Automated 5-D analysis of cell migration and interaction in the thymic cortex from time-lapse sequences of 3-D multi-channel multi-photon images

This paper presents automated methods to quantify dynamic phenomena such as cell-cell interactions and cell migration patterns from time-lapse series of multi-channel three-dimensional image stacks of living specimens. Various 5-dimensional (x, y, z, t, λ) images containing dendritic cells (DC), and T-cells or thymocytes in the developing mouse thymic cortex and lymph node were acquired by two-photon laser scanning microscopy (TPLSM). The cells were delineated automatically using a mean-shift clustering algorithm. This enables morphological measurements to be computed. A robust multiple-hypothesis tracking algorithm was used to track thymocytes (the DC were stationary). The tracking data enable dynamic measurements to be computed, including migratory patterns of thymocytes, and duration of thymocyte-DC contacts. Software was developed for efficient inspection, corrective editing, and validation of the automated analysis results. Our software-generated results agreed with manually generated measurements to within 8%.