Evidence map›Paper›PMID 31471752›Full record

Trial reportEuropean radiology2020

Clinical evaluation of in silico planning and real-time simulation of hepatic radiofrequency ablation (ClinicIMPPACT Trial).

Michael Moche, Harald Busse, Jurgen J Futterer, Camila A Hinestrosa, Daniel Seider, Philipp Brandmaier, Marina Kolesnik, Sjoerd Jenniskens, Roberto Blanco Sequeiros, Gaber Komar and 7 more

Abstract readClinical TrialMulticenter Study
PubMed Publisher
In one paragraph

Trial report in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Software-based planning of ultrasound and CT-guided percutaneous radiofrequency ablation in hepatic tumors.International journal of computer assisted radiology and surgery · 2021
    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

17 authors.

Michael MocheDepartment of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103, Leipzig, Germany.
Harald BusseDepartment of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103, Leipzig, Germany.
Jurgen J FuttererDepartment of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, Netherlands.
Camila A HinestrosaDepartment of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103, Leipzig, Germany.
Daniel SeiderDepartment of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103, Leipzig, Germany.
Philipp BrandmaierDepartment of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103, Leipzig, Germany.
Marina KolesnikFraunhofer Institute for Applied Information Technology FIT, Sankt Augustin, Germany.
Sjoerd JenniskensDepartment of Radiology and Nuclear Medicine, Radboudumc, Nijmegen, Netherlands.
Roberto Blanco SequeirosDepartment of Radiology, Turku University Hospital, Turku, Finland.
Gaber KomarDepartment of Radiology, Turku University Hospital, Turku, Finland.
Mika PollariDepartment of Computer Science, Aalto University School of Science and Technology, 02150, Espoo, Finland.
Martin EibisbergerUniversity Clinic of Radiology Graz, Graz, Austria.
Horst Rupert PortugallerUniversity Clinic of Radiology Graz, Graz, Austria.
Philip VoglreiterInstitute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria.
Ronan FlanaganNUMA Engineering Services Ltd., Louth, Ireland.
Panchatcharam MariappanNUMA Engineering Services Ltd., Louth, Ireland.
Martin ReinhardtDepartment of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Liebigstraße 20, 04103, Leipzig, Germany. martin.reinhardt@medizin.uni-leipzig.de.ORCID http://orcid.org/0000-0002-7288-0639

Funding

FP7 Health grant #610886; grant #600641
6 · The paper itself

Abstract

objectivesTo evaluate the accuracy and clinical integrability of a comprehensive simulation tool to plan and predict radiofrequency ablation (RFA) zones in liver tumors.

methodsForty-five patients with 51 malignant hepatic lesions of different origins were included in a prospective multicenter trial. Prior to CT-guided RFA, all patients underwent multiphase CT which included acquisitions for the assessment of liver perfusion. These data were used to generate a 3D model of the liver. The intra-procedural position of the RFA probe was determined by CT and semi-automatically registered to the 3D model. Size and shape of the simulated ablation zones were compared with those of the thermal ablation zones segmented in contrast-enhanced CT images 1 month after RFA; procedure time was compared with a historical control group.

resultsSimulated and segmented ablation zone volumes showed a significant correlation (ρ = 0.59, p < 0.0001) and no significant bias (Wilcoxon's Z = 0.68, p = 0.25). Representative measures of ablation zone comparison were as follows: average surface deviation (absolute average error, AAE) with 3.4 ± 1.7 mm, Dice similarity coefficient 0.62 ± 0.14, sensitivity 0.70 ± 0.21, and positive predictive value 0.66 ± 0. There was a moderate positive correlation between AAE and duration of the ablation (∆t; r = 0.37, p = 0.008). After adjustments for inter-individual differences in ∆t, liver perfusion, and prior transarterial chemoembolization procedures, ∆t was an independent predictor of AAE (ß = 0.03 mm/min, p = 0.01). Compared with a historical control group, the simulation added 3.5 ± 1.9 min to the procedure.

conclusionThe validated simulation tool showed acceptable speed and accuracy in predicting the size and shape of hepatic RFA ablation zones. Further randomized controlled trials are needed to evaluate to what extent this tool might improve patient outcomes. KEY POINTS: • More reliable, patient-specific intra-procedural estimation of the induced RFA ablation zones in the liver may lead to better planning of the safety margins around tumors. • Dedicated real-time simulation software to predict RFA-induced ablation zones in patients with liver malignancies has shown acceptable agreement with the follow-up results in a first prospective multicenter trial suggesting a randomized controlled clinical trial to evaluate potential outcome benefit for patients.

Indexed as

AdolescentAdultAgedCarcinoma, HepatocellularCatheter AblationChemoembolization, TherapeuticComputer SimulationFemaleHumansLiverLiver NeoplasmsMaleMargins of ExcisionMiddle AgedPatient Care PlanningProspective StudiesLiverPerfusionRadiofrequency ablationSoftware

Identifiers

What OpenQuestion holds

Textmetadata
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.