Evidence map›Paper›PMID 38377383›Full record

ArticleMedical physics2024

Motion correction of 3D dynamic contrast-enhanced ultrasound imaging without anatomical B-Mode images: Pilot evaluation in eight patients.

Jia-Shu Chen, Maged Goubran, Gaeun Kim, Matthew J Kim, Jürgen K Willmann, Michael Zeineh, Dimitre Hristov, Ahmed El Kaffas

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

8 authors.

Jia-Shu ChenDepartment of Neuroscience, Brown University, Providence, Rhode Island, USA.
Maged GoubranSunnybrook Health Sciences Center, Toronto, Ontario, Canada.
Gaeun KimDepartment of Radiology, Stanford University, Stanford, California, USA.
Matthew J KimDepartment of Radiation Oncology - Radiation Physics, Stanford School of Medicine, Stanford University, Stanford, California, USA.
Jürgen K Willmann *Department of Radiology, Molecular Imaging Program, Stanford School of Medicine, Stanford University, Stanford, California, USA.
Michael ZeinehDepartment of Radiology, Stanford University, Stanford, California, USA.
Dimitre HristovDepartment of Radiation Oncology - Radiation Physics, Stanford School of Medicine, Stanford University, Stanford, California, USA.
Ahmed El KaffasDepartment of Radiology, Molecular Imaging Program, Stanford School of Medicine, Stanford University, Stanford, California, USA.

Funding

Three-Dimensional Multi-Parametric Ultrasound for Monitoring Therapy of Liver MetastasisR01CA195443 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Ahmed El Kaffas · 2016 to 2026
$3.6M
NCI NIH HHS R01 CA195443
6 · The paper itself

Abstract

backgroundDynamic contrast-enhanced ultrasound (DCE-US) is highly susceptible to motion artifacts arising from patient movement, respiration, and operator handling and experience. Motion artifacts can be especially problematic in the context of perfusion quantification. In conventional 2D DCE-US, motion correction (MC) algorithms take advantage of accompanying side-by-side anatomical B-Mode images that contain time-stable features. However, current commercial models of 3D DCE-US do not provide side-by-side B-Mode images, which makes MC challenging. PURPOSE: This work introduces a novel MC algorithm for 3D DCE-US and assesses its efficacy when handling clinical data sets.

methodsIn brief, the algorithm uses a pyramidal approach whereby short temporal windows consisting of three consecutive frames are created to perform local registrations, which are then registered to a master reference derived from a weighted average of all frames. We applied the algorithm to imaging studies from eight patients with metastatic lesions in the liver and assessed improvements in original versus motion corrected 3D DCE-US cine using: (i) frame-to-frame volumetric overlap of segmented lesions, (ii) normalized correlation coefficient (NCC) between frames (similarity analysis), and (iii) sum of squared errors (SSE), root-mean-squared error (RMSE), and r-squared (R

resultsWe noted improvements in frame-to-frame lesion overlap across all patients, from 68% ± 13% without correction to 83% ± 3% with MC (p = 0.023). Frame-to-frame similarity as assessed by NCC also improved on two different sets of time points from 0.694 ± 0.057 (original cine) to 0.862 ± 0.049 (corresponding MC cine) and 0.723 ± 0.066 to 0.886 ± 0.036 (p ≤ 0.001 for both). TIC analysis displayed a significant decrease in RMSE (p = 0.018) and a significant increase in R

conclusionsOverall, results suggest decreases in 3D DCE-US motion after applying the proposed algorithm.

Indexed as

AlgorithmsContrast MediaImaging, Three-DimensionalUltrasonographyArtifactsFemaleHumansLiver NeoplasmsMaleMiddle AgedMovementPilot ProjectsContrast Mediacancercontrast‐enhanced (CE)dynamic contrast‐enhanced ultrasound (DCE‐US)motion correction (MC)three‐dimensional (3D)ultrasound (US)

Identifiers

PMID38377383
PMCPMC11913309

What OpenQuestion holds

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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.