Evidence map›Paper›PMID 34647427›Full record

ArticleInternational journal for numerical methods in biomedical engineering2022

Computer simulation of tumour resection-induced brain deformation by a meshless approach.

Yue Yu, George Bourantas, Benjamin Zwick, Grand Joldes, Tina Kapur, Sarah Frisken, Ron Kikinis, Arya Nabavi, Alexandra Golby, Adam Wittek and 1 more

Abstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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.

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

4 citing papers in PubMed.

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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.

Yue YuIntelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.ORCID 0000-0002-1925-3038
George BourantasIntelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.ORCID 0000-0001-9503-4614
Benjamin ZwickIntelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.ORCID 0000-0003-0184-1082
Grand JoldesIntelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.ORCID 0000-0003-0496-5785
Tina KapurBrigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Sarah FriskenBrigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Ron KikinisBrigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-7227-7058
Arya NabaviDepartment of Neurosurgery, KRH Klinikum Nordstadt, Hannover, Germany.
Alexandra GolbyBrigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-8461-9561
Adam WittekIntelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.ORCID 0000-0001-9780-8361
Karol MillerIntelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.ORCID 0000-0002-6577-2082

Funding

Training and DisseminationP41EB015902 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI PUJOL, SONIA · 2012 to 2022
$20.9M
Image Guided Therapy Center - Ultrasound-based sensor system for the monitoring of COVID-19 patientsP41EB015898 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI TEMPANY, CLARE M · 2012 to 2021
$18.9M
TRD 3 - Enabling Technologies for Intraprocedural GuidanceP41EB028741 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI Nobuhiko Hata, CLARE M TEMPANY · 2021 to 2026
$10.7M
Continuous Compensation of Brain Shift during NeurosurgeryR01EB027134 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI FRISKEN, SARAH · 2018 to 2021
$1.8M
NIBIB NIH HHS P41 EB015898NIBIB NIH HHS P41 EB015902NIBIB NIH HHS P41 EB028741NIBIB NIH HHS R01 EB027134
6 · The paper itself

Abstract

Tumour resection requires precise planning and navigation to maximise tumour removal while simultaneously protecting nearby healthy tissues. Neurosurgeons need to know the location of the remaining tumour after partial tumour removal before continuing with the resection. Our approach to the problem uses biomechanical modelling and computer simulation to compute the brain deformations after the tumour is resected. In this study, we use meshless Total Lagrangian explicit dynamics as the solver. The problem geometry is extracted from the patient-specific magnetic resonance imaging (MRI) data and includes the parenchyma, tumour, cerebrospinal fluid and skull. The appropriate non-linear material formulation is used. Loading is performed by imposing intra-operative conditions of gravity and reaction forces between the tumour and surrounding healthy parenchyma tissues. A finite frictionless sliding contact is enforced between the skull (rigid) and parenchyma. The meshless simulation results are compared to intra-operative MRI sections. We also calculate Hausdorff distances between the computed deformed surfaces (ventricles and tumour cavities) and surfaces observed intra-operatively. Over 80% of points on the ventricle surface and 95% of points on the tumour cavity surface were successfully registered (results within the limits of two times the original in-plane resolution of the intra-operative image). Computed results demonstrate the potential for our method in estimating the tissue deformation and tumour boundary during the resection.

Indexed as

BrainHeadComputer SimulationFinite Element AnalysisHumansSkullbrain shiftmedical image registrationmeshless methodspatient-specific biomechanical simulationsTotal Lagrangian formulationtumour resection

Identifiers

PMID34647427
PMCPMC8881972

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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.