Cholangioscopy in the diagnosis and management of cholangiocarcinoma

Table 1 Comparison of the Monaco and Carlos-Robles-Medranda classification systems for digital single-operator cholangioscopy visual diagnosis

	Monaco classification	Carlos-Robles-Medranda classification
Ref.	Sethi et al[35], 2022	Robles-Medranda et al[36], 2018
Primary purpose	Standardize DSOC visual features distinguishing benign vs malignant biliary strictures	Provide a macroscopic classification correlating morphologic and vascular patterns with neoplastic vs non-neoplastic lesions
Key diagnostic parameters	Eight features: (1) Stricture symmetry; (2) Presence of lesion; (3) Mucosal surface; (4) Papillary projections; (5) Ulceration; (6) Abnormal vessels; (7) Scarring; and (8) Pit-pattern	Four morphologic patterns subdivided by vascularity: Non-neoplastic: Villous, polypoid, or inflammatory with regular vascularity; neoplastic: Flat, polypoid, ulcerated, or honeycomb with irregular/spider vascularity
Representative visual cues	Irregular vessels, papillary or nodular mucosa, asymmetric stricture, ulceration, or diffuse scarring	Disrupted vascular network, irregular or spider vessels, loss of normal pit pattern, polypoid or honeycomb architecture
Training/ease of use	Relatively simple checklist (8 binary variables); designed to facilitate teaching and reproducibility among non-experts	Requires detailed morphologic assessment; higher interpretive demand, but integrates vascular evaluation, improving histologic correlation
Diagnostic accuracy	Sensitivity approximately 80%-85%, specificity approximately 90% in expert hands	Sensitivity approximately 96%, specificity approximately 92% for neoplastic lesions
Inter-observer agreement	Moderate agreement overall (κ approximately = 0.31-0.52); improved with experience and structured training	Higher reproducibility - excellent among experts (κ approximately = 0.80-0.83) and substantial among non-experts (κ approximately = 0.65)
Strengths	Simple, reproducible, and suitable for multicenter teaching and video-library scoring; good standardization for visual training modules	Strong histopathologic correlation, incorporates vascular and morphologic features, higher diagnostic performance, and IOA
Limitations	Limited vascular assessment; relies heavily on mucosal pattern recognition; moderate IOA in trainees	More complex and time-consuming; may require advanced image quality and operator expertise
Overall summary	Practical and training-friendly system emphasizing accessibility and reproducibility	Pathology-driven classification offering superior accuracy and inter-observer reliability, but requiring more expertise

DSOC: Digital single-operator cholangioscopy; IOA: Interobserver agreement.