ArticleNeuro-oncology2024
Automated segmentation of ablated lesions using deep convolutional neural networks: A basis for response assessment following laser interstitial thermal therapy.
Article in Neuro-oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Laser interstitial thermal therapy (LITT) for brain metastases: a systematic review and pooled analysis of Efficacy/Safety and the role of combination treatments.Journal of neuro-oncology · 2026Pooled it
- Imaging-based techniques for ablation zone definition and volumetry after laser interstitial thermal therapy (LITT) for intracranial lesions: a systematic review.Acta neurochirurgica · 2025Pooled it
- Laser Interstitial Thermal Therapy for High-Grade Gliomas: Current Evidence, Clinical Applications and Emerging Role of Artificial Intelligence.Journal of clinical medicine · 2026Review
- RN-DFrontiers in artificial intelligence · 2026Article
- Imaging Changes and Clinical Outcome after MR-Guided Laser Interstitial Thermal Therapy.Stereotactic and functional neurosurgery · 2026Article
- Volumetric and diffusion MRI longitudinal patterns in brain metastases after laser interstitial thermal therapy.European radiology · 2025Article
- Disparities in clinical trial enrollment related to laser interstitial thermal therapy for central nervous system metastases.Neurosurgical review · 2025Article
- The LITT Fit in neuro-oncology: indications, imaging, and adjunctive therapies.Journal of neuro-oncology · 2025Review
- The University of California San Francisco Adult Longitudinal Post-Treatment Diffuse Glioma MRI Dataset.Radiology. Artificial intelligence · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundLaser 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.
methodsAll 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.
resultsThree 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).
conclusionsPost-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.
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