Title: A systematic review of neuroimaging in delirium. Key Words: delirium, neuroimaging Key Points: 1. Neuroimaging can provide useful information about predictors, correlates and consequences of delirium. 2. Neuroimaging studies offer useful information pertaining to structural risk factors which make an individual more vulnerable to developing delirium. 3. Functional neuroimaging studies demonstrate abnormalities in cerebral perfusion, oxygenation, glucose metabolism and neural connectivity during an episode of delirium, however, small sample sizes prevent firm conclusions from being drawn. 4. There are limited studies examining structural and functional neuroimaging consequences following an episode of delirium. 5. Despite the inherent challenges of performing neuroimaging studies in delirious patients, future research is paramount to further our understanding of the pathophysiology and neural outcomes of this common and serious condition. Names of authors: Anita Nitchingham MBBS 1,2 Varun Kumar MBBS, FRANZCP 3 Susan Shenkin MBChB, BSc (Hons), MSc, MD, FRCP (UK) 4 Karen J Ferguson, BSc, PhD 4
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Title: A systematic review of neuroimaging in delirium.
Key Words: delirium, neuroimaging
Key Points:
1. Neuroimaging can provide useful information about predictors, correlates and consequences of delirium.
2. Neuroimaging studies offer useful information pertaining to structural risk factors which make an individual more vulnerable to developing delirium.
3. Functional neuroimaging studies demonstrate abnormalities in cerebral perfusion, oxygenation, glucose metabolism and neural connectivity during an episode of delirium, however, small sample sizes prevent firm conclusions from being drawn.
4. There are limited studies examining structural and functional neuroimaging consequences following an episode of delirium.
5. Despite the inherent challenges of performing neuroimaging studies in delirious patients, future research is paramount to further our understanding of the pathophysiology and neural outcomes of this common and serious condition.
Names of authors:Anita Nitchingham MBBS1,2 Varun Kumar MBBS, FRANZCP3
Susan Shenkin MBChB, BSc (Hons), MSc, MD, FRCP (UK)4
Karen J Ferguson, BSc, PhD4
Gideon A Caplan MD 1,2
1Department of Geriatric Medicine, Prince of Wales Hospital, Sydney, Australia2Prince of Wales Clinical School, University of New South Wales, Sydney, Australia3Department of Psychiatry, Blacktown Hospital, Sydney, Australia4Department of Geriatric Medicine, The University of Edinburgh, Scotland
Corresponding author:Name: Gideon A Caplan MDAddress: Department of Geriatric Medicine, Prince of Wales Hospital, Edmund
Blackett Building, Randwick, New South Wales 2031 Australia.Telephone: (+61) 02 9382 4252Fax: (+61) 02 9382 4241
Word Count: 4734
Abstract
Objective: Neuroimaging advances our understanding of delirium pathophysiology and its
Microvascular abnormalities indicated by NIRS and TCD may reflect the cerebrovascular deficits
underpinning WMHs and ischemic lesions. More work is required to determine the impact of
small vessel disease on delirium in older patients, but microcirculatory changes resulting in
cytokine release are involved in the development of delirium during sepsis (Sonneville et al.,
2013) which may suggest common neuroinflammatory mechanisms.
Opportunities for future research are vast. Larger sample sizes would enable more definitive
conclusions to be drawn. Studies involving more vulnerable patients such as those with acute
illness and dementia would be more representative. Novel research opportunities include
assessing microcirculatory changes using dynamic susceptibility contrast MR perfusion, and
blood-brain-barrier integrity using contrast-enhanced MRI (Alsop et al., 2006, Wang et al.,
2006). The application of NIRS using units with multiple detectors offer opportunities to assess
variations in oxygenation beyond the frontal lobe as well as multi-modality integration with
MRI.
This review has some limitations. We did not seek unpublished data, only included full text
published articles for quality assessment, and utilised strict inclusion criteria regarding the use
of validated diagnostic tools. It is possible that articles were missed despite screening 4117
articles and hand searching their reference lists. The heterogeneity of study design and imaging
modalities also precluded meta-analysis.
Neuroimaging offers a means of understanding brain-specific predisposing factors as well as
functional and molecular changes during delirium. It also enables investigation of long-term
brain changes associated with delirium, an area that is neglected despite evidence of accelerated
cognitive impairment following delirium. So far, the application of neuroimaging in delirium has
been limited, but with expanding interest, advances in technology and wider scanning
availability, this field will grow and provide valuable insights into delirium pathophysiology.
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Studies identified through database searching
n = 4214
Studies identified though forward citation search
n = 40
Total studies identified after removal of duplicates
n = 4117
Articles retrieved for detailed evaluation
n = 78
Articles excluded after screening titles and abstracts
n = 4039
Articles reviewed for detailed evaluation
n = 84
Additional articles retrieved through: Reference lists, n = 5.
Discussion with field experts, n = 1.
Articles included in systematic reviewn = 32
Articles excludedn = 52
No original material, n = 22.No validated diagnostic criteria for delirium used, n = 10.No neuroimaging data on delirium, n = 9.Assessment of post-operative cognitive impairment not delirium, n = 2.Conference abstract, n = 7. Preliminary report, n = 1 (final report included in review).Article not in English, n = 1.
Figure 1. Flow chart of selection of studies for inclusion in this review.
Reduced grey matter volume (delirium vs no-delirium, expressed as a fraction [%] of total intracranial volume) in:Temporal lobe:5.467±0.665 vs 6.116±0.552 (p<0.0063)Limbic lobe:3.661±0.340 vs 3.973±0.284 (p<0.0063)Temporal transverse gyrus:0.071±0.018 vs 0.381±0.057 (p<0.0036)Middle temporal gyrus:1.664±0.219 vs 1.926±0.219 (p<0.0036)Fusiform gyrus:1.144±0.117 vs 1.291±0.113 (p<0.0036)Hippocampus:0.433±0.092 vs 0.502±0.061 (p<0.0036)
Brown et al., 2015 United States
Prospective cohort;
79 patients, cardiothoracic surgery with elevated risk of stroke.
136 patients, elective surgery (orthopaedic, vascular, GI).
76 CAM, chart review method.
29/136 (21.3%)
DTI
<2 weeks prior to surgery
Delirium incidence and severity associated with pre-surgical DTI abnormalities (lower FA, higher mean, axial and radial diffusivity) in various regions including:Cerebellum, cingulum, thalamus, basal forebrain, occipital, parietal and temporal lobes and hippocampus (p<0.05).
FA delirium vs non-delirium:Cingulum: 0.315±0.026 vs 0.333±0.023; p=0.002.Corpus callosum: 0.353±0.025 vs 0.370±0.022; p=0.002.
Morandi et al., 2012 Prospective 58 CAM-ICU. DTI After adjusting for age and sepsis, longer
United States cohort;
47 patients, surviving ICU admission.
32/47 (68.1%) Hospital discharge and 3 month follow up.
duration of delirium was associated with lower FA at hospital discharge:Genu of Corpus callosum (-0.02, 95%CI: -0.04-0; p = 0.04)Splenium of corpus callosum (-0.01, 95%CI: -0.02-0; p=0.02)Anterior limb of the internal capsule (-0.02, 95%CI: -0.03-20.01; p=0.01)
These associations persisted for 3 months in the genu (-0.02, p=0.02) and splenium (-0.01, p=0.004).
Shioiri et al., 2010 Japan
Prospective cohort;
116 patients, cardiothoracic surgery.
64 DSM IV, DRS-98.
19/119 (16%)
DTI
Preoperative.
Lower FA after adjusting for age: Left subgyral of frontal lobe (p<0.001)Right cingulate gyrus (p<0.001)Left ventral anterior nucleus of thalamus (p<0.01)Corpus callosum (p<0.01).
Resolution of delirium improves FV (p=0.005).FV correlates with delirium severity (p=0.009).
Schramm et al., 2012 Germany
Prospective cohort;
29 patients, severe sepsis in ICU.
64 CAM-ICU.
23/29 (79.3%)
TCD
60 minutes daily for first four days in ICU.
Impaired cerebral AR at day 1 associated with delirium (p=0.035).
Rudolph et al., 2009 United States
Prospective cohort;
68 patients, elective cardiothoracic surgery.
71 CAM.
33/68 (48.5%)
TCD
Opening of pericardium to closure of chest cavity.
Post-operative delirium not associated with increase microemboli intraoperatively:(299± 350 vs 303 ± 449; p=0.97).
Pfister et al., 2008 Switzerland
Prospective cohort;
16 patients,Severe sepsis in ICU.
75 CAM-ICU.
12/16 (75%).
TCD
Over a 60 minute period. (Near-infrared spectroscopy also conducted).
Disturbed AR (p=0.015).
No significant difference in cerebral perfusion.FV (p=0.3).ScO2 (p=0.2).
Jackson et al., 2015 United States
Prospective cohort;
47 patients,
58 CAM-ICU.
32/47 (68.1%)
fMRI
At hospital discharge and 3 months follow
No significant association observed delirium duration and activation of specific brain regions at discharge or 3 months (p>0.25 across all regions of interest).
surviving ICU admission.
up.
Choi et al., 2012 South Korea
Case-control;
42 patients, delirium of varying aetiologies and matched controls.
73 MDAS, DRS-98.
20/42 (47.6%)
fMRI
During delirium.
13 patients underwent repeat imaging following resolution of delirium (mean 5.8 days).
Increased functional connectivity in dorsolateral prefrontal cortex and posterior cingulate cortex (p<0.05).
Increased connectivity in precuneus and posterior cingulate cortex (p<0.05).
Reversible reduction in intralaminar thalamic and caudate nuclei with subcortical regional activity (p<0.05).
Yager et al., 2010 United States
Prospective cohort;
23 patients, bone marrow transplant recipients and healthy controls.
58 MDAS, DRS-98.
5/23 (22%)
1H-MRS
Mean 15.6 days post-bone marrow transplant.
In white matter superior to the corpus callosum:
Higher tCho/tCre (p=0.049).
Lower NAA/tCho (p<0.05).
Haggstrom et al., 2017 Australia
Prospective cohort;
13 patients, acute geriatric unit.
84 CAM, delirium index.
13/13 (100%)
FDG-PET
During delirium.
6 patients underwent repeat imaging following resolution of delirium (mean 73.5 days).
Cortical hypometabolism (13/13) of varying severity and extent which improved with delirium resolution (6/6).
Hypermetabolic sensorimotor cortex (11/13) which resolved with delirium resolution (5/6).
Whole brain metabolism 1.4% higher post-recovery from delirium (p=0.03).
Table 3 – Summary of Neuroimaging Outcomes and Bias AssessmentNeuroimaging Outcomes Studies Total Studies Association
Risk of Bias: A = selection of participants; B = confounding variables; C = assessment of delirium; D = method of imaging; E = Blinding of Imaging Assessments (also see Appendix C).
Table 3 - continued
Appendix A - Search Strategy:
Database: Medline Embase Psycinfo1 Exp delirium/ or
delirium.tw.Exp delirium/ or delirium.tw.
Delirium/ or delirium.tw.
2 Exp confusion/ or Acute confusion.tw.
Acute confusion/ or acute confusion.tw.
Mental confusion/ or acute confusion.tw.
3 1 or 2 1 or 2 1 or 24 Exp Tomography, X-
Ray ComputedExp computer assisted tomography/
Exp tomography/ or neuroimaging/ or magnetic resonance imaging/ or positron emission tomography/ or single photon emission computed tomography/
5 Exp Magnetic Resonance Imaging/
Exp nuclear magnetic resonance imaging/
Functional magnetic resonance imaging/
6 Exp Magnetic Resonance Spectroscopy/
Exp nuclear magnetic resonance spectroscopy/
Magnetic resonance spectroscopy.mp.
7 Functional MRI.mp. Functional magnetic resonance imaging/
Transcranial Doppler.mp.
8 Positron-emission tomography/ or tomography, emission-computed, single-photon/
Positron emission tomography/ or single photon emission computer tomography/
4 or 5 or 6 or 7
9 Ultrasonography, Doppler, Transcranial/
Transcranial Doppler/
3 and 8
10 Exp neuroimaging/ or neuroimaging.mp.
Exp neuroimaging/ or neuroimaging.mp.
Exp BRAIN/
11 4 or 5 or 6 or 7 or 8 or 9 or 10
4 or 5 or 6 or 7 or 8 or 9 or 10
3 and 10
12 3 and 11 3 and 11 9 and 1113 Exp Brain/ Exp brain/ or
brain.mp.Limit 12 to yr=”2006-Current”
14 3 and 13 3 and 1315 12 or 14 12 or 1416 Limit 15 to
yr=”2006-Current”Limit 15 to yr=”2006-Current”
TOTAL: 647 3440 124
Appendix B - BIAS CRITERIA
Adapted from Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS) (Kim et al., 2013)and quality criteria from previous systematic review on Neuroimaging in Delirium (Soiza et al., 2008).
Bias Type: LOW RISK BIAS UNCLEAR HIGH RISK BIASSelection of Participants Method of recruitment and
participant selection is clearly described. Study participants were consecutively recruited.
Case-control studies:Delirious and non-delirious groups are the same population group (identical institution and period) OR they are selected from a comparable population group.
Cohort studies:The absence of delirium was confirmed at the starting point of the study.
It is uncertain whether the selection of participants results in a “high risk” or a “low risk” bias.
It is unclear or not documented how participants were selected.
Study participants were recruited using convenience sampling.
Case-control studies:Delirious and non-delirious groups are selected from different population groups (e.g. differing study centre or historical control groups were used).
Cohort studies:The absence of delirium was not confirmed at the starting point.
Confounding Variables Study reports appropriate information on participant background characteristics. In particular, prevalence and previous diagnosis of dementia, depression, medications, vascular risk factors.
Confounding variables are considered during analysis of
It is unclear is confounding variables were adequately considered.
Major confounding variables are not considered.
Major confounding variables are reported, however, these variables were not adequately considered during the design and analysis phases.
No exploration of possible
results.
For prospective studies, baseline cognitive testing was performed or collateral history was obtained to determine possible cognitive impairment or dementia.
In surgical studies, standardised operating and anaesthetic procedures were adopted.
cognitive impairment or mood disorder.
Assessment of Delirium(Performance and Measurement Bias)
Delirium was assessed prospectively.
Assessment conducted by a dedicated trained clinician.
Delirium assessment was standardised.
Diagnosis of delirium was blinded i.e. without prior knowledge of scan results.
It is uncertain whether delirium assessment results in a “high risk” or “low risk” of bias.
Delirium was identified retrospectively.
It is unclear who conducted delirium assessment. Several clinicians of varying expertise assessed for delirium and inter-rater reliability was not assessed.
Delirium was diagnosed based on one brief clinical encounter.
Method of Imaging(Performance and Measurement Bias)
Scans conducted for the purpose of research on dedicated scanners.
Use of validated methods of measuring scan outcomes. E.g. validated scales measuring white matter disease or brain volumes.
Adequate quality control of scan
It is uncertain whether the method of imaging results in a “high risk” or a “low risk” of bias.
Scans conducted for non-research purposes and retrospectively evaluated.
Low scan report detail. No validated scales utilised.
Inadequate quality control of scan results. E.g. no documentation of
results. E.g. use of two independent radiology reporters OR reporting inter-reporter reliability in two reporters OR use of quantitative analysis e.g. voxel based mapping and single trained reporter interpreted all scans.
For Transcranial Doppler (TCD): Scanning conducted by single trained investigator. TCD and delirium assessments occurred within a defined time period.
For Near-infrared Spectroscopy (NIRS):A clear protocol exists for placement of sensors.
who interpreted scans, single reporter without the use of a predefined scales or semi-quantitative analysis.
For TCD: Scanning conducted by several investigators (not standardised).
For NIRS: No documented protocol for placement of sensors.
Blinding of imaging assessments
Scan reporters were blinded (i.e., no subject information available to the reporter).
Although blinding was not present its absence was judged to have no effect on the outcome of measurements.
It is uncertain whether the exposure measurement results in a “high risk” or a “low risk” of bias.
No documentation regarding blinding.
Scan reporters not blinded, this lack of appropriate blinding appears likely to have affected the outcome measures.
Incomplete data and selective outcome reporting
There is no missing data.
All participants accounted for at conclusion of study.
The experimental protocol is
It is uncertain whether the incomplete outcome data or selective outcome reporting resulted in a “high risk” or a “low risk” of bias.
Missing data could affect study outcomes.
Participants lost to follow up and not accounted for at end of study.
available and the pre-defined primary and secondary outcomes were described as planned.
All of the expected outcomes were included in the study descriptions (even in the absence of the experimental protocols).
The pre-defined primary outcomes were not fully reported.
The outcomes were not reported in accordance with the previously defined standards
Primary outcomes that were not pre-specified in the study existed.
The existence of incomplete reporting regarding the primary outcome of interest.
The absence of reports on important outcomes that would be expected to be reported for studies in related fields.
Kim, S. Y., Park, J. E., Lee, Y. J., Seo, H.-J., Sheen, S.-S., Hahn, S., Jang, B.-H. & Son, H.-J. 2013. Testing a tool for assessing the risk of bias for nonrandomized studies showed moderate reliability and promising validity. Journal of Clinical Epidemiology, 66, 408-414.Soiza, R. L., Sharma, V., Ferguson, K., Shenkin, S. D., Seymour, D. G. & Maclullich, A. M. J. 2008. Neuroimaging studies of delirium: A systematic review. Journal of Psychosomatic Research, 65, 239-248.
Haggstrom et al., 2017 + + ? + ? +Lopez et al., 2017 + + + ? + +Shioiri et al., 2016 + + + ? - +Hshieh et al., 2016 + + + + + -Wood et al., 2016 ? - + + + ?
Naidech et al., 2016 - - + - + +Mailhot et al., 2016 + + - + + +
Cavallari et al., 2016 + + + + + +Omiya et al., 2015 + + + + + +
Jackson et al., 2015 - + + ? - +Cavallari et al., 2015 + + + + + +
Brown et al., 2015 - + - + + +Pierrakos et al., 2014 - - + - + ?
Caplan et al., 2014 + + ? ? + +Root et al., 2013 - - - - - +
Otomo et al., 2013 + + + + + +Hatano et al., 2013 + ? - + + +Polito et al., 2013 - - + - - +
Schramm et al., 2012 - - - + + +Morandi et al., 2012 - + + ? + +
Lai et al., 2012 + + - - + +Kostalova et al., 2012 + + + ? - +Gunther et al., 2012 - + + + + +
Choi et al., 2012 ? - + ? + +Yager et al., 2011 - - + ? ? +
Schoen et al., 2011 + + + + + +Oldenbeuving et al., 2011 + + - ? + -
Shioiri et al., 2010 + + + ? - +Rudolph et al., 2009 ? + + + + +
Morimoto et al., 2009 - + ? + ? ?Pfister et al., 2008 + - - + ? +Fong et al., 2006 - - ? + + ?