Augmented surgical decision-making for glioblastoma: integrating AI tools into education and practice.

Surgical decision-making for glioblastoma poses significant challenges due to its complexity and variability. This study investigates the potential of artificial intelligence (AI) tools in improving "decision-making processes" for glioblastoma surgery. A systematic review of literature identified 10 relevant studies, primarily focused on predicting resectability and surgery-related neurological outcomes. AI tools, especially rooted in radiomics and connectomics, exhibited promise in predicting resection extent through precise tumor segmentation and tumor-network relationships. However, they demonstrated limited effectiveness in predicting postoperative neurological due to dynamic and less quantifiable nature of patient-related factors. Recognizing these challenges, including limited datasets and the interpretability requirement in medical applications, underscores the need for standardization, algorithm optimization, and addressing variability in model performance and then further validation in clinical settings. While AI holds potential, it currently does not possess the capacity to emulate the nuanced decision-making process utilized by experienced neurosurgeons in the comprehensive approach to glioblastoma surgery.

Focused ultrasound as a treatment modality for gliomas.

Ultrasound waves were initially used as a diagnostic tool that provided critical insights into several pathological conditions (e.g., gallstones, ascites, pneumothorax, etc.) at the bedside. Over the past decade, advancements in technology have led to the use of ultrasound waves in treating many neurological conditions, such as essential tremor and Parkinson's disease, with high specificity. The convergence of ultrasound waves at a specific region of interest/target while avoiding surrounding tissue has led to the coined term "focused ultrasound (FUS)." In tumor research, ultrasound technology was initially used as an intraoperative guidance tool for tumor resection. However, in recent years, there has been growing interest in utilizing FUS as a therapeutic tool in the management of brain tumors such as gliomas. This mini-review highlights the current knowledge surrounding using FUS as a treatment modality for gliomas. Furthermore, we discuss the utility of FUS in enhanced drug delivery to the central nervous system (CNS) and highlight promising clinical trials that utilize FUS as a treatment modality for gliomas.

Antibody Conjugated Nano-Enabled Drug Delivery Systems Against Brain Tumors.

The use of antibody-conjugated nanoparticles for brain tumor treatment has gained significant attention in recent years. Nanoparticles functionalized with anti-transferrin receptor antibodies have shown promising results in facilitating nanoparticle uptake by endothelial cells of brain capillaries and post-capillary venules. This approach offers a potential alternative to the direct conjugation of biologics to antibodies. Furthermore, studies have demonstrated the potential of antibody-conjugated nanoparticles in targeting brain tumors, as evidenced by the specific binding of these nanoparticles to brain cancer cells. Additionally, the development of targeted nanoparticles designed to transcytoses the blood-brain barrier (BBB) to deliver small molecule drugs and therapeutic antibodies to brain metastases holds promise for brain tumor treatment. While the use of nanoparticles as a delivery method for brain cancer treatment has faced challenges, including the successful delivery of nanoparticles to malignant brain tumors due to the presence of the BBB and infiltrating cancer cells in the normal brain, recent advancements in nanoparticle-mediated drug delivery systems have shown potential for enhancing the efficacy of brain cancer therapy. Moreover, the development of brain-penetrating nanoparticles capable of distributing over clinically relevant volumes when administered via convection-enhanced delivery presents a promising strategy for improving drug delivery to brain tumors. In conclusion, the use of antibody-conjugated nanoparticles for brain tumor treatment shows great promise in overcoming the challenges associated with drug delivery to the brain. By leveraging the specific targeting capabilities of these nanoparticles, researchers are making significant strides in developing effective and targeted therapies for brain tumors.

Microsurgical anatomy of the olfactory filaments in the nasal mucosa.

OBJECTIVE: The aim of this study was to examine the distribution of olfactory filaments (OFs) in the nasal mucosa to facilitate preservation of olfactory function in endonasal approaches and preparation of a nasoseptal flap. METHODS: One formalin-fixed and 9 fresh cadaveric silicone-injected specimens with 20 total sides were studied to measure the distance of the OFs to the anatomical landmarks and compare the OF presence in the nasal septum mucosa (NSM) and ethmoidal mucosa (EM). RESULTS: The mean distance from the first to the last OF was 19.37 ± 2.16 mm in the NSM and 23.44 ± 5.42 mm in the EM. The NSM had a mean of 7.55 ± 1.31 OFs and the EM had 14.3 ± 1.78. Average OF lengths were measured at 6.44 ± 1.48 (range 3.75-12.40) mm in the NSM and 8.05 ± 1.76 (range 4.14-13.20) mm in the EM. The mean values of the EM measurements were compared with those of the NSM; the number of OFs, the distance between the first and last OF, the average OF length, and the number of OFs between anterior and posterior ethmoidal arteries in the NSM were significantly less (p < 0.05) than those in the EM. The distance between the first OF to the nasal bone on the NSM was greater than on the EM. CONCLUSIONS: Compared with the EM, the OFs are significantly fewer in number and smaller in size in the NSM. The uppermost edge of the nasoseptal flap incision in the NSM might be safer to start below 12 mm from the cribriform plate for OF protection.