Evidence map›Paper›PMID 39918041›Full record

ArticleMolecular imaging and radionuclide therapy2025

Correlation of 3T Diffusion-weighted MRI and

Ahmet Tanyeri, Rıdvan Akbulut, Emir Hüseyin Nevai, Yakup Yürekli

Abstract read
In one paragraph

Article in Molecular imaging and radionuclide therapy, 2025. 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. Article
  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

4 authors.

Ahmet TanyeriAydın Adnan Menderes University, Faculty of Medicine, Department of Radiology, Aydın, Türkiye.ORCID 0000-0002-1097-1172
Rıdvan AkbulutAydın Adnan Menderes University, Faculty of Medicine, Department of Radiology, Aydın, Türkiye.ORCID 0009-0004-8091-6322
Emir Hüseyin NevaiAydın Adnan Menderes University, Faculty of Medicine, Department of Radiology, Aydın, Türkiye.ORCID 0000-0002-0907-0182
Yakup YürekliAydın Adnan Menderes University Faculty of Medicine, Department of Nuclear Medicine, Aydın, Türkiye.ORCID 0000-0001-5823-0659

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) are widely used in the diagnosis and follow-up of liver metastases. Both modalities provide anatomical and functional information and have advantages and disadvantages. The objective of this study was to investigate the correlation between apparent diffusion coefficient (ADC) and standardized uptake value (SUV) values in metastatic liver lesions. Methods: Abdominal magnetic resonance (MR) scans performed between April 2021 and 2024 using the 3T MR scanner were retrospectively evaluated. Thirty-three patients with liver metastases, less than one month between magnetic resonance imaging (MRI) and PET/CT, no treatment during this period, and lesions larger than 1 cm were included in the study. In each MRI scan, an index lesion was selected for ADC measurement. The radiologist and nuclear medicine specialist measured the same index lesion without the patient being informed of the results. Results: The mean age of the 33 patients was 59±12 years, with 17 (51%) men and 16 (49%) women. The mean size of the index lesions was 27±9 mm. In MRI, mean ADC Conclusion: There was no correlation between ADC and SUV values in liver metastases. Prospective studies with a large patient group are needed.

Indexed as

apparent diffusion coefficientdiffusion magnetic resonance imagingLiver neoplasmspositron emission tomography computed tomographystandardized uptake value

Identifiers

PMID39918041
PMCPMC11827527

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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.