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Record W4292682950 · doi:10.21037/tcr-22-1919

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

2022· letter· en· W4292682950 on OpenAlexaff
Guodong Fu, Ian Witterick

Bibliographic record

VenueTranslational Cancer Research · 2022
Typeletter
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsUniversity of TorontoLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsFine needle aspiration cytologyMedicineFine-needle aspirationIndeterminateThyroid nodulesCytologyGrayscaleThyroidRadiologyBiopsyPathologyInternal medicineMathematics

Abstract

fetched live from OpenAlex

Determinate cancer screening enhances accurate cancer diagnosis and timely decision-making for treatment. Neck ultrasonography (US) has become the first routine evaluation of all patients with a known or suspected thyroid nodule to stratify its risk of malignancy. The morphological features of thyroid nodules observed during the US are reported via scoring classification systems for malignancy risk stratification based on the Thyroid Imaging Reporting And Data System (TIRADS) or 2015 American Thyroid Association (ATA) guideline (1,2). Different versions of TIRADS have been developed in different countries in line with their national conditions and medical status, such as Chinese TIRADS (3), European TIRADS (4) and Korean TIRADS (5). The sonographic features/patterns of thyroid ultrasound are widely used to identify nodules for further biopsy or followup ultrasound. Nodules with the more suspicious features of US are recommended to undergo thyroid biopsy. The Chinese TIRADS guideline recommends ultrasound-guided fine-needle aspiration (FNA) biopsy for TIRADS 4A nodules >15 mm and TIRADS 4B or 4C or 5 nodules >10 mm, but not for TIRADS 2 and 3 nodules (3). Needle biopsy was first introduced for diagnosis of thyroid nodules using an 18-gauge-needle puncture and aspiration by Martin and Ellis in 1930 and then fine needle (22-27-gauge) in the 1960s (6,7). This technique came into widespread use in North America in the 1980s and has become a gold standard to distinguish malignancy from benign thyroid nodules (7-9). Advances in diagnostics, including increasing use of computed tomography and magnetic resonance imaging, allow the detection and biopsy of thyroid nodules as small as 2 mm (10). Thyroid FNA cytological findings are classified across six diagnostic categories by the Bethesda System for Reporting Thyroid Cytopathology (BSRTC) with risk of malignancy in each category, including (I) nondiagnostic or unsatisfactory (ND), (II) benign, (III) atypia of undetermined significance (AUS)/follicular lesion of undetermined significance (FLUS), (IV) follicular neoplasm/suspicious for a follicular neoplasm (FN/SFN), (V) suspicious for malignancy (SM), and (VI) malignant (11). A nodule may be considered for resection if its cytology is malignant or SM FNA cytology is the most accurate and cost-effective method for evaluating thyroid nodules. However, discrepancies exist between the US and FNA results in real world clinical practice. Up to 30% of the FNA biopsies are reported as indeterminate cytology: ND, AUS/FLUS, FN/SFN, or SM. According to the 2015 ATA guidelines, a repeat ultrasound-guided FNA is recommended to re-do the cytology examination or perform molecular testing when a nodule was predicted highly SM by US but

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.357
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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