Evidence map›Paper›PMID 38400229›Full record

ArticleSensors (Basel, Switzerland)2024

Three-Dimensional Multi-Modality Registration for Orthopaedics and Cardiovascular Settings: State-of-the-Art and Clinical Applications.

Simone Garzia, Katia Capellini, Emanuele Gasparotti, Domenico Pizzuto, Giuseppe Spinelli, Sergio Berti, Vincenzo Positano, Simona Celi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  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.

Simone GarziaBioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, 54100 Massa, Italy.ORCID 0009-0008-2874-0218
Katia CapelliniBioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, 54100 Massa, Italy.ORCID 0000-0002-4938-9569
Emanuele GasparottiBioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, 54100 Massa, Italy.ORCID 0000-0003-0122-5175
Domenico PizzutoDepartment of Information Engineering, University of Pisa, 56122 Pisa, Italy.
Giuseppe SpinelliMaxillofacial Surgery Department, Azienda Ospedaliero-Universitaria Careggi, 50134 Firenze, Italy.
Sergio BertiDiagnostic and Interventional Cardiology Department, Fondazione Toscana G. Monasterio, 54100 Massa, Italy.ORCID 0000-0002-5244-0556
Vincenzo PositanoBioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, 54100 Massa, Italy.ORCID 0000-0001-6955-9572
Simona CeliBioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, 54100 Massa, Italy.ORCID 0000-0002-7832-0122

Funding

Regione Toscana CUP B14I20001160005
6 · The paper itself

Abstract

The multimodal and multidomain registration of medical images have gained increasing recognition in clinical practice as a powerful tool for fusing and leveraging useful information from different imaging techniques and in different medical fields such as cardiology and orthopedics. Image registration could be a challenging process, and it strongly depends on the correct tuning of registration parameters. In this paper, the robustness and accuracy of a landmarks-based approach have been presented for five cardiac multimodal image datasets. The study is based on 3D Slicer software and it is focused on the registration of a computed tomography (CT) and 3D ultrasound time-series of post-operative mitral valve repair. The accuracy of the method, as a function of the number of landmarks used, was performed by analysing root mean square error (RMSE) and fiducial registration error (FRE) metrics. The validation of the number of landmarks resulted in an optimal number of 10 landmarks. The mean RMSE and FRE values were 5.26 ± 3.17 and 2.98 ± 1.68 mm, respectively, showing comparable performances with respect to the literature. The developed registration process was also tested on a CT orthopaedic dataset to assess the possibility of reconstructing the damaged jaw portion for a pre-operative planning setting. Overall, the proposed work shows how 3D Slicer and registration by landmarks can provide a useful environment for multimodal/unimodal registration.

Indexed as

OrthopedicsAlgorithmsHeartImaging, Three-DimensionalLungSoftwareTomography, X-Ray Computed3D Slicercardiovascularlandmarkmultimodal registrationorthopaedic

Identifiers

PMID38400229
PMCPMC10891817

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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.