Cell wall polysaccharides from Gelidium species: physico-chemical studies using MRI techniques

Magnetic resonance imaging (MRI) has already been successively used to investigate polysaccharide matrices. In particular, MRI at microscopic resolution (MR microscopy) is now one of the most powerful techniques for studying the physical properties of natural hydrogels. To contribute to a better understanding of the correlation between chemical and physical properties of agar gels, we report here the measurement of the water magnetic parameters for agar gels extracted from different species of Gelidium: T1 and T2 relaxation times, magnetisation transfer (Ms /M0) and diffusion (D) were measured to evaluate their use for studying the gel characteristics. MR microscopic images were acquired at 7.05 Tesla using various pulse sequences. The results obtained confirmed the possibility to use quantitative MRI for the characterisation of physical parameters correlated with the type of agar chemical structure. In particular, T2 data obtained for gels at different concentrations indicate that this magnetic parameter is very sensitive to the agar concentration and hence particularly useful for the gel strength determination. This revised version was published online in June 2006 with corrections to the Cover Date.     

PET/CT Assessment of Response to Therapy: Tumor Change Measurement,Truth Data,and Error

We describe methods and issues that are relevant to the measurement of change in tumor uptake of ¹⁸F-fluorodeoxyglucose (FDG) or other radiotracers, as measured from positron emission tomography/computed tomography (PET/CT) images, and how this would relate to the establishment of PET/CT tumor imaging as a biomarker of patient response to therapy. The primary focus is on the uptake of FDG by lung tumors, but the approach can be applied to diseases other than lung cancer and to tracers other than FDG. The first issue addressed is the sources of bias and variance in the measurement of tumor uptake of FDG, and where there are still gaps in our knowledge. These are discussed in the context of measurement variation and how these would relate to the early detection of response to therapy. Some of the research efforts currently underway to identify the magnitude of some of these sources of error are described. In addition, we describe resources for these investigations that are being made available through the Reference Image Database for the Evaluation of Response project. Measures derived from PET image data that might be predictive of patient response as well as the additional issues that each of these metrics may encounter are described briefly. The relationship between individual patient response to therapy and utility for multicenter trials is discussed. We conclude with a discussion of moving from assessing measurement variation to the steps necessary to establish the efficacy of PET/CT imaging as a biomarker for response.     

Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging

Many modalities of magnetic resonance imaging (MRI) have been confirmed to be of great diagnostic value in glioma grading. Contrast enhanced T1-weighted imaging allows the recognition of blood-brain barrier breakdown. Perfusion weighted imaging and MR spectroscopic imaging enable the quantitative measurement of perfusion parameters and metabolic alterations respectively. These modalities can potentially improve the grading process in glioma if combined properly. In this study, Bayesian Network, which is a powerful and flexible method for probabilistic analysis under uncertainty, is used to combine features extracted from contrast enhanced T1-weighted imaging, perfusion weighted imaging and MR spectroscopic imaging. The networks were constructed using K2 algorithm along with manual determination and distribution parameters learned using maximum likelihood estimation. The grading performance was evaluated in a leave-one-out analysis, achieving an overall grading accuracy of 92.86% and an area under the curve of 0.9577 in the receiver operating characteristic analysis given all available features observed in the total 56 patients. Results and discussions show that Bayesian Network is promising in combining features from multiple modalities of MRI for improved grading performance.     

Diffusion Magnetic Resonance Imaging: An Imaging Treatment Response Biomarker to Chemoradiotherapy in a Mouse Model of Squamous Cell Cancer of the Head and Neck

For the treatment of squamous cell cancer of the head and neck (SCCHN), the assessment of treatment response is traditionally accomplished by volumetric measurements and has been suggested to be prognostic for an eventual response to treatment. An early evaluation response during the course of radiation therapy could provide an opportunity to tailor treatment to individual patients. Diffusion magnetic resonance imaging (MRI) allows for the quantification of tissue water diffusion values, thus treatment-induced loss of tumor cells will result in the increase in water mobility at the microscopic level, which can be detected as an increase in tumor diffusion values before any volumetric changes occur. We evaluated the use of diffusion MRI as an imaging biomarker of treatment response in an orthotopic mouse model of SCCHN. Mice with murine squamous cells expressing the yeast transgene cytosine deaminase were treated with 5-fluorocytosine (5FC), ionizing radiation, and combined therapy and were compared with control animals both during and after treatment for changes in tumor volumes, diffusion values, and survival. Radiation therapy had minimal effect on volumetric growth rate, diffusion, or survival. Although 5FC and combination treatment resulted in similar reductions in tumor volumes, the combination treatment elicited a much greater increase in tumor diffusion values, which correlated with improved survival. Thus, diffusion MRI as an imaging biomarker has a potential for early evaluation of the response to chemoradiation treatment in SCCHN.     

Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive

The Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate theminto clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation.     

Computed Tomography Assessment of Response to Therapy: Tumor Volume Change Measurement,Truth Data,and Error

RATIONALE AND OBJECTIVES: This article describes issues and methods that are specific to the measurement of change in tumor volume as measured from computed tomographic (CT) images and how these would relate to the establishment of CT tumor volumetrics as a biomarker of patient response to therapy. The primary focus is on the measurement of lung tumors, but the approach should be generalizable to other anatomic regions. MATERIALS AND METHODS: The first issues addressed are the various sources of bias and variance in the measurement of tumor volumes, which are discussed in the context of measurement variation and its impact on the early detection of response to therapy. RESULTS AND RESOURCES: Research that seeks to identify the magnitude of some of these sources of error is ongoing, and several of these efforts are described herein. In addition, several resources for these investigations are being made available through the National Institutes of Health-funded Reference Image Database to Evaluate Response to therapy in cancer project, and these are described as well. Other measures derived from CT image data that might be predictive of patient response are described briefly, as well as the additional issues that each of these metrics may encounter in real-life applications. CONCLUSIONS: The article concludes with a brief discussion of moving from the assessment of measurement variation to the steps necessary to establish the efficacy of a metric as a biomarker for response.     

Multiparametric Characterization of Grade 2 Glioma Subtypes Using Magnetic Resonance Spectroscopic,Perfusion, and Diffusion Imaging

BACKGROUND AND PURPOSE: The purpose of this study was to derive quantitative parameters from magnetic resonance (MR) spectroscopic, perfusion, and diffusion imaging of grade 2 gliomas according to the World Health Organization and to investigate how these multiple imaging modalities can contribute to evaluating their histologic subtypes and spatial characteristics. MATERIALS AND METHODS: MR spectroscopic, perfusion, and diffusion images from 56 patients with newly diagnosed grade 2 glioma (24 oligodendrogliomas, 18 astrocytomas, and 14 oligoastrocytomas) were retrospectively studied. Metabolite intensities, relative cerebral blood volume (rCBV), and apparent diffusion coefficient (ADC) were statistically evaluated. RESULTS: The 75th percentile rCBV and median ADC were significantly different between oligodendrogliomas and astrocytomas (P < .0001) and between oligodendrogliomas and oligoastrocytomas (P < .001). Logistic regression analysis identified both 75th percentile rCBV and median ADC as significant variables in the differentiation of oligodendrogliomas from astrocytomas and oligoastrocytomas. Group differences in metabolite intensities were not significant, but there was a much larger variation in the volumes and maximum values of metabolic abnormalities for patients with oligodendroglioma compared with the other tumor subtypes. CONCLUSIONS: Perfusion and diffusion imaging provide quantitative MR parameters that can help to differentiate grade 2 oligodendrogliomas from grade 2 astrocytomas and oligoastrocytomas. The large variations in the magnitude and spatial extent of the metabolic lesions between patients and the fact that their values are not correlated with the other imaging parameters indicate that MR spectroscopic imaging may provide complementary information that is helpful in targeting therapy, evaluating residual disease, and assessing response to therapy.     

A methodology for registration of a histological slide and in vivo MRI volume based on optimizing mutual information

We present a method for registering histology and in vivo imaging that requires minimal microtoming and is automatic following the user's initialization. In this demonstration, we register a single hematoxylin-and-eosin-stained histological slide of a coronal section of a rat brain harboring a 9L gliosarcoma with an in vivo 7T MR image volume of the same brain. Because the spatial resolution of the in vivo MRI is limited, we add the step of obtaining a high spatial resolution, ex vivo MRI in situ for intermediate registration. The approach taken was to maximize mutual information in order to optimize the registration between all pairings of image data whether the sources are MRI, tissue block photograph, or stained sample photograph. The warping interpolant used was thin plate splines with the appropriate basis function for either 2-D or 3-D applications. All registrations were implemented by user initialization of the approximate pose between the two data sets, followed by automatic optimization based on maximizing mutual information. Only the higher quality anatomical images were used in the registration process; however, the spatial transformation was directly applied to a quantitative diffusion image. Quantitative diffusion maps from the registered location appeared highly correlated with the H&E slide. Overall, this approach provides a robust method for coregistration of in vivo images with histological sections and will have broad applications in the field of functional and molecular imaging.     

Advanced diffusion MRI fiber tracking in neurosurgical and neurodegenerative disorders and neuroanatomical studies: A review

Diffusion MRI enabled in vivo microstructural imaging of the fiber tracts in the brain resulting in its application in a wide range of settings, including in neurological and neurosurgical disorders. Conventional approaches such as diffusion tensor imaging (DTI) have been shown to have limited applications due to the crossing fiber problem and the susceptibility of their quantitative indices to partial volume effects. To overcome these limitations, the recent focus has shifted to the advanced acquisition methods and their related analytical approaches. Advanced white matter imaging techniques provide superior qualitative data in terms of demonstration of multiple crossing fibers in their spatial orientation in a three dimensional manner in the brain. In this review paper, we discuss the advancements in diffusion MRI and introduce their roles. Using examples, we demonstrate the role of advanced diffusion MRI-based fiber tracking in neuroanatomical studies. Results from its preliminary application in the evaluation of intracranial space occupying lesions, including with respect to future directions for prognostication, are also presented. Building upon the previous DTI studies assessing white matter disease in Huntington's disease and Amyotrophic lateral sclerosis; we also discuss approaches which have led to encouraging preliminary results towards developing an imaging biomarker for these conditions.     

Hyperpolarized MRI,functional MRI,MR spectroscopy and CEST to provide metabolic information in vivo

Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where fast, simple, and reliable measurement and diagnosis are key. Recent advances in functional MRI and chemical exchange saturation transfer (CEST) MRI allow the use of water imaging to study oxygen metabolism and tissue metabolite levels. These, together with the use of novel data analysis approaches such as machine learning for all of these metabolic MR approaches, are increasing the likelihood of their clinical translation.     

Molecular magnetic resonance imaging with targeted contrast agents

Magnetic resonance imaging (MRI) produces high-resolution three-dimensional maps delineating morphological features of the specimen. Differential contrast in soft tissues depends on endogenous differences in water content, relaxation times, and/or diffusion characteristics of the tissue of interest. The specificity of MRI can be further increased by exogenous contrast agents (CA) such as gadolinium chelates, which have been successfully used for imaging of hemodynamic parameters including blood perfusion and vascular permeability. Development of targeted MR CA directed to specific molecular entities could dramatically expand the range of MR applications by combining the noninvasiveness and high spatial resolution of MRI with specific localization of molecular targets. However, due to the intrinsically low sensitivity of MRI (in comparison with nuclear imaging), high local concentrations of the CA at the target site are required to generate detectable MR contrast. To meet these requirements, the MR targeted CA should recognize targeted cells with high affinity and specificity. They should also be characterized by high relaxivity, which for a wide variety of CA depends on the number of contrast-generating groups per single molecule of the agent. We will review different designs and applications of targeted MR CA and will discuss feasibility of these approaches for in vivo MRI.     

Feasibility of using ultra-high field (7 T) MRI for clinical surgical targeting

The advantages of ultra-high magnetic field (7 Tesla) MRI for basic science research and neuroscience applications have proven invaluable. Structural and functional MR images of the human brain acquired at 7 T exhibit rich information content with potential utility for clinical applications. However, (1) substantial increases in susceptibility artifacts, and (2) geometrical distortions at 7 T would be detrimental for stereotactic surgeries such as deep brain stimulation (DBS), which typically use 1.5 T images for surgical planning. Here, we explore whether these issues can be addressed, making feasible the use of 7 T MRI to guide surgical planning. Twelve patients with Parkinson's disease, candidates for DBS, were scanned on a standard clinical 1.5 T MRI and a 7 T MRI scanner. Qualitative and quantitative assessments of global and regional distortion were evaluated based on anatomical landmarks and transformation matrix values. Our analyses show that distances between identical landmarks on 1.5 T vs. 7 T, in the mid-brain region, were less than one voxel, indicating a successful co-registration between the 1.5 T and 7 T images under these specific imaging parameter sets. On regional analysis, the central part of the brain showed minimal distortion, while inferior and frontal areas exhibited larger distortion due to proximity to air-filled cavities. We conclude that 7 T MR images of the central brain regions have comparable distortions to that observed on a 1.5 T MRI, and that clinical applications targeting structures such as the STN, are feasible with information-rich 7 T imaging.     

TEP/IRM hybride en neuro-imagerie

The hybrid Positron Emission Tomography/Magnetic Resonance Imaging (PET/MRI) is a newly available imaging modality combining the molecular and metabolic PET information with the morphological and functional data provided by MRI. Integrated PET/MRI tomographs were conceived in analogy to the current PET/Computed Tomography (PET/CT) technology, with specific properties linked to the intrinsic differences of MRI and CT imaging. In the field of neuro-imaging, in particular, MRI provides a larger panel of information, as compared with CT, and is already systematically fused and used as a support for PET images for diagnostic and research purposes. We summarize here our current experience with the first integrated PET/MRI tomograph installed in Switzerland, concerning specifically three clinical applications: brain tumors characterization, the diagnosis of neurodegenerative dementias and the presurgical evaluation of pharmaco-resistant epilepsy. With this sequential tomograph, we could combine the full range of diagnostic MR sequences (including diffusion tensor imaging, tractography, spectroscopy, functional MR) with PET imaging of brain glucose metabolism (by ¹⁸F-Fluorodeoxyglucose–FDG) and of amino acid transport (by ¹⁸F-Fluoroethyltyrosine–FET). We also summarize the main results obtained in neuro-imaging by the different groups working with these new hybrid tomographs. These data show that PET/MRI, acquired in a single imaging session, may represent the modality of choice for neuro-imaging.     

New concepts in characterization of ischemically injured myocardium by MRI

New concepts regarding the assessment of ischemic myocardial injuries have been addressed in this Minireview using magnetic resonance imaging (MRI). MRI, with its different techniques, brings not only anatomic, but also physiologic, information on ischemic heart disease. It has the ability to measure identical parameters in preclinical and clinical studies. MRI techniques provide the ideal package for repeated and noninvasive assessment of myocardial anatomy, viability, perfusion, and function. MR contrast agents can be applied in a variety of ways to improve MRI sensitivity for detecting and assessing ischemically injured myocardium. With MR contrast agents protocol, it becomes possible to identify ischemic, acutely infarcted, and peri-infarcted myocardium in occlusive and reperfused infarctions. Necrosis specific and nonspecific extracellular contrast-enhanced MRI has been used to assess myocardial viability. Contrast-enhanced perfusion MRI can explore the disturbances in large (angiography) and small coronary arteries (myocardial perfusion) as the underlying cause of myocardial dysfunction. Perfusion MRI has been used to measure myocardial perfusion (ml/min/g) and to demonstrate the difference in transmural myocardial blood flow. Information on no-reflow phenomenon is derived from dynamic changes in regional signal intensity after bolus injection of MR contrast agents. Another development is the near future availability of blood pool MR contrast agents. These agents are able to assess microvascular permeability and integrity and are advantageous in MR angiography (MRA) due to their persistence in the blood. Noncontrast-enhanced MRI such as cine MRI at rest/stress, sodium MRI, and MR spectroscopy also have the potential to noninvasively assess myocardial viability in patients. Futuristic applications for MRI in the heart will focus on identifying coronary artery disease at an early stage and the beneficial effects of new therapeutic agents such as intra-arterial gene therapy. MR techniques will have great future in the drug discovery process and in testing the effects of drugs on myocardial biochemistry, physiology, and morphology. Molecular imaging is going to bloom in this decade.     

Brain Magnetic Resonance in the Diagnostic Evaluation of Mitochondrial Encephalopathies

Brain MR imaging techniques are important ancillary tests in the diagnosis of a suspected mitochondrial encephalopathy since they provide details on brain structural and metabolic abnormalities. This is particularly true in children where non-specific neurologic symptoms are common, biochemical findings can be marginal and genetic defects may be not discovered. MR imaging modalities include conventional, or structural, imaging (MRI) and functional, or ultrastructural, imaging (spectroscopy, MRS; diffusion, DWI-ADC; perfusion, DSCI––ASL). Among them MRI and MRS are the main tools for diagnosis and work up of MD, and this review will focus mainly on them. The MRI findings of MD are very heterogeneous, as they depend on the metabolic brain defects, age of the patient, stage and severity of the disease. No correlation has been found between genetic defects and neuroimaging picture; however, some relationships between MR findings and clinical phenotypes may be identified. Different combinations of MRI signal abnormalities are often encountered but the most common findings may be summarized into three main MR patterns: (i) non-specific; (ii) specific; (iii) leukodystrophic-like. Regarding the functional MR techniques, only proton MRS plays an important role in demonstrating an oxidative metabolism impairment in the brain since it can show the accumulation of lactate, present as a doublet peak at 1.33 ppm. Assessment of lactate should be always performed on brain tissue and on the ventricular cerebral spinal fluid. As for MRI, metabolic MRS abnormalities can be of different types, and two distinct patterns can be recognized: non-specific and specific. The specific metabolic profiles, although not frequent to find, are highly pathognomonic of MD. The un-specific metabolic profiles add value to structural images in allowing to define the lesion load and to monitor the response to therapy trials.     

Magnetic Resonance Imaging Assessment of Effective Ablated Volume following High Intensity Focused Ultrasound

Under magnetic resonance (MR) guidance, high intensity focused ultrasound (HIFU) is capable of precise and accurate delivery of thermal dose to tissues. Given the excellent soft tissue imaging capabilities of MRI, but the lack of data on the correlation of MRI findings to histology following HIFU, we sought to examine tumor response to HIFU ablation to determine whether there was a correlation between histological findings and common MR imaging protocols in the assessment of the extent of thermal damage. Female FVB mice (n = 34), bearing bilateral neu deletion tumors, were unilaterally insonated under MR guidance, with the contralateral tumor as a control. Between one and five spots (focal size 0.5 × 0.5 × 2.5 mm³) were insonated per tumor with each spot receiving approximately 74.2 J of acoustic energy over a period of 7 seconds. Animals were then imaged on a 7T MR scanner with several protocols. T1 weighted images (with and without gadolinium contrast) were collected in addition to a series of T2 weighted and diffusion weighted images (for later reconstruction into T2 and apparent diffusion coefficient maps), immediately following ablation and at 6, 24, and 48 hours post treatment. Animals were sacrificed at each time point and both insonated/treated and contralateral tumors removed and stained for NADH-diaphorase, caspase 3, or with hematoxylin and eosin (H&E). We found the area of non-enhancement on contrast enhanced T1 weighted imaging immediately post ablation correlated with the region of tissue receiving a thermal dose CEM43 ≥ 240 min. Moreover, while both tumor T2 and apparent diffusion coefficient values changed from pre-ablation values, contrast enhanced T1 weighted images appeared to be more senstive to changes in tissue viability following HIFU ablation.     

Anatomical and functional assessment of brown adipose tissue by magnetic resonance imaging

Brown adipose tissue (BAT) is the primary tissue responsible for nonshivering thermogenesis in mammals. The amount of BAT and its level of activation help regulate the utilization of excessive calories for thermogenesis as opposed to storage in white adipose tissue (WAT) which would lead to weight gain. Over the past several years, BAT activity in vivo has been primarily assessed by positron emission tomography-computed tomography (PET-CT) scan using 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG) to measure glucose utilization associated with BAT mitochondrial respiration. In this study, we demonstrate the feasibility of mapping and estimating BAT volume and metabolic function in vivo in rats at a 9.4T magnetic resonance imaging (MRI) scanner using sequences available from clinical MR scanners. Based on the morphological characteristics of BAT, we measured the volume distribution of BAT with MRI sequences that have strong fat-water contrast. We also investigated BAT volume by utilizing spin-echo MRI sequences. The in vivo MRI-estimated BAT volumes were correlated with direct measurement of BAT mass from dissected samples. Using MRI, we also were able to map hemodynamic responses to changes in BAT metabolism induced pharmacologically by β3-adrenergic receptor agonist, CL-316,243 and compare this to BAT activity in response to CL-316,243 assessed by PET 18F-FDG. In conclusion, we demonstrate the feasibility of measuring BAT volume and function in vivo using routine MRI sequences. The MRI measurement of BAT volume is consistent with quantitative measurement of the tissue ex vivo.     

Can we use diffusion MRI as a bio-marker of neurodegenerative processes?

Magnetic resonance imaging (MRI) is an imaging technique with a rapidly expanding application range. This methodology, which relies on quantum physics and substance magnetic properties, is now being routinely used in the clinics and medical research. With the advent of measuring functional brain activity with MRI (functional MRI), this methodology has reached a larger section of the neuroscience community (e.g. psychologists, neurobiologists). In the past, the use of MRI as a biomarker or as an assay to probe tissue pathophysiological condition was limited. However, with the new applications of MRI: molecular imaging, contrast-enhanced imaging and diffusion imaging, MRI is turning into a powerful tool for in vivo characterization of tissue pathophysiology. This review focuses on the diffusion MRI. Although it only measures the averaged Brownian translational motion of water molecules, using different analysis schemes, one can extract a wide range of quantitative indices that represent tissue morphology and compartmentalization. Statistical and visualization routines help to relate these indices to biologically relevant measures such as cell density, water content and size distribution. The aim of this review is to shed light on the potential of this methodology to be used in biological research. To that end, this review is intended for the non-MRI specialists who wish to pursue biological research with this methodology. We will overview the current applications of diffusion MRI and its relation to cellular biology of brain tissue.     

Current issues and perspectives in small rodent magnetic resonance imaging using clinical MRI scanners

Small rodents such as mice and rats are frequently used in animal experiments for several reasons. In the past, animal experiments were frequently associated with invasive methods and groups of animals had to be killed to perform longitudinal studies. Today's modern imaging techniques such as magnetic resonance imaging (MRI) allow non-invasive longitudinal monitoring of multiple parameters. Although only a few institutions have access to dedicated small animal MR scanners, most institutions carrying out animal experiments have access to clinical MR scanners. Technological advances and the increasing field strength of clinical scanners make MRI a broadly available and viable technique in preclinical in vivo research. This review provides an overview of current concepts, limitations, and recent studies dealing with small animal imaging using clinical MR scanners.     

Uninterpretable Dynamic Susceptibility Contrast-Enhanced Perfusion MR Images in Patients with Post-Treatment Glioblastomas: Cross-Validation of Alternative Imaging Options

Purpose

The purpose of this study was to evaluate the accuracy of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) perfusion MR imaging for distinguishing tumor recurrence from post-treatment effect as alternatives to dynamic-susceptibility contrast-enhanced (DSC) perfusion MR imaging when the DSC image is uninterpretable.

Materials and Methods

This retrospective study was approved by our institutional review board. Seventy one post-treatment glioblastoma patients who showed enlarged contrast-enhancing lesions on follow-up MR images after concurrent chemoradiotherapy and uninterpretable DSC images for corresponding enhancing lesions, underwent additional DWI and DCE MR imaging. The primary outcome was the frequency of interpretable DWI and DCE MR cases in these 71 patients. The secondary outcome was the area under the receiver operating characteristic curve (AUC) of DWI and DCE imaging parameters for distinguishing tumor recurrence from post-treatment effect in selected patients with interpretable DWI and DCE images. The imaging parameters were quantified as 10% cumulative histogram cutoff of apparent diffusion coefficient (ADC10) and 90% cumulative histogram cutoff of initial area under the time signal intensity curve (IAUC90). The AUCs were cross-validated by using leave-one-out method.

Results

Of the 71 patients, the uninterpretable DSC images were associated with treatment-related hemorrhage within the corresponding enhancing lesions (n = 54, 76.1%) and a near skull base location (n = 17, 23.9%). The frequencies of interpretable DWI and DCE image were 51 (71.8%) and 59 (83.1%) of the 71 cases with uninterpretable DSC images, respectively. Of the 45 selected patients with interpretable DWI and DCE images, the combination of DWI with DCE imaging showed a superior diagnostic performance than DWI or DCE imaging alone for differentiating tumor recurrence from post-treatment effect (cross-validated AUC: 0.78 versus 0.55 and 0.73 for reader 1; cross-validated AUC: 0.78 versus 0.53 and 0.75 for reader 2, respectively). Cross-validated accuracy of the single and combined imaging parameters also showed the highest for the combination of DWI with DCE MR imaging (72.9% for reader 1; 72.5% for reader 2) and the lowest for DWI alone (54.0% for reader 1; 56.4% for reader 2). Inter-reader agreement for DCE imaging was higher than that for DWI (intraclass correlation coefficient: 0.95 versus 0.87).

Conclusion

DCE MR imaging could be a superior and more reproducible imaging biomarker than DWI for differentiating tumor recurrence from post-treatment effect in patients with post-treatment glioblastoma when DSC MR images are not interpretable.