Evidence map›Paper›PMID 33468358›Full record

ArticleUltrasound in medicine & biology2021

Improved Ultrasound Microvessel Imaging Using Deconvolution with Total Variation Regularization.

U-Wai Lok, Joshua D Trzasko, Chengwu Huang, Shanshan Tang, Ping Gong, Yohan Kim, Fabrice Lucien, Matthew R Lowerison, Pengfei Song, Shigao Chen

Abstract read
In one paragraph

Article in Ultrasound in medicine & biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. High-Resolution Power Doppler Using Null Subtraction Imaging.IEEE transactions on medical imaging · 2024
    Article
  4. Super-Resolution Ultrasound Imaging for Monitoring the Therapeutic Efficacy of a Vascular Disrupting Agent in an Animal Model of Breast Cancer.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2024
    Article
  5. Contrast-Free Super-Resolution Power Doppler (CS-PD) Based on Deep Neural Networks.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2023
    Article
  6. Article
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

10 authors.

U-Wai LokDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA.
Joshua D TrzaskoDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA.
Chengwu HuangDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA.
Shanshan TangDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA.
Ping GongDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA.
Yohan KimDepartment of Urology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota, USA.
Fabrice LucienDepartment of Urology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota, USA.
Matthew R LowerisonDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA; Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA; Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Pengfei SongDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA; Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA; Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Shigao ChenDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA. Electronic address: Chen.Shigao@mayo.edu.

Funding

Quantitative Ultrasound Imaging Biomarkers of Crohn's DiseaseR01DK120559 · NIDDK · MAYO CLINIC ROCHESTER · PI BRUINING, DAVID HENRY, CHEN, SHIGAO · 2019 to 2022
$1.7M
Early prediction of colorectal liver metastases treatment response with ultrasound microvessel imagingR00CA214523 · NCI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI SONG, PENGFEI · 2019 to 2021
$684k
Long-Coded Pulses in Contrast-Enhanced Ultrasound Imaging for Improved Endocardial Border DelineationR03EB027742 · NIBIB · MAYO CLINIC ROCHESTER · PI GONG, PING · 2019 to 2020
$159k
NCI NIH HHS R00 CA214523NIBIB NIH HHS R03 EB027742NIDDK NIH HHS R01 DK120559
6 · The paper itself

Abstract

Singular value decomposition-based clutter filters can robustly reject tissue clutter, allowing for detection of slow blood flow in imaging microvasculature. However, to identify microvessels, high ultrasound frequency must be used to increase the spatial resolution at the expense of shorter depth of penetration. Deconvolution using Tikhonov regularization is an imaging processing method widely used to improve spatial resolution. The ringing artifact of Tikhonov regularization, though, can produce image artifacts such as non-existent microvessels, which degrade image quality. Therefore, a deconvolution method using total variation is proposed in this study to improve spatial resolution and mitigate the ringing artifact. Performance of the proposed method was evaluated using chicken embryo brain, ex ovo chicken embryo chorioallantoic membrane and tumor data. Results revealed that the reconstructed power Doppler (PD) images are substantially improved in spatial resolution compared with original PD images: the full width half-maximum (FWHM) of the cross-sectional profile of a microvessel was improved from 132 to 83 µm. Two neighboring microvessels that were 154 µm apart were better separated using the proposed method than conventional PD imaging. Additionally, 223 FWHMs measured from the cross-sectional profiles of 223 vessels were used to determine the improvement in FWHM with the proposed method statistically. The mean ± standard deviation of the FWHM without and with the proposed method was 233.19 ± 85.08 and 172.31 ± 75.11 μm, respectively; the maximum FWHM without and with the proposed method was 693.01 and 668.69 μm; and the minimum FWHM without and with the proposed method was 73.92 and 45.74 μm. There were statistically significant differences between FWHMs with and without the proposed method according to the rank-sum test, p < 0.0001. The contrast-to-noise ratio improved from 1.06 to 4.03 dB with use of the proposed method. We also compared the proposed method with Tikhonov regularization using ex ovo chicken embryo chorioallantoic membrane data. We found that the proposed method outperformed Tikhonov regularization as false microvessels appeared using the Tikhonov regularization but not with the proposed method. These results indicate that the proposed method is capable of providing more robust PD images with higher spatial resolution and higher contrast-to-noise ratio.

Indexed as

AnimalsArtifactsBrainCarcinoma, Renal CellChick EmbryoChorioallantoic MembraneImage Processing, Computer-AssistedMicrovesselsNeoplasm TransplantationSignal Processing, Computer-AssistedSignal-To-Noise RatioUltrasonography, DopplerDeconvolutionMicrovessel imagingPower Doppler imaging

Identifiers

PMID33468358
PMCPMC7908678

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Registered trials

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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.