ReviewNeurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics2017
Magnetic Resonance Imaging-Guided Laser Interstitial Thermal Therapy for Treatment of Drug-Resistant Epilepsy.
Review in Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- An examination of seizure-free outcome and visual field deficits: Anterior temporal lobectomy versus selective amygdalohippocampectomy for temporal lobe epilepsy-a systematic review and meta-analysis for comprehensive understanding.Acta neurochirurgica · 2024Pooled it
- Trends in the studies of pharmacoresistant epilepsy- a review based on literature analysis (2015-2025).Acta epileptologica · 2026Review
- Epilepsy: Molecular Pathogenesis and Emerging Therapies.MedComm · 2026Review
- A Flexible, Implantable, Bioelectronic Electroporation Device for Targeted Ablation of Seizure Foci in the Mouse Brain.Sensors (Basel, Switzerland) · 2024Article
- Clinical Management of Drug Resistant Epilepsy: A Review on Current Strategies.Neuropsychiatric disease and treatment · 2021Review
- Data-driven evolution of neurosurgical gene therapy delivery in Parkinson's disease.Journal of neurology, neurosurgery, and psychiatry · 2020Review
- Resting-state network complexity and magnitude changes in neonates with severe hypoxic ischemic encephalopathy.Neural regeneration research · 2019Article
- Presurgical epilepsy evaluation and epilepsy surgery.F1000Research · 2019Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Surgery is the most effective treatment for drug-resistant epilepsy. Long-term studies demonstrate that about 60% to 80% of patients become seizure-free after anterior temporal lobectomy and a majority of patients (about 95%) report significant seizure reduction after surgery. In the last few years, there has been significant advances in minimally invasive surgical techniques to treat drug-resistant epilepsy. These minimally invasive procedures have significant advantages over open surgery in that they produce less immediate discomfort and disability, while allowing for greater preservation of functional tissue. Laser interstitial thermal therapy (LiTT) is an example of such a procedure. Recent advances in imaging, surgical navigation, and real-time thermal monitoring have made LiTT safer and easier to implement, offering an effective and powerful neurosurgical tool for drug-resistant epilepsy. This article will review the technical considerations, uses, and potential future directions for LiTT in drug-resistant epilepsy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.