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STUDY DESIGN: Development of a clinical practice guideline following the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) process. OBJECTIVE: The objectives of this study were to develop guidelines that outline the utility of intraoperative neuromonitoring (IONM) to detect intraoperative spinal cord injury (ISCI) among patients undergoing spine surgery, to define a subset of patients undergoing spine surgery at higher risk for ISCI and to develop protocols to prevent, diagnose, and manage ISCI. METHODS: All systematic reviews were performed according to PRISMA standards and registered on PROSPERO. A multidisciplinary, international Guidelines Development Group (GDG) reviewed and discussed the evidence using GRADE protocols. Consensus was defined by 80% agreement among GDG members. A systematic review and diagnostic test accuracy (DTA) meta-analysis was performed to synthesize pooled evidence on the diagnostic accuracy of IONM to detect ISCI among patients undergoing spinal surgery. The IONM modalities evaluated included somatosensory evoked potentials (SSEPs), motor evoked potentials (MEPs), electromyography (EMG), and multimodal neuromonitoring. Utilizing this knowledge and their clinical experience, the multidisciplinary GDG created recommendations for the use of IONM to identify ISCI in patients undergoing spine surgery. The evidence related to existing care pathways to manage ISCI was summarized and based on this a novel AO Spine-PRAXIS care pathway was created. RESULTS: Our recommendations are as follows: (1) We recommend that intraoperative neurophysiological monitoring be employed for high risk patients undergoing spine surgery, and (2) We suggest that patients at high risk for ISCI during spine surgery be proactively identified, that after identification of such patients, multi-disciplinary team discussions be undertaken to manage patients, and that an intraoperative protocol including the use of IONM be implemented. A care pathway for the prevention, diagnosis, and management of ISCI has been developed by the GDG. CONCLUSION: We anticipate that these guidelines will promote the use of IONM to detect and manage ISCI, and promote the use of preoperative and intraoperative checklists by surgeons and other team members for high risk patients undergoing spine surgery. We welcome teams to implement and evaluate the care pathway created by our GDG.

We investigated the effect of 0.6 MeV proton irradiation on the superconducting and normal-state properties of thin-film YBa 2 Cu 3 O 7 − δ superconductors. A thin-film YBCO superconductor (≈567 nm thick) was subject to a series of proton irradiations with a total fluence of 7.6 × 10 16   p / cm 2 . Upon irradiation, T c was drastically decreased from 89.3 K towards zero with a corresponding increase in the normal-state resistivity above T c . This increase in resistivity, which indicates an increase in defects inside the thin-film sample, can be converted to the dimensionless scattering rate. We found that the relation between T c and the dimensionless scattering rate obtained during proton irradiation approximates the generalized d-wave Abrikosov–Gor'kov theory better than the previous results obtained from electron irradiations. This is an unexpected result, since the electron irradiation is known to be most effective to suppress superconductivity over other heavier ion irradiations such as proton irradiation. In comparison with the previous irradiation studies, we found that the result can be explained by two facts. First, the dominant defects created by 0.6 MeV protons can be point-like when the implantation depth is much longer than the sample thickness. Second, the presence of defects on all element sites is important to effectively suppress T c . [ABSTRACT FROM AUTHOR]

The primary treatment method for intramedullary spinal cord tumor (IMSCT) is surgical resection, but this procedure carries a significant risk of neurological damage. Intraoperative neurophysiological monitoring (IONM) has become a necessary adjunctive tool for IMSCT resection. The current study aimed to explore the application value of D-wave monitoring in IMSCT surgery, and tried to investigate a tailored criterion for its early warning. A retrospective clinical study. A retrospective analysis was conducted based on the data of patients who underwent IMSCT surgeries performed by the same neurosurgical team at our hospital. IONM was applied in all surgeries. According to inclusion and exclusion criteria, ultimately 90 patients were enrolled in the study. The McCormick Scale (MMS) was applied to assess the functional outcome through outpatient visits or telephone follow-up at one month and six months postoperatively. Patients with an MMS grade over II one month after surgery were considered to have newly developed postoperative motor dysfunction (PMD). If the MMS grade could be restored to I or II six months after surgery, it was defined as a short-term PMD. Otherwise, it was defined as a long-term PMD. The predictive value of different IONM modalities, including somatosensory evoked potential (SEP), muscle motor evoked potential (MEP), and D-wave for PMD, was assessed with sensitivity, specificity, positive predictive value, negative predictive value, and subsequent logistic regression analysis. At last, the cut-off value of the D-wave amplitude reduction ratio for predicting PMD was obtained through the receiver operating characteristic (ROC) curve analysis. SEP showed the worst performance in predicting short-term and long-term PMD. Significant MEP changes were indicated as an independent predictive factor for short-term PMD (OR 5.062, 95% CI 1.947–13.166, p =.001), while D-wave changes were demonstrated as an independent predictor for long-term PMD (OR 339.433, 95% CI 11.337–10770.311, p =.001). The optimum cut-off value of the D-wave amplitude reduction ratio for predicting long-term PMD was 42.18%, with a sensitivity of 100% and a specificity of 93.8% (AUC=0.981, p <.001). D-wave monitoring showed extremely high specificity in predicting PMD compared to SEP and MEP monitoring. Moreover, the authors suggested that a D-wave amplitude reduction of over 40% during IMSCT surgery generally indicates long-term PMD for patients. [ABSTRACT FROM AUTHOR]

D-waves (also called direct waves) result from the direct activation of fast-conducting, thickly myelinated corticospinal tract (CST) fibres after a single electrical stimulus. During intraoperative neurophysiological monitoring, D-waves are used to assess the long-term motor outcomes of patients undergoing surgery for intramedullary spinal cord tumours, selected cases of intradural extramedullary tumours and surgery for syringomyelia. In the present manuscript, we discuss D-wave monitoring and its role as a tool for monitoring the CST during spinal cord surgery. We describe the neurophysiological background and provide some recommendations for recording and stimulation, as well as possible future perspectives. Further, we introduce the concept of anti D-wave and present an illustrative case with successful recordings. [ABSTRACT FROM AUTHOR]

Quantum computing (QC) is a rapidly growing technology in the field of computation that has garnered significant attention in recent years. This emerging technology has become particularly relevant due to the increasing complexity of optimization problems and their expanding search spaces. As a result, innovative solutions that can surpass the limitations of the current optimization paradigms executed on classic computers are becoming necessary. D-wave, a specialized quantum computer, presents a novel solution for addressing intricate optimization problems with remarkable speed advantages over traditional methods. However, a major hurdle in terms of utilizing the D-wave platform for topology optimization design is the conversion of an optimization problem into formulas that can be comprehended by a quantum annealing machine. This is because the D-wave platform is limited to solving quadratic unconstrained binary optimization problems or Ising model problems, making it necessary to find a way to adapt the task of interest to these specific types of optimization problems. This paper examines the current reality concerning the extremely limited availability of quantum computing resources. We focus on small-scale discrete structural topology optimization problems as a starting point and establish a mapping relationship between quantum bits and the cross-sectional area variables of truss elements. Utilizing this mapping, a quadratic unconstrained binary optimization model is developed with these variables. We propose a nested optimization process with dynamically adjusted cross-sectional areas, which enables the development of a quantum annealing approach for optimizing the topology of discrete variables. Our method is validated through numerical experiments, demonstrating its efficiency. [ABSTRACT FROM AUTHOR]

In this article, we study the problem of digital pre/postcoding design in multiple-input multiple-output (MIMO) systems with 1-b resolution per complex dimension. The optimal solution that maximizes the received signal-to-noise ratio relies on an NP-hard combinatorial problem that requires exhaustive searching with exponential complexity. By using the principles of alternating optimization and quantum annealing (QA), an iterative QA-based algorithm is proposed that achieves near-optimal performance with polynomial complexity. The algorithm is associated with a rigorous mathematical framework that casts the pre/postcoding vector design to appropriate real-valued quadratic unconstrained binary optimization (QUBO) problems. Experimental results in a state-of-the-art D-WAVE QA device validate the efficiency of the proposed algorithm. To further improve the efficiency of the D-WAVE quantum device, a new preprocessing technique, which preserves the quadratic QUBO matrix from the detrimental effects of the Hamiltonian noise through nonlinear companding, is proposed. The proposed preprocessing technique significantly improves the quality of the D-WAVE solutions as well as the occurrence probability of the optimal solution.

Simple Summary: Despite advances in surgical and imaging techniques, intramedullary spinal cord tumors (IMSCTs) still represent a challenge. Surgical removal of IMCTs carries a substantial risk of spinal cord injury and neurologic morbidity. This study aimed to assess the predictive potential of multimodal intraoperative neurophysiological monitoring (IONM) for functional outcomes in IMSCTs. Clinical data were collected from 64 patients who underwent surgery between 2011 and 2020. Monitoring of motor evoked potentials (MEPs) and somatosensory evoked potentials (SSEPs) was conducted for all patients, while a D-waves recording was obtained in 57 patients. Postoperative neurologic outcomes were measured with Frankel and modified McCormick scales. D-wave monitoring provided valuable insights into motor outcomes, enabling us to proceed with surgery even in cases where MEPs/SSEPs were lost. D-wave monitoring demonstrated superior accuracy and predictive ability compared to MEPs and SSEPs alone. Multimodal IONM has the potential to significantly enhance the extent of tumor resection while minimizing the risk of neurological morbidity in IMSCT surgery. Objective: The study aimed at evaluating the efficacy and the ability of D-wave monitoring combined with somatosensory evoked potentials (SSEPs) and motor evoked potentials (MEPs) to predict functional outcomes in intramedullary spinal cord tumor (IMSCT) surgery. Methods: Between December 2011 and December 2020, all patients harboring IMSCT who underwent surgery at our institution were prospectively collected in a surgical spinal registry and retrospectively analyzed. Patient charts and surgical and histological reports were analyzed. The multimodal IONM included SSEPs, MEPs, and—whenever possible—D-waves. All patients were evaluated using the modified McCormick and Frankel grade at admission and 3, 6, and 12 months of follow-up. Results: Sixty-four patients were enrolled in the study. SSEP and MEP monitoring was performed in all patients. The D-wave was not recordable in seven patients (11%). Significant IONM changes (at least one evoked potential modality) were registered in 26 (41%) of the 64 patients. In five cases (8%) where the SSEPs and MEPs lost and the D-wave permanently dropped by about 50%, patients experienced a permanent deterioration of their neurological status. Multimodal IONM (SSEP, MEP, and D-wave neuromonitoring) significantly predicted postoperative deficits (p = 0.0001), with a sensitivity of 100.00% and a specificity of 95.65%. However, D-waves demonstrated significantly higher sensitivity (100%) than MEPs (62.5%) and SSEPs (71.42%) alone. These tests' specificities were 85.10%, 13.89%, and 17.39%, respectively. Comparing the area under ROC curves (AUCs) of these evoked potentials in 53 patients (where all three modalities of IONM were registered) using the pairwise t-test, D-wave monitoring appeared to have higher accuracy and ability to predict postoperative deficits with strong statistical significance compared with MEP and SSEP alone (0.992 vs. 0.798 vs. 0.542; p = 0.018 and p < 0.001). Conclusion: The use of multimodal IONM showed a statistically significant greater ability to predict postoperative deficits compared with SSEP, MEP, and D-wave monitoring alone. D-wave recording significantly increased the accuracy and clinical value of neurophysiological monitoring in IMSCT tumor resection. [ABSTRACT FROM AUTHOR]

This paper investigates how to reduce the elliptic curve discrete logarithm problem over prime fields to the quadratic unconstrained binary optimization (QUBO) problem in order to obtain as few logical qubits as possible. In the best case scenario, if n is the bitlength of a characteristic of prime field Fp, approximately 3n³ logical qubits are required for such a reduction in the Edwards curve case. We present a practical attack on an elliptic curve discrete logarithm problem over the 3-bit prime field F7 for an elliptic curve with the subgroup of order 8. We solved this problem using the D-Wave Advantage QPU. To the best of the authors' knowledge, no one has made, so far, a practical attack on the elliptic curve discrete logarithm over a prime field using the direct quantum method. [ABSTRACT FROM AUTHOR]

This paper investigates how to reduce the elliptic curve discrete logarithm problem over prime fields to the quadratic unconstrained binary optimization (QUBO) problem in order to obtain as few logical qubits as possible. In the best case scenario, if n is the bitlength of a characteristic of prime field Fp, approximately 3n³ logical qubits are required for such a reduction in the Edwards curve case. We present a practical attack on an elliptic curve discrete logarithm problem over the 3-bit prime field F7 for an elliptic curve with the subgroup of order 8. We solved this problem using the D-Wave Advantage QPU. To the best of the authors' knowledge, no one has made, so far, a practical attack on the elliptic curve discrete logarithm over a prime field using the direct quantum method.

Abstract Intramedullary tumors are a class of central nervous system tumors with an incidence of 2 to 4%. As they are located very deep and frequently cause postoperative neurological complications, surgical resection is difficult. In recent years, many surgeons have performed electrophysiological monitoring to effectively reduce the occurrence of postoperative neurological complications. Modern electrophysiological monitoring technology has advanced considerably, leading to the development of many monitoring methods, such as SSEPs, MEPs, DCM, and EMG, to monitor intramedullary tumors. However, electrophysiological monitoring in tumor resection is still being studied. In this article, we discussed the different monitoring methods and their role in monitoring intramedullary tumors by reviewing previous studies. Intratumorally tumors need to be monitored for a summary of the condition of the patient. Only by using various monitoring methods flexibly and through clear communication between surgeons and neurophysiological experts can good decisions be made during surgery and positive surgical results be achieved.

D-waves (also called direct waves) result from the direct activation of fast-conducting, thickly myelinated corticospinal tract (CST) fibres after a single electrical stimulus. During intraoperative neurophysiological monitoring, D-waves are used to assess the long-term motor outcomes of patients undergoing surgery for intramedullary spinal cord tumours, selected cases of intradural extramedullary tumours and surgery for syringomyelia. In the present manuscript, we discuss D-wave monitoring and its role as a tool for monitoring the CST during spinal cord surgery. We describe the neurophysiological background and provide some recommendations for recording and stimulation, as well as possible future perspectives. Further, we introduce the concept of anti D-wave and present an illustrative case with successful recordings.

Intramedullary tumors are a class of central nervous system tumors with an incidence of 2 to 4%. As they are located very deep and frequently cause postoperative neurological complications, surgical resection is difficult. In recent years, many surgeons have performed electrophysiological monitoring to effectively reduce the occurrence of postoperative neurological complications. Modern electrophysiological monitoring technology has advanced considerably, leading to the development of many monitoring methods, such as SSEPs, MEPs, DCM, and EMG, to monitor intramedullary tumors. However, electrophysiological monitoring in tumor resection is still being studied. In this article, we discussed the different monitoring methods and their role in monitoring intramedullary tumors by reviewing previous studies. Intratumorally tumors need to be monitored for a summary of the condition of the patient. Only by using various monitoring methods flexibly and through clear communication between surgeons and neurophysiological experts can good decisions be made during surgery and positive surgical results be achieved. [ABSTRACT FROM AUTHOR]

Quantum annealing is a promising method for solving hard optimization problems by transforming them into quadratic unconstrained binary optimization (QUBO) problems. However, when constraints are involved, particularly multiple inequality constraints, incorporating them into the objective function poses challenges. In this paper, the authors present two novel approaches for solving problems with multiple inequality constraints on a quantum annealer and apply them to the set cover problem (SCP). The first approach uses the augmented Lagrangian method to represent the constraints, while the second approach employs a higher‐order binary optimization (HUBO) formulation. The experiments show that both approaches outperform the standard approach for solving the SCP on the D‐Wave Advantage quantum annealer. The HUBO formulation performs slightly better than the augmented Lagrangian method in solving the SCP, but its scalability in terms of embeddability in the quantum chip is worse. The results demonstrate that the proposed augmented Lagrangian and HUBO methods can successfully implement a large number of inequality constraints, making them applicable to a broad range of constrained problems beyond the SCP. [ABSTRACT FROM AUTHOR]

Study Design: Retrospective multicenter cohort study Objectives: We aimed to clarify the efficacy of multimodal intraoperative neuromonitoring (IONM), especially in transcranial electrical stimulation of motor-evoked potentials (TES-MEPs) with spinal cord-evoked potentials after transcranial stimulation of the brain (D-wave) in the detection of reversible spinal cord injury in high-risk spinal surgery. Methods: We reviewed 1310 patients who underwent TES-MEPs during spinal surgery at 14 spine centers. We compared the monitoring results of TES-MEPs with D-wave vs TES-MEPs without D-wave in high-risk spinal surgery. Results: There were 40 cases that used TES-MEPs with D-wave and 1270 cases that used TES-MEPs without D-wave. Before patients were matched, there were significant differences between groups in terms of sex and spinal disease category. Although there was no significant difference in the rescue rate between TES-MEPs with D-wave (2.0%) and TES-MEPs (2.5%), the false-positivity rate was significantly lower (0%) in the TES-MEPs-with-D-wave group. Using a one-to-one propensity score-matched analysis, 40 pairs of patients from the two groups were selected. Baseline characteristics did not significantly differ between the matched groups. In the score-matched analysis, one case (2.5%) in both groups was a case of rescue (P = 1), five (12.5%) cases in the TES-MEPs group were false positives, and there were no false positives in the TES-MEPs-with-D-wave group (P =.02). Conclusions: TES-MEPs with D-wave in high-risk spine surgeries did not affect rescue case rates. However, it helped reduce the false-positivity rate. [ABSTRACT FROM AUTHOR]

Quantum annealing has emerged as a powerful platform for simulating and optimizing classical and quantum Ising models. Quantum annealers, like other quantum and/or analog computing devices, are susceptible to non-idealities including crosstalk, device variation, and environmental noise. Compensating for these effects through calibration refinement or “shimming” can significantly improve performance but often relies on ad-hoc methods that exploit symmetries in both the problem being solved and the quantum annealer itself. In this tutorial, we attempt to demystify these methods. We introduce methods for finding exploitable symmetries in Ising models and discuss how to use these symmetries to suppress unwanted bias. We work through several examples of increasing complexity and provide complete Python code. We include automated methods for two important tasks: finding copies of small subgraphs in the qubit connectivity graph and automatically finding symmetries of an Ising model via generalized graph automorphism. We conclude the tutorial by surveying additional methods, providing practical implementation tips, and discussing limitations and remedies of the calibration procedure. Code is available at: https://github.com/dwavesystems/shimming-tutorial.

Syringomyelia can be associated with multiple etiologies. The treatment of the underlying causes is first-line therapy; however, a direct approach to the syrinx is accepted as rescue treatment. Any direct intervention on the syrinx requires a myelotomy, posing a significant risk of iatrogenic spinal cord (SC) injury. Intraoperative neurophysiological monitoring (IONM) is crucial to detect and prevent surgically induced damage in neural SC pathways. We retrospectively reviewed the perioperative and intraoperative neurophysiological data and perioperative neurological examinations in ten cases of syringomyelia surgery. All the monitored modalities remained stable throughout the surgery in six cases, correlating with no new postoperative neurological deficits. In two patients, significant transitory attenuation, or loss of motor evoked potentials (MEPs), were observed and recovered after a corrective surgical maneuver, with no new postoperative deficits. In two cases, a significant MEP decrement was noted, which lasted until the end of the surgery and was associated with postoperative weakness. A transitory train of neurotonic electromyography (EMG) discharges was reported in one case. The surgical plan was adjusted, and the patient showed no postoperative deficits. The dorsal nerve roots were stimulated and identified in the seven cases where the myelotomy was performed via the dorsal root entry zone. Dorsal column mapping guided the myelotomy entry zone in four of the cases. In conclusion, multimodal IONM is feasible and reliable and may help prevent iatrogenic SC injury during syringomyelia surgery. [ABSTRACT FROM AUTHOR]

The classic game of Battleship involves two players taking turns attempting to guess the positions of a fleet of vertically or horizontally positioned enemy ships hidden on a $10\times 10$ grid. One variant of this game, also referred to as Battleship Solitaire, Bimaru or Yubotu, considers the game with the inclusion of X-ray data , represented by knowledge of how many spots are occupied in each row and column in the enemy board. This paper considers the Battleship puzzle problem : the problem of reconstructing an enemy fleet from its X-ray data. We generate non-unique solutions to Battleship puzzles via certain reflection transformations akin to Ryser interchanges. Furthermore, we demonstrate that solutions of Battleship puzzles may be reliably obtained by searching for solutions of the associated classical binary discrete tomography problem which minimise the discrete Laplacian. We reformulate this optimisation problem as a quadratic unconstrained binary optimisation problem and approximate solutions via a simulated annealer, emphasising the future practical applicability of quantum annealers to solving discrete tomography problems with predefined structure. [ABSTRACT FROM AUTHOR]

Quantum annealing is a specialized type of quantum computation that aims to use quantum fluctuations in order to obtain global minimum solutions of combinatorial optimization problems. Programmable D-Wave quantum annealers are available as cloud computing resources, which allow users low-level access to quantum annealing control features. In this article, we are interested in improving the quality of the solutions returned by a quantum annealer by encoding an initial state into the annealing process. We explore two D-Wave features that allow one to encode such an initial state: the reverse annealing (RA) and the h-gain (HG) features. RA aims to refine a known solution following an anneal path starting with a classical state representing a good solution, going backward to a point where a transverse field is present, and then finishing the annealing process with a forward anneal. The HG feature allows one to put a time-dependent weighting scheme on linear ($h$) biases of the Hamiltonian, and we demonstrate that this feature likewise can be used to bias the annealing to start from an initial state. We also consider a hybrid method consisting of a backward phase resembling RA and a forward phase using the HG initial state encoding. Importantly, we investigate the idea of iteratively applying RA and HG to a problem, with the goal of monotonically improving on an initial state that is not optimal. The HG encoding technique is evaluated on a variety of input problems including the edge-weighted maximum cut problem and the vertex-weighted maximum clique problem, demonstrating that the HG technique is a viable alternative to RA for some problems. We also investigate how the iterative procedures perform for both RA and HG initial state encodings on random whole-chip spin glasses with the native hardware connectivity of the D-Wave Chimera and Pegasus chips.

Quantum annealing has the potential to find low energy solutions of NP-hard problems that can be expressed as quadratic unconstrained binary optimization problems. However, the hardware of the quantum annealer manufactured by D-Wave Systems, which we consider in this work, is sparsely connected and moderately sized (on the order of thousands of qubits), thus necessitating a minor-embedding of a logical problem onto the physical qubit hardware. The combination of relatively small hardware sizes and the necessity of a minor-embedding can mean that solving large optimization problems is not possible on current quantum annealers. In this research, we show that a hybrid approach combining parallel quantum annealing with graph decomposition allows one to solve larger optimization problem accurately. We apply the approach to the Maximum Clique problem on graphs with up to 120 nodes and 6395 edges. [ABSTRACT FROM AUTHOR]

Motivated by an application in Computer Vision, we present an e cient QUBO solution for the minimum multi-way cut problem. For an edge-weighted input graph G = (V;E) and a set of terminals T = {t1, t2,. . ., tk} V we want to nd a subset of edges Ec of minimum total cost such that G0 = G n Ec separates T. QUBO rep-resentations are useful for solving problems on an adiabatic quantum computer like those produced by D-Wave Systems. Our reduction from the multi-way cut problem requires only O(kjV j) binary variables/qubits. The main result of this paper is a proof of correctness of this model. Furthermore, our reduction is small enough to be able to empirically test it with an existing D-Wave hybrid quantum-classical solver, which is illustrated at the end of this paper. [ABSTRACT FROM AUTHOR]

At present, surgical resection of primary intramedullary spinal cord tumors is the mainstay of treatment. However, given the dimensional constraints of the narrow spinal canal and dense organization of the ascending and descending tracts, intramedullary spinal cord tumor resection carries a significant risk of iatrogenic neurological injury. Intraoperative neurophysiological monitoring (IONM) and mapping techniques have been developed to evaluate the functional integrity of the essential neural pathways and optimize the surgical strategies. IONM can also inform on impending harm to at-risk structures and can correlate with postoperative functional recovery if damage has occurred. Direct waves (D-waves) will provide immediate feedback on the integrity of the lateral corticospinal tract. In the present review, we have provided an update on the utility of D-waves for spinal cord tumor resection. We have highlighted the neuroanatomical and neurophysiological insights from the use of D-wave monitoring, the technical considerations and limitations of the D-wave technique, and multimodal co-monitoring with motor-evoked potentials and somatosensory-evoked potentials. Together with motor-evoked potentials, D-waves can help to guide the extent of tumor resection and provide intraoperative warning signs and alarm criteria to direct the surgical strategy. D-waves can also serve as prognostic biomarkers for long-term recovery of postoperative motor function. We propose that the use of D-wave IONM can contribute key findings for clinical decision-making during spinal cord tumor resection.

Quasi-phase-matching (QPM) makes it possible to design domain engineered nonlinear crystals for highly efficient and multitasking nonlinear frequency conversion. However, finding the optimal crystal domain arrangement in a meaningful time is very challenging sometimes impossible by classical computing. In this paper, we proposed a quantum annealing computing method and used D-Wave superconducting quantum computer to design aperiodically poled lithium niobate (APPLN) for coupled third harmonic generation (CTHG). We converted the optical transformation efficiency function to an Ising model which can be solved by D-Wave quantum computer. The crystal design results were simulated by using nonlinear envelope equation (NEE), which showed very similar conversion efficiencies to the crystals designed by using simulated annealing (SA) method, demonstrating that quantum annealing computing is a powerful method for QPM crystal design.

To assess the accuracy of intraoperative neurophysiological monitoring (IONM) in predicting immediate and 3-month postoperative neurological new deficit (or deterioration) in patients benefiting from spinal cord (SC) surgery; and to identify factors associated with a higher risk of postoperative clinical worsening. Consecutive patients who underwent SC surgery with IONM were included. Pre and postoperative clinical (modified McCormick scale), radiological (lesion-occupying area ratio), and electrophysiological features were collected. A total of 99 patients were included: 14 (14.1%) underwent extradural surgery, 50 (50.5%) intradural extramedullary surgery, and 35 (35.4%) intramedullary surgery. Cumulatively, multimodal IONM (motor and somatosensory evoked potentials, D-wave whenever possible) significantly predicted postoperative deficits (p <0.001), with a sensitivity, specificity, positive predictive value, and negative predictive value of 0.81, 0.93, 0.83, and 0.92, respectively. Sixty (60.6%) patients displayed no IONM change, whereas 39 (39.4%) displayed IONM worsening. In multivariate analysis, predictors for postoperative clinical worsening were: abnormal preoperative electrophysiological assessment (p =0.03), intramedullary tumor (p<0.001), lesion-occupying area ratio ≥0.7 (p <0.001), and IONM alterations (p <0.001). Three months after the surgical procedure, in patients presenting at least one of the risk factors described above, 45/81 (55.6%) and 19/81 (23.5%) were clinically and electrophysiologically improved, respectively; while 13/81 (16.0%) and 10/81 (12.3%) were clinically and electrophysiologically worsened. Multimodal IONM is an essential tool to guide SC surgery, and enables the accurate prediction of postoperative neurological outcome. Specific attention should be given to patients presenting with preoperative electrophysiological abnormalities, large tumor volume, and intramedullary tumor location. [ABSTRACT FROM AUTHOR]

Background: Intramedullary spinal cord tumours are formidable lesions in spine surgery due to the high risk of postoperative deficits associated with surgical resection. Traditional MRI imaging fails to provide a 3-D rendering of the relationship between the tumour and spinal cord sensory and motor pathways; in contrast, DTI/tractography can show this relationship with the potential to reduce surgery-related morbidity. The use of intraoperative somatosensory evoked potentials (SSEP) and transcranial motor evoked potentials (MEP) have also been considered a standard of care to minimize neurologic complications of surgery. However, in situations where both baseline SSEPs and MEPs are unobtainable, D-wave and direct cord stimulation can become invaluable intra-operative tools. Methods: A 6 year old child presented with new growth from an incompletely resected thoracic intramedullary dermoid tumour. Pre-operative DTI/tractography images were obtained. During tumour resection, SSEP and MEP signals were unable to be obtained, however intraoperative monitoring of the spinal cord was undertaken with D-wave monitoring and direct cord stimulation. Results: This multimodal monitoring technique allowed identification of the corticospinal tracts intra-operatively and allowed safe tumour resection. Post-operative MRI revealed gross total resection and the patient returned to her pre-operative neurological baseline without incurring any further deficits. Conclusions: We have presented a technical description of the clinical utility of DTI/tractography in surgical planning, and D-wave monitoring with direct cord stimulation as adjuncts in the resection of an intramedullary cord tumour. This is particularly useful in the scenario where TcMEP/SSEP signals cannot be obtained and in revision surgery for intramedullary spinal cord tumours.

Objective. To analyze the results of a multimodal approach in intraoperative neurophysiological monitoring during surgical correction of spinal deformities. Material and Methods. The paper describes a variant of intraoperative neurophysiological monitoring of the spinal cord and nerve root functions which was used in the correction of scoliotic deformity of the spine in 138 patients. Surgery was performed in 83 patients aged 10 to 17 years and in 55 patients older than 17 years. The average age of patients was 20.23 ± 8.3 years. There were 41 male and 97 female patients. The primary scoliotic curve was localized in the thoracic spine in 90 cases, in the thoracolumbar spine in 27 cases, and in the lumbar spine in 21 cases. Results. In the early postoperative period, two patients developed neurological deficit, the electrophysiological predictors of which were recorded during intraoperative neurophysiological monitoring. In one case, the deficit gradually regressed completely due to the measures taken by the operating team during surgery; in the second case, a persistent neurological deficit in the form of lower paraplegia persisted, despite the measures taken during the surgical treatment. In other cases, intraoperative neurophysiological monitoring did not reveal any changes in the spinal cord and nerve roots, which in the early postoperative period would lead to the appearance or aggravation of motor deficit. Conclusion. A multimodal approach to intraoperative neurophysiological monitoring provides an operating surgeon with an objective assessment of the state of the spinal cord and nerve roots at any stage of surgery, which allows timely identification and elimination of the causes of their damage, thereby reducing the likelihood of neurological deficit development or aggravation in the postoperative period.