An interactive 3D atlas of sentinel lymph nodes in breast cancer developed using SPECT/CT.

BACKGROUND: The identification and assessment of sentinel lymph nodes (SLNs) in breast cancer is important for optimised patient management. The aim of this study was to develop an interactive 3D breast SLN atlas and to perform statistical analyses of lymphatic drainage patterns and tumour prevalence. METHODS: A total of 861 early-stage breast cancer patients who underwent preoperative lymphoscintigraphy and SPECT/CT were included. Lymphatic drainage and tumour prevalence statistics were computed using Bayesian inference, non-parametric bootstrapping, and regression techniques. Image registration of SPECT/CT to a reference patient CT was carried out on 350 patients, and SLN positions transformed relative to the reference CT. The reference CT was segmented to visualise bones and muscles, and SLN distributions compared with the European Society for Therapeutic Radiology and Oncology (ESTRO) clinical target volumes (CTVs). The SLN atlas and statistical analyses were integrated into a graphical user interface (GUI). RESULTS: Direct lymphatic drainage to the axilla level I (anterior) node field was most common (77.2%), followed by the internal mammary node field (30.4%). Tumour prevalence was highest in the upper outer breast quadrant (22.9%) followed by the retroareolar region (12.8%). The 3D atlas had 765 SLNs from 335 patients, with 33.3-66.7% of axillary SLNs and 25.4% of internal mammary SLNs covered by ESTRO CTVs. CONCLUSION: The interactive 3D atlas effectively displays breast SLN distribution and statistics for a large patient cohort. The atlas is freely available to download and is a valuable educational resource that could be used in future to guide treatment.

High-Resolution Spatiotemporal Quantification of Intestinal Motility With Free-Form Deformation.

OBJECTIVE: To develop a method to quantify strain fields from in vivo intestinal motility recordings that mitigate accumulation of tracking error. METHODS: The deforming geometry of the intestine in video sequences was modeled by a biquadratic B-spline mesh. Green-Lagrange strain fields were computed to quantify the surface deformations. A nonlinear optimization scheme was applied to mitigate the accumulation of tracking error associated with image registration. RESULTS: The optimization scheme maintained the RMS strain error under 1% and reduced the rate of strain error by 97% during synthetic tests. The algorithm was applied to map 64 segmental, 12 longitudinal, and 23 propagating circular contractions in the jejunum. Coordinated activity of the two muscle layers could be identified and the strain fields were able to map and quantify the anisotropic contractions of the intestine. Frequency and velocity were also quantified, from which two types of propagating circular contractions were identified: (i) [Formula: see text] strain contractions that originated spontaneously and propagated at [Formula: see text] mm/s in two pigs, and (ii) cyclic propagating contractions of [Formula: see text] strain occurred at [Formula: see text] cpm and propagated at [Formula: see text] mm/s in a rabbit. CONCLUSION: The algorithm simultaneously mapped the circular, longitudinal activity of the intestine with high spatial resolution and quantified anisotropic contractions and relaxations. SIGNIFICANCE: The proposed algorithm can now be used to define the interactions of muscle layers during motility patterns. It can be integrated with high-resolution bioelectrical recordings to investigate the regulatory mechanisms of motility.