Evidence map›Paper›PMID 35212785›Full record

ReviewNeuroradiology2022

New insights into the evaluation of peripheral nerves lesions: a survival guide for beginners.

Teodoro Martín-Noguerol, Rafael Barousse, Antonio Luna, Mariano Socolovsky, Juan M Górriz, Manuel Gómez-Río

Erratum issuedAbstract readReview
PubMed Publisher
In one paragraph

Review in Neuroradiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Teodoro Martín-NoguerolMRI unit, Radiology Department, HT Medica, Carmelo Torres 2, 23007, Jaén, Spain. t.martin.f@htime.org.ORCID http://orcid.org/0000-0001-7200-5028
Rafael BaroussePeripheral Nerve and Plexus Department, Centro Rossi, Sánchez de Loria 117, C1173 AAC, Buenos Aires, Argentina.ORCID https://orcid.org/0000-0001-5940-7540
Antonio LunaMRI unit, Radiology Department, HT Medica, Carmelo Torres 2, 23007, Jaén, Spain.ORCID https://orcid.org/0000-0001-9358-3396
Mariano SocolovskyNerve & Plexus Surgery Program, Division of Neurosurgery, Hospital de Clínicas, University of Buenos Aires School of Medicine, Paraguay 2155, C1121 ABG, Buenos Aires, Argentina.ORCID https://orcid.org/0000-0002-0667-3463
Juan M GórrizDepartment of Signal Theory, Networking and Communications, University of Granada, Avenida de Fuente Nueva, s/n, 18071, Granada, Spain.ORCID https://orcid.org/0000-0001-7069-1714
Manuel Gómez-RíoDepartment of Nuclear Medicine, Virgen de las Nieves University Hospital, Av. de las Fuerzas Armadas, 2, 18014, Granada, Spain.ORCID https://orcid.org/0000-0002-1132-3716

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo perform a review of the physical basis of DTI and DCE-MRI applied to Peripheral Nerves (PNs) evaluation with the aim of providing readers the main concepts and tools to acquire these types of sequences for PNs assessment. The potential added value of these advanced techniques for pre-and post-surgical PN assessment is also reviewed in diverse clinical scenarios. Finally, a brief introduction to the promising applications of Artificial Intelligence (AI) for PNs evaluation is presented.

methodsWe review the existing literature and analyze the latest evidence regarding DTI, DCE-MRI and AI for PNs assessment. This review is focused on a practical approach to these advanced sequences providing tips and tricks for implementing them into real clinical practice focused on imaging postprocessing and their current clinical applicability. A summary of the potential applications of AI algorithms for PNs assessment is also included.

resultsDTI, successfully used in central nervous system, can also be applied for PNs assessment. DCE-MRI can help evaluate PN's vascularization and integrity of Blood Nerve Barrier beyond the conventional gadolinium-enhanced MRI sequences approach. Both approaches have been tested for PN assessment including pre- and post-surgical evaluation of PNs and tumoral conditions. AI algorithms may help radiologists for PN detection, segmentation and characterization with promising initial results.

conclusionDTI, DCE-MRI are feasible tools for the assessment of PN lesions. This manuscript emphasizes the technical adjustments necessary to acquire and post-process these images. AI algorithms can also be considered as an alternative and promising choice for PN evaluation with promising results.

Indexed as

Artificial IntelligenceMagnetic Resonance ImagingAlgorithmsHumansPeripheral NervesArtificial intelligenceDCE-MRIDTIMRIPeripheral nerve

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.