J Pathol Transl Med.  2024 Jan;58(1):43-44. 10.4132/jptm.2023.12.04.

Response to comment on “A stepwise approach to fine needle aspiration cytology of lymph nodes”

Affiliations
  • 1Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, Seoul, Korea
  • 2Department of Pathology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
  • 3Department of Pathology, Inje University Sanggye Paik Hospital, Seoul, Korea
  • 4Department of Pathology, Samkwang Medical Laboratories, Seoul, Korea
  • 5Department of Pathology, Korea Institute of Radiological and Medical Sciences, Seoul, Korea


Reference

References

1. Maffei E, Ciliberti V, Zeppa P, Caputo A. Comment on “A stepwise approach to fine needle aspiration cytology of lymph nodes”. J Pathol Transl Med. 2024; 58:40–2.
2. Chong Y, Park G, Cha HJ, et al. A stepwise approach to fine needle aspiration cytology of lymph nodes. J Pathol Transl Med. 2023; 57:196–207.
3. Al-Abbadi MA, Barroca H, Bode-Lesniewska B, et al. A proposal for the performance, classification, and reporting of lymph node fine-needle aspiration cytopathology: the Sydney system. Acta Cytol. 2020; 64:306–22.
4. Gupta P, Gupta N, Kumar P, et al. Assessment of risk of malignancy by application of the proposed Sydney system for classification and reporting lymph node cytopathology. Cancer Cytopathol. 2021; 129:701–18.
5. Falini B, Martino G, Lazzi S. A comparison of the International Consensus and 5th World Health Organization classifications of mature B-cell lymphomas. Leukemia. 2023; 37:18–34.
6. Caputo A, Ciliberti V, D’Antonio A, et al. Real-world experience with the Sydney System on 1458 cases of lymph node fine needle aspiration cytology. Cytopathology. 2022; 33:166–75.
7. Caputo A, Fraggetta F, Cretella P, et al. Digital examination of LYmph node CYtopathology Using the Sydney system (DELYCYUS): an international, multi-institutional study. Cancer Cytopathol. 2023; 131:679–92.
8. Thakur N, Alam MR, Abdul-Ghafar J, Chong Y. Recent application of artificial intelligence in non-gynecological cancer cytopathology: a systematic review. Cancers (Basel). 2022; 14:3529.
9. Park HS, Chong Y, Lee Y, et al. Deep learning-based computational cytopathologic diagnosis of metastatic breast carcinoma in pleural fluid. Cells. 2023; 12:1847.
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