ArticleTranslational cancer research2022
Clinical utility of histogram analysis of grayscale sonograms in assessing sonographic suspicious malignant thyroid nodules.
Article in Translational cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Ultrasound histogram metrics for subscapularis tendon: Toward standardized musculoskeletal image interpretation.Medicine · 2026Article
- Quantitative Spatial Analysis on Radiographic Features of Rotator Cuff Calcifications: An Exploratory Study.Biomedicines · 2025Article
- Management of thyroid nodules with indeterminate fine-needle aspiration cytology: histogram analysis of greyscale sonograms and molecular assay of residual tissue from fine-needle aspiration biopsies.Translational cancer research · 2022Article
- Wall characteristics of atherosclerotic middle cerebral arteries in patients with single or multiple infarcts: A high-resolution MRI Study.Frontiers in neurology · 2022Article
Corrections and comments
- Commented on by
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: When sonographic suspicious malignant thyroid nodules initially proven to be inconsistent by aspiration, repeat fine-needle aspiration cytology (FNAC) is commonly recommended. Although FNAC is simple and reliable, it is also an invasive operation with inevitable false negative results. To determine which sonographic features and histogram parameters based on gray-scale ultrasonic images need repeat aspiration. Methods: All of the nodules were suspicious for malignancy by preoperative ultrasound (US), and their initial FNAC findings indicated Bethesda category II, or III. Histogram analyses were performed for gray-scale ultrasonic images. Mean, variance, skewness, kurtosis, percentiles (1st, 10th, 50th, 90th, 99th), and sonographic features were compared between pathological benign nodules and malignant ones. Thereafter, receiver operator characteristic (ROC) curves were analyzed for the valuable indicators. Results: One hundred and nineteen consecutive patients with 123 histopathologically diagnosed focal thyroid nodules were included in the cohort. The factors associated with malignancy were taller-than-wide shape [odds ratio (OR) =15.165; 95% confidence interval (CI): 3.157-72.854], irregular margins (OR =11.492; 95% CI: 1.747-75.573), microcalcifications (OR =5.107; 95% CI: 1.455-17.927) and skewness (OR =25.800; 95% CI: 1.034-76.422). The skewness of malignant thyroid nodules is higher than that of benign thyroid nodules and has an area under the curve (AUC) of 0.776 in the diagnosis. Conclusions: For thyroid nodules suspicious on US but not on cytology, skewness, together with taller-than-wide shape, irregular margins and microcalcifications might be a promising marker for clinicians to perform repetitive FNACs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.