Evidence map›Paper›PMID 30078152›Full record

ReviewInternational journal of computer assisted radiology and surgery2018

Model checking for trigger loss detection during Doppler ultrasound-guided fetal cardiovascular MRI.

Sven-Thomas Antoni, Sascha Lehmann, Maximilian Neidhardt, Kai Fehrs, Christian Ruprecht, Fabian Kording, Gerhard Adam, Sibylle Schupp, Alexander Schlaefer

Abstract readReview
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In one paragraph

Review in International journal of computer assisted radiology and surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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

9 authors at 2 institutions in 1 country.

Sven-Thomas AntoniInstitute of Medical Technology, Hamburg University of Technology, Hamburg, Germany. antoni@tuhh.de.ORCID http://orcid.org/0000-0003-4127-2697
Sascha LehmannInstitute for Software Systems, Hamburg University of Technology, Hamburg, Germany.
Maximilian NeidhardtInstitute of Medical Technology, Hamburg University of Technology, Hamburg, Germany.
Kai FehrsCenter for Radiology and Endoscopy, Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Christian RuprechtCenter for Radiology and Endoscopy, Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Fabian KordingCenter for Radiology and Endoscopy, Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Gerhard AdamCenter for Radiology and Endoscopy, Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Sibylle SchuppInstitute for Software Systems, Hamburg University of Technology, Hamburg, Germany.
Alexander SchlaeferInstitute of Medical Technology, Hamburg University of Technology, Hamburg, Germany.
Universität Hamburg · DEUniversity Medical Center Hamburg-Eppendorf · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeUltrasound (US) is the state of the art in prenatal diagnosis to depict fetal heart diseases. Cardiovascular magnetic resonance imaging (CMRI) has been proposed as a complementary diagnostic tool. Currently, only trigger-based methods allow the temporal and spatial resolutions necessary to depict the heart over time. Of these methods, only Doppler US (DUS)-based triggering is usable with higher field strengths. DUS is sensitive to motion. This may lead to signal and, ultimately, trigger loss. If too many triggers are lost, the image acquisition is stopped, resulting in a failed imaging sequence. Moreover, losing triggers may prolong image acquisition. Hence, if no actual trigger can be found, injected triggers are added to the signal based on the trigger history.

methodWe use model checking, a technique originating from the computer science domain that formally checks if a model satisfies given requirements, to simultaneously model heart and respiratory motion and to decide whether respiration has a prominent effect on the signal. Using bounds on the physiological parameters and their variability, the method detects when changes in the signal are due to respiration. We use this to decide when to inject a trigger.

resultsIn a real-world scenario, we can reduce the number of falsely injected triggers by 94% from more than 87% to less than 5%. On a subset of motion that would allow CMRI, the number can be further reduced to below 0.2%. In a study using simulations with a robot, we show that our method works for different types of motions, motion ranges, starting positions and heartbeat traces.

conclusionWhile DUS is a promising approach for fetal CMRI, correct trigger injection is critical. Our model checking method can reduce the number of wrongly injected triggers substantially, providing a key prerequisite for fast and artifact free CMRI.

Indexed as

FemaleFetal HeartHeart DiseasesHumansMagnetic Resonance ImagingModels, BiologicalPregnancyPrenatal DiagnosisSignal Processing, Computer-AssistedUltrasonography, DopplerCardiovascularFetalHeartModel checkingMRITriggering

Identifiers

PMID30078152
OpenAlexW2885401093

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.