Abstract:
Background: Anorectal diseases constitute a significant portion of surgical practice
worldwide, affecting quality of life and productivity. Accurate diagnosis is essential for
appropriate management, with proctoscopy being a fundamental diagnostic tool. This study
aimed to evaluate the role of dual lens endo proctoscopy in the diagnosis and management of
anorectal diseases.
Methods: This prospective study was conducted at Shri B.M. Patil Medical College,
Hospital and Research Centre, Vijayapura from April 2023 to January 2025. A total of 384
patients presenting with anorectal symptoms underwent evaluation using dual lens endo
proctoscopy. Demographic data, diagnoses, histopathological findings, and management
approaches were recorded and analysed. The images were utilised for patient counselling,
HPR annotation and to create Image bank for AI based diagnosis of anorectal disease.
Results: The majority of patients were in the 31-40 years age group (27.6%) with a male
predominance (71.4%). Anal fissure (20.3%), Grade 2 hemorrhoids (19.8%), and fistula in
ano (15.6%) were the predominant diagnoses. Management was nearly equally distributed
between conservative (50.5%) and operative (49.5%) approaches, with significant
associations between specific diagnoses and treatment strategies (p<0.001). Gender-specific
patterns in disease distribution were observed (p=0.008), with anal fissures more common in
females and fistula in ano more prevalent in males. In nearly half of operated population,
these images were utilised for HPR annotation by pathologists.
Conclusion: Dual lens endo proctoscopy demonstrated significant utility in the evaluation
of anorectal diseases, offering enhanced visualization that facilitated accurate diagnosis and
appropriate management planning. The demographic and clinical patterns observed largely
aligned with existing literature, with some notable regional variations. The technology's
integration into routine clinical practice appears justified based on its diagnostic advantages,
and for future use in AI based diagnosis of anorectal disease.
