Towards the definition of progressive disease in brain metastasis treated with laser ablation: an evidence-based study

The Impact of Perilesional Heatsink Structures on Ablation Volumes in Laser Interstitial Thermal Therapy for Brain Metastases

BACKGROUND AND OBJECTIVES

Laser interstitial thermal therapy (LITT) has demonstrated promise in surgical neuro-oncology because of its effectiveness in delivering precise thermal energy to lesions. The extent of ablation (EOA) is a prognostic factor in improving patient outcomes but is often affected by perilesional heatsink structures, which can lead to asymmetric ablations. The purpose of this study was to quantitatively evaluate the impact of various perilesional heatsink structures on the EOA in LITT for brain metastases.

METHODS

Twenty-seven procedures for 22 unique patients with brain metastases fit the inclusion criteria. Intracranial heatsink structures were identified: sulci, meninges, cerebrospinal fluid (CSF) spaces, and vasculature. Asymmetric ablation was determined by measuring 3 pairs of orthogonal distances from the proximal, midpoint, and distal locations along the laser catheter to the farthest edge of the ablation zone bilaterally. Distances from the same points on the laser catheter to the nearest heatsink were also recorded. The Heatsink Effect Index was created to serve as a proxy for asymmetric ablation. Pearson correlations, t -tests, and analysis of variance were the statistical analyses performed.

RESULTS

From the midpoint of the catheter, the 27 heatsinks were meninges (40.7%), sulci (22.2%), vasculature (22.2%), and CSF spaces (14.8%). Across all points along the catheter track, there was a significant generalized heatsink effect on asymmetric ablations ( P < .0001). There was a negative correlation observed between asymmetric ablations and EOA from the midpoint of the laser catheter (r = -0.445, P = .020). Compared with sulci, CSF spaces trended toward a greater effect on asymmetric ablation volumes ( P = .069).

CONCLUSION

This novel quantitative analysis shows that perilesional heatsinks contribute to asymmetric ablations. CSF spaces trended toward higher degrees of asymmetric ablations. Importantly, neurosurgeons may anticipate asymmetric ablations preoperatively if heatsinks are located within 13.3 mm of the laser probe midpoint. These preliminary results may guide surgical decision-making in LITT for metastatic brain lesions.

The Learning Curve and Clinical Outcomes With 250 Laser Ablations for Brain Tumors: A Pathway to Experience

BACKGROUND AND OBJECTIVES

Laser interstitial thermal therapy (LITT) has gained popularity as a minimally invasive technique for treating brain tumors. Despite its proven safety profile, LITT is not yet widely available, and there is a lack of data on the learning curve required to achieve proficiency. This study analyzes a 250-patient cohort of laser-ablated tumors to describe changes in patient selection and clinical outcomes over time and experience, with the aim of providing insight into the learning curve for incorporating LITT into a neuro-oncology program and identifying a cutoff point that distinguishes novice from expert performance.

METHODS

We retrospectively reviewed 250 patients with brain tumor who underwent LITT between 2013 and 2022. Demographic and clinical data were analyzed. Kaplan Meier curves were used for survival analysis. Operative time was evaluated using exponential curve-fit regression analysis to identify when consistent improvement began.

RESULTS

The patients were divided into quartiles (Q) based on their date of surgery. Mean tumor volume increased over time (Q1 = 5.7 and Q4 = 11.9 cm 3 , P = .004), and newly diagnosed lesions were more frequently ablated ( P = .0001). Mean operative time (Q1 v Q4 = 322.3 v 204.6 min, P < .0001) and neurosurgical readmission rate (Q1 v Q4 = 7.8% v 0%, P = .03) were reduced over time. The exponential curve-fit analysis showed a sustained decay in operative time after case #74. The extent of ablation ( P = .69), the recurrence ( P = .11), and the postoperative complication rate ( P = .78) did not vary over time.

CONCLUSION

After treating 74 patients, a downward trend in the operative time is observed. Patient selection is broadened as experience increases.

Automated segmentation of ablated lesions using deep convolutional neural networks: A basis for response assessment following laser interstitial thermal therapy

BACKGROUND

Laser interstitial thermal therapy (LITT) of intracranial tumors or radiation necrosis enables tissue diagnosis, cytoreduction, and rapid return to systemic therapies. Ablated tissue remains in situ, resulting in characteristic post-LITT edema associated with transient clinical worsening and complicating post-LITT response assessment.

METHODS

All patients receiving LITT at a single center for tumors or radiation necrosis from 2015 to 2023 with ≥9 months of MRI follow-up were included. An nnU-Net segmentation model was trained to automatically segment contrast-enhancing lesion volume (CeLV) of LITT-treated lesions on T1-weighted images. Response assessment was performed using volumetric measurements.

RESULTS

Three hundred and eighty four unique MRI exams of 61 LITT-treated lesions and 6 control cases of medically managed radiation necrosis were analyzed. Automated segmentation was accurate in 367/384 (95.6%) images. CeLV increased to a median of 68.3% (IQR 35.1-109.2%) from baseline at 1-3 months from LITT (P = 0.0012) and returned to baseline thereafter. Overall survival (OS) for LITT-treated patients was 39.1 (9.2-93.4) months. Lesion expansion above 40% from volumetric nadir or baseline was considered volumetric progression. Twenty-one of 56 (37.5%) patients experienced progression for a volumetric progression-free survival of 21.4 (6.0-93.4) months. Patients with volumetric progression had worse OS (17.3 vs 62.1 months, P = 0.0015).

CONCLUSIONS

Post-LITT CeLV expansion is quantifiable and resolves within 6 months of LITT. Development of response assessment criteria for LITT-treated lesions is feasible and should be considered for clinical trials. Automated lesion segmentation could speed the adoption of volumetric response criteria in clinical practice.