The objective of this work was to develop and then validate a stereotactic fiduciary marker system for tumor xenografts in rodents which could be used to co-register magnetic resonance imaging (MRI), PET, tissue histology, autoradiography, and measurements from physiologic probes. A Teflon fiduciary template has been designed which allows the precise insertion of small hollow Teflon rods (0.71 mm diameter) into a tumor. These rods can be visualized by MRI and PET as well as by histology and autoradiography on tissue sections. The methodology has been applied and tested on a rigid phantom, on tissue phantom material, and finally on tumor bearing mice. Image registration has been performed between the MRI and PET images for the rigid Teflon phantom and among MRI, digitized microscopy images of tissue histology, and autoradiograms for both tissue phantom and tumor-bearing mice. A registration accuracy, expressed as the average Euclidean distance between the centers of three fiduciary markers among the registered image sets, of 0.2 +/- 0.06 mm was achieved between MRI and microPET image sets of a rigid Teflon phantom. The fiduciary template allows digitized tissue sections to be co-registered with three-dimensional MRI images with an average accuracy of 0.21 and 0.25 mm for the tissue phantoms and tumor xenografts, respectively. Between histology and autoradiograms, it was 0.19 and 0.21 mm for tissue phantoms and tumor xenografts, respectively. The fiduciary marker system provides a coordinate system with which to correlate information from multiple image types, on a voxel-by-voxel basis, with sub-millimeter accuracy--even among imaging modalities with widely disparate spatial resolution and in the absence of identifiable anatomic landmarks.
Spatial maps of the percentage cellularity in pelvic bone marrow were calculated at a resolution of 15.6 mm3 from six volunteers and 10 patients treated for documented hematologic disease using a three-point Dixon MRI pulse sequence. The percentage cellularity calculation was aided by analyzing a two-dimensional feature space consisting of the apparent water fraction (Wa), and the T2 relaxation time of water (T2w). An extracellular water fraction was assigned to each voxel on the basis of a two-component T2w algorithm. In six cases, the method was compared to results obtained from core biopsies or aspirates of the posterior iliac crest. The results indicate that segmentation schemes that combine high-quality phase-contrast imaging with nuclear relaxation time measurements can potentially identify the true fractional marrow volume occupied by hematopoietic elements in a variety of clinical situations.
Magnetic resonance (MR) imaging is an imaging modality that is used in the management and diagnosis of acute stroke. Common MR imaging techniques such as diffusion weighted imaging (DWI) and apparent diffusion coefficient maps (ADC) are used routinely in the diagnosis of acute infarcts. However, advances in radiology information systems and imaging protocols have led to an overload of image information that can be difficult to manage and time consuming. Automated techniques to assist in the identification of acute ischemic stroke can prove beneficial to 1) the physician by providing a mechanism for early detection and 2) the patient by providing effective stroke therapy at an early stage. We have processed DW images and ADC maps using a novel automated Relative Difference Map (RDM) method that was tailored to the identification and delineation of the stroke region. Results indicate that the technique can delineate regions of acute infarctions on DW images and ADC maps. A formal evaluation of the RDM algorithm was performed by comparing accuracy measurements between 1) expert generated ground truths with the RDM delineated DWI infarcts and 2) RDM delineated DWI infarcts with RDM delineated ADC infarcts. The accuracy measurements indicate that the RDM delineated DWI infarcts are comparable to the expert generated ground truths. The true positive volume fraction value (TPVF), between RDM delineated DWI and ADC infarcts, is nonzero for all cases with an acute infarct while the value for non-acute cases remains zero.
In this work a 5 x 5 mesh dome resonator that has been optimized for functional brain imaging is presented. The resonator was reduced in length and diameter compared with previous versions to reduce sample losses, thus enhancing the signal-to-noise ratio of the acquired data. In addition, a 5 x 5 mesh design was employed, which offered improved axial homogeneity over an earlier 3 x 3 mesh version. The new resonator exhibited high sensitivity and good homogeneity over the brain volume, permitting analysis of functional activation over large areas of the cerebral cortex. In a direct comparison with a standard clinical head-imaging resonator, the high sensitivity of the 5 x 5 mesh dome resonator resulted in greater statistical confidence in functional activation.
The rapidly developing domain of molecular imaging represents the merging of current advances in the fields of molecular biology and imaging research. Despite this merger, an information gap continues to exist between the scientists who discover new gene products and the imaging scientists who can exploit this information. The Gene Ontology (GO) Consortium seeks to provide a set of structured terminologies for the conceptual annotation of gene product function, process and location in databases. However, no such structured set of concept-oriented terminology exists for the molecular imaging domain. Since the purpose of GO is to capture the information about the role of gene products, we propose that the mapping of GO's established ontological concepts to a molecular imaging terminology will provide the necessary bridge to fill the information gap between the two fields. We have extracted terms and definitions from an already published molecular imaging glossary as well as molecular imaging research articles, and developed molecular imaging concepts. We then mapped our molecular imaging concepts to the existing gene ontology concepts as a method to comprehensively represent molecular imaging.
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