Homeostasis, which supports and maintains brain function, results from the continuous regulation of thermodynamics within tissue: the balance of heat production, redox oscillations, and vascular convection regulates coherent energy flow within the organ. Neuroinflammation disturbs this balance, creating measurable entropy gradients that precede structural damage to its tissue components. This paper proposes that a thermodynamic unity can be devised that incorporates nanoscale physics, energetic neurophysiology, and systems neuroscience, and can be used to understand and treat neuroinflammatory processes. Using multifactorial modalities such as quantum thermometry, nanoscale calorimetry, and redox oscillometry we define how local entropy production (s_t), relaxation time (τ^R), and coherence lengths (λc) allow quantification of the progressive loss of energetic symmetry within neural tissues. It is these variables that provide the basis for the etiology of thermodynamic biomarkers which on a molecular-redox-to-network scale characterize the transitions governing the onset of the neuroinflammatory process as well as the recovery potential of the organism. The entropic probing of systems (PEP) further allows the translation of these parameters into dynamic patient-specific trajectories that model the behavior of individuals by predicting recurrent bouts of instability through the application of machine learning algorithms to the vectors of entropy flux. The parallel development of the nanothermodynamic intervention, which includes thermoplasmonic heat rebalancing, catalytic redox nanoreacting systems, and adaptive field-oscillation synchronicity, shows by example how the corrections that can be applied to the entropy balance of the cell and system as a whole offer a feasible form of restoration of energy coherence. Such closed loop therapy would not function by the suppression of inflammatory signaling, but rather by the re-establishment of reversible energy relations between mitochondrial, glial, and vascular territories. The combination of these factors allows for correction of neuroinflammation, which can now be viewed from a fresh perspective as a dynamic phase disorder that is diagnosable, predictable, and curable through the physics of coherence rather than the molecular suppression of inflammatory signaling. The significance of this set of ideas is considerable as it introduces a feasible and verifiable structure to what must ultimately become the basis of a new branch of science: predictive energetic medicine. It is anticipated that entropy, as a measurable and modifiable variable in therapeutic “inscription”, will be found to be one of the most significant parameters determining the neurorestoration potential in future medical science.

Background and Clinical Significance: Giant sphenoid wing meningiomas are generally viewed as skull base masses that compress frontal centers and their respective pathways gradually enough to cause a dysexecutive–apathetic syndrome, which can mimic primary neurodegenerative disease. The aim of this report is to illustrate how bedside phenotyping and multimodal imaging can disclose similar clinical presentations as surgically treatable network lesions. Case Presentation: An independent, right-handed older female developed an incremental, two-year decline of her ability to perform executive functions, extreme apathy, lack of instrumental functioning, and a frontal-based gait disturbance, culminating in a first generalized seizure and a newly acquired left-sided upper extremity pyramidal sign. Standardized neuropsychological evaluation revealed a predominant frontal-based dysexecutive profile with intact core language skills, similar to behavioral-variant frontotemporal dementia (bvFTD). MRI demonstrated a large, right fronto-temporo-basal extra-axial tumor attached to the sphenoid wing with homogeneous postcontrast enhancement, significant vasogenic edema within the frontal projection pathways, and a marked midline displacement of structures with an open venous pathway. With the use of a skull-base flattening pterional craniotomy with early devascularization followed by staged internal debulking, arachnoid preserving dissection, and conservative venous preservation, the surgeon accomplished a Simpson Grade I resection. Sequential improvements in the patient’s frontal “re-awakening” were demonstrated through postoperative improvements on standardized stroke, cognitive and functional assessment scales that correlated well with persistent decompression and symmetric ventricles on follow-up images. Conclusions: This case illustrates the possibility of a non-dominant sphenoid wing meningioma resulting in a pseudo-degenerative frontal syndrome and its potential for reversal if recognized as a network lesion and treated with tailored, venous-sparing skull-base surgery. Contrast-enhanced imaging and routine frontal testing in atypical “dementia” presentations may aid in identifying additional patients with potentially surgically remediable cases.

Background/Objectives: Managing large midline olfactory groove meningiomas is especially difficult in elderly patients who have limited physiological reserves. Here we describe a unique and dangerous geriatric case where we used new quantifiable anatomical measurements and developed a structured multidisciplinary preoperative and postoperative protocol to assist in all aspects of surgery. Case Presentation: A 68-year-old male with fronto-lobe syndrome and disability (astasia-abasia; Tinetti Balance Score of 4/16 and Gait Score of 0/12) as well as cognitive dysfunction (MoCA score of 12/30) and blindness bilaterally. Imaging prior to surgery demonstrated a very large olfactory groove meningioma which severely compressed both optic pathways at the level of the optic canals (up to 71% reduction in cross-sectional area of the optic nerves) and had complex vascular relationships with the anterior cerebral artery complex (210° contact surface). Due to significant cardiovascular disease and liver disease, his care followed a coordinated optimization protocol for the perioperative period. He underwent bifrontal craniotomy, initial early devascularization and then staged ultrasonic internal decompression (approximately 70% reduction in tumor volume) and finally microsurgical dissection of the tumor under multi-modal monitoring of neurophysiology. Discussion: We analyzed his imaging data prior to surgery using a standardized measurement protocol to provide quantitative measures of the degree of compression of the optic pathways (traction-stretch index = 1.93; optic angulation = 47.3°). These quantitative measures allowed us to make a risk-based evaluation of the anatomy and to guide our choices of corridors through which to dissect and remove the tumor. Following surgery, imaging studies demonstrated complete removal of the tumor with significant relief of the frontal lobe and optic apparatus from compression. His pathology showed that he had a WHO Grade I meningioma with an AKT1(E17K) mutation identified on molecular profiling. Conclusions: This case is intended to demonstrate the feasibility of integrating quantitative anatomical measurements into a multidisciplinary, protocol-based perioperative pathway to maximize the safety and effectiveness of the surgical removal of a complex and high-risk skull-base tumor. While the proposed quantitative indices are experimental and require additional validation, the use of a systematic approach such as this may serve as a useful paradigm for other complex skull-base cases.

Background and Clinical Significance: Modern neuro-oncologists encounter a major challenge when dealing with glioblastomas located in the dominant hemisphere’s temporo-basal area, because their invasive nature disrupts the proximity to eloquent cortical areas (language and speech), as well as skull base venous structures, which can lead to a quick decline in function from the disruptions in these networks and the disconnection of corridor-level pathways. This manuscript illustrates the application of metric-based phenotyping, anatomically defined imaging, and venous-anchored microsurgical techniques that can aid in preserving the remaining functional reserve in patients with dominant hemisphere glioblastomas and demonstrate measurable outcomes through longitudinal follow-up data. Case Presentation: A 48-year-old right-handed male patient presented with a four-week history of progressively worsening symptoms consistent with a dominant hemisphere syndrome, resulting in a significant decrease in his independence (mRS 0 → 4; BI 55/100; IADL 2/8). His symptoms included non-fluent expressive aphasia with a marked inability to generate words and respond to verbal cues (BNT 8/30; SF 4 WPM). Additionally, he experienced prolonged lateralizing hemisensory decompensation and corticospinal tract dysfunction. Imaging studies revealed a large multiloculated cystic lesion located in the left temporo-basal region. The lesion displayed a thick irregular peripheral enhancement pattern with mural nodules and septa, and surrounding T2 hyperintensity extending into the temporal associative white matter, indicating disruption of the lexical–semantic networks and corridor-level tracts. Utilizing continuous SSEPS/MEPs during surgery, a skull base parallel ventral temporal corridor was developed to allow decompression of the cyst first, followed by cyst evacuation, inside-out cytoreduction, subpial dissection, and specific preservation of both superficial and deep temporal veins using selective capsular preservation at venous interface locations where necessary. Postoperative CT scans performed on POD #3 and POD #7 indicated stable decompression without hemorrhage or hydrocephalus complications, followed by rapid quantitative improvement in NIHSS (8 → 2), MoCA (18 → 26), BNT (8 → 26), SF (4 → 12), mRS (2 at discharge, 1 at follow-up), BI (85 at discharge, 95 at follow-up), and IADL (6/8 at discharge, 8/8 at follow-up). Histopathological examination confirmed a diagnosis of glioblastoma. Conclusions: This case study supports a model of a network- and vein-constrained glioblastoma of the dominant hemisphere in the temporo-basal region that can result in substantial restoration of language capabilities and preservation of functional reserves for additional therapies using venous-anchored subpial microsurgical approaches. The use of objective and quantifiable measures of phenotyping and longitudinal follow-up tracking could provide a reproducible method for measuring the degree of recovery of the affected network(s) and establishing safe boundaries for temporal glioma surgery.

Background/Objectives: Lymph-node metastasis remains central to staging, prognosis, surveillance, and treatment planning in malignant melanoma. At present, most statistical models assessing nodal metastatic risk in malignant melanoma consider pathological descriptors, inflammatory markers, metabolic alterations, clinical data, and related variables independently of each other. Therefore, we developed a transparent artificial intelligence (AI)-based approach to assess whether the propensity for nodal metastasis is determined by a single layer of local histopathological aggressiveness or by the integration of different biological levels, including local histopathological aggressiveness, systemic inflammatory–metabolic dysregulation, biological heterogeneity, or a clinicobiological pattern. Methods: In this retrospective study, we assessed 73 adult patients undergoing surgical removal of malignant melanoma. The primary endpoint was histopathologically confirmed lymph-node metastasis. Routinely collected patient-related data, including clinical, anatomical, operative, histopathological, nodal, comorbidity, biological, clinical course, and available staging data, were structured into interpretable constructs. These included the Histopathologic Aggressiveness Index (HAI), the Inflammatory–Metabolic Dysregulation Index (IMDI), the Biological–Histological Discordance Score (BHDS), model-estimated nodal metastatic probability, integrated clinicobiological risk, and explanation stability. The AI-based framework was evaluated by applying bias-reduced and penalized logistic regression, machine learning benchmarking, leave-one-out cross-validation, bootstrap estimation, permutation testing, decision curve analysis, rule extraction, feature stability evaluation, network analysis, similarity-based retrieval, conformal uncertainty estimation, and unsupervised phenomapping. Results: For 72 out of 73 patients, nodal histopathology results were available. Among these patients, 22 had positive nodal status. Positive nodal status was associated with a higher Breslow thickness, an increased mitotic rate, ulceration, lymphovascular invasion, a nodular subtype, and palpable adenopathy. The HAI demonstrated the strongest discriminative signal between node-positive and node-negative patients (median values of 67.8 vs. 45.3; p < 0.001) and retained an independent association with nodal metastasis within the bias-reduced logistic model (odds ratio [OR] per 10-point increase: 2.74; 95% confidence interval [CI]: 1.58–4.75; p < 0.001). The IMDI showed a weak exploratory relationship and did not retain an independent association after adjustment. Similarly, the BHDS did not show significant differences in separating the two endpoint groups. The penalized logistic model including only the HAI showed good performance under leave-one-out cross-validation, with ROC AUC = 0.889, PR-AUC = 0.706, and Brier score = 0.137. Through rule extraction, we found a cohort-specific HAI threshold value > 58.6, above which all node-positive cases were located. With respect to explainability, feature stability, network analysis, similarity retrieval, conformal prediction, and phenomapping, there was convergence toward a dominant high-risk phenotype defined primarily by histopathological criteria. Conclusions: Routine melanoma registries may be transformed into internally evaluated melanoma intelligence frameworks. Histopathologically confirmed lymph-node metastasis among patients with malignant melanoma was organized primarily along an axis of local histopathological aggressiveness, while systemic inflammatory–metabolic dysregulation provided subordinate contextual biological information.