Sandhya I

Abstract

Introduction: Abnormal uterine bleeding (AUB) is one of the commonest symptom with which the perimenopausal female visits the gynaecologist accounting for over 70% of all gynecological consultations in that age group. The clinical presentation of AUB can range anywhere menorrhagia, polymenorrhea, polymenorrhagia, metrorrhagia, and menometrorrhagia. Though biopsy is the gold standard it is an invasive procedure and hence often an Ultrasound is used to evaluate the pathology of the endometrium routinely hence, we decided to study the accuracy between radiological ET thickened and its usefulness in detecting endometrial pathology. Materials and Methods: This study was carried out in the Department of Pathology at AJIMS, Mangalore for a period of 2 years. The sample included endometrial biopies and hysterectomy specimens of perimenopausal women for AUB. The ultrasonographic findings and Histopathological (HPE) reports were analysed. Results: Among 101 cases for AUB, 67 cases were diagnosed as non secretory endometrium. Out of these 67 cases, 49 cases were associated with fibroids. Out of the rest of the AUB cases, 31 of them were diagnosed to have endometrial hyperplasia and 3 cases were diagnosed to have endometrial carcinoma. USG thickness of 17(54%) out of 31 endometrial hyperplasia cases were abnormal. Conclusion: Radiological and pathological evaluation were concordant with diagnosis of AUB associated with fibroids. However only 54% of the endometrial hyperplasia were found to have abnormal endometrial thickness. Radiological evaluation of endometrial thickness is not concordant in 46 % of the cases. This implies that histopathological examination is gold standard diagnostic tool for endometrial abnormalities in perimenopausal women.   Keywords : Abnormal uterine bleeding, Endometrium

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Background: Pigmented lesions can be close mimickers of melanoma and clinically challenging to diagnose. These can be melanocytic or non-melanocytic pigmented disorders. Pigmented lesions are close mimickers of melanoma and histopathology is a cornerstone for diagnosing these lesions. Aims and Objectives: 1. To study the histomorphological patterns of pigmented lesions of the skin; 2. To categorise and differentiate pigmented lesions from melanoma based on histomorphology. Settings and Design: A total of 70 histologically diagnosed cases of pigmented lesions of the skin were retrospectively studied from January 2018 to December 2019 in department of Pathology, of a Tertiary care center, Mangalore (India). Materials and Methods: Clinically suspicious skin lesions were taken up for the study. Sections from the skin punch biopsies and wide excision of the lesion were processed, stained with Hematoxylin and Eosin stain and studied for its histomorphological features. Results: Out of the 70 cases studied, 22 cases were melanocytic lesions including 12 cases of Malignant melanoma (17.1%), Benign Naevi- 10 cases (14.2%) and 48 cases were non-melanocytic lesions including Lichen planus- 30 cases (42%), Seborrheic keratosis- 10 cases (14.3%), Basal cell carcinoma- 8 cases (11.4%). Conclusion: The pigmented lesions are categorised into melanocytic and non melanocytic lesions for a better understanding. Among the Melanocytic lesions, our study witnessed predominantly cutaneous melanoma. And in non melanocytic lesions lichen planus predominated. Keywords: Melanoma, Naevi, Seborrhoeic keratosis, Basal cell carcinoma.

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Introduction: Ki67 labeling index (LI) for breast carcinoma is essential for the therapy. It is done by visual assessment under the microscope which is subjective, hence has limitations of inter-observer variability. A standardized method for evaluating Ki67 LI is necessary due to reduce subjectivity and improve precision. Hence automated Digital Image Analysis (DIA) has been attempted as one of the potential methods for evaluating Ki67 index. Materials and Methods: 48 cases of invasive breast carcinoma were included in this study. Ki67 immunostaining was carried out on paraffin embedded sections of all cases. Visual assessment (VA) of Ki67 index was carried out and images of Ki67 stained slides were obtained under a magnification of 40X. The mean value of two observers was considered as final visual assessment scores. The images were processed using Tissue Quant software to pick up positively stained areas. The area and count of the positively stained regions were obtained. Statistical analysis by calculating kappa value was performed to check the agreement between DIA and visual assessment. Results: Out of 48 cases, 40 cases showed substantial agreement between DIA and visual analysis established by calculating kappa value (0.636). Conclusion: DIA is an emerging and competitive alternative for biomarker evaluation in breast cancer and can be effectively put in use for clinical practice to obtain precise results. Keywords: Ki67, Digital Image Analysis, Breast cancer.

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