ArticleEuropean radiology2026
The role of microflow patterns combined with greyscale ultrasound in enhancing diagnostic validity and reducing unnecessary biopsy rate of thyroid nodules.
Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Reply to the Letter to the Editor: Microflow imaging for ultrasound risk stratification of thyroid nodules: potential roles and key considerations.European radiology · 2026Article
- Letter to the Editor: Microflow imaging for ultrasound risk stratification of thyroid nodules: potential roles and key considerations.European radiology · 2026Article
Corrections and comments
- Commented on by
Authors and funding
7 authors.
Funding
Abstract
objectiveTo explore the value of microflow patterns based on superb microvascular imaging (SMI) combined with greyscale ultrasound in thyroid nodule diagnosis and biopsy recommendation. MATERIALS AND
methodsAdult patients with thyroid nodules were recruited from May 2023 to February 2024. The greyscale features of nodules were evaluated according to the five ultrasound risk stratification systems (RSSs). The microflow patterns on SMI were used to adjust the category of nodules. The crab claw-like and the root hair-like patterns were malignant signs for upgrading, with the wheel-like and the arborescent patterns for downgrading. The diagnostic performance and biopsy recommendation of microflow patterns combined with greyscale ultrasound were analyzed.
resultsA total of 253 nodules (136 malignant, 117 benign) in 203 patients were included. Chinese Thyroid Imaging Reporting and Data System (C-TIRADS) owned the best diagnostic sensitivity and the largest AUC, with no significant improvement for the former (0.853 vs 0.904, p = 0.096) but an evident increase for the latter (0.834 vs 0.900, p < 0.001) when combined with SMI. American College of Radiology (ACR) TI-RADS had the highest specificity, which was further enhanced by SMI (0.803 vs 0.855, p = 0.041). The unnecessary biopsy rates of RSSs were reduced by 1.27-20.30% according to microflow patterns on SMI. Among these, C-TIRADS had the lowest unnecessary biopsy rate and the largest reduction after the adjustment by SMI (38.04% vs 17.74%).
conclusionThe microflow patterns on SMI could enhance the diagnostic validity of greyscale ultrasound for thyroid nodules. Besides, the unnecessary biopsy rate could also be decreased by combining with SMI. KEY POINTS: Question The utility of combining superb microvascular imaging (SMI) with greyscale ultrasound for the diagnosis of thyroid nodules and the recommendation of biopsies remains unclear. Findings Risk stratification systems adjusted by microflow patterns on SMI outperformed the original systems in distinguishing thyroid carcinoma and recommending biopsies. Clinical relevance Microflow patterns combined with greyscale ultrasound can enhance the diagnostic validity and reduce the unnecessary biopsy rate for thyroid nodules.
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.