275 related articles for article (PubMed ID: 26318821)
1. Early-stage invasive ductal carcinoma: Association of tumor apparent diffusion coefficient values with axillary lymph node metastasis.
Kim JY; Seo HB; Park S; Moon JI; Lee JW; Lee NK; Lee SW; Bae YT
Eur J Radiol; 2015 Nov; 84(11):2137-43. PubMed ID: 26318821
[TBL] [Abstract][Full Text] [Related]
2. Role of diffusion-weighted MRI: predicting axillary lymph node metastases in breast cancer.
Chung J; Youk JH; Kim JA; Gweon HM; Kim EK; Ryu YH; Son EJ
Acta Radiol; 2014 Oct; 55(8):909-16. PubMed ID: 24234236
[TBL] [Abstract][Full Text] [Related]
3. Apparent diffusion coefficient ratio between axillary lymph node with primary tumor to detect nodal metastasis in breast cancer patients.
Luo N; Su D; Jin G; Liu L; Zhu X; Xie D; Liu Y
J Magn Reson Imaging; 2013 Oct; 38(4):824-8. PubMed ID: 23440958
[TBL] [Abstract][Full Text] [Related]
4. Diagnostic Performance of Fused Diffusion-Weighted Imaging Using T1-Weighted Imaging for Axillary Nodal Staging in Patients With Early Breast Cancer.
Kim SH; Shin HJ; Shin KC; Chae EY; Choi WJ; Cha JH; Kim HH
Clin Breast Cancer; 2017 Apr; 17(2):154-163. PubMed ID: 27843006
[TBL] [Abstract][Full Text] [Related]
5. Predictors of axillary lymph node metastases in patients with T1 breast carcinoma.
Barth A; Craig PH; Silverstein MJ
Cancer; 1997 May; 79(10):1918-22. PubMed ID: 9149018
[TBL] [Abstract][Full Text] [Related]
6. Invasive ductal carcinoma: correlation of apparent diffusion coefficient value with pathological prognostic factors.
Razek AA; Gaballa G; Denewer A; Nada N
NMR Biomed; 2010 Jul; 23(6):619-23. PubMed ID: 20232453
[TBL] [Abstract][Full Text] [Related]
7. Prediction of Axillary Lymph Node Metastasis in Early-stage Triple-Negative Breast Cancer Using Multiparametric and Radiomic Features of Breast MRI.
Song SE; Woo OH; Cho Y; Cho KR; Park KH; Kim JW
Acad Radiol; 2023 Sep; 30 Suppl 2():S25-S37. PubMed ID: 37331865
[TBL] [Abstract][Full Text] [Related]
8. Predicting metastasis in clinically negative axillary lymph nodes with minimum apparent diffusion coefficient value in luminal A-like breast cancer.
Kato F; Kudo K; Yamashita H; Baba M; Shimizu A; Oyama-Manabe N; Kinoshita R; Li R; Shirato H
Breast Cancer; 2019 Sep; 26(5):628-636. PubMed ID: 30937834
[TBL] [Abstract][Full Text] [Related]
9. Volume-based metabolic parameter of breast cancer on preoperative 18F-FDG PET/CT could predict axillary lymph node metastasis.
An YS; Kang DK; Jung Y; Kim TH
Medicine (Baltimore); 2017 Nov; 96(45):e8557. PubMed ID: 29137072
[TBL] [Abstract][Full Text] [Related]
10. Diffusion-weighted MR imaging increases diagnostic accuracy of breast MR imaging for predicting axillary metastases in breast cancer patients.
Guvenc I; Whitman GJ; Liu P; Yalniz C; Ma J; Dogan BE
Breast J; 2019 Jan; 25(1):47-55. PubMed ID: 30444286
[TBL] [Abstract][Full Text] [Related]
11. Breast MRI for prediction of lymphovascular invasion in breast cancer patients with clinically negative axillary lymph nodes.
Igarashi T; Furube H; Ashida H; Ojiri H
Eur J Radiol; 2018 Oct; 107():111-118. PubMed ID: 30292254
[TBL] [Abstract][Full Text] [Related]
12. Predictive factors associated with axillary lymph node metastases in T1a and T1b breast carcinomas: analysis in more than 900 patients.
Rivadeneira DE; Simmons RM; Christos PJ; Hanna K; Daly JM; Osborne MP
J Am Coll Surg; 2000 Jul; 191(1):1-6; discussion 6-8. PubMed ID: 10898177
[TBL] [Abstract][Full Text] [Related]
13. Nomogram Based on Breast MRI and Clinicopathologic Features for Predicting Axillary Lymph Node Metastasis in Patients with Early-Stage Invasive Breast Cancer: A Retrospective Study.
Xue M; Che S; Tian Y; Xie L; Huang L; Zhao L; Guo N; Li J
Clin Breast Cancer; 2022 Jun; 22(4):e428-e437. PubMed ID: 34865995
[TBL] [Abstract][Full Text] [Related]
14. Assessment of axillary lymph nodes in patients with breast cancer with diffusion-weighted MR imaging in combination with routine and dynamic contrast MR imaging.
Razek AA; Lattif MA; Denewer A; Farouk O; Nada N
Breast Cancer; 2016 May; 23(3):525-32. PubMed ID: 25763535
[TBL] [Abstract][Full Text] [Related]
15. Diffusion weighted images of metastatic as compared with nonmetastatic axillary lymph nodes in patients with newly diagnosed breast cancer.
Yamaguchi K; Schacht D; Nakazono T; Irie H; Abe H
J Magn Reson Imaging; 2015 Sep; 42(3):771-8. PubMed ID: 25556886
[TBL] [Abstract][Full Text] [Related]
16. Correlations between apparent diffusion coefficient values of invasive ductal carcinoma and pathologic factors on diffusion-weighted MRI at 3.0 Tesla.
Park SH; Choi HY; Hahn SY
J Magn Reson Imaging; 2015 Jan; 41(1):175-82. PubMed ID: 24353241
[TBL] [Abstract][Full Text] [Related]
17. Investigation of synthetic MRI with quantitative parameters for discriminating axillary lymph nodes status in invasive breast cancer.
Qu M; Feng W; Liu X; Li Z; Li Y; Lu X; Lei J
Eur J Radiol; 2024 Jun; 175():111452. PubMed ID: 38604092
[TBL] [Abstract][Full Text] [Related]
18. Diagnostic value of diffusion-weighted magnetic resonance imaging: differentiation of benign and malignant lymph nodes in different regions of the body.
Seber T; Caglar E; Uylar T; Karaman N; Aktas E; Aribas BK
Clin Imaging; 2015; 39(5):856-62. PubMed ID: 26091745
[TBL] [Abstract][Full Text] [Related]
19. Apparent diffusion coefficient cannot predict molecular subtype and lymph node metastases in invasive breast cancer: a multicenter analysis.
Surov A; Chang YW; Li L; Martincich L; Partridge SC; Kim JY; Wienke A
BMC Cancer; 2019 Nov; 19(1):1043. PubMed ID: 31690273
[TBL] [Abstract][Full Text] [Related]
20. The Breast Tumor Strain Ratio Is a Predictive Parameter for Axillary Lymph Node Metastasis in Patients With Invasive Breast Cancer.
Kim JY; Shin JK; Lee SH
AJR Am J Roentgenol; 2015 Dec; 205(6):W630-8. PubMed ID: 26587952
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
