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Overview of Imaging Modalities in Oncology

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Multimodality Imaging and Intervention in Oncology

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Abstract

Tomosynthesis is a low-dose X-ray modality that acquires at multiple angles a 3D volume of the breast. During image acquisition, the X-ray tube and the detector may have different movement geometries. In particular, there are three main motion geometries: parallel path, full isocentric motion, and partial isocentric motion. In parallel-path geometry, the X-ray tube moves by describing a trajectory parallel to the plane of the detector, while the detector can move along its plane. Full isocentric geometry foresees that the X-ray tube and the detector move together maintaining a fixed distance and describes a curvilinear trajectory. In partial isocentric geometry, the detector remains stationary while the X-ray tube moves, describing a curvilinear trajectory [1, 2].

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References

  1. Dobbins JT 3rd. Tomosynthesis imaging: at a translational crossroads. Med Phys. 2009;36(6):1956–67. PMID: 19610284; PMCID: PMC2832060. https://doi.org/10.1118/1.3120285.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Yaffe MJ, Mainprize JG. Digital tomosynthesis: technique. Radiol Clin North Am. 2014;52(3):489–97. PMID: 24792651. https://doi.org/10.1016/j.rcl.2014.01.003.

    Article  PubMed  Google Scholar 

  3. Ferrari A, Bertolaccini L, Solli P, Di Salvia PO, Scaradozzi D. Digital chest tomosynthesis: the 2017 updated review of an emerging application. Ann Transl Med. 2018;6(5):91. https://doi.org/10.21037/atm.2017.08.18.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Hooley RJ, Durand MA, Philpotts LE. Advances in digital breast tomosynthesis. AJR Am J Roentgenol. 2017;208(2):256–66. Epub 2016 Oct 27. PMID: 27786548. https://doi.org/10.2214/AJR.16.17127.

    Article  PubMed  Google Scholar 

  5. Terzi A, Bertolaccini L, Viti A, Comello L, Ghirardo D, Priotto R, Grosso M, SOS Study Group. Lung cancer detection with digital chest tomosynthesis: baseline results from the observational study SOS. J Thorac Oncol. 2013;8(6):685–92. PMID: 23612466. https://doi.org/10.1097/JTO.0b013e318292bdef.

    Article  PubMed  Google Scholar 

  6. Chong A, Weinstein SP, McDonald ES, Conant EF. Digital breast tomosynthesis: concepts and clinical practice. Radiology. 2019;292(1):1–14. https://doi.org/10.1148/radiol.2019180760.

    Article  PubMed  Google Scholar 

  7. Bertolaccini L, Viti A, Terzi A. Digital tomosynthesis in lung cancer: state of the art. Ann Transl Med. 2015;3(10):139. https://doi.org/10.3978/j.issn.2305-5839.2015.06.03.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kim EY, Bista AB, Kim T, et al. The advantage of digital tomosynthesis for pulmonary nodule detection concerning influence of nodule location and size: a phantom study. Clin Radiol. 2017;72:796.e1–8.

    Article  CAS  PubMed  Google Scholar 

  9. Choo JY, Lee KY, Yu A, et al. A comparison of digital tomosynthesis and chest radiography in evaluating airway lesions using computed tomography as a reference. Eur Radiol. 2016;26:3147–54.

    Article  PubMed  Google Scholar 

  10. García de Casasola G, Casado López I, Torres-Macho J. Clinical ultrasonography in the decision-making process in medicine point-of-care ultrasound in clinical decision making. Rev Clin Esp. 2020;220(1):49–56. https://doi.org/10.1016/j.rce.2019.04.004.

    Article  PubMed  Google Scholar 

  11. Ang TL, Kwek ABE, Wang LM. Diagnostic endoscopic ultrasound: technique, current status and future directions. Gut Liver. 2018;12(5):483–96. https://doi.org/10.5009/gnl17348.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Santos DW, Fernandes PC Jr, Guedes CA Jr, Debs Diniz AL. Potential application value of doppler ultrasonography in neoadjuvant chemotherapy for breast cancer. Minerva Ginecol. 2016;68(4):405–11.

    PubMed  Google Scholar 

  13. Beckmann S, Simanowski J. H: update in contrast-enhanced ultrasound. Visc Med. 2020;36:476–86. https://doi.org/10.1159/000511352.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Bartolotta TV, Terranova M, Gagliardo C, et al. CEUS LI-RADS: a pictorial review. Insights Imaging. 2020;11:9. https://doi.org/10.1186/s13244-019-0819-2.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Ding H, Tu H, Qu C, Cao G, Zhuang H, Zhao P, Xu X, Yang Y, Lu S, Committee for Prevention and Control of Hepatobiliary and Pancreatic Diseases of Chinese Preventive Medicine Association, Committee of Hepatology of Chinese Research Hospital Association, Hepatology Society of Chinese Medical Association, Prevention of Infection Related Cancer (PIRCA) Group, Specialist Committee of Cancer Prevention and Control of Chinese Preventive Medicine Association. Guideline for stratified screening and surveillance in patients with high risk of primary liver cancer (2020). Hepatoma Res. 2021;7:17. https://doi.org/10.20517/2394-5079.2021.13.

    Article  Google Scholar 

  16. Arlt F, Chalopin C, Müns A, Meixensberger J, Lindner D. Intraoperative 3D contrast-enhanced ultrasound (CEUS): a prospective study of 50 patients with brain tumours. Acta Neurochir. 2016;158(4):685–94. https://doi.org/10.1007/s00701-016-2738-z.

    Article  PubMed  Google Scholar 

  17. Liu J, Liu X, He J, et al. Percutaneous contrast-enhanced ultrasound for localization and diagnosis of sentinel lymph node in early breast cancer. Sci Rep. 2019;9:13545. https://doi.org/10.1038/s41598-019-49736-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Riegler J, Labyed Y, Rosenzweig S, Carano RAD, et al. Tumor elastography and its association with collagen and the tumor microenvironment. Clin Cancer Res. 2018;24(18):4455–67. https://doi.org/10.1158/1078-0432.CCR-17-3262.

    Article  CAS  PubMed  Google Scholar 

  19. Crocetti L, de Baére T, Pereira PL, Tarantino FP. CIRSE standards of practice on thermal ablation of liver tumours. Cardiovasc Intervent Radiol. 2020;43(7):951–62. https://doi.org/10.1007/s00270-020-02471-z.

    Article  PubMed  Google Scholar 

  20. Theek B, Opacic T, Magnuska Z, Lammers T, Kiessling F. Radiomic analysis of contrast-enhanced ultrasound data. Sci Rep. 2018;8(1):11359. Published 2018 Jul 27. https://doi.org/10.1038/s41598-018-29653-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zhang H, Zeng D, Zhang H, Wang J, Liang Z, Ma J. Applications of nonlocal means algorithm in low-dose X-ray CT image processing and reconstruction: a review. Med Phys. 2017;44(3):1168–85. PMID: 28303644; PMCID: PMC5381744. https://doi.org/10.1002/mp.12097.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. McLeavy CM, Chunara MH, Gravell RJ, Rauf A, Cushnie A, Staley Talbot C, Hawkins RM. The future of CT: deep learning reconstruction. Clin Radiol. 2021;76(6):407–15. Epub 2021 Feb 23. https://doi.org/10.1016/j.crad.2021.01.010.

    Article  CAS  PubMed  Google Scholar 

  23. Immonen E, Wong J, Nieminen M, Kekkonen L, Roine S, Törnroos S, Lanca L, Guan F, Metsälä E. The use of deep learning towards dose optimization in low-dose computed tomography: a scoping review. Radiography (Lond). 2022;28(1):208–14. Epub 2021 Jul 27. https://doi.org/10.1016/j.radi.2021.07.010.

    Article  CAS  PubMed  Google Scholar 

  24. Willemink MJ, Persson M, Pourmorteza A, Pelc NJ, Fleischmann D. Photon-counting CT: technical principles and clinical prospects. Radiology. 2018;289(2):293–312. Epub 2018 Sep 4. https://doi.org/10.1148/radiol.2018172656.

    Article  PubMed  Google Scholar 

  25. Bette SJ, Braun FM, Haerting M, Decker JA, Luitjens JH, Scheurig-Muenkler C, Kroencke TJ, Schwarz F. Visualization of bone details in a novel photon-counting dual-source CT scanner-comparison with energy-integrating CT. Eur Radiol. 2021;32:2930. Epub ahead of print. https://doi.org/10.1007/s00330-021-08441-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Prezzi D, Khan A, Goh V. Perfusion CT imaging of treatment response in oncology. Eur J Radiol. 2015;84(12):2380–5. Epub 2015 Mar 27. https://doi.org/10.1016/j.ejrad.2015.03.022.

    Article  PubMed  Google Scholar 

  27. Perik TH, van Genugten EAJ, Aarntzen EHJG, Smit EJ, Huisman HJ, Hermans JJ. Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review. Abdom Radiol (NY). 2021;47:3101. Epub ahead of print. https://doi.org/10.1007/s00261-021-03190-w.

    Article  PubMed  Google Scholar 

  28. Kim SH, Kamaya A, Willmann JK. CT perfusion of the liver: principles and applications in oncology. Radiology. 2014;272(2):322–44. PMID: 25058132; PMCID: PMC4263626. https://doi.org/10.1148/radiol.14130091.

    Article  PubMed  Google Scholar 

  29. McCollough CH, Leng S, Yu L, Fletcher JG. Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology. 2015;276(3):637–53. PMID: 26302388; PMCID: PMC4557396. https://doi.org/10.1148/radiol.2015142631.

    Article  PubMed  Google Scholar 

  30. Mastrodicasa D, Delli Pizzi A, Patel BN. Dual-energy CT of the pancreas. Semin Ultrasound CT MR. 2019;40(6):509–14. Epub 2019 Jun 11. https://doi.org/10.1053/j.sult.2019.05.002.

    Article  PubMed  Google Scholar 

  31. Siegel MJ, Ramirez-Giraldo JC. Dual-energy CT in children: imaging algorithms and clinical applications. Radiology. 2019;291(2):286–97. Epub 2019 Mar 26. https://doi.org/10.1148/radiol.2019182289.

    Article  PubMed  Google Scholar 

  32. Lell MM, Kachelrieß M. Recent and upcoming technological developments in computed tomography: high speed, low dose, deep learning, multienergy. Invest Radiol. 2020;55(1):8–19. https://doi.org/10.1097/RLI.0000000000000601.

    Article  PubMed  Google Scholar 

  33. Bloch F, Hansen WW, Packard ME. Nuclear induction. Phys Rev. 1946;69:127.

    Article  Google Scholar 

  34. Hagstrum HD et al. LETTERS TO THE EDITOR resonance absorption by nuclear magnetic moments in a solid. 1945.

    Google Scholar 

  35. Geva T. Magnetic resonance imaging: Historical perspective. J Cardiovasc Magn Reson. 2006;8(4):573–80. https://doi.org/10.1080/10976640600755302.

    Article  PubMed  Google Scholar 

  36. Hawkes RC, Holland GN, Moore WS, Worthington BS. Nuclear magnetic resonance (NMR) tomography of the brain: a preliminary clinical assessment with demonstration of pathology. J Comput Assist Tomogr. 1980;4(5):577–86.

    Article  CAS  PubMed  Google Scholar 

  37. Smith FW, Hutchison JM, Mallard JR. Oesophageal carcinoma demonstrated by whole-body nuclear magnetic resonance imaging. Br Med J. 1981;282:510.

    Article  CAS  Google Scholar 

  38. Grover VPB, Tognarelli JM, Crossey MME, Cox IJ, Taylor-Robinson SD, McPhail MJW. Magnetic resonance imaging: principles and techniques: lessons for clinicians. J Clin Exp Hepatol. 2015;5(3):246–55. https://doi.org/10.1016/j.jceh.2015.08.001.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Karaosmanoglu AD, Onur MR, Ozmen MN, Akata D, Karcaaltincaba M. Magnetic resonance imaging of liver metastasis. Semin Ultrasound CT MRI. 2016;37(6):533–48. https://doi.org/10.1053/j.sult.2016.08.005.

    Article  Google Scholar 

  40. Bloem J, Bluemm R, Tamlnlau A, van Oosterom MA, Stolk J, Doornbos J. Magnetic resonance imaging of primary malignant bone tumors. Radiographics. 1986;7(3).

    Google Scholar 

  41. Jhaveri KS, Hosseini-Nik H. MRI of rectal cancer: an overview and update on recent advances. Am J Roentgenol. 2015;205(1):W42–55. https://doi.org/10.2214/AJR.14.14201.

    Article  Google Scholar 

  42. Plevritis SK, et al. Cost-effectiveness of screening BRCA1/2 mutation carriers with breast magnetic resonance imaging. JAMA. 2006;295:2374.

    Article  CAS  PubMed  Google Scholar 

  43. Atri M. New technologies and directed agents for applications of cancer imaging. J Clin Oncol. 2006;24(20):3299–308. https://doi.org/10.1200/JCO.2006.06.6159.

    Article  PubMed  Google Scholar 

  44. Evelhoch JL. Key factors in the acquisition of contrast kinetic data for oncology. J Magn Reson Imaging. 1999;10:254.

    Article  CAS  PubMed  Google Scholar 

  45. Baliyan V, Das CJ, Sharma R, Gupta AK. Diffusion weighted imaging: Technique and applications. World J Radiol. 2016;8(9):785. https://doi.org/10.4329/wjr.v8.i9.785.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Schouten S, et al. Response evaluation after chemoradiotherapy for advanced nodal disease in head and neck cancer using diffusion-weighted MRI and 18F-FDG-PET-CT. Oral Oncol. 2015;51(5):541–7. https://doi.org/10.1016/j.oraloncology.2015.01.017.

    Article  PubMed  Google Scholar 

  47. Takahara T, Kwe TC. diffusion-weighted whole-body imaging with background body signal suppression (DWIBS). Radiat Med. 2004;22:275–82.

    PubMed  Google Scholar 

  48. Petralia G, et al. Whole-body magnetic resonance imaging (WB-MRI) in oncology: recommendations and key uses. Radiol Med. 2019;124(3):218–33. https://doi.org/10.1007/s11547-018-0955-7.

    Article  PubMed  Google Scholar 

  49. Morone M, et al. Whole-body MRI: current applications in oncology. Am J Roentgenol. 2017;209(6):W336–49. https://doi.org/10.2214/AJR.17.17984.

    Article  Google Scholar 

  50. Zampa V, Cosottini M, Michelassi MC, Ortori S, Bruschini L, Bartolozzi C. Value of opposed-phase gradient-echo technique in distinguishing between benign and malignant vertebral lesions. Eur Radiol. 2002;12(7):1811–8. https://doi.org/10.1007/s00330-001-1229-6.

    Article  PubMed  Google Scholar 

  51. Hernando CG, Esteban L, Cañas T, van den Brule E, Pastrana M. The role of magnetic resonance imaging in oncology. Clin Transl Oncol. 2010;12(9):606–13. https://doi.org/10.1007/s12094-010-0565-x.

    Article  Google Scholar 

  52. Stanwell P, Mountford C. In vivo proton MR spectroscopy of the breast. Radiographics. 2007;27:S253. https://doi.org/10.1148/rg.27si075519.

    Article  PubMed  Google Scholar 

  53. Seale MK, Catalano OA, Saini S, Hahn PF, Sahani DV. Hepatobiliary-specific MR contrast agents: role in imaging the liver and biliary tree. Radiographics. 2009;29(6):1725–48. https://doi.org/10.1148/rg.296095515.

    Article  PubMed  Google Scholar 

  54. Lonsdale MN, Beyer T. Dual-modality PET/CT instrumentation—today and tomorrow. Eur J Radiol. 2010;73:452–60.

    Article  PubMed  Google Scholar 

  55. Beyer T, Townsend DW, Brun T, Kinahan PE, Charron M, Roddy R, et al. A combined PET/CT scanner for clinical oncology. J Nucl Med. 2000;41:1369.

    CAS  PubMed  Google Scholar 

  56. Surti S, Kuhn A, Werner ME, Perkins AE, Kolthammer J, Karp JS. Performance of Philips Gemini TF PET/CT scanner with special consideration for its time-of-flight imaging capabilities. J Nucl Med. 2007;48:471–80.

    PubMed  Google Scholar 

  57. Theek B, Magnuska Z, Gremse F, Hahn H, Schulz V, Kiessling F. Automation of data analysis in molecular cancer imaging and its potential impact on future clinical practice. Methods. 2021;188:30–6.

    Article  CAS  PubMed  Google Scholar 

  58. Nadig V, Herrmann K, Mottaghy FM, Schulz V. Hybrid total-body pet scanners—current status and future perspectives. Eur J Nucl Med Mol Imaging. 2022;49:445–59.

    Article  PubMed  Google Scholar 

  59. Humm JL, Rosenfeld A, Del Guerra A. From PET detectors to PET scanners. Eur J Nucl Med Mol Imaging. 2003;30:1574–97.

    Article  PubMed  Google Scholar 

  60. Basu S, Kwee TC, Surti S, Akin EA, Yoo D, Alavi A. Fundamentals of PET and PET/CT imaging: fundamentals of PET and PET/CT. Ann N Y Acad Sci. 2011;1228:1–18.

    Article  CAS  PubMed  Google Scholar 

  61. Kinahan PE, Townsend DW, Beyer T, Sashin D. Attenuation correction for a combined 3D PET/CT scanner. Med Phys. 1998;25:2046–53.

    Article  CAS  PubMed  Google Scholar 

  62. Vandenberghe S, Moskal P, Karp JS. State of the art in total body PET. EJNMMI Phys. 2020;7:35.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Tan H, Gu Y, Yu H, Hu P, Zhang Y, Mao W, et al. Total-body PET/CT: current applications and future perspectives. Am J Roentgenol. 2020;215:325–37.

    Article  Google Scholar 

  64. Singh D, Miles K. Multiparametric PET/CT in oncology. Cancer Imaging. 2012;12:336–44.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Zaidi H, Alavi A, Naqa IE. Novel quantitative PET techniques for clinical decision support in oncology. Semin Nucl Med. 2018;48:548–64.

    Article  PubMed  Google Scholar 

  66. Zaidi H, Karakatsanis N. Towards enhanced PET quantification in clinical oncology. BJR. 2018;91:20170508.

    Article  PubMed  Google Scholar 

  67. Singnurkar A, Poon R, Metser U. Comparison of 18F-FDG-PET/CT and 18F-FDG-PET/MR imaging in oncology: a systematic review. Ann Nucl Med. 2017;31:366–78.

    Article  PubMed  Google Scholar 

  68. Basu S, Alavi A. PET-based personalized management in clinical oncology. PET Clin. 2016;11:203–7.

    Article  PubMed  Google Scholar 

  69. Caswell DR, Swanton C. The role of tumour heterogeneity and clonal cooperativity in metastasis, immune evasion and clinical outcome. BMC Med. 2017;15:133.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Voigt W. Advanced PET imaging in oncology: status and developments with current and future relevance to lung cancer care. Curr Opin Oncol. 2018;30:77–83.

    Article  PubMed  Google Scholar 

  71. Giesel FL, Kratochwil C, Lindner T, Marschalek MM, Loktev A, Lehnert W, et al. 68Ga-FAPI PET/CT: biodistribution and preliminary dosimetry estimate of 2 DOTA-containing FAP-targeting agents in patients with various cancers. J Nucl Med. 2019;60:386–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. De Jong M. New tracers to the clinic. Q J Nucl Med Mol Imaging. 2017;61:133–4.

    PubMed  Google Scholar 

  73. Seifert R, Kersting D, Rischpler C, Opitz M, Kirchner J, Pabst KM, Mavroeidi I-A, Laschinsky C, Grueneisen J, Schaarschmidt B, Catalano OA, Herrmann K, Umutlu L. Clinical use of PET/MR in oncology: an update. Semin Nucl Med. 2022;52:356. https://doi.org/10.1053/j.semnuclmed.2021.11.012.

    Article  PubMed  Google Scholar 

  74. Kjær A, Torigian DA. Clinical PET/MR imaging in oncology. PET Clin. 2016;11(4):489–93. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  PubMed  Google Scholar 

  75. Hu Z, Yang W, Liu H, Wang K, Bao C, Song T, Wang J, Tian J. From PET/CT to PET/MRI: advances in instrumentation and clinical applications. Mol Pharm. 2014;11(11):3798–809. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  CAS  PubMed  Google Scholar 

  76. Bailey DL, Pichler BJ, Gückel B, Antoch G, Barthel H, Bhujwalla ZM, Biskup S, Biswal S, Bitzer M, Boellaard R, Braren RF, Brendle C, Brindle K, Chiti A, la Fougère C, Gillies R, Goh V, Goyen M, Hacker M, Beyer T. Combined PET/MRI: global warming—summary report of the 6th international workshop on PET/MRI, March 27–29, 2017, Tübingen, Germany. Mol Imaging Biol. 2018;20(1):4–20. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  CAS  PubMed  Google Scholar 

  77. States LJ, Reid JR. Whole-body PET/MRI applications in pediatric oncology. Am J Roentgenol. 2020;215(3):713–25. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  Google Scholar 

  78. Sałyga A, Guzikowska-Ruszkowska I, Czepczyński R, Ruchała M. PET/MR—a rapidly growing technique of imaging in oncology and neurology. Nucl Med Rev. 2016;19(1):5.

    Article  Google Scholar 

  79. Hope TA, Fayad ZA, Fowler KJ, Holley D, Iagaru A, McMillan AB, Veit-Haiback P, Witte RJ, Zaharchuk G, Catana C. Summary of the first ISMRM–SNMMI workshop on PET/MRI: applications and limitations. J Nucl Med. 2019;60(10):1340–6. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Mehranian A, Arabi H, Zaidi H. Vision 20/20: magnetic resonance imaging guided attenuation correction in PET/MRI: challenges, solutions, and opportunities. Med Phys. 2016;43(3):1130–55. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  PubMed  Google Scholar 

  81. Han X. MR-based synthetic CT generation using a deep convolutional neural network method. Med Phys. 2017;44:1408–19.

    Article  CAS  PubMed  Google Scholar 

  82. Gutte H, Hansen AE, Larsen MME, Rahbek S, Henriksen ST, Johannesen HH, Ardenkjaer-Larsen J, Kristensen AT, Højgaard L, Kjær A. Simultaneous hyperpolarized 13C-pyruvate MRI and 18F-FDG PET (HyperPET) in 10 dogs with cancer. J Nuclear Med. 2015;56(11):1786–92. https://doi.org/10.2967/jnumed.115.156364.

    Article  CAS  Google Scholar 

  83. Chen H-Y, Aggarwal R, Bok RA, Ohliger MA, Zhu Z, Lee P, Gordon JW, van Criekinge M, Carvajal L, Slater JB, Larson PEZ, Small EJ, Kurhanewicz J, Vigneron DB. Hyperpolarized 13C-pyruvate MRI detects real-time metabolic flux in prostate cancer metastases to bone and liver: a clinical feasibility study. Prostate Cancer Prostatic Dis. 2020;23(2):269–76. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  CAS  PubMed  Google Scholar 

  84. Sotoudeh H, Sharma A, Fowler KJ, McConathy J, Dehdashti F. Clinical application of PET/MRI in oncology: PET/MRI in oncology. J Magn Reson Imaging. 2016;44(2):265–76. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  PubMed  Google Scholar 

  85. Evangelista L, Zattoni F, Cassarino G, Artioli P, Cecchin D, dal Moro, F., & Zucchetta, P. PET/MRI in prostate cancer: a systematic review and meta-analysis. Eur J Nucl Med Mol Imaging. 2021;48(3):859–73. https://doi.org/10.1007/s00259-020-05025-0.

    Article  PubMed  Google Scholar 

  86. Hope TA, Kassam Z, Loening A, McNamara MM, Paspulati R. The use of PET/MRI for imaging rectal cancer. Abdom Radiol. 2019;44(11):3559–68. https://doi.org/10.1007/s00261-019-02089-x.

    Article  Google Scholar 

  87. Umutlu L, Beyer T, Grueneisen J, Rischpler C, Quick H, Veit-Haibach P, Eiber M, Purz S, Antoch G, Gatidis S, Nikolaou K, Schaefer J, Rausch I, Herrmann K, Vorstand der Interdisziplinären AG für Hybride Bildgebung in alphabetischer Reihenfolge:, & Vorstand der Deutschen Röntgengesellschaft (DRG) und der Deutschen Gesellschaft für Nuklearmedizin (DGN) in alphabetischer Reihenfolge. Whole-body [18F]-FDG-PET/MRI for oncology: a consensus recommendation. RöFo - Fortschritte Auf Dem Gebiet Der Röntgenstrahlen Und Der Bildgebenden Verfahren. 2019;191(04):289–97. https://doi.org/10.1055/a-0828-8654.

    Article  Google Scholar 

  88. Schillaci O, Urbano N. Personalized medicine: a new option for nuclear medicine and molecular imaging in the third millennium. Eur J Nucl Med Mol Imaging. 2017;44(4):563–6. https://doi.org/10.1007/s00259-017-3616-5.

    Article  PubMed  Google Scholar 

  89. Miles KA, Voo SA, Groves AM. Additional clinical value for PET/MRI in oncology: moving beyond simple diagnosis. J Nucl Med. 2018;59(7):1028–32. Errore. Riferimento a collegamento ipertestuale non valido.

    Article  CAS  PubMed  Google Scholar 

  90. Broski SM, Goenka AH, Kemp BJ, Johnson GB. Clinical PET/MRI: 2018 update. Am J Roentgenol. 2018;211(2):295–313. https://doi.org/10.2214/AJR.18.20001.

    Article  Google Scholar 

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Authors and Affiliations

  1. Academic Radiology, Department of Surgical, Medical, Molecular Pathology and Emergency Medicine, University of Pisa, Pisa, Italy

    Dania Cioni

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  1. Academic Radiology, Department of Translational Research and new Technologies in Medicine and Surgery, University of Pisa, PISA, Pisa, Italy

    Emanuele Neri

  2. Department of Medicine and Surgery, University of Milan Bicocca, and Nuclear Medicine ASST-Ospedale Papa Giovanni XXIII, Bergamo, Italy

    Paola Anna Erba

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Cioni, D. (2023). Overview of Imaging Modalities in Oncology. In: Neri, E., Erba, P.A. (eds) Multimodality Imaging and Intervention in Oncology. Springer, Cham. https://doi.org/10.1007/978-3-031-28524-0_2

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  • DOI: https://doi.org/10.1007/978-3-031-28524-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-28523-3

  • Online ISBN: 978-3-031-28524-0

  • eBook Packages: MedicineMedicine (R0)

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