Explore the vast range of titles available.

It is unclear whether the site of origin of papillary thyroid microcarcinoma (mPTC) with respect to the thyroid surface has an influence on clinicopathologic parameters. The objectives of the study were to: (i) Accurately measure the mPTC distance from the thyroid surface; (ii) analyze whether this distance correlates with relevant clinicopathologic parameters; and (iii) investigate the impact of the site of origin of the mPTC on risk stratification. Clinicopathologic features and BRAF mutational status were analyzed and correlated with the site of origin of the mPTC in a multicenter cohort of 298 mPTCs from six Italian medical institutions. Tumors arise at a median distance of 3.5 mm below the surface of the thyroid gland. Statistical analysis identified four distinct clusters. Group A, mPTC: size ≥ 5 mm and distance of the edge of the tumor from the thyroid capsule = 0 mm; group B, mPTC: size ≥ 5 mm and distance of the edge of the tumor from the thyroid capsule > 0 mm; group C, mPTC: size < 5 mm and distance of the edge of the tumor from the thyroid capsule = 0 mm; and group D, mPTC: size < 5 mm and distance of the edge of the tumor from the thyroid capsule > 0 mm. Univariate analysis demonstrates significant differences between the groups: Group A shows the most aggressive features, and group D the most indolent ones. By multivariate analysis, group A tumors are characterized by tall cell histotype, BRAF V600E mutation, tumor fibrosis, aggressive growth with invasive features, vascular invasion, lymph node metastases, and intermediate ATA risk. The mPTC clinicopathologic features vary according to the tumor size and distance from the thyroid surface. A four-group model may be useful for risk stratification and to refine the selection of nodules to be targeted for fine needle aspiration.

Aims: Approximately 80-85% of thyroid malignancies are papillary thyroid cancer (PTC). This study evaluated the relationship between thyroid capsule invasion (TCI) in PTC and macroscopic histopathological findings. Methods: A single-center, retrospective study was conducted using the medical records of adult patients who underwent PTC surgery. The patients were classified as TCI (+) or TCI (-) based on the postoperative pathological examination. Tumor localization, calcification, and multifocality were evaluated between the two groups. Results: The study included 236 patients (mean age: 44.3[+ or -]12.0 years, female sex: 76.7%). Preoperative basic characteristics, comorbidities, thyroid function status, nodule calcification, halo border irregularity, and nodule diameter on ultrasonography were similar between the two groups. However, more TCI (+) patients had positive or suspicious fine needle aspiration biopsy findings preoperatively. The duration of surgery was longer in TCI (+) patients (86 minutes vs. 75 minutes, p<0.001), whereas the length of hospital stay was similar. Surgical margin >1 mm was more common in TCI (+) vs. TCI (-) patients (47.3% vs. 81.8%, p<0.001). Postoperative macroscopic pathological reports showed that middle lobe tumor localization was more common in TCI (+) (38.2%) than in TCI (-) (23.2%) patients (p=0.028), whereas tumor localization in the upper pole, lower pole, and isthmus was not different. Multifocal involvement (41.8% vs. 38.1%) was also similar between the two groups. Conclusions: This study showed that fine needle biopsy positivity and nodule localization in the middle thyroid gland were more common in TCI (+) PTC patients as detected postoperatively. The other macroscopic pathological findings were not different. Keywords: Thyroid cancer, thyroid papillary carcinoma, thyroid capsule invasion, lymph node metastasis, thyroglobulin

Objective Thyroid capsule invasion (TCI) predicts early progression in papillary thyroid microcarcinoma (PTMC). This study aimed to develop an integrated model that combines handcrafted peri-tumoral radiomics features with deep learning (DL)-derived intra-tumoral features for accurate early prediction of TCI, to support clinical decision-making. Materials and methods Retrospective data from 964 patients with 964 pathologically confirmed PTMC lesions across three centers were collected. Radiomics features were extracted from multiple peri-tumoral regions, and the optimal peri-tumor region with the best radiomics features was selected using a support vector machine (SVM). The selected radiomics features were then combined with intra-tumoral DL features extracted from the tumors before being fed into four different DL models for training and validation. Performance was validated on the internal ( n  = 177) and external ( n  = 84) test sets. Six radiologists (senior/attending/junior) assessed TCI with/without DL assistance. Results The radiomics features, which achieved the best diagnostic performance with an AUC of 0.795 using SVM, were extracted from the peri-tumor region with 30% expansion from the original tumor. By further combining these radiomics features with intra-tumoral DL features, four different DL models were established to identify TCI in PTMC. Swin-Transformer achieved superior performance (internal AUC: 0.923; external AUC: 0.892). With DL model assistance, the AUCs of six radiologists significantly improved, for example, from 0.720 to 0.796 and from 0.725 to 0.790 for senior radiologists, and similar gains were observed for attending and junior radiologists. Conclusions As an effective clinical assistive tool,  this integrated model can provide TCI identification with high level of accuracy. With its ability to enhance radiologists’ diagnostic performance, it supports early PTMC risk stratification and personalized intervention. Critical relevance statement This retrospective multicenter study establishes an integrated model for identifying TCI in PTMC. The model significantly enhances radiologists’ diagnostic precision across multiple experience levels, supporting early clinical decision-making for optimized intervention strategies. Key Points Accurate prediction of TCI facilitates early assessment of PTMC progression and guides subsequent individualized clinical management. DL significantly improves the predictive performance for TCI. DL effectively assists radiologists in TCI diagnosis. Graphical Abstract

Background Injury to the external branch of the superior laryngeal nerve (EBSLN) during thyroidectomy results in a lowered fundamental frequency of the voice and deteriorated voice performance in producing high-frequency sounds. It remains unclear if the use of intraoperative nerve monitoring (IONM) can improve the clinical outcome of thyroidectomy in terms of preserved individual voice performance. This study was designed to test that hypothesis. Methods A total of 210 consenting female patients planned for total thyroidectomy were randomly assigned to two groups equal in size (n = 105): visual inspection of the EBSLN and RLN vs. this plus additional EBSLN and RLN monitoring. The primary outcome was the identification rate of the EBSLN. The secondary outcomes included: anatomical variability of the EBSLN according to the Cernea classification and changes in postoperative voice performance. Voice assessment included pre- and postoperative videostrobolaryngoscopy and an analysis of maximum phonation time (MPT), voice level (VL), fundamental frequency (Fo), and voice quality rating on the GRBAS scale. Results The following differences were found for operations without vs. with IONM: identification rate of the EBSLN was 34.3 % vs. 83.8 % ( p  < 0.001), whereas a 10 % or higher decrease in phonation parameters was found in 10 % vs. 2 % patients for MPT ( p  = 0.018), 13 % vs. 2 % for VL ( p  = 0.003), and 9 % vs. 1 % for Fo ( p  = 0.03), a change in the GRBAS scale > 4 points in 7 % vs. 1 % ( p  = 0.03), and temporary RLN injury was found in 2 % vs. 1 % ( p  = 0.56), respectively. Conclusions The use of IONM significantly improved the identification rate of the EBSLN during thyroidectomy, as well as reduced the risk of early phonation changes after thyroidectomy.

Microscopic evaluation of tissue sections stained with hematoxylin and eosin is the current gold standard for diagnosing thyroid pathology. Digital pathology is gaining momentum providing the pathologist with additional cues to traditional routes when placing a diagnosis, therefore it is extremely important to develop new image analysis methods that can extract image features with diagnostic potential. In this work, we use histogram and texture analysis to extract features from microscopic images acquired on thin thyroid nodule capsules sections and demonstrate how they enable the differential diagnosis of thyroid nodules. Targeted thyroid nodules are benign (i.e., follicular adenoma) and malignant (i.e., papillary thyroid carcinoma and its sub-type arising within a follicular adenoma). Our results show that the considered image features can enable the quantitative characterization of the collagen capsule surrounding thyroid nodules and provide an accurate classification of the latter’s type using random forest.

Abstract Context Tumor capsule integrity is becoming a relevant issue to predict the biological behavior of human tumors, including thyroid cancer. Objective This work aims to verify whether a whole tumor capsule in the classical variant of papillary thyroid carcinoma (CVPTC) could have as a predictive role of a good outcome as for follicular variant (FVPTC). Methods FVPTC (n = 600) and CVPTC (n = 554) cases were analyzed. We distinguished between encapsulated-FVPTC (E-FVPTC) and encapsulated-CVPTC (E-CVPTC) and, thereafter, invasive (Ei-FVPTC and Ei-CVPTC) and noninvasive (En-FVPTC and En-CVPTC) tumors, according to the invasion or integrity of the tumor capsule, respectively. Cases without a tumor capsule were indicated as invasive-FVPTC (I-FVPTC) and invasive-CVPTC (I-CVPTC). The subgroup of each variant was evaluated for BRAF mutations. Results E-FVPTC was more frequent than E-CVPTC (P < .001). No differences were found between En-FVPTC and En-CVPTC or between Ei-FVPTC and Ei-CVPTC. After 18 years of follow-up, a greater number of not-cured cases were observed in Ei-CVPTC with respect to Ei-FVPTC, but not in En-CVPTC to En-FVPTC. Multivariate clustering analysis showed that En-FVPTC, En-CVPTC, and Ei-FVPTC have similar features but different from I-FVPTC and I-CVPTC and, to a lesser extent, from Ei-CVPTC. A total of 177 of 614 (28.8%) cases were BRAFV600E mutated, and 10 of 614 (1.6%) carried BRAF-rare alterations. A significantly higher rate of En-CVPTC (22/49, 44.9%) than En-FVPTC (15/195, 7.7%) (P < .0001) were BRAFV600E mutated. Conclusion En-CVPTC is less prevalent than En-FVPTC. However, it has good clinical/ pathological behavior comparable to En-FVPTC. This finding confirms the good prognostic role of a whole tumor capsule in CVPTC as well. New nomenclature for En-CVPTC, similar to that introduced for En-FVPTC (ie, noninvasive follicular thyroid neoplasm with papillary-like nuclear features; NIFTP) could be envisaged.

Background The surgical indications for follicular thyroid neoplasms (FTNs) remain controversial due to challenges in the preoperative follicular thyroid carcinoma (FTC) diagnosis. We aimed to explore the sonographic features of the FTN capsule and establish a prediction model for diagnosing FTC without high‐risk features. Methods This prospective cohort study enrolled consecutive adult patients with FTN. Patients presenting with extrathyroidal extension or extracapsular angioinvasion on preoperative imaging were excluded. Intraoperative ultrasound (US)‐guided incisions were conducted in 20 patients during thyroidectomy. Sonographic features of FTN capsules were identified and validated through comparison with US, macroscopic, and microscopic pathology images from the same US‐selected section. Invaded capsules were categorized based on pathological indicators of capsular invasion. The diagnostic performance of the US capsule‐based model and US risk stratification systems (American College of Radiology Thyroid Imaging Reporting and Data System [ACR‐TIRADS] and Ultrasound Follicular Thyroid Imaging Reporting and Data System [F‐TIRADS]) were compared. Results Seventy‐four patients with unifocal lesions and 14 patients with multifocal lesions were enrolled and pathologically diagnosed with follicular thyroid adenoma (n = 67) and FTC (n = 35). As widely invasive FTC was initially excluded, there were 34 minimally invasive subtypes and 1 encapsulated angioinvasive subtype. The areas under the curves for the US capsule‐based model, ACR‐TIRADS, and F‐TIRADS were 0.839 (95% confidence interval [CI], 0.753–0.904), 0.852 (95% CI, 0.768–0.914), and 0.840 (95% CI, 0.755–0.905), respectively. No significant differences were observed in the areas under the curves, sensitivity, or accuracy of the US capsule‐based model, ACR‐TIRADS, and F‐TIRADS. The specificities of the US capsule‐based model and F‐TIRADS were higher than that of the ACR‐TIRADS (88.1% and 80.60%, respectively, vs. 44.8%, p < 0.05). Conclusions Careful US scanning enables clear FTN capsule visualization, providing a straightforward, specific method for diagnosing FTC and guiding completion thyroidectomy by detecting intracapsular angioinvasion in patients with FTC. US successfully identified the capsule of follicular thyroid nodules, with discontinuity in the capsule serving as a specific indicator for follicular thyroid carcinoma (FTC). Intracapsular angioinvasion could also be identified by US, showing promise for guiding completion thyroidectomy by identifying patients with encapsulated angioinvasive FTC. US capsule‐based model exhibited higher specificity than ACR‐TIRADS systems, while maintaining comparable AUC values, despite lower sensitivity for certain nodule locations.

This study examined the contribution of long-term use of Lipiodol capsules, as a supplement to iodised salt to the control of iodine deficiency disorders among women in Xinjiang of China. A total of 1220 women across Kashgar, Aksu, Turpan and Yili Prefectures were surveyed in 2017. Lipiodol capsules were administered twice yearly in Kashgar and once yearly in Aksu and Turpan, but not in Yili. Urinary iodine concentration (UIC), free triiodothyronine (FT3), free thyroxine (FT4), thyroid-stimulating hormone (TSH), thyroglobulin antibody, thyroid peroxidase antibody and thyroid volume values were assessed. All the women in the four areas were in a state of non-iodine deficiency by UIC. The UIC were higher than adequate in Kashgar and Aksu (619·4 v. 278·6 μg/l). Thyroid hormone levels differed significantly in Turpan and Yili (FT3: 4·4 v. 4·6 pmol/l, FT4: 13·8 v. 14·2 pmol/l, TSH: 2·0 v. 2·7 mIU/l), but did not differ significantly in Kashgar, Aksu and Yili. The four areas did not differ significantly with regard to thyroid nodules, autoimmune thyroiditis or goitre. However, the detection rates of subclinical hypothyroidism (16·6 %) and total thyroid dysfunction (25·4 %) were higher among women in Yili. The supplementation with Lipiodol capsules had improved the iodine nutrition status of women in iodine-deficient areas of Xinjiang since 2006. To avoid negative effects of excess iodine, we suggest a gradual discontinuation of Lipiodol capsules in women with special needs based on the existing iodine nutrition level of local women.

This study aimed to evaluate the impact of cinobufacini capsules in patients who underwent total thyroidectomy for differentiated thyroid cancer (DTC). A prospective cohort study was conducted, and a total of 120 DTC patients were selected. The patients were divided into two groups: a control group receiving standard postoperative treatment (n = 60) and a cinobufacini group receiving cinobufacini capsules in addition to standard treatment (n = 60). Various assessments were conducted, including pain evaluation, lymphocyte subset measurement, as well as the quantification of interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), free sulfhydryl (-SH) levels, and lipid hydroperoxides (LOOH) in serum. Both groups experienced reduced pain levels after one month of treatment, with the cinobufacini group demonstrating a more significant reduction. In comparison to the control group, one month of cinobufacini treatment resulted in substantial increases in NK cell activity, percentages of NK cells, activated NK cells, and CD8+ T-cells. It also led to the mitigation of oxidative stress and inflammation response. These findings indicate that cinobufacini may serve as an adjunctive therapy for DTC patients, offering benefits in pain management, immune modulation, and reducing inflammation and oxidative stress after surgery.

Background The ultrasound diagnostic system for extrathyroidal extension (ETE) of papillary thyroid carcinoma (PTC) has not been thoroughly explored. To develop and validate a nomogram model based on ultrasound features to predict ETE of papillary thyroid carcinoma for preoperative assessment. Methods The training set retrospectively included 560 patients from two hospitals with preoperative ultrasound images showing capsule contact and confirmed as unifocal PTC by surgical pathology. The external validation set prospectively included 150 PTC patients with similar features and dynamic ultrasound videos. Univariate and multivariate logistic regression analyses were used to identify independent predictors of ETE in PTC, and an ETE nomogram prediction model was constructed to predict the risk of ETE in capsule-contacting PTC. The predictive efficiency of the model was evaluated using receiver operating characteristic (ROC) curve and calibration curves, and the clinical value of the model was determined through decision curve analysis (DCA). Results Among 710 capsule-contacting unifocal PTC patients, the incidence of ETE was 66.62% (473/710). Independent predictors of ETE were: Capsule bulging (OR = 8.951, 95%CI: 5.192–15.134), capsule contact angle ≥ 90° (OR = 2.331, 95%CI: 1.405–3.868), capsule contact extent ≥ 25% (OR = 5.708, 95%CI: 3.429–9.503), irregular morphology (OR = 1.856, 95%CI: 1.114–3.094), and coarse margins (OR = 4.198, 95%CI: 2.396–7.352). Based on these factors, an ETE nomogram diagnostic prediction model for PTC was established. The model’s ROC curve demonstrated an area under the curve (AUC) of 0.887 (95% CI: 0.857–0.917), with diagnostic sensitivity, specificity, and accuracy of 0.811, 0.799 and 0.807, respectively. The AUC of the external validation set was 0.896 (95% CI: 0.847–0.945), with diagnostic sensitivity, specificity, and accuracy of 0.862, 0.762, and 0.820, respectively. The calibration curve showed good consistency between the predicted and actual probabilities of ETE. DCA showed that the model had good clinical application value. Conclusion The ETE nomogram scoring prediction model based on conventional ultrasound features can provide a relatively convenient and intuitive preoperative quantitative assessment of ETE in PTC, serving as a reference for clinical decision-making.