Role of Nuclear Morphometry in The Diagnosis of Various Breast Lesions By Fine Needle Aspiration Cytology- A Study of Diagnostic Accuracy
Year: 2024
Type: article
Abstract: Introduction The Nuclear Morphometric Study can improve. During the past several years, it has been well-established that several clinical, cytological and histopathological variables are helpful in predicting the clinical outcome of cancer patients. Objectives 1. To study the Nuclear Morphometric parameters of the benign and malignant breast FNA aspirates 2. To determine suitable cutoff values differentiating benign and malignant in case of nuclear parameters with significant difference. 3. To study correlation of nuclear parameters with cytological grades Materials and Methods Nuclear Morphometric parameters (MAJX-Major Axis ,MINX-Minor Axis, NAR-Nuclear Aspect Ratio, NA- Nuclear Area, NP- Nuclear Perimeter) study on 50 histopathologicaly proven cases of both benign and malignant breast lesions each. Nuclear Morphometric parameters were evaluated on FNAC slides using Digital Image analyzing software. Appropriate statistical tests where applied wherever necessary and P value of less than 0.05 was considered for significant difference. Receiver Operating Characteristics (ROC) curve between sensitivity (true positive) and 1-specificity (false negative) was plotted to determine the optimal cut-off of various nuclear parameters Results -The nuclear parameters showed a significant difference. All nuclear parameters showed positive correlation with their variability. Cut-off values with sensitivity=1 for differentiation between the benign and malignant cases were MAJX>5.6µmicron(specificity =1), MINX>4.6µmicron(specificity=0.99),NA>88.98µmicron²(specificity=1), NP>33.67µmicron(specificity =1) Conclusion Nuclear Morphometric analysis along with routine FNAC proves very helpful in further grading and appropriate management of the patient. Nuclear Morphometry approach overcomes interobserver variability &can be gainfully exploited in the diagnosis of breast carcinoma Thus, Computerized nuclear morphometry is an efficient objective Tool to supplement the subjective FNAC, improving the diagnostic capabilities of FNAC
Author: International Journal of Medical Science and Innovative Research (IJMSIR)
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W6949667417
FWCI:
Cites:
Cited by:
Related to: