158 related articles for article (PubMed ID: 33391426)
1. Risk-predicted dual nomograms consisting of clinical and ultrasound factors for downgrading BI-RADS category 4a breast lesions - A multiple centre study.
Niu Z; Tian JW; Ran HT; Ren WD; Chang C; Yuan JJ; Kang CS; Deng YB; Wang H; Luo BM; Guo SL; Zhou Q; Xue ES; Zhan WW; Zhou Q; Li J; Zhou P; Zhang CQ; Chen M; Gu Y; Xu JF; Chen W; Zhang YH; Wang HQ; Li JC; Wang HY; Jiang YX
J Cancer; 2021; 12(1):292-304. PubMed ID: 33391426
[No Abstract] [Full Text] [Related]
2. Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS.
Luo WQ; Huang QX; Huang XW; Hu HT; Zeng FQ; Wang W
Sci Rep; 2019 Aug; 9(1):11921. PubMed ID: 31417138
[TBL] [Abstract][Full Text] [Related]
3. An Improved Nomogram to Reduce False-Positive Biopsy Rates of Breast Imaging Reporting and Data System Ultrasonography Category 4A Lesions.
Hai L; Feng Y; Zhao J; Tang Q; Wang X; Cao X; Xiao C
Cancer Control; 2022; 29():10732748221122703. PubMed ID: 37735939
[TBL] [Abstract][Full Text] [Related]
4. Automatic Breast Volume Scanner and B-Ultrasound-Based Radiomics Nomogram for Clinician Management of BI-RADS 4A Lesions.
Ma Q; Wang J; Xu D; Zhu C; Qin J; Wu Y; Gao Y; Zhang C
Acad Radiol; 2023 Aug; 30(8):1628-1637. PubMed ID: 36456445
[TBL] [Abstract][Full Text] [Related]
5. A Nomogram for Enhancing the Diagnostic Effectiveness of Solid Breast BI-RADS 3-5 Masses to Determine Malignancy Based on Imaging Aspects of Conventional Ultrasonography and Contrast-Enhanced Ultrasound.
Yan M; Peng C; He D; Xu D; Yang C
Clin Breast Cancer; 2023 Oct; 23(7):693-703. PubMed ID: 37394416
[TBL] [Abstract][Full Text] [Related]
6. A new nomogram for predicting the malignant diagnosis of Breast Imaging Reporting and Data System (BI-RADS) ultrasonography category 4A lesions in women with dense breast tissue in the diagnostic setting.
Yang Y; Hu Y; Shen S; Jiang X; Gu R; Wang H; Liu F; Mei J; Liang J; Jia H; Liu Q; Gong C
Quant Imaging Med Surg; 2021 Jul; 11(7):3005-3017. PubMed ID: 34249630
[TBL] [Abstract][Full Text] [Related]
7. A nomogram to predict for malignant diagnosis of BI-RADS Category 4 breast lesions.
Mazouni C; Sneige N; Rouzier R; Balleyguier C; Bevers T; André F; Vielh P; Delaloge S
J Surg Oncol; 2010 Sep; 102(3):220-4. PubMed ID: 20740578
[TBL] [Abstract][Full Text] [Related]
8. Multimodal Ultrasound Imaging in Breast Imaging-Reporting and Data System 4 Breast Lesions: A Prediction Model for Malignancy.
Li XL; Lu F; Zhu AQ; Du D; Zhang YF; Guo LH; Sun LP; Xu HX
Ultrasound Med Biol; 2020 Dec; 46(12):3188-3199. PubMed ID: 32896449
[TBL] [Abstract][Full Text] [Related]
9. Evaluation of diagnostic efficacy of multimode ultrasound in BI-RADS 4 breast neoplasms and establishment of a predictive model.
Chen Y; Lu J; Li J; Liao J; Huang X; Zhang B
Front Oncol; 2022; 12():1053280. PubMed ID: 36505867
[TBL] [Abstract][Full Text] [Related]
10. Downgrade BI-RADS 4A Patients Using Nomogram Based on Breast Magnetic Resonance Imaging, Ultrasound, and Mammography.
Xie Y; Zhu Y; Chai W; Zong S; Xu S; Zhan W; Zhang X
Front Oncol; 2022; 12():807402. PubMed ID: 35155244
[TBL] [Abstract][Full Text] [Related]
11. Nomogram based on the O-RADS for predicting the malignancy risk of adnexal masses with complex ultrasound morphology.
Gong LP; Li XY; Wu YN; Dong S; Zhang S; Feng YN; Lv YE; Guo XJ; Peng YQ; Du XS; Tian JW; Sun CX; Sun LT
J Ovarian Res; 2023 Mar; 16(1):57. PubMed ID: 36945000
[TBL] [Abstract][Full Text] [Related]
12. A bimodal nomogram as an adjunct tool to reduce unnecessary breast biopsy following discordant ultrasonic and mammographic BI-RADS assessment.
Xu Z; Lin Y; Huo J; Gao Y; Lu J; Liang Y; Li L; Jiang Z; Du L; Lang T; Wen G; Li Y
Eur Radiol; 2024 Apr; 34(4):2608-2618. PubMed ID: 37840099
[TBL] [Abstract][Full Text] [Related]
13. Nomograms for prediction of breast cancer in breast imaging reporting and data system (BI-RADS) ultrasound category 4 or 5 lesions: A single-center retrospective study based on radiomics features.
Hong ZL; Chen S; Peng XR; Li JW; Yang JC; Wu SS
Front Oncol; 2022; 12():894476. PubMed ID: 36212503
[TBL] [Abstract][Full Text] [Related]
14. Ultrasound-Based Nomogram for Distinguishing Malignant Tumors from Nodular Sclerosing Adenoses in Solid Breast Lesions.
Liang T; Cong S; Yi Z; Liu J; Huang C; Shen J; Pei S; Chen G; Liu Z
J Ultrasound Med; 2021 Oct; 40(10):2189-2200. PubMed ID: 33438775
[TBL] [Abstract][Full Text] [Related]
15. Combination of different types of elastography in downgrading ultrasound Breast Imaging-Reporting and Data System category 4a breast lesions.
Zheng X; Huang Y; Wang Y; Liu Y; Li F; Han J; Wang J; Cao L; Zhou J
Breast Cancer Res Treat; 2019 Apr; 174(2):423-432. PubMed ID: 30515679
[TBL] [Abstract][Full Text] [Related]
16. Development and Validation of a Nomogram for Predicting Breast Malignancy in Male Patients Based on Clinical and Ultrasound Features.
Dong WH; Wu G; Zhao N; Zhang J
Curr Radiopharm; 2024 Jan; ():. PubMed ID: 38288830
[TBL] [Abstract][Full Text] [Related]
17. A clinical-radiomics nomogram based on multimodal ultrasound for predicting the malignancy risk in solid hypoechoic breast lesions.
Shiyan G; Liqing J; Yueqiong Y; Yan Z
Front Oncol; 2023; 13():1256146. PubMed ID: 37916158
[TBL] [Abstract][Full Text] [Related]
18. Automated Breast Volume Scanner (ABVS)-Based Radiomic Nomogram: A Potential Tool for Reducing Unnecessary Biopsies of BI-RADS 4 Lesions.
Wang SJ; Liu HQ; Yang T; Huang MQ; Zheng BW; Wu T; Qiu C; Han LQ; Ren J
Diagnostics (Basel); 2022 Jan; 12(1):. PubMed ID: 35054339
[TBL] [Abstract][Full Text] [Related]
19. Photoacoustic Imaging Radiomics to Identify Breast Cancer in BI-RADS 4 or 5 Lesions.
Li G; Huang Z; Luo H; Tian H; Ding Z; Deng Y; Xu J; Wu H; Dong F
Clin Breast Cancer; 2024 Feb; ():. PubMed ID: 38548517
[TBL] [Abstract][Full Text] [Related]
20. Ultrasound Elastography Combined With BI-RADS-US Classification System: Is It Helpful for the Diagnostic Performance of Conventional Ultrasonography?
Hao SY; Jiang QC; Zhong WJ; Zhao XB; Yao JY; Li LJ; Luo BM; Ou B; Zhi H
Clin Breast Cancer; 2016 Jun; 16(3):e33-41. PubMed ID: 26639065
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]