Protoporphyrin IX in serum of high-grade glioma patients: A novel target for disease monitoring via liquid biopsy.

High-grade gliomas (HGG) carry a dismal prognosis. Diagnosis comprises MRI followed by histopathological evaluation of tissue; no blood biomarker is available. Patients are subjected to serial MRIs and, if unclear, surgery for monitoring of tumor recurrence, which is laborious. MRI provides only limited diagnostic information regarding the differentiation of true tumor progression from therapy-associated side effects. 5-aminolevulinic acid (5-ALA) is routinely used for induction of protoporphyrin IX (PpIX) accumulation in malignant glioma tissue, enabling improved tumor visualization during fluorescence-guided resection (FGR). We investigated whether PpIX can also serve as a serum HGG marker to monitor relapse. Patients (HGG: n = 23 primary, pHGG; n = 5 recurrent, rHGG) undergoing FGR received 5-ALA following standard clinical procedure. The control group of eight healthy volunteers (HCTR) also received 5-ALA. Serum was collected before and repeatedly up to 72 h after drug administration. Significant PpIX accumulation in HGG was observed after 5-ALA administration (ANOVA: p = 0.005, post-hoc: HCTR vs. pHGG p = 0.029, HCTR vs. rHGG p = 0.006). Separation of HCTR from pHGG was possible when maximum serum PpIX levels were reached (CI95% of tMax). ROC analysis of serum PpIX within CI95% of tMax showed successful classification of HCTR and pHGG (AUCROC 0.943, CI95% 0.884-1.000, p < 0.001); the optimal cut-off for diagnosis was 1275 pmol PpIX/ml serum, reaching 87.0% accuracy, 90.5% positive predictive and 84.0% negative predictive value. Baseline PpIX level was similar in patient and control groups. Thus, 5-ALA is required for PpIX induction, which is safe at the standard clinical dosage. PpIX is a new target for liquid biopsy in glioma. More extensive clinical studies are required to characterize its full potential.

Towards machine learning-based quantitative hyperspectral image guidance for brain tumor resection.

BACKGROUND: Complete resection of malignant gliomas is hampered by the difficulty in distinguishing tumor cells at the infiltration zone. Fluorescence guidance with 5-ALA assists in reaching this goal. Using hyperspectral imaging, previous work characterized five fluorophores' emission spectra in most human brain tumors. METHODS: In this paper, the effectiveness of these five spectra was explored for different tumor and tissue classification tasks in 184 patients (891 hyperspectral measurements) harboring low- (n = 30) and high-grade gliomas (n = 115), non-glial primary brain tumors (n = 19), radiation necrosis (n = 2), miscellaneous (n = 10) and metastases (n = 8). Four machine-learning models were trained to classify tumor type, grade, glioma margins, and IDH mutation. RESULTS: Using random forests and multilayer perceptrons, the classifiers achieve average test accuracies of 84-87%, 96.1%, 86%, and 91% respectively. All five fluorophore abundances vary between tumor margin types and tumor grades (p < 0.01). For tissue type, at least four of the five fluorophore abundances are significantly different (p < 0.01) between all classes. CONCLUSIONS: These results demonstrate the fluorophores' differing abundances in different tissue classes and the value of the five fluorophores as potential optical biomarkers, opening new opportunities for intraoperative classification systems in fluorescence-guided neurosurgery.

Complete surgical removal of some primary brain tumors is difficult because it can be hard to distinguish the edge of the tumor. We evaluated whether the edges of tumors and the tumor type and grade can be more accurately determined if the tumor is imaged using many different wavelengths of light. We used measurements taken from the tumors of people undergoing brain tumor surgery and developed machine-learning algorithms that could predict where the edge of the tumor was. The methods could also provide information about the type and grade of the brain tumor. These classifications could potentially be used during operations to remove brain tumors more accurately and thus improve the outcome of surgery for people with brain tumors.

The importance of social networks in neurosurgery training in low/middle income countries.

Introduction: Neurosurgery is evolving with new techniques and technologies, relies heavily on high-quality education and training. Social networks like Twitter, Facebook, Instagram and LinkedIn have become integral to this training. These platforms enable sharing of surgical experiences, fostering global knowledge-sharing and collaboration among neurosurgeons. Virtual conferences and courses are accessible, enhancing learning regardless of location. While these networks offer real-time communication and collaborative opportunities, they also pose challenges like the spread of misinformation and potential distractions. According to the PICO format, the target population (P) for the purpose of this paper are medical students, neurosurgical residents and consultants on the role of social media (I) in neurosurgery among Low-Middle income countries (C) with the main outcome to understand the collaborative domain of learning. Material and method: This cross-sectional survey, conducted in June-July 2023, involved 210 medical students, neurosurgery residents, fellows, and practicing neurosurgeons from low and middle-income countries. A structured questionnaire assessed social network usage for neurosurgery training, covering demographic details, usage frequency, and purposes like education, collaboration, and communication. Participants rated these platforms' effectiveness in training on a 1-5 scale. Data collection employed emails, social media groups, and direct messaging, assuring respondent anonymity. The survey aimed to understand and improve social networks' use in neurosurgery, focusing on professional development, challenges, and future potential in training. Results: In a survey of 210 participants from low and middle-income countries, 85.5% were male, 14.5% female, with diverse roles: 42.9% neurosurgery residents, 40% practicing neurosurgeons, 14.6% medical students, and 2.4% other healthcare professionals. Experience ranged from 0 to 35 years, with Mexico, Nigeria, and Kenya being the top participating countries. Most respondents rated neurosurgery training resources in their countries as poor or very poor. 88.7% used social media professionally, predominantly WhatsApp and YouTube. Content focused on surgical videos, research papers, and webinars. Concerns included information quality and data privacy. Interactive case discussions, webinars, and lectures were preferred resources, and most see a future role for social media in neurosurgery training. Conclusions: Our study underscores the crucial role of social media in neurosurgery training and practice in low and middle-income countries (LMICs). Key resources include surgical videos, research papers, and webinars. While social media offers a cost-effective, global knowledge-sharing platform, challenges like limited internet access, digital literacy, and misinformation risks remain significant in these regions.

Insights from a multicenter study on adult H3 K27M-mutated glioma: Surgical resection's limited influence on overall survival, ATRX as molecular prognosticator.

BACKGROUND: H3 K27M-mutated gliomas were first described as a new grade 4 entity in the 2016 World Health Organization classification. Current studies have focused on its typical appearance in children and young adults, increasing the need to better understand the prognostic factors and impact of surgery on adults. Here, we report a multicentric study of this entity in adults. METHODS: We included molecularly confirmed H3 K27M-mutated glioma cases in patients ≥ 18 years diagnosed between 2016 and 2022. Clinical, radiological, and surgical features were analyzed. Univariate and multivariate analyses were performed to identify prognostic factors. RESULTS: Among 70 patients with a mean age of 36.1 years, the median overall survival (OS) was 13.6 ±â€…14 months. Gross-total resection was achieved in 14.3% of patients, whereas 30% had a subtotal resection and 54.3% a biopsy. Tumors located in telencephalon/diencephalon/myelencephalon were associated with a poorer OS, while a location in the mesencephalon/metencephalon showed a significantly longer OS (8.7 vs. 25.0 months, P = .007). Preoperative Karnofsky-Performance Score (KPS) ≤ 80 showed a reduced OS (4.2 vs. 18 months, P = .02). Furthermore, ATRX loss, found in 25.7%, was independently associated with an increased OS (31 vs. 8.3 months, P = .0029). Notably, patients undergoing resection showed no survival benefit over biopsy (12 vs. 11 months, P = .4006). CONCLUSIONS: The present study describes surgical features of H3 K27M-mutated glioma in adulthood in a large multicentric study. Our data reveal that ATRX status, location and KPS significantly impact OS in H3 K27M-mutated glioma. Importantly, our dataset indicates that resection does not offer a survival advantage over biopsy.

Localization of protoporphyrin IX during glioma-resection surgery via paired stimulated Raman histology and fluorescence microscopy.

The most widely used fluorophore in glioma-resection surgery, 5-aminolevulinic acid (5-ALA), is thought to cause the selective accumulation of fluorescent protoporphyrin IX (PpIX) in tumour cells. Here we show that the clinical detection of PpIX can be improved via a microscope that performs paired stimulated Raman histology and two-photon excitation fluorescence microscopy (TPEF). We validated the technique in fresh tumour specimens from 115 patients with high-grade gliomas across four medical institutions. We found a weak negative correlation between tissue cellularity and the fluorescence intensity of PpIX across all imaged specimens. Semi-supervised clustering of the TPEF images revealed five distinct patterns of PpIX fluorescence, and spatial transcriptomic analyses of the imaged tissue showed that myeloid cells predominate in areas where PpIX accumulates in the intracellular space. Further analysis of external spatially resolved metabolomics, transcriptomics and RNA-sequencing datasets from glioblastoma specimens confirmed that myeloid cells preferentially accumulate and metabolize PpIX. Our findings question 5-ALA-induced fluorescence in glioma cells and show how 5-ALA and TPEF imaging can provide a window into the immune microenvironment of gliomas.