Tracer-kinetic modeling of dynamic contrast-enhanced MRI and CT: a primer

Workflow sensitivity of post-processing methods in renal DCE-MRI

OBJECTIVE

Estimation of renal filtration using dynamic contrast-enhanced imaging (DCE-MRI) requires a series of analysis steps. The possible number of distinct post-processing chains is large and grows rapidly with increasing number of processing steps or options. In this study we introduce a framework for systematic evaluation of the post-processing chains. The framework is later used to highlight the workflow processing chain sensitivity towards accuracy in estimation of glomerular filtration rate (GFR).

METHODS

Twenty healthy volunteers underwent DCE-MRI examinations as well as iohexol clearance for reference GFR measurements. In total, 692 different combinations of post-processing steps were explored for analysis, including options for kidney segmentation, B1 inhomogeneity correction, placement of arterial input function, gadolinium concentration estimation as well as handling of motion-corrupted volumes and breathing motion. The evaluation of various processing chains is presented using a classification tree framework and random forest ensemble learning.

RESULTS

Among the processing steps subject to testing, methods for calculating the gadolinium concentration as well as B1 inhomogeneity correction had the largest impact on accuracy of GFR estimations. Different segmentation methods did not play an important role in the post-processing of the MR data except from one processing chain where the automated segmentation outperformed the manual segmentation.

CONCLUSION

The proposed classification trees were efficiently used as a statistical tool for visualization and communication of results to distinguish between important and less influential processing steps in renal DCE-MRI. We also identified several crucial factors in the processing chain.

Technical Note: Quantitative dynamic contrast-enhanced MRI of a 3-dimensional artificial capillary network

PURPOSE

Variability across devices, patients, and time still hinders widespread recognition of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as quantitative biomarker. The purpose of this work was to introduce and characterize a dedicated microchannel phantom as a model for quantitative DCE-MRI measurements.

METHODS

A perfusable, MR-compatible microchannel network was constructed on the basis of sacrificial melt-spun sugar fibers embedded in a block of epoxy resin. Structural analysis was performed on the basis of light microscopy images before DCE-MRI experiments. During dynamic acquisition the capillary network was perfused with a standard contrast agent injection system. Flow-dependency, as well as inter- and intrascanner reproducibility of the computed DCE parameters were evaluated using a 3.0 T whole-body MRI.

RESULTS

Semi-quantitative and quantitative flow-related parameters exhibited the expected proportionality to the set flow rate (mean Pearson correlation coefficient: 0.991, P < 2.5e-5). The volume fraction was approximately independent from changes of the applied flow rate through the phantom. Repeatability and reproducibility experiments yielded maximum intrascanner coefficients of variation (CV) of 4.6% for quantitative parameters. All evaluated parameters were well in the range of known in vivo results for the applied flow rates.

CONCLUSION

The constructed phantom enables reproducible, flow-dependent, contrast-enhanced MR measurements with the potential to facilitate standardization and comparability of DCE-MRI examinations.

Characterization of the Tumor Microenvironment and Tumor-Stroma Interaction by Non-invasive Preclinical Imaging

Tumors are often characterized by hypoxia, vascular abnormalities, low extracellular pH, increased interstitial fluid pressure, altered choline-phospholipid metabolism, and aerobic glycolysis (Warburg effect). The impact of these tumor characteristics has been investigated extensively in the context of tumor development, progression, and treatment response, resulting in a number of non-invasive imaging biomarkers. More recent evidence suggests that cancer cells undergo metabolic reprograming, beyond aerobic glycolysis, in the course of tumor development and progression. The resulting altered metabolic content in tumors has the ability to affect cell signaling and block cellular differentiation. Additional emerging evidence reveals that the interaction between tumor and stroma cells can alter tumor metabolism (leading to metabolic reprograming) as well as tumor growth and vascular features. This review will summarize previous and current preclinical, non-invasive, multimodal imaging efforts to characterize the tumor microenvironment, including its stromal components and understand tumor-stroma interaction in cancer development, progression, and treatment response.

Contrast-Enhanced Ultrasound with VEGFR2-Targeted Microbubbles for Monitoring Regorafenib Therapy Effects in Experimental Colorectal Adenocarcinomas in Rats with DCE-MRI and Immunohistochemical Validation

OBJECTIVES

To investigate contrast-enhanced ultrasound (CEUS) with VEGFR2-targeted microbubbles for monitoring therapy effects of regorafenib on experimental colon carcinomas in rats with correlation to dynamic contrast-enhanced MRI (DCE-MRI) and immunohistochemistry.

MATERIALS AND METHODS

Human colorectal adenocarcinoma xenografts (HT-29) were implanted subcutaneously in n = 21 (n = 11 therapy group; n = 10 control group) female athymic nude rats (Hsd: RH-Foxn1rnu). Animals were imaged at baseline and after a one-week daily treatment with regorafenib or a placebo (10 mg/kg bodyweight), using CEUS with VEGFR2-targeted microbubbles and DCE-MRI. In CEUS tumor perfusion was assessed during an early vascular phase (wash-in area under the curve = WiAUC) and VEGFR2-specific binding during a late molecular phase (signal intensity after 8 (SI8min) and 10 minutes (SI10min)), using a conventional 15L8 linear transducer (transmit frequency 7 MHz, dynamic range 80 dB, depth 25 mm). In DCE-MRI functional parameters plasma flow (PF) and plasma volume (PV) were quantified. For validation purposes, CEUS parameters were correlated with DCE-MRI parameters and immunohistochemical VEGFR2, CD31, Ki-67 and TUNEL stainings.

RESULTS

CEUS perfusion parameter WiAUC decreased significantly (116,989 ± 77,048 a.u. to 30,076 ± 27,095a.u.; p = 0.005) under therapy with no significant changes (133,932 ± 65,960 a.u. to 84,316 ± 74,144 a.u.; p = 0.093) in the control group. In the therapy group, the amount of bound microbubbles in the late phase was significantly lower in the therapy than in the control group on day 7 (SI8min: 283 ± 191 vs. 802 ± 460 a.u.; p = 0.006); SI10min: 226 ± 149 vs. 645 ± 461 a.u.; p = 0.009). PF and PV decreased significantly (PF: 147 ± 58 mL/100 mL/min to 71 ± 15 mL/100 mL/min; p = 0.003; PV: 13 ± 3% to 9 ± 4%; p = 0.040) in the therapy group. Immunohistochemistry revealed significantly fewer VEGFR2 (7.2 ± 1.8 vs. 17.8 ± 4.6; p < 0.001), CD31 (8.1 ± 3.0 vs. 20.8 ± 5.7; p < 0.001) and Ki-67 (318.7 ± 94.0 vs. 468.0 ± 133.8; p = 0.004) and significantly more TUNEL (672.7 ± 194.0 vs. 357.6 ± 192.0; p = 0.003) positive cells in the therapy group. CEUS parameters showed significant (p < 0.05) correlations to DCE-MRI parameters and immunohistochemistry.

CONCLUSIONS

CEUS with VEGFR2-targeted microbubbles allowed for monitoring regorafenib functional and molecular therapy effects on experimental colorectal adenocarcinomas with a significant decline of CEUS and DCE-MRI perfusion parameters as well as a significant reduction of specifically bound microbubbles under therapy, consistent with a reduced expression of VEGFR2.

DCE-MRI blood–brain barrier assessment in acute ischemic stroke

Objective:

To quantitatively evaluate blood–brain barrier changes in ischemic stroke patients using dynamic contrast-enhanced (DCE) MRI.

Methods:

We examined 54 stroke patients (clinicaltrials.govNCT00715533, NCT02077582) in a 3T MRI scanner within 48 hours after symptom onset. Twenty-eight patients had a follow-up examination on day 5–7. DCE T1 mapping and Patlak analysis were employed to assess BBB permeability changes.

Results:

Median stroke Ktrans values (0.7 × 10−3 min−1 [interquartile range (IQR) 0.4–1.8] × 10−3 min−1) were more than 3-fold higher compared to median mirror Ktrans values (0.2 × 10−3 min−1, IQR 0.1–0.7 × 10−3 min−1, p < 0.001) and further increased at follow-up (n = 28, 2.3 × 10−3 min−1, IQR 0.8–4.6 × 10−3 min−1, p < 0.001). By contrast, mirror Ktrans values decreased over time with a clear interaction of timepoint and stroke/mirror side (p < 0.001). Median stroke Ktrans values were 2.5 times lower than in hemorrhagic transformed regions (0.7 vs 1.8 × 10−3 min−1; p = 0.055). There was no association between stroke Ktrans values and the delay from symptom onset to baseline examination, age, and presence of hyperintense acute reperfusion marker.

Conclusion:

BBB in acute stroke patients can be successfully assessed quantitatively. The decrease of BBB permeability in unaffected regions at follow-up may be an indicator of global BBB leakage even in vessel territories remote from the index infarct.

Dynamic Contrast-Enhanced MRI to Study Atherosclerotic Plaque Microvasculature

Rupture of a vulnerable atherosclerotic plaque of the carotid artery is an important underlying cause of clinical ischemic events, such as stroke. Abundant microvasculature has been identified as an important aspect contributing to plaque vulnerability. Plaque microvasculature can be studied non-invasively with dynamic contrast-enhanced (DCE-)MRI in animals and patients. In recent years, several DCE-MRI studies have been published evaluating the association between microvasculature and other key features of plaque vulnerability (e.g., inflammation and intraplaque hemorrhage), as well as the effects of novel therapeutic interventions. The present paper reviews this literature, focusing on DCE-MRI methods of acquisition and analysis of atherosclerotic plaques, the current state and future potential of DCE-MRI in the evaluation of plaque microvasculature in clinical and preclinical settings.

Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review

Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.

Vascular Magnetic Resonance Imaging in Brain Tumors During Antiangiogenic Therapy--Are We There Yet?

Abnormal tumor vasculature is a potent mediator of treatment resistance because it results in heterogeneous perfusion, hypoxia, increased interstitial fluid pressure, and incomplete penetration of cytotoxic chemotherapies. Targeting this abnormal tumor vasculature is a promising therapeutic strategy, but results with antiangiogenic drugs in brain cancer have been mixed. Vasculature's response to treatment is a dynamic physiological process that can change rapidly throughout treatment, so it requires noninvasive techniques to serially monitor these changes in order to improve outcome. We review the role of vascular magnetic resonance imaging to measure tumor response to treatment and highlight opportunities and future avenues for expanding these promising techniques.

Phase-based vascular input function: Improved quantitative DCE-MRI of atherosclerotic plaques

PURPOSE

Quantitative pharmacokinetic modeling of dynamic contrast-enhanced (DCE)-MRI can be used to assess atherosclerotic plaque microvasculature, which is an important marker of plaque vulnerability. Purpose of the present study was (1) to compare magnitude- versus phase-based vascular input functions (m-VIF vs ph-VIF) used in pharmacokinetic modeling and (2) to perform model calculations and flow phantom experiments to gain more insight into the differences between m-VIF and ph-VIF.

METHODS

Population averaged m-VIF and ph-VIFs were acquired from 11 patients with carotid plaques and used for pharmacokinetic analysis in another 17 patients. Simulations, using the Bloch equations and the MRI scan geometry, and flow phantom experiments were performed to determine the effect of local blood velocity on the magnitude and phase signal enhancement.

RESULTS

Simulations and flow phantom experiments revealed that flow within the lumen can lead to severe underestimation of m-VIF, while this is not the case for the ph-VIF. In line, the peak concentration of the m-VIF is significantly lower than ph-VIF (p < 0.001), in vivo. Quantitative model parameters for m- and ph-VIF differed in absolute values but were moderate to strongly correlated with each other [K(trans) Spearman's ρ > 0.93 (p < 0.001) and vp Spearman's ρ > 0.58 (p < 0.05)].

CONCLUSIONS

m-VIF is strongly influenced by local blood velocity, which leads to underestimation of the contrast medium concentration. Therefore, it is advised to use ph-VIF for DCE-MRI analysis of carotid plaques for accurate quantification.

Kinetic Curve Type Assessment for Classification of Breast Lesions Using Dynamic Contrast-Enhanced MR Imaging

OBJECTIVE

The aim of this study was to employ a kinetic model with dynamic contrast enhancement-magnetic resonance imaging to develop an approach that can efficiently distinguish malignant from benign lesions.

MATERIALS AND METHODS

A total of 43 patients with 46 lesions who underwent breast dynamic contrast enhancement-magnetic resonance imaging were included in this retrospective study. The distribution of malignant to benign lesions was 31/15 based on histological results. This study integrated a single-compartment kinetic model and dynamic contrast enhancement-magnetic resonance imaging to generate a kinetic modeling curve for improving the accuracy of diagnosis of breast lesions. Kinetic modeling curves of all different lesions were analyzed by three experienced radiologists and classified into one of three given types. Receiver operating characteristic and Kappa statistics were used for the qualitative method. The findings of the three radiologists based on the time-signal intensity curve and the kinetic curve were compared.

RESULTS

An average sensitivity of 82%, a specificity of 65%, an area under the receiver operating characteristic curve of 0.76, and a positive predictive value of 82% and negative predictive value of 63% was shown with the kinetic model (p = 0.017, 0.052, 0.068), as compared to an average sensitivity of 80%, a specificity of 55%, an area under the receiver operating characteristic of 0.69, and a positive predictive value of 79% and negative predictive value of 57% with the time-signal intensity curve method (p = 0.003, 0.004, 0.008). The diagnostic consistency of the three radiologists was shown by the κ-value, 0.857 (p<0.001) with the method based on the time-signal intensity curve and 0.826 (p<0.001) with the method of the kinetic model.

CONCLUSIONS

According to the statistic results based on the 46 lesions, the kinetic modeling curve method showed higher sensitivity, specificity, positive and negative predictive values as compared with the time-signal intensity curve method in lesion classification.

Perfusion MRI in hips with metal-on-metal and metal-on-polyethylene total hip arthroplasty: A pilot study

Objectives

Hips with metal-on-metal total hip arthroplasty (MoM THA) have a high rate of adverse local tissue reactions (ALTR), often associated with hypersensitivity reactions. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measures tissue perfusion with the parameter Ktrans (volume transfer constant of contrast agent). Our purpose was 1) to evaluate the feasibility of DCE-MRI in patients with THA and 2) to compare DCE-MRI in patients with MoM bearings with metal-on-polyethylene (MoP) bearings, hypothesising that the perfusion index Ktrans in hips with MoM THA is higher than in hips with MoP THA.

Methods

In this pilot study, 16 patients with primary THA were recruited (eight MoM, eight MoP). DCE-MRI of the hip was performed at 1.5 Tesla (T). For each patient, Ktrans was computed voxel-by-voxel in all tissue lateral to the bladder. The mean Ktrans for all voxels was then calculated. These values were compared with respect to implant type and gender, and further correlated with clinical parameters.

Results

There was no significant difference between the two bearing types with both genders combined. However, dividing patients by THA bearing and gender, women with MoM bearings had the highest Ktrans values, exceeding those of women with MoP bearings (0.067 min⁻¹versus 0.053 min⁻¹; p-value < 0.05) and men with MoM bearings (0.067 min⁻¹versus 0.034 min⁻¹; p-value < 0.001). Considering only the men, patients with MoM bearings had lower Ktrans than those with MoP bearings (0.034 min⁻¹versus 0.046 min⁻¹; p < 0.05).

Conclusion

DCE-MRI is feasible to perform in tissues surrounding THA. Females with MoM THA show high Ktrans values in DCE-MRI, suggesting altered tissue perfusion kinematics which may reflect relatively greater inflammation.

Cite this article: Dr P. E. Beaule. Perfusion MRI in hips with metal-on-metal and metal-on-polyethylene total hip arthroplasty: A pilot stud. Bone Joint Res 2016;5:73–79. DOI: 10.1302/2046-3758.53.2000572.

In silico toxicology: computational methods for the prediction of chemical toxicity

Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models. WIREs Comput Mol Sci 2016, 6:147-172. doi: 10.1002/wcms.1240 For further resources related to this article, please visit the WIREs website.

An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited

Background

Perfusion imaging has become an important image based tool to derive the physiological information in various applications, like tumor diagnostics and therapy, stroke, (cardio-) vascular diseases, or functional assessment of organs. However, even after 20 years of intense research in this field, perfusion imaging still remains a research tool without a broad clinical usage. One problem is the lack of standardization in technical aspects which have to be considered for successful quantitative evaluation; the second problem is a lack of tools that allow a direct integration into the diagnostic workflow in radiology.

Results

Five compartment models, namely, a one compartment model (1CP), a two compartment exchange (2CXM), a two compartment uptake model (2CUM), a two compartment filtration model (2FM) and eventually the extended Toft’s model (ETM) were implemented as plugin for the DICOM workstation OsiriX. Moreover, the plugin has a clean graphical user interface and provides means for quality management during the perfusion data analysis. Based on reference test data, the implementation was validated against a reference implementation. No differences were found in the calculated parameters.

Conclusion

We developed open source software to analyse DCE-MRI perfusion data. The software is designed as plugin for the DICOM Workstation OsiriX. It features a clean GUI and provides a simple workflow for data analysis while it could also be seen as a toolbox providing an implementation of several recent compartment models to be applied in research tasks. Integration into the infrastructure of a radiology department is given via OsiriX. Results can be saved automatically and reports generated automatically during data analysis ensure certain quality control.

The Added Prognostic Value of Preoperative Dynamic Contrast-Enhanced MRI Histogram Analysis in Patients with Glioblastoma: Analysis of Overall and Progression-Free Survival

BACKGROUND AND PURPOSE

The prognostic value of dynamic contrast-enhanced MR imaging in patients with glioblastoma is controversial. We investigated the added prognostic value of dynamic contrast-enhanced MR imaging to clinical parameters and molecular biomarkers in patients with glioblastoma by using histogram analysis.

MATERIALS AND METHODS

This retrospective study consisted of 61 patients who underwent preoperative dynamic contrast-enhanced MR imaging for glioblastoma. The histogram parameters of dynamic contrast-enhanced MR imaging, including volume transfer constant, extravascular extracellular volume fraction, and plasma volume fraction, were calculated from entire enhancing tumors. Univariate analyses for overall survival and progression-free survival were performed with preoperative clinical and dynamic contrast-enhanced MR imaging parameters and postoperative molecular biomarkers. Multivariate Cox regression was performed to build pre- and postoperative models for overall survival and progression-free survival. The performance of models was assessed by calculating the Harrell concordance index.

RESULTS

In univariate analysis, patients with higher volume transfer constant and extravascular extracellular volume fraction values showed worse overall survival and progression-free survival, whereas plasma volume fraction showed no significant correlation. In multivariate analyses for overall survival, the fifth percentile value of volume transfer constant and kurtosis of extravascular extracellular volume fraction were independently prognostic in the preoperative model, and kurtosis of volume transfer constant and extravascular extracellular volume fraction were independently prognostic in the postoperative model. For progression-free survival, independent prognostic factors were minimum and fifth percentile values of volume transfer constant and kurtosis of extravascular extracellular volume fraction in the preoperative model and kurtosis of extravascular extracellular volume fraction in the postoperative model. The performance of preoperative models for progression-free survival was significantly improved when minimum or fifth percentile values of volume transfer constant and kurtosis of extravascular extracellular volume fraction were added.

CONCLUSIONS

Higher volume transfer constant and extravascular extracellular volume fraction values are associated with worse prognosis, and dynamic contrast-enhanced MR imaging may have added prognostic value in combination with preoperative clinical parameters, especially in predicting progression-free survival.

High Spatiotemporal Resolution Dynamic Contrast-Enhanced MR Enterography in Crohn Disease Terminal Ileitis Using Continuous Golden-Angle Radial Sampling, Compressed Sensing, and Parallel Imaging

OBJECTIVE

The purpose of this article was to assess the feasibility of golden-angle radial acquisition with compress sensing reconstruction (Golden-angle RAdial Sparse Parallel [GRASP]) for acquiring high temporal resolution data for pharmacokinetic modeling while maintaining high image quality in patients with Crohn disease terminal ileitis.

MATERIALS AND METHODS

Fourteen patients with biopsy-proven Crohn terminal ileitis were scanned using both contrast-enhanced GRASP and Cartesian breath-hold (volume-interpolated breath-hold examination [VIBE]) acquisitions. GRASP data were reconstructed with 2.4-second temporal resolution and fitted to the generalized kinetic model using an individualized arterial input function to derive the volume transfer coefficient (K(trans)) and interstitial volume (v(e)). Reconstructions, including data from the entire GRASP acquisition and Cartesian VIBE acquisitions, were rated for image quality, artifact, and detection of typical Crohn ileitis features.

RESULTS

Inflamed loops of ileum had significantly higher K(trans) (3.36 ± 2.49 vs 0.86 ± 0.49 min(-1), p < 0.005) and v(e) (0.53 ± 0.15 vs 0.20 ± 0.11, p < 0.005) compared with normal bowel loops. There were no significant differences between GRASP and Cartesian VIBE for overall image quality (p = 0.180) or detection of Crohn ileitis features, although streak artifact was worse with the GRASP acquisition (p = 0.001).

CONCLUSION

High temporal resolution data for pharmacokinetic modeling and high spatial resolution data for morphologic image analysis can be achieved in the same acquisition using GRASP.

Dynamic contrast-enhanced magnetic resonance imaging assessment of kidney function and renal masses: single slice versus whole organ/tumor

OBJECTIVES

The aim of this study was to compare single-slice and 3-dimensional (3D) analysis for magnetic resonance renography (plasma flow [FP], plasma volume [VP], and glomerular filtration rate [GFR]) and for dynamic contrast-enhanced magnetic resonance imaging (MRI) of renal tumors (FP, VP, permeability-surface area product), respectively.

MATERIAL AND METHODS

We prospectively included 22 patients (43 kidneys with 22 suspicious renal lesions) and performed preoperative and postoperative imaging before and after partial nephrectomy, respectively. Of the 22 renal lesions, 15 turned out to be renal cell carcinoma and were included in the tumor analysis, altogether leading to 86 renal and 15 tumor MRI scans, respectively. Dynamic contrast-enhanced MRI was performed with a time-resolved angiography with stochastic trajectories sequence (spatial resolution, 2.6 × 2.6 × 2.6 mm3; temporal resolution, 2.5 seconds) at 3 T (Magnetom Verio; Siemens Healthcare Sector) after injection of 0.05 mmol/kg body weight Gadobutrol (Bayer Healthcare Pharmaceuticals). Analysis was performed using regions of interest encompassing a single central slice and the whole kidney/tumor, respectively. A 2-compartment model yielding FP, VP, GFR, or tumor permeability-surface area product was used for kinetic modelling. Modelling was performed based on relative contrast enhancement to account for coil-related inhomogeneity. Significance in difference, agreement, and goodness of fit of the data to the curve was assessed with paired t tests, Bland-Altman plots, and χ2 test, respectively.

RESULTS

Bland-Altman analysis revealed a good agreement between both types of measurement for kidneys and tumors, respectively. Results between single-slice and whole-kidney regions of interest showed significant differences for Fp (single slice, 256.1 ± 104.1 mL/100 mL/min; whole kidney, 217.2 ± 92.5 mL/100 mL/min; P < 0.01). Regarding VP and GFR, no significant differences were observed. The χ2 test showed a significantly better goodness of fit of the data to the curve for whole kidneys (0.30% ± 0.18%) than for single slices (0.43% ± 0.26%) (P < 0.01). In contrast to renal assessment, tumor analysis showed no significant differences regarding functional parameters and χ test, respectively.

CONCLUSION

In dynamic contrast-enhanced MRI of the kidney, both 3D whole-organ/tumor and single-slice analyses provide roughly comparable values in functional analysis. However, 3D assessment is considerably more precise and should be preferred if available.

Anti-angiogenic Effects of Bumetanide Revealed by DCE-MRI with a Biodegradable Macromolecular Contrast Agent in a Colon Cancer Model

PURPOSE

To assess the antiangiogenic effect of bumetanide with dynamic contrast enhanced (DCE)-MRI and a biodegradable macromolecular MRI contrast agent.

METHODS

A new polydisulfide containing macrocyclic gadolinium (Gd(III)) chelates, poly([(Gd-DOTA)-DETA]-co-DTBP) (GODP), was synthesized as a safe biodegradable macromolecular MRI contrast agent for DCE-MRI. Nude mice bearing flank HT29 colon cancer xenografts were then treated daily with either bumetanide or saline for a total of 3 weeks. DCE-MRI was performed before and after the treatment weekly. The DCE-MRI data were analyzed using the adiabiatic approximation to the tissue homogeneity (AATH) model to assess the change of tumor vascularity in response to the treatment. Immunohistochemistry (IHC) and western blot were performed to study tumor angiogenic biomarkers and hypoxia.

RESULTS

DCE-MRI with GODP revealed that bumetanide reduced vascular permeability and plasma volume fraction by a significantly greater extent than the saline control therapy after 3 weeks of therapy. These changes were verified by the significant decline of CD31 and VEGF expression in the bumetanide treatment group. Despite a significant regression in vascularity, the tumors remained highly proliferative. Overexpression of the transcription factor HIF-1α in response to elevated hypoxia is thought to be the driving force behind the uninterrupted tumor expansion.

CONCLUSION

This study demonstrated the effectiveness of DCE-MRI with GODP in detecting vascular changes following the administration of bumetanide. Bumetanide has the potential to curtail growth of the tumor vasculature and can be employed in future therapeutic strategies.

DCE-MRI biomarkers for monitoring an anti-angiogenic triple combination therapy in experimental hypopharynx carcinoma xenografts with immunohistochemical validation

BACKGROUND

Novel anti-angiogenic treatments are increasingly complementing established cancer therapy strategies in head and neck tumors. Contrast-enhanced magnetic resonance imaging (MRI) can be applied for early and non-invasive therapy monitoring by non-invasive quantitative assessment of tumor microcirculation as in vivo imaging biomarkers of therapy response.

PURPOSE

To monitor the anti-angiogenic effects of a novel combination therapy on experimental head and neck squamous cell carcinomas (HNSCC) with dynamic contrast-enhanced (DCE)-MRI.

MATERIAL AND METHODS

Athymic rats (n = 18) with subcutaneous HNSCC xenografts were investigated by DCE-MRI before and after 7 days of a daily triple therapy regimen combining the COX-II-inhibitor celecoxib, the matrix-metalloproteinase-inhibitor GM6001, and the uPA-inhibitor upamostat. Quantitative measurements of tumor blood flow (tBF), tumor blood volume (tBV), and permeability-surface area product (PS) were calculated and validated by immunohistochemistry.

RESULTS

Mean tBF and tBV in triple-therapy animals decreased significantly from day 0 to day 7 (tBF, 41.0 ± 14.2 to 20.4 ± 5.7 mL/100 mL/min; P < 0.01; tBV, 17.7 ± 3.9 to 7.5 ± 3.3%; P < 0.01). No significant effects on PS were observed in either group (P > 0.05). Immunohistochemical analysis showed a significantly lower tumor vascularity in the therapy group than in the control group (CD31), significantly fewer Ki-67+ proliferating tumor cells and significantly more Capase-3+ apoptotic tumor cells (P < 0.05). Significant (P < 0.05) correlations were observed between tBF/tBV and CD31 (tBF, r = 0.84; tBV, r = 0.70), tBV and Ki-67 (r = 0.62), as well as tBF and caspase-3 (r = -0.64).

CONCLUSION

DCE-MRI may be a suitable tool for the non-invasive monitoring of the anti-vascular effects of this innovative triple therapy regimen with potential for clinical translation.

Correlation of perfusion MRI and 18F-FDG PET imaging biomarkers for monitoring regorafenib therapy in experimental colon carcinomas with immunohistochemical validation

Objectives

To investigate a multimodal, multiparametric perfusion MRI / ¹⁸F-fluoro-deoxyglucose-(¹⁸F-FDG)-PET imaging protocol for monitoring regorafenib therapy effects on experimental colorectal adenocarcinomas in rats with immunohistochemical validation.

Materials and Methods

Human colorectal adenocarcinoma xenografts (HT-29) were implanted subcutaneously in n = 17 (n = 10 therapy group; n = 7 control group) female athymic nude rats (Hsd:RH-Foxn1^rnu). Animals were imaged at baseline and after a one-week daily treatment protocol with regorafenib (10 mg/kg bodyweight) using a multimodal, multiparametric perfusion MRI/¹⁸F-FDG-PET imaging protocol. In perfusion MRI, quantitative parameters of plasma flow (PF, mL/100 mL/min), plasma volume (PV, %) and endothelial permeability-surface area product (PS, mL/100 mL/min) were calculated. In ¹⁸F-FDG-PET, tumor-to-background-ratio (TTB) was calculated. Perfusion MRI parameters were correlated with TTB and immunohistochemical assessments of tumor microvascular density (CD-31) and cell proliferation (Ki-67).

Results

Regorafenib significantly (p<0.01) suppressed PF (81.1±7.5 to 50.6±16.0 mL/100mL/min), PV (12.1±3.6 to 7.5±1.6%) and PS (13.6±3.2 to 7.9±2.3 mL/100mL/min) as well as TTB (3.4±0.6 to 1.9±1.1) between baseline and day 7. Immunohistochemistry revealed significantly (p<0.03) lower tumor microvascular density (CD-31, 7.0±2.4 vs. 16.1±5.9) and tumor cell proliferation (Ki-67, 434.0 ± 62.9 vs. 663.0 ± 98.3) in the therapy group. Perfusion MRI parameters ΔPF, ΔPV and ΔPS showed strong and significant (r = 0.67-0.78; p<0.01) correlations to the PET parameter ΔTTB and significant correlations (r = 0.57-0.67; p<0.03) to immunohistochemical Ki-67 as well as to CD-31-stainings (r = 0.49-0.55; p<0.05).

Conclusions

A multimodal, multiparametric perfusion MRI/PET imaging protocol allowed for non-invasive monitoring of regorafenib therapy effects on experimental colorectal adenocarcinomas in vivo with significant correlations between perfusion MRI parameters and ¹⁸F-FDG-PET validated by immunohistochemistry.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Blood-brain barrier imaging in human neuropathologies

The blood-brain barrier (BBB) is essential for normal function of the brain, and its role in many brain pathologies has been the focus of numerous studies during the last decades. Dysfunction of the BBB is not only being shown in numerous brain diseases, but animal studies have indicated that it plays a direct key role in the genesis of neurovascular dysfunction and associated neurodegeneration. As such evidence accumulates, the need for robust and clinically applicable methods for minimally invasive assessment of BBB integrity is becoming urgent. This review provides an introduction to BBB imaging methods in the clinical scenario. First, imaging modalities are reviewed, with a focus on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We then proceed to review image analysis methods, including quantitative and semi-quantitative methods. The advantages and limitations of each approach are discussed, and future directions and questions are highlighted.

Radiation protection issues in dynamic contrast-enhanced (perfusion) computed tomography

Dynamic contrast-enhanced (DCE) CT studies are increasingly used in both medical care and clinical trials to improve diagnosis and therapy management of the most common life-threatening diseases: stroke, coronary artery disease and cancer. It is thus the aim of this review to briefly summarize the current knowledge on deterministic and stochastic radiation effects relevant for patient protection, to present the essential concepts for determining radiation doses and risks associated with DCE-CT studies as well as representative results, and to discuss relevant aspects to be considered in the process of justification and optimization of these studies. For three default DCE-CT protocols implemented at a latest-generation CT system for cerebral, myocardial and cancer perfusion imaging, absorbed doses were measured by thermoluminescent dosimeters at an anthropomorphic body phantom and compared with thresholds for harmful (deterministic) tissue reactions. To characterize stochastic radiation risks of patients from these studies, life-time attributable cancer risks (LAR) were estimated using sex-, age-, and organ-specific risk models based on the hypothesis of a linear non-threshold dose-response relationship. For the brain, heart and pelvic cancer studies considered, local absorbed doses in the imaging field were about 100-190 mGy (total CTDI(vol), 200 mGy), 15-30 mGy (16 mGy) and 80-270 mGy (140 mGy), respectively. According to a recent publication of the International Commission on Radiological Protection (ICRP Publication 118, 2012), harmful tissue reactions of the cerebro- and cardiovascular systems as well as of the lenses of the eye become increasingly important at radiation doses of more than 0.5 Gy. The LARs estimated for the investigated cerebral and myocardial DCE-CT scenarios are less than 0.07% for males and 0.1% for females at an age of exposure of 40 years. For the considered tumor location and protocol, the corresponding LARs are more than 6 times as high. Stochastic radiation risks decrease substantially with age and are markedly higher for females than for males. To balance the diagnostic needs and patient protection, DCE-CT studies have to be strictly justified and carefully optimized in due consideration of the various aspects discussed in some detail in this review.

Dynamic contrast-enhanced magnetic resonance imaging of the liver: Applications in treatment of hepatic malignancies with vascular targeting agents

Dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging of the liver as a trendy technique can be applied in various kinds of liver diseases to evaluate perfusion and vascular characteristics of liver tissue and tumor. It has been proved that DCE-MR imaging plays an important role in the treatment of liver malignancies with vascular targeting agents. This review aims to give an overview of DCE-MR imaging of the liver in terms of semi-quantitative analysis methods, common quantitative analysis models and contrast agents and discuss its application value in the treatment of liver malignancies with vascular targeting agents.

[Therapy monitoring of neoadjuvant therapy with MRI. RECIST and functional imaging]

CLINICAL/METHODICAL ISSUE

Neoadjuvant chemotherapy is increasingly being applied in patients with operable breast cancer. Thus, an early prediction of response to neoadjuvant chemotherapy is of high relevance.

STANDARD RADIOLOGICAL METHODS

The interobserver variability of clinical examination, mammography and ultrasonography in the assessment of response to neoadjuvant chemotherapy is high.

METHODICAL INNOVATIONS

Magnetic resonance imaging (MRI) allows the assessment of functional parameters in addition to changes in tumor size and morphology.

PERFORMANCE

A reliable therapy response monitoring aims at optimizing individualized patient care.

ACHIEVEMENTS

This paper summarizes current guidelines for the assessment of response to neoadjuvant chemotherapy in breast cancer according to the response evaluation criteria in solid tumors (RECIST). Furthermore, the technical principles of MRI-based therapy monitoring are described and an overview of the clinical studies that have assessed the feasibility of functional MRI in response to treatment evaluation is given.

PRACTICAL RECOMMENDATIONS

The technology of functional MRI offers promising results concerning therapy response monitoring. However, the level of evidence is not sufficiently evaluated for the technologies of functional MRI presented here.

Quantitative multimodality imaging in cancer research and therapy

Advances in hardware and software have enabled the realization of clinically feasible, quantitative multimodality imaging of tissue pathophysiology. Earlier efforts relating to multimodality imaging of cancer have focused on the integration of anatomical and functional characteristics, such as PET-CT and single-photon emission CT (SPECT-CT), whereas more-recent advances and applications have involved the integration of multiple quantitative, functional measurements (for example, multiple PET tracers, varied MRI contrast mechanisms, and PET-MRI), thereby providing a more-comprehensive characterization of the tumour phenotype. The enormous amount of complementary quantitative data generated by such studies is beginning to offer unique insights into opportunities to optimize care for individual patients. Although important technical optimization and improved biological interpretation of multimodality imaging findings are needed, this approach can already be applied informatively in clinical trials of cancer therapeutics using existing tools. These concepts are discussed herein.

A review of technical aspects of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in human brain tumors

In the last few years, several imaging methods, such as magnetic resonance imaging (MRI) and computed tomography, have been used to investigate the degree of blood-brain barrier (BBB) permeability in patients with neurological diseases including multiple sclerosis, ischemic stroke, and brain tumors. One promising MRI method for assessing the BBB permeability of patients with neurological diseases in vivo is T1-weighted dynamic contrast-enhanced (DCE)-MRI. Here we review the technical issues involved in DCE-MRI in the study of human brain tumors. In the first part of this paper, theoretical models for the DCE-MRI analysis will be described, including the Toft-Kety models, the adiabatic approximation to the tissue homogeneity model and the two-compartment exchange model. These models can be used to estimate important kinetic parameters related to BBB permeability. In the second part of this paper, details of the data acquisition, issues related to the arterial input function, and procedures for DCE-MRI image analysis are illustrated.

[PET-MR in patients with glioblastoma multiforme]

Glioblastoma multiforme (GBM) is the most common and most aggressive primary tumor of the brain. In recent years newer therapeutic approaches have been developed. To allow for an optimized treatment planning it is important to precisely delineate necrotic tissue, edema and vital tumor tissue and to identify the most aggressive parts of the GBM. The magnetic resonance (MR) portion of an MR-positron emission tomography (PET) examination in patients with GBM should consist of both structural and functional sequences including diffusion-weighted and perfusion sequences. The use of (18)F-fluorodeoxyglucose ((18)F-FDG) is limited in patients with gliomas as glucose metabolism is already physiologically high in parts of the brain but (18)F-FDG is nevertheless a commonly used radiopharmaceutical for neuro-oncological questions. (18)F-fluorothymidine reflects the cellular activity of thymidine kinase 1 and correlates with the expression of KI-67 as an index of mitotic activity. The nitroimidazole derivatives (18)F-fluoromisonidazole and (18)F-fluoroazomycin arabinoside ((18)F-FAZA) allow the detection of hypoxic areas within the tumor. In recent years amino acid tracers, such as (18)F-fluoroethyltyrosine are increasingly being used in the diagnosis of gliomas. The simultaneous PET-MR image acquisition allows new approaches, e.g. motion correction by the simultaneous acquisition of MR data with a high temporal resolution and an improved quantification of the PET signal by integrating the results of functional MR sequences. Moreover, the simultaneous acquisition of these two time-consuming methods leads to reduced imaging times for this, often severely ill patient group.

DCE-MRI in hepatocellular carcinoma-clinical and therapeutic image biomarker

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables tumor vascular physiology to be assessed. Within the tumor tissue, contrast agents (gadolinium chelates) extravasate from intravascular into the extravascular extracellular space (EES), which results in a signal increase on T1-weighted MRI. The rate of contrast agents extravasation to EES in the tumor tissue is determined by vessel leakiness and blood flow. Thus, the signal measured on DCE-MRI represents a combination of permeability and perfusion. The semi-quantitative analysis is based on the calculation of heuristic parameters that can be extracted from signal intensity-time curves. These enhancing curves can also be deconvoluted by mathematical modeling to extract quantitative parameters that may reflect tumor perfusion, vascular volume, vessel permeability and angiogenesis. Because hepatocellular carcinoma (HCC) is a hypervascular tumor, many emerging therapies focused on the inhibition of angiogenesis. DCE-MRI combined with a pharmacokinetic model allows us to produce highly reproducible and reliable parametric maps of quantitative parameters in HCC. Successful therapies change quantitative parameters of DCE-MRI, which may be used as early indicators of tumor response to anti-angiogenesis agents that modulate tumor vasculature. In the setting of clinical trials, DCE-MRI may provide relevant clinical information on the pharmacodynamic and biologic effects of novel drugs, monitor treatment response and predict survival outcome in HCC patients.

Flip angle-optimized fast dynamic T1 mapping with a 3D gradient echo sequence

PURPOSE

To analyze the flip angle dependence and to optimize the statistical precision of a fast three-dimensional (3D) T1 mapping technique based on the variable flip angle (VFA) method. The proposed single flip angle (1FA) approach acquires only a single 3D spoiled gradient echo data set for each time point of the dynamical series in combination with a longer baseline measurement.

THEORY AND METHODS

The optimal flip angle for the dynamic series can be calculated as αdyn,opt  = arccos[(2E1  - 1)/(2 - E1 )] (with E1  = exp(-TR /T1 )) by minimizing the statistical error of T1 . T1 maps of a liquid phantom with step-wise increasing concentrations of contrast agent were measured using a saturation recovery (SR) and a VFA/1FA technique with 11 flip angles. The standard deviation of the parameter maps was defined as statistical error of the 1FA measurement.

RESULTS

The measured statistical error of the 1FA technique as a function of αdyn agrees with the derived theoretical curve. The optimal flip angle increases from about 5° for T1  = 2629 ms to 30° for T1  = 137 ms. The relative deviation between 1FA and SR measurements varies between -2.9 % and +10.3 %. Measurements in vivo confirm the expression for the optimal flip angle.

CONCLUSION

The proposed flip angle-optimized 1FA technique optimizes the precision of T1 values in dynamic phantom measurements.

Image registration for quantitative parametric response mapping of cancer treatment response

Imaging biomarkers capable of early quantification of tumor response to therapy would provide an opportunity to individualize patient care. Image registration of longitudinal scans provides a method of detecting treatment associated changes within heterogeneous tumors by monitoring alterations in the quantitative value of individual voxels over time, which is unattainable by traditional volumetric-based histogram methods. The concepts involved in the use of image registration for tracking and quantifying breast cancer treatment response using parametric response mapping (PRM), a voxel-based analysis of diffusion-weighted magnetic resonance imaging (DW-MRI) scans, are presented. Application of PRM to breast tumor response detection is described, wherein robust registration solutions for tracking small changes in water diffusivity in breast tumors during therapy are required. Methodologies that employ simulations are presented for measuring expected statistical accuracy of PRM for response assessment. Test-retest clinical scans are used to yield estimates of system noise to indicate significant changes in voxel-based changes in water diffusivity. Overall, registration-based PRM image analysis provides significant opportunities for voxel-based image analysis to provide the required accuracy for early assessment of response to treatment in breast cancer patients receiving neoadjuvant chemotherapy.

Towards whole-body fluorescence imaging in humans

Dynamic near-infrared fluorescence (DNIF) whole-body imaging of small animals has become a popular tool in experimental biomedical research. In humans, however, the field of view has been limited to body parts, such as rheumatoid hands, diabetic feet or sentinel lymph nodes. Here we present a new whole-body DNIF-system suitable for adult subjects. We explored whether this system (i) allows dynamic whole-body fluorescence imaging and (ii) can detect modulations in skin perfusion. The non-specific fluorescent probe indocyanine green (ICG) was injected intravenously into two subjects, and fluorescence images were obtained at 5 Hz. The in- and out-flow kinetics of ICG have been shown to correlate with tissue perfusion. To validate the system, skin perfusion was modulated by warming and cooling distinct areas on the chest and the abdomen. Movies of fluorescence images show a bolus passage first in the face, then in the chest, abdomen and finally in the periphery (~10, 15, 20 and 30 seconds, respectively). When skin perfusion is augmented by warming, bolus arrives about 5 seconds earlier than when the skin is cooled and perfusion decreased. Calculating bolus arrival times and spatial fitting of basis time courses extracted from different regions of interest allowed a mapping of local differences in subcutaneous skin perfusion. This experiment is the first to demonstrate the feasibility of whole-body dynamic fluorescence imaging in humans. Since the whole-body approach demonstrates sensitivity to circumscribed alterations in skinperfusion, it may be used to target autonomous changes in polyneuropathy and to screen for peripheral vascular diseases.

Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues

Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.