Tethered spinal cord tension assessed via ultrasound elastography in computational and intraoperative human studies.

BACKGROUND: Tension in the spinal cord is a trademark of tethered cord syndrome. Unfortunately, existing tests cannot quantify tension across the bulk of the cord, making the diagnostic evaluation of stretch ambiguous. A potential non-destructive metric for spinal cord tension is ultrasound-derived shear wave velocity (SWV). The velocity is sensitive to tissue elasticity and boundary conditions including strain. We use the term Ultrasound Tensography to describe the acoustic evaluation of tension with SWV. METHODS: Our solution Tethered cord Assessment with Ultrasound Tensography (TAUT) was utilized in three sub-studies: finite element simulations, a cadaveric benchtop validation, and a neurosurgical case series. The simulation computed SWV for given tensile forces. The cadaveric model with induced tension validated the SWV-tension relationship. Lastly, SWV was measured intraoperatively in patients diagnosed with tethered cords who underwent treatment (spinal column shortening). The surgery alleviates tension by decreasing the vertebral column length. RESULTS: Here we observe a strong linear relationship between tension and squared SWV across the preclinical sub-studies. Higher tension induces faster shear waves in the simulation (R2 = 0.984) and cadaveric (R2 = 0.951) models. The SWV decreases in all neurosurgical procedures (p < 0.001). Moreover, TAUT has a c-statistic of 0.962 (0.92-1.00), detecting all tethered cords. CONCLUSIONS: This study presents a physical, clinical metric of spinal cord tension. Strong agreement among computational, cadaveric, and clinical studies demonstrates the utility of ultrasound-induced SWV for quantitative intraoperative feedback. This technology is positioned to enhance tethered cord diagnosis, treatment, and postoperative monitoring as it differentiates stretched from healthy cords.

Tethered spinal cord syndrome occurs when surrounding tissue attaches to and causes stretching across the spinal cord. People with a tethered cord can experience weakness, pain, and loss of bladder control. Although increased tension in the spinal cord is known to cause these symptoms, evaluating the amount of stretching remains challenging. We investigated the ability of an ultrasound imaging approach to measure spinal cord tension. We studied our method in a computer simulation, a benchtop validation model, and in six people with tethered cords during surgery that they were undergoing to reduce tension. In each phase, the approach could detect differences between stretched spinal cords and spinal cords in a healthy state. Our method could potentially be used in the future to improve the care of people with a tethered cord.

Unidirectional brain-computer interface: Artificial neural network encoding natural images to fMRI response in the visual cortex.

While significant advancements in artificial intelligence (AI) have catalyzed progress across various domains, its full potential in understanding visual perception remains underexplored. We propose an artificial neural network dubbed VISION, an acronym for "Visual Interface System for Imaging Output of Neural activity," to mimic the human brain and show how it can foster neuroscientific inquiries. Using visual and contextual inputs, this multimodal model predicts the brain's functional magnetic resonance imaging (fMRI) scan response to natural images. VISION successfully predicts human hemodynamic responses as fMRI voxel values to visual inputs with an accuracy exceeding state-of-the-art performance by 45%. We further probe the trained networks to reveal representational biases in different visual areas, generate experimentally testable hypotheses, and formulate an interpretable metric to associate these hypotheses with cortical functions. With both a model and evaluation metric, the cost and time burdens associated with designing and implementing functional analysis on the visual cortex could be reduced. Our work suggests that the evolution of computational models may shed light on our fundamental understanding of the visual cortex and provide a viable approach toward reliable brain-machine interfaces.

Visualizing tactile feedback: an overview of current technologies with a focus on ultrasound elastography.

Tissue elasticity remains an essential biomarker of health and is indicative of irregularities such as tumors or infection. The timely detection of such abnormalities is crucial for the prevention of disease progression and complications that arise from late-stage illnesses. However, at both the bedside and the operating table, there is a distinct lack of tactile feedback for deep-seated tissue. As surgical techniques advance toward remote or minimally invasive options to reduce infection risk and hasten healing time, surgeons lose the ability to manually palpate tissue. Furthermore, palpation of deep structures results in decreased accuracy, with the additional barrier of needing years of experience for adequate confidence of diagnoses. This review delves into the current modalities used to fulfill the clinical need of quantifying physical touch. It covers research efforts involving tactile sensing for remote or minimally invasive surgeries, as well as the potential of ultrasound elastography to further this field with non-invasive real-time imaging of the organ's biomechanical properties. Elastography monitors tissue response to acoustic or mechanical energy and reconstructs an image representative of the elastic profile in the region of interest. This intuitive visualization of tissue elasticity surpasses the tactile information provided by sensors currently used to augment or supplement manual palpation. Focusing on common ultrasound elastography modalities, we evaluate various sensing mechanisms used for measuring tactile information and describe their emerging use in clinical settings where palpation is insufficient or restricted. With the ongoing advancements in ultrasound technology, particularly the emergence of micromachined ultrasound transducers, these devices hold great potential in facilitating early detection of tissue abnormalities and providing an objective measure of patient health.

Simulated driving in the epilepsy monitoring unit: Effects of seizure type, consciousness, and motor impairment.

People with epilepsy face serious driving restrictions, determined using retrospective studies. To relate seizure characteristics to driving impairment, we aimed to study driving behavior during seizures with a simulator. Patients in the Yale New Haven Hospital undergoing video-electroencephalographic monitoring used a laptop-based driving simulator during ictal events. Driving function was evaluated by video review and analyzed in relation to seizure type, impairment of consciousness/responsiveness, or motor impairment during seizures. Fifty-one seizures in 30 patients were studied. In terms of seizure type, we found that focal to bilateral tonic-clonic or myoclonic seizures (5/5) and focal seizures with impaired consciousness/responsiveness (11/11) always led to driving impairment; focal seizures with spared consciousness/responsiveness (0/10) and generalized nonmotor (generalized spike-wave bursts; 1/19) usually did not lead to driving impairment. Regardless of seizure type, we found that seizures with impaired consciousness (15/15) or with motor involvement (13/13) always led to impaired driving, but those with spared consciousness (0/20) or spared motor function (5/38) usually did not. These results suggest that seizure types with impaired consciousness/responsiveness and abnormal motor function contribute to impaired driving. Expanding this work in a larger cohort could further determine how results with a driving simulator may translate into real world driving safety.