Aims and objectives: To build an artificial neural network (ANN) model for the detection of carcinoma in effusion cytology.Materials and methods: We selected a total of 114 effusion cytology cases consisting of 57 each benign and malignant case. In all these cases, detailed cytological features, image morphometric data, densitometric data, and chromatin textural data were collected. Based on these data, we made a back propagation ANN model for diagnosing malignancy in effusion cytology. This network was designed as 25-2-1 (input nodes-hidden nodes-output node). Online back propagation method was applied for training the network. The training of the network was continued until the network error was reduced to 0.000654. Simultaneously, we also performed logistic regression (
The aim of this study is to compare micronucleus assay in buccal smear of breast carcinoma patients versus normal benign cases as control group. In this prospective study, we selected a total 32 patients of carcinoma of breast and 49 patients of benign breast lesions diagnosed in fine needle aspiration cytology (FNAC). Acridine orange stain was done on buccal smears of these cases and micronucleus (MN) scoring was performed in 40× 0bjective in a fluorescent microscope. The MN score was expressed as positivity per 1,000 cells. The MN scoring in buccal smear was compared in malignant and benign breast cases. In fluorescence microscope, the micronucleus was detected as round orange shaped small intracytoplasmic structure around the nucleus. The mean MN scores in buccal smears of benign and carcinoma cases were 0.5014 ± 0.45768 and 2.1938 ± 1.08656 cases respectively. Independent sample Student's t test showed significantly high MN score in buccal smear of the cancer patients (P < 0.001). Micronucleated cells are significantly increased in buccal cells of the breast carcinoma cases. The increased number of MN in buccal smears raises the possibility that the genetic damage in breast cancer patients is generalized. In future, MN scoring could be used as biomonitoring of DNA damage and in early detection of high risk cases of carcinoma of breast.
Introduction We evaluated the role of simultaneous use of multiple antibodies in flow cytometry (FCM) to detect metastatic carcinomas in effusion samples. Methods Cytological examination of 75 successive cases of effusion samples was performed. There were 48 peritoneal, 26 pleural and one pericardial fluid. Multi‐coloured FCM examination was undertaken using a cocktail of CD45, CD14 and epithelial cell adhesion molecule (EpCAM), antibodies tagged with different fluorochromes. The percentage of EpCAM positivity was calculated in the CD45 and CD14 dual negative population by selective gating. The EpCAM value was correlated with the cytological findings, follow‐up data and MOC‐31 immunostaining. Results There were 20 benign, 35 malignant and 20 atypical cases diagnosed on cytomorphology. The primary sources of carcinomas were mainly from the ovary, followed by lung, gall bladder, intestine and other areas. Out of 20 cytologically benign cases, there were two malignant cases on the final follow‐up, and EpCAM on FCM picked up all 18 benign cases and one malignant case. Out of 35 cytologically detected malignant cases, EpCAM picked up 32 malignant cases. The EpCAM detected 15/18 malignant and both benign cases out of 20 cytological atypical cases. EpCAM antibody by FCM showed 87% sensitivity, 100% specificity, 100% positive predictive value and 74% negative predictive value. Conclusion This comprehensive study highlights the potential use of multi‐coloured FCM along with cytological examination to diagnose metastatic carcinoma in effusion samples. Multi‐coloured FCM is rapid and quantitative and is helpful in atypical cases.
<b><i>Background:</i></b> Cell blocks (CBs) are an essential adjunct in cytopathology practice. The aim of this study was to compare 2 techniques of CB preparation – plasma thrombin (PT) method with sodium alginate (SA) method for overall cellularity, morphological preservation, obscuring artefacts, immunocytochemistry (ICC), suitability for molecular analysis, and cost of preparation. <b><i>Design:</i></b> A total of 80 fine-needle aspirates from various sites and serous effusion samples were included. Of these cases, by random selection, 40 each were prepared by PT method and SA methods, respectively. The haematoxylin-eosin-stained sections from the formalin-fixed, paraffin-embedded CBs from both methods were evaluated in a blinded fashion by 2 cytopathologists and scored for cellularity, artefacts, and morphological preservation and analysed by χ<sup>2</sup> test with Yates correction. We evaluated 6 cases from each method by ICC for a range of membrane, cytoplasmic and nuclear marker expression. DNA was extracted from four cases to evaluate their utility for molecular analysis. <b><i>Results:</i></b> CB sections from PT and SA techniques showed comparable cellularity and excellent cytomorphological preservation. Blue gel-like artefacts were common in the SA technique but did not interfere with morphological evaluation. ICC staining results were also similar. DNA yield and utility for PCR were also comparable. The SA-CB cost half that of PT-CB (USD 0.4 vs. USD 1). <b><i>Conclusion:</i></b> SA technique of CB preparation is an excellent low-cost alternative to PT method for CB preparation.
The rapid Pap technique is a cost-effective alternative to conventional Pap which also saves time and provides good staining quality without compromising the diagnostic interpretation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.