SpringerLink
Log in

Somatostatin receptor PET/MRI for the evaluation of neuroendocrine tumors

  • Review Article
  • Published:
Clinical and Translational Imaging Aims and scope Submit manuscript

Abstract

With the introduction of simultaneous PET/MRI scanners, concurrent acquisition of PET and MRI data is feasible, allowing for improved patient convenience and decreased radiation dose. Although PET/MRI has been used in many settings, not all cancers benefit from the combined modality. With the availability of somatostatin receptor-targeted PET tracers such as 68Ga-DOTA-TOC and 68Ga-DOTA-TATE, imaging of NET patients has refocused on targeted imaging, particularly with the development of peptide receptor radiotherapy. Nonetheless, there are many patients who continue to benefit from dedicated MR imaging, such as those with liver-predominant disease. In these patients, SSR PET/MRI is an important option for optimal imaging. Both diffusion-weighted imaging and hepatobiliary phase imaging provide improved lesion detection compared to conventional MRI and CT, and the results can effect therapeutic decisions. Additionally, the use of motion correction techniques can be used to leverage the additional PET data acquired in dedicated liver PET/MRI to remove respiratory artifacts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Spain)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Hallet J, Law CHL, Cukier M, Saskin R, Liu N, Singh S (2015) Exploring the rising incidence of neuroendocrine tumors: a population-based analysis of epidemiology, metastatic presentation, and outcomes. Cancer 121:589–597

    Article  PubMed  Google Scholar 

  2. Klimstra DS, Modlin IR, Coppola D, Lloyd RV, Suster S (2010) The pathologic classification of neuroendocrine tumors: a review of nomenclature, grading, and staging systems. Pancreas 39:707–712

    Article  PubMed  Google Scholar 

  3. Bosman FT, Carneiro F, Hruban RH, Theise ND. WHO classification of tumours of the digestive system. 2010

  4. Ferrone CR, Tang LH, Tomlinson J et al (2007) Determining prognosis in patients with pancreatic endocrine neoplasms: can the WHO classification system be simplified? J Clin Oncol 25:5609–5615

    Article  PubMed  Google Scholar 

  5. Modlin IM, Oberg K, Chung DC et al (2008) Gastroenteropancreatic neuroendocrine tumours. Lancet Oncol 9:61–72

    Article  CAS  PubMed  Google Scholar 

  6. Hakim FA, Alexander JA, Huprich JE, Grover M, Enders FT (2011) CT-enterography may identify small bowel tumors not detected by capsule endoscopy: eight years experience at Mayo Clinic Rochester. Dig Dis Sci 56:2914–2919

    Article  PubMed  Google Scholar 

  7. Sankowski AJ, Ćwikla JB, Nowicki ML et al (2012) The clinical value of MRI using single-shot echoplanar DWI to identify liver involvement in patients with advanced gastroenteropancreatic-neuroendocrine tumors (GEP-NETs), compared to FSE T2 and FFE T1 weighted image after i.v. Gd-EOB-DTPA contrast enhancement. Med Sci Monit 18:33–40

    Article  Google Scholar 

  8. Mayerhoefer ME, Ba-Ssalamah A, Weber M et al (2013) Gadoxetate-enhanced versus diffusion-weighted MRI for fused Ga-68-DOTANOC PET/MRI in patients with neuroendocrine tumours of the upper abdomen. Eur Radiol 23:1978–1985

    Article  PubMed  Google Scholar 

  9. Rinke A, Müller H-H, Schade-Brittinger C et al (2009) Placebo-controlled, double-blind, prospective, randomized study on the effect of octreotide LAR in the control of tumor growth in patients with metastatic neuroendocrine midgut tumors: a report from the PROMID Study Group. J Clin Oncol 27:4656–4663

    Article  CAS  PubMed  Google Scholar 

  10. Harris AG (1994) Somatostatin and somatostatin analogues: pharmacokinetics and pharmacodynamic effects. Gut 35:S1–S4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Bombardieri E, Ambrosini V, Aktolun C, et al. (2010) 111 In-pentetreotide scintigraphy: procedure guidelines for tumour imaging. Eur J Nucl Med Mol Imaging 37:1441–1448

    Article  PubMed  Google Scholar 

  12. Balon HR, Brown TLY, Goldsmith SJ et al (2011) The SNM practice guideline for somatostatin receptor scintigraphy 2.0. J Nucl Med Technol. 39:317–324

    Article  PubMed  Google Scholar 

  13. Deppen SA, Liu E, Blume JD, et al. (2016) Safety and Efficacy of 68Ga-DOTATATE PET/CT for Diagnosis, Staging, and Treatment Management of Neuroendocrine Tumors. J Nucl Med 57:708–714

    Article  PubMed  Google Scholar 

  14. Poeppel TD, Binse I, Petersenn S et al (2011) 68Ga-DOTATOC versus 68Ga-DOTATATE PET/CT in functional imaging of neuroendocrine tumors. J Nucl Med 52:1864–1870

    Article  CAS  PubMed  Google Scholar 

  15. Velikyan I, Sundin A, Sörensen J et al (2014) Quantitative and qualitative intrapatient comparison of 68Ga-DOTATOC and 68Ga-DOTATATE: net uptake rate for accurate quantification. J Nucl Med 55:204–210

    Article  CAS  PubMed  Google Scholar 

  16. Krausz Y, Freedman N, Rubinstein R et al (2011) 68Ga-DOTA-NOC PET/CT imaging of neuroendocrine tumors: comparison with 111In-DTPA-octreotide (OctreoScan®). Mol Imaging Biol 13:583–593

    Article  PubMed  Google Scholar 

  17. Hofman MS, Lau WFE, Hicks RJ (2015) Somatostatin receptor imaging with 68Ga DOTATATE PET/CT: clinical utility, normal patterns, pearls, and pitfalls in interpretation. Radiographics 35:500–516

    Article  PubMed  Google Scholar 

  18. Kayani I, Bomanji JB, Groves A et al (2008) Functional imaging of neuroendocrine tumors with combined PET/CT using 68Ga-DOTATATE (DOTA-DPhe1, Tyr3-octreotate) and 18F-FDG. Cancer 112:2447–2455

    Article  PubMed  Google Scholar 

  19. Tan EH, Tan CH (2011) Imaging of gastroenteropancreatic neuroendocrine tumors. World J Clin Oncol 2:28–43

    Article  PubMed  PubMed Central  Google Scholar 

  20. Binderup T, Knigge U, Loft A et al (2010) Functional imaging of neuroendocrine tumors: a head-to-head comparison of somatostatin receptor scintigraphy, 123I-MIBG scintigraphy, and 18F-FDG PET. J Nucl Med 51:704–712

    Article  PubMed  Google Scholar 

  21. Severi S, Nanni O, Bodei L et al (2013) Role of 18FDG PET/CT in patients treated with 177Lu-DOTATATE for advanced differentiated neuroendocrine tumours. Eur J Nucl Med Mol Imaging 40:881–888

    Article  CAS  PubMed  Google Scholar 

  22. Hope TA, Pampaloni MH, Nakakura E et al. (2015) Simultaneous (68)Ga-DOTA-TOC PET/MRI with gadoxetate disodium in patients with neuroendocrine tumor. Abdom Imaging

  23. Burris NS, Johnson KM, Larson PEZ et al. (2015) Detection of small pulmonary nodules with ultrashort echo time sequences in oncology patients by using a PET/MR system. Radiology 278(1):239–246. doi:10.1148/radiol.2015150489

    Article  PubMed  PubMed Central  Google Scholar 

  24. de Mestier L, Dromain C, d’Assignies G et al (2014) Evaluating digestive neuroendocrine tumor progression and therapeutic responses in the era of targeted therapies: state of the art. Endocr Relat Cancer BioScientifica 21:R105–R120. doi:10.1530/ERC-13-0365

    Article  Google Scholar 

  25. Beiderwellen KJ, Poeppel TD, Hartung-Knemeyer V et al (2013) Simultaneous 68Ga-DOTATOC PET/MRI in patients with gastroenteropancreatic neuroendocrine tumors: initial results. Invest Radiol 48:273–279

    Article  CAS  PubMed  Google Scholar 

  26. Hope TA, Verdin EF, Bergsland EK, Ohliger MA, Corvera CU, Nakakura EK (2015) Correcting for respiratory motion in liver PET/MRI: preliminary evaluation of the utility of bellows and navigated hepatobiliary phase imaging. EJNMMI Phys 2:21

    Article  PubMed  PubMed Central  Google Scholar 

  27. Catana C (2015) Motion correction options in PET/MRI. Semin Nucl Med 45:212–223

    Article  PubMed  PubMed Central  Google Scholar 

  28. Grimm R, Fürst S, Souvatzoglou M et al (2015) Self-gated MRI motion modeling for respiratory motion compensation in integrated PET/MRI. Med Image Anal 19:110–120

    Article  PubMed  Google Scholar 

  29. Manber R, Thielemans K, Hutton B et al (2015) Practical PET respiratory motion correction in clinical PET/MR. J Nucl Med

  30. Nagle SK, Busse RF, Brau AC et al (2012) High resolution navigated three-dimensional T1-weighted hepatobiliary MRI using gadoxetic acid optimized for 1.5 Tesla. J Magn Reson Imaging 36:890–899. doi:10.1002/jmri.23713

    Article  PubMed  PubMed Central  Google Scholar 

  31. Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M (1988) Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 168:497–505

    Article  PubMed  Google Scholar 

  32. Shah B, Anderson SW, Scalera J, Jara H, Soto JA (2011) Quantitative MR imaging: physical principles and sequence design in abdominal imaging. Radiographics 31:867–880

    Article  PubMed  Google Scholar 

  33. Taouli B, Koh D-M (2010) Diffusion-weighted MR imaging of the liver. Radiology 254:47–66

    Article  PubMed  Google Scholar 

  34. Soyer P, Boudiaf M, Placé V et al (2011) Preoperative detection of hepatic metastases: comparison of diffusion-weighted, T2-weighted fast spin echo and gadolinium-enhanced MR imaging using surgical and histopathologic findings as standard of reference. Eur J Radiol 80:245–252

    Article  PubMed  Google Scholar 

  35. d’Assignies G, Fina P, Bruno O et al (2013) High sensitivity of diffusion-weighted MR imaging for the detection of liver metastases from neuroendocrine tumors: comparison with T2-weighted and dynamic gadolinium-enhanced MR imaging. Radiology 268:390–399

    Article  PubMed  Google Scholar 

  36. Vandecaveye V, De Keyzer F, Verslype C et al (2009) Diffusion-weighted MRI provides additional value to conventional dynamic contrast-enhanced MRI for detection of hepatocellular carcinoma. Eur Radiol 19:2456–2466

    Article  PubMed  Google Scholar 

  37. Vandecaveye V, Dirix P, De Keyzer F et al (2012) Diffusion-weighted magnetic resonance imaging early after chemoradiotherapy to monitor treatment response in head-and-neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys 82:1098–1107

    Article  PubMed  Google Scholar 

  38. Kokabi N, Camacho JC, **ng M et al (2014) Apparent diffusion coefficient quantification as an early imaging biomarker of response and predictor of survival following yttrium-90 radioembolization for unresectable infiltrative hepatocellular carcinoma with portal vein thrombosis. Abdom Imaging 39:969–978

    Article  PubMed  Google Scholar 

  39. Jacobsson H, Larsson P, Jonsson C, Jussing E, Grybäck P (2012) Normal uptake of 68Ga-DOTA-TOC by the pancreas uncinate process mimicking malignancy at somatostatin receptor PET. Clin Nucl Med 37:362–365

    Article  PubMed  Google Scholar 

  40. Al-Ibraheem A, Bundschuh RA, Notni J et al (2011) Focal uptake of 68Ga-DOTATOC in the pancreas: pathological or physiological correlate in patients with neuroendocrine tumours? Eur J Nucl Med Mol Imaging 38:2005–2013

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Avenue-0628, San Francisco, CA, 94143-0628, USA

    Thomas A. Hope, Miguel Hernandez Pampaloni & Robert R. Flavell

  2. Department of Radiology, San Francisco VA Medical Center, San Francisco, CA, USA

    Thomas A. Hope

  3. Division of Surgical Oncology, Department of Surgery, University of California San Francisco, San Francisco, CA, USA

    Eric K. Nakakura

  4. Division of Hematology/Oncology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA

    Emily K. Bergsland

Authors
  1. Thomas A. Hope
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Miguel Hernandez Pampaloni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Robert R. Flavell
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Eric K. Nakakura
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Emily K. Bergsland
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thomas A. Hope.

Ethics declarations

Conflict of interest

Dr. Hope received grant support from Wylie J. Dodds Research Award, Society of Abdominal Radiology, and is on the speakers’ bureau for GE Healthcare. Drs. Pampaloni, Flavell, Nakakura, and Bergsland have no conflicts of interest.

Research involving human participants and/or animals

All procedures performed in studies involving animals were in accordance with the ethical standards of the institution or practice at which the studies were conducted.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hope, T.A., Pampaloni, M.H., Flavell, R.R. et al. Somatostatin receptor PET/MRI for the evaluation of neuroendocrine tumors. Clin Transl Imaging 5, 63–69 (2017). https://doi.org/10.1007/s40336-016-0193-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40336-016-0193-8

Keywords

Search

Navigation