1naresh<pre>Array
(
    [urn:ac.highwire.org:guest:identity] => Array
        (
            [runtime-id] => urn:ac.highwire.org:guest:identity
            [type] => guest
            [service-id] => ajnr-ac.highwire.org
            [access-type] => Controlled
            [privilege] => Array
                (
                    [urn:ac.highwire.org:guest:privilege] => Array
                        (
                            [runtime-id] => urn:ac.highwire.org:guest:privilege
                            [type] => privilege-set
                            [privilege-set] => GUEST
                        )

                )

            [credentials] => Array
                (
                    [method] => guest
                )

        )

)
1naresh<pre>Array
(
    [urn:ac.highwire.org:guest:identity] => Array
        (
            [runtime-id] => urn:ac.highwire.org:guest:identity
            [type] => guest
            [service-id] => ajnr-ac.highwire.org
            [access-type] => OpenAccess
            [privilege] => Array
                (
                    [urn:ac.highwire.org:guest:privilege] => Array
                        (
                            [runtime-id] => urn:ac.highwire.org:guest:privilege
                            [type] => privilege-set
                            [privilege-set] => GUEST
                        )

                )

            [credentials] => Array
                (
                    [method] => guest
                )

        )

)
PT  - JOURNAL ARTICLE
AU  - Parsons, N.
AU  - Outsikas, A.
AU  - Parish, A.
AU  - Clohesy, R.
AU  - D’Aprano, F.
AU  - Toomey, F.
AU  - Advani, S.
AU  - Poudel, G.R.
TI  - Modelling the Anatomic Distribution of Neurologic Events in Patients with COVID-19: A Systematic &lt;br/&gt;Review of MRI Findings
AID  - 10.3174/ajnr.A7113
DP  - 2021 Jul 01
TA  - American Journal of Neuroradiology
PG  - 1190--1195
VI  - 42
IP  - 7
4099  - http://www.ajnr.org/content/42/7/1190.short
4100  - http://www.ajnr.org/content/42/7/1190.full
SO  - Am. J. Neuroradiol.2021 Jul 01; 42
AB  - BACKGROUND: Neurologic events have been reported in patients with coronavirus disease 2019 (COVID-19). However, a model-based evaluation of the spatial distribution of these events is lacking.PURPOSE: Our aim was to quantitatively evaluate whether a network diffusion model can explain the spread of small neurologic events.DATA SOURCES: The MEDLINE, EMBASE, Scopus, and LitCovid data bases were searched from January 1, 2020, to July 19, 2020.STUDY SELECTION: Thirty-five case series and case studies reported 317 small neurologic events in 123 unique patients with COVID-19.DATA ANALYSIS: Neurologic events were localized to gray or white matter regions of the Illinois Institute of Technology (gray-matter and white matter) Human Brain Atlas using radiologic images and descriptions. The total proportion of events was calculated for each region. A network diffusion model was implemented, and any brain regions showing a significant association (P &amp;lt; .05, family-wise error–corrected) between predicted and measured events were considered epicenters.DATA SYNTHESIS: Within gray matter, neurologic events were widely distributed, with the largest number of events (∼10%) observed in the bilateral superior temporal, precentral, and lateral occipital cortices, respectively. Network diffusion modeling showed a significant association between predicted and measured gray matter events when the spread of pathology was seeded from the bilateral cerebellum (r = 0.51, P &amp;lt; .001, corrected) and putamen (r = 0.4, P = .02, corrected). In white matter, most events (∼26%) were observed within the bilateral corticospinal tracts.LIMITATIONS: The risk of bias was not considered because all studies were either case series or case studies.CONCLUSIONS: Transconnectome diffusion of pathology via the structural network of the brain may contribute to the spread of neurologic events in patients with COVID-19.COVID-19coronavirus disease 2019IITIllinois Institute of TechnologyNDMnetwork diffusion modelSARS-CoV-2Severe Acute Respiratory Syndrome coronavirus 2