Human breast duct anatomy, the ‘sick lobe’ hypothesis and intraductal approaches to breast cancer

Abstract

Information about central and peripheral duct anatomy is a requirement for developing intraductal approaches to human breast cancer, but remains sparse. This study looks at the acquisition and digital modelling of data describing breast duct branching from thick ('subgross') sections using data structures from the neurosciences, and at high-throughput imaging of duct anatomy in the nipple. The branching of a large breast duct system was modelled using data extracted from cleared and stained 2 mm 'subgross' sections of an autopsy breast using a public-domain neuron modelling program (CVAPP), and episcopic fluorescence image capture (EFIC) was used to collect a stack of 1100 autofluorescence images of ducts in a mastectomy nipple. The duct skeleton was captured in 440 line segments with some pruning of terminal ducts. Extracting this data manually in a usable form was, however, laborious and error prone, emphasising the need for improved morphological informatics. EFIC captured anatomical detail and subsequent 3D reconstruction was consistent with the distinction between 'type A' and 'type B' nipple ducts proposed by Going and Moffat (J Pathol 203: 538-544, 2004). Whole-lobe duct modelling and EFIC reveal central and peripheral duct anatomy in human breast. Such knowledge is required for understanding normal breast development, the growth of cancer precursors, and for developing the intraductal approach to breast cancer.