Thomas Gaass^1,2, Moritz Schneider¹, Michael Ingrisch¹, Julia Herzen³, and Julien Dinkel^1,2
1Institute for Clinical Radiology, Ludwig-Maximilians University, Munich, Germany, ²Comprehensive Pneumology Center, German Center for Lung Research, Munich, Germany, ³Department of Physics, Technische Universität München, Munich, Germany

The presented work demonstrates the applicability of a dedicated 3-dimensional phantom as a realistic MR- and CT-compatible phantom for microvascular perfusion simulation. The device constructed using resin-embedded, melt-spun, sacrificial sugar structures was examined using dynamic contrast enhanced MRI. Parameters, such as flow and volume fraction gained from deconvolving the signal enhancement curve showed very good agreement with the pre-set perfusion parameters. The presented phantom showed great potential in realistically simulating the capillary bed and can potentially serve as a quality insurance device for quantitative dynamic contrast enhanced MRI in the future.  

André Ahlgren¹, Ronnie Wirestam¹, Freddy Ståhlberg^1,2,3, and Linda Knutsson^1
1Department of Medical Radiation Physics, Lund University, Lund, Sweden, ²Department of Diagnostic Radiology, Lund University, Lund, Sweden, ³Lund University Bioimaging Center, Lund University, Lund, Sweden

Deconvolution is an ill-posed and ill-conditioned inverse problem that often yields non-physiological residue functions in perfusion MRI. Deconvolution methods based on Fourier transform or matrix decomposition often yield solutions with spurious oscillations. Although the perfusion value, estimated from the peak of the tissue impulse response function, may still be useful, any estimate that depends on the actual shape of the residue function will be prone to errors. To obtain physiologically reasonable residue functions in perfusion MRI, we propose the use of Bézier curves, and demonstrate initial experiences from the application to DSC-MRI in vivo data.

Deqiang Qiu¹, Junjie Wu¹, Seena Dehkharghani¹, and Amit Saindane^1
1Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States

We proposed a novel multi-band multi-echo DSC perfusion imaging method to estimate leakage-corrected perfusion parameters and additional vascular permeability parameters. Simulations were performed and showed that higher temporal resolution provided by the novel sequence improves the accuracy in the calculation of perfusion parameters.

Marco Pizzolato¹, Rutger Fick¹, Timothé Boutelier², and Rachid Deriche^1
1Athena Project-Team, Inria Sophia Antipolis - Méditerranée, Sophia Antipolis, France, ²Olea Medical, La Ciotat, France

In DSC-MRI the presence of dispersion affects the estimation, via deconvolution, of the residue function that characterizes the perfusion in each voxel. Dispersion is described by a Vascular Transport Function (VTF) which knowledge is essential to recover a dispersion-free residue function. State-of-the-art techniques aim at characterizing the VTF but assume a specific shape for it, which in reality is unknown. We propose to estimate the residue function without assumptions by means of Dispersion-Compliant Bases (DCB). We use these results to find which VTF model better describes the in-vivo data for each tissue type by means of control point interpolation approaches.

Jeff L. Zhang¹, Christopher Hanrahan¹, Christopher C. Conlin¹, Corey Hart², Gwenael Layec², Kristi Carlston¹, Daniel Kim¹, Michelle Mueller³, and Vivian S. Lee^1
1Radiology, University of Utah, Salt Lake City, UT, United States, ²Internal Medicine, University of Utah, Salt Lake City, UT, United States, ³Vascular surgery, University of Utah, Salt Lake City, UT, United States

One major challenge for measuring exercise perfusion of skeletal muscle with ASL is the potential heterogeneity of arterial transit time (ATT) across the muscle. In this study, we used reliable DCE MRI technique to measure ATT of calf muscle in both healthy controls and peripheral artery disease patients and after plantar flexion of different loads. Our study showed that ATT of calf muscle varied with multiple factors, including muscle group, exercise load and healthy status, and had a wide range of 0~4 sec. The result suggests the necessity of performing calf-muscle ASL with multiple different post-labeling delays.

Sajan Goud Lingala¹, Yi Guo¹, Yinghua Zhu¹, Naren Nallapareddy¹, R. Marc Lebel², Meng Law³, and Krishna Nayak^1
1Electrical Engineering, University of Southern California, Los Angeles, CA, United States, ²GE Health care, Calgary, Canada, ³Radiology, University of Southern California, Los Angeles, CA, United States

We propose a novel tracer-kinetic model based constrained reconstruction scheme to enable highly accelerated DCE-MRI. The proposed approach efficiently leverages information of the contrast agent kinetic modeling into the reconstruction, and provides a novel alternative to current constraints that are blind to tracer kinetic modeling.  We develop the frame-work to include constraints derived from the extended-Tofts (e-Tofts) model. We perform noise sensitivity analysis to determine the accuracy and precision of parameter mapping with the proposed e-Tofts derived temporal bases. We demonstrate its utility in retrospectively accelerating brain tumor DCE datasets with different tumor characteristics. 

Dennis Lai-Hong Cheong¹, Bo Zhang¹, Bingwen Zheng¹, Limiao Jiang¹, Eugene Wai Mun Ong², Soo Chin Lee^3,4, and Thian C Ng^1
1Clinical Imaging Research Centre, A*STAR-NUS, Singapore, Singapore, ²Department of Diagnostic Imaging, National University Hospital in Singapore, Singapore, Singapore, ³Department of Haematology-Oncology, National University Cancer Institute, National University Health System, Singapore, Singapore, ⁴Cancer Science Institute of Singapore, Singapore, Singapore

Higher resolution DCE-MRI is readily attainable and should allow for more realistic distributed parameter tracer kinetics models to be used. However, simpler, faster and lesser parameters compartmental models such as the modified Tofts model are still preferred by many researchers. We present here how we have implemented a distributed parameter model to analyze 2.4sec/frame DCE MRI data in a clinical trial of neo-adjuvant chemotherapy with or without short-course anti-angiogenic therapy in breast cancer patients. The results from modified Tofts and the distributed parameter model differ. More realistic distributed parameter models might be better in analyzing high temporal resolution DCE-MRI data.

Dimitra Flouri^1,2, Daniel Lesnic², and Steven P Sourbron ^1
1Division of Biomedical Imaging, University of Leeds, Leeds, United Kingdom, ²Department of Applied Mathematics, University of Leeds, Leeds, United Kingdom

Tracer-kinetic model-driven motion correction is an attractive solution for DCE-MRI, but previous studies only use the extended Tofts model. We propose a generalisation based on a 4-parameter 2-compartment tracer-kinetic model, and evaluate it in simulated and patient kidney data. Results show a significantly improved alignment of the data and removal of the motion-induced parameter error at a wide range of noise levels. With improvement in calculation time this is viable method for motion correction in arbitrary DCE-MRI data.

Charlotte Debus¹, Ralf Floca², Amir Abdollahi¹, Jürgen Debus³, and Michael Ingrisch^4
1Translational Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany, ²Software development for Integrated Diagnostics and Therapy, German Cancer Research Center (DKFZ), Heidelberg, Germany, ³Department of Radiology, University of Heidelberg Medical School, Heidelberg, Germany, ⁴Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich, Germany

The two-compartment exchange model is a tracer-kinetic model that is defined by two coupled first-order differential equations. These can be solved analytically or by direct integration. In this simulation study, we compared both strategies for different parameter scenarios in synthetic 4D images. The sum of squared residuals was calculated either by numeric integration with the Runge-Kutta method or by numeric convolution. The resulting parameter estimates were evaluated in terms of accuracy, precision and computational speed. Both approaches yield similar results in parameter determination, the convolution excelled in computational speed.

Silvin P. Knight¹, Jacinta E. Browne², James F. Meaney¹, David S. Smith³, and Andrew J. Fagan^1
1National Centre for Advanced Medical Imaging (CAMI), St James Hospital / School of Medicine, Trinity College University of Dublin, Dublin, Ireland, ²School of Physics, Medical Ultrasound Group, Dublin Institute of Technology, Dublin, Ireland, ³Institute of Imaging Science / Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States

A method is lacking to comprehensively validate and optimise the ability of prostate DCE-MRI techniques to accurately measure pharmacokinetic (PK) parameters. We present a novel flow phantom capable of simultaneously producing two measurable, reproducible, and known arbitrarily-shaped contrast time-intensity curves, from which PK parameters can be derived. K^trans values were derived from MR data acquired at different temporal resolutions (2.3-20.3s) and were found to differ by -8.1% to -44.6%, when compared to calibrated ‘truth estimate’ values, with the lowest variance measured at a temporal resolution of 6.8s. The phantom can be used to help establish robust DCE-MRI prostate protocols.