Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma

References

1. 1.↵
   1. Biswal B,
   2. Yetkin FZ,
   3. Haughton VM, et al

   . Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34:537–41 pmid:8524021

   CrossRefPubMedWeb of Science
2. 2.↵
   1. Pasquini L,
   2. Peck KK,
   3. Jenabi M, et al

   . Functional MRI in neuro-oncology: state of the art and future directions. Radiology 2023;308:e222028 doi:10.1148/radiol.222028 pmid:37668519

   CrossRefPubMed
3. 3.↵
   1. Gohel S,
   2. Laino ME,
   3. Rajeev-Kumar G, et al

   . Resting-state functional connectivity of the middle frontal gyrus can predict language lateralization in patients with brain tumors. AJNR Am J Neuroradiol 2019;40:319–25 doi:10.3174/ajnr.A5932 pmid:30630835

   Abstract/FREE Full Text
4. 4.↵
   1. Kumar VA,
   2. Heiba IM,
   3. Prabhu SS, et al

   . The role of resting-state functional MRI for clinical preoperative language mapping. Cancer Imaging 2020;20:47 doi:10.1186/s40644-020-00327-w pmid:32653026

   CrossRefPubMed
5. 5.↵
   1. Leuthardt EC,
   2. Guzman G,
   3. Bandt SK, et al

   . Integration of resting state functional MRI into clinical practice: a large single institution experience. PLoS One 2018;13:e0198349 doi:10.1371/journal.pone.0198349 pmid:29933375

   CrossRefPubMed
6. 6.↵
   1. Sair HI,
   2. Yahyavi-Firouz-Abadi N,
   3. Calhoun VD, et al

   . Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: comparison with task fMRI. Hum Brain Mapp 2016;37:913–23 doi:10.1002/hbm.23075 pmid:26663615

   CrossRefPubMed
7. 7.↵
   1. Tie Y,
   2. Rigolo L,
   3. Norton IH, et al

   . Defining language networks from resting-state fMRI for surgical planning: a feasibility study. Hum Brain Mapp 2014;35:1018–30 doi:10.1002/hbm.22231 pmid:23288627

   CrossRefPubMedWeb of Science
8. 8.↵
   1. Greicius MD,
   2. Krasnow B,
   3. Reiss AL, et al

   . Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci U S A 2003;100:253–58 doi:10.1073/pnas.0135058100 pmid:12506194

   Abstract/FREE Full Text
9. 9.↵
   1. Greicius MD,
   2. Supekar K,
   3. Menon V, et al

   . Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex 2009;19:72–78 doi:10.1093/cercor/bhn059 pmid:18403396

   CrossRefPubMedWeb of Science
10. 10.↵
    1. Huang Q,
    2. Zhang R,
    3. Hu X, et al

    . Disturbed small-world networks and neurocognitive function in frontal lobe low-grade glioma patients. PLoS One 2014;9:e94095 doi:10.1371/journal.pone.0094095 pmid:24714669

    CrossRefPubMed
11. 11.↵
    1. Kocher M,
    2. Jockwitz C,
    3. Caspers S, et al

    . Role of the default mode resting-state network for cognitive functioning in malignant glioma patients following multimodal treatment. Neuroimage Clin 2020;27:102287 doi:10.1016/j.nicl.2020.102287 pmid:32540630

    CrossRefPubMed
12. 12.↵
    1. Noll KR,
    2. Chen HS,
    3. Wefel JS, et al

    . Alterations in functional connectomics associated with neurocognitive changes following glioma resection. Neurosurgery 2021;88:544–51 doi:10.1093/neuros/nyaa453 pmid:33080024

    CrossRefPubMed
13. 13.↵
    1. Seitzman BA,
    2. Anandarajah H,
    3. Dworetsky A, et al

    . Cognitive deficits and altered functional brain network organization in pediatric brain tumor patients. Brain Imaging Behav 2023;17:689–701 doi:10.1007/s11682-023-00798-y pmid:37695507

    CrossRefPubMed
14. 14.↵
    1. Wang C,
    2. Van Dyk K,
    3. Cho N, et al

    . Characterization of cognitive function in survivors of diffuse gliomas using resting-state functional MRI (rs-fMRI). Brain Imaging Behav 2022;16:239–51 doi:10.1007/s11682-021-00497-6 pmid:34350525

    CrossRefPubMed
15. 15.↵
    1. Nayak L,
    2. DeAngelis LM,
    3. Brandes AA, et al

    . The Neurologic Assessment in Neuro-Oncology (NANO) scale: a tool to assess neurologic function for integration into the Response Assessment in Neuro-Oncology (RANO) criteria. Neuro Oncol 2017;19:625–35 doi:10.1093/neuonc/nox029 pmid:28453751

    CrossRefPubMed
16. 16.↵
    1. Correa DD

    . Neurocognitive function in brain tumors. Curr Neurol Neurosci Rep 2010;10:232–39 doi:10.1007/s11910-010-0108-4 pmid:20425039

    CrossRefPubMed
17. 17.↵
    1. Kickingereder P,
    2. Sahm F,
    3. Radbruch A, et al

    . IDH mutation status is associated with a distinct hypoxia/angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging in human glioma. Sci Rep 2015;5:16238 doi:10.1038/srep16238 pmid:26538165

    CrossRefPubMed
18. 18.↵
    1. Leu K,
    2. Ott GA,
    3. Lai A, et al

    . Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II–III diffuse gliomas. J Neurooncol 2017;134:177–88 doi:10.1007/s11060-017-2506-9 pmid:28547590

    CrossRefPubMed
19. 19.↵
    1. Fatterpekar GM,
    2. Galheigo D,
    3. Narayana A, et al

    . Treatment-related change versus tumor recurrence in high-grade gliomas: a diagnostic conundrum—use of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI. AJR Am J Roentgenol 2012;198:19–26 doi:10.2214/AJR.11.7417 pmid:22194475

    CrossRefPubMed
20. 20.↵
    1. Kim YH,
    2. Oh SW,
    3. Lim YJ, et al

    . Differentiating radiation necrosis from tumor recurrence in high-grade gliomas: assessing the efficacy of 18F-FDG PET, 11C-methionine PET and perfusion MRI. Clin Neurol Neurosurg 2010;112:758–65 doi:10.1016/j.clineuro.2010.06.005 pmid:20619531

    CrossRefPubMed
21. 21.↵
    1. Kumar VA,
    2. Lee J,
    3. Liu HL, et al

    . Recommended resting-state fMRI acquisition and preprocessing steps for preoperative mapping of language and motor and visual areas in adult and pediatric patients with brain tumors and epilepsy. AJNR Am J Neuroradiol 2024;45:139–48 doi:10.3174/ajnr.A8067 pmid:38164572

    Abstract/FREE Full Text
22. 22.↵
    1. Wefel JS,
    2. Vardy J,
    3. Ahles T, et al

    . International Cognition and Cancer Task Force recommendations to harmonise studies of cognitive function in patients with cancer. Lancet Oncol 2011;12:703–08 doi:10.1016/S1470-2045(10)70294-1 pmid:21354373

    CrossRefPubMedWeb of Science
23. 23.↵
    1. Reijneveld JC,
    2. Sitskoorn MM,
    3. Klein M, et al

    . Cognitive status and quality of life in patients with suspected versus proven low-grade gliomas. Neurology 2001;56:618–23 doi:10.1212/wnl.56.5.618 pmid:11245713

    CrossRefPubMed
24. 24.↵
    1. Ingraham LJ,
    2. Aiken CB

    . An empirical approach to determining criteria for abnormality in test batteries with multiple measures. Neuropsychology 1996;10:120–24 doi:10.1037/0894-4105.10.1.120

    CrossRefWeb of Science
25. 25.↵
    1. Ellingson BM,
    2. Bendszus M,
    3. Boxerman J, et al

    ; Jumpstarting Brain Tumor Drug Development Coalition Imaging Standardization Steering Committee. Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials. Neuro Oncol 2015;17:1188–98 doi:10.1093/neuonc/nov095 pmid:26250565

    CrossRefPubMed
26. 26.↵
    1. Whitfield-Gabrieli S,
    2. Nieto-Castanon A

    . Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect 2012;2:125–41 doi:10.1089/brain.2012.0073 pmid:22642651

    CrossRefPubMed
27. 27.↵
    1. Jenkinson M,
    2. Beckmann CF,
    3. Behrens TEJ, et al

    . FSL. Neuroimage 2012;62:782–90 doi:10.1016/j.neuroimage.2011.09.015 pmid:21979382

    CrossRefPubMedWeb of Science
28. 28.↵
    1. Otten ML,
    2. Mikell CB,
    3. Youngerman BE, et al

    . Motor deficits correlate with resting state motor network connectivity in patients with brain tumours. Brain 2012;135:1017–26 doi:10.1093/brain/aws041 pmid:22408270

    CrossRefPubMed
29. 29.↵
    1. Leu K,
    2. Boxerman JL,
    3. Cloughesy TF, et al

    . Improved leakage correction for single-echo dynamic susceptibility contrast perfusion MRI estimates of relative cerebral blood volume in high-grade gliomas by accounting for bidirectional contrast agent exchange. AJNR Am J Neuroradiol 2016;37:1440–46 doi:10.3174/ajnr.A4759 pmid:27079371

    Abstract/FREE Full Text
30. 30.↵
    1. Leu K,
    2. Boxerman JL,
    3. Lai A, et al

    . Bidirectional contrast agent leakage correction of dynamic susceptibility contrast (DSC)-MRI improves cerebral blood volume estimation and survival prediction in recurrent glioblastoma treated with bevacizumab. J Magn Reson Imaging 2016;44:1229–37 doi:10.1002/jmri.25227 pmid:26971534

    CrossRefPubMed
31. 31.↵
    1. Cox RW

    . AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 1996;29:162–73 doi:10.1006/cbmr.1996.0014 pmid:8812068

    CrossRefPubMedWeb of Science
32. 32.↵
    1. Hanley JA,
    2. McNeil BJ

    . A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983;148:839–43 doi:10.1148/radiology.148.3.6878708 pmid:6878708

    CrossRefPubMedWeb of Science
33. 33.↵
    1. Rudie JD,
    2. Brown JA,
    3. Beck-Pancer D, et al

    . Altered functional and structural brain network organization in autism. Neuroimage Clin 2012;2:79–94 doi:10.1016/j.nicl.2012.11.006 pmid:24179761

    CrossRefPubMed
34. 34.↵
    1. Tomasi D,
    2. Volkow ND

    . Aging and functional brain networks. Mol Psychiatry 2012;17:549–58 doi:10.1038/mp.2011.81 pmid:21727896

    CrossRefPubMedWeb of Science
35. 35.↵
    1. Wang K,
    2. Liang M,
    3. Wang L, et al

    . Altered functional connectivity in early Alzheimer's disease: A resting-state fMRI study. Hum Brain Mapp 2007;28:967–78 doi:10.1002/hbm.20324 pmid:17133390

    CrossRefPubMedWeb of Science
36. 36.↵
    1. Park CH,
    2. Chang WH,
    3. Ohn SH, et al

    . Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke 2011;42:1357–62 doi:10.1161/STROKEAHA.110.596155 pmid:21441147

    Abstract/FREE Full Text
37. 37.↵
    1. Daniel AGS,
    2. Park KY,
    3. Roland JL, et al

    . Functional connectivity within glioblastoma impacts overall survival. Neuro Oncol 2021;23:412–21 doi:10.1093/neuonc/noaa189 pmid:32789494

    CrossRefPubMed
38. 38.↵
    1. Petridis PD,
    2. Horenstein CI,
    3. Pereira B, et al

    . BOLD asynchrony elucidates tumor burden in IDH-mutated gliomas. Neuro Oncol 2022;24:78–87 doi:10.1093/neuonc/noab154 pmid:34214170

    CrossRefPubMed
39. 39.↵
    1. Boxerman JL,
    2. Quarles CC,
    3. Hu LS, et al

    ; Jumpstarting Brain Tumor Drug Development Coalition Imaging Standardization Steering Committee. Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas. Neuro Oncol 2020;22:1262–75 doi:10.1093/neuonc/noaa141 pmid:32516388

    CrossRefPubMed
40. 40.↵
    1. Van Dijk KR,
    2. Hedden T,
    3. Venkataraman A, et al

    . Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. J Neurophysiol 2010;103:297–321 doi:10.1152/jn.00783.2009 pmid:19889849

    CrossRefPubMedWeb of Science
41. 41.↵
    1. Ellingson BM,
    2. Bendszus M,
    3. Boxerman J, et al

    ; Jumpstarting Brain Tumor Drug Development Coalition Imaging Standardization Steering Committee. Consensus recommendations for a standardized brain tumor imaging protocol in clinical trials. Neuro Oncol 2015;17:1188–98 doi:10.1093/neuonc/nov095 pmid:26250565

    CrossRefPubMed
42. 42.↵
    1. Chakhoyan A,
    2. Leu K,
    3. Pope WB, et al

    . Improved spatiotemporal resolution of dynamic susceptibility contrast perfusion MRI in brain tumors using simultaneous multi-slice echo-planar imaging. AJNR Am J Neuroradiol 2018;39:43–45 doi:10.3174/ajnr.A5433 pmid:29074632

    Abstract/FREE Full Text
43. 43.↵
    1. Bathla G,
    2. Gene MN,
    3. Peck KK, et al

    . Resting state functional connectivity of the supplementary motor area to motor and language networks in patients with brain tumors. J Neuroimaging 2019;29:521–26 doi:10.1111/jon.12624 pmid:31034698

    CrossRefPubMed
44. 44.↵
    1. Cho NS,
    2. Peck KK,
    3. Gene MN, et al

    . Resting-state functional MRI language network connectivity differences in patients with brain tumors: exploration of the cerebellum and contralesional hemisphere. Brain Imaging Behav 2022;16:252–62 doi:10.1007/s11682-021-00498-5 pmid:34333725

    CrossRefPubMed
45. 45.↵
    1. Stokes AM,
    2. Bergamino M,
    3. Alhilali L, et al

    . Evaluation of single bolus, dual-echo dynamic susceptibility contrast MRI protocols in brain tumor patients. J Cereb Blood Flow Metab 2021;41:3378–90 doi:10.1177/0271678X211039597 pmid:34415211

    CrossRefPubMed
46. 46.↵
    1. Tordjman M,
    2. Madelin G,
    3. Gupta PK, et al

    . Functional connectivity of the default mode, dorsal attention and fronto-parietal executive control networks in glial tumor patients. J Neurooncol 2021;152:347–55.doi:10.1007/s11060-021-03706-w pmid:33528739

    CrossRefPubMed
47. 47.↵
    1. Gardini S,
    2. Venneri A,
    3. Sambataro F, et al

    . Increased functional connectivity in the default mode network in mild cognitive impairment: a maladaptive compensatory mechanism associated with poor semantic memory performance. J Alzheimers Dis 2015;45:457–70 doi:10.3233/JAD-142547 pmid:25547636

    CrossRefPubMed
48. 48.↵
    1. Zhu S,
    2. Fang Z,
    3. Hu S, et al

    . Resting-state brain function analysis using concurrent BOLD in ASL perfusion fMRI. PL0S One 2013;8:e65884 doi:10.1371/journal.pone.0065884 pmid:23750275

    CrossRefPubMed