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Record W2900912348 · doi:10.1002/mp.13298

Selective embolization with magnetized microbeads using magnetic resonance navigation in a controlled‐flow liver model

2018· article· en· W2900912348 on OpenAlexafffund
François Michaud, Ning Li, Rosalie Plantefève, Zeynab Nosrati, Charles Tremblay, Katayoun Saatchi, Gerald Moran, Alexandre Bigot, Urs O. Häfeli, Samuel Kadoury, An Tang, Pierre Perreault, Sylvain Martel, Gilles Soulez

Bibliographic record

VenueMedical Physics · 2018
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsSiemens (Canada)Polytechnique MontréalUniversité de MontréalUniversity of British ColumbiaCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsImaging phantomMagnetic resonance imagingBiomedical engineeringPulsatile flowBlood flowEmbolizationMaterials scienceFlow velocityFlow (mathematics)Nuclear medicinePhysicsMechanicsRadiologyMedicine

Abstract

fetched live from OpenAlex

Purpose The purpose of this study was to demonstrate the feasibility of using a custom gradient sequence on an unmodified 3T magnetic resonance imaging ( MRI ) scanner to perform magnetic resonance navigation ( MRN ) by investigating the blood flow control method in vivo , reproducing the obtained rheology in a phantom mimicking porcine hepatic arterial anatomy, injecting magnetized microbead aggregates through an implantable catheter, and steering the aggregates across arterial bifurcations for selective tumor embolization. Materials and Methods In the first phase, arterial hepatic velocity was measured using cine phase‐contrast imaging in seven pigs under free‐flow conditions and controlled‐flow conditions, whereby a balloon catheter is used to occlude arterial flow and saline is injected at different rates. Three of the seven pigs previously underwent selective lobe embolization to simulate a chemoembolization procedure. In the second phase, the measured in vivo controlled‐flow velocities were approximately reproduced in a Y‐shaped vascular bifurcation phantom by injecting saline at an average rate of 0.6 mL /s with a pulsatile component. Aggregates of 200‐μm magnetized particles were steered toward the right or left hepatic branch using a 20‐ mT /m MRN gradient. The phantom was oriented at 0°, 45°, and 90° with respect to the B 0 magnetic field. The steering differences between left–right gradient and baseline were calculated using Fisher's exact test. A theoretical model of the trajectory of the aggregate within the main phantom branch taking into account gravity, magnetic force, and hydrodynamic drag was also designed, solved, and validated against the experimental results to characterize the physical limitations of the method. Results At an injection rate of 0.5 mL /s, the average flow velocity decreased from 20 ± 15 to 8.4 ± 5.0 cm/s after occlusion in nonembolized pigs and from 13.6 ± 2.0 to 5.4 ± 3.0 cm/s in previously embolized pigs. The pulsatility index measured to be 1.7 ± 1.8 and 1.1 ± 0.1 for nonembolized and embolized pigs, respectively, decreased to 0.6 ± 0.4 and 0.7 ± 0.3 after occlusion. For MRN performed at each orientation, the left–right distribution of aggregates was 55%, 25%, and 75% on baseline and 100%, 100%, and 100% ( P < 0.001, P = 0.003, P = 0.003) after the application of MRN , respectively. According to the theoretical model, the aggregate reaches a stable transverse position located toward the direction of the gradient at a distance equal to 5.8% of the radius away from the centerline within 0.11 s, at which point the aggregate will have transited through a longitudinal distance of 1.0 mm from its release position. Conclusion In this study, we showed that the use of a balloon catheter reduces arterial hepatic flow magnitude and variation with the aim to reduce steering failures caused by fast blood flow rates and low magnetic steering forces. A mathematical model confirmed that the reduced flow rate is low enough to maximize steering ratio. After reproducing the flow rate in a vascular bifurcation phantom, we demonstrated the feasibility of MRN after injection of microparticle aggregates through a dedicated injector. This work is an important step leading to MRN ‐based selective embolization techniques in humans.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.254
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2018
Admission routes2
Has abstractyes

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