Does Early Mobilization Following Resection of Spinal Intra-Dural Pathology Increase the Risk of Cerebrospinal Fluid Leaks?-A Dual-Center Comparative Effectiveness Research.

Background and Objectives: Prolonged bed rest after the resection of spinal intradural tumors is postulated to mitigate the development of cerebrospinal fluid leaks (CSFLs), which is one of the feared postoperative complications. Nonetheless, the empirical evidence supporting this conjecture remains limited and requires further investigation. The goal of the study was to investigate whether prolonged bed rest lowers the risk of CSFL after the resection of spinal intradural tumors. The primary outcome was the rate of CSFL in each cohort. Materials and Methods: To validate this hypothesis, we conducted a comparative effectiveness research (CER) study at two distinct academic neurosurgical centers, wherein diverse postoperative treatment protocols were employed. Specifically, one center adopted a prolonged bed rest regimen lasting for three days, while the other implemented early postoperative mobilization. For statistical analysis, case-control matching was performed. Results: Out of an overall 451 cases, we matched 101 patients from each center. We analyzed clinical records and images from each case. In the bed rest center, two patients developed a CSFL (n = 2, 1.98%) compared to four patients (n = 4, 3.96%) in the early mobilization center (p = 0.683). Accordingly, CSFL development was not associated with early mobilization (OR 2.041, 95% CI 0.365-11.403; p = 0.416). Univariate and multivariate analysis identified expansion duraplasty as an independent risk factor for CSFL (OR 60.33, 95% CI: 0.015-0.447; p < 0.001). Conclusions: In this CER, we demonstrate that early mobilization following the resection of spinal intradural tumors does not confer an increased risk of the development of CSFL.

Rapid, label-free classification of glioblastoma differentiation status combining confocal Raman spectroscopy and machine learning.

Label-free identification of tumor cells using spectroscopic assays has emerged as a technological innovation with a proven ability for rapid implementation in clinical care. Machine learning facilitates the optimization of processing and interpretation of extensive data, such as various spectroscopy data obtained from surgical samples. The here-described preclinical work investigates the potential of machine learning algorithms combining confocal Raman spectroscopy to distinguish non-differentiated glioblastoma cells and their respective isogenic differentiated phenotype by means of confocal ultra-rapid measurements. For this purpose, we measured and correlated modalities of 1146 intracellular single-point measurements and sustainingly clustered cell components to predict tumor stem cell existence. By further narrowing a few selected peaks, we found indicative evidence that using our computational imaging technology is a powerful approach to detect tumor stem cells in vitro with an accuracy of 91.7% in distinct cell compartments, mainly because of greater lipid content and putative different protein structures. We also demonstrate that the presented technology can overcome intra- and intertumoral cellular heterogeneity of our disease models, verifying the elevated physiological relevance of our applied disease modeling technology despite intracellular noise limitations for future translational evaluation.

Improving the efficacy and reliability of rTMS language mapping by increasing the stimulation frequency.

Repetitive TMS (rTMS) with a frequency of 5-10 Hz is widely used for language mapping. However, it may be accompanied by discomfort and is limited in the number and reliability of evoked language errors. We, here, systematically tested the influence of different stimulation frequencies (i.e., 10, 30, and 50 Hz) on tolerability, number, reliability, and cortical distribution of language errors aiming at improved language mapping. 15 right-handed, healthy subjects (m = 8, median age: 29 yrs) were investigated in two sessions, separated by 2-5 days. In each session, 10, 30, and 50 Hz rTMS were applied over the left hemisphere in a randomized order during a picture naming task. Overall, 30 Hz rTMS evoked significantly more errors (20 ± 12%) compared to 50 Hz (12 ± 8%; p <.01), whereas error rates were comparable between 30/50 and 10 Hz (18 ± 11%). Across all conditions, a significantly higher error rate was found in Session 1 (19 ± 13%) compared to Session 2 (13 ± 7%, p <.05). The error rate was poorly reliable between sessions for 10 (intraclass correlation coefficient, ICC = .315) and 30 Hz (ICC = .427), whereas 50 Hz showed a moderate reliability (ICC = .597). Spatial reliability of language errors was low to moderate with a tendency toward increased reliability for higher frequencies, for example, within frontal regions. Compared to 10 Hz, both, 30 and 50 Hz were rated as less painful. Taken together, our data favor the use of rTMS-protocols employing higher frequencies for evoking language errors reliably and with reduced discomfort, depending on the region of interest.

Invasive versus non-invasive mapping of the motor cortex.

Precise and comprehensive mapping of somatotopic representations in the motor cortex is clinically essential to achieve maximum resection of brain tumours whilst preserving motor function, especially since the current gold standard, that is, intraoperative direct cortical stimulation (DCS), holds limitations linked to the intraoperative setting such as time constraints or anatomical restrictions. Non-invasive techniques are increasingly relevant with regard to pre-operative risk-assessment. Here, we assessed the congruency of neuronavigated transcranial magnetic stimulation (nTMS) and functional magnetic resonance imaging (fMRI) with DCS. The motor representations of the hand, the foot and the tongue regions of 36 patients with intracranial tumours were mapped pre-operatively using nTMS and fMRI and by intraoperative DCS. Euclidean distances (ED) between hotspots/centres of gravity and (relative) overlaps of the maps were compared. We found significantly smaller EDs (11.4 ± 8.3 vs. 16.8 ± 7.0 mm) and better spatial overlaps (64 ± 38% vs. 37 ± 37%) between DCS and nTMS compared with DCS and fMRI. In contrast to DCS, fMRI and nTMS mappings were feasible for all regions and patients without complications. In summary, nTMS seems to be the more promising non-invasive motor cortex mapping technique to approximate the gold standard DCS results.

Cortical Inhibition of Face and Jaw Muscle Activity and Discomfort Induced by Repetitive and Paired-Pulse TMS During an Overt Object Naming Task.

Modulatory effects of transcranial magnetic stimulation (TMS) strongly depend on the stimulation parameters. Here, we compared the immediate, task-locked inhibitory effects on speech-related muscles and the tolerability of different TMS protocols during a language production task. Repetitive TMS (rTMS) and paired-pulse TMS (PP) were applied in 13 healthy subjects over the primary motor cortex (M1) during a finger-tapping/tongue-twisting tasks. The lowest subject-specific TMS intensity leading to movement disruptions was used for TMS over left-sided speech-related areas during picture naming. Here, time-locked PP and rTMS (10/30/50 Hz; randomized sequence) were applied. Cortical silent periods (cSPs) were analyzed from electromyography obtained from various face muscles. 30 Hz- and 50 Hz-rTMS reliably evoked tongue movement disruption (ICC = 0.65) at lower rTMS intensities compared to 10 Hz-rTMS or PP. CSPs were elicited from the left hemisphere by all TMS protocols, most reliably by PP (p < 0.001). Also, cSPs with longest durations were induced by PP. Exploratory analyses of PP suggest that the trials with strongest motor inhibitory effects (presence of cSP) were associated with more articulatory naming errors, hence hinting at the utility of TMS-elicited, facial cSP for mapping of language production areas. Higher-frequency rTMS and PP evoked stronger inhibitory effects as compared to 10 Hz-rTMS during a language task, thus enabling a probably more efficient and tolerable routine for language mapping. The spatial distribution of cranial muscle cSPs implies that TMS might affect not only M1, but also distant parts of the language network.

Dual-Modality Surface-Enhanced Resonance Raman Scattering and Multispectral Optoacoustic Tomography Nanoparticle Approach for Brain Tumor Delineation.

Difficulty in visualizing glioma margins intraoperatively remains a major issue in the achievement of gross total tumor resection and, thus, better clinical outcome of glioblastoma (GBM) patients. Here, the potential of a new combined optical + optoacoustic imaging method for intraoperative brain tumor delineation is investigated. A strategy using a newly developed gold nanostar synthesis method, Raman reporter chemistry, and silication method to produce dual-modality contrast agents for combined surface-enhanced resonance Raman scattering (SERRS) and multispectral optoacoustic tomography (MSOT) imaging is devised. Following intravenous injection of the SERRS-MSOT-nanostars in brain tumor bearing mice, sequential MSOT imaging is performed in vivo and followed by Raman imaging. MSOT is able to accurately depict GBMs three-dimensionally with high specificity. The MSOT signal is found to correlate well with the SERRS images. Because SERRS enables uniquely sensitive high-resolution surface detection, it could represent an ideal complementary imaging modality to MSOT, which enables real-time, deep tissue imaging in 3D. This dual-modality SERRS-MSOT-nanostar contrast agent reported here is shown to enable high precision depiction of the extent of infiltrating GBMs by Raman- and MSOT imaging in a clinically relevant murine GBM model and could pave new ways for improved image-guided resection of brain tumors.

Lymph Node Micrometastases and In-Transit Metastases from Melanoma: In Vivo Detection with Multispectral Optoacoustic Imaging in a Mouse Model.

Purpose To study whether multispectral optoacoustic tomography (MSOT) can serve as a label-free imaging modality for the detection of lymph node micrometastases and in-transit metastases from melanoma on the basis of the intrinsic contrast of melanin in comparison to fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT). Materials and Methods The study was approved by the institutional animal care and use committee. Sequential MSOT was performed in a mouse B16F10 melanoma limb lymph node metastasis model (n = 13) to survey the development of macro-, micro- and in-transit metastases (metastases that are in transit from the primary tumor site to the local nodal basin) in vivo. The in vitro limit of detection was assessed in a B16F10 cell phantom. Signal specificity was determined on the basis of a simultaneous lymphadenitis (n = 4) and 4T1 breast cancer lymph metastasis (n = 2) model. MSOT was compared with intravenous FDG PET/CT. The diagnosis was assessed with histologic examination. Differences in the signal ratio (metastatic node to contralateral limb) between the two modalities were determined with the two-tailed paired t test. Results The mean signal ratios acquired with MSOT in micrometastases (2.5 ± 0.3, n = 6) and in-transit metastases (8.3 ± 5.8, n = 4) were higher than those obtained with FDG PET/CT (1.1 ± 0.5 [P < .01] and 1.3 ± 0.6 [P < .05], respectively). MSOT was able to help differentiate even small melanoma lymph node metastases from the other lymphadenopathies (P < .05 for both) in vivo, whereas FDG PET/CT could not (P > .1 for both). In vitro, the limit of detection was at an approximate cell density of five cells per microliter (P < .01). Conclusion MSOT enabled detection of melanoma lymph node micrometastases and in-transit metastases undetectable with FDG PET/CT and helped differentiate melanoma metastasis from other lymphadenopathies. (©) RSNA, 2016 Online supplemental material is available for this article.

The rabbit blood shunt subarachnoid haemorrhage model.

The recently introduced rabbit blood shunt subarachnoid haemorrhage model is based on the two standard procedures of subclavian artery cannulation and transcutaneous cisterna magna puncture. An extracorporeal shunt placed in between the arterial system and the subarachnoid space allows examiner-independent SAH in a closed cranium. Despite its straightforwardness, it is worth examining some specific features and characteristics of the model. We outline technical considerations to successfully perform the model with minimal mortality and morbidity. In addition, we discuss outcome measures, advantages and limitations, and the applicability of the model for the study of early brain injury and delayed cerebral vasospasm after SAH.

[Intraoperative stimulated Raman histology for personalized brain tumor surgery]. / Personalisierte Hirntumorchirurgie mittels intraoperativer stimulierter Raman-Histologie.

BACKGROUND: In brain tumor surgery a personalized surgical approach is crucial to achieve a maximum safe tumor resection. The extent of resection decisively depends on the histological diagnosis. Stimulated Raman histology (SRH), a fiber laser-based optical imaging method, offers the possibility for evaluation of an intraoperative diagnosis in a few minutes. OBJECTIVE: To provide an overview on the applications of SRH in neurosurgery and transference of the technique to other surgical disciplines. METHODS: Description of the technique and review of the current literature on SRH. RESULTS: The SRH technique was successfully used in multiple neuro-oncological tumor entities. Initial pilot projects showed the potential for analysis of extracranial tumors. CONCLUSION: The use of SRH provides a near real-time diagnosis with high diagnostic accuracy and provides further developmental potential to improve personalized tumor surgery.

Preoperative Performance Status Threshold for Favorable Surgical Outcome in Metastatic Spine Disease.

BACKGROUND AND OBJECTIVES: Surgical treatment is an integral component of multimodality management of metastatic spine disease but must be balanced against the risk of surgery-related morbidity and mortality, making tailored surgical counseling a clinical challenge. The aim of this study was to investigate the potential predictive value of the preoperative performance status for surgical outcome in patients with spinal metastases. METHODS: Performance status was determined using the Karnofsky Performance Scale (KPS), and surgical outcome was classified as "favorable" or "unfavorable" based on postoperative changes in neurological function and perioperative complications. The correlation between preoperative performance status and surgical outcome was assessed to determine a KPS-related performance threshold. RESULTS: A total of 463 patients were included. The mean age was 63 years (range: 22-87), and the mean preoperative KPS was 70 (range: 30-100). Analysis of clinical outcome in relation to the preoperative performance status revealed a KPS threshold between 40% and 50% with a relative risk of an unfavorable outcome of 65.7% in KPS ≤40% compared with the relative chance for a favorable outcome of 77.1% in KPS ≥50%. Accordingly, we found significantly higher rates of preserved or restored ambulatory function in KPS ≥50% (85.7%) than in KPS ≤40% (48.6%; P < .001) as opposed to a significantly higher risk of perioperative mortality in KPS ≤40% (11.4%) than in KPS ≥50% (2.1%, P = .012). CONCLUSION: Our results underline the predictive value of the KPS in metastatic spine patients for counseling and decision-making. The study suggests an overall clinical benefit of surgical treatment of spinal metastases in patients with a preoperative KPS score ≥50%, while a high risk of unfavorable outcome outweighing the potential clinical benefit from surgery is encountered in patients with a KPS score ≤40%.

Streamlined Intraoperative Brain Tumor Classification and Molecular Subtyping in Stereotactic Biopsies Using Stimulated Raman Histology and Deep Learning.

PURPOSE: Recent artificial intelligence algorithms aided intraoperative decision-making via stimulated Raman histology (SRH) during craniotomy. This study assesses deep learning algorithms for rapid intraoperative diagnosis from SRH images in small stereotactic-guided brain biopsies. It defines a minimum tissue sample size threshold to ensure diagnostic accuracy. EXPERIMENTAL DESIGN: A prospective single-center study examined 121 SRH images from 84 patients with unclear intracranial lesions undergoing stereotactic brain biopsy. Unprocessed, label-free samples were imaged using a portable fiber laser Raman scattering microscope. Three deep learning models were tested to (i) identify tumorous/nontumorous tissue as qualitative biopsy control; (ii) subclassify into high-grade glioma (central nervous system World Health Organization grade 4), diffuse low-grade glioma (central nervous system World Health Organization grades 2-3), metastases, lymphoma, or gliosis; and (iii) molecularly subtype IDH and 1p/19q statuses of adult-type diffuse gliomas. Model predictions were evaluated against frozen section analysis and final neuropathologic diagnoses. RESULTS: The first model identified tumorous/nontumorous tissue with 91.7% accuracy. Sample size on slides impacted accuracy in brain tumor subclassification (81.6%, κ = 0.72 frozen section; 73.9%, κ = 0.61 second model), with SRH images being smaller than hematoxylin and eosin images (4.1 ± 2.5 mm2 vs. 16.7 ± 8.2 mm2, P < 0.001). SRH images with more than 140 high-quality patches and a mean squeezed sample of 5.26 mm2 yielded 89.5% accuracy in subclassification and 93.9% in molecular subtyping of adult-type diffuse gliomas. CONCLUSIONS: Artificial intelligence-based SRH image analysis is non-inferior to frozen section analysis in detecting and subclassifying brain tumors during small stereotactic-guided biopsies once a critical squeezed sample size is reached. Beyond frozen section analysis, it enables valid molecular glioma subtyping, allowing faster treatment decisions in the future; however, refinement is needed for long-term application.

Fast intraoperative detection of primary CNS lymphoma and differentiation from common CNS tumors using stimulated Raman histology and deep learning.

Accurate intraoperative diagnosis is crucial for differentiating between primary CNS lymphoma (PCNSL) and other CNS entities, guiding surgical decision-making, but represents significant challenges due to overlapping histomorphological features, time constraints, and differing treatment strategies. We combined stimulated Raman histology (SRH) with deep learning to address this challenge. We imaged unprocessed, label-free tissue samples intraoperatively using a portable Raman scattering microscope, generating virtual H&E-like images within less than three minutes. We developed a deep learning pipeline called RapidLymphoma based on a self-supervised learning strategy to (1) detect PCNSL, (2) differentiate from other CNS entities, and (3) test the diagnostic performance in a prospective international multicenter cohort and two additional independent test cohorts. We trained on 54,000 SRH patch images sourced from surgical resections and stereotactic-guided biopsies, including various CNS tumor/non-tumor lesions. Training and test data were collected from four tertiary international medical centers. The final histopathological diagnosis served as ground-truth. In the prospective test cohort of PCNSL and non-PCNSL entities (n=160), RapidLymphoma achieved an overall balanced accuracy of 97.81% ±0.91, non-inferior to frozen section analysis in detecting PCNSL (100% vs. 78.94%). The additional test cohorts (n=420, n=59) reached balanced accuracy rates of 95.44% ±0.74 and 95.57% ±2.47 in differentiating IDH-wildtype diffuse gliomas and various brain metastasis from PCNSL. Visual heatmaps revealed RapidLymphoma's capabilities to detect class-specific histomorphological key features. RapidLymphoma is valid and reliable in detecting PCNSL and differentiating from other CNS entities within three minutes, as well as visual feedback in an intraoperative setting. This leads to fast clinical decision-making and further treatment strategy planning.

Mapping the hand, foot and face representations in the primary motor cortex - retest reliability of neuronavigated TMS versus functional MRI.

INTRODUCTION: Functional magnetic resonance imaging (fMRI) is a frequently used non-invasive mapping technique for investigating the human motor system. Recently, neuronavigated transcranial magnetic stimulation (nTMS) has been established as an alternative approach. We here compared the test-retest reliability of both mapping techniques with regard to the cortical representations of the hand, leg, face and tongue areas. METHODS: Ten healthy subjects were examined three times (intervals: 3-5days/21-35days) with fMRI and nTMS. Motor-evoked potentials were recorded from the abductor pollicis brevis, plantaris, mentalis and the tongue muscles. The same muscles were activated in an fMRI motor task. Euclidean distances (ED) between hotspots and centers of gravity (CoG) were computed for the respective somatotopic representations. Furthermore, spatial reliability was tested by intersession overlap volumes (OV) and voxel-wise intraclass correlations (ICC). RESULTS: Feasibility of fMRI was 100% for all body parts and sessions. In contrast, nTMS was feasible in all sessions and subjects only for the hand area, while mappings of the foot (90%), face (70%) and tongue representations (40%) remained incomplete in several subjects due to technical constraints and co-stimulation artifacts. On average, the mean ED of the hotspots was better for fMRI (6.2±1.1mm) compared to nTMS (10.8±1.9mm) while stability of CoG was similar for both methods. Peak voxel reliability (ICC) was high for both methods (>0.8), and there was no influence of inter-session intervals. In contrast, the reliability of mapping the spatial extent of the hand, foot, lips and tongue representations was poor to moderate for both fMRI and nTMS (OVs and ICC<50%). Especially nTMS mappings of the face and tongue areas yielded poor reliability estimates. CONCLUSION: Both methods are highly reliable when mapping the core region of a given target muscle, especially for the hand representation area. In contrast, mapping the spatial extent of a cortical representation area was only little reliable for both nTMS and fMRI. In summary, fMRI was better suited when mapping motor representations of the head, while nTMS showed equal reliability for mapping the hand and foot representation areas. Hence, both methods may well complement each other.

Local Recurrence and Development of Spinal Cord Syndrome during Follow-Up after Surgical Treatment of Metastatic Spine Disease.

BACKGROUND: Surgical decompression (SD), with or without posterior stabilization followed by radiotherapy, is an established treatment for patients with metastatic spinal disease with epidural spinal cord compression (ESCC). This study aims to identify risk factors for occurrence of neurological compromise resulting from local recurrence. METHODS: All patients who received surgical treatment for metastatic spinal disease at our center between 2011 and 2022 were included in this study. Cases were evaluated for tumor entity, surgical technique for decompression (decompression, hemilaminectomy, laminectomy, corpectomy) neurological deficits, grade of ESCC, time interval to radiotherapy, and perioperative complications. RESULTS: A total of 747 patients were included in the final analysis, with a follow-up of 296.8 days (95% CI (263.5, 330.1)). During the follow-up period, 7.5% of the patients developed spinal cord/cauda syndrome (SCS). Multivariate analysis revealed prolonged time (>35 d) to radiation therapy as a solitary risk factor (p < 0.001) for occurrence of SCS during follow-up. CONCLUSION: Surgical treatment of spinal metastatic disease improves patients' quality of life and Frankel grade, but radiation therapy needs to be scheduled within a time frame of a few weeks in order to reduce the risk of tumor-induced neurological compromise.

Pseudoprogression of Vestibular Schwannoma after Stereotactic Radiosurgery with Cyberknife®: Proposal for New Response Criteria.

(1) Background: Transient increase in volume of vestibular schwannomas (VS) after stereotactic radiosurgery (SRS) is common and complicates differentiation between treatment-related changes (pseudoprogression, PP) and tumor recurrence (progressive disease, PD). (2) Methods: Patients with unilateral VS (n = 63) underwent single fraction robotic-guided SRS. Volume changes were classified according to existing RANO criteria. A new response type, PP, with a >20% transient increase in volume was defined and divided into early (within the first 12 months) and late (>12 months) occurrence. (3) Results: The median age was 56 (range: 20-82) years, the median initial tumor volume was 1.5 (range: 0.1-8.6) cm3. The median radiological and clinical follow-up time was 66 (range: 24-103) months. Partial response was observed in 36% (n = 23), stable disease in 35% (n = 22) and PP in 29% (n = 18) of patients. The latter occurred early (16%, n = 10) or late (13%, n = 8). Using these criteria, no case of PD was observed. (4) Conclusion: Any volume increase after SRS for vs. assumed to be PD turned out to be early or late PP. Therefore, we propose modifying RANO criteria for SRS of VS, which may affect the management of vs. during follow-up in favor of further observation.

Role of Decompressive Surgery in Neurologically Intact Patients with Low to Intermediate Intraspinal Metastatic Tumor Burden.

BACKGROUND: Surgical decompression (SD) followed by radiotherapy (RT) is superior to RT alone in patients with metastatic spinal disease with epidural spinal cord compression (ESCC) and neurological deficit. For patients without neurological deficit and low- to intermediate-grade intraspinal tumor burden, data on whether SD is beneficial are scarce. This study aims to investigate the neurological outcome of patients without neurological deficit, with a low- to intermediate-ESCC, who were treated with or without SD. METHODS: This single-center, multidepartment retrospective analysis includes patients treated for spinal epidural metastases from 2011 to 2021. Neurological status was assessed by Frankel grade, and intraspinal tumor burden was categorized according to the ESCC scale. Spinal instrumentation surgery was only considered as SD if targeted decompression was performed. RESULTS: ESCC scale was determined in 519 patients. Of these, 190 (36.6%) presented with no neurological deficit and a low- to intermediate-grade ESCC (1b, 1c, or 2). Of these, 147 (77.4% were treated with decompression and 43 (22.65%) without. At last follow-up, there was no difference in neurological outcome between the two groups. CONCLUSIONS: Indication for decompressive surgery in neurologically intact patients with low-grade ESCC needs to be set cautiously. So far, it is unclear which patients benefit from additional decompressive surgery, warranting further prospective, randomized trials for this significant cohort of patients.

Intraoperative microscopic autofluorescence detection and characterization in brain tumors using stimulated Raman histology and two-photon fluorescence.

Introduction: The intrinsic autofluorescence of biological tissues interferes with the detection of fluorophores administered for fluorescence guidance, an emerging auxiliary technique in oncological surgery. Yet, autofluorescence of the human brain and its neoplasia is sparsely examined. This study aims to assess autofluorescence of the brain and its neoplasia on a microscopic level by stimulated Raman histology (SRH) combined with two-photon fluorescence. Methods: With this experimentally established label-free microscopy technique unprocessed tissue can be imaged and analyzed within minutes and the process is easily incorporated in the surgical workflow. In a prospective observational study, we analyzed 397 SRH and corresponding autofluorescence images of 162 samples from 81 consecutive patients that underwent brain tumor surgery. Small tissue samples were squashed on a slide for imaging. SRH and fluorescence images were acquired with a dual wavelength laser (790 nm and 1020 nm) for excitation. In these images tumor and non-tumor regions were identified by a convolutional neural network that reliably differentiates between tumor, healthy brain tissue and low quality SRH images. The identified areas were used to define regions.of- interests (ROIs) and the mean fluorescence intensity was measured. Results: In healthy brain tissue, we found an increased mean autofluorescence signal in the gray (11.86, SD 2.61, n=29) compared to the white matter (5.99, SD 5.14, n=11, p<0.01) and in the cerebrum (11.83, SD 3.29, n=33) versus the cerebellum (2.82, SD 0.93, n=7, p<0.001), respectively. The signal of carcinoma metastases, meningiomas, gliomas and pituitary adenomas was significantly lower (each p<0.05) compared to the autofluorescence in the cerebrum and dura, and significantly higher (each p<0.05) compared to the cerebellum. Melanoma metastases were found to have a higher fluorescent signal (p<0.01) compared to cerebrum and cerebellum. Discussion: In conclusion we found that autofluorescence in the brain varies depending on the tissue type and localization and differs significantly among various brain tumors. This needs to be considered for interpreting photon signal during fluorescence-guided brain tumor surgery.

102 AI-Based Molecular Classification of Diffuse Gliomas using Rapid, Label-Free Optical Imaging.

INTRODUCTION: Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. Access to timely molecular diagnostic testing for brain tumor patients is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. METHODS: By combining stimulated Raman histology (SRH), a rapid, label-free, non-consumptive, optical imaging method, and deep learning-based image classification, we are able to predict the molecular genetic features used by the World Health Organization (WHO) to define the adult-type diffuse glioma taxonomy, including IDH-1/2, 1p19q-codeletion, and ATRX loss. We developed a multimodal deep neural network training strategy that uses both SRH images and large-scale, public diffuse glioma genomic data (i.e. TCGA, CGGA, etc.) in order to achieve optimal molecular classification performance. RESULTS: One institution was used for model training (University of Michigan) and four institutions (NYU, UCSF, Medical University of Vienna, and University Hospital Cologne) were included for patient enrollment in the prospective testing cohort. Using our system, called DeepGlioma, we achieved an average molecular genetic classification accuracy of 93.2% and identified the correct diffuse glioma molecular subgroup with 91.5% accuracy within 2 minutes in the operating room. DeepGlioma outperformed conventional IDH1-R132H immunohistochemistry (94.2% versus 91.4% accuracy) as a first-line molecular diagnostic screening method for diffuse gliomas and can detect canonical and non-canonical IDH mutations. CONCLUSIONS: Our results demonstrate how artificial intelligence and optical histology can be used to provide a rapid and scalable alternative to wet lab methods for the molecular diagnosis of brain tumor patients during surgery.

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging.

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid (<90 seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas. DeepGlioma is trained using a multimodal dataset that includes stimulated Raman histology (SRH); a rapid, label-free, non-consumptive, optical imaging method; and large-scale, public genomic data. In a prospective, multicenter, international testing cohort of patients with diffuse glioma (n = 153) who underwent real-time SRH imaging, we demonstrate that DeepGlioma can predict the molecular alterations used by the World Health Organization to define the adult-type diffuse glioma taxonomy (IDH mutation, 1p19q co-deletion and ATRX mutation), achieving a mean molecular classification accuracy of 93.3 ± 1.6%. Our results represent how artificial intelligence and optical histology can be used to provide a rapid and scalable adjunct to wet lab methods for the molecular screening of patients with diffuse glioma.

Cerebrospinal fluid leaks following intradural spinal surgery-Risk factors and clinical management.

Background: Cerebrospinal fluid leakage (CSFL) following spinal durotomy can lead to severe sequelae. However, while several studies have investigated accidental spinal durotomies, the risk factors and influence of clinical management in planned durotomies remain unclear. Methods: We performed a retrospective analysis of all patients who underwent planned intradural spinal surgery at our institution between 2010 and 2020. Depending on the occurrence of a CSFL, patients were dichotomized and compared with respect to patient and case-related variables as well as dural closure technique, epidural drainage placement, and timing of mobilization. Results: A total of 351 patients were included. CSFL occurred in 4.8% of all cases. Surgical indication, tumor histology, location within the spine, previous intradural surgery, and medical comorbidities were not associated with an increased risk of CSFL development (all p > 0.1). Age [odds ratio (OR), 0.335; 95% confidence interval (CI), 0.105-1.066] and gender (OR, 0.350; 95% CI, 0.110-1.115) were not independently associated with CSFL development. There was no significant association between CSFL development and the dural closure technique (p = 0.251), timing of mobilization (p = 0.332), or placement of an epidural drainage (p = 0.321). Conclusion: CSFL following planned durotomy pose a relevant and quantifiable complication risk of surgery that should be factored in during preoperative patient counseling. Our data could not demonstrate superiority of any particular dural closure technique but support the safety of both early mobilization within 24 h postoperatively and epidural drainage with reduced or no force of suction.