A geometric framework for volumetric decision-making in oncoplastic breast-conserving surgery: A mixed methods...

Breast-conserving surgery (BCS) lacks a reproducible, patient-specific framework linking anthropometric and tumour characteristics to guide surgical technique selection. We present a mixed methods development study which develops a volumetric decision-algorithm to inform the feasibility of simple approximation, volume displacement with or without skin envelope reduction or the need for volume replacement.

The optimal tumour resection volume was modelled as a radially-orientated ellipsoid with 1 cm macroscopic margins. Maximum resection volume was determined by modelling breast volume using anthropometric chest-wall measurements and implant configurations. Skin envelope reduction was estimated using reduction in parenchymal surface area. Decision criteria for technique selection (e.g. breast density) were synthesised from systematic review of the oncoplastic literature.

Modelled tumour volume as an ellipsoidal excision in radial long-axis orientation removes 47.6% less volume than a rectangular block excision of identical nominal dimensions. Anthropometric chest-wall data and the median implant projection (p) to diameter (d) ratio (0.478) informed patient-specific maximum resection volume ( [Formula: see text] . When the excision dimension with margins exceeds 30% of the breast base diameter, skin envelope reduction is required. Fatty breasts (ACR density A-B) carry a fourfold higher fat necrosis risk with extensive undermining. NAC-involving procedures that disrupt the fifth anterior intercostal artery perforator (5th AICAP/MICAP) compromise subsequent nipple-sparing mastectomy feasibility. An interactive web-based calculator was developed as a geometric framework for oncoplastic decision-making: https://jameslucocq.shinyapps.io/opbcs-geometric-calculator/ CONCLUSIONS: This framework integrates volumetric thresholds, breast composition, and vascular anatomy into a reproducible patient-specific volumetric decision algorithm to guide oncoplastic technique selection. It aligns with emerging evidence that the clinically meaningful resection-ratio threshold is patient-specific and may be as low as 7%.