Xiaoping Zhu¹, John R Cain¹, Shaonan Wang¹, Maria Feldmann^1,2, Gerry Thompson¹, Ka-Loh Li¹, Marie Claude Asselin¹, and Alan Jackson^1
1Wolfson Molecular Imaging Centre, University of Manchester, Manchester, United Kingdom, ²Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom

Conventional multi-compartment kinetic models designed to identify the intra- and extravascular spaces in human brain failed in separating K_trans from V_p due to the well-known covariance errors in the fitting procedure. An extended first pass model (EFPM) was implemented to reduce these errors. The new DCE-MRI method using EFPM significantly improved differentiation. Excellent accordance was found between the 3D EFPM permeability maps from DCE-MRI and 3D VPM-PET images. Strong separation between CP and surrounding veins has practical significance for partial volume correction of PET images. Good separation of K_trans and V_p will help understanding roles of CP in drug delivery

Henrik Pedersen¹, Adam E. Hansen¹, and Henrik B.W. Larsson^1
1Functional Imaging Unit (KFNA), Glostrup Hospital, Glostrup, Denmark

T1-weighted dynamic contrast enhanced (DCE) MRI has emerged as a promising technique for quantifying cerebral blood flow (CBF) and other vascular properties. However, the clinical feasibility of DCE-MRI perfusion imaging is currently limited by low SNR and poor spatial coverage. The recently proposed k-t PCA technique allows a considerable data reduction in dynamic MRI by jointly exploiting the separation of the aliased signals in x-f space and the sparsity of dynamic data when subjected to principal component analysis (PCA).This paper investigates the quality of whole-brain CBF measurements using DCE-MRI and 3D k-t PCA with 20 slices.

Greg O. Cron¹, Claire Foottit¹, Jean Francois Mercier¹, Rebecca Thornhill¹, Viviane Thanh-Van Nguyen², Ian Cameron¹, Mark E Schweitzer¹, J J Shankar¹, John Sinclair¹, John Woulfe¹, Matthew J Hogan³, and Thanh B Nguyen^1
1The Ottawa Hospital, Ottawa, Ontario, Canada, ²University of Montreal, ³Neuroradiology, University of Ottawa, Ottawa, Ontario, Canada

For quantitative DCE-MRI of human brain tumors, there is no single, widely implemented data acquisition protocol. This lack of standardization makes it difficult to compare different studies, especially between institutions. We propose standardizing the data acquired with any DCE pulse sequence by saving phase data during DCE and by performing Bookend T1 measurements before and after DCE. The phase and bookends enable reliable estimation of the AIF and tissue function, both in terms of absolute concentrations. Initial evaluation has shown that DCE-MRI tumor blood volume values are consistent with equivalent CT perfusion estimates, thus supporting the strategy.

Rishi Awasthi¹, Prativa Sahoo², Nuzhat Husain³, Priyanka Soni³, Ashish Awasthi⁴, Rohit Kumar Singh⁵, Sanjay Behari⁵, Chandra M Pandey⁴, Ram Kishan Singh Rathore⁶, and Rakesh Kumar Gupta^1
1Radiodiagnosis, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, Lucknow, Uttar Pradesh, India, ²Indian Institute of Technology, Kanpur, Kanpur, Uttar Pradesh, India, ³Pathology, Chatrapati Sahu ji Maharaj Medical University, Lucknow, Uttar Pradesh, India, ⁴Biostatistics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, Lucknow, Uttar Pradesh, India, ⁵Neurosurgery, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, Lucknow, Uttar Pradesh, India, ⁶Mathematics & Statistics, Indian Institute of Technology, Kanpur, Kanpur, Uttar Pradesh, India

Seventy six patients of brain tumor (55 high grades and 21 low grades) with a postoperative diagnosis of either high or low grade glioma were imaged using conventional, and DCE MRI. On discriminant analysis, rCBV, Kep, Ve and HIF-1α were proved to be significant discriminators of tumor grade and these parameters were able to classify high and low grade tumors with 92.1% accuracy at a significance level of p<0.001.

Heiko Schmiedeskamp¹, Matus Straka¹, Greg Zaharchuk¹, Nancy J Fischbein¹, Marteen G Lansberg², Jean-Marc Olivot², Greg W Albers², Michael E Moseley¹, and Roland Bammer^1
1Department of Radiology, Stanford University, Stanford, CA, United States, ²Department of Neurology, Stanford University, Stanford, CA, United States

A spin- and gradient-echo (SAGE) EPI sequence was used for simultaneous acquisition of spin- and gradient-echo weighted perfusion maps through the acquisition of 5 echo trains per readout. Hereby, perfusion parameters were calculated from estimates of R2 and R2*, rather than relative changes in signal intensity, with the goal to produce T1-independent, more quantitative PWI maps and to facilitate vessel size imaging.

Peter Sherman LaViolette¹, Alex D Cohen¹, Scott D Rand², Wade Mueller³, and Kathleen M Schmainda^1,2
1Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States, ²Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, ³Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States

It is well known that tumor growth beyond a size of about 2 mm requires the development of its own blood vessels, a process termed angiogenesis. While physiologic angiogenesis, such as that occurs with wound healing, results in the formation of well-ordered mature vessels, pathologic angiogenesis such as that observed with tumors, results in the formation of chaotic and immature vessels. It is therefore not surprising that the resulting tumor perfusion patterns are likewise altered. We hypothesized that application of ICA (independent component analysis) to DSC-MRI signals would provide a new approach for distinguishing tumor from normal tissue, thus demonstrating the potential to serve as a novel biomarker to predict response to anti-angiogenic drugs thought to normalize tumor vasculature.

David Bonekamp¹, and Peter B Barker^1
1Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States

The purpose of this study is to implement a PC-MRA calibration for absolute quantification of CBF with DCE-MRI that is clinically feasible in routine examinations and to test the method and compare it with quantitative DCE-MRI CBF measurements with and without enhancement correction in patients with brain tumors. Twenty-six consecutive patients with gliomas (n=15), meningiomas (n=7, 6 WHO I, 1 WHO III), non-neoplastic lesions (n=2; hemorrhage and gliosis) or metastases (n=2) were included. Calibration of quantitative DSC-MRI CBF measurements significantly improves the differentiation between brain tumors compared to quantitative DSC-MRI with or without the use of extravasation correction alone.

Kyrre E Emblem^1,2, Kim Mouridsen¹, Ronald JH. Borra¹, Gregory Sorensen¹, Tracy T Batchelor³, Rakesh K Jain⁴, and Atle Bjornerud^2,5
1A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, United States, ²The Interventional Center, Oslo University Hospital - Rikshospitalet, Oslo, Norway, ³Pappas Center for Neuro-Oncology, Massachusetts General Hospital, Boston, Massachusetts, United States, ⁴Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts, United States, ⁵Department of Physics, University of Oslo, Oslo, Norway

A ‘byproduct’ of DSC-based leakage correction methods is the leakage term reflecting estimated contrast agent extravasation into the interstitial space. Potentially, if properly understood and corrected for, this parameter could provide estimates similar to that of DCE K^trans. In this study, we have compared contrast agent extravasation from DSC and DCE using simulations and patient data.

Clément Stephan Debacker^1,2, Nicolas Pannetier^1,2, Franck Mauconduit^1,2, Thomas Christen^1,3, and Emmanuel Luc Barbier^1,2
1INSERM - U836, Grenoble, France, ²Grenoble Institut des Neurosciences, Université Joseph Fourier, Grenoble, France, ³Department of Radiology, Stanford University, Stanford, California, United States

There is a growing interest in Dynamic Contrast Enhanced (DCE) MRI to characterize tumor perfusion and microvasculature. Current DCE approaches generally use a global parameter which concatenates two phenomena: permeability and diffusion of the CA in the interstitium. In this study, we evaluate, using numerical simulations, an MR experiment designed to estimate separately these two contributions. Accounting for relaxivity and susceptibility effects, results indicate that permeability measured at short echo times are not sensitive to the diffusion of CA. Moreover, at long echo times, it seems that the diffusion of CA in interstitium could be characterized.

Chao Xu¹, Valerij Kiselev², Peter Brunecker¹, and Jochen Fiebach^1
1Center for Stroke Research Berlin (CSB), Berlin, Berlin, Germany, ²Department of Diagnostic Radiology, University Hospital Freiburg, Freiburg, Germany

The characterization of the cerebral microvascular morphology can be achieved by assessing the ratio R_2GE/R_2SE^3/2 during DSC perfusion imaging. Rather than following a reversible line, the dynamic ratio forms a counter-clockwise loop in normal brain tissue. We simulated the dynamic involvement of microvasculature during the bolus passage and found out that the counter-clockwise loop results from the higher blood volume of venous blood than that of arterial blood. We suggest that the direction of the loop may indicate the local arterial and venous volume contribution.