J. Gibbs

发表

MRI measurements of breast tumor volume predict response to neoadjuvant chemotherapy and recurrence-free survival.

L. Esserman, N. Hylton, E. Hwang, 2005, AJR. American journal of roentgenology.

Additive value of diffusion‐weighted MRI in the I‐SPY 2 TRIAL

L. Esserman, N. Hylton, S. Partridge, 2019, Journal of magnetic resonance imaging : JMRI.

Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL

John Kornak, Bonnie N. Joe, Nola M. Hylton, 2016, Tomography.

Test–retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial

L. Esserman, N. Hylton, T. Chenevert, 2018, Journal of magnetic resonance imaging : JMRI.

Accuracy of MR imaging for revealing residual breast cancer in patients who have undergone neoadjuvant chemotherapy.

Ying Lu, Savannah C Partridge, L. Esserman, 2002, AJR. American journal of roentgenology.

Combined diffuse optical spectroscopy and contrast-enhanced magnetic resonance imaging for monitoring breast cancer neoadjuvant chemotherapy: a case study.

Bruce J Tromberg, Albert Cerussi, Nola Hylton, 2005, Journal of biomedical optics.

Magnetic resonance imaging for secondary assessment of breast density in a high-risk cohort.

Catherine Klifa, Julio Carballido-Gamio, Bo Fan, 2010, Magnetic resonance imaging.

Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer

L. Esserman, N. Hylton, J. Gibbs, 2020, Tomography.

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL

D. Berry, L. Esserman, D. Kontos, 2020, npj Breast Cancer.

Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy

L. Esserman, N. Hylton, J. Gibbs, 2020, Tomography.

Effect of Inter-Reader Variability on Diffusion-Weighted MRI Apparent Diffusion Coefficient Measurements and Prediction of Pathologic Complete Response for Breast Cancer

L. Esserman, N. Hylton, S. Partridge, 2022, Tomography.

Study of Breast Tissue Composition Using Magnetic Resonance Imaging and Diffuse Optical Spectroscopy

N. Hylton, B. Tromberg, N. Shah, 2006 .

Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1

Rhea D. Chitalia, Siddhesh P. Thakur, D. Kontos, 2022, Scientific Data.

Breast stromal enhancement on MRI is associated with response to neoadjuvant chemotherapy.

Catherine Klifa, Nola Hylton, Jimmy Hwang, 2008, AJR. American journal of roentgenology.

Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy

L. V. van't Veer, L. Esserman, N. Hylton, 2022, Cancers.

Characterization of breast tumors using the FIESTA technique and contrast-enhanced MRI

N. Hylton, S. Partridge, J. Gibbs, 2002 .

Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk

L. Esserman, C. Yau, J. Gibbs, 2021, npj Breast Cancer.

Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk

L. Esserman, N. Hylton, C. Yau, 2021, NPJ breast cancer.

Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial.

Zheng Zhang, Hiroyuki Abe, Thomas L Chenevert, 2018, Radiology.

Repeatability of quantitative MRI measurements in normal breast tissue.

John Kornak, Catherine Klifa, Bonnie N Joe, 2014, Translational oncology.

Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.

D. Berry, L. Esserman, D. Kontos, 2021, Radiology.

Biologic significance of false-positive magnetic resonance imaging enhancement in the setting of ductal carcinoma in situ.

Daniel F Chen, L. Esserman, N. Hylton, 2006, American journal of surgery.

AG-013736, a novel inhibitor of VEGF receptor tyrosine kinases, inhibits breast cancer growth and decreases vascular permeability as detected by dynamic contrast-enhanced magnetic resonance imaging.

Ying Lu, Ka-Loh Li, Roland G Henry, 2007, Magnetic resonance imaging.

Quantification of breast tissue index from MR data using fuzzy clustering

C. Klifa, N. Hylton, J. Gibbs, 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Diffuse Optical Spectroscopy and Magnetic Resonance Imaging of Breast Tissue

N. Hylton, B. Tromberg, N. Shah, 2004 .

Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial

N. Hylton, T. Chenevert, S. Partridge, 2022, Tomography.

Invasive breast cancer: predicting disease recurrence by using high-spatial-resolution signal enhancement ratio imaging.

Ying Lu, Ka-Loh Li, Savannah C Partridge, 2008, Radiology.

Kinetic assessment of breast tumors using high spatial resolution signal enhancement ratio (SER) imaging

Ying Lu, Ka-Loh Li, Roland G Henry, 2007, Magnetic resonance in medicine.

Invasive Breast Cancer: Predicting DiseaseRecurrencebyUsingHigh- Spatial-ResolutionSignal

L. Esserman, N. Hylton, S. Partridge, 2008 .

Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial

L. Esserman, N. Hylton, J. Gibbs, 2020, Tomography.

Invasive breast cancer: predicting disease recurrence by using high-spatial-resolution signal enhancement ratio imaging.

L. Esserman, N. Hylton, S. Partridge, 2008, Radiology.

Value of RECIST (Unidimensional), WHO (Bidimensional) and Volumetric Measures of Breast Tumor Response on MRI for Predicting Recurrence Free Survival in Patients Undergoing Preoperative Chemotherapy

N. Hylton, S. Partridge, J. Gibbs, 2005 .