Counting plaques and tangles in Alzheimer's disease: Concordance of technicians and pathologists

transcript

JOURNALOFTNE

NEUROLOGICALSCIENCES

Journal of the Neurological Sciences 145(1997) 141-146

Countingplaques and tangles in Alzheimer’sdisease: Concordanceoftechniciansand pathologists

Gerald van Belle a’b’*,Kathleen Gibson a, David Nochlin “C,Mark Sumi “C,Eric B. Larson daAlzheimer Disease Research Cen(er, University of Washington,Seattle, WA, USA

bDepartments of EnvironmentalHealth and Biostatis(ics, University of Washington,Seattle, WA, USAc Division of Neurology, Universip of Washington,Seattle, WA, USA

~ University of WashingtonMedical Cen/er, Seattle, WA, USA

Received 24 November 1995;revised 2 July 1996; accepted 10 July 1996

Abstract

Ourprimary aim is to provide a descriptive approach to the analysis of counts of plaques and tanglesby differentreaders.Wewantedto findoutwhethersubjectswithminimaltrainingcancountplaquesandtanglesin histologicalspecimensof patientswithAlzheimer’sdiseaseandcontrols.Twoexperiencedneuropathologiststrainedthreestudenthelpersto recognizeplaquesandtanglesinslidesobtainedfromautopsymaterial.Aftertraining,thestudentsandpathologistsexaminedcodedslidesfrompatientswithAlzheimer’sdiseaseandcontrols.Someof theslideswererepeatedto providean estimateof reliability.Eachreaderreadfourfieldswhichwereaveragedtoobtainestimatesofplaqueandtanglecounts.Ratersarecomparedonfouraspectsofconcordance:kxation,scale,precisionandaccuracy.Precisionandaccuracyarecombinedto providean estimateof concordance.Weconcludethatsubjectswithminimaltrainingcanbetaughttocountplaquesandtangles.Concordancewiththeneuropathologistswassomewhatgreaterfortangles.Thispaperalsoprovidesamethodologyforcomparingraters.0 1997 Elsevier Science B.V. All rights reserved.

Keywords: Alzheimer’s disease; Neuropathology; Plaque; Tangle; Accuracy; Precision; Concordance

1. Introduction

The neuropathologicaldiagnosisof Alzheimer’sdiseaseis time-consumingand difficult — even for experiencedneuropathologists.Workin the late 1960’sandearly 1970’sfound that the presenceof senile neuritic plaques in theneocortex and hippocampusjustified a neuropathologicaldiagnosisof Alzheimer’sdisease(Tomlinsonet al., 1968;Tomlinsonet al., 1970).Thesestudiesalsofoundthat largenumbers of neurofibrillarytangles were often present inthe neocortex and the hippocampus of brains fromAlzheimer’sdisease victims. In some cases, however, adementedindividual’sbrain showedno evidenceof tanglesbut numerousplaques.Later studies showed that plaquesand tanglescouldbe foundin the brainsof elderlyindivid-uals with preservedmental status.Thus, the quantityand

* Corresponding author. Department of Environmental Health, 357234,University of Washington, Seattle, WA, 98195-7234, USA. Tel: + 1(206) 543-6991. Fax: + 1 (206) 543-9616. E-mail: vrmbelle@u.washing-ton.edu.

distributionof plaques and tangles, rather than their merepresence, are important in distinguishing Alzheimer’sbrains from the brains of normal aging individuals(Tomlinson,1982; Ulrich, 1982;Mann, 1985;Crystal etal., 1988;Hansenet al., 1988;Katzmanet al., 1988).Thehypothesisof a continuumbetween quantityof lesions inbrains exhibitingAlzheimer’sdisease and those showing .normal changes associated with aging necessitates theestablishmentof quantitativecriteria for the neuropatho-logical diagnosis of Alzheimer’sdisease. The NINCDS,NIA and AARP joint conferenceof 1985 (Khachaturian,1985)stressedthe need for standardizedclinicaland neu-ropathologicaldiagnoses for Alzheimer’s disease. Sincethat time, there have been a numberof studiescorrelatingclinicaldiagnosisof Alzheimer’sdiseasewith neuropatho-Iogicaldiagnoses(Martin et al., 1987;Molsaet al., 1985;Tiemey et al., 1988),but few studiesof the reliabilityandvalidityof the neuropathologicaldiagnosesof Alzheimer’sdisease.Three groups,one in the United States (Khacha-turian, 1988),one in Great Britain (Blessed et al., 1968;Tomlinsonet al., 1968, 1970),and one in Canada(Ball etal., 1985,1988)have proposeddifferentsetsof criteriafor

142 G. van Belle et aL/Journal of the Neurological Sciences 145 (1997) 141-146

the neuropathologicaldiagnoses of Alzheimer’sdisease.Recentwork by the Consortiumto Establisha RegistryofAlzheimer’sDisease (CERAD) has begun to standardizethe neuropathologicaldiagnosis(Mirraet al., 1991).

The present work investigatesthe degree of variabilityassociated with the counting of plaques and tangles bybrieflytrainedstudentsand experiencedneuropathologists.If quantitativeplaque and tangle counts are to be used inthe diagnosis of Alzheimer’sdisease, then these countsmustbe repeatablefromobserverto observer(i.e. reliable).If the variabilityin countsbetweenobserversis too large,then diagnosticcriteria based on the counts will be oflimiteduse. If the counts are found to be reliable,then itmay be more cost-effectiveto have trained techniciansgatherthis data while the neuropathologistmakesthe finaldiagnosis.

2. Materials and methods

Ten sequential cases with a primary clinical and aneuropathologicaldiagnosisof Alzheimer’sdisease werechosen from the Alzheimer’sDisease Research Center’s(ADRC)brain autopsyregistry.Age at death rangedfrom67 years to 88 years, with a mean of 75.7 years and astandarddeviationof 5.9 years.

Ten age-matchedcontrolswereexaminedfor this study.Nine controls were selected from the ADRC registry ofpatientswith brain autopsy,representingall subjectsin theregistry with no neuropathologicalevidence of SDAT.Four of these did have a clinicaldiagnosisof Alzheimer’sdisease,however.One additionalcontrolwas drawn fromfiles at the Universityof Washington’sDivisionof Neu-ropathology.This control,aged 65 years at death,had noclinicalhistoryof Alzheimer’sdisease.

Controlage at death ranged from 63 years to 93 yearswith a mean of 77.3 years and a standarddeviationof 10.8years.Table 1 showsthe primaryclinicaland neuropatho-logicaldiagnosesfor controlsused in the study.

For each case and control,sectionsfrom the hippocam-pus, temporal,parietal, and frontal lobes were viewedby

Table 1Primarv and neurorrathological diagnoses for cases

two neuropathologistsand three technicians. The threetechnicianswere a first year medical school student, agraduatestudentin biostatisticswith previoushistologicalexperience,and a pre-medicalschool student.The techni-cianswerebrieflytrained(severalhours)by a neuropathol-ogist. The training consisted of looking at brain tissue(both Alzheimer’s cases and normal brains) with adouble-headedmicroscopeand at photographsof tissue.The neuropathologisttrained the technicians to identifyplaques and tangles in the tissue samples viewed. Thetrainingendedwhen the neuropathologistwas satisfiedthatthe technicians would be able to identify plaques andtangles in brain tissue sampleson their own for the pur-posesof this study.

The silverHolmesstainused in this study(Luna, 1968)only enablesvisualizationof the three characteristictypesof ‘neuritic plaques’: primitive, mature or classic andburned out (Wisniewski and Terry, 1973), which byKhachaturian’scriterionand sinceCERAD’Sinceptionarethe ones required to make the diagnosis.(At the time thestudywas donethe Bielschowskystainsilverstainwas notin use in our laboratory).We report here only the resultsfor the hippocampussincethere is strongevidencethat thedeclinein cognitivefunctionsin Alzheimertype dementiais attributable to histopathologicalchanges in the hip-pocarnpusand parahippocampus(Ball et al., 1985;Braakand Braak, 1991).

Minimally,to qualify for the study, a subject had tohave a hippocampusslide and a slide from at least oneother area of the brain. The slides were masked to hidepatientidentityand were arbitrarilydividedintobatchesoffive subjects,with cases and controlsmixed.Four batchesof five slideswere read by both the neuropathologistsandthe three technicians. The technicians also read a fifthbatch containingfive randomlychosen subjectsfrom thefirst four batches. This fifth batch was read two monthsafter the last of the first four batches was viewed. Eachviewerwas asked to scan the entire slide to find the areasof the slidewith the highestdensityof plaquesand tangles(impliedby Khachaturian,1985).The viewer then chosethe four fields on the on the slide which appeared to

Clinical diagnosis n Neuropathological diagnosis n

SDAT 10Primary clinical and neuropathological diagnoses for controlsSDAT 4Adenocarcinoma 1Alcoholic dementia 1Atherosclerosis 1Dementia, cause unknown IDepression ISevere coronary artery disease 1

Alzheimer’s disease

Parkinson’s diseaseAthero and arteriosclerosis, mild diffuseCerebral atrophyInfarcts, multipleInfarct, oldNormal brainNormal with Alzheimer’s changesSenile changes, diffuseWemicke’s disease

2II1II111

G. van Belle et aL/Journal oj’the Neurological Sciences 145 (1997) 141–146 143

contain the highest density of plaques and tangles whenviewedat 25 X . Neurofibrillarytanglesand senileplaqueswere counted in these four fields at 200 X . If the fieldcontained more than 30 plaques or tangles, the viewerscoredthe numberof lesionsin that field as 30.

Raterswere comparedin severalways.To assesswithinrater variability we compared the variabilityof the fourreplicate readings by means of coefficientsof variation.The coefficientof variationof a sampleof observationsisthe standarddeviationdividedby themean.This statisticisuseful in that it adjusts for the fact that with increasinglevels of response the variabilityincreases also. This islikely to be the case with counts of plaques and tangles.(Note that the increasein standarddeviationwith the memimpliesthat analysesof such data shouldbe be based on atransformedmeasuresuch as the logarithm).

Between-ratercomparisonswere made along four di-mensionssuggestedby Lin (1989).This approachformal-izes many aspects of concordanceconsideredby Duyck-aertset al. (1990).If therewereperfectagreementbetweentwo raters their measurementswould fall on a line at 45degrees through the origin. When this is not the case,agreement,or lack of agreementbetweenthe raters can beexamined from the aspect of location shift, scale shift,precisionand accuracy.Locationshift refers to the degreeto which the means differ. A scale shift measures thedifferences in variability. Precision is quantified by ameasureof correlation(Pearson’sproductmomentcorrela-tion in this paper), accuracy is estimatedby the distancethat the observationsare from the 45 degree line throughthe origin. For example, if the observationsfall on a 45degree parallel to the 45 degree line through the originthen one rater reads consistentlyhigher than the other(locationshift), the variabilityis the same (no scale shift),the precisionis high (correlationof 1) but the accuracyisless than perfect (less than 1). Concordanceis defined asthe productof the precisionand the accuracy.In symbols,denote two raters by subscripts1 and 2. Then we define,

Imcationshift= u = [(Y, – XL)]/fi

where xl, Xz, s,, Szare the meansand standarddeviationsfor raters 1 and 2, respectively.

Scaleshift= v =s ,/s2Precision= rwhich is the Pearsonproduct–momentcorrelationbetweenthe two raters, and

Accuracy= A = [(v+ l/v+ u2)/2] -‘

Concordance= rA.The location shift is a standardizedestimate of the

differencebetween the two raters. The quantity m isthe geometricmean of the two standarddeviations.If thereis no locationdifferencebetweenthe two raters the quan-tity, u, is centeredaroundzero.The scale shift, sl/sz, is aratio; if there is no scale shift this quantity is centered

around1. The precisionis the usualcorrelationcoefficient;if the paireddata fall on a straightline the correlationis 1.The accuracyis madeup of a mixtureof the meansand thestandard deviations.Note that if there is no location orscale shift the accuracy is 1 — the upper limit for thisstatistic.The concordancebeing the product of the accu-racy and the precisionis also boundedby 1.

In order to simplify notation we have removed sub-scripts indicatingraters from the estimates of precision,accuracyandconcordance.However,the contextwillmakeit clear which raters are being referred to.

The most importantarea in the brain for the diagnosisof Alzheimer’sis the hippocampusand the majority ofresults will be presentedfor that region.Resultsfor otherregionswere similar.

3. Results

3.1. Description of cases and controls

Table 1 contains the clinical and neuropathologicaldiagnosesfor cases and age-matchedcontrols.All of thecases used had a primary clinical diagnosis of seniledementiaof Alzheimer’stype (SDAT) and a neuropatho-logicaldiagnosisof Alzheimer’sdisease.Four of the con-trols had a primary clinical diagnosisof SDAT and onehad a clinicaldiagnosisof ‘dementia,causeunknown’.Onautopsy,however,none of these five were diagnosedwithAlzheimer’sdisease.Two controlson autopsywere foundto have ‘Alzheimer’schanges’ and ‘senile changes’,butthese changes were apparently not marked enough towarrant a neuropathologicaldiagnosisof Alzheimer’sdis-ease.

3.2. Within-rater variability

As indicated,each of the five raters read a slide fourtimesby scanningthe slidefor the areasof highestdensity.A coefficientof variationcould then be calculatedfor eachreader for each slide. For plaques in the hippocampususing the Holmesstain the coefficientsof variationrangedfrom 0.09 to 2.0 with a mean of 0.51 or 51%. The twoneuropathologistsdifferedsubstantiallyin the variabilityoftheir readings.For tanglesthe averageof the coefficientsof variationfor all the raters was 0.39 or 3970.There weresubstantialdifferences among the raters. Similar resultswere obtainedin other areas of the brain.

Two problemsoccur in assessingthe variability.First,in the absenceof any plaques,or tangles,the mean and thestandarddeviationwill be zero. For this reasonwe did notcalculatethe coefficientsof variationfor replicatereadingsof control slides. Second,values of 30 were coded 30 toreducethe countingtime. This occurredoccasionallywhencounting tangles and will tend to make the estimatedcoefficientof variationtoo small.

Table 2Characteristics of ratings of three technicians and two neuropathologists

Tech. Path. Location Scale Preeision Accuracy ConcordanceShift(u) Shift(v) (r) (Cb) (Cone) (Cone)

1A 0.046 0.815 0.757 0.978 0.741B –0.070 0.749 0.805 0.957 0.771

2A 0.228 1.106 0.878 0.970 0.852B 0.120 1.017 0.912 0.993 0.905

3A 0.571 1.587 0.858 0.786 0.675B 0.465 1.458 0.776 0.847 0.657

AB –0.103 0.919 0.895 0.991 0.887

Analysis of plaque counts in the hippoearnpus for cases and controls.Tech 1 = Technician #1.Tech 2 = Technician #2.Tech 3 = Technician #3.Path A = Pathologist A.Path B = Pathologist B.

With averages based on four replicate readings wewould expect the coefficientof variationto decreaseby afactor of two (standarderror of the mean of four observa-tion), suggesting25~o and 20Y0values for plaques andtangles,respectively.

3.3. Analysis of components of concordance

The estimatednumberof plaquesin the hippocampusofcases (usingthe Holmesstain)variedconsiderablyrangingfrom zero to more than twenty. An analysisof variance(notshown) indicated that there were significantdiffer-ences among techniciansin the estimationof the numberof plaques. Most of the variability was attributable to

.TECE3

Fig. 1. ScatterPlot of counts of plaques by technicians and neuropatholo-gists. Cases and controls; hippocampus using the Holmes stain. Lines areleast-square regression lines. Scale from O to 22. (Adapted from Fisherand van Belle, 1993, with permission.)

Table 3Characteristics of ratings of three technicians and two neuropathologists

Tech. Path. Location Scale Precision Accuracy ConcordanceShift(u) Shift (u) (r) (Cb) (Cone)

1A –0.130 0.948 0.936 0.990 0.927B 0.143 1.070 0.978 0.988 0.966

2A –0.117 0.903 0.940 0.988 0.929B 0.165 1.019 0.930 0.986 0.917

3A –0.463 0.726 0.690 0.863 0.595B –0.170 0.819 0.732 0.967 0.708

AB 0.274 1.129 0.938 0.957 0.898

Analysis of tangle counts in the hippoeampus for cases and controls.

Technician3 who tended to read consistentlyhigher thanthe otherobservers.DeletingTechnician3 from the analy-ses makesthe comparisonsof techniciansand neuropathol-ogistsin the analysisof variancenon-significant.The datawere systematicallyanalyzedin terms of the five charac-teristicsof rater agreement.Table 2 lists the statistics.Theconcordancebetween the two neuropathologistsis esti-mated to be 0.887. Technician2 comparedfavorablywiththis figure with concordancesof 0.852 and 0.905 withneurpathologistsA and B, respectively.Technician 1 dis-played less concordanceand Technician 3 was substan-tially lower with values of 0.675 and 0.657, respectively.Examination of the table indicates that the technicianstendedto see more plaques(locationshift) and Technician2 was more variable than the neuropathologistsin thenumberof plaquesestimated.

Fig. 1 illustratesthese aspects for plaques in the hip-pocampusfor casesand controls.The concordanceis equalto one if, and only if, values for two observersare identi-

rTEC81

. . ... . . .

. . .,

2EI..PAT5..

Fig. 2. ScatterPlot of counts of tangles by technicians and neuropatholo-gists. Cases and controls; hippocampus using the Holmes stain. Lines areleast squares regression lines. Scale from O to 30.

G. van Belle et al. /Journal of the Neurological Sciences 145 (1997) 141–146 145

Table 4Correlations among technicians for replicate readings of five slides threemonths apart

Technician Plaques Tangles

Tech 1 0.880 0.985Tech 2 0.812 0.850Tech 3 0.247 0.734

cal, that is, if they fall on a line at 45 degrees to theX-axis.The correlationwouldbe one as long as the paireddatafell on a straightline.The figurepresentsscattergramscomparingobserverstwo at a time. The graph of data forPathologistsA and B providesa standardfor comparingthe technicianswith the pathologists.The regressionlinesare the least squarelines.The greaterthe deviationfrom a45 degree line the smallerthe accuracy.From Fig. 1 andTable 2, it is evidentthat the accuracyfor Technicians1and 2 is acceptable.

Table 3 and Fig. 2 contain the analogousresults fortangles. The concordancefor tangles for the two neu-ropathologistsis comparable to that for plaques. Also,Technicians1 and 2 do very well in termsof concordancewith the neuropathologists.Technician3’s results are sig-nificantlyworse, indicatedby lower precisionbut compa-rable accuracy.This is also illustratedin Fig. 2 with thecorrespondingregression lines reasonably close to a 45degreeline. The variabilityin countsis comparableamongthe raters.

Similar relationshipswere obtained in the analysis ofcountsof plaquesand tanglesin the temporallobe.

3.4. Reading slides after an interval of two months

Five sets of slides(two cases and three controls)wererandomlyselectedand submittedto the techniciansfor asecond reading approximatelytwo months after complet-ing the initial reading. Table 4 lists the correlationsbe-tween the first and second readings for plaques and tan-gles. Correlations for Technician 1 were highest withvaluesof 0.880 and 0.985for plaquesand tangles,respec-tively. Technician 2’s correlationswere slightly lower.Technician3 was substantiallylower. Since these correla-tions are based on only five samples the differencesaresuggestive— and consistentwith earlier patterns — butcannotbe comparedfor statisticallysignificantdifferences.

4. Discussion

These analysesindicate,in a descriptivefashion,that itis possibleto traintechniciansto countplaquesand tangleswith concordancecomparable to that of highly trainedneuropathologists.We have also provided a method forgrading the effectivenessof technician raters. This ap-proachindicatesthat not all techniciansare equallyskilled

at countingplaquesand tangles— at least with the levelof trainingas provided.Using this approachit will also bepossibleto indicatewhich aspect of countingneeds to beimproved.

The above analyseshave pooled results for cases andcontrols.Analysesfor cases and controls separatelygivesomewhatlower but comparableresults. Pooling the datafrom cases and controlsis more realisticsince, in practice,cases and controlsdo not come labelledas such.

Currentneuropathologicalguidelinescontain an unfor-tunate element of subjectivity by requiring the neu-ropathologistto ‘select’ the area on the slide with thedensest concentrationof plaques and tangles. This intro-ducesan elementof arbitrarinesswhichmakescomparisonof raters more difficultwith potentialbias when differentareas are selected. There are well-defined stereologicalapproachesto unbiasedcharacterizationof the distributionof plaquesand tangles in histologicalsamples.However,these methods will be more labor intensiveand will re-quire new definitionsof the histopathologicaldiagnosisofAlzheimer’sdisease.

In this paper the neuropathologistshave been consid-ered the ‘gold standard.’ It other situations it not bepossibleto use this approachand the dimensionsof agree-ment may be required to be more symmetrical.In thiscurrent schemethe scale shift is asymmetrical;for exam-ple, givenstandarddeviationsof 1 and 0.25 the scaleshift,u = sl/s2, is either 0.25 or 4. This is not satisfactoryforthe situation where there is no gold standard. A moreappropriatemeasureof scale shift would be (u + l/tJ)/2.Its value for the above example is 2.125. It is equal to 1only when the two standard deviations are equal. Thismeasureis also an integralpart of the definitionof accu-racy.

5. Conclusion

We concludethat it is possible to train relativelyun-skilledworkersin the countingof plaquesand tangles.Theconcordance is, initially, greater for tangles than forplaques.Trainingof workersshouldtake this into account.It is alsopossibleto gradethe effectivenessof workersin astandardizedfashion.The grading schemeidentifiesareaswhere improvementis needed and also indicates whenconcordancewith neuropathologistshas been reached.

Agreementamong neuropathologistsmay be improvedif a more precise approach to counting is applied usingstandardizedstereologicalprinciples.

Acknowledgements

We acknowledgethe assistanceof Mr. Duane Beekly,Mr. Steve Edwards, Mr. Robert Fletcher and Mr. JimHughesin data preparation,consultingadviceand reading

of slides (SE and RF). We also acknowledgesubstantialsupport from the following grants: Alzheimer DiseaseResearch Center NIA AG 0513 (all authors);AlzheimerDisease Patient Registry NIA AG 06781 (GvB, DN andEBL); Consortiumto Establisha Registryof Alzheimer’sDisease,NIA AG 06790(GvB).

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Counting plaques and tangles in Alzheimer's disease: Concordance of technicians and pathologists

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