Evidence map›Paper›PMID 30790172›Full record

ReviewInternational journal of computer assisted radiology and surgery2019

The Adaptive Hermite Fractal Tree (AHFT): a novel surgical 3D path planning approach with curvature and heading constraints.

Marlene Pinzi, Stefano Galvan, Ferdinando Rodriguez Y Baena

Registry-linked trialAbstract readReview
In one paragraph

Review in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05526352 (@neurIST), which is not on this map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

NCT05526352 recruitingnot on this map

@neurIST : Informatique biomédicale intégrée Pour la Gestion Des anévrismes cérébraux

Typeobservational_patient_registrySponsorUniversity Hospital, GenevaRan2015 to 2040Enrolled20,000ConditionsIntracranial Aneurysm
3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Safe Start Regions for Medical Steerable Needle Automation.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Toward certifiable optimal motion planning for medical steerable needles.The International journal of robotics research · 2023
    Article
  11. Article
  12. A Metric for Finding Robust Start Positions for Medical Steerable Needle Automation.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2022
    Article
  13. Resolution-Optimal Motion Planning for Steerable Needles.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation · 2022
    Article
  14. Review
  15. Article
  16. Toward Certifiable Motion Planning for Medical Steerable Needles.Robotics science and systems : online proceedings · 2021
    Article
  17. Backward Planning for a Multi-Stage Steerable Needle Lung Robot.IEEE robotics and automation letters · 2021
    Article
  18. Path planning for endovascular catheterization under curvature constraints via two-phase searching approach.International journal of computer assisted radiology and surgery · 2021
    Article
  19. Article
  20. 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

3 authors.

Marlene PinziMechatronics in Medicine Laboratory, Department of Mechanical Engineering, Imperial College, London, UK. marlene.pinzi16@imperial.ac.uk.ORCID http://orcid.org/0000-0001-9854-6105
Stefano GalvanMechatronics in Medicine Laboratory, Department of Mechanical Engineering, Imperial College, London, UK.
Ferdinando Rodriguez Y BaenaMechatronics in Medicine Laboratory, Department of Mechanical Engineering, Imperial College, London, UK.

Funding

Horizon 2020 688279
6 · The paper itself

Abstract

purposeIn the context of minimally invasive neurosurgery, steerable needles such as the one developed within the Horizon2020-funded EDEN2020 project (Frasson et al. in Proc Inst Mech Eng Part H J Eng Med 224(6):775-88, 2010. https://doi.org/10.1243/09544119JEIM663 ; Secoli and y Baena in IEEE international conference on robotics and automation, 2013) aspire to address the clinical challenge of better treatment for cancer patients. The direct, precise infusion of drugs in the proximity of a tumor has been shown to enhance its effectiveness and diffusion in the surrounding tissue (Vogelbaum and Aghi in Neuro-Oncology 17(suppl 2):ii3-ii8, 2015. https://doi.org/10.1093/neuonc/nou354 ). However, planning for an appropriate insertion trajectory for needles such as the one proposed by EDEN2020 is challenging due to factors like kinematic constraints, the presence of complex anatomical structures such as brain vessels, and constraints on the required start and target poses.

methodsWe propose a new parallelizable three-dimensional (3D) path planning approach called Adaptive Hermite Fractal Tree (AHFT), which is able to generate 3D obstacle-free trajectories that satisfy curvature constraints given a specified start and target pose. The AHFT combines the Adaptive Fractal Tree algorithm's efficiency (Liu et al. in IEEE Robot Autom Lett 1(2):601-608, 2016. https://doi.org/10.1109/LRA.2016.2528292 ) with optimized geometric Hermite (Yong and Cheng in Comput Aided Geom Des 21(3):281-301, 2004. https://doi.org/10.1016/j.cagd.2003.08.003 ) curves, which are able to handle heading constraints.

resultsSimulated results demonstrate the robustness of the AHFT to perturbations of the target position and target heading. Additionally, a simulated preoperative environment, where the surgeon is able to select a desired entry pose on the patient's skull, confirms the ability of the method to generate multiple feasible trajectories for a patient-specific case.

conclusionsThe AHFT method can be adopted in any field of application where a 3D path planner with kinematic and heading constraints on both start and end poses is required.

Indexed as

AlgorithmsImaging, Three-DimensionalFractalsHumansNeoplasmsNeurosurgical ProceduresRoboticsBio-inspiredMinimally invasive surgeryNeedle steeringNonholonomic constraintPath planningRobotic surgery

Identifiers

PMID30790172
PMCPMC6420904

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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.