Significance: Although the clinical potential for Raman spectroscopy (RS) has been anticipated for decades, it has only recently been used in neurosurgery. Still, few devices have succeeded in making their way into the operating room. With recent technological advancements, however, vibrational sensing is poised to be a revolutionary tool for neurosurgeons. Aim: We give a summary of neurosurgical workflows and key translational milestones of RS in clinical use and provide the optics and data science background required to implement such devices. Approach: We performed an extensive review of the literature, with a specific emphasis on research that aims to build Raman systems suited for a neurosurgical setting. Results: The main translatable interest in Raman sensing rests in its capacity to yield label-free molecular information from tissue intraoperatively. Systems that have proven usable in the clinical setting are ergonomic, have a short integration time, and can acquire high-quality signal even in suboptimal conditions. Moreover, because of the complex microenvironment of brain tissue, data analysis is now recognized as a critical step in achieving high performance Raman-based sensing. Conclusions: The next generation of Raman-based devices are making their way into operating rooms and their clinical translation requires close collaboration between physicians, engineers, and data scientists.

Navigation‐guided brain biopsies are the standard of care for diagnosis of several brain pathologies. However, imprecise targeting and tissue heterogeneity often hinder obtaining high‐quality tissue samples, resulting in poor diagnostic yield. We report the development and first clinical testing of a navigation‐guided fiberoptic Raman probe that allows surgeons to interrogate brain tissue in situ at the tip of the biopsy needle prior to tissue removal. The 900 μm diameter probe can detect high spectral quality Raman signals in both the fingerprint and high wavenumber spectral regions with minimal disruption to the neurosurgical workflow. The probe was tested in three brain tumor patients, and the acquired spectra in both normal brain and tumor tissue demonstrated the expected spectral features, indicating the quality of the data. As a proof‐of‐concept, we also demonstrate the consistency of the acquired Raman signal with different systems and experimental settings. Additional clinical development is planned to further evaluate the performance of the system and develop a statistical model for real‐time tissue classification during the biopsy procedure.

A new method to improve the statistical interpretability of biological Raman Spectroscopy was applied to spectra acquired in vivo during neurosurgical resection of brain cancer, revealing oncogenic processes captured by the Raman system.

OBJECTIVESphenoid wing meningiomas are a heterogeneous group of tumors with variable surgical risks and prognosis. Those that have grown to a very large size, encasing the major cerebral arteries, are associated with a high risk of stroke. In reviewing the authors’ series of giant sphenoid wing meningiomas, the goal was to evaluate how the extent of the tumor’s invasion of surrounding structures affected the ability to safely remove the tumor and restore function.METHODSThe authors conducted a retrospective study of a series of giant sphenoid wing meningiomas operated on between 1996 and 2016. Inclusion criteria were meningiomas with a globoid component ≥ 6 cm, encasing at least 1 major intradural cerebral artery. Extent of resection was measured according to Simpson grade.RESULTSThis series included 12 patients, with a mean age of 59 years. Visual symptoms were the most common clinical presentation. There was complete or partial encasement of all 3 major cerebral arteries except for 3 cases in which only the anterior cerebral artery was not involved. The lateral wall of the cavernous sinus was invaded in 8 cases (67%) and the optic canal in 6 (50%). Complete resection was achieved in 2 cases (Simpson grades 2 and 3). In the remaining 10 cases of partial resection (Simpson grade 4), radical removal (> 90%) was achieved in 7 cases (70%). In the immediate postoperative period, there were no deaths. Four of 9 patients with visual deficits improved, while the 5 others remained unchanged. Two patients experienced transient neurological deficits. Other than an asymptomatic lacuna of the internal capsule, there were no ischemic lesions following surgery. Tumor recurrence occurred in 5 patients, between 24 and 168 months (mean 61 months) following surgery.CONCLUSIONSAlthough these giant lesions encasing major cerebral arteries are particularly treacherous for surgery, this series demonstrates that it is possible to safely achieve radical removal and at times even gross-total resection. However, the risk of recurrence remains high and larger studies are needed to see if and how improvement can be achieved, whether in surgical technique or technological advances, and by determining the timing and modality of adjuvant radiation therapy.

Significance: Ensuring spectral quality is prerequisite to Raman spectroscopy applied to surgery. This is because the inclusion of poor-quality spectra in the training phase of Raman-based pathology detection models can compromise prediction robustness and generalizability to new data. Currently, there exists no quantitative spectral quality assessment technique that can be used to either reject low-quality data points in existing Raman datasets based on spectral morphology or, perhaps more importantly, to optimize the in vivo data acquisition process to ensure minimal spectral quality standards are met.Aim: To develop a quantitative method evaluating Raman signal quality based on the variance associated with stochastic noise in important tissue bands, including C─C stretch, CH 2 ∕CH 3 deformation, and the amide bands.Approach: A single-point hand-held Raman spectroscopy probe system was used to acquire 315 spectra from 44 brain cancer patients. All measurements were classified as either high or low quality based on visual assessment (qualitative) and using a quantitative quality factor (QF) metric. Receiver-operator-characteristic (ROC) analyses were performed to evaluate the performance of the quantitative metric to assess spectral quality and improve cancer detection accuracy. Results:The method can separate high-and low-quality spectra with a sensitivity of 89% and a specificity of 90% which is shown to increase cancer detection sensitivity and specificity by up to 20% and 12%, respectively. Conclusions:The QF threshold is effective in stratifying spectra in terms of spectral quality and the observed false negatives and false positives can be linked to limitations of qualitative spectral quality assessment.

In a real-world setting, ROTEM-based algorithm implementation could help reduce excess erythrocytes transfusion for complex aortic procedures. We advocate for a strict adherence and concerted team effort to maximize the benefits of such addition to patients' management.

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractA flowing well continuously looses heat to its surroundings. An accurate prediction for the flowing surface temperature is necessary for production operations. Above optimum surface temperature, chillers are required to cool the gas prior to flowing in pipelines. Too cold of a surface temperature can cause precipitation problems that restrict flow and may require an insulating packer fluid. Economic justification must be decided based on the increased flowing surface temperature that an insulating packer fluid can provide above a conventional one. Therefore, a predictive model was developed that can accurately predict the surface temperature for a flowing well for any Newtonian fluid. The model predicted the flowing well surface temperature (FWST) within 5°F of the measured temperature for the wells studied.The uniqueness of this model is that a newly derived equation is used to predict the velocity of the packer fluid along the tubing wall caused by free convection for a vertical annulus. Laminar or turbulent flow can be determined from this velocity. In turbulent flow, a friction factor for flat plate or pipe flow must be used to insure accurate predictions. Only when the thickness of the boundary layer equals the midpoint within the annulus can friction factors from pipe flow be used. The model showed how the addition of friction reducers can decrease a well's flowing surface temperature due to the increase in free convection, i.e., by up to 17°F for one case.