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| ORIGINAL ARTICLE |
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| Year : 2015 | Volume
: 4
| Issue : 1 | Page : 51-55 |
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Diagnostic application of computerised nuclear morphometric image analysis in fine needle aspirates of breast lesions
D Parmar, Nilima Sawke, GK Sawke
Department of Pathology, People's College of Medical Sciences and Research Centre, Bhopal, Madhya Pradesh, India
| Date of Web Publication | 13-Feb-2015 |
Correspondence Address:
G K Sawke
Department of Pathology, People's College of Medical Sciences and Research Centre, Bhopal - 462 010, Madhya Pradesh
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/2278-0521.151409
Background: Alterations in nuclear structure are the indications of cancer diagnosis. This study has thus focused on variation in nuclear morphometry in breast lesions. Aim: The aim of the study is to compare morphometric characteristics of different types of breast lesions and evaluate its utility in differentiating benign against malignant. Study Design: Sixty fine needle aspiration cytology (FNAC) of ethanol fixed samples were obtained and stained with Papanicolou stain. All diagnoses reported were confirmed histopathologically. Nuclear morphometric parameters for free cells in smears were calculated using the ImageJ 1.47 morphometric computer software. Result: The nuclear morphometric parameters including mean nuclear area, perimeter, diameter, long axis, and short axis were found to be statistically significant (ANOVA, P < 0.0001) in differentiating benign and malignant breast aspirates. Conclusion: Nuclear morphometry has been found to be a valuable objective method in differentiating benign and malignant breast lesions, especially in the grey zones, when diagnostic dilemmas are encountered. This study results demonstrate that the size-related parameters (area, perimeter, diameter, long, and short axes) of the nucleus are the most appropriate nuclear morphometric parameters for differentiating between benign lesions and infiltrative ductal carcinoma of the breast. Keywords: Image analysis, fine needle aspiration cytology, morphometry
How to cite this article:
Parmar D, Sawke N, Sawke G K. Diagnostic application of computerised nuclear morphometric image analysis in fine needle aspirates of breast lesions. Saudi J Health Sci 2015;4:51-5 |
How to cite this URL:
Parmar D, Sawke N, Sawke G K. Diagnostic application of computerised nuclear morphometric image analysis in fine needle aspirates of breast lesions. Saudi J Health Sci [serial online] 2015 [cited 2023 Mar 20];4:51-5. Available from: https://www.saudijhealthsci.org/text.asp?2015/4/1/51/151409 |
| Introduction | |  |
Breast carcinoma is the most common malignancy in female population. It is also the leading cause of cancer mortality in the Indian women.
Fine needle aspiration cytology (FNAC) is applied as the primary tool for diagnosis of breast masses. It is an easy, rapid and comparatively minimal invasive and inexpensive procedure for quick diagnosis. However, it is largely a subjective tool. There is always overlap among the precancerous group and frank carcinoma. These grey zone cases in cytology constitute about 8-9%. [1]
The FNAC has been routinely used as a screening test for lumps along with mammography and clinical examination. However, cytological diagnosis is based on subjective evaluation of cellularity and nuclear features like abnormal size, shape, chromatin pattern and mitotic activity etc.
Morphometry is the measurement of various cell parameters microscopically. In the last few decades there have been some studies based on computerised morphometry on benign and malignant cells, which can support the diagnosis in many cases and can improve sensitivity and specificity of diagnosis. [2]
There have been studies on computerised nuclear morphometric analysis, which successfully differentiated between benign and malignant aspirates and correlated significantly with cytologic grades. It has been proved to be an useful objective tool in the diagnosis of atypical ductal hyperplasia (ADH) and ductal carcinoma in situ. [3],[4],[5]
This study was undertaken to study nuclear features in benign and malignant lesions in specimen obtained by fine needle aspiration of breast masses.
| Materials and methods | | |
This study included total 60 cases of FNAC from breast lump in a tertiary level hospital in Bhopal, India. The cases were categorised cytologically into group I - fibroadenoma (FA) and fibrocystic disease (FCD) (37 cases), group II - epithelial hyperplasia with atypia (6 cases) and group III - invasive carcinoma (17 cases). Only those cases which had confirmed histopathological correlation were included in the study. A 640 × 400 pixel digital image was taken by a camera on the microscope with 10× eyepiece and 100× objective. Using the imageJ 1.47 analysis software, morphometric analysis of around 50 nuclei/case was done. Only the free cells without any overlapping were analysed. Cells with overlapping, folding or distorted morphology were excluded from the analysis.
The following nuclear morphometric features were analysed.
- Area was within the outlined nuclear perimeter in fit spline
- Perimeter was measured as the length around the nuclear border in fit spline
- Diameter was the diameter of a circle with the same area as the outlined nucleus
- Longest axis was measured as the longest axis of the best fitting ellipse
- Shortest axis was measured as the shortest axis of the best fitting ellipse.
Following form factors were calculated based on above measured values:
- AR form factor (area divided by ð/4 × longest axis × shortest axis)
- Circularity/PE form factor (4ð × area divided by the square of the perimeter) with a value of 1.0 indicating a perfect circle
- NCI (nuclear contour index) form factor (perimeter divided by the square root of area)
- Contour ratio, the shape factor calculated by using the formula (perimeter) 2/(4ð × area)
- Nuclear roundness [In a circular nucleus, the values of the roundness correspond to 1. If the nucleus is elliptic, the roundness becomes less than 1]
- Solidity: - [Area]/[Convex area]. [6]
Following statistical parameters were calculated for each nuclear feature in each group: Mean, median, range of values, minimum and maximum values, and standard deviation.
The data obtained was statistically analysed and compared for the three groups.
| Results | | |
The sample size was of total 60 cases including 37 cases of FA and FCD (group I), 6 cases of epithelial hyperplasia with atypia (group II) and 17 cases of invasive carcinoma (group III). Age distribution shows maximum number of breast lumps within the age range of 31-40 years with maximum number being in group I (15) followed by group III (6). Age distribution within each group is tabulated in [Table 1].
Cytological features of group I, group II, and group III are summarised in [Figure 1], [Figure 2], and [Figure 3], respectively. | Figure 1: Fibroadenoma: Oil immersion view showing well cohesive sheet of ductal epithelial cells with myoepithelial cells (PAP ×1000)
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 | Figure 2: Atypical hyperplasia: Oil immersion view showing mildly discohesive ductal epithelial cells with mild anisonucleosis and presence of bare nuclei (PAP ×1000)
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 | Figure 3: Invasive carcinoma: Oil immersion view showing discohesive group of ductal epithelial cells with anisonucleosis, hyperchromasia and prominent nucleoli (PAP ×1000)
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The FNAC smears were studied for nuclear morphometric parameters using ImageJ 1.47 image analysis software [Figure 4]. | Figure 4: Nuclear morphometric analysis using Image J1.47 image analysis software
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Nuclear morphometric analysis using ImageJ 1.47 image analysis software showed the results as shown in [Table 2]. | Table 2: Nuclear morphometric analysis using ImageJ 1.47 image analysis software showed the following result
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The parameters included were mean nuclear area (MNA), perimeter, diameter, long axis, short axis, AR form factor, circularity, NCI, contour ratio, round, and solidity for each nucleus respectively. The measured parameters were MNA, perimeter, diameter, long axis, and short axis. The MNA for group I, group II, and group III were 36.89 ± 3.53, 64.97 ± 3.12 and 98.9 ± 19.56. The perimeter of nucleus was found to be 26.69 ± 1.45, 32.78 ± 3.1, and 39.86 ± 2.23 for group I, group II, and group III, respectively. Diameter for group I, group II, and group III were 6.81 ± 0.33, 9.1 ± 0.21, and 11.1 ± 1.07, respectively. The long and short axes were 8.34 ± 0.38 and 6.02 ± 0.33 for group I, 10.71 ± 0.45 and 8.10 ± 0.38 for group II and 13.14 ± 0.99 and 9.83 ± 1.0 for group III, respectively. The calculated parameters were AR form factor, circularity, NCI, contour ratio, round, and solidity. These parameters show form related features of the nucleus.
The measured and calculated parameters were subjected to statistical analysis using one-way analysis of variance (ANOVA), post hoc and found to be statistically significant. The P value for all size-related parameters were statistically significant (P < 0.001) but was not found to be uniformly significant for form related parameters, notably aspect ratio and roundedness (P > 0.001).
| Discussion | | |
Breast carcinoma is the most common tumour and the leading cause of cancer death in women, worldwide. The spectrum of breast lesions that is normal breast to ductal fibroadenoma (FA), to ADH to ductal and lobular carcinomas in situ and to invasive carcinoma has to be identified as they represent sequential from precancerous to frank carcinoma.
Most of our traditional knowledge of diagnostic cytology exists in descriptive terms and only a small amount of such information is available in numeric form. Measurement of morphometric parameters could provide points of references, basic descriptive measures of value and variation, as a basis for checking reproducibility.
This study results demonstrate that the size-related parameters (area, perimeter, diameter, long, and short axes) of the nucleus are the most appropriate nuclear morphometric parameters for differentiating between benign lesions and infiltrative ductal carcinoma of the breast. The relation between size parameters of nuclei and the diagnosis of malignancy was also previously observed by others. [7],[8],[9],[10],[11],[12],[13],[14]
In our study, we used 50% ethanol-fixed smears and Papanicolaou stain; such fixation and stain turned out to be reproducible for morphometric analysis. Studies on air-dried smears stained with May-Grόnwald-Giemsa technique led to cell spreading and resulted in variation in nuclear size. [12],[13],[14] In this study, there was a gradual increase in the nuclear area and perimeter in group I, group II, and group III lesions.
Mean nuclear area is the most studied parameter in nuclear morphometry in the published literature. [2],[14],[15],[16],[17],[18],[19] Our benign cases showed a mean nuclear area <68.09 sq. microns (group I and group II) and malignant ones had a mean nuclear area >79.34 sq. microns.
Our results were in concordance with that of Abdalla Fathi et al. [2] with their mean nuclear area being 64-82 μm 2 for benign cases and 72-163 μm 2 for malignant cases. Abdalla et al. [2] also showed that clearly reduced cohesiveness was associated with larger nuclear size. Wittekind and Schulte in their study showed that perimeter was the most powerful feature to differentiate between benign and malignant breast lesions. [10]
In this study, mean nuclear area, perimeter, diameter, long axis, and short axis were highly significant in differentiating hyperplasia from carcinoma. These parameters were found to be statistically significant (P < 0.0001).
Shape is one of the factors to assess nuclear atypicality. Shape factors have been shown to have prognostic value in breast cancer as proved by Yan et al.[20] He reported that the shape factor that includes short nuclear axis and the long nuclear axis is of value to predict subsequent development of breast cancer among women with benign breast disease.
This study, based on cytology, has brought out the gradual increase in the mean numerical values of the parameters like mean nuclear area, perimeter, diameter, long axis, and short axis from benign (group I) to atypical (group II), and further to invasive carcinoma (group III).
Nuclear form factor, a measure of the regularity of the nuclear perimeter was shown to have predictive value for discriminating benign and malignant conditions as proved by Mapstone and Zakhour. [8]
The grey zones in cytology are around 8.9% as reported by Al-Kaisi. These included technical limitations (4.5%), inexperience of the cytopathologist (2.4%), and overlap of cytological features of benign against malignant (2%). [1] This study explores the possible role of nuclear morphometric analysis to differentiate such grey zone lesions.
In this study, observation of 6 cases of ADH (group II) and 17 cases of carcinoma (group III) could be distinctly classified into the benign and malignant categories, by morphometric parameters, even though these are strictly histological diagnoses. Four cases which had been diagnosed as ADH in cytology, turned out to be carcinoma in histopathology. In these cases, the morphometric findings will help in categorising the grey zone objectively.
In various studies, the clinicopathological features like tumour grade, tumour size, and lymph node status on the histopathology material are analysed and found to be correlated on the basis of morphometric parameters. [10],[16],[20]
In this study, we found the image morphometry, an important quantitative method to add objective measurements to diagnostic assessment and improvement in diagnostic capabilities.
| Conclusion | | |
This study suggests that nuclear image analysis of breast lesions is an important tool for objective pathological analysis and assessment of benign, malignant, and grey zone lesions. Despite the limitation of small sample size, our study indicates that nuclear parameters chiefly area, perimeter, diameter, long and short axes are the most appropriate nuclear parameters for differentiating between benign lesions and infiltrative ductal carcinoma. The use of such an approach will overcome the limitations of inter-observer agreement and improve the diagnostic assessment and capabilities.
| References | | |
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[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2]
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