Evidence map›Paper›PMID 32743728›Full record

ArticleEuropean radiology experimental2020

Multiexponential T2 relaxometry of benign and malignant adipocytic tumours.

Katerina Nikiforaki, Georgios S Ioannidis, Eleni Lagoudaki, Georgios H Manikis, Eelco de Bree, Apostolos Karantanas, Thomas G Maris, Kostas Marias

Open access · goldAbstract read
In one paragraph

Article in European radiology experimental, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

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  2. Improved myelin water imaging using BImaging neuroscience (Cambridge, Mass.) · 2024
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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 at 3 institutions in 1 country.

Katerina NikiforakiComputational Bio-Medicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), Nikolaou Plastira 100, Vassilika Vouton, GR-70013, Heraklion, Crete, Greece. nikiforakik@gmail.com.ORCID 0000-0003-0792-9800
Georgios S IoannidisComputational Bio-Medicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), Nikolaou Plastira 100, Vassilika Vouton, GR-70013, Heraklion, Crete, Greece.
Eleni LagoudakiDepartment of Pathology, University Hospital of Crete, Heraklion, Greece.
Georgios H ManikisComputational Bio-Medicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), Nikolaou Plastira 100, Vassilika Vouton, GR-70013, Heraklion, Crete, Greece.
Eelco de BreeDepartment of Surgical Oncology, University Hospital of Crete, Heraklion, Greece.
Apostolos KarantanasComputational Bio-Medicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), Nikolaou Plastira 100, Vassilika Vouton, GR-70013, Heraklion, Crete, Greece.
Thomas G MarisComputational Bio-Medicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), Nikolaou Plastira 100, Vassilika Vouton, GR-70013, Heraklion, Crete, Greece.
Kostas MariasComputational Bio-Medicine Laboratory (CBML), Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), Nikolaou Plastira 100, Vassilika Vouton, GR-70013, Heraklion, Crete, Greece.
University of Crete · GRUniversity Hospital of Heraklion · GRHellenic Mediterranean University · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe investigated a recently proposed multiexponential (Mexp) fitting method applied to T2 relaxometry magnetic resonance imaging (MRI) data of benign and malignant adipocytic tumours and healthy subcutaneous fat. We studied the T2 distributions of the different tissue types and calculated statistical metrics to differentiate benign and malignant tumours.

methodsTwenty-four patients with primary benign and malignant adipocytic tumours prospectively underwent 1.5-T MRI with a single-slice T2 relaxometry (Carr-Purcell-Meiboom-Gill sequence, 25 echoes) prior to surgical excision and histopathological assessment. The proposed method adaptively chooses a monoexponential or biexponential model on a voxel basis based on the adjusted R

resultsHealthy subcutaneous fat and benign lipoma were better described by biexponential fitting with a monoexponential and biexponential prevalence of 0.0/100% and 0.2/99.8% respectively. Well-differentiated liposarcomas exhibit 17.6% monoexponential and 82.4% biexponential behaviour, while more aggressive liposarcomas show larger degree of monoexponential behaviour. The monoexponential/biexponential prevalence was 47.6/52.4% for myxoid tumours, 52.8/47.2% for poorly differentiated parts of dedifferentiated liposarcomas, and 24.9/75.1% pleomorphic liposarcomas. The percentage monoexponential or biexponential model prevalence per patient was the best classifier distinguishing between malignant and benign adipocytic tumours with a 0.81 sensitivity and a 1.00 specificity.

conclusionsHealthy adipose tissue and benign lipomas showed a pure biexponential behaviour with similar T2 distributions, while decreased adipocytic cell differentiation characterising aggressive neoplasms was associated with an increased rate of monoexponential decay curves, opening a perspective adipocytic tumour classification.

Indexed as

Adipose TissueAdultDiagnosis, DifferentialFemaleHumansLipomaLiposarcomaMagnetic Resonance ImagingMaleNeoplasm GradingNeoplasms, Adipose TissueProspective StudiesLipomaLiposarcomaMagnetic resonance imagingNeoplasms (adipose tissue)Subcutaneous fat

Identifiers

PMID32743728
PMCPMC7396415
OpenAlexW3046738512

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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.