Integrated Optical Density (IOD), Syntactic Structure Analysis, and Survival in Operated Lung Carcinoma Patients

Path. Res. Pract. 190, 1031-1038 (1994)

Integrated Optical Density (IOD ), ,Syntactic Structure Analysis, and Survival in Operated Lung Carcinoma Patients K. Kayser\ F. Liewald 2 , K. Kremer 1 and M. Tacke 1 1 Department of Pathology, Thoraxklinik, Heidelberg; 2Department of Cardio-vascular and Thoracic Surgery, University Ulm, Ulm, FRG

SUMMARY Histological sections of formalin fixed, paraffin-embedded tissue comprising 19 5 specimens of human lung carcinomas were Feulgen stained. The nuclei of the histomorphological images were segmented using an automated image analyzing system, and the attributed minimum spanning trees (MST) were calculated. Features related to the DNA-content of the nuclei (integrated optical density (IOD), IOD-entropy, Sphase related fraction, percentage > 5C, etc.), and structural parameters (minimum distance between tumor cell nuclei, minimum distance between tumor cells and neighboring lymphocytes, MST-entropy, MST-current of entropy (entropiefluss), distance between neighboring proliferating tumor cells, etc.) were measured. The following results were obtained: the measured IOD and MST features showed significant differences between the primary carcinomas and metastatic carcinomas in the intrapulmonary lymph nodes. The survival of patients was remarkably improved if the carcinomas displayed a low S-phase related fraction, a low percentage of tumor cells> 5C, a low number of stem lines, and a low MST-current of entropy.

Introduction The following study was performed in order to analyze the clinical significance of measurements of the integrated optical density (IOD) and syntactic structure analysis in primary bronchial carcinomas. Patients with lung carcinomas have a poor prognosis in generaJl• 2 , and the prognosis is mainly related to clinical and postsurgical parameters such as the size and expansion of the carcinomas (T, pT stage), lymph node involvement (pN stage), and the presence of extrapulmonary metastases (M stage). Other parameters with some prognostic influence include features of DNA measurements such as the 2C deviation index, percentage of proliferating cells; and the classification of the carcinomas into diploid/aneuploid tumors 3 •4 •5. All © 1994 by Gustav Fischer Verlag, Stuttgart

these measurements have been performed either by use of flow cytometry3· \ or by static DNA-analysis with tumor imprints or disintegrated tumor cell nuclei after treatment with dissolving agents such as proteinase5. Although analyses of the integrated optical density (IOD) performed on Feulgen stained slides cannot measure the total DNA content of the tumor cells due to cutting artifacts, they offer, on the other hand, the possibility to analyze intercellular arrangements (structures) in combination with DNA-related features6· 7 • Some of these features (for instance, the distance ·between neighboring tumor cell nuclei in small cell lung carcinomas) have been reported to be of prognostic importance 8• The analysis of tumor structures on the level of light microscopy has been shown to be associated with the prognosis of breast carcinoma pa0344-0338/94/0190-1031$3.50/0

1032 · K. Kayser et a!.

tients 9· This technique can also be used for analyzing the behavior of neighboring cells, and allows an insight into tumor cell organization 10 , or that of proliferating tumor cells if corresponding markers are additionally applied. Furthermore, the errors caused by cutting artifacts are negligible for small tumor cells and do not exceed 30% in very large tumor nuclei 10 . We now report on a prospective study of operated lung carcinoma patients in order to evaluate the prognostic significance of measurements of the IOD and syntactic structure analysis. In addition, we want to demonstrate that applications of the graph theory using attributed graphs can be considered as reproducible quantitative analysis of intercellular structures which may have even more clinical significance than expected.

Material and Methods

a) Specimens, Tumor Classification, and Survival Histological sections, 4-5 J.lm thick, were obtained from 195 surgical specimens of primary human lung carcinomas comprising 59 epidermoid carcinomas, 56 adenocarcinomas, 48 large cell carcinomas, and 32 small cell carcinomas. Tissue for examination was taken from the lung carcinomas and, if existent, from excised lymph node metastases. The sections were cut from formalin-fixed, paraffin-embedded tissue blocks and Feulgen stained according to the technique of MikeP 1 using 3.3 N HCl for hydrolysis at 37 oc for 40 min. The carcinomas were classified according to the rules of the WH0 12 based upon slides stained with HE, PAS, and a modified Sirius stain. Only patients with potential curative resections (RO stage) were taken into account. Survival of patients was monitored by repeated questionnaires sent to the house physicians every three months after operation. Detailed follow up data were missing in only 19 patients; the maximum follow up time was 78 months. Survival data were calculated using the Kaplan Meier estimation and the log rank test 13 •

b) Image Selection and Segmentation Only tumor boundaries with characteristic microscopic texture were chosen as areas of interest, and were interactively marked. The image to be measured was filtered by a 420-470 nm filter (filter No B12, Leica, Wetzlar) and digitized using a one chip real color video camera (JVC TK70E) connected to a personal computer via a frame grabber (Leutron XFP). Self-written programs based upon commercially avaible "digitized image analyzing software (DIAS)" allowed automatic image segmentation of nuclei of tumor cells and lymphocytes after interactively teaching a hierarchic classifier. Nuclei not segmented were interactively included into the segmentation after termination of the automated segmentation. Magnification was set x2.5 allowing the measurement of 100-150 tumor cell nuclei per image in primary carci-

nomas and lymph node metastases. Automated current feedback of the TV camera was disabled in order to assure a linear relation between grey value and extinction, which was confirmed by previous measurements10· 14 . A constant background was defined by color tables for certain grey values allowing the detection of possible changes of illumination during measurements. The background levels were automatically subtracted from the segmented nuclei. A matrix of 25 6 x 25 6 pixels at 8 bits per pixel was used. 300 tumor cell nuclei and 100 nuclei of lymphocytes for internal standardization were measured at minimum. Usually, 3 different areas of interest were randomly chosen from tumor boundary and from metastases occupying major parts of cross sections of lymph nodes. Apart from lymphocytes, non-tumorous cells were disregarded in the measurements.

c) Syntactic Structure Analysis The analysis of the two dimensional structure of the digitized image was performed using the attributed minimum spanning tree (MST) as basic procedure. The technique is described in detail elsewhere 15 ·' 6 • Briefly: the coordinates of the gravity centers of the segmented nuclei were defined as vertices (nodes) and the three basic MSTs were constructed in a vector oriented mode (MST of tumor cells only; MST of lymphocytes only; MST of both tumor cells and lymphocytes). Edges above a distance of 30 J.lm and below a distance of 4 J.lm were disregarded according to previous experiments (the lower limit reflects to overlapping nuclei, the upper limit to non-neighboring cells, if the neighborhood condition of O'Callaghan 17 is used). The features of the segmented nuclei were associated with the corresponding vertex allowing the construction of a weighted (attributed) MST. In a similar way, weighted MSTs of only those nuclei with an IOD > 5C (aneuploid-related fraction) or with 2.75 < IOD < 3.25 (S-phase related fraction) were constructed. The reproducibility of the calculated MST (labelling of vertices) was tested by arbitrary renumbering of the sequence of vertices and recalculation of the MST; that of boundary effects by gradual decreasing of the digitized matrix down to 64 x 64 pixels. No significant influence of both parameters could be noted on the defined neighbors and on the length of the distance between neighboring nuclei in accordance with previous measurements 10·

Measured Features of the IOD and MST The following nuclear features were measured: area, perimeter, sum of extinction (IOD), hole area (percentage of pale areas in the nuclei), form factor. The IOD was graded according to that measured from intratumorous lymphocytes which was multiplied by 1.18 according to calibration differences between the IOD of lymphocytes and that of normal epithelial cells. A linear calibration of the IOD-curve was assumed between 0 and that of the corrected IOD of lympho-

IOD and Survival in Primary Lung Carcinomas · 1033

properties and the derivation of the MST entropy and MST current of entropy are described in detail elsewhere14. Briefly, the MST entropy is computed according to the following formula:

cytes, which was associated with the 2C peak of cytometric measurements. The fraction of tumor cells having 2.75 < IOD < 3.25 was named "S-phase related fraction", and that of tumor cells with IOD > 5C "aneuploid-related fraction". It should be noted that these labels only roughly reflect to the underlying biologic terms which can only be accurately defined by solely cytometric measurements. The MST features included the distance between the centers of neighboring nuclei, cell type and IOD of neighboring nuclei, average distance between tumor cell nuclei, lymphocytes, aneuploid-related fraction of tumor cell nuclei, and S-phaserelated fraction of tumor cell nuclei. Statistical tests used were the F-test and the Kolmogorov-Smirnov test.

E (MST) = k ,. [D(IODIIOD) 2 + (D(r)/r) 2 ] [1] with D(IOD) = difference in IOD between nearest neighboring nuclei = mean IOD of the two neighboring IOD nuclei (tumor cells) difference in distance between nearD(r) est neighboring nuclei and mean distance of nuclei = mean distance between nearest r neighboring nuclei constant, set to 1 k

Entropy and Current of Entropy

This entropy measures the amount of all processes of labors related to structural differences, and assumes an energy field which is in proportion to the square of distances between neighboring structure elements. E (MST) reflects to the total of energy needed for disturbance of symmetrical distribution of neighboring nuclei either in genetic substance (measured in IOD) or structural differences (measured in distance between the centers of gravity of neighboring tumor cells). It becomes zero if both the genetic substance and the distance between two neighboring nuclei correspond to the mean of the underlying structure. Entropy, generally speaking, measures the amount of "lost" energy or

The entropy of the IOD distribution was computed according to the formula given by Stenkvist18 . It describes the statistically defined information content of the IOD frequency distribution of tumor cells. If all tumor cells had exactly the same IOD the information of the whole system in respect to IOD could be described by one class only, namely that containing the value of the IOD. The following modifications were made: the number of different channels (N) of the IOD distribution (classes of the corresponding IOD diagram) was set at 100, and the computed entropy was divided by N''ln"(N); i.e. the modified entropy is independent from the number of channels used. The

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Fig. 1: Survival rates of operated bronchial carcinoma patients grouped according to number of stem lines Group Feature 1 2 3 total

1 stem line 2 stem lines >2 stem lines

Patiens Deaths included 42 46 - 107 195

11

15 76 102

8

16

23

31

39

Months

47

55

62

70

78

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Fig. 2: Survival rates of operated bronchial carcinoma patients grouped according to S-phase related fraction

23

Group Feature 1

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31

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62

70

78

Months

"lost" information in a closed system which transforms energy or transfers information. It is, however, only of limited value in a biological system which is thermodynamically open. According to Onsager's theory the current of entropy describes the total of irreversible created heat in a thermodynamically open system which has to be removed through its surface. According to the theory of irreversible thermodynamics any such system tries to minimize its current of entropy, i.e. the greater the current of entropy the more the system is deviated from its steady state 14 • If the tumor volume V and its mean diameter DT are known, the current of entropy EF (IOD) and EF (MST) can be approximated by the formulas EF (IOD) = k*E (IOD) •;s·=· (DT/r) 3 ':- (DTN) [2] EF (MST) = k•=·E (MST) ·;s·=· (DT/r) 3 •:- (DTN) [3] with

s

S-phase related fraction

DT

= mean tumor diameter

k

= constant, set to 1

v

tumor volume

mean distance between nearest neighboring cells E (IOD) entropy of IOD distribution E(MST) = entropy of MST as defined by [1] r

S reflects to the percentage of proliferating cells, DT/ V to the tumor surface, and E*(DT/r) 3 to the total of entropy within the tumor.

2 3 total

Patients Deaths included

<15% S-phase 115 > 15 % and > 20 % 46 >20 o/o 34 195

45 36

21 102

Results A synopsis of the material is given in table 1. All in all, 195 patients were included in the study. The majority of carcinomas had to be classified into the pT2 and pN1 stages. In order to test the reproducibility of measurements, 25 cases were randomly selected and measured again after a time period of 1 year by a different person. The result is given in table 2. No statistically significant differences could be seen in any of the measured features. The measured IOD and MST features in relation to the cell types are shown in table 3. All frequency distributions of the measured features have an approximated Gauss distribution. Therefore, confidence limits for better estimation of statistical significances are given. The IOD associated features were similar in all carcinomas except the nuclear area which was significantly smaller in the small cell carcinoma cases. Within the MST related features the MST entropy was significantly smaller in the small cell carcinomas (p < 0.05), whereas the current of entropy was found to be independent from the cell type. A comparison between the measured features of the primary tumors and the lymph node metastases revealed significant differences between both groups (table 4 ). These differenc;es were found to be independent from the corresponding cell type. The survival of the patients was closely related to the number of stem lines (Fig. 1), to the S-phase related fraction (Fig. 2), to the percentage of tumor cells with an IOD > 5C (Fig. 3), and

IOD and Survival in Primary Lung Carcinomas · 1035 19

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Fig. 3: Survival rates of operated bronchial carcinoma patients grouped according to aneuploid tumos cell fraction > 5C Group Feautre 1

2 3 total

Patients Deaths included

< 5%

21 53 28 102

87 > 5 % and < 20 % 75 > 15% 33 195

8

16

23

31

39

47

55

62

78

Months

to the MST current of entropy (Fig. 4). These differences in survival were also seen in the cohorts of patients with identical tumor stages, i.e. in patients with pTl (pT2,pT3,pNO,pN1,etc.) tumor stages only. A similar influence on the survival was found for the IOD current of entropy, whereas the IOD entro-

py, the 2CV standard deviation, and the MST entropy, as well as the maximum tumor diameter or the tumor volume were not significantly related with the survival of the patients.

Table 1. Synopsis of Material

Measurements of strucural features in human carcinomas may give an important insight into the relationship between structure and function, i.e. biological

Discussion

Feature

Sex Men

Total Cell Type Epidermoid Adeno Large cell Small cell T stage T-1 T-2 T-3 T-4 T-X

156

39

195

54 37 36 29

5 19 12 3

59 56 48 32

34 78 28 4 12

9 21 5 3 1

43 99 33 7 13

IOD Entrophy

53 41 38 14 10

14 7 11 4 3

67 48 49 18 13

IOD Entropiefluss Distance TU-TU (/-l) Distance TU-LY (/-l) MST Entropy MST Entropiefluss

N stage N- 0 N -1 N -2 N -3 N-X

Women

Total

Table 2. Reproducibility of IOD and MST Measurements Feature

Measurements (N =25, Mean and stand DEV) Previous 12 Months Later

% S-Phase

13±6 7±6 11 ±7 220±50 132 ±71 12±2 11±2 104 ± 71 23 ±13

% >5C 2CV-STND

12±6 8±7 12±7 208 ±51 137 ± 65 12±2 11 ±3 105 ± 81 35 ± 14

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behavior. Van Diest et aP applied the graph theory procedure to breast carcinomas and reported a close relationship between the number of neighboring tumor cells, the distance between neighboring tumor cells, and the average length of the minimum spanning tree and the survival of patients. Kayser et al. 8 reported an improved survival of patients with smaJl cell anaplastic carcinomas if the distance between neighboring tumor cells measured > 8 11m. There is increasing evidence

78

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total

< 10 > 10 and< 30 > 30

Patients Deaths included 77

80 38 195

that the con truction of attributed graphs is a suitable technique and an easy to use tool for analysis of microscopic tumor growth patterns. They can be used as tools for analysis of soft tissue structures 16 , growth characteristics of malignant epithelial tumors 10 • 1\ or spatial agglutinations of cells with different binding sites to antibodies. Measurements of DNA properties (DNA content) performed on histological slides cannot define the absolute DNA content in principle,

Table 3. Features of IOD and MST in Realtion to cell Type (confidence Limits, P>0.95) Feature

Cell Type Epidermoid

Adeno

Large Cell

Small Cell

Nuclear Area (112 )

55- 60

73- 80

66- 75

33- 38

% S-Phases

10- 14

10- 14

10- 14

12- 16

8- 13

8- 13

% >5C

2CV-STND IOD Entropy

5- 11

4-

9

75-135

61-127

76-143

36-116

192-241

199-251

202-253

211-249

IOD Entropiefluss

99-143

97-137

103-144

105-153

Distance TU-TU (Jl)

11- 13

12- 14

9- 11

Distance TU-LY (Jl)

10- 12

11- 13 10- 13

11- 13

10- 12

MST Entropy

79-126

78-127

84-136

59- 77

MST Entropiefluss

29- 43

27- 41

31- 44

31- 44

TU =Tumor Cell Nucleus, LY = Lymphocyte Nucleus.

25 49 28 102

IOD and Survival in Primary Lung Carcinomas · 1037 Table 4. Features of IOD and MST in Primary Lung Carcinomas and Involved Lymph Nodes (Confidence Limits, P>0.95) Feature IOD Features: % S-Phases % >5C 2CV-STND (''10) Entropy MST Features: Distance TU-TU"· (J.!) Distance TU-LY'-· (J.!) Distance Pro! Tumor Cells (J.!) Distance Tumor Cells >5C (~t) MST Entropy

Tumor (N=195)

Lymph node (N=115)

12- 14 6- 8 85-107 215-231

8- 10 17- 23 31- 53 256-276

11- 12 10- 11 37- 41 25- 28 89-105

14- 16 12- 14 47- 59 37- 49 125-188

'' TU = Tumor Cell Nucleus; LY = Lymphocyte Nucleus.

and are, in addition, less precise than measurements performed on cytological material. Several authors have reported that lung carcinoma are aneuploid in a high percentage 3• 4 • 19 and that the information about their S-phase fraction and stem lines may be of prognostic importance 20• 21 • 22 • The results of our measurements can be separated into two basic statements: a) Lymph node metastases of primary lung carcinomas have different DNA and growth pattern related features in comparison to their intrapulmonary origins. b) The survival of the patients is stronly related to IOD and structural related features. The tumor cells growing in lymphatic tissue (intrapulmonary lymph nodes) are characterized by a smaller S-phase related fraction and a higher percentage of tumor cells with an IOD > 5C compared to the tumor cells growing in the lung parenchyma. In addition, the distance between the centers of nearest neighboring tumor cells, between tumor cells and nearest neighboring lymphocytes, between proliferating tumor cells, and between tumor cells with an IOD > 5 C is larger in carcinomas growing in the lymph nodes compared to tumors growing in the lung parenchyma (Table 4). These data reflect to previous results which reported different structures of lymph node metastases compared to their original carcinomas 10 . These differences are probably related to the properties of the environment of the host tissue: lymph nodes have no empty air spaces for easy cell proliferation, probably an increased level of immune defense, and a lower volume fraction of vascularization compared to peripheral lung tissue. The obtained importance of the S-phase related tumor cell fraction, percentage of tumor cells > 5C, number of stem lines, and MST current of entropy for the survival of patients is in accordance with data reported from flow cytometry. Ten Velde et al. 21 , and Miyamoto et al. 23 divided bronchial carcinomas into diploid and aneuploid tumors, and reported a poor survival of patients with aneuploid tumors compared to the diploid ones. Our study confirms the close relation between results obstained from flow cytometry and static

DNA analysis in respect to the biological behavior of bronchial carcinomas. The influence of the above mentioned features on the survival holds not only true for all the patients, but is, in addition, a still powerful prognostic indicator for cohorts grouped according to clinical stages; i.e. for patients with pTl, pT2, etc. tumors. Patients with pTl tumors and a lowS-phase dated fraction (< 5%) have an improved survival compared to patients with the same tumor stage and a high S-phase related fraction (> 5% ). A similar influence is seen for patients grouped according to the pN stages. The differences of these features between the intra-pulmonary tumors and the tumor cells growing in the (intrapulmonary) lymph nodes induce a strict separation of these tumor compartments if measured for prognostic purposes. This may be sometimes difficult in central bronchial carcinomas, especially if the carcinoma cells are measured by tissue degradation, i.e. by flow cytometry. References 1 Biilzebruck H, Dringes P, Kayser K, Schulz V, Tuengerthal S, Vogt-Moykopf I (1991) Classification of lung cancer: first experiences with the new TNM classification (4th edition). Eur Respir J 4: 1197-1206 2 Kayser K, Btilzebruck H, Probst G, Vogt-Moykopf I (1987) Retrospective and prospective tumor staging evaluating prognostic factors in operated bronchus carcinoma patients. Cancer 59: 335-361 3 Sahin A, Ro J, El Naggar A, Lee J, Ayala A, Teague K, Hong W (1990) Flow cytometric analysis of DNA content of non-small cell lung cancer. Ploidy as a significant prognostic indicator in squamous cell carcinoma of the lung. Cancer 65: 530-537 4 Shiota T, Konishi T, Kosaba S, Mitsouka A, Matsubara Y, Hatakenaka R, Funatsu T, Ikeda S, Matsumoto H, Ishigami F (1999) Flow cytometric analysis of cellular DNA content of lung cancer with reference to survival. Nippon Kyobu Geka Gakkai Zasshi 38: 2364-2369 5 Liewald F, Sunder-Piassmann L, Dienemann H, Kahle H, Wulf G, Valet G (1992) Prognostic value of flow dytometrically determined DNA-ploidy, intracellular pH, and esterase

1038 · K. Kayser eta!. activity of non-small cell lung carcinomas. Anacel 4: 103114 6 Kayser K (1987) Neighborhood condition and application of syntactic structure analysis in histo-pathology. Acta Stereo! 6: 373-384 7 Kayser K, Stute H, Ebert W (1987) Analysis of branching points and minimum, distance between neighboring cells in primary bronchus carcinoma. Acta Stereo! 6: 207-212 8 Kayser K, Fitzer M, Biilzebruck H, Bosslet K, Drings P (1987) TNM stage, immunohistology, syntactic structure analysis, and survival in patients with small cell anaplastic carcinoma of the lung. J Cancer Res Clin Oncol113: 473-480 9 van Diest (1990) Quantitative cyto- and histoprognosis in breast cancer. University Press 1081, HV Amsterdam 10 Kayser K, Stute H, Bubenzer ], Paul J (1990) Combined morphometrical and syntactic structure analysis as tools for histomorphological insight into human lung carcinoma growth. Anacel 2: 167-178 11 Mikel U, Fishbein W, Bahr G (1985) Some practical considerations in quantitative absorbance microspectrophotometry. Analyt Quant Cytol Histol 7: 107-118 12 World Health Organisation (WHO, 1981) Histological classification of lung tumors, Geneva 13 Kaplan EL, Meier P (1958) Nonparametric estimations from incomplete observations. Am Stat Ass J 53: 457-481 14 Kayser K, Kremer C, Tacke M (1993) Integrated optical density and entropiefluss (current of entropy) in bronchial carcinoma. In vivo 7: 387-392 15 Kayser K, Sandau K, Paul J, Weisse G (1992) An approach based on two-dimensional graph theory for structural

cluster detection and its histopathological application. J Micros 165: 281-288 16 Kayser K, Sandau K, Bi.ihm G, Kunze K, Paul J (1991) Analysis of soft tissue tumors by attributed minimum spanning tree. Analyt Quant Cytol Histol 13: 329-334 17 O'Callaghan JF (1975) An alternative definition for neighborhood of a point. IEEE Trans Comput 24: 107-118 18 Stenkvist B, Strande G (1990) Entropy as an algorithm for the statistical description of DNA cytometry data obtained from image analysis microscopy. Anacel 2: 159-166 19 Isobe H, Mijamoto H, Shimizu T, Haneda H, Hashimoto M, Inoue K, Mizuno S, Kawakami Y (1990) Prognostic and therapeutic significance of flow cytometric nuclear DNA content in non-small cell lung cancer. Cancer 65: 1391-1395 20 Volm M, Bak M, HahnE, Mattern J, Weber E (1988) DNA and S-phase distribution and incidence of metastasis in human primary lung carcinoma. Cytometry 9: 183-188 21 ten Velde G, Schutte B, Vermeulen A, Volovics A, Reynders M, Blijham G (1988) Flow cytometric analysis of DNA ploidy level in paraffin embedded tissue of non-small-cell lung cancer. Eur J Cancer Clin Oncol 24: 455-460 22 Zimmermann P, Hawson G, Bint M, Parsons P (1987) Ploidy as a prognostic determinant in surgically treated lung cancer. Lancet 5: 530-533 23 Miyamoto H, Harada M, Isobe H, Akity H, Yamaguchi E, Kuzumaki N, Kawakami Y (1991) Prognostic value of DNA content and expression of ras oncogene product in lung cancer. Cancer Res 51: 6346-6350

Received September 14, 1993 · Accepted in revised form June 26, 1994

Key words: Lung carcinoma - Integrated optical density - Syntactic Structure analysis - Survival K. Kayser, M.D., Ph.D., Department of Pathology, Thoraxklinik, Amalienstr. 5, 69126 Heidelberg, Germany