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Case-Based Guide for Image Interpretation and Reporting

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Molecular Imaging of Neurodegenerative Disorders

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Abstract

The brain is the most complex and intriguing part of the human body. Acceleration of neuroscience research and development over the last few decades has given us exciting new technologies to better understand brain function. Imaging modalities have become fundamental tools for the diagnosis and evaluation of brain pathologies, with molecular imaging offering the possibility to image and quantify brain function “in vivo.”

However, functional imaging interpretation can be challenging and requires appropriate training. Single-photon emission tomography (SPECT) and positron emission tomography (PET) possess a lower spatial resolution compared to anatomic imaging methods such as magnetic resonance imaging (MRI). In addition, the introduction of hybrid technologies, which can provide correlative anatomic imaging via CT or MRI into the functional studies, requires additional training.

The intent of this chapter is to provide a rational guide for molecular brain imaging interpretation, which is suitable for all levels of expertise. The content includes a teaching directory with fundamental knowledge, and a tutorial for systematic imaging analysis based on visual assessment as well as semiquantitative analysis. Suggestions for how to adequately report studies in each molecular imaging modality will be presented in a case mode. Clinical situations where molecular imaging can aid in the diagnosis of different neurodegenerative pathologies will be discussed.

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References

  1. Jenkinson M, Chappell M. Introduction to neuroimaging analysis. In: Oxford neuroimaging primers. 1st ed. Oxford: Oxford University Press; 2018.

    Google Scholar 

  2. Haines DE, et al. Neuroanatomy in clinical context: an atlas of structures, sections, systems, and syndromes. 9th ed. Philadelphia: Wolters Kluwer Health; 2015.

    Google Scholar 

  3. Hendelman W. Atlas of functional neuroanatomy. 3rd ed. Boca Raton: CRC Press; 2015.

    Book  Google Scholar 

  4. Lee TC, et al. Netter’s correlative imaging: neuroanatomy. Netter clinical science. Philadelphia, PA: Elsevier Saunders; 2015.

    Google Scholar 

  5. Berger W, Berger J. Neuroanatomy. Case closed! Boca Raton: CRC Press; 2017.

    Book  Google Scholar 

  6. Agarwal N, Port JD. Neuroimaging: anatomy meets function. 1st ed. Cham: Springer International Publishing; 2018.

    Book  Google Scholar 

  7. Splittgerber R, Lippincott W, Wilkins. Snell’s clinical neuroanatomy. 8th ed. Philadelphia: Wolters Kluwer; 2018. p. xxvi, 527 pages: illustrations (black and white, and colour).

    Google Scholar 

  8. Waxman SG, Waxman SG. Clinical neuroanatomy. In: McGraw-Hill’s AccessNeurology. 29th ed. New York: McGraw-Hill Education LLC; 2020.

    Google Scholar 

  9. Berkowitz AL. Clinical neurology and neuroanatomy: a localization-based approach. In: Berkowitz A, editor. Neurology collection. 1st ed. New York, NY: McGraw-Hill Education LLC; 2017.

    Google Scholar 

  10. Martin JH, Martin JH. Neuroanatomy: text and atlas. In: McGraw-Hill’s access neurology. 5th ed. New York: McGraw-Hill Education LLC; 2021.

    Google Scholar 

  11. Bui T, Das JM. Neuroanatomy, cerebral hemisphere. In: StatPearls, StatPearls Publishing Copyright © 2021. Treasure Island, FL: StatPearls Publishing LLC; 2021.

    Google Scholar 

  12. Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human brain: 3-dimensional proportional system: an approach to medical cerebral imaging. Stuttgart/New York: Thieme Thieme Medical; 1988. p. viii, 122 p. : ill. (chiefly col.)

    Google Scholar 

  13. Brock DG, Mancall EL, Gray H. Gray’s Clinical neuroanatomy: the anatomic basis for clinical neuroscience (Clinical neuroanatomy). W B Saunders Company; 2011.

    Google Scholar 

  14. Jacobson S, et al. Neuroanatomy for the neuroscientist. Cham: Springer; 2018.

    Book  Google Scholar 

  15. Van Heertum RL, Tikofsky RS, Ichise M. Functional cerebral SPECT and PET imaging. 4th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2010. p. xvi, 458 pages: illustrations (some color)

    Google Scholar 

  16. Anand KS, Dhikav V. Hippocampus in health and disease: an overview. Ann Indian Acad Neurol. 2012;15(4):239–46.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Vanderah TW, Gould DJ, Ebscohost. Nolte’s the human brain: an introduction to its functional anatomy. In: ClinicalKey. 7th ed. Philadelphia, PA: Elsevier; 2016.

    Google Scholar 

  18. Kenhub. Cerebral cortex. March 14, 2022. https://www.kenhub.com/en/library/anatomy/cerebral-cortex.

  19. Osborn AG. Diagnostic and surgical imaging anatomy: brain, head & neck, spine. London: Amirsys; 2006. 227pages : illustrations (some colour)

    Google Scholar 

  20. Toth P, et al. Functional vascular contributions to cognitive impairment and dementia: mechanisms and consequences of cerebral autoregulatory dysfunction, endothelial impairment, and neurovascular uncoupling in aging. Am J Physiol Heart Circ Physiol. 2017;312(1):H1–H20.

    Article  PubMed  Google Scholar 

  21. Minoshima S, et al. Brain [F-18]FDG PET for clinical dementia workup: differential diagnosis of Alzheimer’s disease and other types of dementing disorders. Semin Nucl Med. 2021;51(3):230–40.

    Article  PubMed  Google Scholar 

  22. Kapucu OL, et al. EANM procedure guideline for brain perfusion SPECT using 99mTc-labelled radiopharmaceuticals, version 2. Eur J Nucl Med Mol Imaging. 2009;36(12):2093–102.

    Article  CAS  PubMed  Google Scholar 

  23. Kung HF, Kung MP, Choi SR. Radiopharmaceuticals for single-photon emission computed tomography brain imaging. Semin Nucl Med. 2003;33(1):2–13.

    Article  PubMed  Google Scholar 

  24. Koyama M, et al. SPECT imaging of normal subjects with technetium-99m-HMPAO and technetium-99m-ECD. J Nucl Med. 1997;38(4):587–92.

    CAS  PubMed  Google Scholar 

  25. Guedj E, et al. EANM procedure guidelines for brain PET imaging using [(18)F]FDG, version 3. Eur J Nucl Med Mol Imaging. 2022;49(2):632–51.

    Article  PubMed  Google Scholar 

  26. Berti V, Mosconi L, Pupi A. Brain: normal variations and benign findings in fluorodeoxyglucose-PET/computed tomography imaging. PET Clin. 2014;9(2):129–40.

    Article  PubMed  Google Scholar 

  27. Saroja SR, et al. Differential expression of tau species and the association with cognitive decline and synaptic loss in Alzheimer’s disease. Alzheimers Dement. 2022;18(9):1602–15.

    Article  CAS  PubMed  Google Scholar 

  28. Minoshima S, et al. SNMMI procedure standard/EANM practice guideline for amyloid PET imaging of the brain 1.0. J Nucl Med. 2016;57(8):1316–22.

    Article  CAS  PubMed  Google Scholar 

  29. Bischof GN, et al. Impact of tau and amyloid burden on glucose metabolism in Alzheimer’s disease. Ann Clin Transl Neurol. 2016;3(12):934–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Bejanin A, et al. Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer’s disease. Brain. 2017;140(12):3286–300.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Ricci M, et al. Tau biomarkers in dementia: positron emission tomography radiopharmaceuticals in tauopathy assessment and future perspective. Int J Mol Sci. 2021;22(23)

    Google Scholar 

  32. Tian M, et al. International consensus on the use of tau PET imaging agent (18)F-flortaucipir in Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2022;49(3):895–904.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Mattay VS, et al. Brain tau imaging: Food and Drug Administration approval of (18)F-flortaucipir injection. J Nucl Med. 2020;61(10):1411–2.

    Article  PubMed  Google Scholar 

  34. Bischof GN, et al. Clinical validity of second-generation tau PET tracers as biomarkers for Alzheimer’s disease in the context of a structured 5-phase development framework. Eur J Nucl Med Mol Imaging. 2021;48(7):2110–20.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Scholl M, et al. PET imaging of tau deposition in the aging human brain. Neuron. 2016;89(5):971–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Eshuis SA, et al. Comparison of FP-CIT SPECT with F-DOPA PET in patients with de novo and advanced Parkinson’s disease. Eur J Nucl Med Mol Imaging. 2006;33(2):200–9.

    Article  CAS  PubMed  Google Scholar 

  37. Morbelli S, et al. EANM practice guideline/SNMMI procedure standard for dopaminergic imaging in Parkinsonian syndromes 1.0. Eur J Nucl Med Mol Imaging. 2020;47(8):1885–912.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zhang K, et al. PET imaging of neural activity, beta-amyloid, and tau in normal brain aging. Eur J Nucl Med Mol Imaging. 2021;48(12):3859–71.

    Article  CAS  PubMed  Google Scholar 

  39. Silverman D, Silverman D. PET in the evaluation of Alzheimer’s disease and related disorders. 1st ed. New York: Springer; 2009.

    Book  Google Scholar 

  40. Varrone A, et al. European multicentre database of healthy controls for [123I]FP-CIT SPECT (ENC-DAT): age-related effects, gender differences and evaluation of different methods of analysis. Eur J Nucl Med Mol Imaging. 2013;40(2):213–27.

    Article  CAS  PubMed  Google Scholar 

  41. Parkinson Progression Marker Initiative. The Parkinson Progression Marker Initiative (PPMI). Prog Neurobiol. 2011;95(4):629–35.

    Article  Google Scholar 

  42. Burns CM, et al. Higher serum glucose levels are associated with cerebral hypometabolism in Alzheimer regions. Neurology. 2013;80(17):1557–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Juni JE, et al. Procedure guideline for brain perfusion SPECT using (99m)Tc radiopharmaceuticals 3.0. J Nucl Med Technol. 2009;37(3):191–5.

    Article  PubMed  Google Scholar 

  44. Salmon E, Bernard Ir C, Hustinx R. Pitfalls and limitations of PET/CT in brain imaging. Semin Nucl Med. 2015;45(6):541–51.

    Article  PubMed  Google Scholar 

  45. Kim J, et al. Usefulness of 3-dimensional stereotactic surface projection FDG PET images for the diagnosis of dementia. Medicine (Baltimore). 2016;95(49):e5622.

    Article  PubMed  Google Scholar 

  46. Brown RK, et al. Brain PET in suspected dementia: patterns of altered FDG metabolism. Radiographics. 2014;34(3):684–701.

    Article  PubMed  Google Scholar 

  47. Minoshima S, et al. A diagnostic approach in Alzheimer's disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med. 1995;36(7):1238–48.

    CAS  PubMed  Google Scholar 

  48. Minoshima S, et al. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol. 1997;42(1):85–94.

    Article  CAS  PubMed  Google Scholar 

  49. Kim EJ, et al. Glucose metabolism in early onset versus late onset Alzheimer’s disease: an SPM analysis of 120 patients. Brain. 2005;128(Pt 8):1790–801.

    Article  CAS  PubMed  Google Scholar 

  50. Johnson KA, et al. Appropriate use criteria for amyloid PET: a report of the Amyloid Imaging Task Force, the Society of Nuclear Medicine and Molecular Imaging, and the Alzheimer’s Association. J Nucl Med. 2013;54(3):476–90.

    Article  CAS  PubMed  Google Scholar 

  51. Rowe CC, Villemagne VL. Brain amyloid imaging. J Nucl Med. 2011;52(11):1733–40.

    Article  CAS  PubMed  Google Scholar 

  52. Amyvid (florbetapir F 18 Injection) Leaflet. 2012. https://www.accessdata.fda.gov/drugsatfda_docs/label/2012/202008s000lbl.pdf.

  53. Jie C, et al. Tauvid: the first FDA-approved PET tracer for imaging tau pathology in Alzheimer’s disease. Pharmaceuticals (Basel). 2021;14(2)

    Google Scholar 

  54. Brendel M, et al. Assessment of 18F-PI-2620 as a biomarker in progressive supranuclear palsy. JAMA Neurol. 2020;77(11):1408–19.

    Article  PubMed  Google Scholar 

  55. Mueller A, et al. Tau PET imaging with (18)F-PI-2620 in patients with Alzheimer disease and healthy controls: a first-in-humans study. J Nucl Med. 2020;61(6):911–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Sonni I, et al. Evaluation of a visual interpretation method for tau-PET with (18)F-flortaucipir. Alzheimers Dement (Amst). 2020;12(1):e12133.

    PubMed  Google Scholar 

  57. Eli Lilly and Company. TAUVID TM (flortaucipir F 18 injection) Leaflet. 2020. https://pi.lilly.com/us/tauvid-uspi.pdf.

  58. Langston JW, Wiley JC, Tagliati M. Optimizing Parkinson’s disease diagnosis: the role of a dual nuclear imaging algorithm. NPJ Parkinsons Dis. 2018;4:5.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Marek K, et al. Longitudinal follow-up of SWEDD subjects in the PRECEPT study. Neurology. 2014;82(20):1791–7.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Waxman AD, Lewis DH, Herscovitch P, Minoshima S, Ichise M, Drzezga AE, Devous MD, Mountz JM. Society of Nuclear Medicine procedure guideline for FDG PET brain imaging 1.0; 2009.

    Google Scholar 

  61. Li CH, et al. Frontal variant of Alzheimer’s disease with asymmetric presentation mimicking frontotemporal dementia: case report and literature review. Brain Behav. 2020;10(3):e01548.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Ossenkoppele R, et al. Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. JAMA. 2015;313(19):1939–49.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Whitwell JL, et al. (18)F-FDG PET in posterior cortical atrophy and dementia with Lewy bodies. J Nucl Med. 2017;58(4):632–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Minoshima S, Cross D, Thientunyakit T, Foster NL, Drzezga A. 18F-FDG PET imaging in neurodegenerative dementing disorders: insights into subtype classification, emerging disease categories, and mixed dementia with copathologies. J Nucl Med. 2022;63(Suppl 1):2S–12S.

    Article  CAS  PubMed  Google Scholar 

  65. Chandran V, Stoessl AJ. Imaging in multiple system atrophy. Neurol Clin Neurosci. 2014;2:178–87. https://doi.org/10.1111/ncn3.125.

    Article  Google Scholar 

  66. Shivamurthy VKN, Tahari AK, Marcus C, Subramaniam RM. Brain FDG PET and the diagnosis of dementia. Am J Roentgenol. 2015;204(1):W76–85.

    Article  Google Scholar 

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Acknowledgments

The authors would like to thank Drs. Kazunari Ishii (Kindai University, Japan), Ming-Kai Chen (Yale University, USA), Chakmeedaj Sethanandha (Mahidol University, Thailand), Jan Booij (University of Amsterdam, Holland), and Victor Villemagne (University of Melbourne, Australia) for contributing the images and cases for this chapter.

Author information

Authors and Affiliations

  1. Department of Nuclear Medicine, Hospital das Forças Armadas (HFA), Brasilia, Distrito Federal, Brazil

    Karina Mosci

  2. Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand

    Tanyaluck Thientunyakit

  3. Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA

    Donna J. Cross & Satoshi Minoshima

  4. Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany

    Gérard N. Bischof

  5. Molecular Organization of the Brain, Institute for Neuroscience and Medicine (INM-2), Jülich, Germany

    Gérard N. Bischof

  6. Department of Nuclear Medicine, Clínica Universidad de Navarra, Pamplona, Navarra, Spain

    Javier Arbizu

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  1. Karina Mosci
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  2. Tanyaluck Thientunyakit
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  3. Donna J. Cross
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  4. Gérard N. Bischof
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  5. Javier Arbizu
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  6. Satoshi Minoshima
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Corresponding author

Correspondence to Karina Mosci .

Editor information

Editors and Affiliations

  1. Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA

    Donna J. Cross

  2. Department of Nuclear Medicine, Hospital das Forças Armadas (HFA), Brasilia, Distrito Federal, Brazil

    Karina Mosci

  3. Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA

    Satoshi Minoshima

Appendix

Appendix

MR Atlas

The images presented are from a healthy middle-aged male subject, acquired on a GE SIGNA Pioneer 3.0T MRI scanner. Each page contains images in axial plane from top-to-bottom, demonstrating the structures whose recognition is essential in the interpretation of a molecular imaging scan.

2 M R I of the axial views of the brain has the following labels. The frontal lobe, precentral gyrus, postcentral gyrus, central sulcus, and parietal lobe.
2 M R I of the axial views of the brain has the following labels. The frontal lobe, cingulate cortex, precuneus, and parietal lobe.
2 M R I scans. They illustrate the axial views of the brain. It is labeled frontal lobe, parietal lobe, parietal-occipital sulcus, caudate nucleus, lateral ventricle, cingulate cortex, precuneus, thalamus, occipital lobe, insular cortex, corpus callosum, and insular cortex.
2 M R I scans. They illustrate the axial views of the brain. It is labeled frontal lobe, caudate nucleus, insular cortex, third ventricle, temporal lobe, internal capsule, lentiform nucleus, lateral ventricle, thalamus, and occipital lobe.
2 M R I scans. It illustrates the axial views of the brain. It is labeled frontal lobe, third ventricle, temporal lobe, occipital lobe, caudate nucleus, lentiform nucleus, thalamus, lateral ventricle, cerebellum, Sylvian fissure, and midbrain.
2 M R I scans. They illustrate the horizontal plane of the brain. It is labeled temporal lobe, midbrain, cerebellum, hippocampus plus amygdala, cerebral aqueduct, and occipital lobe.
2 M R I scans. They illustrate the horizontal plane of the brain. The labels read temporal lobe, occipital lobe, pons, fourth ventricle, and cerebellum.

FDG Atlas

The images presented are from a healthy cognitively normal middle-aged female subject, acquired on a PET/CT (Discovery PET/CT scanner). The PET images were co-registered to the patient’s MR acquired in a 3T MR system (Ingenia, Philips Medical system). Each page contains images in axial plane from top-to-bottom, demonstrating the structures whose recognition is essential in the interpretation of a molecular imaging scan.

Images courtesy from Dr. Chakmeedaj Sethanandha, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

4 P E T scans. They illusterate of the axial views of the brain. The labels are the frontal lobe, parietal lobe, and central sulcus.
4 P E T scans. They illustrate the axial views of the brain. The labels are the frontal lobe, central sulcus, parietal lobe, postcentral gyrus, precentral gyrus, white matter, grey matter, and primary sensorimotor cortex.
8 P E T scans. They illusterate the axial views of the brain. The labels are the frontal lobe, parietal lobe, precuneus, white matter, lateral ventricle, and posterior cingulate.
8 P E T scans. They illustrate the axial views of the brain. The labels are the frontal lobe, thalamus, midbrain, temporal lobe, occipital lobe, primary visual cortex, lateral ventricle, putamen, cuneus, and caudate.
8 P E T scans. They illustrate the axial views of the brain. The labels are the frontal lobe, midbrain, temporal lobe, occipital lobe, cerebellar vermis, caudate, pons, cerebellum, and hippocampus.
4 P E T scans. They illustrate the axial views of the brain. The labels are the frontal lobe, pons, temporal lobe, and cerebellum.

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Mosci, K., Thientunyakit, T., Cross, D.J., Bischof, G.N., Arbizu, J., Minoshima, S. (2023). Case-Based Guide for Image Interpretation and Reporting. In: Cross, D.J., Mosci, K., Minoshima, S. (eds) Molecular Imaging of Neurodegenerative Disorders. Springer, Cham. https://doi.org/10.1007/978-3-031-35098-6_17

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