Impact of Total Knee Arthroplasty with General Anesthesia on Brain Networks: Cognitive Efficiency and Ventricular Volume Predict Functional Connectivity Decline in Older Adults
Restricted accessResearch articleFirst published online February 6, 2018
Impact of Total Knee Arthroplasty with General Anesthesia on Brain Networks: Cognitive Efficiency and Ventricular Volume Predict Functional Connectivity Decline in Older Adults
Using resting state functional magnetic resonance imaging (RS-fMRI), we explored: 1) pre- to post-operative changes in functional connectivity in default mode, salience, and central executive networks after total knee arthroplasty (TKA) with general anesthesia, and 2) the contribution of cognitive/brain reserve metrics these resting state functional declines. Individuals age 60 and older electing unilateral total knee arthroplasty (TKA; n = 48) and non-surgery peers with osteoarthritis (n = 45) completed baseline cognitive testing and baseline and post-surgery (post-baseline, 48-h post-surgery) brain MRI. We acquired cognitive and brain estimates for premorbid (vocabulary, reading, education, intracranial volume) and current (working memory, processing speed, declarative memory, ventricular volume) reserve. Functional network analyses corrected for pain severity and pain medication. The surgery group declined in every functional network of interest (p < 0.001). Relative to non-surgery peers, 23% of surgery participants declined in at least one network and 15% of the total TKA sample declined across all networks. Larger preoperative ventricular volume and lower scores on preoperative metrics of processing speed and working memory predicted default mode network connectivity decline. Premorbid cognitive and premorbid brain reserve did not predict decline. Within 48 hours after surgery, at least one fourth of the older adult sample showed significant functional network decline. Metrics of current brain status (ventricular volume), working memory, and processing speed predicted the severity of default mode network connectivity decline. These findings demonstrate the relevance of preoperative cognition and brain integrity on acute postoperative functional network change.
LuckT, ThenFS, SchroeterML, WitteV, EngelC, LoefflerM, ThieryJ, VillringerA, Riedel-HellerSG (2017) Prevalence of DSM-5 mild neurocognitive disorder in dementia-free older adults: Results of the population-based life-adult-study. Am J Geriatr Psychiatry25, 328–339.
2.
MollerJT, CluitmansP, RasmussenLS, HouxP, RasmussenH, CanetJ, RabbittP, JollesJ, LarsenK, HanningCD, LangeronO, JohnsonT, LauvenPM, KristensenPA, BiedlerA, van BeemH, FraidakisO, SilversteinJH, BenekenJE, GravensteinJS (1998) Long-term postoperative cognitive dysfunction in the elderly ISPOCD1 study. ISPOCD investigators. International study of post-operative cognitive dysfunction. Lancet351, 857–861.
3.
MonkTG, WeldonBC, GarvanCW, DedeDE, van der AaMT, HeilmanKM, GravensteinJS (2008) Predictors of cognitive dysfunction after major noncardiac surgery. Anesthesiology108, 18–30.
4.
AbildstromH, RasmussenLS, RentowlP, HanningCD, RasmussenH, KristensenPA, MollerJT (2000) Cognitive dysfunction 1-2 years after non-cardiac surgery in the elderly. ISPOCD group. International study of post-operative cognitive dysfunction. Acta Anaesthesiol Scand44, 1246–1251.
5.
RasmussenLS, JohnsonT, KuipersHM, KristensenD, SiersmaVD, VilaP, JollesJ, PapaioannouA, AbildstromH, SilversteinJH, BonalJA, RaederJ, NielsenIK, KorttilaK, MunozL, DoddsC, HanningCD, MollerJT (2003) Does anaesthesia cause postoperative cognitive dysfunction? A randomised study of regional versus general anaesthesia in 438 elderly patients. Acta Anaesthesiol Scand47, 260–266.
6.
GreeneNH, AttixDK, WeldonBC, SmithPJ, McDonaghDL, MonkTG (2009) Measures of executive function and depression identify patients at risk for postoperative delirium. Anesthesiology110, 788–795.
7.
SmithPJ, AttixDK, WeldonBC, GreeneNH, MonkTG (2009) Executive function and depression as independent risk factors for postoperative delirium. Anesthesiology110, 781–787.
8.
ShioiriA, KurumajiA, TakeuchiT, NemotoK, AraiH, NishikawaT (2016) A decrease in the volume of gray matter as a risk factor for postoperative delirium revealed by an atlas-based method. Am J Geriatr Psychiatry24, 528–536.
9.
SaczynskiJS, InouyeSK, KosarCM, TommetD, MarcantonioER, FongT, HshiehT, VasunilashornS, MetzgerED, SchmittE, AlsopDC, JonesRN, SAGES Study Group (2014) Cognitive and brain reserve and the risk of postoperative delirium in older patients: Analysis of data from a prospective observational study. Lancet Psychiatry1, 437–443.
10.
PriceCC, GarvanC, HizelL, LopezMG, BillingsI, FredericT (2017) Delayed recall and working memory MMSE domains predict delirium following cardiac surgery. J Alzheimers Dis59, 1027–1035.
11.
PriceCC, TannerJJ, SchmalfussI, GarvanCW, GearenP, DickeyD, HeilmanK, McDonaghDL, LibonDJ, LeonardC, BowersD, MonkTG (2014) A pilot study evaluating presurgery neuroanatomical biomarkers for postoperative cognitive decline after total knee arthroplasty in older adults. Anesthesiology120, 601–613.
12.
MenonV (2011) Large-scale brain networks and psychopathology: A unifying triple network model. Trends Cogn Sci15, 483–506.
13.
VassalM, CharroudC, DeverdunJ, Le BarsE, MolinoF, BonnetblancF, BoyerA, DuttaA, HerbetG, Moritz-GasserS, BonaféA, DuffauH, de ChampfleurNM (2017) Recovery of functional connectivity of the sensorimotor network after surgery for diffuse low-grade gliomas involving the supplementary motor area. J Neurosurg126, 1181–1190.
14.
HartMG, PriceSJ, SucklingJ (2017) Functional connectivity networks for preoperative brain mapping in neurosurgery. J Neurosurg126, 1941–1950.
15.
BrowndykeJN, BergerM, HarshbargerTB, SmithPJ, WhiteW, BisanarTL, AlexanderJH, GacaJG, Welsh-BohmerK, NewmanMF, MathewJP (2017) Resting-state functional connectivity and cognition after major cardiac surgery in older adults without preoperative cognitive impairment: Preliminary findings. J Am Geriatr Soc65, e6–e12.
16.
PalancaBJA, MitraA, Larson-PriorL, SnyderAZ, AvidanMS, RaichleME (2015) Resting state functional magnetic resonance imaging correlates of sevoflurane-induced unconsciousness. Anesthesiology123, 346–356.
17.
AmicoE, GomezF, Di PerriC, VanhaudenhuyseA, LesenfantsD, BoverouxP, BonhommeV, BrichantJ-F, MarinazzoD, LaureysS (2014) Posterior cingulate cortex-related co-activation patterns: A resting state fMRI study in propofol-induced loss of consciousness. PLoS One9, e100012.
18.
NoirhommeQ, SodduA, LehembreR, VanhaudenhuyseA, BoverouxP, BolyM, LaureysS (2010) Brain connectivity in pathological and pharmacological coma. Front Sys Neurosci4, 160.
19.
HudetzAG (2012) General anesthesia and human brain connectivity. Brain Connect2, 291–302.
20.
RiehlJR, PalancaBJ, ChingS (2017) High energy brain dynamics during anesthesia-induced unconsciousness. Netw Neurosci1, 431–445.
21.
ChoiS-H, LeeH, ChungT-S, ParkK-M, JungY-C, KimSI, KimJ-J (2012) Neural network functional connectivity during and after an episode of delirium. Am J Psychiatry169, 498–507.
22.
MohanA, RobertoAJ, MohanA, LorenzoA, JonesK, CarneyMJ, Liogier-WeybackL, HwangS, LapidusKAB (2016) The significance of the default mode network (DMN) in neurological and neuropsychiatric disorders: A review. Yale J Biol Med89, 49–57.
23.
BucknerRL, Andrews-HannaJR, SchacterDL (2008) The brain’s default network: Anatomy, function, and relevance to disease. Ann N Y Acad Sci1124, 1–38.
Andrews-HannaJR, SnyderAZ, VincentJL, LustigC, HeadD, Raichle MarcusE, BucknerRL (2007) Disruption of large-scale brain systems in advanced aging. Neuron56, 924–935.
26.
DamoiseauxJS, BeckmannCF, ArigitaEJS, BarkhofF, ScheltensP, StamCJ, SmithSM, RomboutsSARB (2008) Reduced resting-state brain activity in the “default network” in normal aging. Cereb Cortex18, 1856–1864.
27.
McFaddenKL, CornierM-A, MelansonEL, BechtellJL, TregellasJR (2013) Effects of exercise on resting-state default mode and salience network activity in overweight/obese adults. Neuroreport24, 866–871.
28.
Sole-PadullesC, Bartres-FazD, LladoA, BoschB, Pena-GomezC, CastellviM, RamiL, BargalloN, Sanchez-ValleR, MolinuevoJL (2013) Donepezil treatment stabilizes functional connectivity during resting state and brain activity during memory encoding in Alzheimer’s disease. J Clin Psychopharmacol33, 199–205.
29.
HeX, QinW, LiuY, ZhangX, DuanY, SongJ, LiK, JiangT, YuC (2014) Abnormal salience network in normal aging and in amnestic mild cognitive impairment and Alzheimer’s disease. Hum Brain Mapp35, 3446–3464.
30.
BresslerSL, MenonV (2010) Large-scale brain networks in cognition: Emerging methods and principles. Trends Cogn Sci14, 277–290.
31.
WelshKA, BreitnerJCS, Magruder-HabibKM (1993) Detection of dementia in the elderly using telephone screening of cognitive status. Cog Behav Neurol6, 103.
32.
CookSE, MarsiskeM, McCoyKJ (2009) The use of the modified telephone interview for cognitive status (TICS-M) in the detection of amnestic mild cognitive impairment. J Geriatr Psychiatry Neurol22, 103–109.
33.
AssociationAP (2013) Diagnostic and statistical manual of mental disorders, American Psychiatric Publishing, Washington, DC.
34.
CharlsonME, PompeiP, AlesKL, MacKenzieCR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis40, 373–383.
35.
LawtonMP, BrodyEM (1969) Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist9, 179–186.
36.
InouyeSK, van DyckCH, AlessiCA, BalkinS, SiegalAP, HorwitzRI (1990) Clarifying confusion: The confusion assessment methoda new method for detection of delirium. Ann Intern Med113, 941–948.
37.
WylieGR, GenovaH, DeLucaJ, ChiaravallotiN, SumowskiJF (2012) Functional magnetic resonance imaging movers and shakers: Does subject-movement cause sampling bias?Hum Brain Mapp35, 1–13.
KunerR, FlorH (2016) Structural plasticity and reorganisation in chronic pain. Nat Rev Neurosci18, 20–30.
43.
Khalili MahaniN, ZoethoutRMW, BeckmannCF, BaerendsE, de KamML, SoeterRP, DahanA, van BuchemMA, van GervenJMA, RomboutsSARB (2012) Effects of morphine and alcohol on functional brain connectivity during “resting state”: A placebo-controlled crossover study in healthy young men. Hum Brain Mapp33, 1003–1018.
44.
DowellD, HaegerichTM, ChouR (2016) CDC guideline for prescribing opioids for chronic pain—United States, 2016. JAMA315, 1624–1645.
45.
HeatonRK, TemkinN, DikmenS, AvitableN, TaylorMJ, MarcotteTD, GrantI (2001) Detecting change: A comparison of three neuropsychological methods, using normal and clinical samples. Arch Clin Neuropsychol16, 75–91.
46.
IversonGL (2001) Interpreting change on the WAIS-III/WMS-III in clinical samples. Arch Clin Neuropsychol16, 183–191.
47.
BuckleyJ, ShangY (2003) Estimating policy and program effects with observational data: The “differences-in-differences” estimator. Prac Assess Res Eval8, 1–10.
48.
SatzP (1993) Brain reserve capacity on symptom onset after brain injury: A formulation and review of evidence for threshold theory. Neuropsychology7, 273–295.
49.
TateDF, NeeleyES, NortonMC, TschanzJT, MillerMJ, WolfsonL, HuletteC, LeslieC, Welsh-BohmerKA, PlassmanB, BiglerED (2011) Intracranial volume and dementia: Some evidence in support of the cerebral reserve hypothesis. Brain Res1385, 151–162.
CrowleyS, TannerJJ, RamonD, SchwabNA, HizelL, PriceCC (2017) Reliability and utility of manual and automated estimates of total intracranial volume. J Int Neuropsychol Soc, doi: 10.1017/S1355617717000868
52.
FischlB, SalatDH, BusaE, AlbertM, DieterichM, HaselgroveC, van der KouweA, KillianyR, KennedyD, KlavenessS, MontilloA, MakrisN, RosenB, DaleAM (2002) Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron33, 341–355.
53.
FischlB (2012) FreeSurfer. Neuroimage62, 774–781.
54.
CoffeyCE, SaxtonJA, RatcliffG, BryanRN, LuckeJF (1999) Relation of education to brain size in normal aging: Implications for the reserve hypothesis. Neurology53, 189–196.
JakAJ, BondiMW, Delano-WoodL, WierengaC, Corey-BloomJ, SalmonDP, DelisDC (2009) Quantification of five neuropsychological approaches to defining mild cognitive impairment. Am J Geriatr Psychiatry17, 368–375.
66.
BucknerRL, CarrollDC (2007) Self-projection and the brain. Trends Cogn Sci11, 49–57.
67.
AmodioDM, FrithCD (2006) Meeting of minds: The medial frontal cortex and social cognition. Nat Rev Neurosci7, 268–277.
68.
SprengRN, MarRA, KimASN (2009) The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: A quantitative meta-analysis. J Cogn Neurosci21, 489–510.
69.
GusnardDA, AkbudakE, ShulmanGL, RaichleME (2001) Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function. Proc Natl Acad Sci U S A98, 4259–4264.
70.
CabezaR, DaselaarSM, DolcosF, PrinceSE, BuddeM, NybergL (2004) Task-independent and task-specific age effects on brain activity during working memory, visual attention and episodic retrieval. Cereb Cortex14, 364–375.
71.
BinderJR, DesaiRH, GravesWW, ConantLL (2009) Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb Cortex19, 2767–2796.
72.
BonnelleV, HamTE, LeechR, KinnunenKM, MehtaMA, GreenwoodRJ, SharpDJ (2012) Salience network integrity predicts default mode network function after traumatic brain injury. Proc Natl Acad Sci U S A109, 4690–4695.
BotvinickMM, CohenJD, CarterCS (2004) Conflict monitoring and anterior cingulate cortex: An update. Trends Cogn Sci8, 539–546.
75.
SingerT, CritchleyHD, PreuschoffK (2009) A common role of insula in feelings, empathy and uncertainty. Trends Cogn Sci13, 334–340.
76.
DosenbachNU, VisscherKM, PalmerED, MiezinFM, WengerKK, KangHC, BurgundED, GrimesAL, SchlaggarBL, PetersenSE (2006) A core system for the implementation of task sets. Neuron50, 799–812.
77.
WenX, LiuY, YaoL, DingM (2013) Top-down regulation of default mode activity in spatial visual attention. J Neurosci33, 6444–6453.
78.
MüllerNG, KnightRT (2006) The functional neuroanatomy of working memory: Contributions of human brain lesion studies. Neuroscience139, 51–58.
79.
BabcockRL, SalthouseTA (1990) Effects of increased processing demands on age differences in working memory. Psychol Aging5, 421–428.
80.
KailR, SalthouseTA (1994) Processing speed as a mental capacity. Acta Psychol86, 199–225.
81.
SalthouseTA, TothJ, DanielsK, ParksC, PakR, WolbretteM, HockingKJ (2000) Effects of aging on efficiency of task switching in a variant of the trail making test. Neuropsychology14, 102–111.
82.
RamirezJ, McNeelyAA, ScottCJ, StussDT, BlackSE (2014) Subcortical hyperintensity volumetrics in Alzheimer’s disease and normal elderly in the Sunnybrook Dementia Study: Correlations with atrophy, executive function, mental processing speed, and verbal memory. Alzheimers Res Ther6, 49.
83.
MadsenSK, GutmanBA, JoshiSH, TogaAW, JackCRJr, WeinerMW, ThompsonPM (2013) Mapping dynamic changes in ventricular volume onto baseline cortical surfaces in normal aging, mci, and Alzheimer’s disease. Lect Notes Comput Sci8159, 84–94.
84.
PerneczkyR, WagenpfeilS, LunettaKL, CupplesLA, GreenRC, DeCarliC, FarrerLA, KurzA, MIRAGE Study Group (2010) Head circumference, atrophy, and cognition: Implications for brain reserve in Alzheimer disease. Neurology75, 137–142.
85.
GreiciusMD, SupekarK, MenonV, DoughertyRF (2008) Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex19, 72–78.
86.
WangK, LiangM, WangL, TianL, ZhangX, LiK, JiangT (2007) Altered functional connectivity in early Alzheimer’s disease: A resting-state fMRI study. Hum Brain Mapp28, 967–978.
87.
BinnewijzendMA, SchoonheimMM, Sanz-ArigitaE, WinkAM, van der FlierWM, TolboomN, AdriaanseSM, DamoiseauxJS, ScheltensP, van BerckelBN, BarkhofF (2012) Resting-state fMRI changes in Alzheimer’s disease and mild cognitive impairment. Neurobiol Aging33, 2018–2028.
PatriatR, MolloyEK, MeierTB, KirkGR, NairVA, MeyerandME, PrabhakaranV, BirnRM (2013) The effect of resting condition on resting-state fMRI reliability and consistency: A comparison between resting with eyes open, closed, and fixated. Neuroimage78, 463–473.
93.
MurphyK, FoxMD (2017) Towards a consensus regarding global signal regression for resting state functional connectivity MRI. Neuroimage154, 169–173.
94.
Whitfield-GabrieliS, ThermenosHW, MilanovicS, TsuangMT, FaraoneSV, McCarleyRW, ShentonME, GreenAI, Nieto-CastanonA, LaVioletteP, WojcikJ, GabrieliJDE, SeidmanLJ (2009) Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci U S A106, 1279–1284.
95.
SupekarK, MenonV, RubinD, MusenM, GreiciusMD (2008) Network analysis of intrinsic functional brain connectivity in Alzheimer’s disease. PLoS Comput Biol4, e1000100.
96.
SorgC, RiedlV, MühlauM, CalhounVD, EicheleT, LäerL, DrzezgaA, FörstlH, KurzA, ZimmerC, WohlschlägerAM (2007) Selective changes of resting-state networks in individuals at risk for Alzheimer’s disease. Proc Natl Acad Sci U S A104, 18760–18765.
FoxMD, GreiciusMD (2010) Clinical applications of resting state functional connectivity. Front Sys Neurosci4, 1–13.
99.
VutskitsL, XieZ (2016) Lasting impact of general anaesthesia on the brain: Mechanisms and relevance. Nat Rev Neurosci17, 705–717.
100.
BergerM, PonnusamyV, GreeneN, CooterM, NadlerJW, FriedmanA, McDonaghDL, LaskowitzDT, NewmanMF, ShawLM, WarnerDS, MathewJP, JamesML, MAD-PIA Investigators (2017) The effect of propofol vs. Isoflurane anesthesia on postoperative changes in cerebrospinal fluid cytokine levels: Results from a randomized trial. Front Immunol8, 1528.
