High Temporal Resolution Parametric MRI Monitoring of the Initial Ischemia/Reperfusion Phase in Experimental Acute Kidney Injury

Ischemia/reperfusion (I/R) injury, a consequence of kidney hypoperfusion or temporary interruption of blood flow is a common cause of acute kidney injury (AKI). There is an unmet need to better understand the mechanisms operative during the initial phase of ischemic AKI. Non-invasive in vivo parametric magnetic resonance imaging (MRI) may elucidate spatio-temporal pathophysiological changes in the kidney by monitoring the MR relaxation parameters T₂* and T₂, which are known to be sensitive to blood oxygenation. The aim of our study was to establish the technical feasibility of fast continuous T₂*/T₂ mapping throughout renal I/R. MRI was combined with a remotely controlled I/R model and a segmentation model based semi-automated quantitative analysis. This technique enabled the detailed assessment of in vivo changes in all kidney regions during ischemia and early reperfusion. Significant changes in T₂* and T₂ were observed shortly after induction of renal ischemia and during the initial reperfusion phase. Our study demonstrated for the first time that continuous and high temporal resolution parametric MRI is feasible for in-vivo monitoring and characterization of I/R induced AKI in rats. This technique may help in the identification of the timeline of key events responsible for development of renal damage in hypoperfusion-induced AKI.     

Detection of eggs in the living white grub beetle Dasylepida ishigakiensis (Coleoptera: Scarabaeidae) by magnetic resonance imaging

The use of magnetic resonance imaging (MRI) as a tool for in vivo detection of eggs in living Dasylepida ishigakiensis Niijima et Kinoshita, a major pest of sugarcane, was explored using females with an ovary at different developmental stages. MRI measurements of beetles were performed at 13 °C to avoid motion artifacts on the MR images. Spin–lattice relaxation time-weighted images allowed the observation of eggs at short acquisition times (2 min, 8 s). By comparing MR images with dissection data, criteria for determining mature eggs in MR images were a clear circular or ellipsoidal shape surrounded by a relatively bright rim and a size typically larger than 1.3 mm in the minor axis. Although small oocytes could not be detected, females with a developed or undeveloped ovary could be clearly distinguished based on MR images. The possibility of confusing the digestive tract as eggs in a female with a less developed ovary can be eliminated using a proton density weighted image.     

Visual Saliency Models for Text Detection in Real World

This paper evaluates the degree of saliency of texts in natural scenes using visual saliency models. A large scale scene image database with pixel level ground truth is created for this purpose. Using this scene image database and five state-of-the-art models, visual saliency maps that represent the degree of saliency of the objects are calculated. The receiver operating characteristic curve is employed in order to evaluate the saliency of scene texts, which is calculated by visual saliency models. A visualization of the distribution of scene texts and non-texts in the space constructed by three kinds of saliency maps, which are calculated using Itti''s visual saliency model with intensity, color and orientation features, is given. This visualization of distribution indicates that text characters are more salient than their non-text neighbors, and can be captured from the background. Therefore, scene texts can be extracted from the scene images. With this in mind, a new visual saliency architecture, named hierarchical visual saliency model, is proposed. Hierarchical visual saliency model is based on Itti''s model and consists of two stages. In the first stage, Itti''s model is used to calculate the saliency map, and Otsu''s global thresholding algorithm is applied to extract the salient region that we are interested in. In the second stage, Itti''s model is applied to the salient region to calculate the final saliency map. An experimental evaluation demonstrates that the proposed model outperforms Itti''s model in terms of captured scene texts.     

White blood cell detection using saliency detection and CenterNet: A two-stage approach

White blood cell (WBC) detection plays a vital role in peripheral blood smear analysis. However, cell detection remains a challenging task due to multi-cell adhesion, different staining and imaging conditions. Owing to the powerful feature extraction capability of deep learning, object detection methods based on convolutional neural networks (CNNs) have been widely applied in medical image analysis. Nevertheless, the CNN training is time-consuming and inaccuracy, especially for large-scale blood smear images, where most of the images are background. To address the problem, we propose a two-stage approach that treats WBC detection as a small salient object detection task. In the first saliency detection stage, we use the Itti's visual attention model to locate the regions of interest (ROIs), based on the proposed adaptive center-surround difference (ACSD) operator. In the second WBC detection stage, the modified CenterNet model is performed on ROI sub-images to obtain a more accurate localization and classification result of each WBC. Experimental results showed that our method exceeds the performance of several existing methods on two different data sets, and achieves a state-of-the-art mAP of over 98.8%.     

High Dynamic Range Processing for Magnetic Resonance Imaging

Purpose

To minimize feature loss in T₁- and T₂-weighted MRI by merging multiple MR images acquired at different T_R and T_E to generate an image with increased dynamic range.

Materials and Methods

High Dynamic Range (HDR) processing techniques from the field of photography were applied to a series of acquired MR images. Specifically, a method to parameterize the algorithm for MRI data was developed and tested. T₁- and T₂-weighted images of a number of contrast agent phantoms and a live mouse were acquired with varying T_R and T_E parameters. The images were computationally merged to produce HDR-MR images. All acquisitions were performed on a 7.05 T Bruker PharmaScan with a multi-echo spin echo pulse sequence.

Results

HDR-MRI delineated bright and dark features that were either saturated or indistinguishable from background in standard T₁- and T₂-weighted MRI. The increased dynamic range preserved intensity gradation over a larger range of T₁ and T₂ in phantoms and revealed more anatomical features in vivo.

Conclusions

We have developed and tested a method to apply HDR processing to MR images. The increased dynamic range of HDR-MR images as compared to standard T₁- and T₂-weighted images minimizes feature loss caused by magnetization recovery or low SNR.     

Strongly Magnetic Iron Nanoparticles Improve the Diagnosis of Small Tumours in the Reticuloendothelial System by Magnetic Resonance Imaging

Despite advances in non-invasive medical imaging, accurate nodal staging of malignancy continues to rely on surgery. Superparamagnetic iron oxide nanoparticles (IONP) with lymphotropic qualities have shown some promise as contrast agents for MRI of the lymph nodes, but recent large-scale studies failed to show consistent detection of tumours below 5 mm. Herein we compare imaging of splenic and lymph node tissue using iron/iron oxide core/shell nanoparticles (Fe NP) that have superior magnetic qualities to IONP, to determine whether improved negative contrast in T₂-weighted MRI can enhance the diagnosis of small tumours in the reticuloendothelial system. To provide an in vivo pre-clinical model of human lymph node micrometastases, breast cancer cells were injected into the spleens of mice, providing localised areas of tumour growth. MR images of groups of tumour-bearing and sham-treated animals were generated using a 1.5 T imaging system and analysed by two independent, blinded radiologists. Fe NP improved the sensitivity and specificity of MRI when compared to IONP, enabling accurate detection of tumours as small as 1–3 mm. The use of Fe NP as contrast agents have the potential to improve the diagnostic accuracy of MRI in cancer patients, leading to more rapid and effective treatment.     

Characterization of Metabolic,Diffusion, and Perfusion Properties in GBM: Contrast-Enhancing versus Non-Enhancing Tumor

BACKGROUND: Although the contrast-enhancing (CE) lesion on T₁-weighted MR images is widely used as a surrogate for glioblastoma (GBM), there are also non-enhancing regions of infiltrative tumor within the T₂-weighted lesion, which elude radiologic detection. Because non-enhancing GBM (Enh?) challenges clinical patient management as latent disease, this study sought to characterize ex vivo metabolic profiles from Enh? and CE GBM (Enh+) samples, alongside histological and in vivo MR parameters, to assist in defining criteria for estimating total tumor burden. Methods: Fifty-six patients with newly diagnosed GBM received a multi-parametric pre-surgical MR examination. Targets for obtaining image-guided tissue samples were defined based on in vivo parameters that were suspicious for tumor. The actual location from where tissue samples were obtained was recorded, and half of each sample was analyzed for histopathology while the other half was scanned using HR-MAS spectroscopy. Results: The Enh+ and Enh? tumor samples demonstrated comparable mitotic activity, but also significant heterogeneity in microvascular morphology. Ex vivo spectroscopic parameters indicated similar levels of total choline and N-acetylaspartate between these contrast-based radiographic subtypes of GBM, and characteristic differences in the levels of myo-inositol, creatine/phosphocreatine, and phosphoethanolamine. Analysis of in vivo parameters at the sample locations were consistent with histological and ex vivo metabolic data. CONCLUSIONS: The similarity between ex vivo levels of choline and NAA, and between in vivo levels of choline, NAA and nADC in Enh+ and Enh? tumor, indicate that these parameters can be used in defining non-invasive metrics of total tumor burden for patients with GBM.     

Psychophysical tests of the hypothesis of a bottom-up saliency map in primary visual cortex

A unique vertical bar among horizontal bars is salient and pops out perceptually. Physiological data have suggested that mechanisms in the primary visual cortex (V1) contribute to the high saliency of such a unique basic feature, but indicated little regarding whether V1 plays an essential or peripheral role in input-driven or bottom-up saliency. Meanwhile, a biologically based V1 model has suggested that V1 mechanisms can also explain bottom-up saliencies beyond the pop-out of basic features, such as the low saliency of a unique conjunction feature such as a red vertical bar among red horizontal and green vertical bars, under the hypothesis that the bottom-up saliency at any location is signaled by the activity of the most active cell responding to it regardless of the cell's preferred features such as color and orientation. The model can account for phenomena such as the difficulties in conjunction feature search, asymmetries in visual search, and how background irregularities affect ease of search. In this paper, we report nontrivial predictions from the V1 saliency hypothesis, and their psychophysical tests and confirmations. The prediction that most clearly distinguishes the V1 saliency hypothesis from other models is that task-irrelevant features could interfere in visual search or segmentation tasks which rely significantly on bottom-up saliency. For instance, irrelevant colors can interfere in an orientation-based task, and the presence of horizontal and vertical bars can impair performance in a task based on oblique bars. Furthermore, properties of the intracortical interactions and neural selectivities in V1 predict specific emergent phenomena associated with visual grouping. Our findings support the idea that a bottom-up saliency map can be at a lower visual area than traditionally expected, with implications for top-down selection mechanisms.     

Saliency predicts change detection in pictures of natural scenes

It has been proposed that the visual system encodes the salience of objects in the visual field in an explicit two-dimensional map that guides visual selective attention. Experiments were conducted to determine whether salience measurements applied to regions of pictures of outdoor scenes could predict the detection of changes in those regions. To obtain a quantitative measure of change detection, observers located changes in pairs of colour pictures presented across an interstimulus interval (ISI). Salience measurements were then obtained from different observers for image change regions using three independent methods, and all were positively correlated with change detection. Factor analysis extracted a single saliency factor that accounted for 62% of the variance contained in the four measures. Finally, estimates of the magnitude of the image change in each picture pair were obtained, using nine separate visual filters representing low-level vision features (luminance, colour, spatial frequency, orientation, edge density). None of the feature outputs was significantly associated with change detection or saliency. On the other hand it was shown that high-level (structural) properties of the changed region were related to saliency and to change detection: objects were more salient than shadows and more detectable when changed.     

The Contributions of Image Content and Behavioral Relevancy to Overt Attention

During free-viewing of natural scenes, eye movements are guided by bottom-up factors inherent to the stimulus, as well as top-down factors inherent to the observer. The question of how these two different sources of information interact and contribute to fixation behavior has recently received a lot of attention. Here, a battery of 15 visual stimulus features was used to quantify the contribution of stimulus properties during free-viewing of 4 different categories of images (Natural, Urban, Fractal and Pink Noise). Behaviorally relevant information was estimated in the form of topographical interestingness maps by asking an independent set of subjects to click at image regions that they subjectively found most interesting. Using a Bayesian scheme, we computed saliency functions that described the probability of a given feature to be fixated. In the case of stimulus features, the precise shape of the saliency functions was strongly dependent upon image category and overall the saliency associated with these features was generally weak. When testing multiple features jointly, a linear additive integration model of individual saliencies performed satisfactorily. We found that the saliency associated with interesting locations was much higher than any low-level image feature and any pair-wise combination thereof. Furthermore, the low-level image features were found to be maximally salient at those locations that had already high interestingness ratings. Temporal analysis showed that regions with high interestingness ratings were fixated as early as the third fixation following stimulus onset. Paralleling these findings, fixation durations were found to be dependent mainly on interestingness ratings and to a lesser extent on the low-level image features. Our results suggest that both low- and high-level sources of information play a significant role during exploration of complex scenes with behaviorally relevant information being more effective compared to stimulus features.     

Synergistic enhancement of iron oxide nanoparticle and gadolinium for dual-contrast MRI

PurposeThe use of MR contrast agents allows accurate diagnosis by exerting an influence on the longitudinal (T₁) or transverse (T₂) relaxation time of the surrounding tissue. In this study, we combined the use of iron oxide (IO) particles and nonspecific extracellular gadolinium chelate (Gd) in order to further improve the sensitivity and specificity of lesion detection.ProceduresWith a 7-Tesla scanner, pre-contrasted, IO-enhanced and dual contrast agent enhanced MRIs were performed in phantom, normal animals, and animal models of lymph node tumor metastases and orthotopic brain tumor. For the dual-contrast (DC) MRI, we focused on the evaluation of T₂ weighted DC MRI with IO administered first, then followed by the injection of a bolus of gadolinium diethylenetriamine pentaacetic acid (Gd-DTPA).ResultsBased on the C/N ratios and MRI relaxometry, the synergistic effect of coordinated administration of Gd-DTPA and IO was observed and confirmed in phantom, normal liver and tumor models. At 30 min after administration of Feridex, Gd-DTPA further decreased T₂ relaxation in liver immediately after the injection. Additional administration of Gd-DTPA also immediately increased the signal contrast between tumor and brain parenchyma and maximized the C/N ratio to ?4.12 ± 0.71. Dual contrast MRI also enhanced the delineation of tumor borders and small lesions.ConclusionsDC-MRI will be helpful to improve diagnostic accuracy and decrease the threshold size for lesion detection.     

Facilitating tumor functional assessment by spatially relating 3D tumor histology and in vivo MRI: image registration approach

Background

Magnetic resonance imaging (MRI), together with histology, is widely used to diagnose and to monitor treatment in oncology. Spatial correspondence between these modalities provides information about the ability of MRI to characterize cancerous tissue. However, registration is complicated by deformations during pathological processing, and differences in scale and information content.

Methodology/Principal Findings

This study proposes a methodology for establishing an accurate 3D relation between histological sections and high resolution in vivo MRI tumor data. The key features of the methodology are: 1) standardized acquisition and processing, 2) use of an intermediate ex vivo MRI, 3) use of a reference cutting plane, 4) dense histological sampling, 5) elastic registration, and 6) use of complete 3D data sets. Five rat pancreatic tumors imaged by T2*-w MRI were used to evaluate the proposed methodology. The registration accuracy was assessed by root mean squared (RMS) distances between manually annotated landmark points in both modalities. After elastic registration the average RMS distance decreased from 1.4 to 0.7 mm. The intermediate ex vivo MRI and the reference cutting plane shared by all three 3D images (in vivo MRI, ex vivo MRI, and 3D histology data) were found to be crucial for the accurate co-registration between the 3D histological data set and in vivo MRI. The MR intensity in necrotic regions, as manually annotated in 3D histology, was significantly different from other histologically confirmed regions (i.e., viable and hemorrhagic). However, the viable and the hemorrhagic regions showed a large overlap in T2^*-w MRI signal intensity.

Conclusions

The established 3D correspondence between tumor histology and in vivo MRI enables extraction of MRI characteristics for histologically confirmed regions. The proposed methodology allows the creation of a tumor database of spatially registered multi-spectral MR images and multi-stained 3D histology.     

The effectiveness of gadolinium MRI to improve target delineation for radiotherapy in hepatocellular carcinoma: A comparative study of rigid image registration techniques

To achieve consistent target delineation in radiotherapy for hepatocellular carcinoma (HCC), image registration between simulation CT and diagnostic MRI was explored.Twenty patients with advanced HCC were included. The median interval between MRI and CT was 11 days. CT was obtained with shallow free breathing and MRI at exhale phase. On each CT and MRI, the liver and the gross target volume (GTV) were drawn. A rigid image registration was taken according to point information of vascular bifurcation (Method[A]) and pixel information of volume of interest only including the periphery of the liver (Method[B]) and manually drawn liver (Method[C]). In nine cases with an indefinite GTV on CT, a virtual sphere was generated at the epicenter of the GTV. The GTV from CT (V_GTV[CT]) and MRI (V_GTV[MR]) and the expanded GTV from MRI (V_+GTV[MR]) considering geometrical registration error were defined. The underestimation (uncovered V[CT] by V[MR]) and the overestimation (excessive V[MR] by V[CT]) were calculated. Through a paired T-test, the difference between image registration techniques was analyzed.For method[A], the underestimation rates of V_GTV[MR] and V_+GTV[MR] were 16.4 ± 8.9% and 3.2 ± 3.7%, and the overestimation rates were 16.6 ± 8.7% and 28.4 ± 10.3%, respectively. For V_GTV[MR] and V_+GTV[MR], the underestimation rates and overestimation rates of method[A] were better than method[C]. The underestimation rates and overestimation rates of the V_GTV[MR] were better in method[B] than method[C]. By image registration and additional margin, about 97% of HCC could be covered. Method[A] or method[B] could be recommended according to physician preference.     

A saliency-based bottom-up visual attention model for dynamic scenes analysis

This work proposes a model of visual bottom-up attention for dynamic scene analysis. Our work adds motion saliency calculations to a neural network model with realistic temporal dynamics [(e.g., building motion salience on top of De Brecht and Saiki Neural Networks 19:1467–1474, (2006)]. The resulting network elicits strong transient responses to moving objects and reaches stability within a biologically plausible time interval. The responses are statistically different comparing between earlier and later motion neural activity; and between moving and non-moving objects. We demonstrate the network on a number of synthetic and real dynamical movie examples. We show that the model captures the motion saliency asymmetry phenomenon. In addition, the motion salience computation enables sudden-onset moving objects that are less salient in the static scene to rise above others. Finally, we include strong consideration for the neural latencies, the Lyapunov stability, and the neural properties being reproduced by the model.     

Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity

Ultra-low-field (ULF) MRI (B ₀ = 10–100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction.     

Novel Nano-Sized MR Contrast Agent Mediates Strong Tumor Contrast Enhancement in an Oncogene-Driven Breast Cancer Model

The current study was carried out to test the potential of a new nanomaterial (Spago Pix) as a macromolecular magnetic MR contrast agent for tumor detection and to verify the presence of nanomaterial in tumor tissue. Spago Pix, synthesized by Spago Nanomedical AB, is a nanomaterial with a globular shape, an average hydrodynamic diameter of 5 nm, and a relaxivity (r₁) of approximately 30 (mM Mn)⁻¹ s⁻¹ (60 MHz). The material consists of an organophosphosilane hydrogel with strongly chelated manganese (II) ions and a covalently attached PEG surface layer. In vivo MRI of the MMTV-PyMT breast cancer model was performed on a 3 T clinical scanner. Tissues were thereafter analyzed for manganese and silicon content using inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The presence of nanomaterial in tumor and muscle tissue was assessed using an anti-PEG monoclonal antibody. MR imaging of tumor-bearing mice (n = 7) showed a contrast enhancement factor of 1.8 (tumor versus muscle) at 30 minutes post-administration. Contrast was retained and further increased 2–4 hours after administration. ICP-AES and immunohistochemistry confirmed selective accumulation of nanomaterial in tumor tissue. A blood pharmacokinetics analysis showed that the concentration of Spago Pix gradually decreased over the first hour, which was in good agreement with the time frame in which the accumulation in tumor occurred. In summary, we demonstrate that Spago Pix selectively enhances MR tumor contrast in a clinically relevant animal model. Based on the generally higher vascular leakiness in malignant compared to benign tissue lesions, Spago Pix has the potential to significantly improve cancer diagnosis and characterization by MRI.     

Decoding successive computational stages of saliency processing

An important requirement for vision is to identify interesting and relevant regions of the environment for further processing. Some models assume that salient locations from a visual scene are encoded in a dedicated spatial saliency map [1, 2]. Then, a winner-take-all (WTA) mechanism [1, 2] is often believed to threshold the graded saliency representation and identify the most salient position in the visual field. Here we aimed to assess whether neural representations of graded saliency and the subsequent WTA mechanism can be dissociated. We presented images of natural scenes while subjects were in a scanner performing a demanding fixation task, and thus their attention was directed away. Signals in early visual cortex and posterior intraparietal sulcus (IPS) correlated with graded saliency as defined by a computational saliency model. Multivariate pattern classification [3, 4] revealed that the most salient position in the visual field was encoded in anterior IPS and frontal eye fields (FEF), thus reflecting a potential WTA stage. Our results thus confirm that graded saliency and WTA-thresholded saliency are encoded in distinct neural structures. This could provide the neural representation required for rapid and automatic orientation toward salient events in natural environments.     

Longitudinal MRI Evaluation of Intracranial Development and Vascular Characteristics of Breast Cancer Brain Metastases in a Mouse Model

Longitudinal MRI was applied to monitor intracranial initiation and development of brain metastases and assess tumor vascular volume and permeability in a mouse model of breast cancer brain metastases. Using a 9.4T system, high resolution anatomic MRI and dynamic susceptibility contrast (DSC) perfusion MRI were acquired at different time points after an intracardiac injection of brain-tropic breast cancer MDA-MB231BR-EGFP cells. Three weeks post injection, multifocal brain metastases were first observed with hyperintensity on T₂-weighted images, but isointensity on T₁-weighted post contrast images, indicating that blood-tumor-barrier (BTB) at early stage of brain metastases was impermeable. Follow-up MRI revealed intracranial tumor growth and increased number of metastases that distributed throughout the whole brain. At the last scan on week 5, T₁-weighted post contrast images detected BTB disruption in 160 (34%) of a total of 464 brain metastases. Enhancement in some of the metastases was only seen in partial regions of the tumor, suggesting intratumoral heterogeneity of BTB disruption. DSC MRI measurements of relative cerebral blood volume (rCBV) showed that rCBV of brain metastases was significantly lower (mean  = 0.89±0.03) than that of contralateral normal brain (mean  = 1.00±0.03; p<0.005). Intriguingly, longitudinal measurements revealed that rCBV of individual metastases at early stage was similar to, but became significantly lower than that of contralateral normal brain with tumor growth (p<0.05). The rCBV data were concordant with histological analysis of microvascular density (MVD). Moreover, comprehensive analysis suggested no significant correlation among tumor size, rCBV and BTB permeability. In conclusion, longitudinal MRI provides non-invasive in vivo assessments of spatial and temporal development of brain metastases and their vascular volume and permeability. The characteristic rCBV of brain metastases may have a diagnostic value.     

Through a barn owl’s eyes: interactions between scene content and visual attention

In this study we investigated visual attention properties of freely behaving barn owls, using a miniature wireless camera attached to their heads. The tubular eye structure of barn owls makes them ideal subjects for this research since it limits their eye movements. Video sequences recorded from the owl’s point of view capture part of the visual scene as seen by the owl. Automated analysis of video sequences revealed that during an active search task, owls repeatedly and consistently direct their gaze in a way that brings objects of interest to a specific retinal location (retinal fixation area). Using a projective model that captures the geometry between the eye and the camera, we recovered the corresponding location in the recorded images (image fixation area). Recording in various types of environments (aviary, office, outdoors) revealed significant statistical differences of low level image properties at the image fixation area compared to values extracted at random image patches. These differences are in agreement with results obtained in primates in similar studies. To investigate the role of saliency and its contribution to drawing the owl’s attention, we used a popular bottom-up computational model. Saliency values at the image fixation area were typically greater than at random patches, yet were only 20% out of the maximal saliency value, suggesting a top-down modulation of gaze control.     

Radiologically Defined Ecological Dynamics and Clinical Outcomes in Glioblastoma Multiforme: Preliminary Results

MATERIALS AND METHODS: We examined pretreatment magnetic resonance imaging (MRI) examinations from 32 patients with glioblastoma multiforme (GBM) enrolled in The Cancer Genome Atlas (TCGA). Spatial variations in T1 post-gadolinium and either T2-weighted or fluid attenuated inversion recovery sequences from each tumor MRI study were used to characterize each small region of the tumor by its local contrast enhancement and edema/cellularity (“habitat”). The patient cohort was divided into group 1 (survival < 400 days, n = 16) and group 2 (survival > 400 days, n = 16). RESULTS: Histograms of relative values in each sequence demonstrated that the tumor regions were consistently divided into high and low blood contrast enhancement, each of which could be subdivided into regions of high, low, and intermediate cell density/interstitial edema. Group 1 tumors contained greater volumes of habitats with low contrast enhancement but intermediate and high cell density (not fully necrotic) than group 2. Both leave-one-out and 10-fold cross-validation schemes demonstrated that individual patients could be correctly assigned to the short or long survival group with 81.25% accuracy. CONCLUSION: We demonstrate that novel image analytic techniques can characterize regional habitat variations in GBMs using combinations of MRI sequences. A preliminary study of 32 patients from the TCGA database found that the distribution of MRI-defined habitats varied significantly among the different survival groups. Radiologically defined ecological tumor analysis may provide valuable prognostic and predictive biomarkers in GBM and other tumors.