Predictive modeling of brain tumor laser ablation dynamics

A novel predictive model utilizing retinal microstructural features for estimating survival outcome in patients with glioblastoma

PURPOSE

Glioblastoma is a highly aggressive brain tumor with poor prognosis despite surgery and chemoradiation. The visual sequelae of glioblastoma have not been well characterized. This study assessed visual outcomes in glioblastoma patients through neuro-ophthalmic exams, imaging of the retinal microstructures/microvasculature, and perimetry.

METHODS

A total of 19 patients with glioblastoma (9 male, 10 female, average age at diagnosis 69 years) were enrolled. Tumor characteristic, neuro-ophthalmic exam data, Optical Coherence Tomography (OCT) and OCT-Angiography data of all patient eyes were analyzed using Microsoft Excel and a Machine Learning algorithm.

RESULTS

Best-corrected visual acuity ranged from 20/20 - 20/50. Occipital tumors showed worse visual fields than frontal tumors (mean deviation -14.9 and -0.23, respectively, p < 0.0001). Those with overall survival (OS)< 15 months demonstrated thinner retinal nerve fiber layer and ganglion cell complex (p < 0.0001) and enlarged foveal avascular zone starting from 4 months post-diagnosis (p = 0.006). There was no significant difference between eyes ipsilateral and contralateral to radiation fields (average doses were 1370 cGy and 1180 cGy, respectively, p = 0.42). A machine learning algorithm using retinal microstructure and visual fields predicted patients with long (≥15 months) progression-free and overall survival with 78 % accuracy.

CONCLUSION

Glioblastoma patients frequently present with visual field defects despite normal visual acuity. Patients with poor survival duration demonstrated significant retinal thinning and decreased microvascular density. A machine learning algorithm predicted survival though further validation is warranted.

A Novel Predictive Model Utilizing Retinal Microstructural Features for Estimating Survival Outcome in Patients with Glioblastoma

Glioblastoma is a highly aggressive brain tumor with poor prognosis despite surgery and chemoradiation. The visual sequelae of glioblastoma have not been well characterized. This study assessed visual outcomes in glioblastoma patients through neuro-ophthalmic exams, imaging of the retinal microstructures/microvasculature, and perimetry. A total of 19 patients (9 male, 10 female, average age at diagnosis 69 years) were enrolled. Best-corrected visual acuity ranged from 20/20-20/50. Occipital tumors showed worse visual fields than frontal tumors (mean deviation - 14.9 and - 0.23, respectively, p < 0.0001). Those with overall survival (OS) < 15 months demonstrated thinner retinal nerve fiber layer and ganglion cell complex (p < 0.0001) and enlarged foveal avascular zone starting from 4 months post-diagnosis (p = 0.006). There was no significant difference between eyes ipsilateral and contralateral to radiation fields (average doses were 1370 cGy and 1180 cGy, respectively, p = 0.42). A machine learning algorithm using retinal microstructure and visual fields predicted patients with long (≥ 15 months) progression free and overall survival with 78% accuracy. Glioblastoma patients frequently present with visual field defects despite normal visual acuity. Patients with poor survival duration demonstrated significant retinal thinning and decreased microvascular density. A machine learning algorithm predicted survival; further validation is warranted.

Predicting brain temperature in humans using bioheat models: Progress and outlook

Brain temperature, regulated by the balance between blood circulation and metabolic heat generation, is an important parameter related to neural activity, cerebral hemodynamics, and neuroinflammation. A key challenge for integrating brain temperature into clinical practice is the lack of reliable and non-invasive brain thermometry. The recognized importance of brain temperature and thermoregulation in both health and disease, combined with limited availability of experimental methods, has motivated the development of computational thermal models using bioheat equations to predict brain temperature. In this mini-review, we describe progress and the current state-of-the-art in brain thermal modeling in humans and discuss potential avenues for clinical applications.

From Focused Ultrasound Tumor Ablation to Brain Blood Barrier Opening for High Grade Glioma: A Systematic Review

BACKGROUND

Focused Ultrasound (FUS) is gaining a therapeutic role in neuro-oncology considering its novelty and non-invasiveness. Multiple pre-clinical studies show the efficacy of FUS mediated ablation and Blood-Brain Barrier (BBB) opening in high-grade glioma (HGG), but there is still poor evidence in humans, mainly aimed towards assessing FUS safety.

METHODS

With this systematic review our aim is, firstly, to summarize how FUS is proposed for human HGG treatment. Secondly, we focus on future perspectives and new therapeutic options. Using PRISMA 2020 guidelines, we reviewed case series and trials with description of patient characteristics, pre- and post-operative treatments and FUS outcomes. We considered nine case series (five about tumor ablation and four about BBB opening) with FUS-treated HGG patients between 1991 and 2021.

RESULTS

Sixty-eight patients were considered in total, mostly males (67.6%), with a mean age of 50.5 ± 15.3 years old. Major complication rates were found in the tumor ablation group (26.1%). FUS has been rarely applied for direct tumoral ablation in human HGG patients with controversial results, but at the best of current studies, FUS-mediated BBB opening is showing good results with very low complication rates, paving the way for a new reliable technique to improve local chemotherapy delivery and antitumoral immune response.

CONCLUSIONS

FUS can become a complementary technique to surgical resection and standard radiochemotherapy in recurrent HGG. Ongoing trials could provide in the near future more data on FUS-mediated BBB opening impact on progression-free survival, overall survival and potential drug-delivery capacities.

Role of Laser Interstitial Thermal Therapy in the Management of Primary and Metastatic Brain Tumors

OPINION STATEMENT

Laser interstitial thermal therapy (LITT) is a minimally invasive treatment option for brain tumors including glioblastoma, other primary central nervous system (CNS) neoplasms, metastases, and radiation necrosis. LITT employs a fiber optic coupled laser delivery probe stabilized via stereotaxis to deliver thermal energy that induces coagulative necrosis in tumors to achieve effective cytoreduction. LITT complements surgical resection, radiation treatment, tumor treating fields, and systemic therapy, especially in patients who are high risk for surgical resection due to tumor location in eloquent regions or poor functional status. These factors must be balanced with the increased rate of cerebral edema post LITT compared to surgical resection. LITT has also been shown to induce transient disruption of the blood-brain barrier (BBB), especially in the peritumoral region, which allows for enhanced CNS delivery of anti-neoplastic agents, thus greatly expanding the armamentarium against brain tumors to include highly effective anti-neoplastic agents that have poor BBB penetration. In addition, hyperthermia-induced immunogenic cell death is another secondary side effect of LITT that opens up immunotherapy as an attractive adjuvant treatment for brain tumors. Numerous large studies have demonstrated the safety and efficacy of LITT against various CNS tumors and as the literature continues to grow on this novel technique so will its indications.

A Cohort Study on Prognostic Factors for Laser Interstitial Thermal Therapy Success in Newly Diagnosed Glioblastoma

BACKGROUND

Laser interstitial thermal therapy (LITT) is a promising approach for cytoreduction of deep-seated gliomas. However, parameters contributing to treatment success remain unclear.

OBJECTIVE

To identify extent of ablation (EOA) and time to chemotherapy (TTC) as predictors of improved overall and progression-free survival (OS, PFS) and suggest laser parameters to achieve optimal EOA.

METHODS

Demographic, clinical, and survival data were collected retrospectively from 20 patients undergoing LITT for newly diagnosed glioblastoma (nGBM). EOA was calculated through magnetic resonance imaging-based volumetric analysis. Kaplan-Meier and multivariate Cox regression were used to examine the relationship between EOA with OS and PFS accounting for covariates (age, isocitrate dehydrogenase-1 (IDH1) mutation, O6-methylguanine-DNA methyltransferase hypermethylation). The effect of laser thermodynamic parameters (power, energy, time) on EOA was identified through linear regression.

RESULTS

Median OS and PFS for the entire cohort were 36.2 and 3.5 mo respectively. Patient's with >70% EOA had significantly improved PFS compared to ≤70% EOA (5.2 vs 2.3 mo, P = .01) and trended toward improved OS (36.2 vs 11 mo, P = .07) on univariate and multivariate analysis. Total laser power was a significant predictor for increased EOA when accounting for preoperative lesion volume (P = .001). Chemotherapy within 16 d of surgery significantly predicted improved PFS compared to delaying chemotherapy (9.4 vs 3.1 mo, P = .009).

CONCLUSION

Increased EOA was a predictor of improved PFS with evidence of a trend toward improved OS in LITT treatment of nGBM. A strategy favoring higher laser power during tumor ablation may achieve optimal EOA. Early transition to chemotherapy after LITT improves PFS.

Mathematical Modeling of Thermal Damage Estimate Volumes in MR-guided Laser Interstitial Thermal Therapy

BACKGROUND AND PURPOSE

Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive procedure that produces real-time thermal damage estimates (TDEs) of ablation. Currently, MRgLITT software provides limited quantitative parameters for intraoperative monitoring, but orthogonal TDE-MRI slices can be utilized to mathematically estimate ablation volume. The objective of this study was to model TDE volumes and validate using post-24 hours MRI ablative volumes.

METHODS

Ablations were performed with the Visualase Laser Ablation System (Medtronic). Using ellipsoidal parameters determined for dual-TDEs from orthogonal MRI planes, TDE volumes were calculated by two definite integral methods (A and B) implemented in Matlab (MathWorks). Post-24 hours MRI ablative volumes were measured in OsiriX (Pixmeo) by two-blinded raters and compared to TDE volumes via paired t-test and Pearson's correlations.

RESULTS

Twenty-two ablations for 20 patients with various intracranial pathologies were included. Average TDE volume calculated with method A was 3.44 ± 1.96 cm³ and with method B was 4.83 ± 1.53 cm³ . Method A TDE volumes were significantly different than post-24 hours volumes (P < .001). Method B TDE volumes were not significantly different than post-24 hours volumes (P = .39) and strongly correlated with each other (r = .85, R² = .72, P < .0001). A total of eight of 22 (36%) method A versus 17 of 22 (77%) method B TDE volumes were within 25% of the post-24 hours ablative volume.

CONCLUSION

We present a viable mathematical method integrating dual-plane TDEs to calculate volumes. Future algorithmic iterations will incorporate additional calculated variables that improve ablative volume estimations.

The Practical Application of Emerging Technologies Influencing the Diagnosis and Care of Patients With Primary Brain Tumors

Over the past decade, a variety of new and innovative technologies has led to important advances in the diagnosis and management of patients with primary malignant brain tumors. New approaches to surgical navigation and tumor localization, advanced imaging to define tumor biology and treatment response, and the widespread adoption of a molecularly defined integrated diagnostic paradigm that complements traditional histopathologic diagnosis continue to impact the day-to-day care of these patients. In the neuro-oncology clinic, discussions with patients about the role of tumor treating fields (TTFields) and the incorporation of next-generation sequencing (NGS) data into therapeutic decision-making are now a standard practice. This article summarizes newer applications of technology influencing the pathologic, neuroimaging, neurosurgical, and medical management of patients with malignant primary brain tumors.

Contactless Thermometry by MRI and MRS: Advanced Methods for Thermotherapy and Biomaterials

Control of temperature variation is of primordial importance in particular areas of biomedicine. In this context, medical treatments such as hyperthermia and cryotherapy, and also the development and use of hydrogel-based biomaterials, are of particular concern. To enable accurate temperature measurement without perturbing or even destroying the biological tissue or material to be monitored, contactless thermometry methods are preferred. Among these, the most suitable are based on magnetic resonance imaging and spectroscopy (MRI, MRS). Here, we address the latest developments in this field as well as their current and anticipated practical applications. We highlight recent progress aimed at rendering MR thermometry faster and more reproducible, versatile, and sophisticated and provide our perspective on how these new techniques broaden the range of applications in medical treatments and biomaterial development by enabling insight into finer details of thermal behavior. Thus, these methods facilitate optimization of clinical and industrial heating and cooling protocols.