Study Design: Narrative review. Objectives: Artificial intelligence (AI) and machine learning (ML) have emerged as disruptive technologies with the potential to drastically affect clinical decision making in spine surgery. AI can enhance the delivery of spine care in several arenas: (1) preoperative patient workup, patient selection, and outcome prediction; (2) quality and reproducibility of spine research; (3) perioperative surgical assistance and data tracking optimization; and (4) intraoperative surgical performance. The purpose of this narrative review is to concisely assemble, analyze, and discuss current trends and applications of AI and ML in conventional and robotic-assisted spine surgery. Methods: We conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2019 examining AI, ML, and robotics in spine surgery. Key findings were then compiled and summarized in this review. Results: The majority of the published AI literature in spine surgery has focused on predictive analytics and supervised image recognition for radiographic diagnosis. Several investigators have studied the use of AI/ML in the perioperative setting in small patient cohorts; pivotal trials are still pending. Conclusions: Artificial intelligence has tremendous potential in revolutionizing comprehensive spine care. Evidence-based, predictive analytics can help surgeons improve preoperative patient selection, surgical indications, and individualized postoperative care. Robotic-assisted surgery, while still in early stages of development, has the potential to reduce surgeon fatigue and improve technical precision.

In diabetes, there are two major physiological aberrations: (i) Loss of insulin signaling due to absence of insulin (type 1 diabetes) or insulin resistance (type 2 diabetes) and (ii) increased blood glucose levels. The retina has a high proclivity to damage following diabetes, and much of the pathology seen in diabetic retinopathy has been ascribed to hyperglycemia and downstream cascades activated by increased blood glucose. However, less attention has been focused on the direct role of insulin on retinal physiology, likely due to the fact that uptake of glucose in retinal cells is not insulin-dependent. The retinal pigment epithelium (RPE) is instrumental in maintaining the structural and functional integrity of the retina. Recent studies have suggested that RPE dysfunction is a precursor of, and contributes to, the development of diabetic retinopathy. To evaluate the role of insulin on RPE cell function directly, we generated a RPE specific insulin receptor (IR) knockout (RPEIRKO) mouse using the Cre-loxP system. Using this mouse, we sought to determine the impact of insulin-mediated signaling in the RPE on retinal function under physiological control conditions as well as in streptozotocin (STZ)induced diabetes. We demonstrate that loss of RPE-specific IR expression resulted in lower a-and bwave electroretinogram amplitudes in diabetic mice as compared to diabetic mice that expressed IR on the RPE. Interestingly, RPEIRKO mice did not exhibit significant differences in the amplitude of the RPEdependent electroretinogram c-wave as compared to diabetic controls. However, loss of

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OBJECTIVE The number of patients who benefit from deep brain stimulation (DBS) for Parkinson's disease (PD) has increased significantly since the therapy was first approved by the FDA. Suboptimal outcomes, infection, or device failure are risks of the procedure and may require lead removal or repositioning. The authors present here the results of their series of revision and reimplantation surgeries. METHODS The data were reviewed from all DBS intracranial lead removals, revisions, or reimplantations among patients with PD over a 6-year period at the authors' institution. The indications for these procedures were categorized as infection, suboptimal outcome, and device failure. Motor outcomes as well as lead location were analyzed before removal and after reimplant or revision. RESULTS The final sample included 25 patients who underwent 34 lead removals. Thirteen patients had 18 leads reimplanted after removal. There was significant improvement in the motor scores after revision surgery among the patients who had the lead revised for a suboptimal outcome (p = 0.025). The mean vector distance of the new lead location compared to the previous location was 2.16 mm (SD 1.17), measured on an axial plane 3.5 mm below the anterior commissure-posterior commissure line. When these leads were analyzed by subgroup, the mean distance was 1.67 mm (SD 0.83 mm) among patients treated for infection and 2.73 mm (SD 1.31 mm) for those with suboptimal outcomes. CONCLUSIONS Patients with PD who undergo reimplantation surgery due to suboptimal outcome may experience significant benefits. Reimplantation after surgical infection seems feasible and overall safe.