Hennepin Healthcare System, Inc

New York University

The United States Government as Represented by the Department of Veterans Affairs

Hennepin Healthcare Systems, Inc.

Abdullah Bin Zahid

Uzma Samadani

Henry Rusinek

Artem Mikheev

David P Darrow

A method for predicting abnormal eye convergence in a human or animal subject may involve tracking eye movement of at least one eye of the subject to generate eye tracking data for the subject and using the eye tracking data to predict whether the subject has abnormal eye convergence. A method for diagnosing a brain injury in a human or animal subject may involve tracking eye movement of at least one eye of the subject to generate eye tracking data for the subject, using the eye tracking data to predict whether the subject has abnormal eye convergence, and predicting whether a brain injury has occurred in the subject, based on the prediction of whether the subject has abnormal eye convergence.

Method for predicting convergence disorders caused by concussion or other neuropathology

The present disclosure is directed to the first methods and systems for diagnosing a patient being affected by a brain injury from a blast with greater accuracy that previous methods. The methods and system include an automated, non-invasive method for assessing the variance of a patient's ocular motility relative to a matched cohort of unaffected subjects, and using the variance in one or more ocular motility metrics to calculate a score that indicates a likelihood that the patient suffers from a blast brain injury. The score, referred to as a BIS, discriminates between affected an unaffected subjects with a sensitivity of greater than about 85%, a specificity of greater than 75%. The ROCAUC of the BIS is greater than 0.85.

Methods and kits for detection of blast brain injury, its severity, distance from blast epicenter, and classification relative to the larger spectrum of concussion

A surgical navigation system may include a processor and a display. The processor may receive a patient image and sensor data captured by a sensor, receive a medical image, generate a hologram of the medical image, perform coregistration between the patient image and the hologram, superimpose the hologram on the patient image, and display the superimposed image. Coregistration may be performed manually via a user interaction, or automatically based on one or more fiducials in the medical image and sensor data related to the fiducials. The system may monitor a change in the environment and update the display correspondingly. For example, the system may monitor a movement of a body of the patient, monitor the size of an organ of the patient as the organ is being under operation, or a movement of the surgical instrument. The sensor may be an augmented reality (AR) sensor in an AR device.

Using augmented reality in surgical navigation

To that end, in order to overcome some of the deficiencies presented herein above, an exemplary system, method and computer-accessible medium for determining an attribute(s) of a brain of a patient, can include, for example, receiving information obtained from a computed tomography ('CT') scan(s) of a portion(s) of the brain, generating a CT image(s) that can be based on the information, and determining the attribute(s) of the brain based on the CT image(s) by segmenting an intracranial space (ICS) in the CT image(s). The attribute(s) can include a presence or absence of Alzheimer's disease, total volume of the ICS, brain, CSF or a lesion or the volumes of ICS, brain, CSF or lesion(s) expressed as a percentage of other volume(s). The aforementioned areas can be segmented using a combination of thresholding, morphological erosions, morphological dilations, manual segmentation or semi-automatic segmentation techniques, all of which can be parallel procedures. These attributes can be further used to determine treatment, for example, optimizing the location of the twist drill craniotomy to drain hematoma in subdural hematoma.

System, method and computer-accessible medium for the determination of accelerated brain atrophy and an optimal drainage site for a subdural hematoma using computed tomography

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Minneapolis, MN, United States of America

Abdullah Bin Zahid