DCE‐MRI of the prostate using shutter‐speed vs. Tofts model for tumor characterization and assessment of aggressiveness

To quantify Tofts model (TM) and shutter‐speed model (SSM) perfusion parameters in prostate cancer (PCa) and noncancerous peripheral zone (PZ) and to compare the diagnostic performance of dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) to Prostate Imaging and Reporting and Data System (PI‐RADS) classification for the assessment of PCa aggressiveness.

[1]  Jan J W Lagendijk,et al.  Improving the arterial input function in dynamic contrast enhanced MRI by fitting the signal in the complex plane , 2016, Magnetic resonance in medicine.

[2]  Wei Huang,et al.  Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling. , 2016, Journal of magnetic resonance.

[3]  A. Ouzzane,et al.  Impact of arterial input function selection on the accuracy of dynamic contrast‐enhanced MRI quantitative analysis for the diagnosis of clinically significant prostate cancer , 2016, Journal of magnetic resonance imaging : JMRI.

[4]  Thomas E. Yankeelov,et al.  The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge , 2016, Tomography.

[5]  C. Schraml,et al.  Optimized Fast Dynamic Contrast-Enhanced Magnetic Resonance Imaging of the Prostate: Effect of Sampling Duration on Pharmacokinetic Parameters , 2016, Investigative radiology.

[6]  Wei Huang,et al.  DCE-MRI of hepatocellular carcinoma: perfusion quantification with Tofts model versus shutter-speed model—initial experience , 2016, Magnetic Resonance Materials in Physics, Biology and Medicine.

[7]  Wei Huang,et al.  Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI1 , 2016, Translational oncology.

[8]  Baris Turkbey,et al.  DCE MRI of prostate cancer , 2016, Abdominal Radiology.

[9]  Anant Madabhushi,et al.  Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer , 2016, Journal of magnetic resonance imaging : JMRI.

[10]  C. Schraml,et al.  Feasibility of CAIPIRINHA-Dixon-TWIST-VIBE for dynamic contrast-enhanced MRI of the prostate. , 2015, European journal of radiology.

[11]  B. Delahunt,et al.  The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System , 2015, The American journal of surgical pathology.

[12]  Jun Yu,et al.  Combining phase and magnitude information for contrast agent quantification in dynamic contrast‐enhanced MRI using statistical modeling , 2015, Magnetic resonance in medicine.

[13]  D. Chung,et al.  Optimal cut-off value of perfusion parameters for diagnosing prostate cancer and for assessing aggressiveness associated with Gleason score. , 2015, Clinical imaging.

[14]  Xin Li,et al.  Mapping human brain capillary water lifetime: high‐resolution metabolic neuroimaging , 2015, NMR in biomedicine.

[15]  A. Rosenkrantz,et al.  Transition zone prostate cancer: revisiting the role of multiparametric MRI at 3 T. , 2015, AJR. American journal of roentgenology.

[16]  D. Margolis,et al.  Correlation of quantitative diffusion‐weighted and dynamic contrast‐enhanced MRI parameters with prognostic factors in prostate cancer , 2014, Journal of medical imaging and radiation oncology.

[17]  Hassan Bagher-Ebadian,et al.  Dynamic contrast enhanced MRI parameters and tumor cellularity in a rat model of cerebral glioma at 7 T , 2014, Magnetic resonance in medicine.

[18]  T. Tammela,et al.  Overdiagnosis and overtreatment of prostate cancer. , 2014, European Urology.

[19]  Wei Huang,et al.  Intratumor mapping of intracellular water lifetime: metabolic images of breast cancer? , 2014, NMR in biomedicine.

[20]  Xuna Zhao,et al.  Detection of prostate cancer in peripheral zone: comparison of MR diffusion tensor imaging, quantitative dynamic contrast-enhanced MRI, and the two techniques combined at 3.0 T , 2014, Acta radiologica.

[21]  N. Lawrentschuk,et al.  The role of magnetic resonance imaging in the diagnosis and management of prostate cancer , 2013, BJU international.

[22]  Stella K Kang,et al.  High temporal resolution 3D gadolinium‐enhanced dynamic MR imaging of renal tumors with pharmacokinetic modeling: Preliminary observations , 2013, Journal of magnetic resonance imaging : JMRI.

[23]  P. Choyke,et al.  Accuracy of multiparametric magnetic resonance imaging in confirming eligibility for active surveillance for men with prostate cancer , 2013, Cancer.

[24]  M. Giger,et al.  Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score--a computer-aided diagnosis development study. , 2013, Radiology.

[25]  Wei Huang,et al.  Feasibility of shutter‐speed DCE‐MRI for improved prostate cancer detection , 2013, Magnetic resonance in medicine.

[26]  A. Jemal,et al.  Cancer statistics, 2013 , 2013, CA: a cancer journal for clinicians.

[27]  F. Frauscher,et al.  Applications of transrectal ultrasound in prostate cancer. , 2012, The British journal of radiology.

[28]  Wei Huang,et al.  Discrimination of benign and malignant breast lesions by using shutter-speed dynamic contrast-enhanced MR imaging. , 2011, Radiology.

[29]  Piotr Kozlowski,et al.  Combined prostate diffusion tensor imaging and dynamic contrast enhanced MRI at 3T--quantitative correlation with biopsy. , 2010, Magnetic resonance imaging.

[30]  Wei Huang,et al.  The magnetic resonance shutter speed discriminates vascular properties of malignant and benign breast tumors in vivo , 2008, Proceedings of the National Academy of Sciences.

[31]  Tristan Barrett,et al.  Dynamic contrast-enhanced MRI of prostate cancer at 3 T: a study of pharmacokinetic parameters. , 2007, AJR. American journal of roentgenology.

[32]  Silvia D. Chang,et al.  Combined diffusion‐weighted and dynamic contrast‐enhanced MRI for prostate cancer diagnosis—Correlation with biopsy and histopathology , 2006, Journal of magnetic resonance imaging : JMRI.

[33]  F. Schick,et al.  Relaxivity of Gadopentetate Dimeglumine (Magnevist), Gadobutrol (Gadovist), and Gadobenate Dimeglumine (MultiHance) in Human Blood Plasma at 0.2, 1.5, and 3 Tesla , 2006, Investigative radiology.

[34]  L. Egevad,et al.  The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma , 2005, The American journal of surgical pathology.

[35]  N. Rofsky,et al.  MR imaging relaxation times of abdominal and pelvic tissues measured in vivo at 3.0 T: preliminary results. , 2004, Radiology.

[36]  Thomas E Yankeelov,et al.  Variation of the relaxographic “shutter‐speed” for transcytolemmal water exchange affects the CR bolus‐tracking curve shape , 2003, Magnetic resonance in medicine.

[37]  Hedvig Hricak,et al.  MR imaging of the prostate , 2002, Cancer Imaging.

[38]  Cristián Zegers Ariztía,et al.  Manual , 2002 .

[39]  D P Dearnaley,et al.  Dynamic contrast enhanced MRI of prostate cancer: correlation with morphology and tumour stage, histological grade and PSA. , 2000, Clinical radiology.

[40]  Xin Li,et al.  Equilibrium transcytolemmal water‐exchange kinetics in skeletal muscle in vivo , 1999, Magnetic resonance in medicine.

[41]  D. Altman,et al.  Multiple significance tests: the Bonferroni method , 1995, BMJ.

[42]  R Deichmann,et al.  Quantification of T1 values by SNAPSHOT-FLASH NMR imaging , 1992 .

[43]  P. Tofts,et al.  Measurement of the blood‐brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts , 1991, Magnetic resonance in medicine.

[44]  Andriy Fedorov,et al.  A comparison of two methods for estimating DCE-MRI parameters via individual and cohort based AIFs in prostate cancer: a step towards practical implementation. , 2014, Magnetic resonance imaging.

[45]  C. Compton,et al.  AJCC Cancer Staging Manual , 2002, Springer New York.

[46]  N. Dubrawsky Cancer statistics , 2022 .