Evidence map›Paper›PMID 34083642›Full record

ArticleScientific reports2021

Quantitative analysis of in-vivo microbubble distribution in the human brain.

Francesco Prada, Antonio G Gennari, Ian M Linville, Michael E Mutersbaugh, Zhihang Chen, Natasha Sheybani, Francesco DiMeco, Frederic Padilla, John A Hossack

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 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, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. 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 6 institutions in 2 countries.

Francesco PradaDepartment of Neurological Surgery, University of Virginia Health System, Charlottesville, VA, USA. francesco.prada@istituto-besta.it.
Antonio G GennariNeuroradiology Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy.
Ian M LinvilleBiomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Michael E MutersbaughBiomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Zhihang ChenFocused Ultrasound Foundation, Charlottesville, VA, USA.
Natasha SheybaniBiomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Francesco DiMecoDepartment of Neurosurgery, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy.
Frederic PadillaFocused Ultrasound Foundation, Charlottesville, VA, USA.
John A HossackBiomedical Engineering, University of Virginia, Charlottesville, VA, USA.
University of Virginia · USFocused Ultrasound Foundation · USJohns Hopkins University · USNeurological Surgery · USOspedale di Cattinara · ITUniversity of Virginia Health System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbubbles (MB) are widely used as contrast agents to perform contrast-enhanced ultrasound (CEUS) imaging and as acoustic amplifiers of mechanical bioeffects incited by therapeutic-level ultrasound. The distribution of MBs in the brain is not yet fully understood, thereby limiting intra-operative CEUS guidance or MB-based FUS treatments. In this paper we describe a robust platform for quantification of MB distribution in the human brain, allowing to quantitatively discriminate between tumoral and normal brain tissues and we provide new information regarding real-time cerebral MBs distribution. Intraoperative CEUS imaging was performed during surgical tumor resection using an ultrasound machine (MyLab Twice, Esaote, Italy) equipped with a multifrequency (3-11 MHz) linear array probe (LA332) and a specific low mechanical index (MI < 0.4) CEUS algorithm (CnTi, Esaote, Italy; section thickness, 0.245 cm) for non-destructive continuous MBs imaging. CEUS acquisition is started by enabling the CnTI PEN-M algorithm automatically setting the MI at 0.4 with a center frequency of 2.94 MHz-10 Hz frame rate at 80 mm-allowing for continuous non-destructive MBs imaging. 19 ultrasound image sets of adequate length were selected and retrospectively analyzed using a custom image processing software for quantitative analysis of echo power. Regions of interest (ROIs) were drawn on key structures (artery-tumor-white matter) by a blinded neurosurgeon, following which peak enhancement and time intensity curves (TICs) were quantified. CEUS images revealed clear qualitative differences in MB distribution: arteries showed the earliest and highest enhancement among all structures, followed by tumor and white matter regions, respectively. The custom software built for quantitative analysis effectively captured these differences. Quantified peak intensities showed regions containing artery, tumor or white matter structures having an average MB intensity of 0.584, 0.436 and 0.175 units, respectively. Moreover, the normalized area under TICs revealed the time of flight for MB to be significantly lower in brain tissue as compared with tumor tissue. Significant heterogeneities in TICs were also observed within different regions of the same brain lesion. In this study, we provide the most comprehensive strategy for accurate quantitative analysis of MBs distribution in the human brain by means of CEUS intraoperative imaging. Furthermore our results demonstrate that CEUS imaging quantitative analysis enables discernment between different types of brain tumors as well as regions and structures within the brain. Similar considerations will be important for the planning and implementation of MB-based imaging or treatments in the future.

Indexed as

Contrast MediaImage EnhancementMicrobubblesAdultAgedBrainBrain NeoplasmsData AnalysisFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedUltrasonographyYoung AdultContrast Media

Identifiers

PMID34083642
PMCPMC8175375
OpenAlexW3165573495

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.