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Role of Molecular Imaging in the Era of Personalized Medicine: A Review

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Functional Imaging in Oncology

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Abstract

Molecular imaging allows the visual representation, characterization, and quantification of biological processes at the cellular and subcellular levels within intact living organisms. In oncology, it can be used to depict the abnormal molecules as well as the aberrant interactions of altered molecules on which cancers depend.

Knowledge of the fundamental tissue, cellular, genomic, and molecular changes that form the hallmarks of cancer has led to the introduction of cancer therapies aimed at specific molecular targets. This chapter will illustrate why molecular imaging is an invaluable tool for developing and facilitating the appropriate use of such targeted treatments as well as conventional cancer treatments. Alone or combined with anatomic imaging, it is destined to play an increasingly important role in all stages of cancer care, from initial cancer detection through treatment and follow-up.

Please note: Dr. Donati’s work was supported by the Swiss National Science Foundation and the Swiss Radiologic Society. The authors have no other funding support and no conflicts of interest to disclose.

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Abbreviations

ADC:

Apparent diffusion coefficient

BOLD:

Blood oxygen level dependent

11C:

Carbon-11

13C:

Carbon-13

CALGB:

Cancer and leukemia group B

CT:

Computed tomography

Cu:

Copper-60/copper-64

DCE-MRI:

Dynamic contrast-enhanced MRI

DNP:

Dynamic nuclear polarization

DW-MRI:

Diffusion-weighted MRI (also referred to as DWI)

EGFR:

Epidermal growth factor receptor

EPR:

Enhanced permeability and retention

F:

Fluorine-18

FDG:

Fluorodeoxyglucose

FET:

Fluoroethyltyrosine

FLT:

Fluoro-l-thymidine

FMISO:

Fluoro-misonidazole [60/64Cu]copper(II)-diactyl-bis(N4-methylthiosemicarbazone (60/64Cu-ATSM)

HER2:

Human epidermal growth factor receptor 2

ICG:

Indocyanine green

Ktrans :

Volume transfer constant

MR/PET:

Magnetic resonance/PET

MRI:

Magnetic resonance imaging

MRSI:

Magnetic resonance spectroscopic imaging

PET:

Positron emission tomography

SPECT:

Single-photon emission computed tomography

References

  1. Massoud TF, Gambhir SS. Molecular imaging in living subjects: seeing fundamental biological processes in a new light. Genes Dev. 2003;17(5):545–80.

    Article  PubMed  CAS  Google Scholar 

  2. Kircher MF, et al. Noninvasive cell-tracking methods. Nat Rev Clin Oncol. 2011;8(11):677–88.

    Google Scholar 

  3. Kircher MF, Willmann JK. Molecular body imaging: MR imaging, CT, and US. Part II. Applications. Radiology. 2012;264(2):349–68.

    Article  PubMed  Google Scholar 

  4. Kircher MF, Willmann JK. Molecular body imaging: MR imaging, CT, and US. Part I. Principles. Radiology. 2012;263(3):633–43.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Weissleder R, Pittet MJ. Imaging in the era of molecular oncology. Nature. 2008;452(7187):580–9.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  6. Negendank W. Studies of human tumors by MRS: a review. NMR Biomed. 1992;5(5):303–24.

    Article  PubMed  CAS  Google Scholar 

  7. Glunde K, et al. MRS and MRSI guidance in molecular medicine: targeting and monitoring of choline and glucose metabolism in cancer. NMR Biomed. 2011;24(6):673–90.

    PubMed  CAS  PubMed Central  Google Scholar 

  8. Hegde JV, et al. Multiparametric MRI of prostate cancer: an update on state-of-the-art techniques and their performance in detecting and localizing prostate cancer. J Magn Reson Imaging. 2013;37(5):1035–54.

    Article  PubMed  Google Scholar 

  9. Padhani AR, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009;11(2):102–25.

    PubMed  CAS  PubMed Central  Google Scholar 

  10. Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol. 2007;188(6):1622–35.

    Article  PubMed  Google Scholar 

  11. Guo Y, et al. Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging. 2002;16(2):172–8.

    Article  PubMed  Google Scholar 

  12. Choi EK, et al. Node-by-node correlation between MR and PET/CT in patients with uterine cervical cancer: diffusion-weighted imaging versus size-based criteria on T2WI. Eur Radiol. 2009;19(8):2024–32.

    Article  PubMed  Google Scholar 

  13. Partridge SC, et al. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion-weighted MRI. J Magn Reson Imaging. 2010;31(3):562–70.

    Article  PubMed  Google Scholar 

  14. Mardor Y, et al. Pretreatment prediction of brain tumors’ response to radiation therapy using high b-value diffusion-weighted MRI. Neoplasia. 2004;6(2):136–42.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Barrett T, et al. DCE and DW MRI in monitoring response to androgen deprivation therapy in patients with prostate cancer: a feasibility study. Magn Reson Med. 2012;67(3):778–85.

    Article  PubMed  CAS  Google Scholar 

  16. Gollub MJ, et al. Dynamic contrast enhanced-MRI for the detection of pathological complete response to neoadjuvant chemotherapy for locally advanced rectal cancer. Eur Radiol. 2012;22(4):821–31.

    Article  PubMed  CAS  Google Scholar 

  17. Jensen LR, et al. Diffusion-weighted and dynamic contrast-enhanced MRI in evaluation of early treatment effects during neoadjuvant chemotherapy in breast cancer patients. J Magn Reson Imaging. 2011;34(5):1099–109.

    Article  PubMed  Google Scholar 

  18. Kim JH, et al. Dynamic contrast-enhanced 3-T MR imaging in cervical cancer before and after concurrent chemoradiotherapy. Eur Radiol. 2012;22(11):2533–9.

    Article  PubMed  Google Scholar 

  19. Padhani AR, Leach MO. Antivascular cancer treatments: functional assessments by dynamic contrast-enhanced magnetic resonance imaging. Abdom Imaging. 2005;30(3):324–41.

    PubMed  CAS  Google Scholar 

  20. Leach MO, et al. Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging. Eur Radiol. 2012;22(7):1451–64.

    Article  PubMed  CAS  Google Scholar 

  21. Zavaleta CL, et al. Raman’s “effect” on molecular imaging. J Nucl Med. 2011;52(12):1839–44.

    Google Scholar 

  22. Kurhanewicz J, et al. Analysis of cancer metabolism by imaging hyperpolarized nuclei: prospects for translation to clinical research. Neoplasia. 2011;13(2):81–97.

    PubMed  PubMed Central  Google Scholar 

  23. Hricak H, et al. Global trends in hybrid imaging. Radiology. 2010;257(2):498–506.

    Article  PubMed  Google Scholar 

  24. Torigian DA, et al. PET/MR imaging: technical aspects and potential clinical applications. Radiology. 2013;267(1):26–44.

    Article  PubMed  Google Scholar 

  25. Gerlinger M, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366(10):883–92.

    Article  PubMed  CAS  Google Scholar 

  26. Cowin PA, et al. LRP1B deletion in high-grade serous ovarian cancers is associated with acquired chemotherapy resistance to liposomal doxorubicin. Cancer Res. 2012;72(16):4060–73.

    Article  PubMed  CAS  Google Scholar 

  27. Segal E, et al. Decoding global gene expression programs in liver cancer by noninvasive imaging. Nat Biotechnol. 2007;25(6):675–80.

    Article  PubMed  CAS  Google Scholar 

  28. Zinn PO, et al. Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme. PLoS One. 2011;6(10):e25451.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  29. Goh V, et al. Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker. Radiology. 2011;261(1):165–71.

    Article  PubMed  Google Scholar 

  30. Ng F, et al. Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology. 2013;266(1):177–84.

    Article  PubMed  Google Scholar 

  31. Miles KA, et al. Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival. Radiology. 2009;250(2):444–52.

    Article  PubMed  Google Scholar 

  32. Canuto HC, et al. Characterization of image heterogeneity using 2D Minkowski functionals increases the sensitivity of detection of a targeted MRI contrast agent. Magn Reson Med. 2009;61(5):1218–24.

    Article  PubMed  Google Scholar 

  33. Kyriazi S, et al. Metastatic ovarian and primary peritoneal cancer: assessing chemotherapy response with diffusion-weighted MR imaging – value of histogram analysis of apparent diffusion coefficients. Radiology. 2011;261(1):182–92.

    Article  PubMed  Google Scholar 

  34. Rose CJ, et al. Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps. Magn Reson Med. 2009;62(2):488–99.

    Article  PubMed  Google Scholar 

  35. Yang X, Knopp MV. Quantifying tumor vascular heterogeneity with dynamic contrast-enhanced magnetic resonance imaging: a review. J Biomed Biotechnol. 2011;2011:732848.

    PubMed  PubMed Central  Google Scholar 

  36. Tixier F, et al. Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med. 2011;52(3):369–78.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Taruttis A, Ntziachristos V. Translational optical imaging. AJR Am J Roentgenol. 2012;199(2):263–71.

    Article  PubMed  Google Scholar 

  38. Haglund MM, et al. Enhanced optical imaging of human gliomas and tumor margins. Neurosurgery. 1996;38(2):308–17.

    Article  PubMed  CAS  Google Scholar 

  39. Troyan SL, et al. The FLARE intraoperative near-infrared fluorescence imaging system: a first-in-human clinical trial in breast cancer sentinel lymph node mapping. Ann Surg Oncol. 2009;16(10):2943–52.

    Article  PubMed  PubMed Central  Google Scholar 

  40. van Dam GM, et al. Intraoperative tumor-specific fluorescence imaging in ovarian cancer by folate receptor-alpha targeting: first in-human results. Nat Med. 2011;17(10):1315–9.

    Article  PubMed  Google Scholar 

  41. Kircher MF, et al. A multimodal nanoparticle for preoperative magnetic resonance imaging and intraoperative optical brain tumor delineation. Cancer Res. 2003;63(23):8122–5.

    PubMed  CAS  Google Scholar 

  42. Kircher MF, et al. A brain tumor molecular imaging strategy using a new triple-modality MRI-photoacoustic-Raman nanoparticle. Nat Med. 2012;18(5):829–34.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  43. Bradley JD, et al. Positron emission tomography in limited-stage small-cell lung cancer: a prospective study. J Clin Oncol. 2004;22(16):3248–54.

    Article  PubMed  Google Scholar 

  44. Kamel EM, et al. Whole-body (18)F-FDG PET improves the management of patients with small cell lung cancer. J Nucl Med. 2003;44(12):1911–7.

    PubMed  Google Scholar 

  45. van Loon J, et al. 18FDG-PET based radiation planning of mediastinal lymph nodes in limited disease small cell lung cancer changes radiotherapy fields: a planning study. Radiother Oncol. 2008;87(1):49–54.

    Article  PubMed  Google Scholar 

  46. Madani I, et al. Positron emission tomography-guided, focal-dose escalation using intensity-modulated radiotherapy for head and neck cancer. Int J Radiat Oncol Biol Phys. 2007;68(1):126–35.

    Article  PubMed  Google Scholar 

  47. Troost EG, et al. 18F-FLT PET/CT for early response monitoring and dose escalation in oropharyngeal tumors. J Nucl Med. 2010;51(6):866–74.

    Article  PubMed  Google Scholar 

  48. Chan AA, et al. Proton magnetic resonance spectroscopy imaging in the evaluation of patients undergoing gamma knife surgery for Grade IV glioma. J Neurosurg. 2004;101(3):467–75.

    Article  PubMed  Google Scholar 

  49. Grosu AL, et al. An interindividual comparison of O-(2-[18F]fluoroethyl)-L-tyrosine (FET)- and L-[methyl-11C]methionine (MET)-PET in patients with brain gliomas and metastases. Int J Radiat Oncol Biol Phys. 2011;81(4):1049–58.

    Article  PubMed  CAS  Google Scholar 

  50. Pauleit D, et al. O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain. 2005;128(Pt 3):678–87.

    Article  PubMed  Google Scholar 

  51. Kurihara H, et al. Radiolabelled agents for PET imaging of tumor hypoxia. Curr Med Chem. 2012;19(20):3282–9.

    Article  PubMed  CAS  Google Scholar 

  52. Tachibana I, et al. A prospective clinical trial of tumor hypoxia imaging with 18F-fluoromisonidazole positron emission tomography and computed tomography (F-MISO PET/CT) before and during radiation therapy. J Radiat Res. 2013 [Epub ahead of print].

    Google Scholar 

  53. Figueiras RG, et al. Novel oncologic drugs: what they do and how they affect images. Radiographics. 2011;31(7):2059–91.

    Article  PubMed  Google Scholar 

  54. Krohn KA, et al. Molecular imaging of hypoxia. J Nucl Med. 2008;49 Suppl 2:129S–48.

    Article  PubMed  CAS  Google Scholar 

  55. Zips D, et al. Exploratory prospective trial of hypoxia-specific PET imaging during radiochemotherapy in patients with locally advanced head-and-neck cancer. Radiother Oncol. 2012;105(1):21–8.

    Article  PubMed  Google Scholar 

  56. Rischin D, et al. Prognostic significance of [18F]-misonidazole positron emission tomography-detected tumor hypoxia in patients with advanced head and neck cancer randomly assigned to chemoradiation with or without tirapazamine: a substudy of Trans-Tasman Radiation Oncology Group Study 98.02. J Clin Oncol. 2006;24(13):2098–104.

    Article  PubMed  Google Scholar 

  57. Rischin D, et al. Tirapazamine, cisplatin, and radiation versus cisplatin and radiation for advanced squamous cell carcinoma of the head and neck (TROG 02.02, HeadSTART): a phase III trial of the Trans-Tasman Radiation Oncology Group. J Clin Oncol. 2010;28(18):2989–95.

    Article  PubMed  CAS  Google Scholar 

  58. Caulo A, et al. Integrated imaging of non-small cell lung cancer recurrence: CT and PET-CT findings, possible pitfalls and risk of recurrence criteria. Eur Radiol. 2012;22(3):588–606.

    Article  PubMed  Google Scholar 

  59. Even-Sapir E, et al. Detection of recurrence in patients with rectal cancer: PET/CT after abdominoperineal or anterior resection. Radiology. 2004;232(3):815–22.

    Article  PubMed  Google Scholar 

  60. Ho AS, et al. Impact of positron emission tomography/computed tomography surveillance at 12 and 24 months for detecting head and neck cancer recurrence. Cancer. 2013;119(7):1349–56.

    Article  PubMed  Google Scholar 

  61. Prakash P, et al. Role of PET/CT in ovarian cancer. AJR Am J Roentgenol. 2010;194(6):W464–70.

    Article  PubMed  Google Scholar 

  62. Ruers TJ, et al. Improved selection of patients for hepatic surgery of colorectal liver metastases with (18)F-FDG PET: a randomized study. J Nucl Med. 2009;50(7):1036–41.

    Article  PubMed  Google Scholar 

  63. Yi JS, et al. 18F-FDG PET/CT for detecting distant metastases in patients with recurrent head and neck squamous cell carcinoma. J Surg Oncol. 2012;106(6):708–12.

    Article  PubMed  Google Scholar 

  64. Pucar D, et al. Prostate cancer: correlation of MR imaging and MR spectroscopy with pathologic findings after radiation therapy-initial experience. Radiology. 2005;236:545–53.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Pickett B, et al. Use of MRI and spectroscopy in evaluation of external beam radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys. 2004;60(4):1047–55.

    Article  PubMed  Google Scholar 

  66. Mueller-Lisse UG, et al. Localized prostate cancer: effect of hormone deprivation therapy measured by using combined three-dimensional 1H MR spectroscopy and MR imaging: clinicopathologic case-controlled study. Radiology. 2001;221(2):380–90.

    Article  PubMed  CAS  Google Scholar 

  67. Parivar F, et al. Detection of locally recurrent prostate cancer after cryosurgery: evaluation by transrectal ultrasound, magnetic resonance imaging, and three-dimensional proton magnetic resonance spectroscopy. Urology. 1996;48(4):594–9.

    Article  PubMed  CAS  Google Scholar 

  68. Donati OF, et al. Multiparametric prostate MR imaging with T2-weighted, diffusion-weighted, and dynamic contrast-enhanced sequences: are all pulse sequences necessary to detect locally recurrent prostate cancer after radiation therapy? Radiology. 2013;268(2):440–50.

    Google Scholar 

  69. Westphalen AC, et al. Multiparametric 3T endorectal MRI after external beam radiation therapy for prostate cancer. J Magn Reson Imaging. 2012;36(2):430–7.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Giovacchini G, et al. [11C]choline positron emission tomography/computerized tomography for early detection of prostate cancer recurrence in patients with low increasing prostate specific antigen. J Urol. 2013;189(1):105–10.

    Article  PubMed  Google Scholar 

  71. Jilg CA, et al. Salvage lymph node dissection with adjuvant radiotherapy for nodal recurrence of prostate cancer. J Urol. 2012;188(6):2190–7.

    Article  PubMed  CAS  Google Scholar 

  72. Plathow C, Weber WA. Tumor cell metabolism imaging. J Nucl Med. 2008;49 Suppl 2:43S–63.

    Article  PubMed  CAS  Google Scholar 

  73. de Geus-Oei LF, et al. FDG-PET/CT based response-adapted treatment. Cancer Imaging. 2012;12(2):324–35.

    Article  PubMed  Google Scholar 

  74. Lordick F, et al. PET to assess early metabolic response and to guide treatment of adenocarcinoma of the oesophagogastric junction: the MUNICON phase II trial. Lancet Oncol. 2007;8(9):797–805.

    Article  PubMed  Google Scholar 

  75. Day SE, et al. Detecting tumor response to treatment using hyperpolarized 13C magnetic resonance imaging and spectroscopy. Nat Med. 2007;13(11):1382–7.

    Article  PubMed  CAS  Google Scholar 

  76. Dijkers EC, et al. Biodistribution of 89Zr-trastuzumab and PET imaging of HER2-positive lesions in patients with metastatic breast cancer. Clin Pharmacol Ther. 2010;87(5):586–92.

    Article  PubMed  CAS  Google Scholar 

  77. Memon AA, et al. PET imaging of patients with non-small cell lung cancer employing an EGF receptor targeting drug as tracer. Br J Cancer. 2011;105(12):1850–5.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  78. Beattie BJ, et al. Pharmacokinetic assessment of the uptake of 16beta-18F-fluoro-5alpha-dihydrotestosterone (FDHT) in prostate tumors as measured by PET. J Nucl Med. 2010;51(2):183–92.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  79. Linden HM, et al. Fluoroestradiol positron emission tomography reveals differences in pharmacodynamics of aromatase inhibitors, tamoxifen, and fulvestrant in patients with metastatic breast cancer. Clin Cancer Res. 2011;17(14):4799–805.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  80. Scher HI, et al. Antitumour activity of MDV3100 in castration-resistant prostate cancer: a phase 1–2 study. Lancet. 2010;375(9724):1437–46.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  81. Ozdemir V, et al. Shifting emphasis from pharmacogenomics to theranostics. Nat Biotechnol. 2006;24(8):942–6.

    Article  PubMed  CAS  Google Scholar 

  82. Hricak H. Oncologic imaging: a guiding hand of personalized cancer care. Radiology. 2011;259(3):633–40.

    Article  PubMed  Google Scholar 

  83. Weber WA, et al. Technology insight: novel imaging of molecular targets is an emerging area crucial to the development of targeted drugs. Nat Clin Pract Oncol. 2008;5(1):44–54.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  84. Ambrosini V, et al. Radiopeptide imaging and therapy in Europe. J Nucl Med. 2011;52 Suppl 2:42S–55.

    Article  PubMed  CAS  Google Scholar 

  85. Kircher MF, et al. Molecular imaging for personalized cancer care. Mol Oncol 2012;6(2):182–195.

    Article  PubMed  CAS  Google Scholar 

  86. Welch MJ, et al. The advantages of nanoparticles for PET. J Nucl Med. 2009;50(11):1743–6.

    Article  PubMed  CAS  Google Scholar 

  87. Li KC, et al. Combined vascular targeted imaging and therapy: a paradigm for personalized treatment. J Cell Biochem Suppl. 2002;39:65–71.

    Article  PubMed  Google Scholar 

  88. Krestin GP, et al. Integrated diagnostics: proceedings from the 9th biennial symposium of the International Society for Strategic Studies in Radiology. Eur Radiol. 2012;22(11):2283–94.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, room C-278, New York, NY, 10065, USA

    Evis Sala MD, PhD, Hebert Alberto Vargas MD, Olivio F. Donati MD, Wolfgang A. Weber MD, PhD & Hedvig Hricak MD, PhD

  2. Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland

    Olivio F. Donati MD

Authors
  1. Evis Sala MD, PhD
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  2. Hebert Alberto Vargas MD
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  3. Olivio F. Donati MD
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  4. Wolfgang A. Weber MD, PhD
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  5. Hedvig Hricak MD, PhD
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Corresponding author

Correspondence to Hedvig Hricak MD, PhD .

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Editors and Affiliations

  1. Health Time Group, Jaén, Spain

    Antonio Luna

  2. Dept. of MRI, Clínica Girona, Girona, Spain

    Joan C. Vilanova

  3. Botafogo - Rio de Janeiro/RJ, Brazil

    L. Celso Hygino da Cruz Jr.

  4. Centro de Diagnóstico Dr. Enrique Rossi, Buenos Aires, Argentina

    Santiago E. Rossi

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Sala, E., Vargas, H.A., Donati, O.F., Weber, W.A., Hricak, H. (2014). Role of Molecular Imaging in the Era of Personalized Medicine: A Review. In: Luna, A., Vilanova, J., Hygino da Cruz Jr., L., Rossi, S. (eds) Functional Imaging in Oncology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40412-2_3

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