Evidence map›Paper›PMID 28271356›Full record

ArticleInternational journal of computer assisted radiology and surgery2017

Geometric modeling of hepatic arteries in 3D ultrasound with unsupervised MRA fusion during liver interventions.

Maxime Gérard, François Michaud, Alexandre Bigot, An Tang, Gilles Soulez, Samuel Kadoury

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 57% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 2 institutions in 1 country.

Maxime GérardInstitute of Biomedical Engineering, Polytechnique Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada.
François MichaudDepartment of Physics, Université de Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada.
Alexandre BigotCentre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Saint-Denis St, Montreal, QC, H2X 0A9, Canada.
An TangDepartment of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada.
Gilles SoulezDepartment of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada.
Samuel KadouryInstitute of Biomedical Engineering, Polytechnique Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada. samuel.kadoury@polymtl.ca.ORCID http://orcid.org/0000-0002-3048-4291
Centre Hospitalier de l’Université de Montréal · CAPolytechnique Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeModulating the chemotherapy injection rate with regard to blood flow velocities in the tumor-feeding arteries during intra-arterial therapies may help improve liver tumor targeting while decreasing systemic exposure. These velocities can be obtained noninvasively using Doppler ultrasound (US). However, small vessels situated in the liver are difficult to identify and follow in US. We propose a multimodal fusion approach that non-rigidly registers a 3D geometric mesh model of the hepatic arteries obtained from preoperative MR angiography (MRA) acquisitions with intra-operative 3D US imaging.

methodsThe proposed fusion tool integrates 3 imaging modalities: an arterial MRA, a portal phase MRA and an intra-operative 3D US. Preoperatively, the arterial phase MRA is used to generate a 3D model of the hepatic arteries, which is then non-rigidly co-registered with the portal phase MRA. Once the intra-operative 3D US is acquired, we register it with the portal MRA using a vessel-based rigid initialization followed by a non-rigid registration using an image-based metric based on linear correlation of linear combination. Using the combined non-rigid transformation matrices, the 3D mesh model is fused with the 3D US.

results3D US and multi-phase MRA images acquired from 10 porcine models were used to test the performance of the proposed fusion tool. Unimodal registration of the MRA phases yielded a target registration error (TRE) of [Formula: see text] mm. Initial rigid alignment of the portal MRA and 3D US yielded a mean TRE of [Formula: see text] mm, which was significantly reduced to [Formula: see text] mm ([Formula: see text]) after affine image-based registration. The following deformable registration step allowed for further decrease of the mean TRE to [Formula: see text] mm.

conclusionThe proposed tool could facilitate visualization and localization of these vessels when using 3D US intra-operatively for either intravascular or percutaneous interventions to avoid vessel perforation.

Indexed as

AlgorithmsAnimalsHepatic ArteryImaging, Three-DimensionalLiver NeoplasmsMagnetic Resonance AngiographyMultimodal ImagingSwineUltrasonographyFusionImage registrationMagnetic resonance angiographyUltrasoundVessel segmentation

Identifiers

PMID28271356
OpenAlexW2594498922

What OpenQuestion holds

Textmetadata
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.