Evidence map›Paper›PMID 38172949›Full record

Trial reportCancer imaging : the official publication of the International Cancer Imaging Society2024

Contrast-enhanced ultrasonography-CT/MRI fusion guidance for percutaneous ablation of inconspicuous, small liver tumors: improving feasibility and therapeutic outcome.

Yuna Lee, Jeong Hee Yoon, Seungchul Han, Ijin Joo, Jeong Min Lee

Registry-linked trialOpen access · goldAbstract readClinical Trial
In one paragraph

Trial report in Cancer imaging : the official publication of the International Cancer Imaging Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05445973 (Real-Time Contrast-Enhanced Ultrasonography-CT/MRI Fusion Guidance for Percutaneous Radiofrequency Ablation of Inconspicuous, Small Liver Tumors), which is not on this map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
5.5field-weighted citation impact, top 3% 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.

NCT05445973 nacompletednot on this map

Real-Time Contrast-Enhanced Ultrasonography-CT/MRI Fusion Guidance for Percutaneous Radiofrequency Ablation of Inconspicuous, Small Liver Tumors

TypeinterventionalSponsorSeoul National University HospitalRan2019 to 2022Enrolled248ConditionsRadiofrequency Ablation, Ultrasonography, Liver TumorsArmsPercutaneous Radiofrequency Ablation
3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Guideline
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  8. Review
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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

5 authors at 3 institutions in 3 countries.

Yuna LeeDepartment of Radiology, Seoul National University Hospital, #101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Jeong Hee YoonDepartment of Radiology, Seoul National University Hospital, #101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Seungchul HanDepartment of Radiology, Seoul National University Hospital, #101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Ijin JooDepartment of Radiology, Seoul National University Hospital, #101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Jeong Min LeeDepartment of Radiology, Seoul National University Hospital, #101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea. jmsh@snu.ac.kr.ORCID http://orcid.org/0000-0003-0561-8777
Seoul National University · KRSeoul National University Hospital · KRNew Generation University College · ET

Funding

Canon Medical Systems Corporation 0620101950Siemens Healthineers 0620200760
6 · The paper itself

Abstract

backgroundPercutaneous radiofrequency ablation (RFA) is pivotal for treating small malignant liver tumors, but tumors often remain inconspicuous on B-mode ultrasound (US). This study evaluates the potential of CEUS-CT/MRI fusion imaging (FI) to improve tumor visibility and the associated RFA outcomes for small (≤ 3 cm) malignant liver tumors that were inconspicuous on US.

methodsBetween January 2019 and April 2021, a prospective study enrolled 248 patients with liver malignancies (≤ 3 cm) that were poorly visible on B-mode US. Tumor visibility and ablation feasibility were assessed using B-mode US, US-CT/MRI FI, and CEUS-CT/MRI FI, and graded on a 4-point scale. CEUS was employed post-registration of US and CT/MRI images, utilizing either SonoVue or Sonazoid. Comparisons between US-based and CEUS-based fusion visibility and feasibility scores were undertaken using the Friedman test. Moreover, rates of technical success, technique efficacy, local tumor progression (LTP), and major complications were assessed.

resultsThe cohort included 223 hepatocellular carcinomas (HCCs) (89.9%) and 23 metastases (9.3%), with an average tumor size of 1.6 cm. CEUS-CT/MRI FI demonstrated a significant advantage in tumor visibility (3.4 ± 0.7 vs. 1.9 ± 0.6, P < 0.001) and technical feasibility (3.6 ± 0.6 vs. 2.9 ± 0.8, P < 0.001) compared to US-FI. In 85.5% of patients, CEUS addition to US-FI ameliorated tumor visibility. Technical success was achieved in 99.6% of cases. No severe complications were reported. One and two-year post CEUS-CT/MRI FI-guided RFA estimates for LTP were 9.3% and 10.9%, respectively.

conclusionsCEUS-CT/MRI FI significantly improves the visualization of tumors not discernible on B-mode US, thus augmenting percutaneous RFA success and delivering improved therapeutic outcomes.

trial registrationClinicalTrials.gov, NCT05445973. Registered 17 June 2022 - Retrospectively registered, http://clinicaltrials.gov/study/NCT05445973?id=NCT05445973&rank=1 .

Indexed as

Carcinoma, HepatocellularCatheter AblationLiver NeoplasmsContrast MediaFeasibility StudiesHumansMagnetic Resonance ImagingProspective StudiesTomography, X-Ray ComputedTreatment OutcomeUltrasonographyContrast MediaAblationFusion imagingLiver malignanciesTreatment outcomeUltrasound

Identifiers

PMID38172949
PMCPMC10762814
OpenAlexW4390572504

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.