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• W3184590031 abstract "HomeRadiologyVol. 301, No. 1 PreviousNext Reviews and CommentaryFree AccessEditorialTwo for the Price of One? Analyzing Task-based fMRI Data with Resting-State fMRI MethodsAaron Field , Rasmus BirnAaron Field , Rasmus BirnAuthor AffiliationsFrom the Departments of Radiology (A.F.) and Psychiatry (R.B.), University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, M/C 3252, Madison, WI 53792.Address correspondence to A.F. (e-mail: [email protected]).Aaron Field Rasmus BirnPublished Online:Jul 20 2021https://doi.org/10.1148/radiol.2021211239MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In See also the article by Beheshtian et al in this issue.Dr Field is a tenured professor and past chief of neuroradiology in the department of radiology at the University of Wisconsin–Madison. He conducts basic and clinical research involving quantitative MRI of cerebral diffusion, perfusion, magnetization transfer, and T1- and T2-relaxation phenomena, including diffusion tensor imaging and functional MRI. He was recently named an inaugural fellow of the American Society of Functional Neuroradiology.Download as PowerPointOpen in Image Viewer Dr Birn is an associate professor in the departments of psychiatry and medical physics at the University of Wisconsin–Madison. His research is focused on improving the usefulness of fMRI, including developing new imaging strategies and postprocessing techniques to reduce artifacts resulting from patient motion, understanding the dynamics of the BOLD fMRI signal, and reducing the influence of motion and physiologic noise in estimates of functional connectivity.Download as PowerPointOpen in Image Viewer Clinical applications of blood oxygen level–dependent (BOLD) functional MRI (fMRI) have focused on imaging patients while they perform a task designed to elicit the activation of some eloquent cortical network (language, somatomotor, and so on) for preoperative planning. Such task-based fMRI (tb-fMRI) requires that patients be engaged, cooperative, and able to perform the necessary tasks during imaging examinations that may take an hour or more to complete. However, many patients with brain tumors are unable to meet these demands. Therefore, radiology practices are increasingly turning toward an fMRI approach performed with patients at rest or even under sedation. So-called resting-state fMRI (rs-fMRI) is based on the existence of metabolic activity spontaneously oscillating at low frequencies in the cerebral cortex. This phenomenon was recognized well before the development of fMRI and found to exhibit synchrony between homotopic cortical regions (1). Years later, these synchronized low-frequency fluctuations were found in the BOLD signal of resting humans (2). After numerous studies validating that these fluctuations can be used to map various functional brain networks (3–5), an explosion of “functional connectivity” fMRI research followed.Functionally connected networks typically targeted with tb-fMRI (eg, language, somatomotor) can instead be identified with detection of spatiotemporally synchronized low-frequency fluctuations in BOLD signal spontaneously ongoing during an rs-fMRI acquisition lasting several minutes (2). These patterns are extracted from rs-fMRI data by using statistical time-series analysis methods, such as independent component analysis (ICA) (6). The rs-fMRI may be a backup to the more straightforward and reliable tb-fMRI in the event that the latter cannot be performed. However, can rs-fMRI analysis methods (eg, ICA) be effectively applied to tb-fMRI data to identify functional networks other than that which the task was designed to activate? If this can be reliably done, then tb-fMRI examinations could be shortened by using one acquisition to map multiple networks. For example, both language and somatomotor networks might be identifiable using a language task alone. Such a “two-for-one” opportunity could improve patient compliance with fMRI examinations by making them shorter or salvage examinations that are prematurely aborted or partially compromised by patient motion (both fairly common occurrences in clinical practice).Spontaneous, synchronized fluctuations continue to occur during task performance. Arfanakis et al (7) removed the task-related dynamics from tb-fMRI data using ICA and then found spatiotemporally correlated fluctuations in the residual data. Later studies (8,9) showed that connectivity maps generated from fluctuations occurring in the background during task-related dynamics are similar to those generated from rs-fMRI. While such studies identify differences in the strength of functional connectivity across different tasks or between task and rest, they retain the key identification and localization of brain networks.In this issue of Radiology, Beheshtian et al (10) assessed the clinical feasibility of using resting-state methods on tb-fMRI data for preoperative planning. In 100 patients, the authors performed both rs-fMRI and tb-fMRI using a sentence completion language task (sentence completion fMRI [sc-fMRI]). The dorsal somatomotor network (dSMN) (upper and lower extremities) and ventral somatomotor network (vSMN) (orofacial muscles) were mapped from both the rs-fMRI and sc-fMRI data with use of ICA. A neuroradiologist blinded to the original data sources reviewed the resulting network maps. The authors found that sc-fMRI data subjected to ICA yielded successful vSMN mapping nearly as often as did rs-fMRI data (in 59% vs 65% of patients, respectively). Results were better for the dSMN, with essentially the same identification rate for both data sources (86% vs 85%). Further, sc-fMRI was able to demonstrate the somatomotor network in a substantial fraction of patients for whom rs-fMRI failed to do so (75% for the dSMN and 46% for the vSMN).For patients unable to perform the tasks required for tb-fMRI, rs-fMRI can be an essential fallback as the only means available for preoperative mapping. For patients who can undergo tb-fMRI, the role of rs-fMRI is less clear; tb-fMRI is more straightforward to perform and yields more reliable language and somatomotor mapping than rs-fMRI (albeit with a smaller difference for the latter). In cooperative patients, tb-fMRI would be chosen for both language and motor mapping, rather than tb-fMRI for language and rs-fMRI for the somatomotor network. In other words, the single-sequence approach described by Beheshtian et al (10) would substitute not for rs-fMRI, but for a multiple–tb-fMRI approach. Therefore, rather than compare sc-fMRI to rs-fMRI for mapping the somatomotor network, it is arguably more meaningful to compare sc-fMRI to the reference standard tb-fMRI. In a subset of 61 patients, tb-fMRI was performed with use of a somatomotor finger-tapping task, and dSMN was mapped using a standard approach. They reported that these maps generally overlapped with those from sc-fMRI, which is encouraging. It would be interesting to examine the strength and topographic distribution of this correspondence in detail.The idea of applying rs-fMRI analysis methods to tb-fMRI data, extracting a functional network other than the one targeted by the task, is well known in the research domain, but in clinical practice, it is novel and has substantial time-savings potential. This has two important benefits. First, patient motion often becomes more detrimental to image quality as MRI examinations get longer. Second, patients often decide to terminate long examinations prematurely. In such cases, the ability to map a network planned for a later acquisition from an earlier one could salvage an examination that would otherwise remain incomplete. Because many clinical fMRI examinations feature a battery of tasks targeting multiple networks, future work might be aimed at determining which tb-fMRI paradigms are most useful for revealing other networks when subjected to ICA; those acquisitions could then be prioritized accordingly during an examination.The methods of rs-fMRI may be less familiar to many radiologists currently using tb-fMRI for preoperative brain mapping. Increasingly, radiologists are being asked to perform fMRI in young children, sedated adults, and patients with a variety of neurocognitive deficits, including hemiplegia, aphasia, and even vegetative states. The rs-fMRI makes functional brain mapping possible in these challenging patients. In demonstrating that rs-fMRI methods can yield alternate network maps from traditional tb-fMRI data in a clinically feasible way, Beheshtian et al have given us one more reason to include rs-fMRI methods in our functional imaging armamentarium.Disclosures of Conflicts of Interest: A.F. disclosed no relevant relationships. R.B. disclosed no relevant relationships.References1. Vern BA, Schuette WH, Leheta B, Juel VC, Radulovacki M. Low-frequency oscillations of cortical oxidative metabolism in waking and sleep. J Cereb Blood Flow Metab 1988;8(2):215–226. Crossref, Medline, Google Scholar2. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34(4):537–541. Crossref, Medline, Google Scholar3. Cordes D, Haughton VM, Arfanakis K, et al. Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data. AJNR Am J Neuroradiol 2001;22(7):1326–1333. Medline, Google Scholar4. Quigley M, Cordes D, Turski P, et al. Role of the corpus callosum in functional connectivity. AJNR Am J Neuroradiol 2003;24(2):208–212. Medline, Google Scholar5. Johnston JM, Vaishnavi SN, Smyth MD, et al. Loss of resting interhemispheric functional connectivity after complete section of the corpus callosum. J Neurosci 2008;28(25):6453–6458. Crossref, Medline, Google Scholar6. Smitha KA, Akhil Raja K, Arun KM, et al. Resting state fMRI: a review on methods in resting state connectivity analysis and resting state networks. Neuroradiol J 2017;30(4):305–317. Crossref, Medline, Google Scholar7. Arfanakis K, Cordes D, Haughton VM, Moritz CH, Quigley MA, Meyerand ME. Combining independent component analysis and correlation analysis to probe interregional connectivity in fMRI task activation datasets. Magn Reson Imaging 2000;18(8):921–930. Crossref, Medline, Google Scholar8. Fair DA, Schlaggar BL, Cohen AL, et al. A method for using blocked and event-related fMRI data to study “resting state” functional connectivity. Neuroimage 2007;35(1):396–405. Crossref, Medline, Google Scholar9. Shah LM, Cramer JA, Ferguson MA, Birn RM, Anderson JS. Reliability and reproducibility of individual differences in functional connectivity acquired during task and resting state. Brain Behav 2016;6(5):e00456. Crossref, Medline, Google Scholar10. Beheshtian E, Jalilianhasanpour R, Shanechi AM, et al. Identification of the somatomotor network from language task–based fMRI compared with resting-state fMRI in patients with brain lesions. Radiology 2021. https://doi.org/10.1148/radiol.2021204594. Published online July 20, 2021. Link, Google ScholarArticle HistoryReceived: May 14 2021Revision requested: May 25 2021Revision received: May 28 2021Accepted: June 01 2021Published online: July 20 2021Published in print: Oct 2021 FiguresReferencesRelatedDetailsAccompanying This ArticleIdentification of the Somatomotor Network from Language Task–based fMRI Compared with Resting-State fMRI in Patients with Brain LesionsJul 20 2021RadiologyRecommended Articles Wheat from the Chaff: Denoising Functional MRI DataRadiology2021Volume: 299Issue: 1pp. 49-50Whole-Brain Functional and Diffusion Tensor MRI in Human Participants with Metallic Orthodontic BracesRadiology2019Volume: 294Issue: 1pp. 149-157Performing Diffusion Tensor and Functional MRI in Patients with Metallic BracesRadiology2019Volume: 294Issue: 1pp. 158-159Resting-State Functional MRI Changes in Normal Human AgingRadiology2022Volume: 304Issue: 3pp. 633-6342016 RSNA Outstanding ResearcherRadiology2016Volume: 281Issue: 3pp. 663-664See More RSNA Education Exhibits Advanced Imaging Evaluation of Pediatric Language Pathways: Where Do We StandDigital Posters2022Deep-Brain: A Cutting-edge Concept for Outstanding Functional Resolution in fMRIDigital Posters2020Function And Fibers - Functional MRI And DTI Fiber Tractography Application In Brain Tumor ResectionDigital Posters2021 RSNA Case Collection Central Pontine MyelinolisisRSNA Case Collection2021 Grey matter HeterotopiaRSNA Case Collection2021Post-carotid-endarterectomy cerebral hyperperfusion syndromeRSNA Case Collection2021 Vol. 301, No. 1 Metrics Altmetric Score PDF download" @default.
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