Terminology and nomenclature schemes for reporting thyroid cytopathology: An overview

Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules

BACKGROUND

The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity.

METHODS

A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively. Univariate and multivariate logistic regression were used to obtain β coefficients, construct predictive models and nomogram incorporating MRI morphological features in the training cohort, and validated in the validation cohort. The discrimination, calibration, and decision curve analysis of the nomogram were performed. The diagnosis efficacy, area under the curve (AUC) and net reclassification index (NRI) were calculated and compared with TI-RADS.

RESULTS

572 thyroid nodules were included (training cohort: n = 397, validation cohort: n = 175). Age, low signal intensity on T2WI, restricted diffusion, reversed halo sign in delay phase, cystic degeneration and wash-out pattern were independent predictors of malignancy. The nomogram demonstrated good discrimination and calibration both in the training cohort (AUC = 0.972) and the validation cohort (AUC = 0.968). The accuracy, sensitivity, specificity, PPV, NPV and AUC of MRI-based prediction were 94.4%, 96.0%, 93.4%, 89.9%, 96.5% and 0.947, respectively. The MRI-based prediction model exhibited enhanced accuracy (NRI>0) in comparison to TI-RADSs.

CONCLUSIONS

The prediction model for diagnosis of benign and malignant thyroid nodules demonstrated a more notable diagnostic efficacy than TI-RADS. Compared with the TI-RADSs, predictive model had better specificity along with a high sensitivity and can reduce overdiagnosis and unnecessary biopsies.

A Comparative Study of ARHI Imprinted Gene Detection and Fine-Needle Aspiration Cytology in the Differential Diagnosis of Benign and Malignant Thyroid Nodules

Aims: To compare fine-needle aspiration cytology (FNAC) with imprinted gene detection in the differential diagnosis of benign and malignant thyroid nodules.

Methods: A total of 34 patients (35 cases of thyroid nodules) were examined using fine-needle puncture biopsy under ultrasound guidance, and the biopsy tissues were examined by cytologic examination and imprinted gene detection. Combined with postoperative pathology and follow-up results, the diagnostic value and consistency of the two methods were analyzed and compared.

Results: The detection of benign and malignant thyroid nodules by ARHI imprinted gene had a high consistency with FNAC, and ARHI imprinted gene detection had a higher detection rate, sensitivity, and accuracy.

Conclusions: Imprinted gene detection has high accuracy and sensitivity in the differential diagnosis of benign and malignant thyroid nodules. It provides a scientific reference for clinical treatment and should be incorporated into diagnostic protocols for thyroid tumor.

Clinical impact of molecular techniques for the presurgical diagnosis of differentiated thyroid cancer diagnosis

The gold standard for the presurgical diagnosis of thyroid cancer is fine needle aspiration cytology. In about 30% of cases a final diagnosis is not obtained and surgical treatment is required for diagnostic/therapeutic purposes. To avoid unnecessary thyroidectomies, methods based on molecular markers analysis have been explored over the last 10 years. Areas covered: The present review introduces the limits of the cytological diagnosis of thyroid nodules and describes the molecular techniques for the presurgical diagnosis of these nodules focusing on the use of the Thyroseq-V2 (Rule in) and Afirma (Rule out) tests. Expert commentary: These two types of tests have been clinically applied and validated; however they are still confined to specialized laboratories, either academic or private, and not yet routinely used. The evidence of a positive cost-benefit analysis should encourage to set up molecular pathology laboratories to apply new molecular testing(s). In the meantime, clinical judgment, which must take into consideration several parameters including the age of the patient, the size and number of the nodule(s), the ultrasound pattern and the risk level for malignancy, should guide the decision to operate or to follow up the evolution of the nodule.

A combination of immunohistochemistry and molecular approaches improves highly sensitive detection of BRAF mutations in papillary thyroid cancer

The optimal method for BRAF mutation detection remains to be determined despite advances in molecular detection techniques. The aim of this study was to compare, against classical Sanger sequencing, the diagnostic performance of two of the most recently developed, highly sensitive methods: BRAF V600E immunohistochemistry (IHC) and peptide nucleic-acid (PNA)-clamp qPCR. BRAF exon 15 mutations were searched in formalin-fixed paraffin-embedded tissues from 86 papillary thyroid carcinoma using the three methods. The limits of detection of Sanger sequencing in borderline or discordant cases were quantified by next generation sequencing. BRAF mutations were found in 74.4 % of cases by PNA, in 71 % of cases by IHC, and in 64 % of cases by Sanger sequencing. Complete concordance for the three methods was observed in 80 % of samples. Better concordance was observed with the combination of two methods, particularly PNA and IHC (59/64) (92 %), while the combination of PNA and Sanger was concordant in 55 cases (86 %). Sensitivity of the three methods was 99 % for PNA, 94.2 % for IHC, and 89.5 % for Sanger. Our data show that IHC could be used as a cost-effective, first-line method for BRAF V600E detection in daily practice, followed by PNA analysis in negative or uninterpretable cases, as the most efficient method. PNA-clamp quantitative PCR is highly sensitive and complementary to IHC as it also recognizes other mutations besides V600E and it is suitable for diagnostic purposes.