Evidence map›Paper›PMID 34319774›Full record

ArticleDento maxillo facial radiology2022

A comparison among gamma distribution, intravoxel incoherent motion, and mono-exponential models with turbo spin-echo diffusion-weighted MR imaging in the differential diagnosis of orofacial lesions.

Wannakamon Panyarak, Toru Chikui, Kenji Tokumori, Yasuo Yamashita, Takeshi Kamitani, Osamu Togao, Shintaro Kawano, Kazunori Yoshiura

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Dento maxillo facial radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Wannakamon PanyarakGraduate School of Dental Science, Kyushu University, Fukuoka, Japan.ORCID 0000-0003-3557-586X
Toru ChikuiDepartment of Oral and Maxillofacial Radiology, Faculty of Dental Science, Kyushu University, Fukuoka, Japan.
Kenji TokumoriDepartment of Clinical Radiology, Faculty of Medical Technology, Teikyo University, Fukuoka, Japan.
Yasuo YamashitaDepartment of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
Takeshi KamitaniDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Osamu TogaoDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Shintaro KawanoDivision of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka, Japan.
Kazunori YoshiuraDepartment of Oral and Maxillofacial Radiology, Faculty of Dental Science, Kyushu University, Fukuoka, Japan.
Kyushu University · JPKyushu University Hospital · JPTeikyo University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo compare the gamma distribution (GD), intravoxel incoherent motion (IVIM), and monoexponential (ME) models in terms of their goodness-of-fit, correlations among the parameters, and the effectiveness in the differential diagnosis of various orofacial lesions.

methodsA total of 85 patients underwent turbo spin-echo diffusion-weighted imaging with six b-values. The goodness-of-fit of three models was assessed using Akaike Information Criterion. We analysed the correlations and compared the effectiveness in the differential diagnosis among the parameters of GD model (κ, shape parameter; θ, scale parameter; fractions of diffusion: ƒ

resultsThe GD and IVIM models showed a better goodness-of-fit than the ME model (

conclusionsThe strong correlations were found between the GD- and IVIM-derived parameters. Furthermore, the GD model's parameters were useful for characterising the pathological structure in orofacial lesions.

Indexed as

Diffusion Magnetic Resonance ImagingMagnetic Resonance ImagingDiagnosis, DifferentialHumansMotionReproducibility of ResultsSensitivity and SpecificityDifferential diagnosisDiffusion weighted imagingMagnetic resonance imagingOrofacial lesionsStatistical models

Identifiers

PMID34319774
PMCPMC8693325
OpenAlexW3184825883

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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.