MétaCan
Menu
Back to cohort
Record W1559221631 · doi:10.1186/1471-2466-3-2

Diagnostic pitfalls in fine needle aspiration of solitary pulmonary nodules: two cases with radio-cyto-histological correlation

2003· article· en· W1559221631 on OpenAlexaff
Bahman Torkian, Rani Kanthan, Brent Burbridge

Bibliographic record

VenueBMC Pulmonary Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsMedicineFine-needle aspirationLungRadiologyBiopsyLung biopsySolitary pulmonary nodulePathologyComputed tomography

Abstract

fetched live from OpenAlex

BACKGROUND: Fine needle aspiration is an important tool for diagnosis and preoperative evaluation of solitary nodules of the lung. It provides a definitive diagnosis in most patients at low cost with minimal trauma. However, because of the nature of the study and the presentation of the cells in a more distorted and incomplete tissue structure than a histological slide, false positive results can occur. Prior detailed clinical knowledge about the patient, procedures and methods of radiology in obtaining the aspirate specimen is extremely useful in the accurate interpretation of fine needle cytological specimens. CASE PRESENTATION: We report two cases of solitary pulmonary nodules in two elderly females, which were initially diagnosed as malignant by fine needle aspiration biopsy. Both cases subsequently underwent pulmonary lobectomy in which, one turned out to be a pulmonary hamartoma and the other appeared to be a middle lobe syndrome of the right lung with liver tissue contamination at the time of fine needle aspiration of the lung. CONCLUSIONS: We are now strong believers that much care must be taken in the interpretation of fine needle aspiration of solitary nodules of the lung. Complete study of the entire specimen, including the cell block, is warranted, since what one interprets as malignant, could have different features in another part of the sample. Last but not the least, prior knowledge of the complete clinical history of the patient together with the salient radiological findings would greatly facilitate the cytopathologist to reach an accurate diagnosis.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.298
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueBMC Pulmonary MedicineSame topicMedical Imaging and Pathology StudiesFrench-language works237,207