A STANDARDIZED IAC REPORTING SYSTEM ON BREAST LESIONS IN TERTIARY HEALTH CARE CENTER OF FAISALABAD: A CASE SERIES

Background: International academy of cytology (IAC) has established a structured, comprehensive and standardized coding system to segregate the breast lesions into categorically 5 groups C1-5 (C1-Insufficient, C2-Benign, C3-Equivocal/ open to more than one interpretation, C4- Suspicious & C5- Malignant) to approach a uniform and unanimous diagnostic criterion of reporting on cytology. The aim of our analysis in the case series is to classify our available data of breast lesions into different categories as per IAC classification. Method: All routine FNAC done in the breast clinic of Madina Teaching Hospital from June 2014 to June 2023 were included in the study. Results: A total of 718 cases were included in the study, varying in age from 11 to 69 years. Out of all the FNACs done, the percentage of C1 cases was 0.41 % (3), C2 cases was 62.5% (449), C3 cases was 5.7 % (41), C4 cases was 7.1 % (51) and C5 cases was 24.2% (174) Conclusion: Cytological categorization based on structured reporting system utilized internationally, will augment the diagnostic uniformity amongst medical practitioners and use of FNAC for diagnosing breast lesions can help prevent redundant surgery and strain to the patient.

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Journal
Pakistan Postgraduate Medical Journal
Published
2024-12-04
DOI
https://doi.org/10.51642/ppmj.v35i03.705
Primary Topic
AI in cancer detection
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article
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article

A STANDARDIZED IAC REPORTING SYSTEM ON BREAST LESIONS IN TERTIARY HEALTH CARE CENTER OF FAISALABAD: A CASE SERIES

Faiza Wattoo, Sohaib Riaz, Tabinda Roheen, Farhan Javed et al.
1 links
Pakistan Postgraduate Medical Journal
AI in cancer detection
article

A STANDARDIZED IAC REPORTING SYSTEM ON BREAST LESIONS IN TERTIARY HEALTH CARE CENTER OF FAISALABAD: A CASE SERIES

Faiza Wattoo, Sohaib Riaz, Tabinda Roheen, Farhan Javed, Sadia Ijaz, S. Ilyas
article en

Abstract

Background: International academy of cytology (IAC) has established a structured, comprehensive and standardized coding system to segregate the breast lesions into categorically 5 groups C1-5 (C1-Insufficient, C2-Benign, C3-Equivocal/ open to more than one interpretation, C4- Suspicious & C5- Malignant) to approach a uniform and unanimous diagnostic criterion of reporting on cytology. The aim of our analysis in the case series is to classify our available data of breast lesions into different categories as per IAC classification. Method: All routine FNAC done in the breast clinic of Madina Teaching Hospital from June 2014 to June 2023 were included in the study. Results: A total of 718 cases were included in the study, varying in age from 11 to 69 years. Out of all the FNACs done, the percentage of C1 cases was 0.41 % (3), C2 cases was 62.5% (449), C3 cases was 5.7 % (41), C4 cases was 7.1 % (51) and C5 cases was 24.2% (174) Conclusion: Cytological categorization based on structured reporting system utilized internationally, will augment the diagnostic uniformity amongst medical practitioners and use of FNAC for diagnosing breast lesions can help prevent redundant surgery and strain to the patient.

Pakistan Postgraduate Medical JournalVol. 35(03)
Punjab Medical College (PK), CMH Lahore Medical College and Institute of Dentistry (PK), National University of Sciences and Technology (PK)
Openalex Percentile: Top 73%
AI in cancer detection
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A STANDARDIZED IAC REPORTING SYSTEM ON BREAST LESIONS IN TERTIARY HEALTH CARE CENTER OF FAISALABAD: A CASE SERIES — Faiza Wattoo, Sohaib Riaz, et al. · Pakistan Postgraduate Medical Journal (2024) | TGRS Research Map | TGRS