Evidence map›Paper›PMID 40542314›Full record

ReviewEndocrine2025

The management of cytologically indeterminate thyroid nodules in clinical practice: A contemporary perspective with focus on molecular imaging.

Petra Petranović Ovčariček, Alfredo Campennì, Massimo Bongiovanni, Luca Giovanella

Abstract readReview
PubMed Publisher
In one paragraph

Review in Endocrine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  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

4 authors.

Petra Petranović OvčaričekDepartment of Oncology and Nuclear Medicine, University Hospital Center Sestre Milosrdnice, Zagreb, Croatia.
Alfredo CampennìUnit of Nuclear Medicine, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy. acampenni@unime.it.
Massimo BongiovanniUnilabs, Cytopathology Division, Lausanne, Switzerland.
Luca GiovanellaDepartment of Nuclear Medicine, Gruppo Ospedaliero Moncucco, Clinica Moncucco, Lugano, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid nodules are commonly encountered in clinical practice and can be detected by palpation and ultrasound in about 5 and 70% of cases, respectively. Excluding thyroid cancer is the most relevant task when assessing a thyroid nodule, as only 5-10% of evaluated thyroid nodules are malignant. Fine-needle aspiration cytology (FNAC) is pivotal in detecting or excluding malignancy; however, cytologically indeterminate findings occur in up to 30% of cases and carry a malignancy risk ranging from 10-40%. Diagnostic surgery was traditionally performed in such cases resulting, however, in futile procedures in approximately 75% of cases. Accordingly, more accurate diagnostic strategies are warranted. Various methods are currently available to support clinical decision-making, including core needle biopsy (CNB) and multiple molecular testing. In addition, molecular imaging methods have emerged as a valuable tool for stratifying cytologically indeterminate nodules and guiding clinicians in making informed clinical decisions. We aim to describe the basis of thyroid molecular imaging, its clinical use in patients with indeterminate thyroid nodules, and its potential role in the context of different available methods.

Indexed as

Molecular ImagingThyroid GlandThyroid NoduleBiopsy, Fine-NeedleHumansThyroid Neoplasms[18F]FDG-PET/CT[99mTc]-MIBI scintigraphyIndeterminate cytologyMolecular imagingThyroid nodules

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.