Abstract
Aims
Standardised diagnostic criteria in breast pathology primarily guide classification rather than real-world decision-making in borderline or context-dependent scenarios. This study evaluated question-and-answer data from international masterclass cohorts to characterise real-world diagnostic uncertainties, quantify cognitive domain distributions and detail expert decision-making frameworks.
Methods
We analysed a structured dataset of 430 attendee questions collected across five international online Breast Pathology Masterclasses (2022–2026), each attended by over 500 participants. Questions were categorised into thematic and cognitive domains by the lead investigator, followed by a collaborative co-author audit to establish classification consensus. Faculty responses were evaluated to assess reasoning patterns, consensus points and areas of diagnostic variation.
Results
Diagnostic uncertainty clustered within specific recurring clinical challenges, with borderline and grey-zone lesions constituting a primary focus. Threshold-based queries regarding diagnostic boundaries formed the single largest cognitive domain (40%), rather than queries seeking basic entity definitions. Other major clinical domains included biomarker interpretation, radiology–pathology discordance management and core biopsy sampling limitations. Analysis of faculty responses identified a recurring morphology-first, context-integrated and risk-informed approach to diagnostic decision-making. While consensus on foundational diagnostic principles was high, minor variations occurred in setting specific quantitative thresholds and framing diagnostic uncertainty in pathology reports.
Conclusions
These exploratory findings indicate that practical challenges in diagnostic breast pathology frequently arise from boundary determination and contextual ambiguity rather than gaps in established disease classification schemes. Although expert judgement and confidence in managing diagnostic uncertainty develop substantially through experience, educational initiatives may complement experiential learning by making threshold calibration, risk communication and context-dependent reasoning more explicit.