166 related articles for article (PubMed ID: 29871661)
1. Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study.
Hruska CB; Geske JR; Swanson TN; Mammel AN; Lake DS; Manduca A; Conners AL; Whaley DH; Scott CG; Carter RE; Rhodes DJ; O'Connor MK; Vachon CM
Breast Cancer Res; 2018 Jun; 20(1):46. PubMed ID: 29871661
[TBL] [Abstract][Full Text] [Related]
2. Background Parenchymal Uptake on Molecular Breast Imaging and Breast Cancer Risk: A Cohort Study.
Hruska CB; Geske JR; Conners AL; Whaley DH; Rhodes DJ; O'Connor MK; Carter RE; Scott CG; Vachon CM
AJR Am J Roentgenol; 2021 May; 216(5):1193-1204. PubMed ID: 32755210
[No Abstract] [Full Text] [Related]
3. Background parenchymal uptake on molecular breast imaging as a breast cancer risk factor: a case-control study.
Hruska CB; Scott CG; Conners AL; Whaley DH; Rhodes DJ; Carter RE; O'Connor MK; Hunt KN; Brandt KR; Vachon CM
Breast Cancer Res; 2016 Apr; 18(1):42. PubMed ID: 27113363
[TBL] [Abstract][Full Text] [Related]
4. Impact of short-term low-dose tamoxifen on molecular breast imaging background parenchymal uptake: a pilot study.
Hruska CB; Hunt KN; Conners AL; Geske JR; Brandt KR; Degnim AC; Vachon CM; O'Connor MK; Rhodes DJ
Breast Cancer Res; 2019 Mar; 21(1):38. PubMed ID: 30850011
[TBL] [Abstract][Full Text] [Related]
5. Classification of Background Parenchymal Uptake on Molecular Breast Imaging Using a Convolutional Neural Network.
Carter RE; Attia ZI; Geske JR; Conners AL; Whaley DH; Hunt KN; O'Connor MK; Rhodes DJ; Hruska CB
JCO Clin Cancer Inform; 2019 Feb; 3():1-11. PubMed ID: 30807208
[TBL] [Abstract][Full Text] [Related]
6. Effect of menstrual cycle phase on background parenchymal uptake at molecular breast imaging.
Hruska CB; Conners AL; Vachon CM; O'Connor MK; Shuster LT; Bartley AC; Rhodes DJ
Acad Radiol; 2015 Sep; 22(9):1147-56. PubMed ID: 26112057
[TBL] [Abstract][Full Text] [Related]
7. Quantitative Assessment of Breast Parenchymal Uptake on 18F-FDG PET/CT: Correlation with Age, Background Parenchymal Enhancement, and Amount of Fibroglandular Tissue on MRI.
Leithner D; Baltzer PA; Magometschnigg HF; Wengert GJ; Karanikas G; Helbich TH; Weber M; Wadsak W; Pinker K
J Nucl Med; 2016 Oct; 57(10):1518-1522. PubMed ID: 27230924
[TBL] [Abstract][Full Text] [Related]
8. Breast Lesions Detected via Molecular Breast Imaging: Physiological Parameters Affecting Interpretation.
Ching JG; Brem RF
Acad Radiol; 2018 Dec; 25(12):1568-1576. PubMed ID: 29580791
[TBL] [Abstract][Full Text] [Related]
9. Does breast MRI background parenchymal enhancement indicate metabolic activity? Qualitative and 3D quantitative computer imaging analysis.
Mema E; Mango VL; Guo X; Karcich J; Yeh R; Wynn RT; Zhao B; Ha RS
J Magn Reson Imaging; 2018 Mar; 47(3):753-759. PubMed ID: 28646614
[TBL] [Abstract][Full Text] [Related]
10. Preliminary analysis: Background parenchymal 18F-FDG uptake in breast cancer patients appears to correlate with background parenchymal enhancement and to vary by distance from the index cancer.
Kim E; Mema E; Axelrod D; Sigmund E; Kim SG; Babb J; Melsaether AN
Eur J Radiol; 2019 Jan; 110():163-168. PubMed ID: 30599855
[TBL] [Abstract][Full Text] [Related]
11. Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer.
Winkel RR; von Euler-Chelpin M; Nielsen M; Diao P; Nielsen MB; Uldall WY; Vejborg I
BMC Cancer; 2015 Apr; 15():274. PubMed ID: 25884160
[TBL] [Abstract][Full Text] [Related]
12. Predicting interval and screen-detected breast cancers from mammographic density defined by different brightness thresholds.
Nguyen TL; Aung YK; Li S; Trinh NH; Evans CF; Baglietto L; Krishnan K; Dite GS; Stone J; English DR; Song YM; Sung J; Jenkins MA; Southey MC; Giles GG; Hopper JL
Breast Cancer Res; 2018 Dec; 20(1):152. PubMed ID: 30545395
[TBL] [Abstract][Full Text] [Related]
13. Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study.
Winkel RR; von Euler-Chelpin M; Nielsen M; Petersen K; Lillholm M; Nielsen MB; Lynge E; Uldall WY; Vejborg I
BMC Cancer; 2016 Jul; 16():414. PubMed ID: 27387546
[TBL] [Abstract][Full Text] [Related]
14. Background parenchymal uptake during molecular breast imaging and associated clinical factors.
Hruska CB; Rhodes DJ; Conners AL; Jones KN; Carter RE; Lingineni RK; Vachon CM
AJR Am J Roentgenol; 2015 Mar; 204(3):W363-70. PubMed ID: 25714323
[TBL] [Abstract][Full Text] [Related]
15. Mammographic density defined by higher than conventional brightness threshold better predicts breast cancer risk for full-field digital mammograms.
Nguyen TL; Aung YK; Evans CF; Yoon-Ho C; Jenkins MA; Sung J; Hopper JL; Song YM
Breast Cancer Res; 2015 Nov; 17():142. PubMed ID: 26581435
[TBL] [Abstract][Full Text] [Related]
16. Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk.
Hudson S; Vik Hjerkind K; Vinnicombe S; Allen S; Trewin C; Ursin G; Dos-Santos-Silva I; De Stavola BL
Breast Cancer Res; 2018 Dec; 20(1):156. PubMed ID: 30594212
[TBL] [Abstract][Full Text] [Related]
17. Physiological background parenchymal uptake of
Shimizu Y; Satake H; Ishigaki S; Shimamoto K; Uota F; Tadokoro M; Sato T; Kato K; Ishiguchi T; Naganawa S
Ann Nucl Med; 2022 Aug; 36(8):728-735. PubMed ID: 35610443
[TBL] [Abstract][Full Text] [Related]
18. Mammographic density defined by higher than conventional brightness thresholds better predicts breast cancer risk.
Nguyen TL; Aung YK; Evans CF; Dite GS; Stone J; MacInnis RJ; Dowty JG; Bickerstaffe A; Aujard K; Rommens JM; Song YM; Sung J; Jenkins MA; Southey MC; Giles GG; Apicella C; Hopper JL
Int J Epidemiol; 2017 Apr; 46(2):652-661. PubMed ID: 28338721
[TBL] [Abstract][Full Text] [Related]
19. Correlation between mammographic density and volumetric fibroglandular tissue estimated on breast MR images.
Wei J; Chan HP; Helvie MA; Roubidoux MA; Sahiner B; Hadjiiski LM; Zhou C; Paquerault S; Chenevert T; Goodsitt MM
Med Phys; 2004 Apr; 31(4):933-42. PubMed ID: 15125012
[TBL] [Abstract][Full Text] [Related]
20. Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction.
Gastounioti A; Kasi CD; Scott CG; Brandt KR; Jensen MR; Hruska CB; Wu FF; Norman AD; Conant EF; Winham SJ; Kerlikowske K; Kontos D; Vachon CM
Radiology; 2020 Jul; 296(1):24-31. PubMed ID: 32396041
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]