, Turner, JA, Brown, GG, Notestine, R, et al. (2009). Tuning in to the voices: A multisite fMRI study of auditory hallucinations. Schizophr. Bull. 35(1), 58–66.CrossRefGoogle ScholarPubMed
Potkin, SG, & Ford, JM. (2009). Widespread cortical dysfunction in schizophrenia: The FBIRN imaging consortium. Schizophr. Bull. 35(1), 15–18.CrossRefGoogle ScholarPubMed
Haller, S, & Bartsch, AJ. (2009). Pitfalls in fMRI. Eur. Radiol. 19(11), 2689–2706.CrossRefGoogle ScholarPubMed
Iannetti, GD, & Wise, RG. (2007). BOLD functional MRI in disease and pharmacological studies: Room for improvement? Magn. Reson. Imaging. 25(6), 978–988.CrossRefGoogle Scholar
Suckling, J, Ohlssen, D, Andrew, C, Johnson, G, Williams, SC, Graves, M, et al. (2008). Components of variance in a multicentre functional MRI study and implications for calculation of statistical power. Hum. Brain Mapping. 29(10), 1111–1122.CrossRefGoogle Scholar
Desmond, JE, & Glover, GH. (2002). Estimating sample size in functional MRI (fMRI) neuroimaging studies: Statistical power analyses. J. Neurosci. Methods. 118(2), 115–128.CrossRefGoogle ScholarPubMed
Mumford, JA, & Nichols, TE. (2008). Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation. Neuroimage. 39(1), 261–268.CrossRefGoogle Scholar
Murphy, K, & Garavan, H. (2005). Deriving the optimal number of events for an event-related fMRI study based on the spatial extent of activation. Neuroimage. 27(4), 771–777.CrossRefGoogle Scholar
Friedman, L, & Glover, GH. (2006). Report on a multicenter fMRI quality assurance protocol. J. Magn. Reson. Imaging. 23(6), 827–839.CrossRefGoogle ScholarPubMed
Friedman, L, Stern, H, Brown, GG, Mathalon, DH, Turner, J, Glover, GH, et al. (2008). Test-retest and between-site reliability in a multicenter fMRI study. Hum. Brain Mapping. 29(8), 958–972.CrossRefGoogle Scholar
Miller, G. (2009). Alzheimer's biomarker initiative hits its stride. Science. 326(5951), 386–389.CrossRefGoogle ScholarPubMed
Landau, SM, Harvey, D, Madison, CM, Koeppe, RA, Reiman, EM, Foster, NL, et al. (2009). Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol. Aging. Aug. 4. E-pub ahead of print.Google Scholar
Hua, X, Lee, S, Yanovsky, I, Leow, AD, Chou, YY, Ho, AJ, et al. (2009). Optimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry: An ADNI study of 515 subjects. Neuroimage. 48(4), 668–681.CrossRefGoogle ScholarPubMed
Agdeppa, ED, Kepe, V, Liu, J, Flores-Torres, S, Satyamurthy, N, Petric, A, et al. (2001). Binding characteristics of radiofluorinated 6-dialkylamino-2-naphthylethylidene derivatives as positron emission tomography imaging probes for beta-amyloid plaques in Alzheimer's disease. J. Neurosci. 21(24), RC189.CrossRefGoogle ScholarPubMed
Verhoeff, NP, Wilson, AA, Takeshita, S, Trop, L, Hussey, D, Singh, K, et al. (2004). In-vivo imaging of Alzheimer disease beta-amyloid with [11C]SB-13 PET. Am. J. Geriatr. Psychiatry. 12(6), 584–595.Google Scholar
Choi, SR, Golding, G, Zhuang, Z, Zhang, W, Lim, N, Hefti, F, et al. (2009). Preclinical properties of 18F-AV-45: A PET agent for Abeta plaques in the brain. J. Nucl. Med. 50(11), 1887–1894.CrossRefGoogle Scholar
Okello, A, Koivunen, J, Edison, P, Archer, HA, Turkheimer, FE, Nagren, K, et al. (2009). Conversion of amyloid positive and negative MCI to AD over 3 years: An 11C-PIB PET study. Neurology. 73(10), 754–760.CrossRefGoogle ScholarPubMed
Buyse, M, Thirion, P, Carlson, RW, Burzykowski, T, Molenberghs, G, & Piedbois, P. (2000). Relation between tumour response to first-line chemotherapy and survival in advanced colorectal cancer: A meta-analysis. Meta-Analysis Group in Cancer. Lancet. 356(9227), 373–378.CrossRefGoogle Scholar
El-Maraghi, RH, & Eisenhauer, EA. (2008). Review of phase II trial designs used in studies of molecular targeted agents: Outcomes and predictors of success in phase III. J. Clin. Oncol. 26(8), 1346–1354.CrossRefGoogle ScholarPubMed
Goffin, J, Baral, S, Tu, D, Nomikos, D, & Seymour, L. (2005). Objective responses in patients with malignant melanoma or renal cell cancer in early clinical studies do not predict regulatory approval. Clin. Cancer Res. 11(16), 5928–5934.CrossRefGoogle Scholar
Paesmans, M, Sculier, JP, Libert, P, Bureau, G, Dabouis, G, Thiriaux, J, et al. (1997). Response to chemotherapy has predictive value for further survival of patients with advanced non-small cell lung cancer: 10 years experience of the European Lung Cancer Working Party. Eur. J. Cancer. 33(14), 2326–2332.CrossRefGoogle ScholarPubMed
Therasse, P, Arbuck, SG, Eisenhauer, EA, Wanders, J, Kaplan, RS, Rubinstein, L, et al. (2000). New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J. Natl. Cancer Inst. 92(3), 205–216.CrossRefGoogle ScholarPubMed
Workman, P, Aboagye, EO, Chung, YL, Griffiths, JR, Hart, R, Leach, MO, et al. (2006). Minimally invasive pharmacokinetic and pharmacodynamic technologies in hypothesis-testing clinical trials of innovative therapies. J. Natl. Cancer Inst. 98(9), 580–598.CrossRefGoogle ScholarPubMed
Schwarz, AJ, Maisey, NR, Collins, DJ, Cunningham, D, Huddart, R, & Leach, MO. (2002). Early in vivo detection of metabolic response: A pilot study of 1H MR spectroscopy in extracranial lymphoma and germ cell tumours. Br. J. Radiol. 75(900), 959–966.CrossRefGoogle ScholarPubMed
Meisamy, S, Bolan, PJ, Baker, EH, Bliss, RL, Gulbahce, E, Everson, LI, et al. (2004). Neoadjuvant chemotherapy of locally advanced breast cancer: Predicting response with in vivo (1)H MR spectroscopy – a pilot study at 4 T. Radiology. 233(2), 424–431.CrossRefGoogle ScholarPubMed
O'Connor, JP, Jackson, A, Parker, GJ, & Jayson, GC. (2007). DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents. Br. J. Cancer. 96(2), 189–195.CrossRefGoogle ScholarPubMed
Hamstra, DA, Galban, CJ, Meyer, CR, Johnson, TD, Sundgren, PC, Tsien, C, et al. (2008). Functional diffusion map as an early imaging biomarker for high-grade glioma: Correlation with conventional radiologic response and overall survival. J. Clin. Oncol. 26(20), 3387–3394.CrossRefGoogle ScholarPubMed
Padhani, AR, & Leach, MO. (2005). Antivascular cancer treatments: Functional assessments by dynamic contrast-enhanced magnetic resonance imaging. Abdom. Imaging. 30(3), 324–341.CrossRefGoogle ScholarPubMed
Wahl, RL, Jacene, H, Kasamon, Y, & Lodge, MA. (2009). From RECIST to PERCIST: Evolving considerations for PET response criteria in solid tumors. J. Nucl. Med. 50(Suppl 1), 122S–150S.CrossRefGoogle ScholarPubMed
Hayes, C, Padhani, AR, & Leach, MO. (2002). Assessing changes in tumour vascular function using dynamic contrast-enhanced magnetic resonance imaging. NMR Biomed. 15(2), 154–163.CrossRefGoogle ScholarPubMed
Padhani, AR. (2003). MRI for assessing antivascular cancer treatments. Br. J. Radiol. 76 Spec No 1, S60–S80.CrossRefGoogle ScholarPubMed
Miller, JC, Pien, HH, Sahani, D, Sorensen, AG, & Thrall, JH. (2005). Imaging angiogenesis: Applications and potential for drug development. J. Natl. Cancer Inst. 97(3), 172–187.CrossRefGoogle ScholarPubMed
Folkman, J. (1971). Tumor angiogenesis: Therapeutic implications. N. Engl. J. Med. 285(21), 1182–1186.Google ScholarPubMed
Folkman, J. (1985). Tumor angiogenesis. Adv. Cancer Res. 43, 175–203.CrossRefGoogle ScholarPubMed
Kerbel, RS. (2008). Tumor angiogenesis. N. Engl. J. Med. 358(19), 2039–2049.CrossRefGoogle ScholarPubMed
Jackson, A, Buckley, DL, & Parker, GJM (eds.). (2005). Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Oncology. Berlin: Springer-Verlag.CrossRefGoogle Scholar
Tofts, PS. (1997). Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J. Magn. Reson. Imaging. 7(1), 91–101.CrossRefGoogle ScholarPubMed
Taylor, JS, Tofts, PS, Port, R, Evelhoch, JL, Knopp, M, Reddick, WE, et al. (1999). MR imaging of tumor microcirculation: Promise for the new millennium. J. Magn. Reson. Imaging. 10(6), 903–907.3.0.CO;2-A>CrossRefGoogle ScholarPubMed
Tofts, PS, Brix, G, Buckley, DL, Evelhoch, JL, Henderson, E, Knopp, MV, et al. (1999). Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusible tracer: Standardized quantities and symbols. J. Magn. Reson. Imaging. 10(3), 223–232.3.0.CO;2-S>CrossRefGoogle Scholar
Parker, GJ, Suckling, J, Tanner, SF, Padhani, AR, Revell, PB, Husband, JE, et al. (1997). Probing tumor microvascularity by measurement, analysis and display of contrast agent uptake kinetics. J. Magn. Reson. Imaging. 7(3), 564–574.CrossRefGoogle ScholarPubMed
Li, KL, Henry, RG, Wilmes, LJ, Gibbs, J, Zhu, X, Lu, Y, et al. (2007). Kinetic assessment of breast tumors using high spatial resolution signal enhancement ratio (SER) imaging. Magn. Reson. Med. 58(3), 572–581.CrossRefGoogle ScholarPubMed
Wilmes, LJ, Pallavicini, MG, Fleming, LM, Gibbs, J, Wang, D, Li, KL, et al. (2007). AG-013736, a novel inhibitor of VEGF receptor tyrosine kinases, inhibits breast cancer growth and decreases vascular permeability as detected by dynamic contrast-enhanced magnetic resonance imaging. Magn. Reson. Imaging. 25(3), 319–327.CrossRefGoogle ScholarPubMed
Hylton, N. (2006). Dynamic contrast-enhanced magnetic resonance imaging as an imaging biomarker. J. Clin. Oncol. 24(20), 3293–3298.CrossRefGoogle ScholarPubMed
Leach, MO, Brindle, KM, Evelhoch, JL, Griffiths, JR, Horsman, MR, Jackson, A, et al. (2003). Assessment of antiangiogenic and antivascular therapeutics using MRI: Recommendations for appropriate methodology for clinical trials. Br. J. Radiol. 76 Spec No. 1, S87–S91.CrossRefGoogle Scholar
Leach, MO, Brindle, KM, Evelhoch, JL, Griffiths, JR, Horsman, MR, Jackson, A, et al. (2005). The assessment of antiangiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: Issues and recommendations. Br. J. Cancer. 92(9), 1599–1610.CrossRefGoogle ScholarPubMed
Robinson, SP, McIntyre, DJ, Checkley, D, Tessier, JJ, Howe, FA, Griffiths, JR, et al. (2003). Tumour dose response to the antivascular agent ZD6126 assessed by magnetic resonance imaging. Br. J. Cancer. 88(10), 1592–1597.CrossRefGoogle ScholarPubMed
Roberts, C, Issa, B, Stone, A, Jackson, A, Waterton, JC, & Parker, GJ. (2006). Comparative study into the robustness of compartmental modeling and model-free analysis in DCE-MRI studies. J. Magn. Reson. Imaging. 23(4), 554–563.CrossRefGoogle ScholarPubMed
Evelhoch, JL. (1999). Key factors in the acquisition of contrast kinetic data for oncology. J. Magn. Reson. Imaging. 10(3), 254–259.3.0.CO;2-9>CrossRefGoogle ScholarPubMed
Padhani, AR, & Husband, JE. (2001). Dynamic contrast-enhanced MRI studies in oncology with an emphasis on quantification, validation and human studies. Clin. Radiol. 56(8), 607–620.CrossRefGoogle ScholarPubMed
Galbraith, SM, Lodge, MA, Taylor, NJ, Rustin, GJ, Bentzen, S, Stirling, JJ, et al. (2002). Reproducibility of dynamic contrast-enhanced MRI in human muscle and tumours: Comparison of quantitative and semi-quantitative analysis. NMR Biomed. 15(2), 132–142.CrossRefGoogle ScholarPubMed
Padhani, AR, Hayes, C, Landau, S, & Leach, MO. (2002). Reproducibility of quantitative dynamic MRI of normal human tissues. NMR Biomed. 15(2), 143–153.CrossRefGoogle ScholarPubMed
Ashton, E, Raunig, D, Ng, C, Kelcz, F, McShane, T, & Evelhoch, J. (2008). Scan-rescan variability in perfusion assessment of tumors in MRI using both model and data-derived arterial input functions. J. Magn. Reson. Imaging. 28(3), 791–796.CrossRefGoogle ScholarPubMed
Galbraith, SM, Rustin, GJ, Lodge, MA, Taylor, NJ, Stirling, JJ, Jameson, M, et al. (2002). Effects of 5,6-dimethylxanthenone-4-acetic acid on human tumor microcirculation assessed by dynamic contrast-enhanced magnetic resonance imaging. J. Clin. Oncol. 20(18), 3826–3840.CrossRefGoogle ScholarPubMed
Lankester, KJ, Taylor, NJ, Stirling, JJ, Boxall, J, D'Arcy, JA, Leach, MO, et al. (2005). Effects of platinum/taxane based chemotherapy on acute perfusion in human pelvic tumours measured by dynamic MRI. Br. J. Cancer. 93(9), 979–985.CrossRefGoogle ScholarPubMed
O'Donnell, A, Padhani, A, Hayes, C, Kakkar, AJ, Leach, M, Trigo, JM, et al. (2005). A phase I study of the angiogenesis inhibitor SU5416 (semaxanib) in solid tumours, incorporating dynamic contrast MR pharmacodynamic end points. Br. J. Cancer. 93(8), 876–883.CrossRefGoogle ScholarPubMed
McPhail, LD, Chung, YL, Madhu, B, Clark, S, Griffiths, JR, Kelland, LR, et al. (2005). Tumor dose response to the vascular disrupting agent, 5,6-dimethylxanthenone-4-acetic acid, using in vivo magnetic resonance spectroscopy. Clin. Cancer Res. 11(10), 3705–3713.CrossRefGoogle ScholarPubMed
McPhail, LD, McIntyre, DJ, Ludwig, C, Kestell, P, Griffiths, JR, Kelland, LR, et al. (2006). Rat tumor response to the vascular-disrupting agent 5,6-dimethylxanthenone-4-acetic acid as measured by dynamic contrast-enhanced magnetic resonance imaging, plasma 5-hydroxyindoleacetic acid levels, and tumor necrosis. Neoplasia. 8(3), 199–206.CrossRefGoogle ScholarPubMed
Checkley, D, Tessier, JJ, Kendrew, J, Waterton, JC, & Wedge, SR. (2003). Use of dynamic contrast-enhanced MRI to evaluate acute treatment with ZD6474, a VEGF signalling inhibitor, in PC-3 prostate tumours. Br. J. Cancer. 89(10), 1889–1895.CrossRefGoogle ScholarPubMed
Marzola, P, Degrassi, A, Calderan, L, Farace, P, Crescimanno, C, Nicolato, E, et al. (2004). In vivo assessment of antiangiogenic activity of SU6668 in an experimental colon carcinoma model. Clin. Cancer Res. 10(2), 739–750.CrossRefGoogle Scholar
Marzola, P, Degrassi, A, Calderan, L, Farace, P, Nicolato, E, Crescimanno, C, et al. (2005). Early antiangiogenic activity of SU11248 evaluated in vivo by dynamic contrast-enhanced magnetic resonance imaging in an experimental model of colon carcinoma. Clin. Cancer Res. 11(16), 5827–5832.CrossRefGoogle Scholar
Galbraith, SM, Maxwell, RJ, Lodge, MA, Tozer, GM, Wilson, J, Taylor, NJ, et al. (2003). Combretastatin A4 phosphate has tumor antivascular activity in rat and man as demonstrated by dynamic magnetic resonance imaging. J. Clin. Oncol. 21(15), 2831–2842.CrossRefGoogle Scholar
Evelhoch, JL, LoRusso, PM, He, Z, DelProposto, Z, Polin, L, Corbett, TH, et al. (2004). Magnetic resonance imaging measurements of the response of murine and human tumors to the vascular-targeting agent ZD6126. Clin. Cancer Res. 10(11), 3650–3657.CrossRefGoogle ScholarPubMed
Lee, L, Sharma, S, Morgan, B, Allegrini, P, Schnell, C, Brueggen, J, et al. (2006). Biomarkers for assessment of pharmacologic activity for a vascular endothelial growth factor (VEGF) receptor inhibitor, PTK787/ZK 222584 (PTK/ZK): Translation of biological activity in a mouse melanoma metastasis model to phase I studies in patients with advanced colorectal cancer with liver metastases. Cancer Chemother. Pharmacol. 57(6), 761–771.CrossRefGoogle Scholar
Rudin, M, McSheehy, PM, Allegrini, PR, Rausch, M, Baumann, D, Becquet, M, et al. (2005). PTK787/ZK222584, a tyrosine kinase inhibitor of vascular endothelial growth factor receptor, reduces uptake of the contrast agent GdDOTA by murine orthotopic B16/BL6 melanoma tumours and inhibits their growth in vivo. NMR Biomed. 18(5), 308–321.CrossRefGoogle ScholarPubMed
Morgan, B, Thomas, AL, Drevs, J, Hennig, J, Buchert, M, Jivan, A, et al. (2003). Dynamic contrast-enhanced magnetic resonance imaging as a biomarker for the pharmacological response of PTK787/ZK 222584, an inhibitor of the vascular endothelial growth factor receptor tyrosine kinases, in patients with advanced colorectal cancer and liver metastases: Results from two phase I studies. J. Clin. Oncol. 21(21), 3955–3964.CrossRefGoogle ScholarPubMed
Chen, K, Cai, W, Li, ZB, Wang, H, & Chen, X. (2009). Quantitative PET imaging of VEGF receptor expression. Mol. Imaging Biol. 11(1), 15–22.CrossRefGoogle ScholarPubMed
Levashova, Z, Backer, M, Backer, JM, & Blankenberg, FG. (2009). Imaging vascular endothelial growth factor (VEGF) receptors in turpentine-induced sterile thigh abscesses with radiolabeled single-chain VEGF. J. Nucl. Med. 50(12), 2058–2063.CrossRefGoogle ScholarPubMed
Bading, JR, & Shields, AF. (2008). Imaging of cell proliferation: Status and prospects. J. Nucl. Med. 49(Suppl 2), 64S–80S.CrossRefGoogle Scholar
Dowling, C, Bollen, AW, Noworolski, SM, McDermott, MW, Barbaro, NM, Day, MR, et al. (2001). Preoperative proton MR spectroscopic imaging of brain tumors: Correlation with histopathologic analysis of resection specimens. AJNR Am. J. Neuroradiol. 22(4), 604–612.Google ScholarPubMed
Nelson, SJ, Graves, E, Pirzkall, A, Li, X, Antiniw, Chan A, Vigneron, DB, et al. (2002). In vivo molecular imaging for planning radiation therapy of gliomas: An application of 1H MRSI. J. Magn. Reson. Imaging. 16(4), 464–476.CrossRefGoogle ScholarPubMed
Vigneron, D, Bollen, A, McDermott, M, Wald, L, Day, M, Moyher-Noworolski, S, et al. (2001). Three-dimensional magnetic resonance spectroscopic imaging of histologically confirmed brain tumors. Magn. Reson. Imaging. 19(1), 89–101.CrossRefGoogle ScholarPubMed
Kurhanewicz, J, & Vigneron, DB. (2008). Advances in MR spectroscopy of the prostate. Magn. Reson. Imaging Clin. N. Am. 16(4), 697–710, ix–x.CrossRefGoogle ScholarPubMed
Scheenen, TW, Klomp, DW, Roll, SA, Futterer, JJ, Barentsz, JO, & Heerschap, A. (2004). Fast acquisition-weighted three-dimensional proton MR spectroscopic imaging of the human prostate. Magn. Reson. Med. 52(1), 80–88.CrossRefGoogle ScholarPubMed
Jung, JA, Coakley, FV, Vigneron, DB, Swanson, MG, Qayyum, A, Weinberg, V, et al. (2004). Prostate depiction at endorectal MR spectroscopic imaging: Investigation of a standardized evaluation system. Radiology. 233(3), 701–708.CrossRefGoogle ScholarPubMed
Bolan, PJ, Meisamy, S, Baker, EH, Lin, J, Emory, T, Nelson, M, et al. (2003). In vivo quantification of choline compounds in the breast with 1H MR spectroscopy. Magn. Reson. Med. 50(6), 1134–1143.CrossRefGoogle ScholarPubMed
Baik, HM, Su, MY, Yu, H, Mehta, R, & Nalcioglu, O. (2006). Quantification of choline-containing compounds in malignant breast tumors by 1H MR spectroscopy using water as an internal reference at 1.5 T. MAGMA. 19(2), 96–104.CrossRefGoogle ScholarPubMed
Kim, JK, Park, SH, Lee, HM, Lee, YH, Sung, NK, Chung, DS, et al. (2003). In vivo 1H-MRS evaluation of malignant and benign breast diseases. Breast. 12(3), 179–182.CrossRefGoogle ScholarPubMed
Booth, SJ, Pickles, MD, & Turnbull, LW. (2009). In vivo magnetic resonance spectroscopy of gynaecological tumours at 3.0 Tesla. BJOG. 116(2), 300–303.CrossRefGoogle ScholarPubMed
Wang, CK, Li, CW, Hsieh, TJ, Chien, SH, Liu, GC, & Tsai, KB. (2004). Characterization of bone and soft-tissue tumors with in vivo 1H MR spectroscopy: Initial results. Radiology. 232(2), 599–605.CrossRefGoogle ScholarPubMed
Allen, JR, Prost, RW, Griffith, OW, Erickson, SJ, & Erickson, BA. (2001). In vivo proton (H1) magnetic resonance spectroscopy for cervical carcinoma. Am. J. Clin. Oncol. 24(5), 522–529.CrossRefGoogle ScholarPubMed
Baek, HM, Chen, JH, Nalcioglu, O, & Su, MY. (2008). Proton MR spectroscopy for monitoring early treatment response of breast cancer to neo-adjuvant chemotherapy. Ann. Oncol. 19(5), 1022–1024.CrossRefGoogle ScholarPubMed
Hsieh, TJ, Li, CW, Chuang, HY, Liu, GC, & Wang, CK. (2008). Longitudinally monitoring chemotherapy effect of malignant musculoskeletal tumors with in vivo proton magnetic resonance spectroscopy: An initial experience. J. Comput. Assist. Tomogr. 32(6), 987–994.CrossRefGoogle ScholarPubMed
Huang, MQ, Nelson, DS, Pickup, S, Qiao, H, Delikatny, EJ, Poptani, H, et al. (2007). In vivo monitoring response to chemotherapy of human diffuse large B-cell lymphoma xenografts in SCID mice by 1H and 31P MRS. Acad. Radiol. 14(12), 1531–1539.CrossRefGoogle ScholarPubMed
Madhu, B, Waterton, JC, Griffiths, JR, Ryan, AJ, & Robinson, SP. (2006). The response of RIF-1 fibrosarcomas to the vascular-disrupting agent ZD6126 assessed by in vivo and ex vivo 1H magnetic resonance spectroscopy. Neoplasia. 8(7), 560–567.CrossRefGoogle ScholarPubMed
Evelhoch, J, Garwood, M, Vigneron, D, Knopp, M, Sullivan, D, Menkens, A, et al. (2005). Expanding the use of magnetic resonance in the assessment of tumor response to therapy: Workshop report. Cancer Res. 65(16), 7041–7044.CrossRefGoogle ScholarPubMed
Negendank, W, Li, CW, Padavic-Shaller, K, Murphy-Boesch, J, & Brown, TR. (1996). Phospholipid metabolites in 1H-decoupled 31P MRS in vivo in human cancer: Implications for experimental models and clinical studies. Anticancer Res. 16(3B), 1539–1544.Google ScholarPubMed
Arias-Mendoza, F, Zakian, K, Schwartz, A, Howe, FA, Koutcher, JA, Leach, MO, et al. (2004). Methodological standardization for a multi-institutional in vivo trial of localized 31P MR spectroscopy in human cancer research. In vitro and normal volunteer studies. NMR Biomed. 17(6), 382–391.CrossRefGoogle ScholarPubMed
Arias-Mendoza, F, Payne, GS, Zakian, KL, Schwarz, AJ, Stubbs, M, Stoyanova, R, et al. (2006). In vivo 31P MR spectral patterns and reproducibility in cancer patients studied in a multi-institutional trial. NMR Biomed. 19(4), 504–512.CrossRefGoogle Scholar
Dzik-Jurasz, AS, Collins, DJ, Leach, MO, & Rowland, IJ. (2000). Gallbladder localization of (19)F MRS catabolite signals in patients receiving bolus and protracted venous infusional 5-fluorouracil. Magn. Reson. Med. 44(4), 516–520.3.0.CO;2-P>CrossRefGoogle Scholar
Wolf, W, Presant, CA, & Waluch, V. (2000). 19F-MRS studies of fluorinated drugs in humans. Adv. Drug Deliv. Rev. 41(1), 55–74.CrossRefGoogle ScholarPubMed
Klomp, DW, Laarhoven, HW, Kentgens, AP, & Heerschap, A. (2003). Optimization of localized 19F magnetic resonance spectroscopy for the detection of fluorinated drugs in the human liver. Magn. Reson. Med. 50(2), 303–308.CrossRefGoogle ScholarPubMed
Kamm, YJ, Heerschap, A, Bergh, EJ, & Wagener, DJ. (2004). 19F-magnetic resonance spectroscopy in patients with liver metastases of colorectal cancer treated with 5-fluorouracil. Anticancer Drugs. 15(3), 229–233.CrossRefGoogle ScholarPubMed
Laarhoven, HW, Punt, CJ, Kamm, YJ, & Heerschap, A. (2005). Monitoring fluoropyrimidine metabolism in solid tumors with in vivo (19)F magnetic resonance spectroscopy. Crit. Rev. Oncol. Hematol. 56(3), 321–343.CrossRefGoogle Scholar
Klomp, D, Laarhoven, H, Scheenen, T, Kamm, Y, & Heerschap, A. (2007). Quantitative 19F MR spectroscopy at 3 T to detect heterogeneous capecitabine metabolism in human liver. NMR Biomed. 20(5), 485–492.CrossRefGoogle Scholar
Reid, DG, & Murphy, PS. (2008). Fluorine magnetic resonance in vivo: A powerful tool in the study of drug distribution and metabolism. Drug Discov. Today. 13(11–12), 473–480.CrossRefGoogle Scholar
Mankoff, DA, Link, JM, Linden, HM, Sundararajan, L, & Krohn, KA. (2008). Tumor receptor imaging. J. Nucl. Med. 49(Suppl 2), 149S–63S.CrossRefGoogle Scholar
Linden, HM, Stekhova, SA, Link, JM, Gralow, JR, Livingston, RB, Ellis, GK, et al. (2006). Quantitative fluoroestradiol positron emission tomography imaging predicts response to endocrine treatment in breast cancer. J. Clin. Oncol. 24(18), 2793–2799.CrossRefGoogle ScholarPubMed
Faust, A, Hermann, S, Wagner, S, Haufe, G, Schober, O, Schafers, M, et al. (2009). Molecular imaging of apoptosis in vivo with scintigraphic and optical biomarkers – a status report. Anticancer Agents Med. Chem. 9(9), 968–985.CrossRefGoogle ScholarPubMed
Blankenberg, FG. (2008). In vivo imaging of apoptosis. Cancer Biol. Ther. 7(10), 1525–1532.CrossRefGoogle Scholar
Sanz, J, & Fayad, ZA. (2008). Imaging of atherosclerotic cardiovascular disease. Nature. 451(7181), 953–957.CrossRefGoogle ScholarPubMed
Yuan, C, Kerwin, WS, Yarnykh, VL, Cai, J, Saam, T, Chu, B, et al. (2006). MRI of atherosclerosis in clinical trials. NMR Biomed. 19(6), 636–654.CrossRefGoogle ScholarPubMed
Rudd, JH, Warburton, EA, Fryer, TD, Jones, HA, Clark, JC, Antoun, N, et al. (2002). Imaging atherosclerotic plaque inflammation with [18F]-fluorodeoxyglucose positron emission tomography. Circulation. 105(23), 2708–2711.CrossRefGoogle Scholar
Tawakol, A, Migrino, RQ, Bashian, GG, Bedri, S, Vermylen, D, Cury, RC, et al. (2006). In vivo 18F-fluorodeoxyglucose positron emission tomography imaging provides a noninvasive measure of carotid plaque inflammation in patients. J. Am. Coll. Cardiol. 48(9), 1818–1824.CrossRefGoogle ScholarPubMed
Takaya, N, Cai, J, Ferguson, MS, Yarnykh, VL, Chu, B, Saam, T, et al. (2006). Intra- and interreader reproducibility of magnetic resonance imaging for quantifying the lipid-rich necrotic core is improved with gadolinium contrast enhancement. J. Magn. Reson. Imaging. 24(1), 203–210.CrossRefGoogle ScholarPubMed
Saam, T, Hatsukami, TS, Yarnykh, VL, Hayes, CE, Underhill, H, Chu, B, et al. (2007). Reader and platform reproducibility for quantitative assessment of carotid atherosclerotic plaque using 1.5T Siemens, Philips, and General Electric scanners. J. Magn. Reson. Imaging. 26(2), 344–352.CrossRefGoogle ScholarPubMed
Cai, J, Hatsukami, TS, Ferguson, MS, Kerwin, WS, Saam, T, Chu, B, et al. (2005). In vivo quantitative measurement of intact fibrous cap and lipid-rich necrotic core size in atherosclerotic carotid plaque: Comparison of high-resolution, contrast-enhanced magnetic resonance imaging and histology. Circulation. 112(22), 3437–3444.CrossRefGoogle ScholarPubMed
Chu, B, Zhao, XQ, Saam, T, Yarnykh, VL, Kerwin, WS, Flemming, KD, et al. (2005). Feasibility of in vivo, multicontrast-weighted MR imaging of carotid atherosclerosis for multicenter studies. J. Magn. Reson. Imaging. 21(6), 809–817.CrossRefGoogle ScholarPubMed
Kerwin, WS, O'Brien, KD, Ferguson, MS, Polissar, N, Hatsukami, TS, & Yuan, C. (2006). Inflammation in carotid atherosclerotic plaque: A dynamic contrast-enhanced MR imaging study. Radiology. 241(2), 459–468.CrossRefGoogle ScholarPubMed
Rosen, BD, Fernandes, V, McClelland, RL, Carr, JJ, Detrano, R, Bluemke, DA, et al. (2009). Relationship between baseline coronary calcium score and demonstration of coronary artery stenoses during follow-up MESA (Multi-Ethnic Study of Atherosclerosis). JACC Cardiovasc. Imaging. 2(10), 1175–1183.CrossRefGoogle ScholarPubMed
Tahara, N, Kai, H, Ishibashi, M, Nakaura, H, Kaida, H, Baba, K, et al. (2006). Simvastatin attenuates plaque inflammation: Evaluation by fluorodeoxyglucose positron emission tomography. J. Am. Coll. Cardiol. 48(9), 1825–1831.CrossRefGoogle ScholarPubMed
Corti, R, Fayad, ZA, Fuster, V, Worthley, SG, Helft, G, Chesebro, J, et al. (2001). Effects of lipid-lowering by simvastatin on human atherosclerotic lesions: A longitudinal study by high-resolution, noninvasive magnetic resonance imaging. Circulation. 104(3), 249–252.CrossRefGoogle ScholarPubMed
Corti, R, Fuster, V, Fayad, ZA, Worthley, SG, Helft, G, Smith, D, et al. (2002). Lipid lowering by simvastatin induces regression of human atherosclerotic lesions: Two years' follow-up by high-resolution noninvasive magnetic resonance imaging. Circulation. 106(23), 2884–2887.CrossRefGoogle ScholarPubMed
Corti, R, Fuster, V, Fayad, ZA, Worthley, SG, Helft, G, Chaplin, WF, et al. (2005). Effects of aggressive versus conventional lipid-lowering therapy by simvastatin on human atherosclerotic lesions: A prospective, randomized, double-blind trial with high-resolution magnetic resonance imaging. J. Am. Coll. Cardiol. 46(1), 106–112.CrossRefGoogle ScholarPubMed
Rudd, JH, Machac, J, & Fayad, ZA. (2007). Simvastatin and plaque inflammation. J. Am. Coll. Cardiol. 49(19), 1991; author reply 1992.CrossRefGoogle ScholarPubMed
Underhill, HR, Yuan, C, Zhao, XQ, Kraiss, LW, Parker, DL, Saam, T, et al. (2008). Effect of rosuvastatin therapy on carotid plaque morphology and composition in moderately hypercholesterolemic patients: A high-resolution magnetic resonance imaging trial. Am. Heart J. 155(3), 584.e1–e8.CrossRefGoogle ScholarPubMed
Saam, T, Kerwin, WS, Chu, B, Cai, J, Kampschulte, A, Hatsukami, TS, et al. (2005). Sample size calculation for clinical trials using magnetic resonance imaging for the quantitative assessment of carotid atherosclerosis. J. Cardiovasc. Magn. Reson. 7(5), 799–808.CrossRefGoogle ScholarPubMed
Rudd, JH, Myers, KS, Bansilal, S, Machac, J, Pinto, CA, Tong, C, et al. (2008). Atherosclerosis inflammation imaging with 18F-FDG PET: Carotid, iliac, and femoral uptake reproducibility, quantification methods, and recommendations. J Nucl. Med. 49(6), 871–878.CrossRefGoogle ScholarPubMed
Wong, DF, Tauscher, J, & Grunder, G. (2009). The role of imaging in proof of concept for CNS drug discovery and development. Neuropsychopharmacology. 34(1), 187–203.CrossRefGoogle ScholarPubMed
Takaya, N, Yuan, C, Chu, B, Saam, T, Underhill, H, Cai, J, et al. (2006). Association between carotid plaque characteristics and subsequent ischemic cerebrovascular events: A prospective assessment with MRI–initial results. Stroke. 37(3), 818–823.CrossRefGoogle ScholarPubMed
Rominger, A, Saam, T, Wolpers, S, Cyran, CC, Schmidt, M, Foerster, S, et al. (2009). 18F-FDG PET/CT identifies patients at risk for future vascular events in an otherwise asymptomatic cohort with neoplastic disease. J. Nucl. Med. 50(10), 1611–1620.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×