J Clin Pathol 1997;50:365-370

Origins of.. .

Image analysis in clinical pathology

G A Meijer, J AM Belien, P J van Diest, J P A Baak

The term "image analysis" is reserved for aspecial discipline in pathology that aims toobtain diagnostically important information inan objective and reproducible manner, bymeasuring and counting. The origins of meas-uring microscopical images are almost as old asthe microscope itself. Leeuwenhoek (fig 1) inthe 17th century had developed a system tomeasure microscopic objects. As a reference heused sand grains of different sizes, and hairsfrom his head, beard or wig.' 2 Using thismethod, in 1674 he measured human erythro-cytes as 25 000 times smaller than a small sandgrain, corresponding to 8.5 gm.3 Given themeans at his disposal, this is amazingly precise.

This review intends to give an overview ofthe developments that have led to image analy-sis as it is currently applied in routine diagnos-tic cytopathology and histopathology as well asin research. For the purpose of clarity wediscriminate between three different areas ofimage analysis; however, they are not mutuallyexclusive. These areas are measuring morpho-logical characteristics of tissues, cells, nuclei oreven nucleoli; counting of cell or tissue compo-nents; and cytometry and pattern recognition,which aims to measure cytochemical, histo-chemical, and molecular cell or tissue features

Department ofPathology, AcademischZiekenhuis VrijeUniversiteit,Amsterdam, TheNetherlands

Correspondence to:Dr G A Meijer, Departmentof Pathology, VU Hospital,PO Box 7057, 1007 MBAmsterdam, TheNetherlands. e-mail:ga.meijer@azvu.nl

Accepted for publication25 February 1997

Figure 1 Antoni van Leuwenhoek (1632-1723) in the1 7th century had developed a system for measuringmicroscopic objects. (Courtesy the Antoni van LeeuwenhoekHospital, Amsterdam.)

such as the DNA content of nuclei, and toclassify cells according to the distributionpattern of these features in cells or nuclei.

MorphometryMorphometry is the quantitative description ofgeometric features of structures of anydimension.4 This includes planimetry, whichrefers to the measurement of geometric fea-tures of structures in two dimensions. Stereol-ogy denotes all techniques used to obtainquantitative information about geometric fea-tures of structures with a test system of lowerdimension than the structure itself-for exam-ple, point or line grids.Measuring requires a reference or a probe. In

1777, Georges Louis Leclerc, Comte deBuffon, demonstrated that the chance that aneedle of given length (a probe) dropped atrandom on a series of equidistal parallel lineswould intersect one of these lines, depended onthe distance between the lines.5 The concept ofmeasuring distances by randomly dropping aprobe was the cradle of stereology. In general,stereological techniques can be used to esti-mate fractions of different tissue components,inner and outer surface density, shape and vol-ume. Delesse, a French geologist, in 1847measured areas of different compartments inthe microscopical images of random cross sec-tions of rock, and demonstrated that the areasoccupied by each compartment were exactlyproportional to the volume fraction of eachcompartment in the rock.6 The first assess-ments of volume fraction were performed bycutting the different areas from a drawing onpaper and by determining the total weight ofpaper occupied by each compartment. In1898, Rosiwal showed that the same infor-mation could be obtained by taking the ratio ofthe total length of test lines overlying eachcompartment.7 A further improvement in theestimation of volume fraction was initiated bythe Russian petrographer Glagolev, and furtherdeveloped by the American physiologistChalkey, who was one of the first to apply themethod to histological images.8 9 They showedthat volume fractions of different compart-ments could be assessed from the ratio of thesum of points falling on each of these compart-ments. This sequence of dimension reductionsis a key feature of stereology (fig 2). Anauthoritative discussion of the application ofthis, and more advanced stereological methodsin histology, was presented by Weibel." Among

365

on 25 June 2018 by guest. Protected by copyright.

http://jcp.bmj.com

/J C

lin Pathol: first published as 10.1136/jcp.50.5.365 on 1 M

ay 1997. Dow

nloaded from

Meijer, Belien, van Diest, Baak

0 0

u~ ~ ~ ~ ~ v= Pp

Figure 2 Estimation of volume fraction by determining area fractions (V,,=A), linelength fraction (V,=Ld, and point countingfractions (V,=P,). The proportion ofpoinifalling on the hedged square (4 of 16) is proportional to the area occupied by the hedge4square (that is 25% of the large square). (After Bouw, 197559.)

I.

.!z

Arwe h7 quaadrao mikr

Figure 3 Results of the study by Haumeder in 1933 of the size of nuclei and nucleoli imalignant and non-malignant breast tissue.

AlF

s:M;,;~̂~~~~~~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~~~~~~.

Figure 4 In the early 1980s, graphic tablets connected to a computer allowedfor easymeasuring of the area of tissue components, eitherfrom microphotographs or by projectiipinpoint lightfrom the cursor of the graphic tablet through a drawing tube into themicroscopical image.

the more recent advances in stereology is theassessment of the volume-weighted mean

volume of particles of arbitrary shape such as

nuclei by measuring the length of randomintercepts. l

Planimetry, or the measurement of geomet-ric features of structures in the two-dimensional microscopical image is a more

direct approach. The French microscopistDonne, who was among the first to studyhuman cells microscopically, introduced a2.5 ,um micrometer to measure microscopicobjects. He also was the first to use micro-photographs, applying the Daguerreotypetechnique.'2 During many decades to follow,the two approaches to measure microscopical

'tS images were either to use a measuring ocular ord an ocular grid and measure through the micro-

scope, or to take microphotographs or makedrawings using a camera lucida, and then per-form measurements on the prints or drawings.Using these methods, Jacobj in 1925 came to

the conclusion that the size of cells doublesbefore mitosis. 3 The German pathologistsHaumeder, Schairer, and Ehrich, based on

their measurements, were the first to point at° the increased size of nuclei and nucleoli in

tumours compared with normal tissue(fig 3).1416From the 1 970s on, computers became more

e generally available. Graphic tablets connectedto a computer allowed for easy measurement of

Vthe area of cellular or tissue components, either

oN from microphotographs or by projecting a pin-

point light from the cursor of the graphic tabletthrough a drawing tube into the microscopicalimage, allowing tracing of-for example, nuclei

3s0 (fig 4). From these tracings, not only couldnuclear areas easily be computed but also

20 information could be obtained about the shapeof nuclei. When video cameras became widelyavailable in the 1980s, these systems were fur-ther improved. With modern morphometry

o equipment, the microscopical image is re-

corded by a video camera and displayed on a

in computer screen. Measurements can then beperformed by tracing the outlines of-forexample, nuclei on the screen and the precisionof each measurement can be appreciated.The palette of measurements was continu-

ously extended from simple measurements on

objects to more contextual analysis. Forinstance, by measuring the distance from thecentre of gravity of nuclei to the basalmembrane and the epithelial surface, stratifica-tion of nuclei in-for example, dysplasticepithelium, could be quantified. In addition,the angle of the longest axis of nuclei to thebasal membrane could be measured whichyields a measure for loss of polarity. Suchmeasurements help to objectify and quantify"dysplasia".Moreover, the increased power of computers

allowed for more complicated evaluations ofcell and tissue characteristics. Syntactic struc-ture analysis, for instance, is a technique thatallows the analysis and measurement of therelations of tissue objects to each other-for

g example, the minimum spanning tree andVoronoi's tessellation (fig 5).

O>risXnstMs MukI&'us V~re,Yu/n3 in %/60 _ 7A'chmzj5t f,dchel,l7d dii'oKerne

4v347

30 i*hAA'.§ fr*rorzkeffloolm

w _ 7 lSercMmu/7 n ° h -10~~~~~~~ v4 f 49m VL m

Ni~Arle4ofIlhemasel/keoeKt 2 Nzi:htmo/jne AlirchenrflMOSAItKuheolenbkrunk *<.el

366

on 25 June 2018 by guest. Protected by copyright.

http://jcp.bmj.com

/J C

lin Pathol: first published as 10.1136/jcp.50.5.365 on 1 M

ay 1997. Dow

nloaded from

Origins of . . Image analysis in clinical pathology

3A, B, C, E, F: 3 neighboursD: 4 neighboursLength = AB + AD + AC + BD + BE +

CD + CF + DE + DF + EFAverage line length = length/10# Points = 6# Lines = 10Cyclomatic number = 10 - 6 + 1 = 5# Triangles = 5Mean cytoplasmic area =(region A + region B + region C +region D + region E + region F)/6

3

A, B, E: 1 neighbourD: 2 neighboursC: 3 neighboursMST length = AC + CB + CD + DEAverage line length =

(AC + CB + CD + DE)/4Dmin = CDDmax = DE

4 5

Figure 5 Top, Schematic explanation of Voronoi's tessellation. Block 1:field containing sixnuclei with their centroids marked. Block 2: using Delaunay's triangulation, starting withA, a triangle is composed with A, C, and D. The circumcircle of this triangle does notcontain other points than the triangle points, so it is accepted; D and C are neighbours ofA.Block 3: continuing to find neighbours ofA, a triangle is composed with A, B, and E. Thecircumcircle of this triangle however contains point D, so this triangle is not accepted. Block4:following the same process for all possible triangles for all combinations ofpoints, thetriangles drawn have been accepted and the Delaunay graph is complete. Block 5: thecomplementary tessellation of the Delaunay graph is build by drawing a perpendicular(tessellation) line from the middle of the connecting lines that go in both directions until theytouch another tessellation line. At the bottom right, the features drawn from the graph are

shown. Besides features based on Delaunay's graph, the artificial mean cytoplasmic area iscomputed. Bottom, Schematic explanation of the algorithm for building the minimumspanning tree and calculation of spanning tree features. Block J:field containingfive nucleiwith their centroids marked. Block 2: after calculating the distances between all thecentroids, the distance between C and D has been found to be the shortest, so C and D are

connected by a line. Block 3: of the remaining free centroids, B is closest to one of thecentroids already connected to the tree, namely C, so B and C are connected. Block 4: of theremaining free centroids, A is closest to one of the centroids already connected to the tree,namely C, so A and C are connected. Field 5: the last remaining free centroid, E, is closest toD, so E is taken into the tree by connecting E with D. The minimum spanning tree is nowcompletedfor this field, and the features calculatedfrom it are shown at the bottom right.

Different histological patterns produce dif-ferent graphs, and different graphs producedifferent quantitative data. Syntactic structurehas its origin in the graph theory, a geometricaldiscipline. In chemistry it has been applied tostudy the configuration of complexmolecules. "

Counting objectsCounting objects of interest in tissue sections isa widely applied form of image analysis. Mostof the time this concerns counting of prolifera-tion markers in tumours. Greenbough, by1925, found that the number of mitoses was

associated with survival in breast cancer

patients.'8 A similar observation was made byGrinnell for colorectal cancer in 1939.'9 Today,mitotic activity in breast cancer, next to lymphnode status, remains one of the most important

prognostic factors. Moreover, this powerfulmethod in image analysis requires only amicroscope and a haematoxylin and eosinstained slide.20

It became possible to obtain information onproliferation from interphase nuclei with tech-niques that, after incubation, introduced la-belled nucleotide analogues in the DNA ofproliferating cells. Counting the proportion oflabelled cells, the labelling index, yielded a reli-able measure of the proliferation fraction of acell population. At first radioactive labels wereused, like tritium thymidine labelling. Later,non-isotopic labels such as bromodeoxyuridin(BrDU) became available that could be moreeasily visualised with antibodies.2' In the pastdecade, antibodies have been raised againstproliferation associated antigens such as Ki67and proliferating cell nuclear antigen(PCNA).22 23 In particular the possibility ofimmunohistochemical detection of Ki67 informaldehyde fixed, paraffin wax embeddedmaterial was a major improvement. Wheretraditional counting meets with stereology isthe application of point counting methods toscore the proportion of immunohistochemi-cally stained nuclei to obtain a highly reliablelabelling index; however, this procedure isalmost 10 times as fast as the traditionalmethod of counting the number of stainednuclei per 2000 nuclei.24

Cytometry and pattern recognitionCytometry refers to measuring the amount of agiven substance in tissue, cells or nuclei. Theobservation of hyperchromatism in the nucleiof neoplastic cells, reflecting increased DNAcontent, is the subjective counterpart of DNAcytometry in everyday pathology. Cytometrydepends on the ability to detect the substanceof interest by a specific dye and to measure theconcentration of that dye. The relation be-tween the concentration of a dye and the opti-cal density of that dye comes from the work ofLambert in 1760 and Beer in 1854. Thehistory of cytometry actually is the history ofDNA cytometry. In the late 1890s, Kohler andVon Rohr at Carl Zeiss in Jena, Germany,developed an ultraviolet microscope to proveAbbe's theory that the use of a lowerwavelength would increase the resolution of themicroscope. Kohler observed a high absorptionat 280 nm by the chromatin in cells, butbelieved this resulted from the presence ofinorganic substances. It was Caspersson, at theKarolinska hospital in Stockholm, Sweden whoattributed this absorption to DNA, or thymo-nucleic acid, as it was then (fig 6). Heconstructed a system for photographic pho-tometry in 1933.25 Some years later, the photo-graphic detection system was replaced by aphotoelectric spectrophotometric system, fol-lowed by photomultipliers. These were veryprecise and well suited for high resolutionanalysis of intracellular structures, but not veryfast. However, fed by the growing interest incancer research, and the observations byCaspersson, Pollister, Mellors, Leuchten-berger, Richards, Atkin, and several others, thattumour cells and normal cells differed in their

*- F

12

4

B A

FF

5

367

on 25 June 2018 by guest. Protected by copyright.

http://jcp.bmj.com

/J C

lin Pathol: first published as 10.1136/jcp.50.5.365 on 1 M

ay 1997. Dow

nloaded from

Meijer, Belien, van Diest, Baak

Figure 6 Professor T Caspersson who was the first toapply DNA cytometry in the 1930s, at the KarolinskaHospital in Stockholm, Sweden. (Courtesy of theDepartment of Pathology, Karolinska Hospital,Stockholm.)

DNA content, systems were sought that couldeasily measure the total amount of DNA per

cell in a large number of cells.26Meanwhile, DNA cytometry using visible

light emerged. By 1933, Mainland had esti-mated the amount of haematoxylin in cervicalnormal and tumour cells.27 However, haema-toxylin is not a stoichiometric stain for DNA,contrary to the Feulgen reaction discovered byFeulgen and Rossenbeck in 1924.28 This Feul-gen staining proved to be specific for DNA, andthe amount of stain was proportional to theamount of DNA present. Pollister and Ris, in1948, built the first prototype of a simplemicrophotometer using a microscope equippedwith a photomultiplier and a galvanometer tomeasure the output current.29 Also in 1948, Risand Mirsky measured the total amount ofDNA in a nucleus and Swift, in 1950, demon-strated the doubling of DNA prior tomitosis.30 31 In the years to follow, scanningmicroscopes were introduced to cope withinhomogeneities in the staining intensity withinnuclei. Moreover, these developments led tosystems that were able to measure large

i -0

*. :l.1k.i-@

Figure 7 The Taxonomic Intra-cellular Analytic System (TICAS) developed by Wied etal in the 1960s is an example of one of the first computer based image cytometry systems.The system is composed of a microphotospectrometer (A-I) connected to a computer (7-M).(Reprinted with permission ofDr GL Wied.)

numbers of cells. One of the first of suchsystems was the cytoanalyser of Tolles et albased on a scanning microscope.32 This group,in 1961, reported a study on 700 cervical andvaginal smears in which they measured theDNA content of 200 cells each.33 3The introduction of computers has been a

major influence on the evolution of imageanalysis. In addition to enhanced measuringperformance, the use of computers has stimu-lated the development of systems for automaticcell classification based on pattern recognition.In 1961 a system was designed for theautomatic recognition of binucleatedlymphocytes.35 Some years later, systems fol-lowed by Prewitt and Mendelsohn, and Wied etal (fig 7).36 37 At present, systems for automaticclassification of cells have been developed thatare used-for example, for prescreening of Papsmears, and quality control.38 Furthermore,systems have been developed capable ofautomatic recognition of mitoses in tissuesections.39Computer based pattern recognition also

stimulated the analysis of chromatin texture incell nuclei.40 Coarseness of chromatin is a fea-ture widely used in the routine assessment ofnuclear atypia. However, by means of highresolution image analysis, even in apparentlynormal uterine cervix cells next to cervicalneoplasia, chromatin texture changes can bedetected.4" These malignancy associatedchanges, therefore, may be useful in screeningfor cervical neoplasia.DNA cytometry as research tool and in

clinical application was stimulated by thedevelopment of the computer based flowcytometer in the early 1960s by Kamentsky etal.42 Flow cytometers enabled themeasurement of the DNA content in thou-sands of cells, and produced DNA histogramsas we now know them. With time, however,image cytometry systems, thanks to the enor-mous progression of computer technique,could cope with an increasing number of cells.Modern DNA image cytometry systems canmeasure thousands of cells within minutes andproduce histograms like those from DNA flowcytometry systems. At present, due to theongoing fall of prices of computer hardwarewith a concurrent increase in performance, andthe availability of inexpensive high qualityvideo cameras for recording the images, DNAimage cytometry systems have come within thereach of any modern pathology laboratory.DNA cytometry measures the total amount

of DNA per nucleus. For this there are twoprerequisites. First, the complete nucleusneeds to be present in the image. Thiscondition in general is easily met in cytologicalspecimens, but not in standard 4 gm tissuesections. Second, the nucleus must be discrimi-nated from its environment to recognise it asonly one nucleus. This discrimination, orsegmentation, is easy when cells are looselydispersed but difficult when nuclei are overlap-ping, as in thick cytological specimens and tis-sue sections. Against this background it is clearwhy many of the early studies of DNA cytom-etry in tumours focused on cervical

368

.-l:'

--' .,

:l-.i--.,d I..

on 25 June 2018 by guest. Protected by copyright.

http://jcp.bmj.com

/J C

lin Pathol: first published as 10.1136/jcp.50.5.365 on 1 M

ay 1997. Dow

nloaded from

Origins of .. Image analysis in clinical pathology

smears.27 33 4 Later, cytological specimens ofdisaggregated fresh frozen tissue were alsoused,43 and a tremendous step forward wasmade by Hedley et al who developed a methodto disaggregate paraffin wax embedded mater-ial to cell suspensions.44 This discovery dis-closed archival material as a source for DNAcytometry, and greatly increased the opportu-nities to study the clinical value of DNAcytometry in retrospective studies.However, it was felt that the possibility to

measure the DNA content of cells in tissuesections could help to integrate DNA cytomet-ric features with histomorphological infor-mation, so this issue was still tempting.Successful attempts in this area have beenreported for carcinomas in which generallythere is little overlap of nuclei such as renal cellcancer and prostate cancer.4546 In addition,correction formulas have been proposed tocope with incomplete nuclei due tosectioning.47 Recently, the importance of a verystrict measurement protocol has been empha-sised to obtain reliable results by DNA cytom-etry in thin tissue sections.48 Another approachto avoid problems with incomplete cellsbecause of section thickness has been to meas-ure the DNA content in three dimensionalreconstructions of tissue, based on confocallaser scanning microscopy in thick tissuesections with advanced image processing.49While DNA cytometry measures the genetic

alterations in tumours as a change in the totalamount of DNA, recently a new technique-comparative genomic hybridisation (CGH)-has been developed that measures in oneexperiment the genetic changes (gain or loss ofDNA) at the level of individual chromosomes,using digital image analysis.50 51 In this proce-dure DNA isolated from tumour specimens islabelled with a green fluorochrome and mixedwith red labelled DNA obtained from cells witha normal diploid chromosome complement.The mixture is hybridised to normal met-aphase preparations. Hybridised test and con-trol DNA sequences compete in the annealingprocess for their complementary spots on theindividual chromosomes, and are recognisedvia the different fluorochromes. The ratio ofgreen to red fluorescence for each chromo-somal region is a measure of the under or over-representation of genetic material for thatregion in the tumour studied. In this sense,CGH can be regarded as a refinement ofDNAcytometry and, currently, research groups allover world are employing this method to studyits clinical relevance in tumour pathology.52Image cytometry is also used to measure the

amount of immunohistochemically stainedproteins in cells such as oestrogen receptors inbreast cancer.53 At first sight this proceduremay closely resemble DNA image cytometrybut fundamental differences exist. While Feul-gen staining of DNA is stoichiometric, immu-nohistochemical staining of antigens is not; theamount of staining is not proportional to theamount of antigen present and is influenced bymany factors. Therefore, immunoquantitationby image analysis in any case requires calibra-tion of the staining result by using a specimen

with a known amount of antigen, and tissueprocessing is critical.For the many cases in which one wants to

assess the proportion of cells positive for animmunohistochemical staining, rather than theexact distribution of staining intensities overthe cells, a point counting procedure could bemuch more powerful.

This brief overview of the origins of imageanalysis in pathology inevitably cannot becomprehensive as the evolution in this field ofscience has been tremendous. For example,developments in the area of tissue handling andsampling have not been addressed.54- For thewide range of established clinical applicationswe refer to the recent textbooks on thistopic., 58

The help of the photographers from the Antoni van Leeuwen-hoek Hospital, Amsterdam, The Netherlands, and from theDepartment of Pathology, Karolinska Hospital, Stockholm,Sweden in providing figures 1 and 6 is gratefully acknowledged.

1 Schierbeek A. Antoni van Leeuwenhoek, zijn leven en zijnwerken. Vol 1. Lochem: De Tijdstroom, 1950:110.

2 Charnsangavej C. New imaging modalities for follow-up ofcolorectal carcinoma. Cancer 1993;71:4236-40.

3 Leeuwenhoek A. Microscopical observations concerningblood etc. Phil Trans 1674;9:121.

4 Baak JPA, ed. Manual ofquantitative pathology in cancer diag-nosis and prognosis. Heidelberg: Springer-Verlag, 1991.

5 Buffon G. Essai d'arithmetique morale. Suppl a l'HistoireNaturelle (Paris), 1777.

6 Delesse A. Procide mechanique pour determiner la compo-sition des roches. Ann Mines (IV) 1847;13:379.

7 Rosiwal A. Uber geometrische Gesteinsanalysen. Ein einfacherWeg zur ziffermad/igen Feststellung der Quantitatsverhaltnisseder Mineralbestandteile gemengter Gesteine. Wien: Verhand-langen der KK Geologischen Reichsanstalt, 1898;143:5-6.

8 Glagolev AA. On the geometrical methods of quantitativemineralogic analysis of rocks. Transcripts of InstituteEconomic Mineralogy and Metallurgy, Moscow 1933;59: 1.

9 Chalkey HW. Method for quantitative morphological analy-sis of tissues. J Natl Cancer Inst 1943;4:47-53.

10 Weibel ER. Stereological methods. Vol 1: Practical methods forbiological morphometry. London: Academic Press, 1979.

11 Gundersen HJG, Jensen EB. Stereological estimation of thevolume weigthed mean volume of arbitrary particlesobserved on random sections. J Microsc 1985;138:127-42.

12 Donne A. Cours de Microscopie Complementaire des EtudesMidicales: Anatomie Microscopique et Physiologie des Fluidesde l'Economie: Atlas Execute d'Apres Nature au Microscope-Daguerreotype. Paris: Balliere, 1845.

13 Jacobj W Uber das rhyrmische Wachstum der Zellen durchVerdoppelung ihres Volumens. Arch Entwickl 1925;106:124-92.

14 Haumeder E. Vergleichende Kern- und Nukleolenmessun-gen an verscheidenen Organengeweben mit besondererBeruicksichtigung der malignen Tumorzellen. Zeitschrift furKrebsforschung 1933;40: 105-16.

15 Schairer E. Kernmessungen und Chromosomenzahlung anmenschlichen Geschwulsten. Zeitschrift fur Krebsforschung1935;43: 1-38.

16 Ehrich WE. Nuclear sizes in growth disturbances with spe-cial reference to the tumor cell nuclei. Am _7 Med Sci 1936;192:772-90.

17 Diest PJ van, Kayser K, Meijer GA, Baak JPA. Syntacticstructure analysis. Pathologica 1995;87:255-66.

18 Greenbough RB. Varying degrees of malignancy in cancer ofthe breast. Cancer Res 1925;9:452-63.

19 Grinnell RS. The grading and prognosis of carcinoma of thecolon and rectum. Ann Surg 1939;109:500-33.

20 Baak JPA, van Dop H, Kurver PHJ, Hermans J. The value ofmorphometry to classic prognosticators in breast cancer.Cancer 1985;56:374-82.

21 Gratzner HG. Monoclonal antibody to 5-bromo- and5-iododeoxy-uridine: a new reagent for detection of DNAreplication. Science 1982;218:474-5.

22 Howell WM, Black DA. Controlled silver staining ofnucleolus organizer regions with a protective colloidaldeveloper: a one step method. Experientia 1980;36:1014.

23 Gerdes J, Schwab U, Lemke H, Stein H. Production of amouse monoclonal antibody reactive with a human nuclearantigen associated with cell proliferation. Int _7 Cancer1983;31:13-20.

24 Polkowski W, Baak JPA, Lauschot JJB von, Meijer GA,Schuurmans LT. et al. Reproducibility of p53 and Ki67immunoquantitation in Barret's oesophagus. Anal QuantCytol Histol. [In press.]

25 Casperson TO. History of the development of cytophotom-etry from 1935 to the present. Anal Quant Cytol Histol1987;9:2-6.

26 Bartels PH. Quantitation in histopathology. Objectives, ori-gins, digital image analysis, and unresolved issues. In:Marchevsky AM, Bartels PH, eds. Image analysis:A primerfor pathologists. New York: Raven Press, 1994.

369

on 25 June 2018 by guest. Protected by copyright.

http://jcp.bmj.com

/J C

lin Pathol: first published as 10.1136/jcp.50.5.365 on 1 M

ay 1997. Dow

nloaded from

Meijer, Belien, van Diest, Baak

27 Mainland D. Colorimetric tests of nuclear staining. StainTechnology 1933;8:69-72.

28 Feulgen R, Rossenbeck H. Mikroskopisch-chemischerNachweis einer Nukleinsaure vom Typus der Thymonuk-leinsaure und die darauf beruhende Elektiv Farbung vonZellkernen in microskopischen Praparaten. Z Physiol Cheni1924;135:203-48.

29 Pollister AW, Ris H. Nucleoprotein determinations in cyto-logical preparations. Quant Biol 1948;12:147-57.

30 Ris H, Mirsky AE. Quantitative cytochemical determinationof desoxyribonucleic acid with the Feulgen nuclealreaction. J Gen Physiol 1949;33:125-46.

31 Swift H. The desoxyribose nucleic acid content of animalnuclei. Physiol Zool 1950;23:169-98.

32 Koss LG. Analytical quantitative cytology. A historical per-spective. Anal Quant Cytol Histol 1982;4:251-6.

33 Tolles WE, Horvath WJ, Bostrom RC. A study of the quan-titative characteristics of the exfoliated cells from thefemale genital tract: I. Measurement methods and results.Cancer 1961;14:437-54.

34 Tolles WE, Horvath WJ, Bostrom RC. A study of the quan-titative characteristics of the exfoliated cells from thefemale genital tract: II. Suitability of quantitative cytologi-cal measurements for automatic prescreening. Cancer1961;14:455-68.

35 Preston K. The Cellscan system: A leukocyte patternanalyzer. Proc Western J7oint Comput Conference 1961:173.

36 Prewitt JMS, Mendelsohn ML. The analysis of cell images.Ann NYAcad Sci 1966;128:1035-53.

37 Wied GL, Bartels PH, Oldfield DG. Taxonomic intracellu-lar analytic system (TICAS) for cell identification. ActaCytol 1968;12:177-210.

38 Mango LJ. Computer-assisted cervical cancer screeningusing neural networks. Cancer Letters 1994;77: 155-62.

39 Kate TK ten, Belien JAM, Smeulders AWM, Baak JPA.Method for counting mitoses by image processing in Feul-gen stained breast cancer sections. Cytometry 1993;14:241-50.

40 Doudkine A, Macaulay C, Poulin N, Palcic B. Nuclear tex-ture measurements in image cytometry. Pathologica 1995;87:286-99.

41 Guillaud M, Doudkine A, Garner D, MacAulay C, Palcic B.Malignancy associated changes in cervical smears: system-atic changes cytometric features with the grade ofdysplasia. Anal Cell Pathol 1995;9: 191-204.

42 Kamentsky LA, Melamed MR, Derman H.Spectrophotometer: new instrument for ultrarapid cellanalysis. Science 1965;150:630-1.

43 Vindelov L. Flow microfluorometric analysis of nuclearDNA in cell suspensions. Virchows Arch B Cell Pathol 1977;24:227-42.

44 Hedley DW, Friedlander ML, Taylor IW, Rugg CA,Musgrove EA. Method for analysis of cellular DNAcontent of paraffin-embedded pathological material usingflow cytometry. _7 Histocheni Cytochem 1983;31: 1333-5.

45 Bennington JL, Mayall BH. DNA cytometry on four-micrometer sections of paraffin embedded human renaladenocarcinomas. Cytonmetry 1983;4:31-9.

46 Greene DR, Taylor SR, Wheeler TM, Seardino PT. DNAploidy by image analysis of individual foci of prostatecancer: a preliminary report. Cancer Res 199 1;51:4084-9.

47 Haroske G, Dimmer V, Hermann WR, Kunze KD, MeyerW Metastasising APUD cell tumours of the humangastrointestinal tract. Light microscopic and karyometricstudies. Pathol Res Pract 1984;78:363-8.

48 Williams RA, Baak JPA, Meijer GA, Charlton IG. Furthertesting of the value of a measurement protocol for DNAploidy studies using image cytometry: Comparison ofresults obtained from cytologic and paraffin section prepa-rations. Anal Quant Cytol Histol 1996;18:345-50.

49 Zhu Q, Tekola P, Baak JPA, Belien JAM. Measurement bvconfocal laser scanning microscopy of the volume ofepidermal nuclei in thick skin sections. Anial Quant CwtolHistol 1994;16:145-52.

50 Kallioniemi A, Kallioniemi OP, Sudar D, Rutovitz D, GravJW, Waldman F, et al. Comparative genomic hybridizationfor molecular cytogenetic analysis of solid tumors. Science1992;258:818-21.

51 Manoir S du, Speicher MR, Joos S, Schrock E, Popp S,Dohner H, et al. Detection of complete and partialchromosome gains and losses by comparative genomic insitu hybridization. Hunm Genet 1993;90:590-610.

52 Hermsen MAJA, Meijer GA, Baak JPA, Joenje H,Walboomers JJM. Comparative genomic hybridization: anew tool in cancer pathology. Hum Pathol 1996;27:342-9.

53 Colley M, Kommoss F, Bibbo M, Dytch HE, Franklin WA,Holt JA, et al. Assessment of hormone receptors in breastcarcinoma by immunohistochemistry and image analysis.II Estrogen receptors. Anal Quant Cytol Histol 1989;11:307-14.

54 Baak JPA, Noteboom E, Koevoets JJM. The influence offixatives and other variations in tissue processing onnuclear morphometrical features. Anal Quianit CNvtol Histol1989;11:219-24.

55 Bergers E, Jannink I, Diest PJ van, Cuesta MA, Meijer S,Mourik JC van, et al. The influence of fixation delay onmitotic activity and flow cytometric cell cycle variables.Hum Pathol 1997;28:95-100.

56 Gundersen HJG, Osterby R. Optimizing sampling efficiencyof stereological studies in biology: or "do more less well!".J7Microsc 1981;121:65-73.

57 Fleege JC, Diest PJ van, Baak JPA. Systematic random sam-pling for selective interactive nuclear morphometry inbreast cancer sections. Refinement and multiobserverevaluation. Anal Quant Cytol Histol 1993;15:281-9.

58 Hamilton PW, Allen DC, eds. Quantitative clinical pathology.Oxford: Blackwell Scientific Publications, 1995.

59 Bouw GM. Growth and growth retardation of the humanplacenta. PhD Thesis, Free University, Amsterdam, TheNetherlands.

370

on 25 June 2018 by guest. Protected by copyright.

http://jcp.bmj.com

/J C

lin Pathol: first published as 10.1136/jcp.50.5.365 on 1 M

ay 1997. Dow

nloaded from