Thyroid fine needle aspiration biopsy (FNAB) remains indeterminate in 16%-24% of the cases. Molecular testing could improve the diagnostic accuracy of FNAB. This study examined the gene mutation profile of patients with thyroid nodules and analyzed the diagnostic ability of molecular testing for thyroid nodules using a self-developed 18-gene test. Between January 2019 and August 2021, 513 samples (414 FNABs and 99 formalin-fixed paraffin-embedded (FFPE) specimens) underwent molecular testing at Ruijin Hospital. Sensitivity (Sen), specificity (Spe), positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. There were 457 mutations in 428 samples. The rates of BRAF, RAS, TERT promoter, RET/PTC, and NTRK3 fusion mutations were 73.3% (n=335), 9.6% (n=44), 2.8% (n=13), 4.8% (n=22), and 0.4% (n=2), respectively. The diagnostic ability of cytology and molecular testing were evaluated in Bethesda II and V-VI samples. For cytology alone, Sen, Spe, PPV, NPV, and accuracy were 100%, 25.0%, 97.4%, 100%, and 97.4%; these numbers were 87.5%, 50.0%, 98.0%, 12.5%, and 86.2% when considering positive mutation, and 87.5%, 75.0%, 99.0%, 17.6%, and 87.1% when considering positive cytology or and positive mutation. In Bethesda III-IV nodules, when relying solely on the presence of pathogenic mutations for diagnosis, Sen, Spe, PPV, NPV, and AC were 76.2%, 66.7%, 94.1%, 26.8%, and 75.0%, respectively. It might be necessary to analyze the molecular mechanisms of disease development at the genetic level to predict patients with malignant nodules more accurately in different risk strata and develop rational treatment strategies and definite management plans.
Objective To explore the differential diagnostic efficiency of the residual network (ResNet)50, random forest (RF), and DS ensemble models for papillary thyroid carcinoma (PTC) and other pathological types of thyroid nodules. Methods This study retrospectively analyzed 559 patients with thyroid nodules and collected thyroid pathological images and auxiliary examination results (laboratory and ultrasound results) to construct datasets. The pathological image dataset was used to train a ResNet50 model, the text dataset was used to train a random forest (RF) model, and a DS ensemble model was constructed from the results of the two models. The differential diagnostic values of the three models for PTC and other types of thyroid nodules were then compared. Results The DS ensemble model had the highest sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (85.87%, 97.18%, 93.77%, and 0.982, respectively). Conclusions Compared with Resnet50 and the RF models trained only on imaging data or text information, respectively, the DS ensemble model showed better diagnostic value for PTC.
Purpose: To investigate the differential performances in lesions and radio-tracer of 18F-FDG PET/CT between multiple myeloma and unknown osteolytic metastasis. Methods: A retrospective study was performed on 18F-FDG PET/CT imaging of 63 patients with multiple bone destructions without extraosseous primary malignant tumors. By pathological diagnosis, 20 patients were confirmed to have multiple myeloma, and 43 patients have unknown osteolytic metastasis. The whole body was categorized into 8 sites: skull, spine, ribs, pelvis, sternum, clavicle, scapula and limb bone. The length of lesions’cross sections, cortical bone damage, SUVmax and the distribution of radio-tracer were comprehensively compared to differentiate these two diseases in different lesions. Results: The lengths of cross section and SUVmax of the lesions in 5 sites—skull, spine, ribs, pelvis, and limb bone—in the multiple myeloma group were significantly shorter and lower than those of the unknown osteolytic metastasis group(P <0.05). The 18F-FDG was more uniformly distributed in the lesion sites of the skull, spine, ribs, pelvis, scapula, and limb bone in the multiple myeloma group (P <0.05). In the spine and rib lesion sites, the multiple myeloma group was more likely to show noncortical bone damage than the unknown osteolytic metastasis group(P<0.05). Conclusions: We find the differential performances in lesions and 18F-FDG between multiple myeloma and unknown osteolytic metastasis is obvious by comprehensively comparing the length of lesion cross sections, cortical bone damage, SUVmax, the distribution of radio-tracer on18F-FDG PET/CT imaging.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.