A 3D dual-echo spiral sequence for simultaneous dynamic susceptibility contrast and dynamic contrast-enhanced MRI with single bolus injection.

PURPOSE: Perfusion MRI reveals important tumor physiological and pathophysiologic information, making it a critical component in managing brain tumor patients. This study aimed to develop a dual-echo 3D spiral technique with a single-bolus scheme to simultaneously acquire both dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) data and overcome the limitations of current EPI-based techniques. METHODS: A 3D spiral-based technique with dual-echo acquisition was implemented and optimized on a 3T MRI scanner with a spiral staircase trajectory and through-plane SENSE acceleration for improved speed and image quality, in-plane variable-density undersampling combined with a sliding-window acquisition and reconstruction approach for increased speed, and an advanced iterative deblurring algorithm. Four volunteers were scanned and compared with the standard of care (SOC) single-echo EPI and a dual-echo EPI technique. Two patients were scanned with the spiral technique during a preload bolus and compared with the SOC single-echo EPI collected during the second bolus injection. RESULTS: Volunteer data demonstrated that the spiral technique achieved high image quality, reduced geometric artifacts, and high temporal SNR compared with both single-echo and dual-echo EPI. Patient perfusion data showed that the spiral acquisition achieved accurate DSC quantification comparable to SOC single-echo dual-dose EPI, with the additional DCE information. CONCLUSION: A 3D dual-echo spiral technique was developed to simultaneously acquire both DSC and DCE data in a single-bolus injection with reduced contrast use. Preliminary volunteer and patient data demonstrated increased temporal SNR, reduced geometric artifacts, and accurate perfusion quantification, suggesting a competitive alternative to SOC-EPI techniques for brain perfusion MRI.

Assessment and prediction of glioblastoma therapy response: challenges and opportunities.

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.

BACKGROUND: Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. PURPOSE: To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. STUDY TYPE: Prospective. POPULATION: Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE: 3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence. ASSESSMENT: Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). STATISTICAL TEST: Levene's test, P < 0.05 corrected for multiple comparisons was considered statistically significant. RESULTS: The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size. DATA CONCLUSION: We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Development of a spiral spin- and gradient-echo (spiral-SAGE) approach for improved multi-parametric dynamic contrast neuroimaging.

PURPOSE: The purpose of this study was to develop a spiral-based combined spin- and gradient-echo (spiral-SAGE) method for simultaneous dynamic contrast-enhanced (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI). METHODS: Using this sequence, we obtained gradient-echo TEs of 1.69 and 26 ms, a SE TE of 87.72 ms, with a TR of 1663 ms. Using an iterative SENSE reconstruction followed by deblurring, spiral-induced image artifacts were minimized. Healthy volunteer images are shown to demonstrate image quality using the optimized reconstruction, as well as for comparison with EPI-based SAGE. A bioreactor phantom was used to compare dynamic-contrast time courses with both spiral-SAGE and EPI-SAGE. A proof-of-concept cohort of patients with brain tumors shows the range of hemodynamic maps available using spiral-SAGE. RESULTS: Comparison of spiral-SAGE images with conventional EPI-SAGE images illustrates substantial reductions of image distortion and artifactual image intensity variations. Bioreactor phantom data show similar dynamic contrast time courses between standard EPI-SAGE and spiral-SAGE for the second and third echoes, whereas first-echo data show improvements in quantifying T1 changes with shorter echo times. In a cohort of patients with brain tumors, spiral-SAGE-based perfusion and permeability maps are shown with comparison with the standard single-echo EPI perfusion map. CONCLUSION: Spiral-SAGE provides a substantial improvement for the assessment of perfusion and permeability by mitigating artifacts typically encountered with EPI and by providing a shorter echo time for improved characterization of permeability. Spiral-SAGE enables quantification of perfusion, permeability, and vessel architectural parameters, as demonstrated in brain tumors.

Systematic assessment of multi-echo dynamic susceptibility contrast MRI using a digital reference object.

PURPOSE: Brain tumor dynamic susceptibility contrast (DSC) MRI is adversely impacted by T1 and T2∗ contrast agent leakage effects that result in inaccurate hemodynamic metrics. While multi-echo acquisitions remove T1 leakage effects, there is no consensus on the optimal set of acquisition parameters. Using a computational approach, we systematically evaluated a wide range of acquisition strategies to determine the optimal multi-echo DSC-MRI perfusion protocol. METHODS: Using a population-based DSC-MRI digital reference object (DRO), we assessed the influence of preload dosing (no preload and full dose preload), field strength (1.5 and 3T), pulse sequence parameters (echo time, repetition time, and flip angle), and leakage correction on relative cerebral blood volume (rCBV) and flow (rCBF) accuracy. We also compared multi-echo DSC-MRI protocols with standard single-echo protocols. RESULTS: Multi-echo DSC-MRI is highly consistent across all protocols, and multi-echo rCBV (with or without use of a preload dose) had higher accuracy than single-echo rCBV. Regression analysis showed that choice of repetition time and flip angle had minimal impact on multi-echo rCBV and rCBV, indicating the potential for significant flexibility in acquisition parameters. The echo time combination had minimal impact on rCBV, though longer echo times should be avoided, particularly at higher field strengths. Leakage correction improved rCBV accuracy in all cases. Multi-echo rCBF was less biased than single-echo rCBF, although rCBF accuracy was reduced overall relative to rCBV. CONCLUSIONS: Multi-echo acquisitions were more robust than single-echo, essentially decoupling both repetition time and flip angle from rCBV accuracy. Multi-echo acquisitions obviate the need for preload dosing, although leakage correction to remove residual T2∗ leakage effects remains compulsory for high rCBV accuracy.

Analysis of postprocessing steps for residue function dependent dynamic susceptibility contrast (DSC)-MRI biomarkers and their clinical impact on glioma grading for both 1.5 and 3T.

BACKGROUND: Dynamic susceptibility contrast (DSC)-MRI analysis pipelines differ across studies and sites, potentially confounding the clinical value and use of the derived biomarkers. PURPOSE/HYPOTHESIS: To investigate how postprocessing steps for computation of cerebral blood volume (CBV) and residue function dependent parameters (cerebral blood flow [CBF], mean transit time [MTT], capillary transit heterogeneity [CTH]) impact glioma grading. STUDY TYPE: Retrospective study from The Cancer Imaging Archive (TCIA). POPULATION: Forty-nine subjects with low- and high-grade gliomas. FIELD STRENGTH/SEQUENCE: 1.5 and 3.0T clinical systems using a single-echo echo planar imaging (EPI) acquisition. ASSESSMENT: Manual regions of interest (ROIs) were provided by TCIA and automatically segmented ROIs were generated by k-means clustering. CBV was calculated based on conventional equations. Residue function dependent biomarkers (CBF, MTT, CTH) were found by two deconvolution methods: circular discretization followed by a signal-to-noise ratio (SNR)-adapted eigenvalue thresholding (Method 1) and Volterra discretization with L-curve-based Tikhonov regularization (Method 2). STATISTICAL TESTS: Analysis of variance, receiver operating characteristics (ROC), and logistic regression tests. RESULTS: MTT alone was unable to statistically differentiate glioma grade (P > 0.139). When normalized, tumor CBF, CTH, and CBV did not differ across field strengths (P > 0.141). Biomarkers normalized to automatically segmented regions performed equally (rCTH AUROC is 0.73 compared with 0.74) or better (rCBF AUROC increases from 0.74-0.84; rCBV AUROC increases 0.78-0.86) than manually drawn ROIs. By updating the current deconvolution steps (Method 2), rCTH can act as a classifier for glioma grade (P < 0.007), but not if processed by current conventional DSC methods (Method 1) (P > 0.577). Lastly, higher-order biomarkers (eg, rCBF and rCTH) along with rCBV increases AUROC to 0.92 for differentiating tumor grade as compared with 0.78 and 0.86 (manual and automatic reference regions, respectively) for rCBV alone. DATA CONCLUSION: With optimized analysis pipelines, higher-order perfusion biomarkers (rCBF and rCTH) improve glioma grading as compared with CBV alone. Additionally, postprocessing steps impact thresholds needed for glioma grading. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:547-553.

Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI.

In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T1, T2 and T2∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T1, T2 and T2∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics.

Translating preclinical MRI methods to clinical oncology.

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1377-1392.

The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains.

PURPOSE: Quantitative evaluation of dynamic contrast enhanced MRI (DCE-MRI) allows for estimating perfusion, vessel permeability, and tissue volume fractions by fitting signal intensity curves to pharmacokinetic models. These compart mental models assume rapid equilibration of contrast agent within each voxel. However, there is increasing evidence that this assumption is violated for small molecular weight gadolinium chelates. To evaluate the error introduced by this invalid assumption, we simulated DCE-MRI experiments with volume fractions computed from entire histological tumor cross-sections obtained from murine studies. METHODS: A 2D finite element model of a diffusion-compensated Tofts-Kety model was developed to simulate dynamic T1 signal intensity data. Digitized histology slices were segmented into vascular (vp ), cellular and extravascular extracellular (ve ) volume fractions. Within this domain, Ktrans (the volume transfer constant) was assigned values from 0 to 0.5 min-1 . A representative signal enhancement curve was then calculated for each imaging voxel and the resulting simulated DCE-MRI data analyzed by the extended Tofts-Kety model. RESULTS: Results indicated parameterization errors of -19.1% ± 10.6% in Ktrans , -4.92% ± 3.86% in ve , and 79.5% ± 16.8% in vp for use of Gd-DTPA over 4 tumor domains. CONCLUSION: These results indicate a need for revising the standard model of DCE-MRI to incorporate a correction for slow diffusion of contrast agent. Magn Reson Med 80:330-340, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Assessment of renal fibrosis in murine diabetic nephropathy using quantitative magnetization transfer MRI.

PURPOSE: Renal fibrosis is a hallmark of progressive renal disease; however, current clinical tests are insufficient for assessing renal fibrosis. Here we evaluated the utility of quantitative magnetization transfer MRI in detecting renal fibrosis in a murine model of progressive diabetic nephropathy (DN). METHODS: The db/db eNOS-/- mice, a well-recognized model of progressive DN, and normal wild-type mice were imaged at 7T. The quantitative magnetization transfer data were collected in coronal plane using a 2D magnetization transfer prepared spoiled gradient echo sequence with a Gaussian-shaped presaturation pulse. Parameters were derived using a two-pool fitting model. A normal range of cortical pool size ratio (PSR) was defined as Mean±2SD of wild-type kidneys (N = 20). The cortical regions whose PSR values exceeded this threshold (threshold PSR) were assessed. The correlations between the PSR-based and histological (collagen IV or picrosirius red stain) fibrosis measurements were evaluated. RESULTS: Compared with wild-type mice, moderate increases in mean PSR values and scattered clusters of high PSR region were observed in cortex of DN mouse kidneys. Abnormally high PSR regions (% area) that were detected by the threshold PSR were significantly increased in renal cortexes of DN mice. These regions progressively increased on aging and highly correlated with histological fibrosis measures, while the mean PSR values correlated much less. CONCLUSION: Renal fibrosis in DN can be assessed by the quantitative magnetization transfer MRI and threshold analysis. This technique may be used as a novel imaging biomarker for DN and other renal diseases.

Trastuzumab improves tumor perfusion and vascular delivery of cytotoxic therapy in a murine model of HER2+ breast cancer: preliminary results.

To employ in vivo imaging and histological techniques to identify and quantify vascular changes early in the course of treatment with trastuzumab in a murine model of HER2+ breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used to quantitatively characterize vessel perfusion/permeability (via the parameter K (trans) ) and the extravascular extracellular volume fraction (v e ) in the BT474 mouse model of HER2+ breast cancer (N = 20) at baseline, day one, and day four following trastuzumab treatment (10 mg/kg). Additional cohorts of mice were used to quantify proliferation (Ki67), microvessel density (CD31), pericyte coverage (α-SMA) by immunohistochemistry (N = 44), and to quantify human VEGF-A expression (N = 29) throughout the course of therapy. Longitudinal assessment of combination doxorubicin ± trastuzumab (N = 42) tested the hypothesis that prior treatment with trastuzumab will increase the efficacy of subsequent doxorubicin therapy. Compared to control tumors, trastuzumab-treated tumors exhibited a significant increase in K (trans) (P = 0.035) on day four, indicating increased perfusion and/or vessel permeability and a simultaneous significant increase in v e (P = 0.01), indicating increased cell death. Immunohistochemical and ELISA analyses revealed that by day four the trastuzumab-treated tumors had a significant increase in vessel maturation index (i.e., the ratio of α-SMA to CD31 staining) compared to controls (P < 0.001) and a significant decrease in VEGF-A (P = 0.03). Additionally, trastuzumab dosing prior to doxorubicin improved the overall effectiveness of the therapies (P < 0.001). This study identifies and validates improved perfusion characteristics following trastuzumab therapy, resulting in an improvement in trastuzumab-doxorubicin combination therapy in a murine model of HER2+ breast cancer. This data suggests properties of vessel maturation. In particular, the use of DCE-MRI, a clinically available imaging method, following treatment with trastuzumab may provide an opportunity to optimize the scheduling and improve delivery of subsequent cytotoxic therapy.

A simplified spin and gradient echo approach for brain tumor perfusion imaging.

PURPOSE: In this study, we propose a simplified acquisition and analysis approach for spin and gradient echo (SAGE)-based dynamic susceptibility-contrast MRI (DSC-MRI) data that is free of contrast agent T1 leakage effects. METHODS: A five-echo SAGE sequence was used to acquire DSC-MRI data in rat C6 tumors (n = 7). Nonlinear fitting of all echoes was performed to obtain T1-insensitive ΔR2* and ΔR2 time series. The simplified approach, which includes two gradient echoes and one spin echo, was also used to analytically compute T1-insensitive ΔR2* using the two gradient echoes and ΔR2 using all three echoes. The blood flow, blood volume, and vessel size values derived from each method were compared. RESULTS: In all cases, the five-echo and simplified SAGE ΔR2* and ΔR2 were in excellent agreement and demonstrated significant T1 leakage correction compared with the uncorrected single-echo data. The derived hemodynamic parameters for blood volume, blood flow, and vessel size were not significantly different between the two methods. CONCLUSIONS: The proposed simplified SAGE technique enables the acquisition of gradient and spin echo DSC-MRI data corrected for T1 leakage effects yields parameters that are in agreement with the five-echo SAGE approach and does not require nonlinear fitting to extract ΔR2* and ΔR2 time series.

Validation of a T1 and T2* leakage correction method based on multiecho dynamic susceptibility contrast MRI using MION as a reference standard.

PURPOSE: A combined biophysical- and pharmacokinetic-based method is proposed to separate, quantify, and correct for both T1 and T2* leakage effects using dual-echo dynamic susceptibility contrast (DSC) acquisitions to provide more accurate hemodynamic measures, as validated by a reference intravascular contrast agent (CA). THEORY AND METHODS: Dual-echo DSC-MRI data were acquired in two rodent glioma models. The T1 leakage effects were removed and also quantified to subsequently correct for the remaining T2* leakage effects. Pharmacokinetic, biophysical, and combined biophysical and pharmacokinetic models were used to obtain corrected cerebral blood volume (CBV) and cerebral blood flow (CBF), and these were compared with CBV and CBF from an intravascular CA. RESULTS: T1 -corrected CBV was significantly overestimated compared with MION CBV, while T1 + T2*-correction yielded CBV values closer to the reference values. The pharmacokinetic and simplified biophysical methods showed similar results and underestimated CBV in tumors exhibiting strong T2* leakage effects. The combined method was effective for correcting T1 and T2* leakage effects across tumor types. CONCLUSION: Correcting for both T1 and T2* leakage effects yielded more accurate measures of CBV. The combined correction method yields more reliable CBV measures than either correction method alone, but for certain brain tumor types (e.g., gliomas), the simplified biophysical method may provide a robust and computationally efficient alternative. Magn Reson Med 76:613-625, 2016. © 2015 Wiley Periodicals, Inc.

Influence of water compartmentation and heterogeneous relaxation on quantitative magnetization transfer imaging in rodent brain tumors.

PURPOSE: The goal of this study was to investigate the influence of water compartmentation and heterogeneous relaxation properties on quantitative magnetization transfer (qMT) imaging in tissues, and in particular whether a two-pool model is sufficient to describe qMT data in brain tumors. METHODS: Computer simulations and in vivo experiments with a series of qMT measurements before and after injection of Gd-DTPA were performed. Both off-resonance pulsed saturation (pulsed) and on-resonance selective inversion recovery (SIR) qMT methods were used, and all data were fit with a two-pool model only. RESULTS: Simulations indicated that a two-pool fitting of four-pool data yielded accurate measures of pool size ratio (PSR) of macromolecular versus free water protons when there were fast transcytolemmal exchange and slow R1 recovery. The fitted in vivo PSR of both pulsed and SIR qMT methods showed no dependence on R1 variations caused by different concentrations of Gd-DTPA during wash-out, whereas the fitted kex (magnetization transfer exchange rate) changed significantly with R1 . CONCLUSION: A two-pool model provides reproducible estimates of PSR in brain tumors independent of relaxation properties in the presence of relatively fast transcytolemmal exchange, whereas estimates of kex are biased by relaxation variations. In addition, estimates of PSR in brain tumors using the pulsed and SIR qMT methods agree well with one another. Magn Reson Med 76:635-644, 2016. © 2015 Wiley Periodicals, Inc.

Mapping murine diabetic kidney disease using chemical exchange saturation transfer MRI.

PURPOSE: Diabetic nephropathy (DN) is the leading cause of renal failure; however, current clinical tests are insufficient for assessing this disease. DN is associated with changes in renal metabolites, so we evaluated the utility of chemical exchange saturation transfer (CEST) imaging to detect changes characteristic of this disease. METHODS: Sensitivity of CEST imaging at 7 Tesla to DN was evaluated by imaging diabetic mice [db/db, db/db endothelial nitric oxide synthase (eNOS)-/-] that show different levels of nephropathy as well as by longitudinal imaging (8 to 24 weeks). Nondiabetic (db/m) mice were used as controls. RESULTS: Compared with nondiabetic mice, the CEST contrasts of hydroxyl metabolites that correspond to glucose and glycogen were significantly increased in papilla (P), inner medulla (IM), and outer medulla (OM) in db/db and db/db eNOS-/- kidneys at 16 weeks. The db/db eNOS-/- mice that showed advanced nephropathy exhibited greater CEST effects in OM and significant CEST contrasts were also observed in cortex. Longitudinally, db/db mice exhibited progressive increases in hydroxyl signals in IM+P and OM from 12 to 24 weeks and an increase was also observed in cortex at 24 weeks. CONCLUSION: CEST MRI can be used to measure changes of hydroxyl metabolites in kidney during progression of DN. Magn Reson Med 76:1531-1541, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

Assessing tumor cytoarchitecture using multiecho DSC-MRI derived measures of the transverse relaxivity at tracer equilibrium (TRATE).

PURPOSE: In brain tumor dynamic susceptibility contrast (DSC)-MRI studies, multiecho acquisition methods are used to quantify the dynamic changes in T1 and T2 * that occur when contrast agent (CA) extravasates. Such methods also enable the estimation of the effective tissue CA transverse relaxivity. The goal of this study was to evaluate the sensitivity of the transverse relaxivity at tracer equilibrium (TRATE) to tumor cytoarchitecture. METHODS: Computational and in vitro studies were used to evaluate the biophysical basis of TRATE. In 9L, C6, and human brain tumors, TRATE, the apparent diffusion coefficient (ADC), the CA transfer constant (K(trans) ), the extravascular extracellular volume fraction (ve ), and histological data were compared. RESULTS: Simulations and in vitro results indicate that TRATE is highly sensitive to variations in cellular properties such as cell size and density. The histologic cell density and TRATE values were significantly higher in 9L tumors as compared to C6 tumors. In animal and human tumors, a voxel-wise comparison of TRATE with ADC, ve , and K(trans) maps showed low spatial correlation. CONCLUSION: The assessment of TRATE is clinically feasible and its sensitivity to tissue cytoarchitectural features not present in other imaging methods indicate that it could potentially serve as a unique structural signature or "trait" of cancer.

Imaging amide proton transfer and nuclear overhauser enhancement using chemical exchange rotation transfer (CERT).

PURPOSE: This study investigates amide proton transfer (APT) and nuclear overhauser enhancement (NOE) in phantoms and 9L tumors in rat brains at 9.4 Tesla, using a recently developed method that can isolate different contributions to exchange. METHODS: Chemical exchange rotation transfer (CERT) was used to quantify APT and NOEs through subtraction of signals acquired at two irradiation flip angles, but with the same average irradiation power. RESULTS: CERT separates and quantifies specific APT and NOE signals without contamination from other proton pools, and thus overcomes a key shortcoming of conventional CEST asymmetry approaches. CERT thus has increased specificity, though at the cost of decreased signal strength. In vivo experiments show that the APT effect acquired with CERT in 9L rat tumors (3.1%) is relatively greater than that in normal tissue (2.5%), which is consistent with previous CEST asymmetry analysis. The NOE effect centered at -1.6 ppm shows substantial image contrast within the tumor and between the tumor and the surrounding tissue, while the NOE effect centered at -3.5 ppm shows little contrast. CONCLUSION: CERT provides an image contrast that is more specific to chemical exchange than conventional APT by means of asymmetric CEST Z-spectra analysis.

Repeatability and sensitivity of high resolution blood volume mapping in mouse kidney disease.

PURPOSE: To evaluate the repeatability of MRI-derived relative blood volume (RBV) measurements in mouse kidneys across subjects and days and to evaluate sensitivity of this approach to renal pathology. MATERIALS AND METHODS: A 7 Tesla MRI system and an intravascular iron-oxide contrast agent were used to acquire spin-echo-based renal RBV maps in 10 healthy mice on 2 consecutive days. Renal RBV maps were also acquired in the Alport and unilateral ureteral obstruction mouse models of renal disease. RESULTS: The average renal RBV measured on consecutive days was 19.97 ± 1.50 and 19.86 ± 1.62, yielding a concordance correlation coefficient of 0.94, indicating that this approach is highly repeatable. In the disease models, the RBV values were regionally dissimilar and substantially lower than those found in control mice. CONCLUSION: In vivo renal iron-oxide-based RBV mapping in mice complements the physiological information obtained from conventional assays of kidney function and could shed new insights into the pathological mechanisms of kidney disease.

Identification of a single-dose, low flip angle based CBV threshold for fractional tumor burden (FTB) mapping in recurrent glioblastoma.

BACKGROUND AND PURPOSE: DSC-MRI can be used to generate fractional tumor burden (FTB) maps, via application of relative CBV thresholds, to spatially differentiate glioblastoma recurrence from post treatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MRI protocol using preload, a moderate flip angle (MFA, 60°) and post-processing leakage correction. Recently, a DSC-MRI protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected RCBV equivalent to the reference protocol. This study aims to identify the RCBV thresholds for the LFA protocol that generate the most accurate FTB maps, concordant with those obtained from the reference MFA protocol. MATERIALS AND METHODS: Fifty-two patients with grade IV GBM who had prior surgical resection and received chemotherapy and radiotherapy were included in the study. Two sets of DSC-MRI data were collected sequentially first using LFA protocol with no preload, which served as the preload for the subsequent MFA protocol. Standardized relative CBV maps (sRCBV) were obtained for each patient and co-registered with the anatomical post-contrast T1-weighted images. The reference MFA-based FTB maps were computed using previously published sRCBV thresholds (1.0 and 1.56). An ROC analysis was conducted to identify the optimal, voxelwise LFA sRCBV thresholds, and the sensitivity, specificity, and accuracy of the LFA-based FTB maps were computed with respect to the MFA-based reference. RESULTS: The mean sRCBV values of tumors across patients exhibited strong agreement (CCC = 0.99) between the two protocols. Using the ROC analysis, the optimal lower LFA threshold that accurately distinguishes PTRE from tumor recurrence was found to be 1.0 (sensitivity: 87.77%; specificity: 90.22%), equivalent to the ground truth. To identify aggressive tumor regions, the ROC analysis identified an upper LFA threshold of 1.37 (sensitivity: 90.87%; specificity: 91.10%) for the reference MFA threshold of 1.56. CONCLUSION: For LFA-based FTB maps, a sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumor. FTB maps aids in surgical planning, guiding pathological diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MRI. ABBREVIATIONS: LFA = low flip angle; MFA = moderate flip angle; sRCBV = standardized relative cerebral blood volume; FTB = fractional tumor burden; PTRE = post treatment radiation effects; ROC = receiver operating characteristics; CCC = concordance correlation coefficient.

MRI and amino acid PET detection of whole-brain tumor burden.

Background: [18F]fluciclovine amino acid PET has shown promise for detecting brain tumor regions undetected on conventional anatomic MRI scans. However, it remains unclear which of these modalities provides a better assessment of the whole brain tumor burden. This study quantifies the performance of [18F]fluciclovine PET and MRI for detecting the whole brain tumor burden. Methods: Thirteen rats were orthotopically implanted with fluorescently transduced human glioblastoma cells. Rats underwent MRI (T1- and T2-weighted) and [18F]fluciclovine PET. Next brains were excised, optically cleared, and scanned ex vivo with fluorescence imaging. All images were co-registered using a novel landmark-based registration to enable a spatial comparison. The tumor burden identified on the fluorescent images was considered the ground truth for comparison with the in vivo imaging. Results: Across all cases, the PET sensitivity for detecting tumor burden (median 0.67) was not significantly different than MRI (combined T1+T2-weighted) sensitivity (median 0.61; p=0.85). However, the combined PET+MRI sensitivity (median 0.86) was significantly higher than MRI alone (41% higher; p=0.004) or PET alone (28% higher; p=0.0002). The specificity of combined PET+MRI (median=0.91) was significantly lower compared with MRI alone (6% lower; p=0.004) or PET alone (2% lower; p=0.002). Conclusion: In these glioblastoma xenografts, [18F]fluciclovine PET did not provide a significant increase in tumor burden detection relative to conventional anatomic MRI. However, a combined PET and MRI assessment did significantly improve detection sensitivity relative to either modality alone, suggesting potential value in a combined assessment for some tumors.