Evidence map›Paper›PMID 29528488›Full record

ArticleEpilepsia2018

Automated trajectory planning for laser interstitial thermal therapy in mesial temporal lobe epilepsy.

Vejay N Vakharia, Rachel Sparks, Kuo Li, Aidan G O'Keeffe, Anna Miserocchi, Andrew W McEvoy, Michael R Sperling, Ashwini Sharan, Sebastien Ourselin, John S Duncan and 1 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Epilepsia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 6 pooled it
6.8field-weighted citation impact, top 2% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 6 syntheses or guidelines pooled it, 65 citations in OpenAlex.

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  10. Brain Lesion Synthesis via Progressive Adversarial Variational Auto-Encoder.Simulation and synthesis in medical imaging : ... International Workshop, SASHIMI ..., held in conjunction with MICCAI ..., proceedings. SASHIMI (Workshop) · 2022
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  14. CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer Assisted Interventions.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2020
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  19. Optimizing Trajectories for Cranial Laser Interstitial Thermal Therapy Using Computer-Assisted Planning: A Machine Learning Approach.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 3 countries.

Vejay N VakhariaDepartment of Clinical and Experimental Epilepsy, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK.ORCID 0000-0002-9476-4225
Rachel SparksWellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.
Kuo LiDepartment of Clinical and Experimental Epilepsy, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK.
Aidan G O'KeeffeDepartment of Statistical Science, University College London, London, UK.
Anna MiserocchiDepartment of Clinical and Experimental Epilepsy, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK.
Andrew W McEvoyDepartment of Clinical and Experimental Epilepsy, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK.
Michael R SperlingDepartment of Neurology, Vickie and Jack Farber Institute for Neuroscience, Jefferson Comprehensive Epilepsy Center, Thomas Jefferson University, Philadelphia, PA, USA.
Ashwini SharanDivision of Epilepsy and Neuromodulation Neurosurgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, USA.
Sebastien OurselinDepartment of Clinical and Experimental Epilepsy, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK.
John S DuncanDepartment of Clinical and Experimental Epilepsy, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, UK.ORCID 0000-0002-1373-0681
Chengyuan WuDivision of Epilepsy and Neuromodulation Neurosurgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, USA.
National Hospital for Neurology and Neurosurgery · GBThomas Jefferson University · USWellcome / EPSRC Centre for Interventional and Surgical Sciences · GBFirst Affiliated Hospital of Xi'an Jiaotong University · CNUniversity College London · GB

Funding

Wellcome TrustWellcome Trust 203145Z/16/ZWellcome Trust WT106882
6 · The paper itself

Abstract

objectiveSurgical resection of the mesial temporal structures brings seizure remission in 65% of individuals with drug-resistant mesial temporal lobe epilepsy (MTLE). Laser interstitial thermal therapy (LiTT) is a novel therapy that may provide a minimally invasive means of ablating the mesial temporal structures with similar outcomes, while minimizing damage to the neocortex. Systematic trajectory planning helps ensure safety and optimal seizure freedom through adequate ablation of the amygdalohippocampal complex (AHC). Previous studies have highlighted the relationship between the residual unablated mesial hippocampal head and failure to achieve seizure freedom. We aim to implement computer-assisted planning (CAP) to improve the ablation volume and safety of LiTT trajectories.

methodsTwenty-five patients who had previously undergone LiTT for MTLE were studied retrospectively. The EpiNav platform was used to automatically generate an optimal ablation trajectory, which was compared with the previous manually planned and implemented trajectory. Expected ablation volumes and safety profiles of each trajectory were modeled. The implemented laser trajectory and achieved ablation of mesial temporal lobe structures were quantified and correlated with seizure outcome.

resultsCAP automatically generated feasible trajectories with reduced overall risk metrics (P < .001) and intracerebral length (P = .007). There was a significant correlation between the actual and retrospective CAP-anticipated ablation volumes, supporting a 15 mm diameter ablation zone model (P < .001). CAP trajectories would have provided significantly greater ablation of the amygdala (P = .0004) and AHC (P = .008), resulting in less residual unablated mesial hippocampal head (P = .001), and reduced ablation of the parahippocampal gyrus (P = .02). SIGNIFICANCE: Compared to manually planned trajectories CAP provides a better safety profile, with potentially improved seizure-free outcome and reduced neuropsychological deficits, following LiTT for MTLE.

Indexed as

AdultAgedChildEpilepsy, Temporal LobeFemaleHumansHyperthermia, InducedLaser TherapyMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesYoung Adultcomputer-assisted planningEpiNavlaser ablationlaser interstitial thermal therapymesial temporal sclerosis

Identifiers

PMID29528488
PMCPMC5901027
OpenAlexW2791787568

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.