Microscopic image analysis techniques for the morphological characterization of pharmaceutical particles: influence of the software, and the factor algorithms used in the shape factor estimation.

The present report highlights the difficulties of particle shape characterizations of multiparticulate systems obtained using different image analysis techniques. The report describes and discusses a number of shape factors that are widely used in pharmaceutical research. Using photographs of 16 pellets of different shapes, obtained by extrusion-spheronization, we investigated how shape factor estimates vary depending on method of calculation, and among different software packages. The results obtained indicate that the algorithms used (both for estimation of basic dimensions such as perimeter and maximum diameter, and for estimation of shape factors on the basis of these basic dimensions) have marked influences on the shape factor values obtained. These findings suggest that care is required when comparing results obtained using different image analysis programs.

Microscopic image analysis techniques for the morphological characterization of pharmaceutical particles: Influence of process variables.

This study investigated the effects of various process variables on some of the shape factors most widely used in the morphological characterization of pharmaceutical particles (including circularity, aspect ratio, er, and the recently proposed Vr and Vp). After optimization of the illumination system and greyscale thresholds for discrimination of particle background, we evaluated the effects of process variables within the image capture and analysis system, including the image capture device (video or digital camera), image color information (24-bits-per-pixel RGB or 8-bits-per-pixel black and white), file type (JPG or TIFF), and JPG file compression ratio. A key aspect was evaluation of the effect of scaling factor (microm/pixel), dependent on real pixel size and optical magnification, on shape factor estimates. The results obtained indicate that accurate estimation of shape factors requires use of a scaling factor below a certain maximum; however, use of very low scaling factors will mean that the field of view is very small, so that it will contain very few particles, implying a time-consuming increase in the number of images that must be analyzed. Finally, we use statistical procedures to estimate the minimum number of particles that must be analyzed in order to provide accurate estimates of shape factors.

Image analysis of the shape of granulated powder grains.

This study presents and evaluates two new form factors for the characterization of pharmaceutical microparticles using image analysis techniques. The first factor, denoted Vr, is mean percentage variation in radial chord length (for a large number of radial chords drawn at small angular intervals) with respect to mean radial chord length. The second factor, denoted Vp, is percentage deviation of measured perimeter from the perimeter of a circle with radius equal to the mean radial chord length of the particle. Considering both ideal shapes and real pharmaceutical particle populations, these factors are compared with other form factors widely used in pharmaceutical technology. Our results indicate that Vr and Vp allow effective assessment of whether the particles of a given population show pharmaceutically significant deviations from sphericity. The two factors additionally facilitate identification of the basic shapes of particle outlines (notably ellipsoid, rectangular, and irregular). These factors may thus be of value for the characterization and monitoring of pharmaceutical pelleting processes.