Evidence map›Paper›PMID 41760998›Full record

ArticleCardiovascular and interventional radiology2026

Can a Free Open-Source Software Platform Serve as Minimal Ablation Confirmation Assessment Software in Real-Life Practice?

Francesca Menchini, Davide Noascone, Fernanda Ciferri, Carlo Gazzera, Manuela Balma, Paolo Fonio, Bruno Odisio, Marco Calandri, Iwan Paolucci

Abstract read
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In one paragraph

Article in Cardiovascular and interventional radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Francesca MenchiniDepartment of Diagnostic and Interventional Radiology, A.O.U. Città della Salute e della Scienza, Molinette Hospital, Turin, Italy. francesca.menchini@unito.it.ORCID http://orcid.org/0009-0004-7244-525X
Davide NoasconeDepartment of Surgical Sciences, University of Turin, A.O.U. Città della Salute e della Scienza, Turin, Italy.
Fernanda CiferriDepartment of Diagnostic and Interventional Radiology, A.O.U. Città della Salute e della Scienza, Molinette Hospital, Turin, Italy.
Carlo GazzeraDepartment of Diagnostic and Interventional Radiology, A.O.U. Città della Salute e della Scienza, Molinette Hospital, Turin, Italy.
Manuela BalmaDepartment of Diagnostic and Interventional Radiology, A.O.U. Città della Salute e della Scienza, Molinette Hospital, Turin, Italy.
Paolo FonioDepartment of Surgical Sciences, University of Turin, A.O.U. Città della Salute e della Scienza, Turin, Italy.
Bruno OdisioDepartment of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Marco Calandri *Department of Surgical Sciences, University of Turin, A.O.U. Città della Salute e della Scienza, Turin, Italy.
Iwan Paolucci *Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

Università degli Studi di Torino Grant RiLo2023
6 · The paper itself

Abstract

purposeThe study aims to evaluate the potential of the free open-source general purpose image processing software 3D Slicer for minimal ablative margin (MAM) evaluation. MATERIAL AND

methods3D Slicer was retrospectively applied to assess MAM of ablated liver tumors with pre and post intraprocedural CT. Three operators with different years of experience were involved: two of them assessed the MAMs using 3D Slicers software with the segmentation and registration tools and Model-to-Model extension, and categorized MAM in three categories (≤ 0 mm, > 0- < 5 mm, ≥ 5 mm), while the third operator performed a visual assessment of the same MAMs. Concordance among the three operators (K Cohen) and image processing time for MAMs evaluation was evaluated.

resultsAmong 60 ablated tumors between April 2023 and January 2024, 24 tumors from 20 patients (median age 64.8 ± 9.7 years, 80% male) were included in the analysis. Insufficient accuracy registration was the main cause of exclusion. Substantial agreement was found between operators using 3D Slicer across all three categories (≤ 0 mm, > 0- < 5 mm, ≥ 5 mm), with K Cohen between 0.65 and 0.74. Instead, slight or no agreement between software's and visual assessment results was found (K Cohen between - 0.30 and 0.11). Mean time to calculate MAM was respectively of 25' and 16″ for operator 2 and 49' and 26″ for operator 3.

conclusionStrong inter-reader agreement using 3D-Slicer is encouraging, but its workflow and time demands limit clinical use, highlighting the need for task-specific software.

Indexed as

Imaging, Three-DimensionalLiver NeoplasmsMargins of ExcisionRadiographic Image Interpretation, Computer-AssistedSoftwareTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedRetrospective StudiesAblation confirmationLiver thermal ablationMinimal ablative margin

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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.