160 related articles for article (PubMed ID: 38395783)
1. Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules.
Zheng T; Wang L; Wang H; Tang L; Xie X; Fu Q; Wu PY; Song B
BMC Cancer; 2024 Feb; 24(1):256. PubMed ID: 38395783
[TBL] [Abstract][Full Text] [Related]
2. Development and Validation of a Nomogram Based on Multimodality Ultrasonography Images for Differentiating Malignant from Benign American College of Radiology Thyroid Imaging, Reporting and Data System (TI-RADS) 3-5 Thyroid Nodules.
Pang L; Yang X; Zhang P; Ding L; Yuan J; Liu H; Liu J; Gong X; Yu M; Luo W
Ultrasound Med Biol; 2024 Apr; 50(4):557-563. PubMed ID: 38262884
[TBL] [Abstract][Full Text] [Related]
3. Dual-modal radiomics nomogram based on contrast-enhanced ultrasound to improve differential diagnostic accuracy and reduce unnecessary biopsy rate in ACR TI-RADS 4-5 thyroid nodules.
Ren JY; Lv WZ; Wang L; Zhang W; Ma YY; Huang YZ; Peng YX; Lin JJ; Cui XW
Cancer Imaging; 2024 Jan; 24(1):17. PubMed ID: 38263209
[TBL] [Abstract][Full Text] [Related]
4. Discriminating Malignancy in Thyroid Nodules: The Nomogram Versus the Kwak and ACR TI-RADS.
Xiao J; Xiao Q; Cong W; Li T; Ding S; Shao C; Zhang Y; Liu J; Wu M; Jia H
Otolaryngol Head Neck Surg; 2020 Dec; 163(6):1156-1165. PubMed ID: 32689870
[TBL] [Abstract][Full Text] [Related]
5. A new ultrasound nomogram for differentiating benign and malignant thyroid nodules.
Chen L; Zhang J; Meng L; Lai Y; Huang W
Clin Endocrinol (Oxf); 2019 Feb; 90(2):351-359. PubMed ID: 30390403
[TBL] [Abstract][Full Text] [Related]
6. Diagnostic performance of thyroid imaging reporting and data system (TI-RADS) alone and in combination with contrast-enhanced ultrasonography for the characterization of thyroid nodules.
Zhao H; Liu X; Lei B; Cheng P; Li J; Wu Y; Ma Z; Wei F; Su H
Clin Hemorheol Microcirc; 2019; 72(1):95-106. PubMed ID: 30320563
[TBL] [Abstract][Full Text] [Related]
7. Predicting Malignancy in Thyroid Nodules: Radiomics Score Versus 2017 American College of Radiology Thyroid Imaging, Reporting and Data System.
Liang J; Huang X; Hu H; Liu Y; Zhou Q; Cao Q; Wang W; Liu B; Zheng Y; Li X; Xie X; Lu M; Peng S; Liu L; Xiao H
Thyroid; 2018 Aug; 28(8):1024-1033. PubMed ID: 29897018
[TBL] [Abstract][Full Text] [Related]
8. The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules.
Zhang X; Jia C; Sun M; Ma Z
Sci Rep; 2024 Apr; 14(1):7878. PubMed ID: 38570589
[TBL] [Abstract][Full Text] [Related]
9. Clinical diagnostic value of contrast-enhanced ultrasound and TI-RADS classification for benign and malignant thyroid tumors: One comparative cohort study.
Xu Y; Qi X; Zhao X; Ren W; Ding W
Medicine (Baltimore); 2019 Jan; 98(4):e14051. PubMed ID: 30681562
[TBL] [Abstract][Full Text] [Related]
10. [Value of radiomics models based on MRI diffusion weighted imaging and apparent diffusion coefficient in differentiating benign and malignant thyroid nodules].
Xu HJ; Yang Q; He P; Luo HH; Deng WM; Liu Z; Luo DH
Zhonghua Yi Xue Za Zhi; 2023 Nov; 103(41):3279-3286. PubMed ID: 37926572
[No Abstract] [Full Text] [Related]
11. The use of modified TI-RADS using contrast-enhanced ultrasound features for classification purposes in the differential diagnosis of benign and malignant thyroid nodules: A prospective and multi-center study.
Zhou P; Chen F; Zhou P; Xu L; Wang L; Wang Z; Yu Y; Liu X; Wang B; Yan W; Zhou H; Tao Y; Liu W
Front Endocrinol (Lausanne); 2023; 14():1080908. PubMed ID: 36817602
[TBL] [Abstract][Full Text] [Related]
12. Diagnostic efficacy of multiple MRI parameters in differentiating benign vs. malignant thyroid nodules.
Wang H; Wei R; Liu W; Chen Y; Song B
BMC Med Imaging; 2018 Dec; 18(1):50. PubMed ID: 30509198
[TBL] [Abstract][Full Text] [Related]
13. Development and validation of an ultrasound-based nomogram to improve the diagnostic accuracy for malignant thyroid nodules.
Guo BL; Ouyang FS; Ouyang LZ; Liu ZW; Lin SJ; Meng W; Huang XY; Chen HX; Yang SM; Hu QG
Eur Radiol; 2019 Mar; 29(3):1518-1526. PubMed ID: 30209592
[TBL] [Abstract][Full Text] [Related]
14. Predicting malignancy in thyroid nodules based on conventional ultrasound and elastography: the value of predictive models in a multi-center study.
Zhang Y; Huang QY; Wu CJ; Chen Q; Xia CJ; Liu BJ; Liu YY; Zhang YF; Xu HX
Endocrine; 2023 Apr; 80(1):111-123. PubMed ID: 36495391
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of Radiomics Models Based on Computed Tomography for Distinguishing Between Benign and Malignant Thyroid Nodules.
Kong D; Zhang J; Shan W; Duan S; Guo L
J Comput Assist Tomogr; 2022 Nov-Dec 01; 46(6):978-985. PubMed ID: 35759774
[TBL] [Abstract][Full Text] [Related]
16. Nomogram to differentiate benign and malignant thyroid nodules in the American College of Radiology Thyroid Imaging Reporting and Data System level 5.
Hu T; Li Z; Peng C; Huang L; Li H; Han X; Long X; Huang W; Zou R
Clin Endocrinol (Oxf); 2023 Feb; 98(2):249-258. PubMed ID: 36138550
[TBL] [Abstract][Full Text] [Related]
17. ACR TI-RADS classification combined with number of nodules, halo features optimizes diagnosis and prediction of follicular thyroid cancer.
Wu SJ; Tan L; Ruan JL; Qiu Y; Hao SY; Yang HY; Luo BM
Clin Hemorheol Microcirc; 2022; 82(4):323-334. PubMed ID: 36093690
[TBL] [Abstract][Full Text] [Related]
18. Modification of size cutoff for biopsy based on the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) for thyroid nodules in patients younger than 19 years.
Huang Y; Liu J; Zheng T; Zhong J; Tan Y; Liu M; Wang G
Eur Radiol; 2023 Dec; 33(12):9328-9335. PubMed ID: 37389607
[TBL] [Abstract][Full Text] [Related]
19. The diagnostic value of ultrasound on different-sized thyroid nodules based on ACR TI-RADS.
Li W; Chen J; Ye F; Xu D; Fan X; Yang C
Endocrine; 2023 Dec; 82(3):569-579. PubMed ID: 37656349
[TBL] [Abstract][Full Text] [Related]
20. Diagnostic value of ACR TI-RADS combined with three-dimensional shear wave elastography in ACR TI-RADS 4 and 5 thyroid nodules.
Hao L; Liu P; Ding C; Li J; Zhang Y
Chin Med J (Engl); 2023 May; 136(10):1225-1230. PubMed ID: 37075764
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]