Evidence map›Paper›PMID 37608564›Full record

ArticleTechnology in cancer research & treatment

Virtual Treatment Zone From Cone Beam CT Commonly Alters Treatment Plan and Identifies Tumor at Risk for Under-Treatment in US or US Fusion-Guided Microwave Ablation of Liver Tumors.

Antonio Arrichiello, Anna Maria Ierardi, Alessandro Caruso, Pasquale Grillo, Letizia Di Meglio, Pierpaolo Biondetti, Massimo Iavarone, Angelo Sangiovanni, Salvatore Alessio Angileri, Chiara Floridi and 2 more

Open access · goldAbstract read
In one paragraph

Article in Technology in cancer research & treatment. 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
0.2field-weighted citation impact, top 44% 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.

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 citations in OpenAlex.

  1. Review
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

12 authors at 3 institutions in 2 countries.

Antonio ArrichielloOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.ORCID 0000-0002-1250-8675
Anna Maria IerardiOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.
Alessandro CarusoOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.
Pasquale GrilloOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.
Letizia Di MeglioOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.
Pierpaolo BiondettiOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.
Massimo IavaroneSC Gastroenterology and Hepatology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milano, Italy.
Angelo SangiovanniSC Gastroenterology and Hepatology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milano, Italy.
Salvatore Alessio AngileriOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.
Chiara FloridiDepartment of Clinical, Special and Dental Sciences, Division of Interventional Radiology, University Politecnica delle Marche, Ancona, Italy.
Bradford WoodCenter for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA.
Gianpaolo CarrafielloOperative Unit of Radiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy.
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · ITMarche Polytechnic University · ITNational Institutes of Health Clinical Center · US

Funding

Navigation Tools for Image Guided Minimally invasive TherapiesZIACL040011 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
Interventional OncologyZIACL040015 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
6 · The paper itself

Abstract

Tumor ablation is included in several major cancer therapy guidelines. One technical challenge of percutaneous ablation is targeting and verification of complete treatment, which is prone to operator variabilities and human imperfections and are directly related to successful outcomes, risk for residual unablated tumor and local progression. The use of "Prediction Ablation Volume Software" may help the operating Interventional Radiologist to better plan, deliver, and verify before the ablation, via virtual treatment zones fused to target tumor. Fused and superimposed images provide 3-dimensional information from different timepoints, just when that information is most useful. The aim of this study is to evaluate the technical success and efficacy of an ablation treatment flowchart provided by a cone beam computed tomography (CBCT) "Prediction Ablation Volume Software." This is a single-center retrospective study. From April 2021 to January 2022, 29 nonconsecutive evaluable patients with 32 lesions underwent liver ablation with Prediction Ablation Volume Software. Each patient was discussed in a multidisciplinary tumor board and underwent an enhanced computed tomography or magnetic resonance imaging approximately 1 month before the procedure, as well as ∼1 month after. Technical success was defined as treatment of the tumor according to the protocol, covered completely by the Prediction Ablation Volume. Technical efficacy was defined as assessment of complete ablation of the target tumor at imaging follow up (∼1 month). Technical success, technical efficacy, and procedural factors were studied. Technical success was achieved in 30 of 32 liver lesions (94%), measuring 20 mm mean maximum diameter. The antenna was repositioned in 16 of 30 (53%) evaluable target lesions. Residual tumor was detected at 1 month imaging follow up in only 4 of 30 (13%) of the treated lesion. Technical efficacy was of 87% in this retrospective description of our process. The implementation of a CBCT Prediction Ablation Volume Software and flowchart for the treatment of liver malignancies altered the procedure, and demonstrated high technical success and efficacy. Such tools are potentially useful for procedural prediction and verification of ablation.

Indexed as

Catheter AblationLiver NeoplasmsCone-Beam Computed TomographyHumansMicrowavesRetrospective StudiesTreatment Outcome4D CBCTablationcancerintraoperative imagingliver cancerradiology

Identifiers

PMID37608564
PMCPMC10467384
OpenAlexW4386083964

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.