Rahul Saxena Professor, Department of Biochemistry, School of Allied Health Sciences, Sharda Hospital, Sharda University, Greater Noida, Uttar Pradesh, India
Singh Aryan Joseph Student, 3rd semester, MBBS, Samarkand State Medical University, Samarkand, Uzbekistan
Ajit Pal Singh Associate Professor, Department of Medical Lab Technology, School of Allied Health and Sciences, Galgotias University, Greater Noida, Uttar Pradesh, India
Suyash Saxena Associate Professor, Department of Biochemistry, SSAHS, Sharda University, Greater Noida, Uttar Pradesh, India
Address for correspondence: Rahul Saxena, Professor, Department of Biochemistry, School of Allied Health Sciences, Sharda Hospital, Sharda University, Greater Noida, Uttar Pradesh, India E-mail: rahul.saxena@sharda.ac.in
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Singh Aryan Joseph, Ajit Pal Singh, Rahul Saxena et. al, Histopathology in Disease Diagnosis: Interpreting Cellular Patterns. J ENT Allied Sci 2026; 11(1): 11–27.
Timeline
Received : May 11, 2026
Accepted : June 17, 2026
Published : June 30, 2026
Abstract
Histopathology, the microscopic examination of tissues and cells, is fundamental to illness diagnosis as it facilitates intricate visualisation of cellular and tissue structure. The evaluation of cellular morphology and structural patterns
is essential for differentiating benign from malignant tumours, identifying infectious agents, and characterising inflammatory and autoimmune disorders. Improvements in histopathological methods, especially immunohistochemistry
and molecular pathology, have markedly increased diagnosis accuracy by enabling the identification of specific protein markers and genetic changes linked to certain diseases. An in-depth assessment of critical cellular processes, including
differentiation, proliferation rates, apoptosis, and metastatic capability, yields significant insights into disease progression, prognosis, and therapy efficacy. These characteristics are crucial for directing clinical decision-making and formulating
focused treatment regimens. Moreover, emerging technologies such as digital pathology and artificial intelligence are revolutionising the sector by enhancing diagnostic speed, standardisation, and accuracy, while facilitating extensive data
analysis and pattern identification. The amalgamation of conventional microscopy with sophisticated diagnostic instruments has broadened the scope and significance of histopathology, rendering it an essential element of contemporary medicine. Histopathology enables correct interpretation of intricate cellular patterns, hence
aiding precise illness diagnosis and enhancing personalised patient care and clinical outcomes across various conditions.
References
1. Singh, A. P., Saxena, R., & Saxena, S. (2025). Advancements in Cytopathology: New Diagnostic Insights via Molecular and Cellular Analysis. Journal of Biochemistry International, 12(1), 8-32.
2. Mansour, M. R., Ashour, N. A., Gaballah, A. M., Elzoghby, Y. E., Elbatawy, R. M., Shoraba, M., & Shoulah, S. (2025). Comprehensive histopathological and immunohistochemical insights into wound healing from cellular dynamics to translational applications. Advanced Analytical Pathology, 1, 64-83.
3. Wasinger, G., Koeller, M. C., & Compérat, E. (2025).Pathologyintheartificialintelligenceera: practical insights for immunohistochemistry and molecular pathology. Diagnostic Histopathology.
4. kumar Sah, A., Agarwal, S., Abbas, A. M., Shalabi, M. G., Prabhakar, P. K., Elshaikh, R. H., ... & Choudhary, R. K. (2025). Advances in Image Processing and Pattern Recognition in Cancer Detection, Prediction, Diagnosis, and Prognosis.
5. Ali, M., Benfante, V., Basirinia, G., Alongi, P., Sperandeo, A., Quattrocchi, A., ... & Comelli, A. (2025). Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues. Journal of Imaging, 11(2), 59.
6. Abbasi, P., Zeeshan, N., Javed, S., Shah, B. M., & Qazi, M. M. (2026). Role of Histopathology in Early Cancer Detection: Evaluating Cellular Changes, Tumor Microenvironment, and Diagnostic Precision Improvements. Pakistan Journal of Medical & Cardiological Review, 5(2), 322-243.
7. Mansor, S. F., Roslan, M. N. F., Dzulkarnain, S. M. H., Rahim, N. A., Azman, N. A., & Mahyudin, N. F. (2026). Artificial intelligence in breast cancer diagnosis through histopathology and biomarker detection: a scoping review. Biomedical Research and Therapy, 13(3), 8383-8398.
8. Quinn, C., Tan, P. H., Allison, K. H., Brogi, E., Lakhani, S. R., Schnitt, S. J., ... & Tse, G. (2026). World Health Organization classification of tumours of the breast 6th edition 2026. Histopathology.
9. de Almeida, A. L. T., Dos Santos, A. B. G., & Barreto-Vieira, D. F. (2026). Cracking the Code: Computational Image Analysis Tools for Histopathological and Morphometric Insights. Journal of Imaging, 12(4), 173.
10. Guedes, J., Woldmar, N., Szasz, A. M., Wieslander, E., Pawłowski, K., Horvatovich, P., ... & Gil, J. (2025). A perspective on integrating digital pathology, proteomics, clinical data and AI analytics in cancer research. Journal of proteomics, 105493.
11. Chornenkyy, Y., Vyas, M., & Deshpande, V. (2026). The future is now: advancing p53 immunohistochemistry in Barrett’s oesophagus and its implication for the everyday pathologist. Histopathology, 88(2), 380-401.
12. Liu, T., Huang, T., Ding, T., Wu, H., Humphrey, P., Perincheri, S., ... & Zhao, H. (2026). Leveraging multi-modal foundation models for analysing spatial multi-omic and histopathology data. Nature Biomedical Engineering, 1-18.
13. Salmanpour, M. R., Piri, S. M., Mehrnia, S. S., Shariftabrizi, A., Allahmoradi, M., Manem, V. S., ... & Hacihaliloglu, I. (2026). Pathobiological Dictionary Defining Pathomics and Texture Features: Addressing Understandable AI Issues in Personalized Liver Cancer; Dictionary Version LCP1. 0. Journal of imaging informatics in medicine, 1-29.
14. Nampalliwar, A., Ambirwar, S. P., Khandale, S. N., Sasane, P. U., Chavan, S. S., & Sinha, C. P. (2026). Pathological lung tissue changes in common infectious diseases. Bioinformation, 22(1), 529.
15. Zhang, H., Huang, Q., Shang, B., Su, G., & Tu, H. (2026). Deep learning-driven recognition of panoramic tumor microenvironment features in H&E sections and its application. Journal for Immunotherapy of Cancer, 14(4), e014429.
16. Hassan, Y. M., Mohamed, A. S., Hassan, Y. M., Shalaby, A. K., & El-Sayed, W. M. (2026). Advancing biological imaging: computational techniques, AI, and bioinformatics in
18. Bohra, N., Agarwal, R., Ali, S., Kumar, V., Sharma, A., & Riyaz, N. (2026). Dermatoscopy in Hansen’s Disease and Its Correlation with Clinical Spectrum and Histopathology: A Narrative Review. Journal of Chemical Health Risks, 16(1), 1252.
19. Rammal, R., Din, A. M. U., & Alam, T. (2026). Revolutionizing dermatopathology using AI in skin diagnostics: scoping review. Frontiers in Medicine, 13, 1614681.
20. Meeradevi, Maria Rufina, P., Prathik, B., Parthasarathy, C. S., Janya, V., & Mandava, N. R. (2025, September). PathoVision: Multimodal Deep Learning for Advancing Pathology ImagingwithExplainableArtificialIntelligence. In World Conference on Information Systems for Business Management (pp. 276-289). Cham: Springer Nature Switzerland.
21. Al-Raeei, M. (2026). The Applications of Artificial Intelligence in the Diagnosis and Treatment of Diseases in Soft Tissue: From Healthcare to Future Insights. Exploratory Research and Hypothesis in Medicine, 11(1).
22. Bisht, H., Beg, A., Jit, B., Kumar, S., & Sharma, A. (2026). Harnessing Deep Learning for Histopathological Subtyping of Ovarian Cancer: The Role of NOTCH3. International
23. Saha, P., Yasmin, A., Jha, R., Passi, A., Kaur, M., Jindal, S., ... & Goyal, K. (2026). Integrative approaches in lung cancer diagnosis: bridging molecular biomarkers and AI driven imaging. Biomarkers, 1-31.
24. Singh, A. P., Saxena, R., Saxena, S., Maurya, N. K., & Kumar, U. (2025). Malignant Transformation In Vitro by Oncogenic Viruses. In Viral Oncology (pp. 300-310). CRC Press.
25. Singh, A. P., Saxena, R., Saxena, S., & Maurya, N. K. (2024). Unveiling the ocean’s arsenal: Successful integration of marine metabolites into disease management. Uttar Pradesh Journal of Zoology, 45(13), 170-188.
26. Saxena, S., Saxena, R., & Singh, A. P. (2026). Reliability in healthcare systems. In Reliability Analysis and Modeling for Complex Systems (pp. 119-132). Elsevier.
27. Carletti, F., Maggi, M., Fazekas, T., Rajwa, P., Nicoletti, R., Olivier, J., ... & EAU-YAU Prostate Cancer Working Party. (2026). Diagnostic accuracy of multiparametric MRI for detecting unconventional prostate cancer histology: a systematic review and metaanalysis. European radiology, 36(1), 17-29.
28. Khandelwal, A. S., Ansari, M. S., & Aslam, A. (2026). Multimodal Fusion of Histopathology Images and Electronic Health Records for Early Breast Cancer Diagnosis. arXiv preprint arXiv:2604.17122.
29. Zaizen, Y., Saito-Koyama, R., Okudela, K., Terasaki, Y., Tanaka, T., Tabata, K., ... & Fukuoka, J. (2026). A proposed pathological diagnosis flowchart for adult interstitial lung disease with transbronchial lung cryobiopsy: Position paper from the Japanese research group on diffuse lung disease. Respiratory Investigation, 64(2), 101393.
30. Shenk, M. E. R., Meng, Z., & Scribner, J. (2026). Clues in the corneum: enhancing the diagnosis of inflammatory dermatoses. Diagnostic Histopathology
Data Sharing Statement
There are no additional data available. All raw data and code are available upon request.
Funding
This research received no funding.
Author Contributions
All authors contributed significantly to the work and approve its publication.
Ethics Declaration
This article does not involve any human or animal subjects, and therefore does not require ethics approval.
Acknowledgements
We would like to express our gratitude to the patients, their families, and all those who have contributed to this study.
Conflicts of Interest
No conflicts of interest in this work.
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Cite this article
Singh Aryan Joseph, Ajit Pal Singh, Rahul Saxena et. al, Histopathology in Disease Diagnosis: Interpreting Cellular Patterns. J ENT Allied Sci 2026; 11(1): 11–27.
This license enables
reusers to distribute, remix, adapt, and build upon the material in any medium
or format for noncommercial purposes only, and only so long as attribution is
given to the creator
This license enables
reusers to distribute, remix, adapt, and build upon the material in any medium
or format for noncommercial purposes only, and only so long as attribution is
given to the creator