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Computational and Mathematical Methods in Medicine
Volume 2017 (2017), Article ID 1403940, 12 pages
https://doi.org/10.1155/2017/1403940
Research Article

Altered Brain Functional Connectivity in Small-Cell Lung Cancer Patients after Chemotherapy Treatment: A Resting-State fMRI Study

1School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece
2Hellenic Military University, Vari, Athens, Greece
3Research Centre of Radiology and Imaging, “Evgenidion” General Hospital, Athens, Greece
42nd Department of Radiology, Radiotherapy Unit, ATTIKON University Hospital, Athens, Greece

Correspondence should be addressed to Konstantinos Bromis; moc.liamg@shmorpmk and Vasileios Kouloulias; rg.autn.ece@luoluokv

Received 5 February 2017; Revised 6 May 2017; Accepted 15 June 2017; Published 17 July 2017

Academic Editor: Yuhai Zhao

Copyright © 2017 Konstantinos Bromis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. Zhu, Z. Zhou, Y. Wang et al., “Thoracic radiation therapy improves the overall survival of patients with extensive-stage small cell lung cancer with distant metastasis,” Cancer, vol. 117, no. 23, pp. 5423–5431, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. W. Zhang, W. Jiang, L. Luan, L. Wang, X. Zheng, and G. Wang, “Prophylactic cranial irradiation for patients with small-cell lung cancer: A systematic review of the literature with meta-analysis,” BMC Cancer, vol. 14, no. 1, article no. 793, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. A. Aupérin, R. Arriagada, J.-P. Pignon et al., “Prophylactic cranial irradiation for patients with small-cell lung cancer in complete remission,” New England Journal of Medicine, vol. 341, no. 7, pp. 476–484, 1999. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Chen, J. Li, Y. Hu et al., “Prophylactic cranial irradiation could improve overall survival in patients with extensive small cell lung cancer: A retrospective study,” Strahlentherapie und Onkologie, vol. 192, no. 12, pp. 905–912, 2016. View at Publisher · View at Google Scholar · View at Scopus
  5. G. Welzel, K. Fleckenstein, J. Schaefer et al., “Memory Function Before and After Whole Brain Radiotherapy in Patients With and Without Brain Metastases,” International Journal of Radiation Oncology Biology Physics, vol. 72, no. 5, pp. 1311–1318, 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. M. Simó, L. Vaquero, P. Ripollés et al., “Longitudinal brain changes associated with prophylactic cranial irradiation in lung cancer,” Journal of Thoracic Oncology, vol. 11, no. 4, pp. 475–486, 2016. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Simó, L. Vaquero, P. Ripollés et al., “Brain damage following prophylactic cranial irradiation in lung cancer survivors,” Brain Imaging and Behavior, vol. 10, no. 1, pp. 283–295, 2016. View at Publisher · View at Google Scholar · View at Scopus
  8. C. A. Meyers, K. S. Byrne, and R. Komaki, “Cognitive deficits in patients with small cell lung cancer before and after chemotherapy,” Lung Cancer, vol. 12, no. 3, pp. 231–235, 1995. View at Publisher · View at Google Scholar · View at Scopus
  9. D. R. Grosshans, C. A. Meyers, P. K. Allen, S. D. Davenport, and R. Komaki, “Neurocognitive function in patients with small cell lung cancer: effect of prophylactic cranial irradiation,” Cancer, vol. 112, no. 3, pp. 589–595, 2008. View at Publisher · View at Google Scholar · View at Scopus
  10. R. Komaki, C. A. Meyers, D. M. Shin et al., “Evaluation of cognitive function in patients with limited small cell lung cancer prior to and shortly following prophylactic cranial irradiation,” International Journal of Radiation Oncology, Biology, Physics, vol. 33, no. 1, pp. 179–182, 1995. View at Publisher · View at Google Scholar · View at Scopus
  11. M. Simó, J. C. Root, L. Vaquero et al., “Cognitive and brain structural changes in a lung cancer population,” Journal of Thoracic Oncology, vol. 10, no. 1, pp. 38–45, 2015. View at Publisher · View at Google Scholar · View at Scopus
  12. S. Kaasa, B. T. Olsnes, and A. Mastekaasa, “Neuropsychological evaluation of patients with inoperable non-small cell lung cancer treated with combination chemotherapy or radiotherapy,” Acta Oncologica, vol. 27, no. 3, pp. 241–246, 1988. View at Publisher · View at Google Scholar · View at Scopus
  13. H. S. L. Jim, K. M. Phillips, S. Chait et al., “Meta-analysis of cognitive functioning in breast cancer survivors previously treated with standard-dose chemotherapy,” Journal of Clinical Oncology, vol. 30, no. 29, pp. 3578–3587, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. K. Kaemingk, S. Lundy, T. Patton, S. Reminger, and R. Kervick, “Attention is frequently weaker than would be expected based on intelligence in breast cancer survivors treated with chemotherapy: I-2,” Pscyho-oncology, vol. 15, 2006. View at Google Scholar
  15. X. Chen, J. Li, J. Ren et al., “Selective impairment of attention networks in breast cancer patients receiving chemotherapy treatment,” Psycho-Oncology, vol. 23, no. 10, pp. 1165–1171, 2014. View at Publisher · View at Google Scholar · View at Scopus
  16. C. Anderson-Hanley, M. L. Sherman, R. Riggs, V. B. Agocha, and B. E. Compas, “Neuropsychological effects of treatments for adults with cancer: A meta-analysis and review of the literature,” Journal of the International Neuropsychological Society, vol. 9, no. 7, pp. 967–982, 2003. View at Publisher · View at Google Scholar · View at Scopus
  17. C. E. Jausen, C. Miaskowski, M. Dodd, G. Dowling, and J. Kramer, “A metaanalysis of studies of the effects of cancer chemotherapy on various domains of cognitive function,” Cancer, vol. 104, no. 10, pp. 2222–2233, 2005. View at Publisher · View at Google Scholar · View at Scopus
  18. P. Andryszak, M. Wiłkość, P. Izdebski, and B. Żurawski, “A systemic literature review of neuroimaging studies in women with breast cancer treated with adjuvant chemotherapy,” Contemporary Oncology/Współczesna Onkologia (Pozn), vol. 21, no. 1, pp. 6–15, 2017. View at Publisher · View at Google Scholar
  19. B. B. Biswal, M. Mennes, X. N. Zuo, S. Gohel, C. Kelly, S. M. Smith et al., “Toward discovery science of human brain function,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 10, pp. 4734–4739, 2010. View at Google Scholar
  20. C. Rosazza and L. Minati, “Resting-state brain networks: Literature review and clinical applications,” Neurological Sciences, vol. 32, no. 5, pp. 773–785, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. M. P. van den Heuvel and H. E. Hulshoff Pol, “Exploring the brain network: a review on resting-state fMRI functional connectivity,” European Neuropsychopharmacology, vol. 20, no. 8, pp. 519–534, 2010. View at Publisher · View at Google Scholar · View at Scopus
  22. K. Wang, M. Liang, and L. Wang, “Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study,” Human Brain Mapping, vol. 28, no. 10, pp. 967–978, 2007. View at Publisher · View at Google Scholar · View at Scopus
  23. M.-E. Lynall, D. S. Bassett, R. Kerwin et al., “Functional connectivity and brain networks in schizophrenia,” The Journal of Neuroscience, vol. 30, no. 28, pp. 9477–9487, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. J. V. Hull, Z. J. Jacokes, C. M. Torgerson, A. Irimia, and J. D. Van Horn, “Resting-state functional connectivity in autism spectrum disorders: A review,” Frontiers in Psychiatry, vol. 7, 2017. View at Publisher · View at Google Scholar
  25. J. A. Dumas, J. Makarewicz, G. J. Schaubhut et al., “Chemotherapy altered brain functional connectivity in women with breast cancer: A pilot study,” Brain Imaging and Behavior, vol. 7, no. 4, pp. 524–532, 2013. View at Publisher · View at Google Scholar · View at Scopus
  26. S. R. Kesler, J. S. Wefel, S. M. H. Hosseini, M. Cheung, C. L. Watson, and F. Hoeft, “Default mode network connectivity distinguishes chemotherapy-treated breast cancer survivors from controls,” Proceedings of the National Academy of Sciences of the United States of America, vol. 110, no. 28, pp. 11600–11605, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. H. Miao, X. Chen, Y. Yan et al., “Functional connectivity change of brain default mode network in breast cancer patients after chemotherapy,” Neuroradiology, vol. 58, no. 9, pp. 921–928, 2016. View at Publisher · View at Google Scholar · View at Scopus
  28. R. L. Buckner, J. R. Andrews-Hanna, and D. L. Schacter, “The brain's default network: anatomy, function, and relevance to disease,” Annals of the New York Academy of Sciences, vol. 1124, pp. 1–38, 2008. View at Publisher · View at Google Scholar · View at Scopus
  29. M. Simó, X. Rifà-Ros, L. Vaquero, P. Ripollés, N. Cayuela, J. Jové et al., “Brain functional connectivity in lung cancer population: an exploratory study,” Brain Imaging and Behavior, pp. 1–14, 2017. View at Publisher · View at Google Scholar
  30. M. D. Fox, A. Z. Snyder, J. L. Vincent, M. Corbetta, D. C. van Essen, and M. E. Raichle, “The human brain is intrinsically organized into dynamic, anticorrelated functional networks,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 27, pp. 9673–9678, 2005. View at Publisher · View at Google Scholar · View at Scopus
  31. M. B. de Ruiter and S. B. Schagen, “Functional MRI studies in non-CNS cancers,” Brain Imaging and Behavior, vol. 7, no. 4, pp. 388–408, 2013. View at Publisher · View at Google Scholar · View at Scopus
  32. M. Jenkinson, C. F. Beckmann, T. E. J. Behrens, M. W. Woolrich, and S. M. Smith, “FSL,” NeuroImage, vol. 62, no. 2, pp. 782–790, 2012. View at Publisher · View at Google Scholar · View at Scopus
  33. M. Jenkinson, M. Pechaud, and S. Smith, BET2: MR-Based Estimation of Brain, Skull and Scalp Surfaces. In Eleventh Annual Meeting of the Organization for Human Brain Mapping, 2005.
  34. M. Jenkinson, P. Bannister, M. Brady, and S. Smith, “Improved optimization for the robust and accurate linear registration and motion correction of brain images,” NeuroImage, vol. 17, no. 2, pp. 825–841, 2002. View at Publisher · View at Google Scholar · View at Scopus
  35. D. N. Greve and B. Fischl, “Accurate and robust brain image alignment using boundary-based registration,” NeuroImage, vol. 48, no. 1, pp. 63–72, 2009. View at Publisher · View at Google Scholar · View at Scopus
  36. S. Whitfield-Gabrieli and A. Nieto-Castanon, “Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks,” Brain Connectivity, vol. 2, no. 3, pp. 125–141, 2012. View at Publisher · View at Google Scholar
  37. Y. Behzadi, K. Restom, J. Liau, and T. T. Liu, “A component based noise correction method (CompCor) for BOLD and perfusion based fMRI,” NeuroImage, vol. 37, no. 1, pp. 90–101, 2007. View at Publisher · View at Google Scholar · View at Scopus
  38. W. R. Shirer, H. Jiang, C. M. Price, B. Ng, and M. D. Greicius, “Optimization of rs-fMRI pre-processing for enhanced signal-noise separation, test-retest reliability, and group discrimination,” NeuroImage, vol. 117, pp. 67–79, 2015. View at Publisher · View at Google Scholar
  39. J. Richiardi, A. Altmann, A. C. Milazzo, C. Chang, M. M. Chakravarty, T. Banaschewski et al., “Correlated gene expression supports synchronous activity in brain networks,” Science, vol. 348, no. 6240, pp. 1241-1242, 2015, BRAIN NETWORKS. View at Publisher · View at Google Scholar
  40. FIND Lab at Stanford University: Research, https://findlab.stanford.edu/functional_ROIs.html.
  41. J. R. Andrews-Hanna, J. Smallwood, and R. N. Spreng, “The default network and self-generated thought: component processes, dynamic control, and clinical relevance,” Annals of the New York Academy of Sciences, vol. 1316, no. 1, pp. 29–52, 2014. View at Publisher · View at Google Scholar · View at Scopus
  42. M. Corbetta, J. M. Kincade, and G. L. Shulman, “Neural systems for visual orienting and their relationships to spatial working memory,” Journal of Cognitive Neuroscience, vol. 14, no. 3, pp. 508–523, 2002. View at Publisher · View at Google Scholar · View at Scopus
  43. R. Cabeza and L. Nyberg, “Imaging cognition II: an empirical review of 275 PET and fMRI studies,” Journal of Cognitive Neuroscience, vol. 12, no. 1, pp. 1–47, 2000. View at Google Scholar · View at Scopus
  44. S. M. H. Hosseini, D. Koovakkattu, and S. R. Kesler, “Altered small-world properties of gray matter networks in breast cancer,” BMC Neurology, vol. 12, article no. 28, 2012. View at Publisher · View at Google Scholar · View at Scopus
  45. J. Bruno, S. M. H. Hosseini, and S. Kesler, “Altered resting state functional brain network topology in chemotherapy-treated breast cancer survivors,” Neurobiology of Disease, vol. 48, no. 3, pp. 329–338, 2012. View at Publisher · View at Google Scholar · View at Scopus
  46. M. Inagaki, E. Yoshikawa, Y. Matsuoka et al., “Smaller regional volumes of brain gray and white matter demonstrated in breat cancer survivors exposed to adjuvant chemotherapy,” Cancer, vol. 109, no. 1, pp. 146–156, 2007. View at Publisher · View at Google Scholar · View at Scopus
  47. S. R. Kesler, M. Adams, M. Packer, V. Rao, A. M. Henneghan, D. W. Blayney et al., “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, vol. 7, no. 3, 2017. View at Publisher · View at Google Scholar