Evidence map›Paper›PMID 32746182›Full record

ArticleIEEE transactions on ultrasonics, ferroelectrics, and frequency control2021

Real-Time Passive Acoustic Mapping Using Sparse Matrix Multiplication.

Hermes A S Kamimura, Shih-Ying Wu, Julien Grondin, Robin Ji, Christian Aurup, Wenlan Zheng, Marc Heidmann, Antonios N Pouliopoulos, Elisa E Konofagou

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

13 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Three-Dimensional Super-Resolution Passive Cavitation Mapping in Laser Lithotripsy.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024
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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

9 authors at 2 institutions in 1 country.

Hermes A S Kamimura
Shih-Ying Wu
Julien Grondin
Robin Ji
Christian Aurup
Wenlan Zheng
Marc Heidmann
Antonios N Pouliopoulos
Elisa E Konofagou
Columbia University · USBoston Children's Hospital · US

Funding

Assessment of Ultrsound-facilitated Neurotherapeutics in Alzheimer's DiseaseR01AG038961 · NIA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI KONOFAGOU, ELISA E. · 2011 to 2020
$5.1M
Optimization of ultrasound-facilitated blood-brain barrier openingR01EB009041 · NIBIB · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI KONOFAGOU, ELISA E. · 2008 to 2017
$4.4M
A theranostic system for ultrasound-facilitated blood-brain barrier openingR01EB029338 · NIBIB · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KONOFAGOU, ELISA E. · 2020 to 2023
$2.6M
Mechanistic Monitoring of Ultrasound NeuromodulationR01EB027576 · NIBIB · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KONOFAGOU, ELISA E. · 2019 to 2022
$2.5M
Focused ultrasound for noninvasive brain stimulationR01MH112142 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FERRERA, VINCENT P, KONOFAGOU, ELISA E. · 2017 to 2021
$2.1M
NIA NIH HHS R01 AG038961NIBIB NIH HHS R01 EB009041NIBIB NIH HHS R01 EB027576NIBIB NIH HHS R01 EB029338NIMH NIH HHS R01 MH112142
6 · The paper itself

Abstract

Passive acoustic mapping enables the spatiotemporal monitoring of cavitation with circulating microbubbles during focused ultrasound (FUS)-mediated blood-brain barrier opening. However, the computational load for processing large data sets of cavitation maps or more complex algorithms limit the visualization in real-time for treatment monitoring and adjustment. In this study, we implemented a graphical processing unit (GPU)-accelerated sparse matrix-based beamforming and time exposure acoustics in a neuronavigation-guided ultrasound system for real-time spatiotemporal monitoring of cavitation. The system performance was tested in silico through benchmarking, in vitro using nonhuman primate (NHP) and human skull specimens, and demonstrated in vivo in NHPs. We demonstrated the stability of the cavitation map for integration times longer than 62.5 [Formula: see text]. A compromise between real-time displaying and cavitation map quality obtained from beamformed RF data sets with a size of 2000 ×128 ×30 (axial [Formula: see text]) was achieved for an integration time of [Formula: see text], which required a computational time of 0.27 s (frame rate of 3.7 Hz) and could be displayed in real-time between pulses at PRF = 2 Hz. Our benchmarking tests show that the GPU sparse-matrix algorithm processed the RF data set at a computational rate of [Formula: see text]/pixel/sample, which enables adjusting the frame rate and the integration time as needed. The neuronavigation system with real-time implementation of cavitation mapping facilitated the localization of the cavitation activity and helped to identify distortions due to FUS phase aberration. The in vivo test of the method demonstrated the feasibility of GPU-accelerated sparse matrix computing in a close to a clinical condition, where focus distortions exemplify problems during treatment. These experimental conditions show the need for spatiotemporal monitoring of cavitation with real-time capability that enables the operator to correct or halt the sonication in case substantial aberrations are observed.

Indexed as

AcousticsMicrobubblesAlgorithmsAnimalsBlood-Brain BarrierUltrasonography

Identifiers

PMID32746182
PMCPMC7770101
OpenAlexW3038149507

What OpenQuestion holds

Textmetadata
LicenceTDM
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.