Fractal dimensions of breast lesions on cytology smears

In the present study, box-counting fractal dimensions of benign and malignant cells of breast tumors on cytology material were measured and compared. We selected fine-needle aspiration cytology smears of 14 cases of histopathology-proven infiltrating duct carcinomas and 7 cases of fibroadenoma of the breast. Five cells were randomly selected from each case. Box-counting fractal dimensions of all cells were measured with the help of an image cytometer (Leica, Cambridge, UK), using Quantimet 600 software (Leica). In total, 70 malignant cells and 35 benign cells were studied. The mean fractal dimensions of malignant cells and benign cells were 0.9571 +/- 0.1265 and 0.8354 +/- 0.1367, respectively. There was significant difference in the fractal dimension of malignant and benign cells (P = 0.006, Mann-Whitney nonparametric test). The measurement of fractal dimension may be helpful in discriminating malignant from benign cells. This may be another discriminating feature of malignant cells, along with classic image morphometry based on Euclidean geometry.     

Fractal dimension of cell clusters in effusion cytology

In this study, the fractal dimension (FD) of the ball‐like tight clusters of known metastatic adenocarcinoma cells is compared with the tight cell clusters of the benign cells in the effusion fluid to find out the role of FD in differentiating malignant from benign cluster in effusion. A total of 68 and 72 images of cluster of cells from 12 cases of benign and 13 cases of metastatic pleural and peritoneal effusion were studied for FD. The mean FD of the cluster of cells of benign and malignant effusion was 1.4801 ± 0.23260 and 1.7175 ± 0.09006, respectively. Mann–Whitney U‐test showed significant difference of FD between the cell clusters of malignant and benign effusion cases (P < 0.0001). Cytological features along with the measurement of FD of cell clusters in effusion cytology may be helpful in differentiating benign from malignant cases. Diagn. Cytopathol. 2010;38:866–868. © 2010 Wiley‐Liss, Inc.     

Fractal patterns for cells in culture

The present study aims to understand the growth of human malignant tumours in vitro, using the geometry of fractals as a method of analysis. The fractal dimensions of HN-5 and MDCK cell growth patterns have been measured. The first results may suggest the possibility of distinct growth processes characterized by different (time-dependent) effective fractal dimensions for MDCK and HN-5 cells. If this is true, the fractal dimension may yet prove to be a useful discriminant for comparing different diagnostic categories.     

Image analysis of irregularity of cluster shape in cytological diagnosis of breast tumors: cluster analysis with 2D-fractal dimension

To establish diagnostic criteria using comparison of cell cluster shapes, between benign and malignant tumors, breast tumors demonstrating weak cellular atypia in low grade invasive ductal carcinoma (IDC) were compared. Fine-needle aspiration (FNA) specimens of breast tumors were obtained from 37 patients. Among these, 16 were histologically diagnosed as IDC low-grade and the other 21 as benign fibroadenoma (FA). For evaluation, we examined 740 clusters from these 37 FNA specimens. Nine image morphometric parameters were studied, including the cluster area, circumference, maximal length, maximal breadth, ratio of length to breadth, cluster roundness, cluster size, and the edge and distribution image fractal dimensions for cluster analysis. We evaluated the irregularity in cell cluster shape using fractal dimension analysis, and determined the correlation to cluster size. The irregularity in the IDC cluster shape was higher than that in the FA cluster shape. However, six cases (28.5%) of 21 FA clusters showed high fractal dimensions similar to those for IDC. The clusters were classified by cluster analysis into three types: IDC clusters, FA with irregular cluster shape, and FA with no irregular clusters. The average cell cluster area of the FA with irregular shape was found to be about three times larger than that of IDC clusters. When the differential diagnosis between IDC and FA is difficult, it is important to focus on irregularities in the shape and on overall size of the cell clusters. For accurate diagnosis, the cell cluster shape is as important as the individual cellular atypia.     

Comparison of fine-needle aspiration cytology and core biopsy for diagnosis of breast cancer

Both fine-needle aspiration (FNA) cytology and core biopsy are useful in the diagnosis of breast cancer. In order to compare the sensitivities of these procedures, we reviewed 209 patients with breast cancer who had either FNA, core biopsy, or both, and also either mastectomy or lumpectomy. Sensitivities for FNA and core biopsies for diagnosing breast cancer were calculated and compared. Sensitivity for FNA or core biopsies interpreted as either atypical or malignant was 93.8% for FNA and 90.1% for core biopsy (P > 0.05). Sensitivity for FNA or core biopsies interpreted as malignant was 65.4% for FNA and 88.7% for core biopsy (P < 0.0001). Sensitivities of FNA interpreted as either atypical or malignant were 92.4% for FNA performed by pathologists and 100% for FNA by nonpathologists (P > 0.05). Sensitivities of FNA interpreted as malignant were 75.8% for FNA by pathologists and 20.0% for FNA by nonpathologists (P < 0.00001). Both FNA and core biopsies are sensitive procedures for the detection of breast cancer. There was no significant difference between sensitivity of FNA and core biopsies interpreted as either atypia or malignancy, although the sensitivity of core biopsies interpreted as unequivocal malignancy was greater than that of FNA. FNAs performed by pathologists were more sensitive than FNAs performed by nonpathologists in making an unequivocal diagnosis of breast cancer.     

细针吸取细胞学检查对乳腺良性病变的鉴别诊断

目的 :探讨鉴别纤维囊性乳腺病和乳腺纤维腺瘤细针吸取细胞学 (FNAC)的主要细胞形态学指标。方法 :运用Logistic多重回归模型的统计分析方法 ,对 2 2 4例有活检证实的乳腺FNAC的良性病变 (4 8例纤维囊性乳腺病和 176例纤维腺瘤 )的5 4个细胞学指标进行分析 ,指标的评价采用 0～ 3 的分级评价方式。结果 :研究发现 ,最有价值的鉴别指标是细胞量 (P =0 0 0 1) ,次要指标是背景的游离肌上皮细胞量 (P <0 0 5 )。组合细胞量 (2～ 3 )和背景的游离肌上皮细胞量 (2～ 3 )作为联合指标进行评价 ,可将纤维腺瘤的阳性预测价值提高至 93 5 %。结果发现 ,在乳腺FNAC检查中 ,分叶结节状的间质在纤维囊性乳腺病和乳腺纤维腺瘤中的发生率存在明显的差异性。结论 :在乳腺细针吸取细胞学的良性病变中 ,细胞量和背景的游离肌上皮细胞量是鉴别纤维囊性乳腺病和纤维腺瘤的最有价值的细胞形态学指标。分叶结节状的间质是管内型纤维腺瘤的间质的组织形态在FNAC中的表现 ,是诊断纤维腺瘤的特征性指标 ,对诊断纤维腺瘤有重要的意义     

Artificial neural network in breast lesions from fine‐needle aspiration cytology smear

Artificial neural networks (ANNs) are applied in engineering and certain medical fields. ANN has immense potential and is rarely been used in breast lesions. In this present study, we attempted to build up a complete robust back propagation ANN model based on cytomorphological data, morphometric data, nuclear densitometric data, and gray level co‐occurrence matrix (GLCM) of ductal carcinoma and fibroadenomas of breast cases diagnosed on fine‐needle aspiration cytology (FNAC). We selected 52 cases of fibroadenomas and 60 cases of infiltrating ductal carcinoma of breast diagnosed on FNAC by two cytologists. Essential cytological data was quantitated by two independent cytologists (SRM, PD). With the help of Image J software, nuclear morphomeric, densitometric, and GLCM features were measured in all the cases on hematoxylin and eosin‐stained smears. With the available data, an ANN model was built up with the help of Neurointelligence software. The network was designed as 41‐20‐1 (41 input nodes, 20 hidden nodes, 1 output node). The network was trained by the online back propagation algorithm and 500 iterations were done. Learning was adjusted after every iteration. ANN model correctly identified all cases of fibroadenomas and infiltrating carcinomas in the test set. This is one of the first successful composite ANN models of breast carcinomas. This basic model can be used to diagnose the gray zone area of the breast lesions on FNAC. We assume that this model may have far‐reaching implications in future. Diagn. Cytopathol. 2014;42:218–224. © 2013 Wiley Periodicals, Inc.     

Metastatic metaplastic carcinoma of the breast: diagnosis by bronchial brush cytology

Metaplastic carcinoma of the female breast is an uncommon lesion that may metastasize to body sites. To our knowledge, this is the first reported case of pulmonary metastasis diagnosed on bronchial brush cytology. The patient presented with pulmonary symptomatology 1 yr and 3 mo after a left modified radical mastectomy for breast carcinoma. Bronchoscopic examination revealed an endobronchial lesion partially obstructing the bronchus intermedius. Bronchial brush cytology showed the presence of nonkeratinizing squamous tumor cells admixed with a few scattered clusters of tumor cells with glandular features. Histologic review of the original breast lesion showed a metaplastic carcinoma of the breast with a predominant squamous-cell component. Accurate knowledge of a patient's clinical history is necessary to differentiate a second primary lesion from a metastatic one, particularly when the original lesion is so uncommon.     

Fine-needle aspiration cytology vs. core biopsy in the diagnosis of breast lesions

Fine-needle aspiration cytology (FNAC) is an established, highly accurate method for diagnosing breast lesions. However, in recent years there has been increased use of core biopsy (CB) in this setting. The aim of this study was to evaluate the accuracy of FNAC and compare the quality assessment parameters of FNAC and CB in palpable and nonpalpable breast lesions. Data regarding FNAC, CB, and excision biopsy (EB) diagnoses were retrieved from the archives of our department. A total of 4,367 FNAC samples from the years 1999-2001 was reviewed. Of these, corresponding histology results were available for 1,275 lesions, of which 1,248 were primary breast epithelial lesions (788 EB, 199 CB, 261 EB+CB). All cases were analyzed for sensitivity and specificity of FNAC. Cases with both FNAC and CB were compared and quality assessment parameters were calculated using the methodology detailed in the National Health Service Breast Screening Program guidelines. High specificity and sensitivity, as calculated for satisfactory specimens, were achieved with the use of both FNAC and CB. False-positive and false-negative diagnoses were seen in 7/404 (1.7%) and 45/635 (7.1%) of biopsy-proven specimens sampled by FNAC. The corresponding values for CB were 0% and 5.7%, respectively. Inadequate sampling (15.1%) with use of FNAC was particularly seen in collagenous lesions and in submitted specimens sampled by physicians lacking experience with the FNAC procedure. FNAC is a valuable method, although moderately less sensitive than CB. CB is the preferred method for preoperative diagnosis when sampling FNAC provides scarce material and suspicion of a fibrotic and collagenous lesion such as lobular carcinoma and radial scar arises. FNAC is most accurate when experienced cytologists are available and when immediate assessment by professionals is performed for evaluation of material adequacy, so that additional aspirations can be done when needed.     

Fractal Analysis of Contours of Breast Masses in Mammograms

Fractal analysis has been shown to be useful in image processing for characterizing shape and gray-scale complexity. Breast masses present shape and gray-scale characteristics that vary between benign masses and malignant tumors in mammograms. Limited studies have been conducted on the application of fractal analysis specifically for classifying breast masses based on shape. The fractal dimension of the contour of a mass may be computed either directly from the 2-dimensional (2D) contour or from a 1-dimensional (1D) signature derived from the contour. We present a study of four methods to compute the fractal dimension of the contours of breast masses, including the ruler method and the box counting method applied to 1D and 2D representations of the contours. The methods were applied to a data set of 111 contours of breast masses. Receiver operating characteristics (ROC) analysis was performed to assess and compare the performance of fractal dimension and four previously developed shape factors in the classification of breast masses as benign or malignant. Fractal dimension was observed to complement the other shape factors, in particular fractional concavity, in the representation of the complexity of the contours. The combination of fractal dimension with fractional concavity yielded the highest area (A ( z )) under the ROC curve of 0.93; the two measures, on their own, resulted in A ( z ) values of 0.89 and 0.88, respectively.     

Using classification and regression trees,liquid‐based cytology and nuclear morphometry for the discrimination of endometrial lesions

‘The objective of this study is to investigate the potential of classification and regression trees (CARTs) in discriminating benign from malignant endometrial nuclei and lesions. The study was performed on 222 histologically confirmed liquid based cytological smears, specifically: 117 benign cases, 62 malignant cases and 43 hyperplasias with or without atypia. About 100 nuclei were measured from each case using an image analysis system; in total, we collected 22783 nuclei. The nuclei from 50% of the cases (the training set) were used to construct a CART model that was used for knowledge extraction. The nuclei from the remaining 50% of cases (test set) were used to evaluate the stability and performance of the CART on unknown data. Based on the results of the CART for nuclei classification, we propose two classification methods to discriminate benign from malignant cases. The CART model had an overall accuracy for the classification of endometrial nuclei equal to 85%, specificity 90.68%, and sensitivity 72.05%. Both methods for case classification had similar performance: overall accuracy in the range 94–95%, specificity 95%, and sensitivity 91–94%. The results of the proposed system outperform the standard cytological diagnosis of endometrial lesions. This study highlights interesting diagnostic features of endometrial nuclear morphology and provides a new classification approach for endometrial nuclei and cases. The proposed method can be a useful tool for the everyday practice of the cytological laboratory. Diagn. Cytopathol. 2014;42:582–591. © 2013 Wiley Periodicals, Inc.     

A comparison of the use of the 'Tru-Cut' needle and fine needle aspiration cytology in the pre-operative diagnosis of carcinoma of the breast

Two methods of obtaining a pre-operative diagnosis of carcinoma of the breast are compared. Tru-Cut needle biopsy was carried out on 368 consecutive patients with palpable breast lumps, and both Tru-Cut biopsy and fine needle aspiration cytology were performed during part of this study on 163 of the patients. A final histological diagnosis was obtained in each patient, at excision biopsy or mastectomy. There were 278 patients with carcinoma and 90 with benign breast disease. A correct positive diagnosis of carcinoma was made by the Tru-Cut method in 73.5% of cases, but in only 52% of cases by aspiration cytology. More importantly, there were no false positive diagnoses of carcinoma with Tru-Cut biopsy, but five cases of benign breast disease were incorrectly diagnosed as carcinoma by aspiration cytology. It is concluded that Tru-Cut biopsy is sufficiently reliable to be able to proceed direct to mastectomy following a positive diagnosis of carcinoma, in distinction to aspiration cytology with which an unacceptably high number of false positives occurs. The benefits of a pre-operative Tru-Cut biopsy diagnosis are identified.     

Artificial neural network in diagnosis of lobular carcinoma of breast in fine‐needle aspiration cytology

In this study, we applied artificial neural network (ANN) for the diagnosis of lobular carcinoma in fine‐needle aspiration cytology (FNAC) material. We selected a total of 64 cases of histology proven breast lesions consisting of 20 fibroadenomas, 28 infiltrating ductal carcinomas (IDC), and 16 infiltrating lobular carcinomas (ILC). Detailed cytomorphological features were studied on representative Haematoxylin–Eosin (H&E) and May‐Grunwald Giemsa stained slides. Image morphometric analysis was performed on Haematoxylin–Eosin stained smears to study nuclear area, diameter, perimeter, roundness, convex area, and convex perimeter. Both the qualitative cytological features and objective morphometric data were collected and a total of 18 variables were studied. Back propagation ANN was designed and this data were used as input values. ANN network was designed as 34‐17‐3. There were a total of 34 first layers neurons, 17 hidden neurons and three output neurons. The total cases were randomly divided automatically by the program into three groups: training set (40), validation set (8), and test set (16). After the successful training, the program was able to differentiate all the benign and lobular carcinoma cases and majority of the ductal carcinoma cases. In test set, the ANN program successfully classified all the cases of benign, and ILC cases and six of seven IDC cases. A suitably designed ANN may be able to diagnose the lobular carcinoma of breast on FNAC material. ANN is an efficient software program with immense potential. Diagn. Cytopathol. 2013. © 2011 Wiley Periodicals, Inc.     

Fine needle aspiration cytology of breast cancer in women aged 70 years and older

Aims: Elderly breast cancers are associated with a more favourable biological marker profile and higher proportion of specific subtypes, some of which are of low histological grade. We reviewed the fine needle aspiration cytology (FNAC) to assess the cytological characteristics and any clues to assist in the diagnosis. Methods: The aspirates of 140 cancers of various histological types and grades and 39 benign lesions were evaluated for 13 cytological parameters including cellularity of the direct and cytospin smears, epithelial cell clusters, cellular atypism, cytoplasmic features, vacuoles, mitotic figures, presence of myoepithelial cells, single background epithelial cells, the presence of naked nuclei, stromal fragments and necrosis. Results: We found that the presence of background single epithelial cells, atypism of such cells, absence of benign appearing epithelial fragments, nuclear atypism of the epithelial cells within the fragments, presence of moderate amount of cytoplasm of these cells, absence of myoepithelial cells within the cluster, and absence of bipolar nuclei in the background have a strong association with malignancy. Scoring only the presence of single cells in the background, single cell atypism and the absence of bipolar nuclei in a scoring system can differentiate between benign and malignant aspirates with high (>90%) sensitivity and specificity. Conclusions: Assessing the presence of single cells in the background, single cell atypism and the absence of bipolar nuclei facilitates identification of malignancy in the aspiration of breast lesions from elderly patients.     

Role of morphometry in evaluation of cytologically borderline breast lesions: a study of 70 cases

Fine needle aspiration, an accepted minimally invasive diagnostic procedure for breast masses, leads to an indeterminate (borderline) diagnosis in a significant proportion of cases. This study was aimed at evaluation of the utility of image analysis and morphometry in the cytologic assessment of borderline breast cases. A 'study' group of 45 cases (including fibroadenoma, fibrocystic change and ductal carcinoma) and a 'test' group of 25 cytologically borderline cases were included. Nuclei from each of the groups (nuclei of monolayer sheet of fibroadenoma, naked nuclei of fibroadenoma, ductal cells nuclei of fibrocystic change and nuclei of carcinoma) were manually traced and analyzed using self-written image analysis software. Discriminant analysis was done on the 'study' group and the resultant discriminant functions were applied to the 'test' group. The percentage of nuclei correctly classified of the study as well as test group was noted. On step-wise discriminant analysis, various morphometric, textural parameters and color information parameters were selected. Of the original 'study' group, 98.49% of nuclei could be correctly classified. No overlapping of benign and malignant nuclei was observed in the 'study' group. When the resulting functions were tested on the 'test' group, all the cases were correctly classified as benign or malignant (compared with the final histologic diagnosis). This study suggests that application of computerized image analysis to cytologically borderline breast cases can help in the classification of these cases as benign or malignant. This may prevent unnecessary surgery in many of these cases.     

Use of imprint cytology for assessment of surgical margins in lumpectomy specimens of breast cancer patients

In the past several years, breast-conservation therapy has provided an alternative to mastectomy. In order to reduce the subsequent local tumor recurrence, it is critical that all the measures are in place to find the residual foci of occult microscopic tumor at the time of the initial lumpectomy procedure. An accepted method to evaluate the lumpectomy margins for presence of residual tumor is the use of imprint cytology (also called touch-prep), which is assessment of the presence or absence of the tumor cells by cytological preparation. This is a rapid, cost effective, and easy to use procedure with added advantage of saving tissue for permanent sectioning and rendering a definitive diagnosis. In this report, we present our experience using intraoperative imprint cytology for evaluation of the status of lumpectomy specimens in breast cancer patients. The objective of this study was to evaluate the diagnostic accuracy of intraoperative imprint cytology for assessment of surgical resection margins in lumpectomy margins of patients with breast carcinoma. This is a retrospective study of 100 cases of breast lumpectomy specimens, which had undergone intraoperative imprint cytology. The cases were retrieved from the archived files of the University of Florida, Department of Pathology at Shands Jacksonville. The results of intraoperative imprint cytology were compared with the histological findings of the corresponding permanent sections of the same cases as the gold standard. Overall, we reviewed 510 cytology imprint slides, which were obtained from 100 lumpectomy specimens. Among these cases, 37 slides from 22 cases were reported positive and the remaining were negative. Only eight slides from six cases of lumpectomy showed discrepancy between the result of intraoperative imprint cytology and the permanent sections of the same cases. In our study, intraoperative imprint cytology showed a sensitivity of 97%, specificity of 99%, with positive predictive value of 84%, and negative predictive value of 99%. This study demonstrates that intraoperative imprint cytology can be used as a reliable diagnostic procedure for the evaluation of the status of lumpectomy margins in breast cancer patients.