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Volumetric brain correlates of approach-avoidance behavior and their relation to chronic back pain

  • Frauke NeesEmail author
  • Michaela Ruttorf
  • Xaver Fuchs
  • Mariela Rance
  • Nicole Beyer
Original Research
  • 35 Downloads

Abstract

Avoiding any harm, such as painful experiences, is an important ability for our physical and mental health. This avoidance behavior might be overactive under chronic pain, and the cortical and subcortical brain volumetry, which also often changes in chronic pain states, might be a significant correlate of this behavior. In the present study, we thus investigated the association between volumetric brain differences using 3 T structural magnetic resonance imaging and pain- versus pleasure-related approach-avoidance behavior using an Approach Avoidance Task in the laboratory in chronic back pain (N = 42; mean age: 51.34 years; 23 female) and healthy individuals (N = 43; mean age: 45.21 years; 15 female). We found significant differences in hippocampal, amygdala and accumbens volumes in patients compared to controls. The patients` hippocampal volume was significantly positively related to pain avoidance, the amygdala volume to positive approach, and the accumbens volume negatively to a bias to pain avoidance over positive approach. These associations were significantly moderated by pain symptom duration. Cortical structure may thus contribute to an overacting pain avoidance system in chronic back pain, and could, together with a reduction in approaching positive stimuli, be related to maladaptive choice and decision-making processes in chronic pain.

Keywords

Approach Avoidance Brain volume Chronic pain Striatal-limbic 

Notes

Funding

This study was funded by the Deutsche Forschungsgemeinschaft (NE 1383/6–1 to F.N., SFB1158/B03 to F.N. and Herta Flor, and NE 1383/14–1).

Compliance with ethical standards

Conflict of interest

All authors declare no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

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

Supplementary material

11682_2019_110_MOESM1_ESM.docx (966 kb)
ESM 1 (DOCX 965 kb)

References

  1. Acevedo, B., Aron, E., Pospos, S., Jessen, D. (2018). The functional highly sensitive brain: A review oft he brain circuits underlying sensory processing sensitivity and seemingly related disorders. Philos. Trans. R. Soc. Lond. B. Biol. Sci., 373:Pii, 20170161.Google Scholar
  2. Affleck, G., Tennen, H., Zautra, A., Urrows, S., Abeles, M., & Karoly, P. (2001). Women’s pursuit of personal goals in daily life with fibromyalgia: A value-expectancy analysis. Journal of Consulting and Clinical Psychology, 69, 587–596.CrossRefGoogle Scholar
  3. Apkarian, V., Bushnell, M. C., Treede, R.-D., & Zubieta, J.-K. (2005). Human brain mechanisms of pain perception and regulation in health and disease. European Journal of Pain, 9, 463–484.CrossRefGoogle Scholar
  4. Apkarian, A. V., Hashmi, J. A., & Baliki, M. N. (2011). Pain and the brain: Specificity and plasticity of the brain in clinical chronic pain. Pain, 152, S49–S64.CrossRefGoogle Scholar
  5. Apkarian, A. V., Mutso, A. A., Centeno, M. V., Kann, L., Wu, M., Levinstein, M., et al. (2016). Role of adult hippocampal neurogenesis in persistent pain. Pain, 157, 418–428.CrossRefGoogle Scholar
  6. Baliki, M. N., Geha, P. Y., Fields, H. L., & Apkarian, A. V. (2010). Predicting value of pain and analgesia: Nucleus accumbens response to noxious stimuli changes in the presence of chronic pain. Neuron, 66, 149–160.CrossRefGoogle Scholar
  7. Barad, M. J., Ueno, T., Younger, J., Chatterjee, N., & Mackey, S. (2014). Complex regional pain syndrome is associated with structural abnormalities in pain-related regions of the human brain. The Journal of Pain, 15, 197–203.CrossRefGoogle Scholar
  8. Berger, S. E., Vachon-Presseau, E., Abdullah, T. B., Baria, A. T., Schnitzer, T. J., & Apkarian, A. V. (2018). Hippocampal morphology mediates biased memories of chronic pain. Neuroimage, 166, 86–98.CrossRefGoogle Scholar
  9. Berrdige, K. C., & Kringelbach, M. L. (2008). Affective neuroscience of pleasure: Reward in humans and animals. Psychopharmacology, 199, 457–480.CrossRefGoogle Scholar
  10. Bishop, J. H., Shpaner, M., Kubicki, A., Clements, S., Watts, R., & Naylor, M. R. (2018). Structural network differences in chronic muskuloskeletal pain: Beyond fractional anisotropy. Neuroimage, 182, 441–455.CrossRefGoogle Scholar
  11. Borszcz, G. S., & Streltsov, N. G. (2000). Amygdaloid-thalamic interactions mediate the antinociceptive action of morphine microinjected into the periaqueductal gray. Behavioral Neuroscience, 114, 574–584.CrossRefGoogle Scholar
  12. Büchel, C., Morris, J., Dolan, R. J., & Friston, K. J. (1998). Brain systems mediating aversive conditioning: An event-related fMRI study. Neuron, 20, 947–957.CrossRefGoogle Scholar
  13. Buckner, R. L., Head, D., Parker, J., Fotenos, A. F., Marcus, D., Morris, J. C., & Snyder, A. Z. (2004). A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: Reliability and validation against manual measurement of total intracranial volume. Neuroimage, 23, 724–738.CrossRefGoogle Scholar
  14. Coppieters, I., Meeus, M., Kregel, J., Caeyenberghs, K., de Pauw, R., Goubert, D., & Cagnie, B. (2016). Relations between brain alterations and clinical pain measures in chronic musculoskeletal pain: A systematic review. The Journal of Pain, 17, 949–962.CrossRefGoogle Scholar
  15. Davidson, R. J. (1983). Hemispheric specialization for cognition and affect. In A. Gale & J. Edwards (Eds.), Physiological correlates of human behavior (pp. 320–365). London: Academic Press.Google Scholar
  16. Davidson, R. J. (1992). Anterior cerebral asymmetry and the nature of emotion. Brain and Cognition, 20, 125–151.CrossRefGoogle Scholar
  17. Davis, M., & Shi, C. (2000). The amygdala. Current Biology, 10, R131.CrossRefGoogle Scholar
  18. Delgado, M. R., Nystrom, L. E., Fissell, C., Noll, D. C., & Fiez, J. A. (2000). Tracking the hemodynamic responses to reward and punishment in the striatum. Journal of Neurophysiology, 84, 3072–3077.CrossRefGoogle Scholar
  19. van den Bos, W., Rodriguez, C. A., Schweitzer, J. B., & McClure, S. M. (2014). Connectivity strength of dissociable striatal tracts predict individual differences in temporal discounting. The Journal of Neuroscience, 34, 10298–10310.CrossRefGoogle Scholar
  20. Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., Albert, M. S., & Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31, 968–980.CrossRefGoogle Scholar
  21. Eccleston, C., & Crombez, G. (1999). Pain demands attention: A cognitive-affective model of the interruptive function of pain. Psychological Bulletin, 125, 356–366.CrossRefGoogle Scholar
  22. Egli, M., Koob, G. F., & Edwards, S. (2012). Alcohol dependence as a chronic pain disorder. Neuroscience and Biobehavioral Reviews, 36, 2179–2192.CrossRefGoogle Scholar
  23. Elman, I., Borsook, D., & Volkow, N. D. (2013). Pain and suicidality: Insights from reward and addiction neuroscience. Progress in Neurobiology, 109, 1–27.CrossRefGoogle Scholar
  24. Euston, D. R., Gruber, A. J., & McNaughton, B. L. (2012). The role of medial prefrontal cortex in memory and decision making. Neuron, 76, 1057–1070.CrossRefGoogle Scholar
  25. Fields, H. L. (2000). Pain modulation: Expectation, opioid analgesia and virtual pain. Progress in Brain Research, 122, 245–253.CrossRefGoogle Scholar
  26. First, M. B., Gibbon, M., Spitzer, R. L., & Williams, J. B. W. (1997). Structured clinical interview for DSM-IV Axis I disorders (SCID-I). Arlington: American Psychiatric Publishing.Google Scholar
  27. Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences of the United States of America, 97, 11050–11055.CrossRefGoogle Scholar
  28. Fischl, B., Sereno, M. I., & Dale, A. M. (1999). Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage, 9, 195–207.CrossRefGoogle Scholar
  29. Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., & Dale, A. M. (2002). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33, 341–355.CrossRefGoogle Scholar
  30. Flor, H., & Birbaumer, N. (1994). Psychobiologie und interdisziplinäre Therapie chronischer Wirbelsäulensyndrome. [psychobiology and interdisciplinary treatment of chronic back pain]. München: GSF Forschungszentrum.Google Scholar
  31. Flor, H., Rudy, T. E., Birbaumer, N., Streit, B., & Schugens, M. M. (1990). Zur Anwendbarkeit des west haven-Yale multidimensional pain inventory im deutschen Sprachraum: Daten zur Reliabilität und Validität des MPI-D [the applicability of the west haven-Yale multidimensional pain inventory in German-speaking countries: Data on the reliability and validity of the MPI-D]. Der Schmerz., 4, 82–87.CrossRefGoogle Scholar
  32. Fonzo, G. A., & Etkin, A. (2017). Affective neuroimaging in generalized anxiety diosrder: An integrated review. Dialogues in Clinical Neuroscience, 19, 169–179.Google Scholar
  33. Gandhi, W., Becker, S., & Schweinhart, P. (2013). Pain increases motivational drive to obtain reward, but does not affect associated hedonic responses: A behavioural study in healthy volunteers. European Journal of Pain, 17, 1093–1103.CrossRefGoogle Scholar
  34. Gatzounis, R., Schrooten, M. G., Crombez, G., & Vlaeyen, J. W. (2014). Interrupted by pain: An anatomy of pain-contingent activity interruptions. Pain, 155, 1192–1195.CrossRefGoogle Scholar
  35. Geissner, E. (1995). Die Schmerzempfindungs-Skala SES [the pain intensity scale SES]. Göttingen: Hogrefe.Google Scholar
  36. Gupta, A., Love, A., Kilpatrick, L. A., Labus, J. S., Bhatt, R., Chang, L., Tillisch, K., Naliboff, B., & Mayer, E. A. (2017). Morphological barin measures of cortico-limbic inhibiton related to resilience. Journal of Neuroscience Research, 95, 1760–1775.CrossRefGoogle Scholar
  37. Harmon-Jones, E. (2004). Contributions from research on anger and cognitive dissonance to understanding the motivational functions of asymmetrical frontal brain activity. Biological Psychology, 67, 51–76.CrossRefGoogle Scholar
  38. Harmon-Jones, E., & Allen, J. J. (1997). Behavioral activation sensitivity and resting frontal EEG asymmetry: Covariation of putative indicators related to risk for mood disorders. Journal of Abnormal Psychology, 106, 159–163.CrossRefGoogle Scholar
  39. Harmon-Jones, E., Gable, P. A., & Peterson, C. K. (2010). The role of asymmetric frontal cortical activity in emotion-related phenomena: A review and update. Biological Psychology, 84, 451–462.CrossRefGoogle Scholar
  40. Hashmi, J. A., Baliki, M. N., Huang, L., Baria, A. T., Torbey, S., Hermann, K. M., Schnitzer, T. J., & Apkarian, A. V. (2013). Shape shifting pain: Chronification of back pain shifts brain representation from nociceptive to emotional circuit. Brain, 136, 2751–2768.CrossRefGoogle Scholar
  41. Hautzinger, M., & Bailer, M. (1993). Allgemeine Depressionsskala [General Depression Scale]. Göttingen: Hogrefe Testzentrale.Google Scholar
  42. Hofmann, S. G., & Hay, A. C. (2018). Rethinking avoidance: Toward a balanced approach to avoidance in treating anxiety disorders. Journal of Anxiety Disorders, 55, 14–21.CrossRefGoogle Scholar
  43. Ikeda, E., Li, T., Kobinata, H., Zhang, S., & Kurata, J. (2018). Anterior insular volume decrease is associated with dysfunction of the reward system in patients with chronic pain. European Journal of Pain, 22, 1170–1179.CrossRefGoogle Scholar
  44. Jackson, P. L., Meltzoff, A. N., & Decety, J. (2005). How do we perceive the pain of others? A window into the neural processes involved in empathy. NeuroImage, 24, 771–779.CrossRefGoogle Scholar
  45. Ji, G., Sun, H., Fu, Y., Li, Z., Pais-Vieira, M., Galhardo, V., & Neugebauer, V. (2010). Cognitive impairment in pain through amygdala-driven prefrontal cortical deactivation. The Journal of Neuroscience, 30, 5451–5464.CrossRefGoogle Scholar
  46. Kamping, S., Bomba, I. C., Kanske, P., Diesch, E., & Flor, H. (2013). Deficient modulation of pain by a positive emotional context in fibromyalgia patients. Pain, 154, 1846–1855.CrossRefGoogle Scholar
  47. Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001). Anticipation of increasing monetary reward selectively recruits nucleus accumbens. The Journal of Neuroscience, 21, RC159.CrossRefGoogle Scholar
  48. Kreitzer, A. C., & Malenka, R. C. (2008). Striatal plasticity and basal ganglia circuit function. Neuron, 60, 543–554.CrossRefGoogle Scholar
  49. Kuperberg, G. R., Broome, M. R., McGuire, P. K., David, A. S., Eddy, M., Ozawa, F., Goff, D., West, W. C., Williams, S. C. R., van der Kouwe, A. J. W., Salat, D. H., Dale, A. M., & Fischl, B. (2003). Regionally localized thinning of the cerebral cortex in schizophrenia. Archives of General Psychiatry, 60, 878–888.CrossRefGoogle Scholar
  50. LaBar, K. S., & Disterhoft, J. F. (1998). Conditioning, awareness, and the hippocampus. Hippocampus, 8, 620–626.CrossRefGoogle Scholar
  51. Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2008). International affective picture system (IAPS): Affective ratings of pictures and instruction manual (Technical report A-8). Gainesville, FL: University of Florida.Google Scholar
  52. Laux, L., Glanzmann, P., Schaffner, P., & Spielberger, C. D. (1981). Das state-trait-angst-Inventar (STAI) [state-trait anxiety inventory]. Beltz Verlagsgesellschaft: Weinheim.Google Scholar
  53. LeDoux, J. (1996). Emotional networks and motor control: A fearful view. Progress in Brain Research, 107, 437–446.CrossRefGoogle Scholar
  54. LeDoux, J. E. (2000). Emotion circuits in the brain. Annual Review of Neuroscience, 23, 155–184.CrossRefGoogle Scholar
  55. Leknes, S., & Tracey, I. (2008). A common neurobiology for pain and pleasure. Nature Reviews. Neuroscience, 9, 314–320.CrossRefGoogle Scholar
  56. Lloyd, D. M., Helbig, T., Findlay, G., Roberts, N., & Nurmikko, T. (2016). Brain areas involved in anticipation of clinically relevant pain in low Back pain populations with high levels of pain behavior. The Journal of Pain, 17, 577–587.CrossRefGoogle Scholar
  57. Mao, C., Wie, L., Zhang, Q., Liao, X., Yang, X., & Zhang, M. (2013). Differences in brain structure in patients with distinct sites of chronic pain: A voxel-based morphometric analysis. Neural Regeneration Research, 8, 2981–2990.Google Scholar
  58. Matsuo, Y., Kurata, J., Sekiguchi, M., Yoshida, K., Nikaido, T., & Konno, S. I. (2017). Attenuation of cortical activity triggering descending pain inhibition in chronic low back pain patients: A functional magnetic resonance imaging study. Journal of Anesthesia, 31, 523–530.CrossRefGoogle Scholar
  59. May, E. S., Nickel, M. M., Ta Dinh, S., Tiemann, L., Heitmann, H., Voth, I., Tölle, T. R., Gross, J., & Ploner, M. (2019). Prefrontal gamma oscillations reflect ongoing pain intensity in chronic back pain patients. Human Brain Mapping, 40, 293–305.CrossRefGoogle Scholar
  60. McCracken, L. M., & Keogh, E. (2009). Acceptnce, mindfulness, and values-based action may counteract fear and avoidance of emotions in chronic pain: An analysis of anxiety sensitivity. The Journal of Pain, 10, 408–415.CrossRefGoogle Scholar
  61. McNaughton, D. B. (2000). A synthesis of qualitative home visiting research. Public Health Nursing, 17, 405–414.CrossRefGoogle Scholar
  62. Nees, F., Becker, S., Millenet, S., Banaschewski, T., Poustka, L., Bokde, A. U., et al. (2017). Brain substrates of reward processing and the μ-opioid receptor: A pathway into pain? Pain, 158, 212–219.CrossRefGoogle Scholar
  63. Nees, F., Witt, S. H., & Flor, H. (2018). Neurogenetic approaches to stress and fear in humans as pathophysiological mechanisms for posttraumatic stress disorder. Biological Psychiatry, 83, 810–820.CrossRefGoogle Scholar
  64. Ochsner, K. N., & Barrett, L. F. (2001). A multiprocess perspective on the neuroscience of emotion. In T. Mayne & G. Bonnano (Eds.), Emotions: Current issues and future Direcitons (pp. 38–81). New York: Guilford Press.Google Scholar
  65. Phelps, E. A., O'Connor, K. J., Gatenby, J. C., Gore, J. C., Grillon, C., & Davis, M. (2001). Activation of the left amygdala to a cognitive representation of fear. Nature Neuroscience, 4, 437–441.CrossRefGoogle Scholar
  66. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879–891.CrossRefGoogle Scholar
  67. Rinck, M., & Becker, E. S. (2007). Approach and avoidance in fear of spiders. Journal of Behavior Therapy and Experimental Psychiatry, 38, 105–120.CrossRefGoogle Scholar
  68. Rodriguez-Raecke, R., Niemeier, A., Ihle, K., Ruether, W., & May, A. (2009). Brain gray matter decrease in chronic pain is the consequence and not the cause of pain. J Neurosci, 29, 13746–13750.CrossRefGoogle Scholar
  69. Rosas, H. D., Hevelone, N. D., Zaleta, a. K., Greve, D. N., Salat, D. H., & Fischl, B. (2005). Regional cortical thinning in preclinical Huntington disease and its relationship to cognition. Neurology, 65, 745–747.CrossRefGoogle Scholar
  70. Schmidt-Wilcke, T., Luerding, R., Weigand, T., Jürgens, T., Schuierer, G., Leinisch, E., & Bogdahn, U. (2007). Striatal grey matter increase in patients suffering from fibromyalgia–a voxel-based morphometry study. Pain, 132, S109–S116.CrossRefGoogle Scholar
  71. Schwartz, N., Miller, C., & Fields, H. L. (2017). Cortico-Accumbens regulation of approach-avoidance behavior is modified by experience and chronic pain. Cell Reports, 19, 1522–1531.CrossRefGoogle Scholar
  72. Schwedt, T. J., Schlaggar, B. L., Mar, S., Nolan, T., Coalson, R. S., Nardos, B., Benzinger, T., & Larson-Prior, L. J. (2013). Atypical restingstate functional connectivity of affective pain regions in chronic migraine. Headache, 53, 737–751.CrossRefGoogle Scholar
  73. Segall, J. M., Allen, E. A., Jung, R. E., Erhardt, E. B., Arja, S. K., Kiehl, K., et al. (2012). Correspondence between structure and function in the human brain at rest. Frontiers in Neuroinformatics, 6, 10.CrossRefGoogle Scholar
  74. Seminowicz, D. A., Labus, J. S., Bueller, J. A., Tillisch, K., Naliboff, B. D., Bushnell, M. C., & Mayer, E. A. (2010). Regional gray matter density changes in brains of patients with irritable bowel syndrome. Gastroenterology, 139, 48–57.e2.CrossRefGoogle Scholar
  75. Seymour, B., O'Doherty, J. P., Koltzenburg, M., Wiech, K., Frackowiak, R., Friston, K., & Dolan, R. (2005). Opponent appetitive-aversive neural processes underlie predicttive learning of pain relief. Nature Neuroscience, 8, 1234–1240.CrossRefGoogle Scholar
  76. Strauman, T. J., Detloff, A. M., Sestokas, R., Smith, D. V., Goetz, E. L., Rivera, C., & Kwapil, L. (2012). What shall I be, what must I be: Neural correlates of personal goal activation. Frontiers in Integrative Neuroscience, 6, 123.Google Scholar
  77. Sutton, S. K., & Davidson, R. J. (1997). Prefrontal brain asymmetry: A biological substrate of the behavioral approach and inhibition systems. Psychological Science, 8, 201–204.CrossRefGoogle Scholar
  78. Talmi, D., Dayan, P., Kiebel, S. J., Frith, C. D., & Dolan, R. J. (2009). How humans integrate the prospects of pain and reward during choice. The Journal of Neuroscience, 29, 14617–14626.CrossRefGoogle Scholar
  79. Updegraff, J. A., Gable, S. L., & Taylor, S. E. (2004). What makes experiences satisfying? The interaction of approach-avoidance motivations and emotions in well-being. Journal of Personality and Social Psychology, 86, 496–504.CrossRefGoogle Scholar
  80. Verkerk, K., Luijsterburg, P. A., Heymans, M. W., Ronchetti, I., Pool-Goudzwaard, A. L., Miedema, H. S., et al. (2013). Prognosis and course of disability in patients with chronic nonspecific low back pain: A 5- and 12-month follow-up cohort study. Physical Therapy, 93, 1603–1614.CrossRefGoogle Scholar
  81. Vlaeyen, J. W., & Linton, S. J. (2000). Fear-avoidance and its consequences in chronic musculoskeletal pain: A state of the art. Pain, 85, 317–332.CrossRefGoogle Scholar
  82. Wang, X., Baeken, C., Fang, M., Qiu, J., Chen, H., & Wu, G. R. (2018). Predicting trait-like individual differences in fear of pain in the healthy state using gray matter volume. Brain Imaging Behavior.  https://doi.org/10.1007/s11682-018-9960-7.
  83. Wittchen, H. U., Zaudig, M., & Fydrich, T. (1997). Strukturiertes Klinisches interview für DSM-IV [structural clinical interview for DSM-IV Axis I disorders]. Göttingen: Hogrefe.Google Scholar
  84. Yuan, C., Shi, H., Pan, P., Dai, Z., Zhong, J., Ma, H., & Sheng, L. (2017). Gray matter abnormalities associated with chronic Back pain: A meta-analysis of voxel-based morphometric studies. The Clinical Journal of Pain, 33, 983–990.CrossRefGoogle Scholar
  85. Ziv, M., Tomer, R., Defrin, R., & Hendler, T. (2010). Individual sensitivity to pain expectancy is related to differential activation of the Hippocampus and amygdala. Human Brain Mapping, 31, 326–338.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Frauke Nees
    • 1
    Email author
  • Michaela Ruttorf
    • 2
  • Xaver Fuchs
    • 1
  • Mariela Rance
    • 3
  • Nicole Beyer
    • 1
  1. 1.Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
  2. 2.Computer Assisted Clinical Medicine, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
  3. 3.Department of Radiology and Biomedical ImagingYale UniversityNew HavenUSA

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