Digital Measurement of Myelofibrosis Associated Platelet Derived Growth Factor Receptor [Beta] (PDGFR [Beta]) Expression in Bone Marrow Biopsies

Jou nal o Compu ing and In o ma ion Technology - CIT 21, 2013, 1, 47–56 doi:10.2498/ci .1002109 47 Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o ββ (PDGFR ββ ) Exp ession in Bone Ma ow Biopsies Szil ia Szeghalmy1, Judi Bedeko ics2,G ´ abo M´ ehes2and A ila Fazekas1 1Depa men o Compu e G aphics and Image P ocessing, Uni e si y o Deb ecen, Hunga y 2Depa men o Pa hology, Uni e si y o Deb ecen, Hunga y In daily ou ine he e iculin sil e s aining is used on bone ma ow biopsy samples as a gold s anda d o he cha ac e iza ion o myelo ib osis, howe e his me hod does no p o ide in o ma ion abou he p e ib o ic s age. Recen ly a speci ic immunohis ochemical me hod was in oduced which may o e come hese weaknesses o e iculin s aining. Ac i a ed ib oblas s esponsible o s omal p oli e a ion a e highligh ed by inc eased PDGFR β exp ession, which can be p esen ed by im- munohis ochemis y in bone ma ow samples. Using his s aining he p e- ib o ic s age can become de ec able and we ha e in o ma ion abou he disease ac i i y. Du ing de elopmen o new s aining me hod i is impo - an o p o e i s eliabili y and usabili y. In his pape we in oduce a digi al image p ocessing me hod o measu e pa anchymal damage in digi alized his ological slides ha can aid co ec in e p e a ion o he s aining. Keywo ds: myelo ib osis, PDGFR, image p ocessing 1. In oduc ion Myelo ib osis (MF)is a linge ing disease which eplaces no mal cells in he bone ma ow o i- b o ic issue con aining a iable deg ees o e i- culin and, in he ad anced phase, collagen i- b es. The se e i y o he disease is usually cha - ac e ized by he deg ee o ibe con en high- ligh ed by he e iculin sil e s aining (G¨ om¨ o i’s s aining)in bone ma ow biopsy samples. Recen ly, di e en g ading sys ems ha e been in oduced o assess bone ma ow ib osis, mos o hem de i ed om he Baue meis e sco - ing sys em [2]. A ew yea s ago, Thiele e al. eached a consensus de ining a g ading sys- em [17]. This scheme consis s o quali a i e and quan i a i e analysis o bone ma ow ib o- sis and dis inguishes ou inc easing ca ego ies, anging om MF0 o MF3. This wide-sp ead g ading sys em allows making mo e accu a e p ognosis [6], desc ibes p ecisely he ibe con- en o he bone ma ow, bu does no p o ide in o ma ion abou ibe p oducing cells which a e called ib oblas s. La ely we iden i ied PDGFR β as a no el bio- ma ke o ac i ed ib oblas s. PDGFR β con- ols s omal p oli e a ions and u ned ou o be selec i e o ib oblas s in he bone ma ow. The amoun o PDGFR β is s ongly dependen on hei numbe and ac i i y and in his con ex i could be applied as a measu e o he ib o ic p o- cess. A new sco ing sys em based on PDGFR β exp ession was also in oduced. This sys em e- sul ed in excellen ag eemen wi h he classical sil e s aining me hod, al hough di e en as- pec s o he same p ocess a e analysed (Table 1, Figu e 1). As a special ea u e, he new me hod also co e s he ea lies , p e ib o ic phase o he disease due o he p esen a ion o all ib ob- las s po en ially pa icipa ing in e iculin ibe syn hesis. The me hod is simple and equi es only a s anda d immunohis ochemical s aining o PDGFR β by one o he comme cially a ail- able an ibodies (an i-PDGFR β clone ab-32570, Abcam was used in his s udy). 48 Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... PDGFR β immunoposi i i y can be assessed in a semi-quan i a i e way du ing isual inspec- ion in he mic oscope. Howe e , a much be - e and ep oducible assay would be equi ed o he compa ison o di e en clinical sam- ples o samples om di e en ime poin s om he same pa ien . In o de o pe o m measu e- men s on PDGFR β ela ed immunoposi i i y in bone ma ow samples, digi al image analysis was used and special algo i hms we e applied o de ec he pa enchyma (use ul egion)and he posi i e componen . G ade Desc ip ion 0No signi ican amoun s o posi i e ib oblas s. 1 Isola ed posi i e ib oblas s and/o hei b anches clea ly ecognizable in he in e cellula space. 2 Many posi i e ib oblas s wi h long p ocesses a e p esen accompanied by in e sec ions o ming a loose ne wo k. 3 Masses o posi i e ib oblas s and p ocesses a e p esen accompanied by equen in e sec ions and bands o ming a dense ne wo k. Table 1. G ading sys em based on PDGFR β exp ession o ac i a ed ib oblas s. Figu e 1. G ading sys em based on PDGFR β exp ession o ac i a ed ib oblas s. 1.1. Rela ed wo ks Al hough manual me hods a e he gold s an- da ds o analysis o immunohis ological s ain- ing, e o s a e being made o apply au oma ic digi al analysis as well. Mos o he solu ions a e semi-au oma ic: manual segmen a ion is pe o med by any image p ocessing ool (Im- ageJ, Pho oShop, Tmaj, e c.), and only he mea- su emen is au oma ic [5]. The e a e some ully au oma ic cha ac e isa- ion algo i hms o simila s aining me hod o ou s, o example he au ho s in [8]analyse lung b eas cance in mice. Bu he bone ma ow e- qui es speci ic analysing me hod because: •No only he issue o be examined can be ound in he sample. •The disease eplaces no mal cells o ib o ic issue. •Fib o ic issue can de o m no mal cells. Ou samples can include some kinds o haema- opoie ic bone ma ow cells, a issue, bone a- becules, blood clo s (Figu e 2), muscula issue, connec i e issue (Figu e 9)and noises. Figu e 2. The e a e bone ma ow nuclei (a), posi i e ib oblas (b), plasma o bone ma ow cells (c) a (d) and de o med nuclei (e)inside he black cu e. ( )is a pa o bones, (g)is a blood clo (ou side he cu e)and (h)shows a s aining ailu e pa . The classi ica ion o di e en , some imes o e - lapping and c inkled issues is no an easy ask. In [12] he au ho s no e, he adi ional au- oma ic classi ica ion algo i hms, such as K- means and Fuzzy-C-means do no gi e co ec esul . They inally de eloped a semi-au oma ic analyse using Gene alised Reg ession Neu al Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... 49 Ne wo ks. The use can se he applied ea u es (Fou ie ans o m o egion o common GLCM ex u e ea u es)and some o he pa ame e s. They did no men ion any s aining p ocedu e, and he e is no in o ma ion whe he pa holog- ical cases we e in es iga ed o no . Anyway, ibe s do no appea as a sepa a e class. In [7]au ho s p oposed a me hod o segmen bone abeculae om bone ma ow biopsy dye wi h haema ology and eosyn. Fi s , hey use Wa e shed T ans o m and compu e ea u es o each segmen . A e ha , hey classi y he ea- u es o ou g oups by K-means. Using bone egions as ma ke s, hey pe o m he Wa e shed T ans o m again o ind he exac bo de s o he bone abeculae. I is e y impo an o us ha he p ocedu e can dis inguish be ween he posi i e ibe s and no mal cells, hus we de eloped an own me hod aking ad an age o he p ope ies o immuno- his ochemical s aining. 1.2. Ma e ials and me hods Fo esea ch 41 bone ma ow biopsy samples we e a ailable. Each sample was p ocessed by immunohis ochemical s aining. In immunehis- ochemis y e e y cell nucleus is displayed by haema oxylin coun e -s aining which gi es he nuclei a blue colo . Tha speci ic p o ein which is in he ocus o in e es is bounded by a spe- ci ic an ibody, in his case his was a p ima y an ibody agains PDGFR β subuni . Then he p ima y an ibody is bounded by a seconda y an ibody which is linked o an enzyme. I we add a subs a e o he sample, a chemical in- e ac ion will p oceed be ween he enzyme and i s subs a e which is accompanied by a b own p ecipi a ion o ma ion. In o he wo ds, unde he mic oscope he b own colo indica es he localiza ion o he analysed p o ein wi hin he issue. The sco e o PDGFR β was assigned o s ained samples manually. The samples we e ob ained a 40x magni ica- ion using Ligh mic oscopy (Leica DM2500 mic oscope, DFC 420 came a and Leica Appli- ca ion Sui e V3 so wa e, We zla , Ge many). The Mi ax SlideAC SDK was used o ead he slides. The size o he whole slides was 256216 ×78336 pixels, ha is why we pe o med he analysis wi h 1 : 4 magni ica ion, ile by ile. Each ile size was 512 ×512 pixels. 2. Digi al Analysis In his sec ion we in oduce ou own me hod. Figu e 3 p esen s he main s eps. In his pape , he wo ds nucleus and cy oplasm will deno e he nucleus and cy oplasm which belong o he haema opoie ic pa enchyma ( he bone ma ow cells, excep cells o bone, a , and connec i e issue).Theuse ul egion is he nuclei and he cy oplasms a ound hem. Figu e 4 shows wo ideal pa s o samples. No mal nuclei a e pu ple, posi i e ib oblas s a e da k b own. The backg ound is clea whi e, he e a e no inapp op ia e hings, only nuclei, cy oplasm and whi e, ound a cells. Figu e 3. Main s eps o he algo i hm. 50 Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... Figu e 4. Ideal pa s o samples. The use ul egion is inside he black lines. On he o he hand, ideal case is a cu iosi y. The examina ion p ocedu e implies many mis akes, since each s ep can cause se e al e o s om he biopsy o he digi aliza ion. Tha is why, man- ual selec ion o some app op ia e egion o he digi al analysis is a s anda d. In ou opinion, his s ep should be omi ed because he samples can be inhomogeneous, so he selec ion may in luence he esul . 2.1. C ea ing mask o posi i e componen The a io o he posi i e ib oblas s and he use- ul egion is one o he mos impo an in o ma- ion o measu e he s a e o disease. As s a ed abo e, he posi i e ib oblas is da k b own, so i s , we need o de ine he b own mask, Bm=1,i H≤60 o 340 ≤H, 0,o he wise,(1) whe e Hdeno es hue channel o HSV ile. I is mo e di icul o ind h eshold le el, which can sepa a e ib oblas om he plasma o o he cells and he backg ound. I can also be im- po an in o ma ion whe he he posi i e ib ob- las s a e o ming a dense ne wo k, and i he h eshold is high, he ne wo k will b eak up. And when he h eshold is low, he de ec o equen ly inds alse ne wo ks because he dis- colou ed backg ound can connec sepa a ed pa s. Using sa u a ion channel seems o be sui able o pa i ion, al hough he shapes o his og am a e a ious. To de ec in e es ing pa s he B=1,i Bm=1andS> , 0,o he wise, o mula is used, whe e is he le el o h eshold compu ed on he Sb=S,i Bm=1, 0,o he wise, whe e Sdeno es sa u a ion and Bmis de ined by (1). We es ed some well-known au oma ic h esh- old algo i hms o ind sui able h eshold alue, such as O su (1997), h ee-le el O su [14],Yen [18], Ki le [11]. We obse ed, ha each es ed me hod is sensi i e o he discolou ed back- g ound and plasma, excep he Ramesh [15] and A o a [1]wi h adequa e pa ame e s ha pe o med well also in he p oblema ic cases. The la e p ocedu e wi h he pa ame e s, which wo ked well in noisy pic u es, was oo s ic in cases o cleane pic u es, hus we chose he Ramesh me hod. The esul o an ideal case can be seen in Figu e 5b and Figu e 5c – 5e gi es example ha discolou ed plasma can mis- lead o he h eshold me hods. (Only he esul s using Ramesh and he wo O su h esholds a e p esen ed he e.) Figu e 5. De ec ed ib oblas s using a ious h eshold me hods. (a)The o iginal image, (b)Ramesh me hod on (a),(c)O iginal image wi h discolou ed plasma, (d) O su me hod on (c),(e)Highe h eshold o h ee-le el O su me hod on (c),( )Ramesh me hod on (c). 2.2. C ea ing mask o use ul egion To de ec use ul egion, he s a ing-poin is he ideal case, when almos all he b own and pu - ple pixels belong o i . A e ha , we elimina e he unwan ed objec s. Finally, we ex end he mask o nuclei inside he emaining pa . Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... 51 2.2.1. De ec ing use ul candida e pixels Since he plasma belongs o he use ul egion he c i e ia o highligh use ul candida e poin s a e mo e pe missi e han when he aim is o de ec posi i e ib oblas s. The mask o use ul candida e om b own pa s is de e mined by Bc and o ha om pu ple pa s is de e mined by Pc. Bc=1,i Bm=1andS>20, 0,o he wise,(2) Pc=1,i 160 ≤Hand H≤320 and S>20, 0,o he wise, (3) whe e His he hue, Sis he sa u a ion channel o he HSV ile. The h eshold o he sa u a ion ensu es ha he whi e a issue is no included in he mask. 2.2.2. De ec ing lobe-like objec s In an ideal case he Bcand Pc o m oge he he use ul egion, bu he pixels o o he is- sue also can sa is y he o mula Pco Bc.The non-use ul pa s in pu ple egion, excep he olds, a e commonly smoo he han he use ul segmen s. Whe eas he middle o nucleus is b igh colou ed su ounded by pale cy oplasm o b own ibe s, he lobe-like objec s a e ho- mogeneous. Figu e 6 displays ypical kinds o non-use ul egions. Figu e 6. Typical kinds o unin e es ing pa s. To de ec lobes, he homogeneous egion was highligh ed om he pu ple egion by L0=1,i 160 ≤Hand H≤320 and Eg+Es<40, 0,o he wise, o mula, whe e Eg,Esa e he edge images com- pu ed by Sobel ope a o wi h 5 ×5maskon he g ay-le el espec i ely sa u a ion image. The o mula causes he segmen s con aining g oup o nucleus o all apa , while he lobe-like ob- jec s emain whole. (Figu e 7b) A e connec ed componen labelling [4]was used on L0 o de ec each blob, we copied all he blobs la ge han he gi en limi o L.(In ou case he limi was se o 500.)Since he edge o blobs does no belong o he L, we dila e L by he ollowing mask: M= ⎡ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎣ 0011100 0111110 1111111 1111111 1111111 0111110 0011100 ⎤ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎦ (4) In he nex s ep, we used hole illing on L o elimina e la ge hole in he blobs. Figu e 7c p esen s he esul image. Finally, we emo e L om Pc.Le Pdeno e he new image. Figu e 7. S eps o elimina ing he lobes. (a)O iginal image, (b)Raw lobe mask (L0),(c)De ec ed lobe (L), (d)Pu ple nuclei (P). 2.2.3. Ex ending mask o nuclei Remembe ha Bccon ains only posi i e ib ob- las s, bu we also need he plasma be ween hem. Since he in e es ing plasma egions a e e y simila o lo s o non-use ul pa s, he egion g ow algo i hms canno be used. Ins ead o hem, we ill he small holes be ween he nu- clei inside he candida e egion, bu hose pixels which we e emo ed om Pc, canno become use ul pixels. U0=Po B, U=(U0•M)and (Po Bc), 52 Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... whe e •is he mo phological close ope a o and Mis he Fo mula 4. Figu e 8a p esen s esul o his s ep on Figu e 7a. Figu e 8c is he de- ec ed ib oblas and he no mal cells (U0)in Figu e 8a. We ex end his egion applying M, which can elimina e he small holes be ween he ibe s and nuclei (Figu e 8d). In good case he ex ended pa is plasma, bu backg ound o lobe-like objec may be added o he esul as well. So we keep only pixels alling in he use ul candida e egion (wi hou lobes)(Figu e 8e). This is ensu ed by he “and” ope a o be- ween he wo pa s o he o mula. We can obse e in his example ha (Po B)almos pe ec ly ma ches he use ul egion. I ’s a bi misleading, because his pa can con ain also he discolou ed backg ound, i he s ain has no been pe ec . Figu e 8. (a)De ec ed use ul egion on 7.a. (b)-( )The de ailed example o compu ing U:(b)an o iginal image, (c)posi i e ib oblas s and no mal cells (U0), (d)U0dila ed by M,(e)use ul candida e egion wi hou lobes (Po Bc),( ) he esul . 2.3. Sa e y il e Howe e , mos o he noise was emo ed by he p e ious s eps, some o unin e es ing pa s could emain in he U. I can happen ha he use ul egion in he slide is much mo e smalle han he o he ( o eg ound) egions. Acco d- ingly, we ha e o deal wi h his p oblem, else lo s o small e o s could in luence he esul s. One eason o he e o is i ano he so o is- sue ge s in o he sample (See Figu e 9), o olds emain in he de ec ed use ul egion. Figu e 9. De ec ed bone ma ow cells in muscle issue (a)and in connec i e issue (b). When he mask o use ul egion was c ea ed, mos o hese e o s we e il e ed ou . The g ea e he di e ence be ween he Pcand P, he mo e likely ha he emaining pa s o pu - ple one a e bugs. Based on ou expe ience he alse emaining pa s a e less han 15% o he emo ed pa . The le side o Fo mula 6 es i- ma es he a io o he emaining lobes a ea and he nuclei a ea. We also ha e o check whe he he ile con ains enough da a (Fo mula 5), because we will in- oduce ea u es o cha ac e ize he samples in he nex sec ion, and some o hem may gi e alse esul i use ul a ea can be ha dly ound in he ile. a(U)>s 10 (5) 0.15 ·(a(Pc)−a(P)) a(B)+a(P)<e,(6) whe e a(X) he a ea o Xand sis he size o he ile, and eis he gi en limi o e o . When ea u es o he whole slide a e compu ed, only iles sa is ying (5)and (6)a e used. On a e age, 48% o he iles (con ains da a)sa is- ies he condi ion. In many cases almos whole sample is bone, a and connec i e issue. This is consis en wi h he expe ience o o he e- sea che s [12]. We ha e p ocessed 25870 Mi ax iles, o which 6819 con ained any da a (o he s only con ained backg ound). Table 2 p esen s he de ailed e- sul . Rejec ed by All Con ains inapp op ia e obj. Fo mula 5. 2488 1681 Fo mula 6. 884 883 Table 2. Numbe o iles il e ed ou by Fo mula 5 and Fo mula 6 wi h e=0.01. Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... 53 To ind ou how e icien ly we il e ou he i - ele an pa s, we implemen ed [7]and es ed i on ou samples (Figu e 10). I is ob ious ha he compa ison canno be comple e because he s aining me hods a e di e en . Mo eo e , he goal o he whole p ocedu e in [7]is o ind bones, while we emo e lobe-like objec s (in- cluding he bone)in a ious s eps. Conside ing only he bone de ec ion, i is a y- ing which algo i hm is mo e e icien . Gonza- lez’s algo i hm uses ix numbe o clus e s, hus i he e is no bone in he pic u e, his algo i hm ine i ably ails. In gene al, he olds can also cause an e o because K-means o en classi y he pixels o he simple and he double laye o bones o di e en classes (Figu e 10b).Ou lobes de ec o is also no pe ec . I he lobes a e discolou ed o b own a bi , ou algo i hm does no ind hem co ec ly (Figu e 10g), bu o he s eps can elimina e hese pa s om he sample (Figu e 10h)and he sa e y- il e can h ow ou he ile. 3. Cha ac e isa ion o Samples A e c ea ing masks, some pa ame e s we e compu ed o cha ac e ise he samples. The a- io o posi i e ib oblas s a ea and use ul e- gion a ea is commonly used in e iculin sil e analysing [17]. Based on ou esul s, his a io is no always app op ia e o dis inguish he s age o samples, because he a ea o hin loose ne - wo k (PDGFR β 2)can be less han he a ea o isola ed posi i e ib oblas (PDGFR β 1). Thus, o he pa ame e s a e also calcula ed. Table 3 in- cludes calcula ed pa ame e s. Pa ame e s Desc ip ion PFib A A ea o posi i e ib oblas s egions. F bCoun Numbe o he posi i e ib oblas blobs (p b). SumPe m Sum o he pe ime e o p b. WPe m Weigh ed sum o he pe ime e o p b. Weigh is he numbe o c oss and end poin s o he skele ons o p b. Top50A Sum o he a ea o he 50 bigges p b on whole slide. Top50P Sum o he pe ime e o he 50 mos leng h pe ime e o p b. Top50S Sum o he leng h o skele on he 50 mos leng h pe ime e o p b. Table 3. Compu ed ea u es. The PFib A,F bCoun , SumPe m and WPe m we e no malised by he a ea o he use ul egion. Figu e 10. (a),(e)O iginal images wi h anno a ion. (The bone abecula is inside he black lines.). (b)Resul o Gonzalez me hod K-means s ep. (c)Resul o Gonzalez me hod on (a). (d)De ec ed lobe by ou me hod on (a).( )Resul s o Gonzalez me hod on (e),(g) De ec ed lobes (L)by ou me hod on (e).(h)De ec ed pu ple nuclei (P)on (e). 54 Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... Ou o he 41 scanned samples 11 a e PDGFR β 0, 9 a e PDGFR β 1, 10 a e PDGFR β 2, 11 a e PDGFR β 3 by manual g ading. Ou ob- se a ion is ha , mos pa ame e s a e di ec ly p opo ional o he manual g ades, bu he e a e some excep ions. Fo example, he F bCoun is o en la ge in PDGFR β 2 hanPDGFR β 3, hence when he p bs connec oge he , he num- be o p bs is dec eased. SumPe m also can be almos equal in bo h cases, because when he p bs close o each o he connec , he pe ime e o he new objec can be less han he sum o he pe ime e s o he o iginal p bs. The weigh in he WPe m can compensa e ha phenomenon. Figu e 11 p esen s he WPe m pa ame e s. The “Top” pa ame e s a e mainly in oduced o de- ec eme gence o posi i e ib oblas ne wo ks. Figu e 11. Rela ionship o WPe m and PDGFR β g ade. A p esen , only he F bCoun is no mal dis- ibu ed based on Shapi o-Wilk Tes wi h 0.05 le el, hus we chose he K uskal-Wallis es o compa e means o g oups. The H0( he median o a iable a e he same ac oss ca ego ies o PDGFR β )was ejec ed o each a iable. The MANOVA analysis con i med his obse a ion. Figu e 12 p esen s he CVA sca e plo [9].O cou se, his esul mus be ea ed wi h cau ion, because o he sample size. Figu e 12. CVA sca e plo : g een, blue, pu ple and ed deno e he a 0, 1, 2, 3 g ades in his o de . 3.1. Reliabili y We de ined some o he ea u es ha can indi- ca e he quali y o sample o eliabili y o e- sul s (Table 4). Some cases con ain only a ew usable iles, which is ele an in o ma ion abou he sample, since his alue is be ween 50 and 200 in gene al. A e using he sa e y il e , mos samples a e homogeneous by PFib A.Oc- casionally, he posi i e ib oblas is s onge in a ew iles, ha can be a isen om de ec ion e o , bu i also can be ue. The s ain e o is mo e ypical, and we canno il e ou his ype o e o well because he w ong segmen can be easily mis aken o heal hy one. The ex u e is he same, only he e o pa is smoo he a bi . Figu e 13 is a scenic example because PDGFR β g ade o his sample is 3. Figu e 13. Thumbnail o whole slide. Only he middle o he sample was s ained well. We c ea e he his og am PFib A wi h 0.1 bin. I e e y hing goes well, he his og am is uni- modal. O he wise one o he e o s (men ioned abo e)occu s. We de e mine he O su h esh- old, and compu e how many iles a e smalle (NumLow)o la ge (NumUsable-NumLow) han he h eshold. Ou expe ience shows ha i he e a e only ew ou lie s, hese iles con ain big essel o he issue is discolou ed nea he bone. I he e a e almos equal iles in bo h sides o h eshold, he sample was p obably badly s ained. In his case he p og am will no compu e he esul au oma ically. Fi s , an expe decides which g oup o iles is sui able o calcula ing he ea u es. Digi al Measu emen o Myelo ib osis Associa ed Pla ele De i ed G ow h Fac o Recep o β (PDGFR β )... 55 Pa ame e s Desc ip ion NumUsable Numbe o iles sa is y (5)and (6). NumFil e ed Numbe o iles sa is y (5)bu do no s a is y (6). Range Range o his og am. His oType Is his og am unimodal o no . NumLow Numbe o iles wi h lowe PFib A han h eshold. Table 4. Reliabili y ea u es. 3.2. Conclusion and u u e plans Immunohis ochemichal assessmen o PDGFR β on bone ma ow biopsy samples is a ypical example o semi-quan i a i e sco ing sys ems which a e equen ly used in pa hological p ac- ice. Biological samples usually show he e o- genei y, he ea u es o s age can be mixed, so i can be di icul o ind he g ade which is he bes o desc ibe whole sample. We ha e been de eloping an image p ocessing me hod ha enables us o analyse he bone ma - ow samples p epa ed by immunohis ochemi- cal s aining and make a possibili y o objec- i e compa ison o he samples. A p esen he me hod wo ks well on ideal samples, and can elimina e om he samples he ino dina e ob- jec s such as bone abecules, connec i e issue, muscle issue ai ly well. Ou me hod can also indica e ce ain s aining ailu e. The incipien esul shows he compu ed pa am- e e s enable a clea dis inc ion o ea ly (MF0-1) om ad anced (MF2-3)myelo ib osis and p o- ide a good basis o u u e classi ica ion o he disease. Howe e , because o he small sample size, u he in es iga ions a e necessa y. The esea ch is going on. Now, we ha e been dealing wi h some na u al phenomena caused by he s aining me hod. Fo example posi i i y may appea besides o bones edge in heal hy samples as well, and he inside o blood essels a e discolou ed ypically. In he immedia e u- u e, u he samples will be a ailable, ha will gi e us he oppo uni y o es ou analysing me hod on mo e a ied samples and selec he bes ea u es o de e mine he s a e o disease. Re e ences [1]S. ARORA,J.ACHARYA,A.VERMA,PRASANTA K. PANIGRAHI, Mul ile el h esholding o image seg- men a ion h ough a as s a is ical ecu si e algo- i hm. Pa e n Recogni ion Le e s,29(2)(2008), 119–125. [2]D. E. BAUERMEISTER, Quan i a ion o bone ma ow e iculin – a no mal ange. Am. J. Clin. 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