Connective tissue progenitors (CTPs) are defined as the heterogeneous population of tissue resident stem and progenitor cells capable of proliferating and differentiating into connective tissue phenotypes. The prevalence and variation in clonal progeny of CTPs can be characterized using a colony formation assay. However, colony assays do not directly assess the characteristics of the colony founding CTP. We developed a large field of view, time lapse microscopy system with phase contrast and fluorescence capabilities that enables tracking from seeding through colony formation.<p> </p>Cells derived from the trabecular surface of bone were prepared and seeded in an Ibidi-Ph+ chamber slide. Phase contrast images of the slide were obtained every hour using a DMI6000 Leica microscope, 10X objective, and Retiga 2000R camera. Cells were stained using fluorescent antibodies for multiple markers at the time of plating to determine marker expression on seeded cells and re-stained to determine expression on their progeny. Colonies were identified and characterized using automated image processing and quantitative analysis methods. Following colony identification, the time lapse was reversed to identify and characterize the colony founding CTP according to morphology and marker expression. As a representative example, a CD73<sup>+</sup>/CD90<sup>-</sup>/CD105<sup>-</sup> and a CD73<sup>+</sup>/CD90<sup>+</sup>/CD105<sup>-</sup> CTP resulted in a colony with an area of 3720826 microns<sup>2</sup> and percent area expression of 2.98%, 3.62%, and 1.13% for CD73, CD90, and CD105, respectively.<p> </p>This method can be used to study CTPs and other stem and progenitor cell populations to benefit point-of-care methods for assay and isolation in cell based therapies.
We present preliminary results of a study in which Fractal Interpolation Function Models (FIFM) are used to generate a fractal dimension (fd) feature to discriminate between benign and malignant masses on digitized mammograms. The FIFM method identifies boundary segments that are approximately self-affine and can be accurately modeled with multiple fractal interpolation functions (FIF). The fd of a segment is estimated to be the mean of the fds from the FIF models of that segment. An overall fd feature is computed as the mean of multiple segment fds. The statistical approach provides a stability to the overall fd feature. The FIFM feature may be useful in improving the performance of computer-assisted-diagnosis systems.
Deformation and motion of the Mitral Annulus (MA) is closely related to the left ventricular function. Measurement and visualization of the characteristic parameters in 3D will help in understanding the relationship. Data for this study was acquired from patients undergoing transesophageal echocardiographic examination with the transducer aligned along the axis roughly perpendicular to the annuli, and rotated automatically to cover 360 degrees. ECG gated images were acquired at 24 angles for each phase of the cardiac cycle. The annuli hinge points were identified from each echo image and the annuli reconstructed. The parameters measured to characterize the annuli were: (1) area of projection, (2) non- planarity, (3) excursion of annulus centroid, (4) change in the annulus orientation. We validated the method using a wire loop shaped in the form of a saddle and a planar rubber ring imaged in a water bath at different orientations. Four MAs were reconstructed using this method. Two were patients with dilated cardiomyopathy (DCM) and two were patients with normal ventricular function. The change in parameters was measured from systole to diastole. Percentage change in area (29% vs. 16%) and excursion (8 mm vs. 3 mm) were much larger for normals than for patients. While, changes in non-planarity (20%) and orientation (6 deg) were similar. These preliminary results show that MA parameters do reflect the abnormality, and could be used for diagnosis and prognosis of patients with bad ventricles.