Purpose:To investigate the ability of magnetic resonance (MR) to monitor radio-frequency (RF) ablation treatments by comparing MR images of thermal lesions to histologically assayed cellular damage. We developed a new methodology using three-dimensional registration for making spatial correlations. Materials and Methods:A low-field, open MRI system was used to guide an ablation probe into rabbit thigh muscle and acquire MR volumes after ablation. After fixation, we sliced and photographed the tissue at 3-mm intervals, using a specially designed apparatus, to obtain a volume of tissue images. Histologic samples were digitized using a video microscopy system. For our three-dimensional registration method, we used the tissue images as the reference, and registered histology and MR images to them using two different computer alignment steps. First, the MR volume was aligned to the volume of tissue images by registering needle fiducials placed near the tissue of interest. Second, we registered the histology images with the tissue images using a two-dimensional warping technique that aligned internal features and the outside boundary of histology and tissue images. Results:The MR and histology images were very well aligned, and registration accuracy, determined from displacement of needle fiducials, was 1.32 Ϯ 0.39 mm (mean Ϯ SD), which compared favorably to the MR voxel dimensions (0.70 mm in-plane and 3.0 mm thick). A preliminary comparison of MR and tissue response showed that the region inside the elliptical hyperintense rim in MR closely corresponds to the region of necrosis as established by histology, with a mean absolute distance between MR and histology boundaries of 1.17 mm, slightly smaller than the mean registration error. The MR region slightly overestimated the region of necrosis, with a mean signed distance between boundaries of 0.85 mm. Conclusion:Our results suggest that our methodology can be used to achieve three-dimensional registration of histology and in vivo MR images. In MR lesion images, the inner border of the hyperintense region corresponds to the border of irreversible cell damage. This is good evidence that during RF ablation treatments, iMRI lesion images can be used for real-time feedback.

We created a method for three-dimensional (3-D) registration of medical images (e.g., magnetic resonance imaging (MRI) or computed tomography) to images of physical tissue sections or to other medical images and evaluated its accuracy. Our method proved valuable for evaluation of animal model experiments on interventional-MRI guided thermal ablation and on a new localized drug delivery system. The method computes an optimum set of rigid body registration parameters by minimization of the Euclidean distances between automatically chosen correspondence points, along manually selected fiducial needle paths, and optional point landmarks, using the iterative closest point algorithm. For numerically simulated experiments, using two needle paths over a range of needle orientations, mean voxel displacement errors depended mostly on needle localization error when the angle between needles was at least 20 degrees. For parameters typical of our in vivo experiments, the mean voxel displacement error was < 0.35 mm. In addition, we determined that the distance objective function was a useful diagnostic for predicting registration quality. To evaluate the registration quality of physical specimens, we computed the misregistration for a needle not considered during the optimization procedure. We registered an ex vivo sheep brain MR volume with another MR volume and tissue section photographs, using various combinations of needle and point landmarks. Mean registration error was always < or = 0.54 mm for MR-to-MR registrations and < or = 0.52 mm for MR to tissue section registrations. We also applied the method to correlate MR volumes of radio-frequency induced thermal ablation lesions with actual tissue destruction. In this case, in vivo rabbit thigh volumes were registered to photographs of ex vivo tissue sections using two needle paths. Mean registration errors were between 0.7 and 1.36 mm over all rabbits, the largest error less than two MR voxel widths. We conclude that our method provides sufficient spatial correspondence to facilitate comparison of 3-D image data with data from gross pathology tissue sections and histology.

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We created a method for three-dimensional registration of medical scanner image volumes to images of physical tissue sections or other volumes, and evaluated its accuracy. The method is applicable for many animal experiments, and we are applying it to evaluate interventional MM imaging ofthermal ablation and to quantify in vivo drug release from a new device for localized, controlled release. The method computes an optimum set of rigid body registration parameters by iterative minimization of the Euclidean distances between automatically generated correspondence points, along manually selected fiducial needle paths, and optional point landmarks. For numerically simulated registrations, using two needle paths over a range of needle orientations, median voxel displacement errors depended only on needle localization error when the angle between needles was at least 1 5 degrees. For parameters typical of our in vivo experiments, the median error was 0. 1 8 mm. In addition, we determined that the distance objective function was a useful diagnostic for predicting registration quality. To evaluate the registration quality of physical specimens, we computed the misregistration for a needle not considered during the optimization procedure. We registered an ex vivo sheep brain MR volume with another MR volume and tissue section photographs, using various combinations of needle and point landmarks. Registration error was always 0.65 mm for MR-to-MR registrations and 0.9 mm for MR to tissue section registrations. We conclude that our method provides sufficient spatial correspondence to facilitate comparison of 3D image data with data from gross pathology tissue sections and histology.

Surface Mount Technology relies on the use of screen or stencil printers for solder paste application. Many systems now incorporate complex vision systems to provide improved accuracy during printing. These systems advertise sub‐mil precision (x1|+3o<0·001 in.) but none provides a method to quantify this precision. With the advent of fine pitch pads [pad pitch ≤0·025 in.), accurate characterisation of the printing machine's capabilities is imperative for a successful manufacturing process. This paper will present a quantitative method with supporting experimental data, for analysing the printing capabilities of the stencilling machine.