**4. The Renaissance of "Functionally" Guided Surgery: Intraoperative Neuromonitoring**

*4.1. Historical Overview and Technological Breakthroughs*

The history of Intraoperative Neuromonitoring (IONM) traces back to 1898, when Dr. Fedor Krause in Berlin used monopolar faradic stimulation during an acoustic nerve neurectomy. Krause's work marked the earliest instance of visual observation of nerve activity during surgery. The technique gained significant momentum in the 1960s, when it was adapted for thyroid surgeries by Flisberg and Lindholm, and also for parotid and ear surgeries through facial nerve stimulators developed by Parsons and Hilger [36].

In contemporary medical practice, IONM has become a staple in various surgical disciplines, especially those involving close proximity to critical nerves. Predominant among these are thyroid surgeries—where the vagus and recurrent laryngeal nerves are monitored—parotidectomy, and surgeries of the posterior cranial fossa where facial nerve monitoring is crucial. During these operations, the surgeon employs a stimulator probe to accurately identify and differentiate the nerve from surrounding tissues. When the probe is placed onto the nerve, a circuit is closed that triggers either visual or auditory cues each time the nerve is contacted. This type of monitoring is often referred to as intermittent IONM (iIONM) [37].

IONM has evolved from its humble beginnings to become an integral part of modern surgery. It provides surgeons with real-time feedback, enhancing surgical precision and thereby potentially reducing post-operative complications. Its applications have been widely adopted in surgeries that risk nerve injury, making it a standard practice in many medical institutions.

#### *4.2. Mechanisms, Modalities, and the Paradigm Shift towards Real-Time Functional Feedback*

Brainstem Auditory Evoked Potentials (BAEPs) are bioelectric neural activities triggered by the stimulation of the vestibulocochlear nerve [38]. These potentials are particularly challenging to distinguish from the background electrical activity of the brain due to their relatively small amplitude [37,38]. To separate the BAEPs from this "noise", thousands of samples of the electric stimulus are gathered and averaged, allowing for a clearer identification of the auditory evoked potential.

In BAEP recordings, data are collected from multiple points along the vestibular nerve pathway as it moves from the peripheral to the central nervous system [39,40]. The peaks in these recordings are categorized as Waves I through V, which correspond to different anatomical locations—from the peripheral cochlear nerve to the inferior colliculus [41,42].

During BAEP monitoring, electrodes are placed on the scalp and earlobes. An auditory stimulator then emits acoustic clicks to the ear being operated on, delivered through an earphone-transducer setup. The electrical pulse rate for these clicks is typically set between 20 to 50 per second. Before the operation starts, the stimulus intensity, usually measured in decibels, is adjusted to a level where the patient can hear the clicks. The final stimulus is then set at an intensity a few decibels higher than this initial threshold. To ensure focused monitoring, white noise is applied to the contralateral ear at a lower intensity to mask its response [41,42].

BAEPs are a critical tool for monitoring neural activity related to auditory functions during surgical procedures. They allow for real-time tracking of auditory pathway integrity, which is particularly useful in surgeries where the auditory nerve might be at risk. This method is complex and requires precise setup and interpretation, but its importance in safeguarding auditory function during surgical procedures is well recognized [43,44].

The monitoring of somatosensory spinal pathways, specifically the dorsal columnmedial lemniscus, relies on subcortical and cortical responses to continuous electrical stimulation of peripheral nerves such as the tibial, peroneal, ulnar, or median nerve. This method of Intraoperative Neuromonitoring is commonly used and easy to implement, having no contraindications. It can be particularly useful for monitoring the posterior spine approach in spinal deformity surgeries, boasting a sensitivity range of 25–92% and a specificity of 96–100% [45]. However, it does have limitations, such as a time lag (1–20 min) in data interpretation due to signal averaging, making it possible for an injury to go undetected until it becomes irreversible. It is also less effective for monitoring patients with pre-existing neurologic deficits or in situations involving isolated motor pathway or nerve root injuries, which are better detected by Motor Evoked Potentials (MEPs) or Electromyography (EMG) [46].

MEPs are particularly sensitive for monitoring motor pathways in the anterior or central regions of the spinal cord and nerve roots. They serve as highly reliable indicators of corticospinal tract injuries and have proven especially useful for detecting spinal cord ischemia during spinal deformity correction [45]. This form of monitoring involves real-time, intermittent stimulation of the motor cortex and subsequent recording at muscles, preferably those rich in corticospinal tract innervations such as distal limb muscles. Transcranial stimulation can be either magnetic or, more commonly in surgical settings, electric (Transcranial Electric Motor Evoked Potentials or TceMEP). The electromyography signals, also known as Compound Motor Action Potentials (CMAP), are typically acquired through needle electrodes inserted bilaterally into the upper limbs. These serve as controls to differentiate systemic, anesthesia, and positioning-related changes [47].

Both somatosensory and motor evoked potentials offer valuable insights into neural integrity during spinal surgeries, albeit with distinct advantages and limitations. While somatosensory monitoring is generally easier to implement and can provide information about both sensory and motor pathways, MEPs offer real-time, direct monitoring of motor pathways, making them invaluable in surgeries where motor function is at high risk.

#### *4.3. Neuromonitoring in Diverse Pathologies: Customized Approaches for Tailored Surgical Interventions*

Direct stimulation of the facial nerve during posterior cranial fossa surgery has been explored by Amano, who used a ball-type electrode to stimulate the root exit zone of the facial nerve. This method was shown to be potentially useful for assessing the state of the facial nerve during surgery. By examining variables such as amplitude preservation ratio and the last maximal amplitude, the method could predict the likelihood of facial nerve palsy postoperatively according to the House–Brackmann (HB) grade [48].

Multipulse Transcranial Electric Stimulation (TES) provides another approach to continuous monitoring of the facial nerve. A cup electrode placed on the skull sends out clusters of electrical pulses that stimulate the corticobulbar pathway, allowing real-time monitoring of facial nerve function through facial nerve muscle motor evoked potentials (FNMEP). This method has been found to accurately predict the postoperative state of the facial nerve, with patients maintaining at least 50% of the baseline amplitude generally experiencing no more than mild deterioration in facial nerve function postoperatively [49].

In contrast to active continuous Intraoperative Neuromonitoring (acIONM), there are methods described as passive continuous IONM (pcIONM) that do not involve direct stimulation but rather analyze natural discharge patterns that occur during the surgical procedure. Free-running electromyography (EMG) is one such method used to monitor the facial nerve during neurosurgery. In this technique, patterns such as spikes, bursts, and trains in the EMG signal are analyzed to provide insights into nerve function. Prass and Lüders described different types of EMG signal patterns such as spikes, bursts, and trains, which they observed during posterior fossa surgeries on 30 patients [50].

Multiple methods exist for intraoperatively monitoring the facial nerve during posterior cranial fossa surgery. Each has its unique advantages and disadvantages. Direct stimulation offers the ability to assess the facial nerve's function at specific times during the procedure, while continuous methods such as TES allow for ongoing, real-time monitoring. Passive methods such as free-running EMG offer a non-intrusive way to monitor the nerve by analyzing its natural activity during surgery.

Despite advances in Intraoperative Neuromonitoring, the retention rates for vestibulocochlear nerve function are not as favorable as those for the facial nerve. This discrepancy could arise from the intrinsic challenges of preserving auditory function, especially when dealing with large tumors and those that have extensive infiltration into the cerebellopontine angle [49–51].

In the context of spine surgery, the choice of monitoring modality depends on the approach used and the specific risks involved. For posterior approaches, somatosensory evoked potentials (SSEPs) may be sufficient. However, for anterior approaches, transcranial motor evoked potentials (MEPs) are typically recommended due to the risk of anterior spinal artery syndrome. Where nerve root or spinal cord deficits are a major concern, additional modalities such as spontaneous and triggered electromyography may be valuable. Multi-modal IONM is highly recommended for procedures such as spine deformity surgery or those involving intradural tumors [52,53]. Anesthesia should be adjusted to allow for the

best possible IONM recordings, with specific anesthetic agents contraindicated for certain types of monitoring [54].

IONM is not just limited to spine or cranial surgeries. It is also used in a variety of other surgical fields such as vascular and cardiothoracic. Its utility extends to preventing perioperative peripheral nerve injury (PPNI), which could occur due to excess mechanical pressure and torsion on the limbs and neck during surgery [55].

The use of IONM is crucial for optimizing outcomes in various types of surgery. While it has shown great promise, there is still room for improvement, particularly in monitoring the vestibulocochlear nerve. The choice of monitoring technique should be tailored to the specific surgical approach and the associated risks, and multi-modal IONM is often recommended for complex cases.

#### **5. The Digital Surgeon: Technological Synergies in Cranial Base Surgery**

*5.1. Endoscopy in the New Era: Advanced Imaging, Robotic Assistance, and Augmented Reality Overlays*

Advancements in skull base surgery are increasingly leveraging the capabilities of virtual reality (VR) and augmented reality (AR). For instance, color-coded stereotactic VR models can be custom-tailored for individual surgical cases, providing a simulated operating field for surgeons and trainees [56]. These models offer invaluable opportunities for surgical education and preoperative simulations. Furthermore, VR technology can be integrated into real-time operative settings by overlaying 3D images onto microscopic or endoscopic views, thus enhancing spatial navigation capabilities for the surgeon [57].

AR technology appears to offer particular benefits to less experienced medical professionals. These systems serve not just as educational tools but also as potential substitutes for existing neural navigation technology. AR can offer both contextual information about underlying structures and direct patient perspectives, potentially revolutionizing conventional neural navigation systems [58].

Beyond surgery, AR also has applications in non-surgical and clinical management at the skull base. For example, it is used for ablating damaged nasal tissue and offers guidance on basic surgical plans and navigational protocols [59]. In cranio-maxillofacial procedures, AR plays a significant role in reconstructing cheekbones and offering data on the underlying structure, albeit without the capability for real-time modifications [60]. Many AR applications superimpose precollected, immersive data onto real endoscopic camera images. However, fields that lie outside the endoscopic view remain hidden to the medical team, necessitating further adaptations to fully realize the technology's potential.

Moreover, the application of Augmented Reality in clinical settings, particularly in the management of base-of-the-skull pathologies, has been gaining significant attention in the medical community, as evidenced by multiple academic conferences exploring its potential [59,60]. A specific clinical model has been proposed, offering an extended observational perspective of the area under examination [61]. In this model, endoscopic images are displayed centrally, while the projection external to the endoscopic field of view is rendered virtually, utilizing pre-existing computerized tomography data. Such an integrated AR framework suggests that, following technological advancements and methodological refinements, AR applications may become increasingly prevalent across a broader spectrum of clinical scenarios necessitating heightened alertness and precision [62].

When it comes to the design of an ideal AR device for clinical applications, certain rigorous criteria must be met to ensure its functional efficacy and safety. The system should feature a focus marker and device alignment capabilities that are intuitive and minimally intrusive, particularly for the medical professional using it. Calibration adjustments should be undertaken before the initiation of the clinical procedure to minimize undue burden or cognitive load on the healthcare provider [63].

Furthermore, conventional imaging techniques that focus solely on two-dimensional visual data may suffer from limitations in perceived depth, thereby potentially compromising the practitioner's situational awareness and decision making accuracy. To mitigate such

limitations, it is advisable to incorporate depth cues to enhance the perceptual veracity of the rendered images [64]. Additionally, in applications where virtual 3D objects are superimposed onto endoscopic images, it becomes imperative to maintain parallax when the viewing position changes in order to preserve spatial relationships and depth perception.

In terms of data presentation, meticulous attention must be devoted to the structural layout of the AR interface. Inadequate design considerations can obscure critical information or induce visual discomfort, thereby diminishing the user experience and potentially compromising clinical outcomes. Therefore, it is essential to engage in an iterative design process, incorporating user feedback and empirical data, to optimize the AR interface and data presentation for the specialized needs of clinical practice.

#### *5.2. Data-Driven Neurosurgery: Machine Learning, AI-Assisted Diagnosis, and Surgical Planning*

The application of Radiomics in oncological diagnostics has emerged as a transformative approach in recent years, particularly in the preoperative assessment of various neoplastic conditions including prostate cancer, lung cancer, and an array of brain tumors such as gliomas, meningiomas, and brain metastases [63–65]. Traditional diagnostic methodologies that rely predominantly on qualitative assessments made by radiologists based on "visible" features, Radiomics facilitates the quantitative extraction of high-dimensional features as parametric data from radiographic images [66,67].

The incorporation of machine learning algorithms further enhances the analytical capabilities of Radiomics, offering unprecedented insights into the pathophysiological characteristics of lesions that are otherwise challenging to discern through conventional visual inspection [68,69]. Several studies have demonstrated the utility of Radiomics-based machine learning in the differential diagnosis of various brain tumors, thus indicating its prospective application in clinical decision making [70].

In the feature selection domain, Least Absolute Shrinkage and Selection Operator (LASSO) has been noted for its effectiveness in handling high-dimensional Radiomics data, particularly when the sample sizes are relatively limited [71,72]. LASSO distinguishes itself by its ability to avoid overfitting, making it an optimal choice for robust feature selection in Radiomics analyses.

Additionally, Linear Discriminant Analysis (LDA) serves as another valuable machine learning classification algorithm tailored for Radiomics applications. LDA seeks to identify and delineate boundaries around clusters belonging to distinct classes and projects these statistical entities into a lower-dimensional space to maximize class discriminatory power. Notably, it has been reported to retain substantial class discrimination information while reducing dimensionality [73–75].

Radiomics has extended its utility beyond diagnostic applications to prognostic evaluations, as exemplified in its role in both the diagnosis and treatment control rate prediction for chordoma [76]. Chordoma, a disease notorious for its refractory nature necessitating multiple surgical interventions and radiotherapeutic treatments, poses unique challenges for sustained disease control. In this context, Radiomic models built on features describing both the morphological shape and the genomic heterogeneity of the tumor have demonstrated superior performance in predicting the effectiveness of radiotherapy for tumor control. Such predictive capabilities underscore the potential benefits of Radiomics in enabling more targeted, efficient treatment regimens for diseases such as chordoma, thereby potentially reducing the need for repetitive, invasive procedures.

In another application, Radiomics-based machine learning algorithms have been shown to assist significantly in the preoperative differential diagnosis between germinoma and choroid plexus papilloma [77]. These two types of primary intracranial tumors often present with overlapping clinical manifestations and radiological features, yet they require markedly different treatment modalities. In addressing this diagnostic conundrum, highperformance prediction models have been developed using sophisticated feature selection methodologies and classifiers. These models suggest that Radiomics can offer a noninvasive diagnostic strategy with substantial reliability.

Notably, the application of Radiomics and machine learning in these scenarios holds the promise of revolutionizing the approach to image-based diagnosis and personalized clinical decision making. By leveraging advanced computational techniques to analyze complex, high-dimensional radiographic data, Radiomics provides a more nuanced understanding of tumor characteristics and treatment responses. This computational approach thereby opens avenues for more accurate, timely, and individualized therapeutic strategies, significantly enhancing the quality of patient care in oncological settings.

In the realm of skull base neurosurgery, machine learning (ML) methods, including neural network models (NNs) (Figure 2), have been rigorously applied to a comprehensive, multi-center, prospective database to predict the occurrence of Cerebrospinal Fluid Rhinorrhoea (CSFR) following endonasal surgical procedures [78]. The predictive capabilities of NNs surpass those of traditional statistical models and other ML techniques in accurately forecasting CSFR events. Notably, NNs have also revealed intricate relationships between specific risk factors and surgical repair techniques that influence CSFR, relationships that remained elusive when examined through conventional statistical approaches. As these predictive models continue to evolve through the integration of more extensive and granular datasets, refined NN architectures, and external validation processes, they hold the promise of significantly impacting future surgical decision making. Such next-generation models may provide invaluable support for more personalized patient counseling and tailored treatment plans. *Brain Sci.* **2023**, *13*, x FOR PEER REVIEW 13 of 28

**Figure 2.** Mechanisms of neural network processing are shown. Input layer refers to heterogenous data which will be analyzed by the neural network incorporated algorithms. Further, output information is obtained, offering new avenues for biomedical fields. **Figure 2.** Mechanisms of neural network processing are shown. Input layer refers to heterogenous data which will be analyzed by the neural network incorporated algorithms. Further, output information is obtained, offering new avenues for biomedical fields.

Regarding automated image segmentation in surgical navigation applications, although there is a high correlation between the automated segmentation and the anatomical landmarks in question, the Dice Coefficient (DC)—a measure commonly used to assess the performance of the segmentation task—was not deemed to be particularly high [79]. Various factors contribute to this finding, including the complexity of anatomical pathways, the absence of clearly delineated contours in certain regions, and inherent variations arising from manual segmentation. These limitations cast doubt on the utility of the DC Regarding automated image segmentation in surgical navigation applications, although there is a high correlation between the automated segmentation and the anatomical landmarks in question, the Dice Coefficient (DC)—a measure commonly used to assess the performance of the segmentation task—was not deemed to be particularly high [79]. Various factors contribute to this finding, including the complexity of anatomical pathways, the absence of clearly delineated contours in certain regions, and inherent variations arising

as a standalone metric for objectively evaluating the performance of this specific task.

In summary, the application of machine learning, and particularly neural networks, appears to be a game-changer in predicting complex clinical outcomes such as CSFR following skull base neurosurgery. Meanwhile, automated image segmentation remains a challenging task, warranting a more nuanced approach to performance assessment than merely relying on singular statistical measures such as the Dice Coefficient. These advancements signify not only the growing impact of computational methods in medicine but also the necessity for ongoing refinement and validation to ensure these techniques

meet the highest standards of clinical efficacy and safety.

**6. Radiosurgery and Radiotherapy: Harmonizing Precision and Efficacy** 

*6.1. An in-Depth Exploration of Radiosurgical Modalities: Gamma Knife, CyberKnife, and* 

Stereotactic radiosurgery has emerged as a pivotal treatment modality for various types of lateral skull base lesions, with perhaps its most significant impact being on the management of glomus jugulare tumors [80]. Many medical centers have adopted this approach as the first-line treatment for growing symptomatic tumors due to its lower

plications such as surgical navigation.

*Beyond* 

from manual segmentation. These limitations cast doubt on the utility of the DC as a standalone metric for objectively evaluating the performance of this specific task. However, the low average Hausdorff Distance (HD) on the testing dataset better encapsulates the high accuracy of the automated segmentation, bolstering its credibility for applications such as surgical navigation.

In summary, the application of machine learning, and particularly neural networks, appears to be a game-changer in predicting complex clinical outcomes such as CSFR following skull base neurosurgery. Meanwhile, automated image segmentation remains a challenging task, warranting a more nuanced approach to performance assessment than merely relying on singular statistical measures such as the Dice Coefficient. These advancements signify not only the growing impact of computational methods in medicine but also the necessity for ongoing refinement and validation to ensure these techniques meet the highest standards of clinical efficacy and safety.

#### **6. Radiosurgery and Radiotherapy: Harmonizing Precision and Efficacy**

*6.1. An In-Depth Exploration of Radiosurgical Modalities: Gamma Knife, CyberKnife, and Beyond*

Stereotactic radiosurgery has emerged as a pivotal treatment modality for various types of lateral skull base lesions, with perhaps its most significant impact being on the management of glomus jugulare tumors [80]. Many medical centers have adopted this approach as the first-line treatment for growing symptomatic tumors due to its lower morbidity compared to traditional surgical interventions, coupled with comparable rates of disease control.

Additionally, the efficacy of radiosurgery in treating skull base meningiomas has been well documented, with long-term follow-up data indicating impressive tumor growth control rates ranging from 92 to 98% [81]. While determining the optimal radiation dosage is critical, findings suggest that doses greater than 12 Gy to the tumor margin are essential for effective control. Suboptimal doses, specifically less than 12 Gy, have been associated with a significant tumor growth rate during one-year follow-up periods [82]. It is generally recommended that the minimum effective radiation dose for skull base meningiomas should be between 13 and 17 Gy, although the suitability of lower doses remains a topic of ongoing debate [83].

Importantly, some nuances exist within the treatment paradigm. For instance, Lee et al. noted that previously resected tumors might pose challenges in accurate radiological delineation due to postoperative changes such as meningeal enhancements or fat signals, which could be mistaken for tumor tissue [83]. Moreover, Zachenhofer and colleagues posited that tumor regrowth often occurs outside the targeted radiosurgical volume, a phenomenon possibly attributable to microscopic remnants of tumor cells within the adjacent dura mater that are not included in the radiosurgical target [84].

Stereotactic radiosurgery offers a promising avenue for managing various types of skull base tumors, including glomus jugulare and meningiomas, with both short-term and long-term efficacy. However, it is crucial to consider factors such as optimal radiation dosage and potential challenges related to the radiological delineation of previously resected tumors. These complexities underscore the necessity for personalized treatment strategies and underscore the importance of ongoing research to fine tune radiosurgical approaches for maximum clinical benefit.

The management of benign meningiomas using radiosurgery must be approached with caution given the potential for malignant transformation. up to 2% of benign meningiomas could transform into malignant forms, and others have found that 28.5% of recurrent benign meningiomas were actually atypical or anaplastic [83,84]. These statistics underline the importance of long-term monitoring and potential re-evaluation of treatment plans [85,86].

Radiosurgical interventions also present challenges related to cranial nerve sensitivity, most notably the optic and trigeminal nerves. The optic nerve is particularly vulnerable to radiation, requiring careful dose planning. Leber et al. suggested that doses below 10 Gy could be safely administered to the optic nerve without complications, but doses between

10–15 Gy carry a 26.5% risk of optic neuropathy [87]. Thus, tumors close to or compressing the optic apparatus are less amenable to radiosurgical treatment, as delivering an effective dose could jeopardize optic nerve function.

Various guidelines have been proposed for dosing the optic apparatus, with Morita et al. allowing for short segments to receive between 12–16 Gy [88], and Stafford et al. reporting no optic neuropathy with a 12 Gy dose [89]. Therefore, radiosurgery might be more appropriately indicated for tumors situated at least 5 mm away from the chiasm and optic nerve.

The trigeminal nerve also shows significant sensitivity to radiation, with various studies reporting the development of trigeminal neuropathy post-treatment. For example, Lee et al. found that 4% of their patients developed this condition, with a portion experiencing permanent deficits [83]. Moreover, Chang et al. reported that although 86% of patients initially experienced pain relief, about half suffered pain recurrence during the follow-up period [90]. Radiation doses exceeding 19 Gy were found to be associated with a high incidence of trigeminal neuropathy [88].

The utility and efficacy of radiosurgery for skull base meningiomas appear to be influenced by several factors including tumor size, dose, and fractionation. Single-session radiosurgery has been reported to yield a five-year actuarial tumor control rate of 88.6% for large skull base meningiomas (>8 cm<sup>3</sup> ). However, tumor control rates tend to decrease with increasing tumor volume, specifically tumoral volumes <sup>≥</sup> 14 cm<sup>3</sup> [91]. With a median dose of 10 Gy (ranging between 8–10 Gy), the five-year and ten-year tumor growth control rates were 78% and 70%, respectively. Notably, only 6% of patients experienced permanent radiation injury with an 84-month follow-up [92].

The CyberKnife® platform offers a technological advancement in frameless robotic radiosurgery, enabling high precision and conformal intracranial tumor targeting. It allows for easy fractionation of treatment, thereby minimizing toxicity, especially when adjacent organs-at-risk (OAR) have low radiation tolerance [93]. However, the outcomes for larger, malignant tumors remain less predictable, with both tumor size and type affecting the treatment outcome [94].

In the case of smaller, radiosensitive tumors such as vestibular schwannomas and meningiomas, radiosurgery has been largely effective with minimal acute toxicity. However, areas for improvement include symptom management and late morbidity. The presence of larger tumors, less optimal dose/fractionation, and other risk factors such as previous cranial radiotherapy can lead to increased treatment-related toxicity [95].

Given these findings, the focus for smaller radiosensitive tumors should be on optimizing dose prescription and fractionation schedules. Careful planning that includes vigilance over multiple dose indices for susceptible OAR may help minimize late toxicity and optimize functional preservation. For tumors of other pathological types, which tend to be larger and/or more radioresistant, initial efforts should aim at increasing local control while minimizing toxicity through optimized dose and fractionation scheduling.

In summary, while radiosurgery has shown promising outcomes for skull base meningiomas and other cranial tumors, there are challenges that need to be addressed. Tumor size, type, and proximity to critical structures such as OAR can impact the efficacy and safety of treatment. Consequently, individualized treatment plans, leveraging advanced technologies such as CyberKnife® and ongoing research, will be key to improving outcomes.

#### *6.2. Radiotherapy Advancements: Modulating Doses, Fractions, and Protocols for Optimal Tumor Control and Preservation of Neural Structures*

Fractionated stereotactic radiotherapy (FSRT) has emerged as another viable option for the treatment of large skull base meningiomas. Studies have shown that FSRT can offer five-year tumor growth control rates ranging between 93–96%. In terms of toxicity, late clinical toxicity has been reported to be relatively low, falling in the range of 1.6–5.5%. The treatment generally involves delivering radiation doses of 50–56.8 Gy for tumor volumes averaging between 35.4–52.5 cm<sup>3</sup> . The mean duration of follow-up in these studies was between 35–42 months [96].

In a more recent study that compared single-session gamma knife surgery (GKS) with fractionated GKS (FGKS) for meningiomas having a volume greater than 10 cm<sup>3</sup> , FGKS appeared to show a marginally higher overall five-year tumor control rate (92.9% for FGKS vs. 88.1% for single-session GKS). However, it is important to note that the difference in the control rates between the two groups was not statistically significant (*p* = 0.389). The mean tumor volume for the single-session GKS group was 15.2 cm<sup>3</sup> , while for the FGKS group, it was 21 cm<sup>3</sup> . The FGKS group also included 16 skull base meningiomas [97].

Fractionated radiation therapy, which involves daily treatments usually spanning several weeks, is a commonly employed strategy for treating certain types of tumors, including WHO grade I meningiomas that are located close to sensitive areas such as the optic chiasm or optic nerves [98]. This approach is backed by evidence showing that external beam radiation therapy (EBRT) can deliver effective doses that control the tumor while preserving visual function [99] (Table 1).

**Table 1.** Pertinent studies on the use of additional radiotherapy in managing WHO grade II and III meningiomas.



**Table 1.** *Cont.*

(TS = total survival, RFS = recurrence-free survival, EBRT = external beam radiation therapy, LRR = local recurrence rate, PTR = partial resection (STR), TR = total resection (GTR), FRT = Fractionated radiotherapy (RT), SRS = stereotactic therapy (radiosurgery), GKR = Gamma Knife radiosurgery).

In cases where meningiomas affect the optic nerve sheath, EBRT is the treatment of choice. Many patients have reported vision improvement following this treatment. Remarkably, no other treatment modalities, including surgical interventions, have been shown to improve vision to the same extent as radiation therapy (RT) for this specific patient group. Therefore, surgical decompression is typically reserved for patients with intracranial extensions and rapidly deteriorating conditions [116].

When it comes to cavernous sinus and petroclival meningiomas, radiation therapy is often the preferred treatment option, either as a primary treatment or as an adjunct to subtotal resection. These locations are associated with a high risk of surgical morbidity if extensive resection is attempted. A recent literature review indicated that stereotactic radiosurgery (SRS) alone resulted in a relatively low recurrence risk of about 3%. In contrast, more invasive procedures such as subtotal resection (STR) and gross total resection (GTR) had recurrence risks of around 11%. Moreover, cranial nerve deficits were more commonly reported among patients who underwent surgical resection [112].

Although chordomas are generally slow-growing tumors, aggressive upfront management has shown significant benefits in long-term survival. A retrospective study conducted in France demonstrated that patients who received RT immediately following surgery had a 10-year survival rate of 65%, whereas none of the patients who only received RT at the time of recurrence survived up to 10 years [117]. In the largest series on chordomas treated with RT, conducted at Harvard University, patients were treated with 60 to 79.2 Cobalt-Gray-Equivalent (CGE), and the local control (LC) rates at 10 years were found to be 44% [118]. A recent review that aggregated data from over 400 patients found that 5-year LC rates were close to 70% and overall survival (OS) was more than 80% [119].

Soft tissue sarcomas of the skull base are usually approached with maximal surgical excision, followed by post-operative radiation therapy. Recurrence risk is higher in these cases compared to soft tissue sarcomas of the extremities, mainly because obtaining clean surgical margins is often challenging. Various radiation therapy techniques are utilized, including external beam radiation therapy (EBRT), stereotactic radiosurgery (SRS), intraoperative RT, and brachytherapy [120].

Modern advancements in EBRT include technologies such as three-dimensional conformal RT (3D-CRT) and intensity-modulated radiation therapy (IMRT). Three-dimensional conformal RT typically delivers radiation from multiple angles in a coplanar fashion, akin to the spokes on a wheel. IMRT, on the other hand, allows the intensity of radiation beams to vary at different positions. This has significantly improved the ability to treat tumors located near sensitive structures, thereby advancing the field of radiation oncology [120].

Advances in radiation therapy and aggressive upfront management strategies have shown promising results in the treatment of chordomas and soft tissue sarcomas of the skull base. These findings underscore the need for individualized, multidisciplinary treatment approaches to optimize long-term outcomes.

#### **7. Holistic Approaches: Interdisciplinary Collaborations and Patient-Centric Care**

*7.1. The Ecosystem of Cranial Base Surgery: Integrating Neurology, Radiology, Oncology, and Rehabilitation*

The complexities involved in the surgery of skull base meningiomas (SBMs) increasingly point to the need for a multimodal treatment approach, integrating both radiosurgery and radiation therapy. This combination aims to maximize both functional outcomes and tumor control. Advances in technology, genomics, and Radiomics are poised to greatly enhance our understanding of tumor biology. This, in turn, allows for the tailoring of treatment plans in line with the tenets of precision medicine [121].

Beside multiple implicated medical specialties, neurosurgeons need to undergo a continuous high standard training for skull base pathology. Achieving surgical proficiency is paramount for educators within the domain of skull base surgery. Diligent effort, coupled with consistent and immediate evaluative feedback, constitutes a cornerstone of successful skill acquisition. Establishing an environment rooted in patient-centric values that fosters scholastic excellence augments the efficacy of a training program. Moreover, the usage of 3D printed models of the skull are currently used as a training possibility even for during the residency program. In the case of skull base pathologies, neurosurgeons can exercise the surgical approaches, especially various types of craniotomies on those synthetic-based models. For optimal knowledge assimilation, it is imperative that both the mentor and mentee engage proactively and with deliberate intent [122–124].

Given the rapidly evolving landscape of SBM treatment—fueled by technological and scientific innovations—a specialized multidisciplinary approach has become essential for optimal patient care. This has led to the conceptualization of "Centers of Excellence", institutions specifically geared towards SBM management. These centers are not only technologically advanced but also guarantee an adequate workload for healthcare providers, ensuring they remain at the forefront of the field.

Moreover, integration of a diverse array of medical and allied health disciplines has the potential to substantially augment the quality of healthcare delivery, particularly in the context of Skull Base multidisciplinary teams. In such specialized tertiary referral centers, the amalgamation of expertise from various subspecialties not only fosters a holistic approach to patient care but also enhances the precision and efficacy of diagnosis, treatment planning, and execution.

Within these multidisciplinary frameworks, palliative care physicians contribute to symptom management and quality-of-life improvement, offering critical perspectives on end-of-life care when required. Neurosurgical anesthetists bring a refined understanding of perioperative management, particularly vital in the intricate surgeries associated with skull base anomalies. Chronic pain specialists offer insights into long-term analgesic strategies, thus contributing to sustained patient comfort and improved functionality post-surgery.

Similarly, clinical psychologists can play a pivotal role in assessing and addressing the psychological comorbidities often accompanying chronic or severe medical conditions. They provide cognitive-behavioral interventions and other psychological supports to enhance patients' coping mechanisms. Audiological scientists and hearing and/or balance therapists contribute expertise on auditory and vestibular systems, which are frequently involved in skull base pathologies. Their input can be invaluable in both the diagnostic and rehabilitative phases of care.

Additionally, maxillofacial prosthetists offer specialized interventions that focus on reconstructive options, including facial prosthetics, which can be instrumental in postoperative rehabilitation. Speech and language therapists address communication and swallowing challenges that might arise due to anatomical changes or neurological impairments associated with skull base disorders. Dietitians further enrich the multidisciplinary team by offering tailored nutritional plans, thereby optimizing patients' metabolic states for improved outcomes in both surgical and nonsurgical interventions.

This expansive collaborative approach is further fortified by interdepartmental interactions with neurosurgeons, neuroradiologists, and neuropathologists. Neurosurgeons offer specialized surgical interventions, while neuroradiologists provide crucial imaging expertise, enhancing the specificity and sensitivity of diagnostic processes. Neuropathologists contribute by offering detailed tissue diagnoses, which are vital for optimal treatment planning.

Given the complex, multifaceted nature of the conditions encountered in skull base pathology, and the necessity for sophisticated diagnostic and therapeutic modalities, the persistence of skull base multidisciplinary teams as a feature of tertiary referral centers seems not only likely but also clinically imperative. This convergence of specialized skills in a collaborative environment serves to enhance patient outcomes, facilitating a more nuanced and comprehensive standard of care [125].

#### *7.2. Patient Narratives and Quality of Life Metrics Post-Surgery*

Patients ultimately want their surgical team to cure, control, or, ideally, facilitate the prevention of disease. They favor minimally invasive approaches. When possible, they want illnesses to be treated by medicines only. If further intervention is necessary, they prefer minimally invasive surgery or radiosurgery without tissue damage. When more extensive surgery cannot be avoided, they prefer it to be without undue risk. Patients rightly place a premium on minimizing morbidity, which means no damage to the surrounding brain, cranial nerves, or blood vessels and no cosmetic deformity. Regardless of the approach, they want to minimize time away from work and family and to be treated at a reasonable cost [126].

#### **8. Conclusions—Epilogue: Gazing into the Future Horizon**

#### *8.1. Challenges, Opportunities, and the Trajectory of Cranial Base Surgery in the Coming Decade*

The adoption of 3D printing technologies is on the rise across various sectors, including neurosurgery. Current applications in this field encompass the fabrication of cranioplasty implants, educational models for tumors and aneurysms, as well as surgical planning aids [127]. Further innovation comes from the Northwestern University School of Engineering, where researchers have developed 3D-printed, patient-specific bioresorbable intravascular stents. Notably, a proof-of-concept for a 3D-printed bionic ear has been developed, featuring advanced auditory sensing capabilities for radiofrequency signals [128,129].

In the realm of cranial surgery, various robotic technologies are making headway. The NeuroArm, developed at the University of Calgary, is a remote-controlled surgical robot designed for use in an MRI suite [130]. Meanwhile, the Shinshu University NeuRobot—a joint effort involving multiple research institutions—consists of a master–slave micromanipulator system equipped with a rigid endoscope and three robotic arms, designed for minimally invasive procedures. This system has already been successfully employed in surgeries and shows potential for remote telesurgical applications, albeit with a minuscule 1 ms delay [131].

Currently, a team at the University of Washington is developing an Artificially Intelligent Neurosurgical Robotic Assistant. This autonomous robot aims to replicate the functions of a microneurosurgical assistant, such as gentle tissue manipulation and precise suction within the surgical field.

The development of an Artificially Intelligent Neurosurgical Robotic Assistant aims to create an intuitive system that can act according to the surgeon's needs, either through innate understanding or voice commands. One of the major challenges lies in understanding the nuanced interaction between the surgeon and their assistant during surgery. To this end, the team has employed convolutional neural networks to analyze the surgeon's

voice and tool movements captured under a microscope [132]. Python speech application program interfaces are also used for more detailed analysis.

Instrument identification and tracking in the surgical field are performed at the pixel level, offering insights into the surgeon's intended direction of movement [133]. An integral part of the project involves adapting natural language parsing to recognize specific medical terms, making the interface between the robotic assistant and the surgeon more intuitive and efficient.

In a novel application, the team recently showcased the fusion of semi-autonomous robotic therapy with a specialized biomarker known as "tumor paint", derived from a component of scorpion toxin [134]. This biomarker specifically labels brain tumors. In studies led by Hu et al., a robotic system scanned a simulated tumor margin for spots marked as positive for tumor cells. Following the surgeon's approval, the robot then executed an automated ablation pathway to remove these areas [135].

In summary, the convergence of robotics, machine learning, and specialized biomarkers is pushing the boundaries of what is possible in neurosurgical interventions. The fusion of these technologies could revolutionize how surgical procedures are planned and executed, with the promise of more precise and potentially less invasive treatments (Table 2).

**Table 2.** Future Advances in Various Fields in Skull Base Surgery.


*8.2. Potential Breakthroughs: Stem Cell Research, Regenerative Medicine, and Genomic Tailoring*

Stem cell recovery techniques are poised to play a transformative role in the treatment of surgically induced and other neurological deficits within the next two decades. These advancements could especially benefit patients requiring surgery for conditions such as vestibular schwannoma, promising better recovery of cranial nerve 7 and 8 function even for those with large or giant tumors. This promising approach could also extend to iatrogenic neurological deficits that may arise after surgeries on the brain or brainstem for tumor or vascular operations. Furthermore, understanding how stem cells interact with tumors may pave the way for the prevention and potential cure of some skull base malignant neoplasms [126].

In a notable development, a 12-month phase II, randomized controlled trial conducted in the US and Japanese centers showed that SB623 stem cells were particularly effective for patients with traumatic brain injury. These cells were implanted around the injury site, leading to significant improvements in motor function as measured by the Fugl-Meyer motor scale. The primary endpoint was reached, with an average improvement of 8.3 points as opposed to an improvement of 2.3 in the control group at 24 weeks (*p* = 0.040). This

promising result has led SanBio Co., Ltd. (Tokyo, Japan), to plan further studies in phase III clinical trials, as per a personal communication from Steinberg GK in 2020 and a press release from SanBio Co., Ltd., in 2019 [136].

Like any groundbreaking medical advancement, the journey of integrating stem cells into clinical practice will require significant financial investment and time. It is also important to brace for setbacks and challenges along the way, much like the development pathways for new drugs or vaccines. Nevertheless, the prospects are exciting and could herald a new era in the treatment of neurological conditions and deficits.

#### *8.3. Reiterating the Ethos of Continuous Learning, Global Collaboration, and Patient-First Principles*

The future of skull base surgery and neurosurgery will undeniably be influenced by rapid technological advancements. While surgeons will need to be agile in integrating these new technologies into their practice, the core tenets that define a great surgeon—knowledge, innovation, technical skill, judgment, and compassion—will stand the test of time. Active engagement with emerging technologies is not just an option but a necessity, as it allows surgeons to have a direct hand in shaping the future of their field [126].

Innovation will be a linchpin in the evolution of medical practice, both now and in the future. These innovations might be subtle, influencing the minutiae of day-to-day work, or they could be groundbreaking, transforming clinical surgery, basic neurosciences, or various aspects of healthcare delivery. They might also aim at improving workflow and efficiency, revamping outpatient and hospital infrastructure, elevating patient satisfaction, or enhancing quality metrics [126].

Young surgeons carry the mantle of responsibility to not only excel in their craft but also to contribute to its progression. They must constantly aspire to leave their field better than how they found it, pushing the boundaries of what is possible and effective in medical care. Furthermore, surgeons should not shy away from roles in hospital and healthcare administration. Such involvement provides them with the opportunity to guide transformative changes, ensuring that innovation and quality improvement are not just theoretical ideals but real-world practices that enhance patient care and outcomes.

**Author Contributions:** Conceptualization, C.T. and C.-I.T.; methodology, C.T., R.-A.C.-B. and L.-A.G.; software, R.-A.C.-B. and H.P.C.; validation, B.-G.B.; formal analysis, H.P.C.; investigation, C.-I.T.; resources, D.-I.D.; data curation, B.-G.B. and L.-A.G.; writing—original draft preparation, R.-A.C.-B.; writing—review and editing, C.-I.T.; visualization, L.E.; supervision, L.E.; project administration, A.V.C.; funding acquisition, A.V.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** All data is available online on libraries such as PubMed.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Abbreviations**



#### **References**


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