Methodology for computing white matter nerve fiber orientation in human histological slices.

BACKGROUND: The gold standard for mapping nerve fiber orientation in white matter of the human brain is histological analysis through biopsy. Such mappings are a crucial step in validating non-invasive techniques for assessing nerve fiber orientation in the human brain by using diffusion MRI. However, the manual extraction of nerve fiber directions of histological slices is tedious, time consuming, and prone to human error. NEW METHOD: The presented semi-automated algorithm first creates a binary-segmented mask of the nerve fibers in the histological image, and then extracts an estimate of average directionality of nerve fibers through a Fourier-domain analysis of the masked image. It also generates an uncertainty level for its estimate of average directionality. RESULTS AND COMPARISON WITH EXISTING METHODS: The average orientations of the semi-automatic method were first compared to a qualitative expert opinion based on visual inspection of nerve fibers. A weighted RMS difference between the expert estimate and the algorithmically determined angle (weighted by expert's confidence in his estimate) was 15.4°, dropping to 9.9° when only cases with an expert confidence level of greater than 50% were included. The algorithmically determined angles were then compared with angles extracted using a manual segmentation technique, yielding an RMS difference of 11.2°. CONCLUSION: The presented semi-automated method is in good agreement with both qualitative and quantitative manual expert-based approaches for estimating directionality of nerve fibers in white matter from images of stained histological slices of the human brain.

Changes in frontal morphology after single-stage open posterior-middle vault expansion for sagittal craniosynostosis.

BACKGROUND: There is controversy regarding whether the frontal bossing associated with sagittal synostosis requires direct surgical correction or spontaneously remodels after isolated posterior cranial expansion. The authors retrospectively measured changes in frontal bone morphology in patients with isolated sagittal synostosis 2 years after open posterior and midvault cranial expansion and compared these changes with those occurring in age-comparable healthy control groups. METHODS: Forty-three patients age 1 year or younger (mean, 6 months) with sagittal synostosis underwent computed tomography scan digital analysis immediately after and 2 years after posterior-middle cranial vault expansion. Quantitative angular and linear measures were taken along the midsagittal and axial planes to capture both aspects of frontal bossing. The change in values over the 2 years were compared with healthy controls with normal computed tomography scans taken to rule out head trauma. RESULTS: All measures indicative of frontal bossing decreased significantly from the time of posterior-middle vault expansion to 2 years postoperatively. Whereas the majority of patients at time of the operation had frontal bossing measures greater than two standard deviations outside the age-comparable control mean, almost all patients were within two standard deviations of the norm 2 years later. Lateral forehead bossing and anterior cranial growth was greater the older the patient was at the time of the operation, suggesting that the more time that passed before the operation, the more compensatory anterior fossa growth occurred. Central forehead position relative to the anterior cranial base was greatest in the younger patients at the time of operation, suggesting that a central forehead bulge was an early compensatory response to premature sagittal fusion. CONCLUSIONS: As a group, patients with sagittal synostosis start to normalize their forehead morphology within 2 years if an isolated posterior operation is performed at 1 year of age or younger, and this occurs by a combination of restriction of growth and reduction relative to patients without synostosis. This protocol decreases the risks of intraoperative positioning, forehead contour deformities, and two-stage operations. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.

Secure communications for PACS in a cloud environment.

Picture Archiving and Communication Systems (PACS) have been traditionally constrained to the premises of the healthcare provider. This has limited the availability of these systems in many parts of the world and mandated major costs in infrastructure for those who employ them. Public cloud services could be a solution that eases the cost of ownership and provide greater flexibility for PACS implementations. Moving these systems to the public cloud requires that an authentication and encryption policy for communications is established within the PACS environment. This paper investigated an implementation which uses Transport Layer Security for communications between a cloud-based PACS server and client.

Online survey system for image-based clinical guideline studies using the Delphi method.

The increasing use of health information technology (HIT) is due to a rising interest in improving the quality of health care. HIT has the potential to reduce cost and transform services. Proper clinical support systems will contribute to the meaningful use of HIT systems by providing a wide array of data to clinicians for the diagnosis and treatments. Clinical guidelines, created by a consensus of experts, can be put in place to assist physicians in making clinical decisions. Delphi methods are commonly used to create consensus from surveys completed by a team of experts. Image based studies could create guidelines that standardize severity, deformity or other clinical classifications. As these studies were traditionally conducted using paper based media, the cost and time requirement often make the process impractical. Ware proposing a web based system to aid medical researchers in conducting image based Delphi studies for improved clinical guidelines and decision support.

Head and neck lymph node region delineation with image registration.

BACKGROUND: The success of radiation therapy depends critically on accurately delineating the target volume, which is the region of known or suspected disease in a patient. Methods that can compute a contour set defining a target volume on a set of patient images will contribute greatly to the success of radiation therapy and dramatically reduce the workload of radiation oncologists, who currently draw the target by hand on the images using simple computer drawing tools. The most challenging part of this process is to estimate where there is microscopic spread of disease. METHODS: Given a set of reference CT images with "gold standard" lymph node regions drawn by the experts, we are proposing an image registration based method that could automatically contour the cervical lymph code levels for patients receiving radiation therapy. We are also proposing a method that could help us identify the reference models which could potentially produce the best results. RESULTS: The computer generated lymph node regions are evaluated quantitatively and qualitatively. CONCLUSIONS: Although not conforming to clinical criteria, the results suggest the technique has promise.

Head and neck lymph node region delineation with 3-D CT image registration.

The success of radiation therapy depends critically on accurately delineating the target volume, which is the region of known or suspected disease in a patient. Methods that can compute a contour set defining a target volume on a set of patient images will contribute greatly to the success of radiation therapy and dramatically reduce the workload of radiation oncologists, who currently draw the target by hand on the images using simple computer drawing tools. The most challenging part of this process is to estimate where there is microscopic spread of disease. We are developing methods for automatically selecting and adapting standardized regions of tumor spread based on the location of lymph nodes in a standard or reference case, together with image registration techniques. The best available image registration techniques (deformable transformations computed using "mutual information" optimization) appear promising but will need to be supplemented by anatomic knowledge-based methods to achieve a clinically acceptable match.