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Chemotherapy-induced brain changes in breast cancer survivors: evaluation with multimodality magnetic resonance imaging

  • Yun Feng
  • Xiao Dong Zhang
  • Gang Zheng
  • Long Jiang ZhangEmail author
REVIEW ARTICLE
  • 79 Downloads

Abstract

Chemotherapy related cognitive impairments are common in breast cancer patients undergoing chemotherapy. These cognitive dysfunctions are mainly attributable to chemotherapy related brain structural and functional alterations. Multimodality magnetic resonance imaging (MRI) can reveal brain gray matter volume loss, white matter microstructural disruption, reduced gray matter density, impaired cerebral blood flow and brain structural and functional connection networks at both local and global levels. This review outlines the potential applications of multimodality MR imaging techniques in chemotherapy induced cognitive deficit in breast cancer survivors and provides future research perspective in this field.

Keywords

Functional magnetic resonance imaging Cognitive impairment Breast cancer Chemotherapy MR imaging techniques 

Abbreviations

MRI

Magnetic resonance imaging

BOLD

Blood oxygen level dependent

fMRI

Functional MRI

VBM

Voxel-based morphological

DTI

Diffusion tensor imaging

ASL

Arterial spin labeling

CRCI

Chemotherapy related cognitive impairment

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval and informed consent

This is a review article and therefore does not contain any new data from studies with human participants or animals performed by any of the authors.

Supplementary material

11682_2019_74_MOESM1_ESM.docx (30 kb)
ESM 1 (DOCX 29.9 kb)

References

  1. Abraham, J., Haut, M. W., Moran, M. T., Filburn, S., Lemiuex, S., & Kuwabara, H. (2008). Adjuvant chemotherapy for breast cancer: effects on cerebral white matter seen in diffusion tensor imaging. Clinical Breast Cancer, 8, 88–91.  https://doi.org/10.3816/CBC.2008.n.007.CrossRefPubMedGoogle Scholar
  2. Ahles, T. A., & Saykin, A. J. (2007). Candidate mechanisms for chemotherapy-induced cognitive changes. Nature Reviews. Cancer, 7, 192–201.  https://doi.org/10.1038/nrc2073.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Ahles, T. A., Root, J. C., & Ryan, E. L. (2012). Cancer- and cancer treatment–associated cognitive change: an update on the state of the science. Journal of Clinical Oncology, 30, 3675–3686.  https://doi.org/10.1200/JCO.2012.43.0116.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Apple, A. C., Ryals, A. J., Alpert, K. I., Wagner, L. I., Shih, P. A., Dokucu, M., et al. (2017). Subtle hippocampal deformities in breast cancer survivors with reduced episodic memory and self-reported cognitive concerns. Neuroimage Clinical, 14(C), 685–691.  https://doi.org/10.1016/j.nicl.2017.03.004.CrossRefPubMedPubMedCentralGoogle Scholar
  5. Ashburner, J., & Friston, K. J. (2001). Why voxel-based morphometry should be used. Neuroimage, 14, 1238–1243.  https://doi.org/10.1006/nimg.2001.0961.CrossRefPubMedGoogle Scholar
  6. Barkhof, F., Haller, S., & Rombouts, S. A. (2014). Resting-state functional MR imaging: a new window to the brain. Radiology, 272, 29–49.  https://doi.org/10.1148/radiol.14132388.CrossRefPubMedGoogle Scholar
  7. Basser, P. J., Mattiello, J., & Lebihan, D. (1994). MR diffusion tensor spectroscopy and imaging. Biophysical Journal, 66, 259–267.  https://doi.org/10.1016/S0006-3495(94)80775-1.CrossRefPubMedPubMedCentralGoogle Scholar
  8. Berman, M. G., Askren, M. K., Jung, M., Therrien, B., Peltier, S., Noll, D. C., Zhang, M., Ossher, L., Hayes, D. F., Reuter-Lorenz, P. A., & Cimprich, B. (2014). Pretreatment worry and neurocognitive responses in women with breast cancer. Health Psychology, 33, 222–231.  https://doi.org/10.1037/a0033425.CrossRefPubMedGoogle Scholar
  9. Billiet, T., Vandenbulcke, M., Mädler, B., Peeters, R., Dhollander, T., Zhang, H., Deprez, S., van den Bergh, B. R. H., Sunaert, S., & Emsell, L. (2015). Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI. Neurobiology of Aging, 36(6), 2107–2121.  https://doi.org/10.1016/j.neurobiolaging.2015.02.029.CrossRefPubMedGoogle Scholar
  10. Billiet, T., Emsell, L., Vandenbulcke, M., Peeters, R., Christiaens, D., Leemans, A., van Hecke, W., Smeets, A., Amant, F., Sunaert, S., & Deprez, S. (2018). Recovery from chemotherapy-induced white matter changes in young breast cancer survivors. Brain Imaging and Behavior, 12, 64–77.  https://doi.org/10.1007/s11682-016-9665-8.CrossRefPubMedGoogle Scholar
  11. Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., & Hwang, D. U. (2006). Complex networks: structure and dynamics. Physics Reports, 424, 175–308.  https://doi.org/10.1016/j.physrep.2005.10.009.CrossRefGoogle Scholar
  12. Borogovac, A., & Asllani, I. (2012). Arterial spin labeling (ASL) fMRI: advantages, theoretical constrains, and experimental challenges in neurosciences. International Journal of Biomedical Imaging, 2012, 818456.  https://doi.org/10.1155/2012/818456.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Bruno, J., Hosseini, S. M., & Kesler, S. (2012). Altered resting state functional brain network topology in chemotherapy-treated breast cancer survivors. Neurobiology of Disease, 48, 329–338.  https://doi.org/10.1016/j.nbd.2012.07.009.CrossRefPubMedPubMedCentralGoogle Scholar
  14. Budde, M. D., Xie, M., Cross, A. H., & Song, S. K. (2009). Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. The Journal of Neuroscience, 29, 2805–2813.  https://doi.org/10.1523/JNEUROSCI.4605-08.2009.CrossRefPubMedPubMedCentralGoogle Scholar
  15. Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews. Neuroscience, 10, 186–198.  https://doi.org/10.1038/nrn2575.CrossRefPubMedGoogle Scholar
  16. Churchill, N. W., Cimprich, B., Askren, M. K., Reuter-Lorenz, P. A., Jung, M. S., Peltier, S., et al. (2015). Scale-free brain dynamics under physical and psychological distress: Pre-treatment effects in women diagnosed with breast cancer. Human Brain Mapping, 36, 1077–1092.  https://doi.org/10.1002/hbm.22687.CrossRefPubMedGoogle Scholar
  17. Cimprich, B., Reuter-Lorenz, P., Nelson, J., Clark, P. M., Therrien, B., Normolle, D., Berman, M. G., Hayes, D. F., Noll, D. C., Peltier, S., & Welsh, R. C. (2010). Prechemotherapy alterations in brain function in women with breast cancer. Journal of Clinical and Experimental Neuropsychology, 32, 324–331.  https://doi.org/10.1080/13803390903032537.CrossRefPubMedGoogle Scholar
  18. Collins, B., MacKenzie, J., Tasca, G. A., Scherling, C., & Smith, A. (2013). Cognitive effects of chemotherapy in breast cancer patients: a dose response study. Psycho-oncology, 22, 1517–1527.  https://doi.org/10.1002/pon.3163.CrossRefPubMedGoogle Scholar
  19. Conroy, S. K., McDonald, B. C., Smith, D. J., Moser, L. R., West, J. D., Kamendulis, L. M., Klaunig, J. E., Champion, V. L., Unverzagt, F. W., & Saykin, A. J. (2013). Alterations in brain structure and function in breast cancer survivors: effect of post-chemotherapy interval and relation to oxidative DNA damage. Breast Cancer Research and Treatment, 137, 493–502.  https://doi.org/10.1007/s10549-012-2385-x.CrossRefPubMedGoogle Scholar
  20. Correa, D. D., & Ahles, T. A. (2007). Cognitive adverse effects of chemotherapy in breast cancer patients. Current Opinion in Supportive and Palliative Care, 1, 57–62.  https://doi.org/10.1097/SPC.0b013e32813a328f.CrossRefPubMedGoogle Scholar
  21. Dai, Z., Yan, C., Li, K., Wang, Z., Wang, J., Cao, et al. (2015). Identifying and mapping connectivity patterns of brain network hubs in Alzheimer’s disease. Cerebral Cortex, 25, 3723–3742.  https://doi.org/10.1093/cercor/bhu246.CrossRefPubMedGoogle Scholar
  22. de Ruiter, M. B., & Schagen, S. B. (2013). Functional MRI studies in non-CNS cancers. Brain Imaging and Behavior, 7(4), 388–408.  https://doi.org/10.1007/s11682-013-9249-9.CrossRefPubMedGoogle Scholar
  23. de Ruiter, M. B., Reneman, L., Boogerd, W., Veltman, D. J., van Dam, F. S., Nederveen, A. J., et al. (2011). Cerebral hyporesponsiveness and cognitive impairment 10 years after chemotherapy for breast cancer. Human Brain Mapping, 32, 1206–1219.  https://doi.org/10.1002/hbm.21102.CrossRefPubMedGoogle Scholar
  24. de Ruiter, M. B., Reneman, L., Boogerd, W., Veltman, D. J., Caan, M., Douaud, G., Lavini, C., Linn, S. C., Boven, E., van Dam, F. S. A. M., & Schagen, S. B. (2012). Late effects of high-dose adjuvant chemotherapy on white and gray matter in breast cancer survivors: converging results from multimodal magnetic resonance imaging. Human Brain Mapping, 33, 2971–2983.  https://doi.org/10.1002/hbm.21422.CrossRefPubMedGoogle Scholar
  25. Deprez, S., Amant, F., Yigit, R., Porke, K., Verhoeven, J., Van den Stock, J., et al. (2011). Chemotherapy-induced structural changes in cerebral white matter and its correlation with impaired cognitive functioning in breast cancer patients. Human Brain Mapping, 32, 480–493.  https://doi.org/10.1002/hbm.21033.CrossRefPubMedGoogle Scholar
  26. Deprez, S., Amant, F., Smeets, A., Peeters, R., Leemans, A., Van Hecke, W., et al. (2012). Longitudinal assessment of chemotherapy-induced structural changes in cerebral white matter and its correlation with impaired cognitive functioning. Journal of Clinical Oncology, 30, 274–281.  https://doi.org/10.1200/JCO.2011.36.8571.CrossRefPubMedGoogle Scholar
  27. Deprez, S., Billiet, T., Sunaert, S., & Leemans, A. (2013). Diffusion tensor MRI of chemotherapy-induced cognitive impairment in non-CNS cancer patients: a review. Brain Imaging and Behavior, 7, 409–435.  https://doi.org/10.1007/s11682-012-9220-1.CrossRefPubMedGoogle Scholar
  28. Deprez, S., Vandenbulcke, M., Peeters, R., Emsell, L., Smeets, A., Christiaens, M. R., Amant, F., et al. (2014). Longitudinal assessment of chemotherapy-induced alterations in brain activation during multitasking and its relation with cognitive complaints. Journal of Clinical Oncology, 32, 2031–2038.  https://doi.org/10.1200/JCO.2013.53.6219.CrossRefPubMedGoogle Scholar
  29. Deprez, S., Kesler, S. R., Saykin, A. J., Silveman, D. H., de Ruiter, M. B., & McDonald, B. C. (2018). International cognition and cancer task force recommendations for neuroimaging methods in the study of cognitive impairment in non-CNS cancer patients. Journal of the National Cancer Institute, 110(3), 223–231.  https://doi.org/10.1093/jnci/djx285.CrossRefPubMedGoogle Scholar
  30. Detre, J. A., Wang, J., Wang, Z., & and Rao, H. (2009). Arterial spin-labeled perfusion MRI in basic and clinical neuroscience. Current Opinion in Neurology 22, 348–355. doi:  https://doi.org/10.1097/WCO.0b013e32832d9505.
  31. Dumas, J. A., Makarewicz, J., Schaubhut, G. J., Devins, R., Albert, K., Dittus, K., & Newhouse, P. A. (2013). Chemotherapy altered brain functional connectivity in women with breast cancer: a pilot study. Brain Imaging and Behavior, 7, 524–532.  https://doi.org/10.1007/s11682-013-9244-1.CrossRefPubMedGoogle Scholar
  32. Engel, A. K., Fries, P., & Singer, W. (2001). Dynamic predictions: oscillations and synchrony in top-down processing. Nature Reviews. Neuroscience, 2, 704–716.  https://doi.org/10.1038/35094565.CrossRefPubMedGoogle Scholar
  33. Ferguson, R. J., McDonald, B. C., Saykin, A. J., & Ahles, T. A. (2007). Brain structure and function differences in monozygotic twins: possible effects of breast cancer chemotherapy. Journal of Clinical Oncology, 25, 3866–3870.  https://doi.org/10.1200/JCO.2007.10.8639.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Glover, G. H. (2011). Overview of functional magnetic resonance imaging. Neurosurgery Clinics of North America, 22, 133–139vii.  https://doi.org/10.1016/j.nec.2010.11.001.
  35. Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N., Friston, K. J., & Frackowiak, R. S. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage., 14, 21–36.  https://doi.org/10.1006/nimg.2001.0786.CrossRefPubMedGoogle Scholar
  36. Grade, M., Hernandez Tamames, J. A., Pizzini, F. B., Achten, E., Golay, X., & Smits, M. A. (2015). neuroradiologist’s guide to arterial spin labeling MRI in clinical practice. Neuroradiology, 57, 1181–1202.  https://doi.org/10.1007/s00234-015-1571-z.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Hampson, J. P., Zick, S. M., Khabir, T., Wright, B. D., & Harris, R. E. (2015). Altered resting brain connectivity in persistent cancer related fatigue. Neuroimage Clinical, 7(8), 305–313.  https://doi.org/10.1016/j.nicl.2015.04.022.CrossRefGoogle Scholar
  38. Henneghan, A. M., Palesh, O., Harrison, M., & Kesler, S. R. (2018). Identifying cytokine predictors of cognitive functioning in breast cancer survivors up to 10 years post chemotherapy using machine learning. Journal of Neuroimmunology, 320, 38–47.  https://doi.org/10.1016/j.jneuroim.2018.04.012.CrossRefPubMedGoogle Scholar
  39. Hooning, M. J., Dorresteijn, L. D., Aleman, B. M., Kappelle, A. C., Klijn, J. G., Boogerd, W., et al. (2006). Decreased risk of stroke among 10-year survivors of breast cancer. Journal of Clinical Oncology, 24, 5388–5394.CrossRefPubMedGoogle Scholar
  40. Hosseini, S. M., Della, K., & Kesle, S. R. (2012). Altered small-world properties of gray matter networks in breast cancer. BMC Neurology, 12, 28.  https://doi.org/10.1186/1471-2377-12-28.CrossRefPubMedPubMedCentralGoogle Scholar
  41. Hurria, A., Patel, S. K., Mortimer, J., Luu, T., Somlo, G., Katheria, V., Ramani, R., Hansen, K., Feng, T., Chuang, C., Geist, C. L., & Silverman, D. H. S. (2013). The effect of aromatase inhibition on the cognitive function of older patients with breast cancer. Clinical Breast Cancer, 14, 132–140.  https://doi.org/10.1016/j.clbc.2013.10.010.CrossRefPubMedPubMedCentralGoogle Scholar
  42. Inagaki, M., Yoshikawa, E., Matsuoka, Y., Sugawara, Y., Nakano, T., Akechi, T., Wada, N., Imoto, S., Murakami, K., Uchitomi, Y., & and The Breast Cancer Survivors’ Brain MRI Database Group. (2007). Smaller regional volumes of gray and white matter demonstrated in breast cancer survivors exposed to adjuvant chemotherapy. Cancer, 109, 146–156.  https://doi.org/10.1002/cncr.22368.CrossRefPubMedGoogle Scholar
  43. Janelsins, M. C., Kohli, S., Mohile, S. G., Usuki, K., Ahles, T. A., & Morrow, G. R. (2011). An update on cancer- and chemotherapy-related cognitive dysfunction: current status. Seminars in Oncology, 38, 431–438.  https://doi.org/10.1053/j.seminoncol.2011.03.014.CrossRefPubMedPubMedCentralGoogle Scholar
  44. Jiang, L., & Zuo, X. N. (2016). Regional homogeneity: a multimodal, multiscale neuroimaging marker of the human connectome. Neuroscientist., 22, 486–505.  https://doi.org/10.1177/1073858415595004.CrossRefPubMedGoogle Scholar
  45. Jim, H. S. L., Phillips, K. M., Chait, S., Faul, L. A., Popa, M. A., Lee, Y. H., Hussin, M. G., Jacobsen, P. B., & Small, B. J. (2012). Meta-analysis of cognitive functioning in breast cancer survivors previously treated with standard-dose chemotherapy. Journal of Clinical Oncology, 30, 3578–3587.  https://doi.org/10.1200/JCO.2011.39.5640.CrossRefPubMedPubMedCentralGoogle Scholar
  46. Joel, S. E., Caffo, B. S., van Zijl, P. C., & Pekar, J. J. (2011). On the relationship between seed-based and ICA-based measures of functional connectivity. Magnetic Resonance in Medicine, 66, 644–657.  https://doi.org/10.1002/mrm.22818.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Jung, M. S., Zhang, M., Askren, M. K., Berman, M. G., Peltier, S., Hayes, D. F., Therrien, B., Reuter-Lorenz, P. A., & Cimprich, B. (2017). Cognitive dysfunction and symptom burden in women treated for breast cancer: a prospective behavioral and fMRI analysis. Brain Imaging and Behavior, 11, 86–97.  https://doi.org/10.1007/s11682-016-9507-8.CrossRefPubMedGoogle Scholar
  48. Kerr, I. G., Zimm, S., Collins, J. M., O'Neill, D., & Poplack, D. G. (1984). Effect of intravenous dose and schedule on cerebrospinal fluid pharmacokinetics of 5-fluorouracil in the monkey. Cancer Research, 44, 4929–4932.PubMedGoogle Scholar
  49. Kesler, S. R. (2014). Default mode network as a potential biomarker of chemotherapy-related brain injury. Neurobiology of Aging, 35(Suppl 2), S11–S19.  https://doi.org/10.1016/j.neurobiolaging.2014.03.036.CrossRefPubMedGoogle Scholar
  50. Kesler, S. R., & Blayney, D. W. (2016). Neurotoxic effects of anthracycline- vs nonanthracycline-based chemotherapy on cognition in breast cancer survivors. JAMA Oncology, 2, 185–192.  https://doi.org/10.1001/jamaoncol.2015.4333.CrossRefPubMedPubMedCentralGoogle Scholar
  51. Kesler, S. R., Bennett, F. C., Mahaffey, M. L., & Spiegel, D. (2009). Regional brain activation during verbal declarative memory in metastatic breast cancer. Clinical Cancer Research, 15, 6665–6673.  https://doi.org/10.1158/1078-0432.CCR-09-1227.CrossRefPubMedPubMedCentralGoogle Scholar
  52. Kesler, S. R., Kent, J. S., & O’Hara, R. (2011). Prefrontal cortex and executive function impairments in primary breast cancer. Archives of Neurology, 68(11), 1447–1453.CrossRefPubMedPubMedCentralGoogle Scholar
  53. Kesler, S., Hadi Hosseini, S. M., Heckler, C., Janelsins, M., Palesh, O., Mustian, K., & Morrow, G. (2013a). Cognitive training for improving executive function in chemotherapy-treated breast cancer survivors. Clinical Breast Cancer, 13, 299–306.  https://doi.org/10.1016/j.clbc.2013.02.004. CrossRefPubMedPubMedCentralGoogle Scholar
  54. Kesler, S., Janelsins, M., Koovakkattu, D., Palesh, O., Mustian, K., Morrow, G., et al. (2013b). Reduced hippocampal volume and verbal memory performance associated with interleukin-6 and tumor necrosis factor-alpha levels in chemotherapy-treated breast cancer survivors. Brain Behavior and Immunity, 30(Suppl3), S109–S116.  https://doi.org/10.1016/j.bbi.2012.05.017.CrossRefGoogle Scholar
  55. Kesler, S. R., Watson, C. L., & Blayney, D. W. (2015). Brain network alterations and vulnerability to simulated neurodegeneration in breast cancer. Neurobiology of Aging, 36, 2429–2442.  https://doi.org/10.1016/j.neurobiolaging.2015.04.015.CrossRefPubMedPubMedCentralGoogle Scholar
  56. Kesler, S. R., Adams, M., Packer, M., Rao, V., Henneghan, A. M., Blayney, D. W., & Palesh, O. (2017a). Disrupted brain network functional dynamics and hyper- correlation of structural and functional connectome topology in patients with breast cancer prior to treatment. Brain and Behavior: A Cognitive Neuroscience Perspective, 7, e00643.  https://doi.org/10.1002/brb3.643. CrossRefGoogle Scholar
  57. Kesler, S. R., Rao, A., Blayney, D. W., Oakley-Girvan, I. A., Karuturi, M., & Palesh, O. (2017b). Predicting long-term cognitive outcome following breast cancer with pre-treatment resting state fMRI and random forest machine learning. Frontiers in Human Neuroscience, 11, 555.  https://doi.org/10.3389/fnhum.2017.00555. CrossRefPubMedPubMedCentralGoogle Scholar
  58. Koch, M. (2018). Artificial intelligence is becoming natural. Cell, 173(3), 531–533.  https://doi.org/10.1016/j.cell.2018.04.007.CrossRefPubMedGoogle Scholar
  59. Koppelmans, V., de Ruiter, M. B., van der Lijn, F., Boogerd, W., Seynaeve, C., van der Lugt, A., Vrooman, H., Niessen, W. J., Breteler, M. M. B., & Schagen, S. B. (2012). Global and focal brain volume in long-term breast cancer survivors exposed to adjuvant chemotherapy. Breast Cancer Research and Treatment, 132, 1099–1106.  https://doi.org/10.1007/s10549-011-1888-1.CrossRefPubMedGoogle Scholar
  60. Koppelmans, V., de Groot, M., de Ruiter, M. B., Boogerd, W., Seynaeve, C., Vernooij, M. W., Niessen, W. J., Schagen, S. B., & Breteler, M. M. B. (2014). Global and focal white matter integrity in breast cancer survivors 20 years after adjuvant chemotherapy. Human Brain Mapping, 35, 889–899.  https://doi.org/10.1002/hbm.22221.CrossRefPubMedGoogle Scholar
  61. Koppelmans, V., Vernooij, M. W., Boogerd, W., Seynaeve, C., Ikram, M. A., Breteler, M. M., et al. (2015). Prevalence of cerebral small-vessel disease in long-term breast cancer survivors exposed to both adjuvant radiotherapy and chemotherapy. Journal of Clinical Oncology, 33, 588–593.  https://doi.org/10.1200/JCO.2014.56.8345.CrossRefPubMedGoogle Scholar
  62. Lee, M. H., Smyser, C. D., & Shimony, J. S. (2013). Resting-state fMRI: a review of methods and clinical applications. AJNR. American Journal of Neuroradiology, 34, 1866–1872.  https://doi.org/10.3174/ajnr.A3263.CrossRefPubMedGoogle Scholar
  63. Lepage, C., Smith, A. M., Moreau, J., Barlow-Krelina, E., Wallis, N., Collins, B., MacKenzie, J., & Scherling, C. (2014). A prospective study of grey matter and cognitive function alterations in chemotherapy-treated breast cancer patients. Springerplus., 3, 444–454.  https://doi.org/10.1186/2193-1801-3-444.CrossRefPubMedPubMedCentralGoogle Scholar
  64. Li, X., Chen, H., Lv, Y., Chao, H. H., Gong, L., Li, C. R., et al. (2018). Diminished gray matter density mediates chemotherapy dosagerelated cognitive impairment in breast cancer patients. Scientific Reports, 8(1), 13801.  https://doi.org/10.1038/s41598-018-32257-w. CrossRefPubMedPubMedCentralGoogle Scholar
  65. Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature., 412, 150–157.  https://doi.org/10.1038/35084005.CrossRefPubMedGoogle Scholar
  66. López Zunini, R. A., Scherling, C., Wallis, N., Collins, B., MacKenzie, J., Bielajew, C., & Smith, A. M. (2013). Differences in verbal memory retrieval in breast cancer chemotherapy patients compared to healthy controls: a prospective fMRI study. Brain Imaging and Behavior, 7, 460–477.  https://doi.org/10.1007/s11682-012-9213-0.CrossRefPubMedGoogle Scholar
  67. Mandelblatt, J. S., Stern, R. A., Luta, G., McGuckin, M., Clapp, J. D., Hurria, A., Jacobsen, P. B., Faul, L. A., Isaacs, C., Denduluri, N., Gavett, B., Traina, T. A., Johnson, P., Silliman, R. A., Turner, R. S., Howard, D., van Meter, J. W., Saykin, A., & Ahles, T. (2014). Cognitive impairment in older patients with breast cancer before systemic therapy: is there an interaction between cancer and comorbidity? Journal of Clinical Oncology, 32, 1909–1918.  https://doi.org/10.1200/JCO.2013.54.2050.CrossRefPubMedPubMedCentralGoogle Scholar
  68. McDonald, B. C., Conroy, S. K., Ahles, T. A., West, J. D., & Saykin, A. J. (2010). Gray matter reduction associated with systemic chemotherapy for breast cancer: a prospective MRI study. Breast Cancer Research and Treatment, 123, 819–828.  https://doi.org/10.1007/s10549-010-1088-4.CrossRefPubMedPubMedCentralGoogle Scholar
  69. McDonald, B. C., Conroy, S. K., Ahles, T. A., West, J. D., & Saykin, A. J. (2012a). Alterations in brain activation during working memory processing associated with breast cancer and treatment: a prospective functional magnetic resonance imaging study. Journal of Clinical Oncology, 30, 2500–2508.  https://doi.org/10.1200/JCO.2011.38.5674. CrossRefPubMedPubMedCentralGoogle Scholar
  70. McDonald, B. C., Conroy, S. K., Smith, D. J., West, J. D., & Saykin, A. J. (2012b). Frontal gray matter reduction after breast cancer chemotherapy and association with executive symptoms: a replication and extension study. Brain Behavior, and Immunity, 30(Suppl), S117–S125.  https://doi.org/10.1016/j.bbi.2012.05.007.CrossRefGoogle Scholar
  71. Menning, S., de Ruiter, M. B., Veltman, D. J., Koppelmans, V., Kirschbaum, C., Boogerd, W., Reneman, L., & Schagen, S. B. (2015). Multimodal MRI and cognitive function in patients with breast cancer prior to adjuvant treatment-the role of fatigue. Neuroimage Clinical, 7, 547–554.  https://doi.org/10.1016/j.nicl.2015.02.005.CrossRefPubMedPubMedCentralGoogle Scholar
  72. Menning, S., De, M. R., Veltman, D. J., Boogerd, W., Oldenburg, H. S., Reneman, L., et al. (2017). Changes in brain activation in breast cancer patients depend on cognitive domain and treatment type. PLoS One, 12(3), e0171724.  https://doi.org/10.1371/journal.pone.0171724.CrossRefPubMedPubMedCentralGoogle Scholar
  73. Meyers, C. A. (2008). How chemotherapy damages the central nervous system. Journal of Biology, 7, 11–13.  https://doi.org/10.1186/jbiol73.CrossRefPubMedPubMedCentralGoogle Scholar
  74. Miao, H., Chen, X., Yan, Y., He, X., Hu, S., Kong, J., Wu, M., Wei, Y., Zhou, Y., Wang, L., Wang, K., & Qiu, B. (2016). Functional connectivity change of brain default mode network in breast cancer patients after chemotherapy. Neuroradiology, 58, 1–8.  https://doi.org/10.1007/s00234-016-1708-8.CrossRefGoogle Scholar
  75. Mo, C., Lin, H., Fu, F., Lin, L., Jie, Z., Meng, H., et al. (2017). Chemotherapy-induced changes of cerebral activity in resting-state functional magnetic resonance imaging and cerebral white matter in diffusion tensor imaging. Oncotarget, 8(46), 81273–81284.  https://doi.org/10.18632/oncotarget.18111.CrossRefPubMedPubMedCentralGoogle Scholar
  76. Nudelman, K. N. H., Wang, Y., Mcdonald, B. C., Conroy, S. K., Smith, D. J., West, J. D., et al. (2014). Altered cerebral blood flow one month after systemic chemotherapy for breast cancer: a prospective study using pulsed arterial spin labeling mri perfusion. PLoS One, 9, e96713.  https://doi.org/10.1371/journal.pone.0096713.CrossRefPubMedPubMedCentralGoogle Scholar
  77. Nudelman, K. N., Mcdonald, B. C., Wang, Y., Smith, D. J., West, J. D., O'Neill, D. P., et al. (2016). Cerebral perfusion and gray matter changes associated with chemotherapy-induced peripheral neuropathy. Journal of Clinical Oncology, 34, 677–683.  https://doi.org/10.1200/JCO.2015.62.1276.CrossRefPubMedGoogle Scholar
  78. Piccirillo, J. F., Hardin, F. M., Nicklaus, J., Kallogjeri, D., Wilson, M., Ma, C. X., Coalson, R. S., Shimony, J., & Schlaggar, B. L. (2015). Cognitive impairment after chemotherapy related to atypical network architecture for executive control. Oncology., 88, 360–368.  https://doi.org/10.1159/000370117.CrossRefPubMedPubMedCentralGoogle Scholar
  79. Pierpaoli, C., Jezzard, P., Basser, P. J., Barnett, A., & Di, C. G. (1996). Diffusion tensor MR imaging of the human brain. Radiology, 201, 637–648.  https://doi.org/10.1148/radiology.201.3.8939209.CrossRefPubMedGoogle Scholar
  80. Pomykala, K. L., de Ruiter, M. B., Deprez, S., Mcdonald, B. C., & Silverman, D. H. (2013). Integrating imaging findings in evaluating the post-chemotherapy brain. Brain Imaging and Behavior, 7, 436–452.  https://doi.org/10.1007/s11682-013-9239-y.CrossRefPubMedGoogle Scholar
  81. Raichle, M. E. (2012). The restless brain. Brain Connectivity, 1, 3–12.  https://doi.org/10.1089/brain.2011.0019.CrossRefGoogle Scholar
  82. Reisberg, B., Franssen, E. H., Hasan, S. M., Monteiro, I., Boksay, I., Souren, L. E. M., et al. (1999). Retrogenesis: clinical, physiologic, and pathologic mechanisms in brain aging, alzheimer’s and other dementing processes. European Archives of Psychiatry and Clinical Neuroscience, 249(Suppl), 28–36.CrossRefPubMedGoogle Scholar
  83. Rick, O., Reußborst, M., Dauelsberg, T., Hass, H. G., König, V., Caspari, R., et al. (2018). Neurocog FX study: a multicenter cohort study on cognitive dysfunction in patients with early breast cancer. Psycho-Oncology, 27(1), 2016–2022.  https://doi.org/10.1002/pon.4763.CrossRefPubMedGoogle Scholar
  84. Rudie, J. D., Brown, J. A., Beck-Pancer, D., Hernandez, L. M., Dennis, E. L., Thompson, P. M., Bookheimer, S. Y., & Dapretto, M. (2012). Altered functional and structural brain network organization in autism. NeuroImage Clinical, 2, 79–94.  https://doi.org/10.1016/j.nicl.2012.11.006.CrossRefPubMedPubMedCentralGoogle Scholar
  85. Sato, C., Sekiguchi, A., Kawai, M., Kotozaki, Y., Rui, N., Tada, H., et al. (2015). Postoperative structural brain changes and cognitive dysfunction in patients with breast cancer. PLoS One, 10(11), e0140655.  https://doi.org/10.1371/journal.pone.0140655.CrossRefPubMedPubMedCentralGoogle Scholar
  86. Scherling, C., Collins, B., Mackenzie, J., Bielajew, C., & Smith, A. (2011). Pre-chemotherapy differences in visuospatial working memory in breast cancer patients compared to controls: an fmri study. Frontiers in Human Neuroscience, 5, 122.  https://doi.org/10.3389/fnhum.2011.00122.CrossRefPubMedPubMedCentralGoogle Scholar
  87. Scherling, C., Collins, B., Mackenzie, J., Bielajew, C., & Smith, A. (2012). Prechemotherapy differences in response inhibition in breast cancer patients compared to controls: a functional magnetic resonance imaging study. Journal of Clinical and Experimental Neuropsychology, 34, 543–560.  https://doi.org/10.1080/13803395.2012.666227.CrossRefPubMedGoogle Scholar
  88. Seigers, R., Schagen, S. B., Van, T. O., & Dietrich, J. (2013). Chemotherapy-related cognitive dysfunction: current animal studies and future directions. Brain Imaging and Behavior, 7(4), 453–459.  https://doi.org/10.1007/s11682-013-9250-3.CrossRefPubMedGoogle Scholar
  89. Simóm, M., Rifà-Ros, X., Rodriguez-Fornells, A., & Bruna, J. (2013). Chemobrain: a systematic review of structural and functional neuroimaging studies. Neuroscience and Biobehavioral Reviews, 37, 1311–1321.  https://doi.org/10.1016/j.neubiorev.2013.04.015.CrossRefGoogle Scholar
  90. Smith, D. V., Utevsky, A. V., Bland, A. R., Nathan, C., Clithero, J. A., Harsch, A. E. W., et al. (2014). Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches. Neuroimage., 95, 1–12.  https://doi.org/10.1016/j.neuroimage.2014.03.042.CrossRefPubMedPubMedCentralGoogle Scholar
  91. Song, S. K., Yoshino, J., Le, T. Q., Lin, S. J., Sun, S. W., Cross, A. H., et al. (2005). Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage., 26, 132–140.  https://doi.org/10.1016/j.neuroimage.2005.01.028.CrossRefPubMedGoogle Scholar
  92. Sporns, O. (2013). Structure and function of complex brain networks. Dialogues in Clinical Neuroscience, 15, 247–262 PMCID:PMC3811098.PubMedPubMedCentralGoogle Scholar
  93. Stouten-Kemperman, M. M., De Ruiter, M. B., Caan, M. W. A., Boogerd, W., Kerst, M. J., Reneman, L., et al. (2015). Lower cognitive performance and white matter changes in testicular cancer survivors 10 years after chemotherapy. Human Brain Mapping, 36(11), 4638–4647.  https://doi.org/10.1002/hbm.22942.CrossRefPubMedGoogle Scholar
  94. Sun, J., Tong, S., & Yang, G. Y. (2012). Reorganization of brain networks in aging and age-related diseases. Aging and Disease, 3, 181–193 PMCID: PMC3377830.PubMedGoogle Scholar
  95. Tao, L., Lin, H., Yan, Y., Xu, X., Wang, L., Zhang, J., et al. (2016). Impairment of the executive function in breast cancer patients receiving chemotherapy treatment: a functional mri study. European Journal of Cancer Care, 26(6).Google Scholar
  96. Valentini, A., Finch, A., Lubiński, J., Byrski, T., Ghadirian, P., Kimsing, C., et al. (2013). Chemotherapy-induced amenorrhea in patients with breast cancer with a brca1 or brca2 mutation. Journal of Clinical Oncology, 31, 3914–3919.  https://doi.org/10.1200/JCO.2012.47.7893.CrossRefPubMedPubMedCentralGoogle Scholar
  97. Vazquez, A. L., & Noll, D. C. (1998). Nonlinear aspects of the BOLD response in functional MRI. Neuroimage, 7, 108–118.  https://doi.org/10.1006/nimg.1997.0316.CrossRefPubMedGoogle Scholar
  98. Wang, Y., Saykin, A. J., Pfeuffer, J., Lin, C., Mosier, K. M., Shen, L., Kim, S., & Hutchins, G. D. (2011). Regional reproducibility of pulsed arterial spin labeling perfusion imaging at 3t. Neuroimage, 54, 1188–1195.  https://doi.org/10.1016/j.neuroimage.2010.08.043.CrossRefPubMedGoogle Scholar
  99. Wefel, J. S., Kesler, S. R., Noll, K. R., & Schagen, S. B. (2015). Clinical characteristics, pathophysiology, and management of noncentral nervous system cancer-related cognitive impairment in adults. CA: a Cancer Journal for Clinicians, 65, 123–138.  https://doi.org/10.3322/caac.21258.CrossRefGoogle Scholar
  100. Wu, X., Lv, X. F., Zhang, Y. L., Wu, H. W., Cai, P. Q., Qiu, Y. W., Zhang, X. L., & Jiang, G. H. (2015). Cortical signature of patients with HBV-related cirrhosis without overt hepatic encephalopathy: a morphometric analysis. Frontiers in Neuroanatomy, 9, 82.  https://doi.org/10.3389/fnana.2015.00082.CrossRefPubMedPubMedCentralGoogle Scholar
  101. Zang, Y., Jiang, T., Lu, Y., He, Y., & Tian, L. (2004). Regional homogeneity approach to fmri data analysis. Neuroimage, 22, 394–400.  https://doi.org/10.1016/j.neuroimage.2003.12.030.CrossRefPubMedGoogle Scholar
  102. Zang, Y. F., He, Y., Zhu, C. Z., Cao, Q. J., Sui, M. Q., Liang, M., et al. (2007). Altered baseline brain activity in children with adhd revealed by resting-state functional mri. Brain & Development, 29, 83–91.  https://doi.org/10.1016/j.braindev.2006.07.002.CrossRefGoogle Scholar
  103. Zhang, X. D., & Zhang, L. J. (2018). Multimodal MR imaging in hepatic encephalopathy: state of the art. Metabolic Brain Disease, 33(3), 1–11.  https://doi.org/10.1007/s11011-018-0191-9.CrossRefGoogle Scholar
  104. Zhang, L. J., Wu, S., Ren, J., & Lu, G. M. (2014). Resting-state functional magnetic resonance imaging in hepatic encephalopathy: current status and perspectives. Metabolic Brain Disease, 29, 569–582.  https://doi.org/10.1007/s11011-014-9504-9.CrossRefPubMedGoogle Scholar
  105. Zou, Q. H., Zhu, C. Z., Yang, Y., Zuo, X. N., Long, X. Y., Cao, Q. J., Wang, Y. F., & Zang, Y. F. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (alff) for resting-state fMRI: fractional alff. Journal of Neuroscience Methods, 172, 137–141.  https://doi.org/10.1016/j.jneumeth.2008.04.012.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

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

Authors and Affiliations

  • Yun Feng
    • 1
    • 2
  • Xiao Dong Zhang
    • 3
  • Gang Zheng
    • 1
    • 4
  • Long Jiang Zhang
    • 1
    • 5
    Email author
  1. 1.Department of Medical Imaging, Jinling HospitalNanjing Medical UniversityNanjingChina
  2. 2.Department of Medical ImagingThe Affiliated Huaian No.1 People’s Hospital of Nanjing Medical UniversityHuaianChina
  3. 3.Department of RadiologyTianjin First Central HospitalTianjinChina
  4. 4.Monash Biomedical ImagingMonash UniversityClaytonAustralia
  5. 5.Department of Medical Imaging, Jinling HospitalMedical School of Nanjing UniversityNanjingChina

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