Evidence map›Paper›PMID 31392717›Full record

ArticleEpilepsia2019

Multicenter validation of automated trajectories for selective laser amygdalohippocampectomy.

Vejay N Vakharia, Rachel E Sparks, Kuo Li, Aidan G O'Keeffe, Fernando Pérez-García, Lucas G S França, Andrew L Ko, Chengyuan Wu, Joshua P Aronson, Brett E Youngerman and 4 more

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

Article in Epilepsia, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
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  7. Article
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

14 authors at 10 institutions in 3 countries.

Vejay N VakhariaDepartment of Clinical and Experimental Epilepsy, Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0002-9476-4225
Rachel E SparksSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Kuo LiThe First Affiliated Hospital of Xi'an, Jiaotong University, Xi'an, China.
Aidan G O'KeeffeDepartment of Statistical Science, University College London, London, UK.
Fernando Pérez-GarcíaWellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.
Lucas G S FrançaDepartment of Clinical and Experimental Epilepsy, Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0003-0853-1319
Andrew L KoDepartment of Neurosurgery, University of Washington, Seattle, Washington.
Chengyuan WuDivision of Epilepsy and Neuromodulation Neurosurgery, Department of Neurosurgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania.ORCID 0000-0002-3954-2929
Joshua P AronsonDepartment of Neurosurgery, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
Brett E YoungermanColumbia University Medical Center, New York, New York.ORCID 0000-0002-4792-3190
Ashwini SharanDivision of Epilepsy and Neuromodulation Neurosurgery, Department of Neurosurgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania.
Guy McKhannColumbia University Medical Center, New York, New York.
Sebastien OurselinSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
John S DuncanDepartment of Clinical and Experimental Epilepsy, Queen Square Institute of Neurology, University College London, London, UK.ORCID 0000-0002-1373-0681
Columbia University Irving Medical Center · USEpilepsy Research UK · GBKing's College London · GBThomas Jefferson University Hospital · USDartmouth–Hitchcock Medical Center · USFirst Affiliated Hospital of Xi'an Jiaotong University · CNNational Hospital for Neurology and Neurosurgery · GBUniversity College London · GBUniversity of Washington · USWellcome / EPSRC Centre for Interventional and Surgical Sciences · GB

Funding

NIHR UCLH/UCL Biomedical Research CentreWellcome/EPSRC 203145Z/16/ZWellcome Trust WT106882
6 · The paper itself

Abstract

objectiveLaser interstitial thermal therapy (LITT) is a novel minimally invasive alternative to open mesial temporal resection in drug-resistant mesial temporal lobe epilepsy (MTLE). The safety and efficacy of the procedure are dependent on the preplanned trajectory and the extent of the planned ablation achieved. Ablation of the mesial hippocampal head has been suggested to be an independent predictor of seizure freedom, whereas sparing of collateral structures is thought to result in improved neuropsychological outcomes. We aim to validate an automated trajectory planning platform against manually planned trajectories to objectively standardize the process.

methodsUsing the EpiNav platform, we compare automated trajectory planning parameters derived from expert opinion and machine learning to undertake a multicenter validation against manually planned and implemented trajectories in 95 patients with MTLE. We estimate ablation volumes of regions of interest and quantify the size of the avascular corridor through the use of a risk score as a marker of safety. We also undertake blinded external expert feasibility and preference ratings.

resultsAutomated trajectory planning employs complex algorithms to maximize ablation of the mesial hippocampal head and amygdala, while sparing the parahippocampal gyrus. Automated trajectories resulted in significantly lower calculated risk scores and greater amygdala ablation percentage, whereas overall hippocampal ablation percentage did not differ significantly. In addition, estimated damage to collateral structures was reduced. Blinded external expert raters were significantly more likely to prefer automated to manually planned trajectories. SIGNIFICANCE: Retrospective studies of automated trajectory planning show much promise in improving safety parameters and ablation volumes during LITT for MTLE. Multicenter validation provides evidence that the algorithm is robust, and blinded external expert ratings indicate that the trajectories are clinically feasible. Prospective validation studies are now required to determine if automated trajectories translate into improved seizure freedom rates and reduced neuropsychological deficits.

Indexed as

AmygdalaDrug Resistant EpilepsyEpilepsy, Temporal LobeHippocampusHumansLaser TherapyMachine LearningNeurosurgical Procedurescomputer-assisted planninglaser interstitial thermal therapymesial temporal lobe epilepsyselective laser amygdalohippocampectomy

Identifiers

PMID31392717
PMCPMC6771574
OpenAlexW2966941474

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.