Evidence map›Paper›PMID 36420224›Full record

ArticleCureus2022

The Role of Diffusion-Weighted Magnetic Resonance Imaging in Differentiating Benign From Malignant Thyroid Nodules: A Descriptive Observational Study.

Vijaykumar Monisha, N Rache Gowda, Sakalecha Anil Kumar

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
0.9field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

3 authors at 1 institution in 1 country.

Vijaykumar MonishaRadiodiagnosis, Sri Devaraj Urs Medical College, Kolar, IND.
N Rache GowdaRadiodiagnosis, MVJ Medical College and Research Hospital, Bengaluru, IND.
Sakalecha Anil KumarRadiodiagnosis, Sri Devaraj Urs Medical College, Kolar, IND.
MVJ Medical College and Research Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Currently, no effective and reproducible imaging method can quantitatively differentiate between benign and malignant thyroid nodules. This study aimed to assess the role of diffusion-weighted imaging (DWI) in differentiating benign from malignant thyroid nodules. Methodology We conducted an observational study in the Department of Radiodiagnosis at R. L. Jalappa Hospital and Research Center, Kolar, India. The study was conducted from January 2020 to June 2021, among 43 patients with thyroid swelling or nodules. We recorded patient baseline data, pertinent clinical history, and relevant laboratory investigations. Patients underwent diffusion-weighted MRI of the neck. We used receiver operator curve analysis to determine the utility of the apparent diffusion coefficient (ADC) of the thyroid nodule in predicting the histopathological diagnosis. Data were analyzed using coGuide (V1.0.3, BDSS Corp., India). Results A total of 43 patients were enrolled in the study (35 women, 81.4%; 8 men, 18.6%). The mean (SD) age was 49.8 (14.3) years. Nodular hyperplasia was the most common histopathologic diagnosis of the nodule (25.5%), followed by lymphocytic thyroiditis (16.2%). The MRI and histopathological findings matched: both found 35 (81.4%) nodules as benign and 8 (18.6%) as malignant. The ADC value of thyroid nodules had excellent predictive validity in predicting malignancy, as indicated by the area under the curve of 0.925 (95% confidence interval [CI] 0.804-1.000;

Indexed as

apparent diffusion coefficient (adc)magnetic resonance imagingmalignancyneoplasmsthyroid cancer

Identifiers

PMID36420224
PMCPMC9678236
OpenAlexW4306947010

What OpenQuestion holds

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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.