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

Power Pitch Session: At the Cutting-Edge of Cancer Imaging

Monday, May 9, 2016
Power Pitch Theatre, Exhibition Hall
16:30 - 18:30
Moderators: Sungheon Gene Kim, Linda Moy

Click Here to view the Power Pitch introductory session

Note: The videos below are only the slides from each presentation.
They do not have audio.

    Plasma #

1 Immune co-stimulatory blockade permits human glioblastoma xenografting in immunocompetent mice: model validation with MRI and bioluminescence imaging
Samantha Lynn Semenkow1, Shen Li2, Eric Raabe1,3, Jiadi Xu2,4, Miroslaw Janowski2,5, Byoung Chol Oh6, Gerald Brandacher6, Jeff W. Bulte2,4, Charles Eberhart1,3,7, and Piotr Walczak2
1Department of Pathology, Johns Hopkins Medical Institue, Baltimore, MD, United States, 2Department of Radiology and Radiological Science, Johns Hopkins Medical Institue, Baltimore, MD, United States, 3Department of Oncology, Johns Hopkins Medical Institue, Baltimore, MD, United States, 4F. M. Kirby Center for Functional Brain Imaging Kennedy Krieger Institute, Johns Hopkins Medical Institue, Baltimore, MD, United States, 5NeuroRepair Department, Mossakowski Medical Research Centre, Warsaw, Poland, 6Department of Plastic and Reconstructive Surgery, Vascularized Composite Allotransplantation (VCA) Laboratory, Johns Hopkins Medical Institue, Baltimore, MD, United States, 7Department of Opthalmology, Johns Hopkins Medical Institue, Baltimore, MD, United States
Immunodeficient mice are currently used for modeling human brain tumor xenografts; however, immunodeficiency is a serious limitation precluding studies based on immunotherapy or inducing tumors in a variety of transgenic animal models. We therefore investigated whether disruption of co-stimulatory signaling using blocking antibodies induces tolerance to intracerebrally transplanted human glioblastoma xenografts in immunocompetent mice. With longitudinal MRI and bioluminescence we established that the growth rate of xenografts is comparable between immunodeficient and tolerance-induced immunocompetent mice. Quantitative MRI including T2/T1 relaxation time, MTR, diffusion parameters and perfusion were not significantly different, validating this new approach as a reliable brain tumor model. 

2 In vivo 1H MRS and MRI longitudinal assessment of GBM mouse xenografts derived from freshly injected human cells
Marta Lai1, Cristina Cudalbu2, Marie-France Hamou3,4, Mario Lepore2, Lijing Xin2, Roy Thomas Daniel4, Andreas Felix Hottinger5, Monika Hegi3,4, and Rolf Gruetter1,6,7
1Laboratory of Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 2Animal Imaging and Technology Core (AIT), Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 3Laboratory of Brain Tumor Biology and Genetics, Neuroscience Research Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland, 4Service of Neurosurgery, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), Lausanne, Switzerland, 5Service of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV), Lausanne, Switzerland, 6Department of Radiology, University of Geneva, Geneva, Switzerland, 7Department of Radiology, University of Lausanne, Lausanne, Switzerland
In the present study orthotopic xenograft mice models of glioblastoma (GBM) derived from freshly dissected human cells of three different patients were compared at the aim of assessing patient-to-patient variability related to tumor metabolism and structural development. Mice were followed longitudinally in vivo in a 14.1 Tesla scanner with MRI and 1H MRS which allowed to precisely quantify a wide range of GBM biomarkers. Finally spectra examined at late stage revealed peculiarity linked to each patient-derived xenograft, while longitudinal evolution of GBM biomarkers showed a close similarity in their expression within the same group and in animal lifespan. 

3 Multi-modal MRI Parametric Maps Combined with Receptor Information to Optimize Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer
Hakmook Kang1,2, Allison Hainline1, Xia Li3, Lori R. Arlinghaus4, Vandana G. Abramson5,6, A. Bapsi Chakravarthy5,7, Brian Bingham8, and Thomas E. Yankeelov2,4,5,9
1Biostatistics, Vanderbilt University, Nashville, TN, United States, 2Center for Quantitative Science, Vanderbilt University, Nashville, TN, United States, 3GE Global Research, Niskayuna, NY, United States,4Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, 5Ingram Cancer Center, Vanderbilt University, Nashville, TN, United States, 6Medical Oncology, Vanderbilt University, Nashville, TN, United States, 7Radiation Oncology, Vanderbilt University, Nashville, TN, United States, 8School of Medicine, Vanderbilt University, Nashville, TN, United States, 9Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States
Pathologic complete response (pCR) following neoadjuvant chemotherapy is used as a short term surrogate marker of ultimate outcome in patients with breast cancer. Current imaging tools are suboptimal in predicting this response. Analyzing voxel-level heterogeneity in multi-modal MRI maps in conjunction with receptor status data, i.e., DCE- and DW-MRI, and ER/PR/HER2 status, allows us to improve the predictive power after the first cycle of neoadjuvant chemotherapy (NAC). 

4 Early post-treatment changes of multi-parametric whole-body MRI quantitative parameters following Bortezomib induction in multiple myeloma; Preliminary results at 3.0 T
Arash Latifoltojar1, Margaret Hall-Craggs2, Alan Bainbridge2, Magdalena Sokolska2, Kwee Yong1, Neil Rabin2, Liam Watson1, Michelle Siu2, Matthew Benger2, Nikolaos Dikaios1, and Shonit Punwani1
1University College London, London, United Kingdom, 2University College London Hospital, London, United Kingdom
Whole body magnetic resonance imaging is becoming the gold standard imaging in initial assessment of multiple myeloma. Recently, functional imaging is being investigated in treatment response monitoring in multiple myeloma. We investigated different functional MRI biomarkers' temporal changes at early post-treatment stage in multiple myeloma patients following  Bortezomib induction.

5 The origins of glucoCEST signal: effect inhibiting glucose transport in brain tumors
Xiang Xu1,2, Jiadi Xu1,2, Linda Knutsson3, Yuguo Li1,2, Huanling Liu1,4, Guanshu Liu1,2, Bachchu Lal5,6, John Laterra5,6, Dmitri Artemov7,8, Michael T. McMahon1,2, Peter C.M. van Zijl1,2, and Kannie WY Chan1,2
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2FM Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, United States, 3Department of Medical Radiation Physics, Lund University, Lund, Sweden, 4Department of Ultrasound, Guangzhou Panyu Central Hospital, Panyu, China, People's Republic of, 5Department of Neurology, Kennedy Krieger Institute, Baltimore, MD, United States, 6Department of Neuroscience, Kennedy Krieger Institute, Baltimore, MD, United States, 7Division of Cancer Imaging Research, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 8JHU In Vivo Cellular Molecular Imaging Center, Baltimore, MD, United States
Recently D-glucose has shown potential to be used as a biodegradable contrast agent for cancer detection. However the origins of the glucoCEST signal is not yet completely understood. To identify the contributions to glucoCEST contrast, we administrated a glucose transporter inhibitor in a group of mice with implanted glioma. By inhibiting glucose transport into the cells, the effects of cellular glucose uptake and metabolism are suppressed and the perfusion properties of the extravascular extracellular space are delineated. A greater increase in glucoCEST contrast was seen in tumors in the group of mice with glucose transporter inhibitor compared to a group of mice without. This greater uptake and retention of glucose in the inhibitor group provides evidence that the intracellular glucose contribution is minimal. 

6 CEST Metrics for Assessing Early Response to Stereotactic Radiosurgery in Human Brain Metastases
Kimberly L. Desmond1,2, Hatef Mehrabian1,2, Arjun Sahgal1,3, Hany Soliman1,3, and Greg J. Stanisz1,2
1Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, 2Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Radiation Oncology, Odette Cancer Centre, Toronto, ON, Canada
Chemical exchange saturation transfer (CEST) spectra were collected at three timepoints following stereotactic radiosurgery (SRS). The magnetization transfer ratio (MTR) and CEST peak properties were evaluated at the offset frequencies of the NOE, amide and amine pools in the lesion and in the surrounding tissue. Positive correlation was found between changes in NOE peak amplitude and amide MTR at 1 week post-therapy and tumour volume change at one month post-therapy, while negative correlation was found between  amide peak width and NOE peak amplitude at the pre-treatment timepoint with volume change at one month post-therapy (p<0.1).  

7 Predicting TP53 mutational status of breast cancers on clinical DCE MRI using directional-gradient based radiogenomic descriptors
Nathaniel Braman1, Prateek Prasanna1, Donna Plecha2, Hannah Gilmore2, Lyndsay Harris2, Kristy Miskimen1, Tao Wan3, Vinay Varadan1, and Anant Madabhushi1
1Case Western Reserve University, Cleveland, OH, United States, 2University Hospitals, Cleveland, OH, United States, 3Beihang University, Beijing, China, People's Republic of
In this work, we report preliminary success in the prediction of TP53 mutational status in breast cancer from DCE-MRI using a computer-extracted radiogenomic descriptor of multi-scale disorder, Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe). A set of 8 distinguishing CoLlAGe features yielded accuracy of 78% in predicting TP53 mutational status and outperformed standard DCE-MRI pharmacokinetic parameters in an unsupervised hierarchical clustering. A non-invasive means of discerning TP53 mutational status may allow clinicians to more easily determine prognosis, assess treatment response, and inform treatment strategy. 

8 A Prototype Image Quality Assurance System for Accelerated Quantitative Breast DCE-MRI
Yuan Le1, Aneela Afzal2, Xiao Chen3, Bruce Spottiswoode4, Wei Huang2, and Chen Lin1
1Radiology and Imaging Science, Indiana University School of Medicine, Indianapolis, IN, United States, 2Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR, United States, 3Siemens Healthcare, Princeton, NJ, United States, 4Siemens Healthcare, Chicago, IL, United States
The goal of this work is to build a prototype quality assurance (QA) system for the quantitative pharmacokinetic (PK) analysis of breast DCE-MRI acquired with accelerated imaging techniques. A 3D digital tumor model with two sub-regions was constructed by segmenting patient images. The dynamic contrast enhanced images were synthesized according to the Tofts and Shutter Speed models with the TWIST technique. The QA system shows how the TWIST technique impacts the estimated pharmacokinetic parameters, and therefore allows necessary adjustments to be made to control the error.

9 Model Evolution Concept in Dynamic Contrast Enhanced MRI for Prediction of Tumor Interstitial Fluid Pressure - Video Not Available
Hassan Bagher-Ebadian1,2, Azimeh NV Dehkordi3, Rasha Alamgharibi2, Tavarekere Nagaraja1, David Nathanson1, Hamid Soltanian-Zadeh1, Stephen Brown1, Hamed Moradi4, Ali Arbab5, and James R Ewing1,2
1Henry Ford Hospital, Detroit, MI, United States, 2Oakland University, Rochester, MI, United States, 3Shahid Beheshti University, Tehran, Iran, 4Tarbiat Modares University, Tehran, Iran, 5Georgia Regents University, Augusta, GA, United States
In this study, three physiologically nested models (NM) are derived from the standard Tofts model to describe possible physiological conditions of underlying tissue pathology. Then, using NM selection technique, Model Evolution (ME) concept is framed to quantify the evolutions of 3 different model volumes throughout the course of Dynamic Contrast Enhanced MRI experiment. We hypothesized that three evolutionary profiles in the course of DCE-MRI experiment generated from the ME concept, highly depend on the inward diffusion and outward convection of CA concentration and contain abundant information for describing the mechanical properties of solid tumors such as Interstitial Fluid Pressure (IFP).

10 Automation of Pattern Recognition Analysis of Dynamic Contrast-Enhanced MRI Data to Assess the Tumor Microenvironment
SoHyun Han1, Radka Stoyanova2, Jason A. Koutcher3, HyungJoon Cho1, and Ellen Ackerstaff3
1Ulsan National Institute of Science and Technology, Ulsan, Korea, Republic of, 2Miller School of Medicine, University of Miami, Miami, FL, United States, 3Memorial Sloan Kettering Cancer Center, New York, NY, United States
Recently, a novel pattern recognition (PR) approach has been developed, identifying extent and spatial distribution of tumor microenvironments based on tumor vascularity. Here, our goal is to develop methods to minimize user intervention and errors from model-based approaches by introducing an automated algorithm for determining the number of classifiers. An SNR approach showed the highest accuracy at ~97% along five different tumor cell models with 104 slices total. The visualization of tumor heterogeneity (perfusion, hypoxia, necrosis) with automated analysis of DCE-MRI can reduce the need for manual expert intervention, extensive pharmacokinetic modeling, and could provide critical information for treatment planning.

11 In vivo measurement of tumor T1 relaxation time using a whole body clinically feasible multiple flip angle method can predict response to chemotherapy
Harbir Singh Sidhu1, Anna Barnes2, Nikolaos Dikaios1, Scott Rice1, Alan Bainbridge3, Robert Stein4, Sandra Strauss5, David Atkinson1, Stuart Taylor1, and Shonit Punwani1
1Centre for Medical Imaging, University College London, London, United Kingdom, 2Institute of Nuclear Medicine, University College London Hospital, London, United Kingdom, 3Medical Physics and Biomedical Engineering, University College London Hospital, London, United Kingdom, 4Medical Oncology, University College London Hospital, London, United Kingdom, 5Research Department of Oncology, University College London, London, United Kingdom
Tumor response assessment currently relies upon measurement of size change, which may not alter significantly early during treatment or at all with newer therapies. Patients may therefore incur significant side-effects (with associated healthcare cost) without benefit.   Assessment of soft tissue tumor T1 relaxation times before and early during treatment can predict lesion response whilst being incorporated within a clinically feasible whole-body MRI scan duration. Tumors undergoing partial response at the end of treatment demonstrated significant reduction in T1 values early during therapy compared to non-responding lesions.

In the future, this could facilitate early response assessment and complement other imaging biomarkers.

12 Quantitative Susceptibility Mapping to Interrogate Colorectal Metastases in Mouse Liver during Normoxia and Hyperoxia
Eoin Finnerty1, Rajiv Ramasawmy2, James O'Callaghan2, Mark F Lythgoe2, Karin Shmueli1, David L Thomas3, and Simon Walker-Samuel2
1Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2University College London, London, United Kingdom, 3Institute of Neurology, University College London, London, United Kingdom
This work examines the application of Quantitative Susceptibility Mapping (QSM) in a mouse model of colorectal liver metastases. It was hypothesised that QSM could provide a novel method of interrogation of liver tumours based on differences in blood oxygenation. Results under hyperoxic and normoxic conditions were compared to assess the response of the liver tissue and tumours. A vascular disrupting agent was then administered to assess its effect on the QSM measurements. A significant difference was found between liver and tumour tissue, and regional differences in susceptibility were found within a tumour. These differences were less apparent after VDA administration.

13 Early Brain Tumor Detection by Active-Feedback MRI - Permission Withheld
Zhao Li1, Chaohsiung Hsu1, Ryan Quiroz1, and Yung-Ya Lin1
1Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, United States
Early detection of high-grade malignancy, such as glioblastoma multiforme (GBM), using enhanced MRI techniques significantly increases not only the treatment options available, but also the patients’ survival rate. For this purpose, a conceptually new approach, termed “Active-Feedback MRI”, was developed. An active feedback electronic device was homebuilt to implement active-feedback pulse sequences to generate avalanching spin amplification and fixed-point spin dynamics, which enhances the local magnetic-field gradient variations due to irregular water contents and deoxyhemoglobin concentration in early GBM. Statistical results (N=22) for in vivo orthotopic xenografts GBM mouse models at various cancer stages validate the superior contrast and robustness of this approach (tumor time constant differs from that of the healthy brain tissue by +24%) towards early GBM detection than conventional T1-weighted (+2.6%) and T2-weighted images (-3.1%). This novel approach provides 4-8 times of improvements in early GBM tumor contrast, as measured by "tumor to normal tissue contrast", “contrast-to-noise ratio” (CNR) or “Visibility”.

14 In Vivo Conductivity Imaging of Rat Tumor Model Using MRI
Jiaen Liu1, Qi Shao1, Yicun Wang1, Gregor Adriany2, John Bischof3, Pierre-Francois Van de Moortele2, and Bin He1,4
1Biomedical Engineering, Univeristy of Minnesota, Minneapolis, MN, United States, 2Center for Magnetic Resonance Research, Univeristy of Minnesota, Minneapolis, MN, United States, 3Mechanical Engineering, Univeristy of Minnesota, Minneapolis, MN, United States, 4Institute for Engineering in Medicine, Univeristy of Minnesota, Minneapolis, MN, United States
Noninvasive in vivo imaging of the tissue conductivity has great potential in cancer diagnosis. Recently, electrical properties tomography (EPT) has been investigated with increasing effort to noninvasively image tissue conductivity in vivo using MRI. A preclinical method for imaging tumor conductivity can be valuable for understanding tumor development and associated conductivity change due to fundamental molecular and cellular reasons. In this study, tumor conductivity was studied based on a xenograft rat tumor model using a small animal EPT system. The result showed elevated conductivity in cancerous tissue compared to healthy tissue, suggesting the clinical value of EPT for tumor diagnosis.

15 Evaluation of T2W MRI-derived Textural Entropy for Assessment of Prostate Cancer Aggressiveness
Gabriel Nketiah1, Mattijs Elschot1, Eugene Kim 1, Tone Frost Bathen 1, and Kirsten Margrete Selnæs1
1Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
The complexity of the prostatic tissue requires sensitive, accurate and reproducible assessment methods for aggressiveness of prostatic carcinomas, especially in differentiating between Gleason score 3+4 and 4+3 tumors. We evaluated the applicability of T2W MRI-derived textural entropy as a potential marker for assessing prostate cancer aggressiveness. Our study found textural entropy to correlate  moderately positive and negative with Gleason score and apparent diffusion coefficient (ADC), respectively. T2W image textural entropy differentiated Gleason score 3+4 and 4+3 tumors with higher accuracy than other MRI-derived parameters (ADC, Ktrans and Ve), indicating the potential of MRI texture analysis in prostate cancer assessment.

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