Evidence map›Paper›PMID 39355054›Full record

ReviewFrontiers in nuclear medicine2023

Radiomics insight into the neurodegenerative "

Gayane Aghakhanyan, Gianfranco Di Salle, Salvatore Claudio Fanni, Roberto Francischello, Dania Cioni, Mirco Cosottini, Duccio Volterrani, Emanuele Neri

Abstract readReview
In one paragraph

Review in Frontiers in nuclear medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. 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

8 authors.

Gayane AghakhanyanAcademic Radiology, Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, Pisa, Italy.
Gianfranco Di SalleAcademic Radiology, Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, Pisa, Italy.
Salvatore Claudio FanniAcademic Radiology, Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, Pisa, Italy.
Roberto FrancischelloAcademic Radiology, Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, Pisa, Italy.
Dania CioniAcademic Radiology, Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, Pisa, Italy.
Mirco CosottiniNeuroradiology Unit, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.
Duccio VolterraniRegional Center of Nuclear Medicine, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.
Emanuele NeriAcademic Radiology, Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, Pisa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The application of radiomics for non-oncologic diseases is currently emerging. Despite its relative infancy state, the evidence highlights the potential of radiomics approaches to serve as neuroimaging biomarkers in the field of the neurodegenerative brain. This systematic review presents the last progress and potential application of radiomics in the field of neurodegenerative nuclear imaging applied to positron-emission tomography (PET) and single-photon emission computed tomography (SPECT) by focusing mainly on the two most common neurodegenerative disorders, Alzheimer's (AD) and Parkinson's disease (PD). A comprehensive review of the current literature was performed using the PubMed and Web of Science databases up to November 2022. The final collection of eighteen relevant publications was grouped as AD-related and PD-related. The main efforts in the field of AD dealt with radiomics-based early diagnosis of preclinical AD and the prediction of MCI to AD conversion, meanwhile, in the setting of PD, the radiomics techniques have been used in the attempt to improve the assessment of PD diagnosis, the differential diagnosis between PD and other parkinsonism, severity assessment, and outcome prediction. Although limited evidence with relatively small cohort studies, it seems that radiomics-based analysis using nuclear medicine tools, mainly [18F]Fluorodeoxyglucose (FDG) and

Indexed as

Alzheimer’s disease (AD)neurodegenerative diseasenuclear medicineParkinson’s disease (PD)radiomics

Identifiers

PMID39355054
PMCPMC11440921

What Socratic 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 Socratic graph.