ISMRM 24th Annual Meeting & Exhibition • 07-13 May 2016 • Singapore

Scientific Session: Prostate

Wednesday, May 11, 2016
Room 331-332
10:00 - 12:00
Moderators: Daniel Margolis, Susan Noworolski

High-resolution distortion-free diffusion imaging of the prostate using stimulated echo based turbo spin echo (DPsti-TSE) sequence
Qinwei Zhang1, Bram F. Coolen1, Gustav J. Strijkers2, Laurens van Buuren3, Uulke van der Heide3, Oliver J. Gurney-Champion 1, Sónia I. Gonçalves4, and Aart J. Nederveen1
1Department of Radiology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands, 2Biomedical Engineering and Physics, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands, 3Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands, 4Institute for Biomedical Imaging and Life Sciences, University of Coimbra, Coimbra, Portugal
Diffusion imaging is part of the standard MR imaging protocol for prostate cancer diagnosis. Conventional echo planar imaging (EPI) diffusion sequence has limitation on image resolution and additionally suffers from image distortion. The present study introduces a new stimulated echo based 3D diffusion preparation turbo spin echo sequence (DPsti-TSE) to achieve high-resolution and distortion free image. The sequence is also proved to be immune to eddy currents. 

Detection of Aggressive Prostate Cancer Using Extradomain-B Fibronectin Targeted MRI Contrast Agent
Zheng Han1, Yajuan Li1, and Zheng-Rong Lu1
1Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
Prostate cancer (PCa) is the second most lethal cancer in American men with a high incidence rate. Current method of PCa screening is not specific to aggressive cancer type, which results in overtreatment with serious adverse effects. We developed a MRI contrast agent, ZD2-Gd(HP-DO3A), that targets to overexpressed extradomain-B in aggressive PCa. Our result showed an increased sensitivity for MRI detection of aggressive PCa using ZD2-Gd(HP-DO3A), compared with the clinical control agent ProHance®.  This contrast agent can potentially facilitate accurate risk stratification and clinical management of PCa. 


Short term Repeatability of Microstructural (VERDICT) MRI vs. ADC in Prostate Cancer
Edward William Johnston1, Eleftheria Panagiotaki2, Elisenda Bonet-Carne2, Nicola Stevens1, David Atkinson1, Daniel Alexander2, and Shonit Punwani1
1UCL Centre for Medical Imaging, London, United Kingdom, 2UCL Centre for Medical Image Computing, London, United Kingdom
VERDICT (Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumours) is a microstructural imaging technique that has shown significant potential in preclinical and pilot studies. However, its technical repeatability is unknown and must be established for translational and clinical application.  


5 patients underwent consecutive VERDICT acquisitions, and their quantitative parametric maps were compared in tumour and non-tumour regions. We found that cellularity was the most reliable parameter, with almost perfect repeatability in both normal and cancerous prostate tissue. Intra and extracellular volume fractions also performed well, with almost perfect repeatability in the normal prostate and excellent repeatability in cancerous tissue.

The Impact of Arterial Input Function Determination Variation on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge
Wei Huang1, Yiyi Chen1, Andriy Fedorov2, Xia Li3, Guido Jajamovich4, Dariya I Malyarenko5, Madhava Aryal5, Peter S LaViolette6, Matthew J Oborski7, Finbarr O’Sullivan8, Richard G Abramson9, Mark Muzi10, Kourosh Jafari-Khouzani 11, Aneela Afzal1, Alina Tudorica1, Brendan Moloney1, Cecilia Besa4, Jayashree Kalpathy-Cramer11, James M Mountz7, Charles M Laymon7, Kathleen Schmainda6, Yue Cao5, Thomas L Chenevert5, Bachir Taouli4, Thomas E Yankeelov9, Fiona Fennessy2, and Xin Li1
1Oregon Health & Science University, Portland, OR, United States, 2Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States, 3General Electric Global Research, Niskayuna, NY, United States, 4Icahn School of Medicine at Mount Sinai, New York, NY, United States, 5University of Michigan, Ann Arbor, MI, United States, 6Medical College of Wisconsin, Milwaukee, WI, United States,7University of Pittsburgh, Pittsburg, PA, United States, 8University College Cork, Cork, Ireland, 9Vanderbilt University, Nashville, TN, United States, 10University of Washington, Seattle, WA, United States,11Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
Dynamic Contrast-Enhanced MRI (DCE-MRI) pharmacokinetic modeling is widely used to extract tissue specific quantitative parameters.  However, the accuracy and precision of these parameters can be affected by many factors, with arterial input function (AIF) determination being a primary source of uncertainties. In this multicenter study, we sought to evaluate variations in DCE-MRI parameters estimated from shared prostate DCE-MRI data as a result of differences in AIFs.

Using low dose prostate dynamic contrast enhanced MRI data to verify newly developed eight-parameter mathematical form of arterial input function - Permission Withheld
Xiaobing Fan1, Shiyang Wang1, Milica Medved 1, Tatjana Antic2, Serkan Guneyli 1, Aytekin Oto 1, and Gregory S Karczmar 1
1Radiology, University of Chicago, Chicago, IL, United States, 2Pathology, University of Chicago, Chicago, IL, United States
Accurate measurements of the arterial input function (AIF) are needed in pharmacokinetic models to analyze dynamic contrast enhanced (DCE) MRI data. The AIF often cannot be accurately measured due to T2* and water exchange effects. Therefore, population AIFs are often employed in pharmacokinetic modeling. Here we report a new 8-parameter empirical mathematical model (EMM) that fits the AIF measured directly from the external femoral artery after a dose of contrast agent that was greatly reduced to minimize artifacts. The results showed that the EMM-AIF accurately models both 1st and 2nd passes of contrast agent circulations.

Quantitative DCE and DWI Characterization of the Index Lesion in Multiparametric MRI of Prostate Cancer Patients
Qing Yuan1, Daniel N Costa1,2, Julien Sénégas3, Yin Xi1, Andrea J Wiethoff2,4, Robert E Lenkinski1,2, and Ivan Pedrosa1,2
1Radiology, UT Southwestern Medical Center, Dallas, TX, United States, 2Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States, 3Philips Research Laboratories, Hamburg, Germany, 4Philips Research North America, Cambridge, MA, United States
We investigated the use of quantitative DWI and DCE measurements in MRI-visible index lesions as a surrogate for aggressiveness in prostate cancer patients. Tissue diffusion coefficient from simplified intravoxel incoherent motion model from DWI, and initial area under the curve from DCE offered the best performance in discriminating low and intermediate-to-high risk tumors. Anatomic and functional multiparametric MRI may provide a more reliable assessment of the aggressiveness of prostate cancer in patients.

Rad-Path correlation and machine learning generate epithelium density maps predictive of pathologically confirmed prostate cancer
Amy L. Kaczmarowski1, Kenneth Iczkowski2, William A. Hall3, Ahmad M. El-Arabi4, Kenneth Jacobsohn4, Paul Knechtges1, Mark Hohenwalter1, William See4, and Peter S. LaViolette1
1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 2Pathology, Medical College of Wisconsin, Milwaukee, WI, United States, 3Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States, 4Urology, Medical College of Wisconsin, Milwaukee, WI, United States
Radiological-pathological correlation is being used to validate prostate cancer imaging technology. This study combines these two modalities with machine learning to generate predictive maps of histological features (i.e. new contrasts) based on segmented histology. We find that epithelium density maps highlight regions pathologically confirmed as Gleason grade ≥3. This allowed the prediction of prostate cancer presence based solely on non-invasive imaging in 23 of 26 cases.

Quantitative MRI-Driven Deep Learning for Detection of Clinical Significant Prostate Cancer
Shiwen Shen1,2, Xinran Zhong1,3, Willam Hsu1, Alex Bui1, Holden Wu1, Michael Kuo1, Steven Raman1, Daniel Margolis1, and Kyunghyun Sung1
1Department of Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States, 2Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States,3Physics and Biology in Medicine IDP, University of California, Los Angeles, Los Angeles, CA, United States
We present a novel automatic classification method to distinguish between indolent and clinically significant prostatic carcinoma using multi-parametric MRI (mp-MRI). The main contributions are 1) utilizing state-of-art deep learning method to characterize the lesion in mp-MRI through a pre-trained convolutional neural network model, OverFeat, 2) building a hybrid two-order classification model that combines deep learning and conventional statistical features, and 3) avoiding annotation of the lesion boundaries and anatomical-location-specific training. The proposed method was evaluated using 102 lesions of prostate cancer and achieved significantly higher accuracy than the method with traditional statistical features.

Dixon with view angle tilting for improved post-contrast MRI of the prostate
Silke Hey1, Vijayasarathy Elanchezhian2, and Marius van Meel2
1Clinical Excellence & Research, Philips HealthTech, Best, Netherlands, 2MR Clinical Applications, Philips HealthTech, Best, Netherlands
A T1w TSE Dixon acquisition is combined with view angle tilting (VAT) in order to reduce susceptibility induced artifacts from orthopedic implants close to the prostate and at the same time improve fat suppression in the area of interest. The comparison with SPIR fat suppression shows clear improvement when using Dixon together with VAT by providing more homogeneous and complete fat suppression and reduced susceptibility artifacts thus allowing clear visualization of T1 based contrast changes in the prostate and the surrounding tissue. Those results have been proven at 1.5T and 3.0T on healthy volunteers with orthopedic hip implants.

Multiparametric Whole-body MRI vs 18FCH-PET-CT in the Primary Staging of Intermediate and High-Risk Prostate Cancer
Edward William Johnston1, Arash Latifoltojar1, Harbir Singh Sidhu1, Navin Ramachandran1, Magdalena Sokolska2, Alan Bainbridge2, Caroline Moore3, Hashim Ahmed3, and Shonit Punwani1
1UCL Centre for Medical Imaging, London, United Kingdom, 2Medical Physics, University College London Hospital, London, United Kingdom, 3Department of Urology, University College Hospital, London, United Kingdom
Whilst whole body MRI is gaining momentum in cancer staging for multiple tumour types, relatively few groups have focused on the primary staging of prostate cancer.  

In this study, we evaluated the role of an extensive multiparametric MRI protocol, including diffusion-weighted imaging in 23 patients against an 18F-choline PET-CT/ expert panel based reference standard.  

According to the reference standard, we found that whole body MRI provided an equivalently high diagnostic accuracy vs. PET-CT in lymph nodes, and outperformed PET-CT in the detection of bone lesions. However, higher technical error rates suggest MRI reporting experience needs to be developed first.


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