Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 14  |  Issue : 2  |  Page : 361-367

Morphometric computer-assisted image analysis of epithelial cells in different grades of oral squamous cell carcinoma


1 Department of Oral and Maxillofacial Pathology, Buddha Institute of Dental Sciences, Patna, Bihar, India
2 Department of Oral and Maxillofacial Pathology, Sri Siddhartha Dental College and Hospital, Sri Siddhartha Academy of Higher Education, Tumkur, Karnataka, India
3 Department of Oral and Maxillofacial Pathology, Sri Sankara Dental College, Varkala, Kerala, India

Date of Web Publication8-Mar-2018

Correspondence Address:
Dr. Pillai Arun Gopinathan
Department of Oral and Maxillofacial Pathology, Sri Sankara Dental College, Akathumuri, Varkala, Kerala
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0973-1482.189423

Rights and Permissions
 > Abstract 


Introduction: Oral squamous cell carcinoma (OSCC) accounts 94% of all malignant lesions in the oral cavity. In the assessment of OSCC, nowadays the WHO grading system has been followed widely but due to its subjectivity, investigators applied the sophisticated technique of computer-assisted image analysis in the grading of carcinoma in larynx, lungs, esophagus, and cervix to make it more objective.
Aims and Objectives: Access, analyze, and compare the cellular area (CA); cytoplasmic area (Cyt A); nuclear area (NA); nuclear perimeter (NP); nuclear form factor (NF); and nuclear-cytoplasmic ratio (N/C) of the cells in different grades of OSCC.
Materials and Methods: Fifty OSCC cases were obtained and stained with hematoxylin and eosin which were graded according to the WHO classification. The sections were subjected to morphometric analysis to analyze all the morphometric parameters in different grades of OSCC and subjected to one-way ANOVA statistical analysis.
Results: CA and Cyt A decreased from normal mucosa with dedifferentiation of OSCC. The NA and NP increased in carcinoma group when compared to normal mucosa but decreased with dedifferentiation of OSCC (P < 0.05). NF had no significance with normal mucosa and different grades of OSCC (P > 0.05), while N/C ratio increased from normal mucosa through increasing grades of OSCC, reaching the highest value in poorly differentiated squamous cell carcinoma (P < 0.05).
Conclusion: Both cellular and nuclear variables provide a more accurate indication of tumor aggressiveness than any single parameter. Morphometric analysis can be a reliable tool to determine objectively the degree of malignancy at the invasive tumor front.

Keywords: Invasive tumor front, morphometric analysis, oral squamous cell carcinoma


How to cite this article:
Ananjan C, Jyothi M, Laxmidevi B L, Gopinathan PA, Nazir SH, Pradeep L. Morphometric computer-assisted image analysis of epithelial cells in different grades of oral squamous cell carcinoma. J Can Res Ther 2018;14:361-7

How to cite this URL:
Ananjan C, Jyothi M, Laxmidevi B L, Gopinathan PA, Nazir SH, Pradeep L. Morphometric computer-assisted image analysis of epithelial cells in different grades of oral squamous cell carcinoma. J Can Res Ther [serial online] 2018 [cited 2019 Nov 22];14:361-7. Available from: http://www.cancerjournal.net/text.asp?2018/14/2/361/189423




 > Introduction Top


The oral cavity is the preferable place in the head and neck region for the primary malignant tumor to manifest and oral squamous cell carcinoma (OSCC) accounts approximately 94% of all malignant lesions in the oral cavity.[1],[2],[3] In the assessment of OSCC, histological grading based on Broder's classification was followed earlier.[4],[5],[6] Since this grading system was subjective in nature and lacks consensus regarding its prognostic value, many other grading systems had been put forth.[1] Bryne suggested that molecular and morphological characteristics at the invasive front area of various SCC may reflect tumor prognosis better than other parts of the tumor.[1],[7] The WHO grades OSCC by the assessment of the degree of keratinization, cellular and nuclear pleomorphism, and mitotic activity[8],[9] and is followed widely.

To create the grading system more objective, sophisticated technique of computer-assisted morphometry was applied to investigate the cellular and the nuclear changes in correlation with the histological behavior of the lesions.[10],[11] The results have been more reliable, objective, and reproducible. It also may help to give a rapid and reliable diagnosis which has been applied with considerable success in pulmonary neuroendocrine neoplasms as shown by Marchevsky et al.[12]

Aims and objectives

  1. To assess and analyze the cellular area (CA), cytoplasmic area (Cyt A), nuclear area (NA), nuclear perimeter (NP), and nuclear form factor (NF) in different grades of OSCC
  2. To assess and analyze the nuclear-cytoplasmic ratio (N/C) of the cells in different grades of OSCC
  3. To compare the CA, Cyt A, NA, NP, NF, and N/C in different grades of OSCC.



 > Materials and Methods Top


The study was conducted on tissue sections which were obtained from the biopsy tissue specimens retrieved from the archives of the department. The study group comprised fifty various grades of differentiation based on the WHO classification of OSCC.

Fifty cases of OSCC were grouped as:

  • Group 1: Twenty cases of well-differentiated squamous cell carcinoma (WDSCC)
  • Group 2: Twenty cases of moderately differentiated squamous cell carcinoma (MDSCC)
  • Group 3: Ten cases of poorly differentiated squamous cell carcinoma (PDSCC).


The control group comprised ten cases of normal oral mucosa from the healthy adult individuals which were obtained during minor oral surgical procedures.

Inclusion criteria

  • Incisional biopsy specimen only were included in the study
  • Cases with the deepest invasive area with its invasive front were considered as that area shows the maximum amount of dysplastic features.


Exclusion criteria

  • No premalignant lesions and conditions were included in the study to reduce the bias between the premalignant and malignant conditions
  • Metastatic lesions were not included in the study.


Sections of 4 microns thickness were stained with freshly prepared Harris hematoxylin and eosin (H and E). The stained sections were observed under a research microscope [Figure 1]: WDSCC, [Figure 2]: MDSCC, and [Figure 3]: PDSCC] and graded using the WHO grading system only.[8],[9]
Figure 1: H and E stained sections of well-differentiated squamous cell carcinoma without morphometric analysis

Click here to view
Figure 2: H and E stained sections of moderately differentiated squamous cell carcinoma without morphometric analysis

Click here to view
Figure 3: H and E stained sections of poorly differentiated squamous cell carcinoma without morphometric analysis

Click here to view


Morphometric technique

The sections were subjected to the morphometric image analysis system. The system comprised a microcomputer, a digitizer tablet, a drawing pen (stylus), and a video camera (CCD) attached to a light microscope (OLYMPUS BX40).

The measurements were made by moving the stylus (drawing pen) around the outline of each dysplastic cells, appearing on the monitor. Once the stylus completes the outline of the cell, the Jenoptik Speed XT Core 3 with Capture Pro Software (Jenoptik, Germany) automatically measured the cellular perimeter and CA. The NP and NA were also measured in the similar way.

A magnification of × 400 was used for the measurements [Figure 4]: WDCC, [Figure 5]: MDSCC, and [Figure 6]: PDSCC]. After the measurements, the image was captured using CCD camera which is attached to the trinocular research microscope so that it could be documented with both premeasured and postmeasured photomicrographs in case if there were any confusion in the statistical analysis.
Figure 4: H and E stained sections of well-differentiated squamous cell carcinoma with morphometric analysis

Click here to view
Figure 5: H and E stained sections of moderately differentiated squamous cell carcinoma with morphometric analysis

Click here to view
Figure 6: H and E stained sections of poorly differentiated squamous cell carcinoma with morphometric analysis

Click here to view


Morphometric parameters

  • Four fields of sections were selected from the invasive front areas of all the grades of OSCC randomly
  • An attempt was made to divide the cell population into large and small cells and then take the average measurements to increase the appropriateness of the study
  • For each section, two large cells and two small cells and nuclei with clear, identifiable outline in each compartment is selected avoiding all the overlapping cells
  • Histologically identifiable nonkeratinocytes such as melanocytes showing clear cell change and inflammatory cells, as well as cells showing degenerative changes and those undergoing mitosis were not measured
  • For carrying out morphometric analysis of the normal mucosa, basal and parabasal layers were considered as these layers have least differentiated oral epithelial cells[13]
  • The actual measurements of the morphometric parameters were done by Image Analyzer Software ProgRes SpeedXT Core 3 (JENOPTIK optical system GmbH, Germany) after accurate calibrations are done using the stage micrometer
  • The size of the cell and its nucleus is measured with the area and the perimeter
  • Two large and two small cells were selected with a clear outline and which were not overlapping.


The CA, NA, and NP and other morphometric parameters such as the N/C and NF were calculated by the following formula:

  1. N/C ratio = N area/(C area − N area)
  2. NF = 4πNA/NP2 where π =22/7


All measurements were in microns (calibrations 1630 pixels = 140 μm, 1 μm = 0.001 mm) and was saved in the Microsoft Excel for further statistical analysis.


 > Results Top


Fifty cases of different grades of OSCC along with ten normal tissues were stained with H and E, and all the obtained values were subjected to one-way ANOVA statistical analysis.

The CA of normal mucosa was highest, and it significantly decreased (P< 0.05), with dedifferentiation of OSCC [Table 1]. The Cyt A decreased gradually from WDSCC to MDSCC but drastically in PDSCC with an overall significant P < 0.05 [Table 2]. The mean NA of various grades of OSCC is more than twice the mean NA of the normal cells which is in contrast to cellular and cytoplasmic parameters. It was also seen that in WDSCC had the largest mean NA followed by MDSCC and PDSCC, respectively, with an overall significant P < 0.05 [Table 3].
Table 1: Cellular area

Click here to view
Table 2: Cytoplasmic area

Click here to view
Table 3: Nuclear area

Click here to view


In OSCC, the mean NP was found to be about 30 μm with not much deviation of values seen within the different grades with a statistical significance of P < 0.05 [Table 4]. Hence, it is analyzed that the mean NP of all grades of OSCC was about 1.5 times the value obtained from the normal cells.
Table 4: Nuclear perimeter

Click here to view


With the obtained N P value, NF was also calculated from the formula (4πNA/NP2) and this parameter had no significance (P > 0.05) with the various grades of OSCC, as well as when compared with the normal tissue [Table 5]. The mean N/C ratio, when compared with various grades of OSCC, was found to be increased in carcinoma groups when compared to normal mucosa, and these values also increased significantly with increasing grades of OSCC [Table 6]. The N/C ratio of PDSCC has the highest value, which is 3.3 times the N/C ratio of normal cells, whereas MDSCC and WDSCC are about 2.7 times the N/C ratio of normal cells. The variation of the value for N/C ratio of WDSCC and MDSCC was not much, but it raised considerably in cases of PDSCC.
Table 5: Nuclear form factor

Click here to view
Table 6: Nuclear-cytoplasmic ratio

Click here to view



 > Discussion Top


OSCC is the most common malignant neoplasm arising from the mucosal epithelium of the oral cavity,[7],[10] and grading is of great importance as it has a direct correlation with the prognostic value.[14] All grading systems that have been put forth have many pitfalls as grading scores differ largely due to interobserver variability.[1] To make it more objective, many investigators have applied a sophisticated technique such as computer-assisted image analysis in the grading of carcinoma in larynx, lungs, esophagus, bladder, cervix, and many more.[10],[11],[15],[16],[17],[18],[19],[20],[21],[22],[23] Studies in oral cavity have also been done using image analysis starting in potentially malignant disorders such as leukoplakia, lichen planus, oral submucous fibrosis, and epithelial dysplasias.[24],[25],[26],[27],[28],[29],[30],[31]

Very few studies have applied the image analysis on different grades of OSCC to analyze the cellular and nuclear features in the invasive tumor front as it is of major significance for the prognosis of oral cancer providing better understanding of the mechanisms involved in tissue structure organization and cellular interplay at this biological “hot zone” of the tumors.[13],[14],[32],[33],[34]

It was observed that there was a considerable amount of variation in the NAs in previous researches; therefore, in this study, it was an effort to consider two large and two small cells in every field of all cases of OSCC to get the overall mean measurements of the epithelial cells to improve the reproducibility of the study.

H and E stain is the most popular routine stain used as the gold standard in the field of histopathology by pathologists for medical diagnosis; hence, we used the stain in all the cases as the focus was on the cellular, cytoplasmic, and nuclear morphology rather than only nuclear contents.

In the present study, the WHO classification[8],[9] was used to grade SCC into well, moderate, and poorly differentiated. Later the cellular, cytoplasmic and nuclear changes of various grades of OSCC were analyzed morphometrically at the invasive tumor front.

The mean CA in normal mucosa was the highest, and it decreased considerably in carcinoma group. With the dedifferentiation of OSCC, the mean CA reduced from 161.07 ± 29.48 to 127.03 ± 31.40 μm2 and MDSCC was found to be within these two ranges. Similar findings were obtained by Hande and Chaudhary,[34] where it was put forth that normal mucosa had the maximum cellular size, but as cells became actively proliferating to trigger carcinoma, the cellular size considerably decreased with increasing grades of OSCC. Cowpe[14] suggested that tissues undergoing malignant transformation show a reduction in the CA before a reduction in the NA.

The Cyt A for normal mucosa was maximum, and it started decreasing significantly with dedifferentiation of SCC. The difference in Cyt A for WDSCC and MODSCC was not obvious, but there was a radical reduction of Cyt A in the cases of PDSCC. Similar findings were observed with Hegde's[28] cytomorphometric study, wherein there was a significant reduction in the mean nuclear and cytoplasmic diameters in the cases of OSCC. Hegde et al.[28] suggested that there was the greatest reduction in the mean Cyt A of squames in SCC with histologic evidence of dysplasia. Thus, the findings can be supported by the statement that the major changes involved in normal cell maturation in oral epithelium are the changes in cell size and shape which may be due to the synthesis of more structural protein in the form of tonofilaments, the appearance of new organelles, and production of additional intercellular material.[13]

Therefore, we can hypothesize that as the cells of carcinoma get dedifferentiated, they also synthesize equally less tonofilaments, organelles, and intercellular material. This further has a direct bearing on the size of the cell, as well as their cohesive properties. Another possible reason for the reduction of CA in increasing grades of OSCC could be due to loss of ability of cells to adhere to each other due to downregulation of E-cadherin expression in carcinomas leading to loss of cellular size and shape.[35],[36] Therefore, in this histomorphological study, we can say that CA and Cyt A are found to be inversely proportional to the increasing grades of OSCC.

When the NA was analyzed in normal mucosa (34.39 ± 3.41 μm2), it was half of the NA in the carcinoma group which ranged from 62 to 88 μm2. Analyzing the NA in different grades of OSCC, NA decreased with the dedifferentiation of OSCC. It was observed that NA increased considerably in the carcinoma group when compared to normal mucosa, but decreased within the grades of OSCC. As the NA decreased, it was quite obvious that even the NP should decrease with increasing grades of OSCC and the exact result was achieved in our study but not much of numerical deviation was observed between the various grades, but whatever difference was obtained, it was found to be statistically significant.

Our observations were in agreement with findings of Laitakari et al.,[18] who observed that nuclear size decreased with decreasing degree of differentiation and Sunitha et al.[30] in the area of invasive tumor front also observed that the mean NA increased in descending order of histological grades of OSCC. Kinoshita et al.[27] mentioned that increase in nuclear size in carcinomatous tissue is because of the fact as the cells proliferate in carcinogenesis, they possess more biological activity comprising increase in chromosomes related to abnormal division, increase of nuclear DNA content which in turn increases the size of the nucleus.

In the present study, when considering the various grades of OSCC, NA decreased significantly with increasing grades, which was in contradiction to various authors. Therefore, we hypothesize that this finding may be due to the fact that high-grade tumors show more mitotic activity, abnormal mitotic figures, less potential for DNA repair thereby increased DNA damage which ultimately leads to irregular nuclear shape thus finally decrease in nuclear size.

NF was assessed as described by Nandini and Subramanyam,[29] and it was suggested that a perfect circle has a form factor of 1.0 and elliptical structures deviate considerably from unity toward zero as their degree of circularity becomes less perfect. Based on this concept, it was found that NF was less in the carcinoma group than normal mucosa suggesting that irregularity or loss of roundness prevails in the carcinoma group. Although NF decreased, there was no statistically significant relationship between normal and carcinoma group or within different grades of OSCC which was in accordance with Nandini and Subramanyam.[29] Tan et al.[37] and Sunitha et al.[30] suggested that the nuclear shape, nuclear roundness, and ellipticity were not an important parameter to differentiate grades of SCC which could be due to inherent problems with tracing irregular nuclear contours of malignant cells for image analysis.

The N/C ratio was a contrasting parameter with respect to CA, Cyt A, and NA as this parameter was directly proportional to the increasing grades of OSCC. The scrutiny regarding N/C ratio fell in with the observations by several investigators as all of them proposed that N/C ratio increases in the carcinoma group when compared to normal mucosa and when various grades of SCC was taken into consideration, N/C ratio increased with dedifferentiation.[10],[14],[25],[28],[38],[39],[40]

It could be hypothesized that the reduction in mean CA and mean Cyt A of the epithelial cells of OSCC is much more than the reduction in the mean NA of the respective cells.

From the overall findings, we could infer that there was not much of numerical deviation observed between the WDSCC and MDSCC cases in all the parameters, but PDSCC showed marked variation within the grades. Therefore, it might be tricky for one to differentiate between WDSCC and MDSCC by morphometric technique, but to differentiate PDSCC from lower grades becomes unmistakable.

There are several investigators who have done extensive researches on nuclear morphometry to assess and analyze only the nuclear features in various tissues of different grades of SCC. However, in the present study, along with the nuclear features such as NA and NP, even the CA and Cyt A seem important parameters that have to be considered while grading the carcinoma to increase the objectivity for better prognostic value.


 > Conclusion Top


The combination of several cellular and nuclear variables provides a more accurate indication of tumor aggressiveness and behavior rather than any single parameter. A truly prospective study on large series of carcinoma patients is required to determine the practical use and validity of this objective system. In the present study, it was found that the morphology of all the cellular and nuclear features reflect cell biologic behavior and general activity.

The results of the research show a significant reduction in CA, cytoplasmic area, NA, and NP with increasing grades of OSCC, while the N/C ratio was increasing with the increasing grades of OSCC. NF had no significant relationship in various grades of OSCC.

This indicates that a combination of several cellular and nuclear variables provide a more accurate indication of tumor aggressiveness and behavior rather than any single parameter. Hence, the computer-assisted histomorphometric techniques can be used as a reliable tool to determine objectively the degree of malignancy of oral tissues at the invasive tumor front.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
 > References Top

1.
Ankur B, Sonal S, Monali C. Histopathological grading systems in oral squamous cell carcinoma: A review. J Int Oral Health 2010;2:1-10. Available from: http://www.ispcd.org/userfiles/rishabh/jioh-02-04-001.pdf. [Last accessed 2016 Aug 02].  Back to cited text no. 1
    
2.
Neville BM, Damm DD, Allen CM, Bouquot JE. Epithelial pathology. Oral and Maxillofacial Pathology. 2nd ed., Ch. 10. Philadelphia: Elsevier; 2002. p. 356-70.  Back to cited text no. 2
    
3.
Massano J, Regateiro FS, Januário G, Ferreira A. Oral squamous cell carcinoma: Review of prognostic and predictive factors. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2006;102:67-76.  Back to cited text no. 3
    
4.
Mohan H. Essential Pathology for Dental Students, General Aspects of Neoplasia. 2nd ed. New Delhi: Jaypee Brothers Medical Publisher (P) Ltd.; 2002. p. 221-30.  Back to cited text no. 4
    
5.
Shafers WG, Hine MK, Levy BM. Benign and malignant tumours. Text Book of Oral Pathology. 4th ed., Ch. 2. Philadelphia: W.B. Saunders Company; 1997. p. 143-60.  Back to cited text no. 5
    
6.
Regezi JA, Sciubba JJ, Jordan RC. Oral Pathology – Clinical Pathologic Correlations. 4th ed. USA: Saunders, Elsevier Science; 2003. p. 52-68.  Back to cited text no. 6
    
7.
Doshi NP, Shah SA, Patel KB, Jhabuawala MF. Histological grading of oral cancer: A comparison of different systems and their relation to lymph node metastasis. Natl J Community Med 2011;2:136-42. Available from: http://www.njcmindia.org/home/download/107. [Last accessed on 2016 Aug 09].  Back to cited text no. 7
    
8.
Woolgar JA. Histopathological prognosticators in oral and oropharyngeal squamous cell carcinoma. Oral Oncol 2006;42:229-39.  Back to cited text no. 8
    
9.
Pindborg JJ, Riechart PA, Smith CJ. Carcinomas. Histological Typing of Cancer and Precancer of the Oral Mucosa. 2nd ed. Ch. 1. Berlin: Springer; 1997. p. 11-6.  Back to cited text no. 9
    
10.
Smitha T, Sharada P, Girish H. Morphometry of the basal cell layer of oral leukoplakia and oral squamous cell carcinoma using computer-aided image analysis. J Oral Maxillofac Pathol 2011;15:26-33.  Back to cited text no. 10
[PUBMED]  [Full text]  
11.
Ooms EC, Kurver PH, Veldhuizen RW, Alons CL, Boon ME. Morphometric grading of bladder tumors in comparison with histologic grading by pathologists. Hum Pathol 1983;14:144-50.  Back to cited text no. 11
    
12.
Marchevsky AM, Gal AA, Shah S, Koss MN. Morphometry confirms the presence of considerable nuclear size overlap between “small cells” and “large cells” in high-grade pulmonary neuroendocrine neoplasms. Am J Clin Pathol 2001;116:466-72.  Back to cited text no. 12
    
13.
Nanci A. Tencate's Oral Histology: Development, Structure and Function. 7th ed. Haryana: Mosby, Elsevier; 2010. p. 328-33.  Back to cited text no. 13
    
14.
Cowpe JG. Quantitative exfoliative cytology of normal and abnormal oral mucosal squames: Preliminary communication. J R Soc Med 1984;77:928-31.  Back to cited text no. 14
    
15.
van Velthoven R, Petein M, Oosterlinck WJ, Zandona C, Zlotta A, Van der Meijden AP, et al. Image cytometry determination of ploidy level, proliferative activity, and nuclear size in a series of 314 transitional bladder cell carcinomas. Hum Pathol 1995;26:3-11.  Back to cited text no. 15
    
16.
François C, Decaestecker C, Petein M, van Ham P, Peltier A, Pasteels JL, et al. Classification strategies for the grading of renal cell carcinomas, based on nuclear morphometry and densitometry. J Pathol 1997;183:141-50.  Back to cited text no. 16
    
17.
Dobros W, Gil K, Chlap Z, Olszewski E. The use of nuclear morphometry for the prediction of survival in patients with advanced cancer of the larynx. Eur Arch Otorhinolaryngol 1999;256:257-61.  Back to cited text no. 17
    
18.
Laitakari J, Harrison D, Stenbäck F. Automated image analysis of proliferating cells in carcinoma of the larynx. Acta Otolaryngol 2003;123:759-66.  Back to cited text no. 18
    
19.
Caruntu ID, Balan R, Visan C. Quantitative versus qualitative in the analysis of cervical squamous cell carcinoma. Rom J Morphol Embryol 2005;46:149-54.  Back to cited text no. 19
    
20.
Decaestecker C, van Velthoven R, Petein M, Janssen T, Salmon I, Pasteels JL, et al. The use of the decision tree technique and image cytometry to characterize aggressiveness in World Health Organization (WHO) grade II superficial transitional cell carcinomas of the bladder. J Pathol 1996;178:274-83.  Back to cited text no. 20
    
21.
Petein M, Michel P, van Velthoven R, Pasteels JL, Brawer MK, Davis JR, et al. Morphonuclear relationship between prostatic intraepithelial neoplasia and cancers as assessed by digital cell image analysis. Am J Clin Pathol 1991;96:628-34.  Back to cited text no. 21
    
22.
Rodríguez Sanjuán JC, Val Bernal F, Blanco García C, García-Castrillo Riesgo L. Nuclear morphometry lacks prognostic value in squamous cell carcinoma of the oesophagus. Histol Histopathol 1993;8:505-8.  Back to cited text no. 22
    
23.
Bernardi Fdel C, Capelozzi VL, Takagaki TY, Younes RN, Saldiva PH. Usefulness of morphometric evaluation of histopathologic slides in predicting long-term outcome of patients with squamous cell carcinoma of the lung. A preliminary report. Chest 1995;107:614-20.  Back to cited text no. 23
    
24.
Raju Ragavendra T, Rammanohar M, Sowmya K. Morphometric computer-assisted image analysis of oral epithelial cells in normal epithelium and leukoplakia. J Oral Pathol Med 2010;39:149-54.  Back to cited text no. 24
    
25.
Shabana AH, el-Labban NG, Lee KW. Morphometric analysis of basal cell layer in oral premalignant white lesions and squamous cell carcinoma. J Clin Pathol 1987;40:454-8.  Back to cited text no. 25
    
26.
Shabana AH, el-Labban NG, Lee KW, Kramer IR. Morphometric analysis of suprabasal cells in oral white lesions. J Clin Pathol 1989;42:264-70.  Back to cited text no. 26
    
27.
Kinoshita Y, Inoue S, Honma Y, Shimura K. Diagnostic significance of nuclear DNA content and nuclear area in oral hyperplasia, dysplasia, and carcinoma. J Oral Maxillofac Surg 1992;50:728-33.  Back to cited text no. 27
    
28.
Hegde V. Cytomorphometric analysis of squames from oral premalignant and malignant lesions. J Clin Exp Dent 2011;3:e441-4.  Back to cited text no. 28
    
29.
Nandini DB, Subramanyam RV. Nuclear features in oral squamous cell carcinoma: A computer-assisted microscopic study. J Oral Maxillofac Pathol 2011;15:177-81.  Back to cited text no. 29
  [Full text]  
30.
Sunitha B, Kiran Kumar K, Hallikeri K, Rekha K. Morphometric analysis of nuclear changes in invasive tumor front of squamous cell carcinoma. J Orofac Sci 2010;2:9-12.  Back to cited text no. 30
  [Full text]  
31.
Bànkfalvi A, Piffkò J. Prognostic and predictive factors in oral cancer: The role of the invasive tumour front. J Oral Pathol Med 2000;29:291-8.  Back to cited text no. 31
    
32.
Piffkò J, Bànkfalvi A, Ofner D, Bryne M, Rasch D, Joos U, et al. Prognostic value of histobiological factors (malignancy grading and AgNOR content) assessed at the invasive tumour front of oral squamous cell carcinomas. Br J Cancer 1997;75:1543-6.  Back to cited text no. 32
    
33.
Chang YC, Nieh S, Chen SF, Jao SW, Lin YL, Fu E. Invasive pattern grading score designed as an independent prognostic indicator in oral squamous cell carcinoma. Histopathology 2010;57:295-303.  Back to cited text no. 33
    
34.
Hande AH, Chaudhary MS. Cytomorphometric analysis of buccal mucosa of tobacco chewers. Rom J Morphol Embryol 2010;51:527-32.  Back to cited text no. 34
    
35.
Cotran RS, Kumar V, Collins T. Robbins Pathologic Basis of Disease. 6th ed. India: W.B. Saunders Company Elsevier Science; 2003. p. 260-326.  Back to cited text no. 35
    
36.
Sarkar A. Biology of Cancer; Cancer Cells. New Delhi: Discovery Publishing House Pvt. Limited; 2009. p. 34-9.  Back to cited text no. 36
    
37.
Tan PH, Goh BB, Chiang G, Bay BH. Correlation of nuclear morphometry with pathologic parameters in ductal carcinoma in situ of the breast. Mod Pathol 2001;14:937-41.  Back to cited text no. 37
    
38.
Boysen M, Reith A. Discrimination of various epithelia by simple morphometric evaluation of the basal cell layer. A light microscopic analysis of pseudostratified, metaplastic and dysplastic nasal epithelium in nickel workers. Virchows Arch B Cell Pathol Incl Mol Pathol 1983;42:173-84.  Back to cited text no. 38
    
39.
Rich AM, Nataatmadja MI, Reade PC. Basal cell nuclear size in experimental oral mucosal carcinogenesis. Br J Cancer 1991;64:96-8.  Back to cited text no. 39
    
40.
Natarajan S, Mahajan S, Boaz K, George T. Morphometric analysis of nuclear features and volume – Corrected mitotic index in the prognosis of oral squamous cell carcinoma. Oral Sci Int 2009;6:85-94.  Back to cited text no. 40
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  >Abstract>Introduction>Materials and Me...>Results>Discussion>Conclusion>Article Figures>Article Tables
  In this article
>References

 Article Access Statistics
    Viewed1354    
    Printed70    
    Emailed0    
    PDF Downloaded127    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]