An integrated visualization system for surgical planning and guidance using image fusion and an open MR

Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial

Comparative preliminary analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data collected in the International Breast MR Consortium 6883 multicenter trial was performed to distinguish benign and malignant breast tumors. Prebiopsy DCE-MRI data from 45 patients with suspicious breast lesions were obtained. Semiquantitative mean signal-enhancement ratio ([Formula: see text]) was calculated for all lesions, and quantitative pharmacokinetic, parameters [Formula: see text], [Formula: see text], and [Formula: see text], were calculated for the subset with available [Formula: see text] maps ([Formula: see text]). Diagnostic performance was estimated for DCE-MRI parameters and compared to standard clinical MRI assessment. Quantitative and semiquantitative metrics discriminated benign and malignant lesions, with receiver operating characteristic area under the curve (AUC) values of 0.71, 0.70, and 0.82 for [Formula: see text], [Formula: see text], and [Formula: see text], respectively ([Formula: see text]). At equal 94% sensitivity, the specificity and positive predictive value of [Formula: see text] (53% and 63%, respectively) and K^trans (42% and 58%) were higher than clinical MRI assessment (32% and 54%). A multivariable model combining [Formula: see text] and clinical MRI assessment had an AUC value of 0.87. Quantitative pharmacokinetic and semiquantitative analyses of DCE-MRI improves discrimination of benign and malignant breast tumors, with our findings suggesting higher diagnostic accuracy using [Formula: see text]. [Formula: see text] has potential to help reduce unnecessary biopsies resulting from routine breast imaging.

Empirical estimation of intravoxel structure with persistent angular structure and Q-ball models of diffusion weighted MRI

The diffusion tensor model is nonspecific in regions where micrometer structural patterns are inconsistent at the millimeter scale (i.e., brain regions with pathways that cross, bend, branch, fan, etc.). Numerous models have been proposed to represent crossing fibers and complex intravoxel structure from in vivo diffusion weighted magnetic resonance imaging (e.g., high angular resolution diffusion imaging-HARDI). Here, we present an empirical comparison of two HARDI approaches-persistent angular structure MRI (PAS-MRI) and Q-ball-using a newly acquired reproducibility dataset. Briefly, a single subject was scanned 11 times with 96 diffusion weighted directions and 10 reference volumes for each of two [Formula: see text] values (1000 and [Formula: see text] for a total of 2144 volumes). Empirical reproducibility of intravoxel fiber fractions (number/strength of peaks), angular orientation, and fractional anisotropy was compared with metrics from a traditional tensor analysis approach, focusing on [Formula: see text] values of 1000 and [Formula: see text]. PAS-MRI is shown to be more reproducible than Q-ball and offers advantages at low [Formula: see text] values. However, there are substantial and biologically meaningful differences between the intravoxel structures estimated both in terms of analysis method as well as by [Formula: see text] value. The two methods suggest a fundamentally different microarchitecture of the human brain; therefore, it is premature to perform meta-analysis or combine results across HARDI studies using a different analysis model or acquisition sequences.

Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results

Pathologic complete response following neoadjuvant therapy (NAT) is used as a short-term surrogate marker of eventual outcome in patients with breast cancer. Analyzing voxel-level heterogeneity in MRI-derived parametric maps, obtained before and after the first cycle of NAT ([Formula: see text]), in conjunction with receptor status, may improve the predictive accuracy of tumor response to NAT. Toward that end, we incorporated two MRI-derived parameters, the apparent diffusion coefficient and efflux rate constant, with receptor status in a logistic ridge-regression model. The area under the curve (AUC) and Brier score of the model computed via 10-fold cross validation were 0.94 (95% CI: 0.85, 0.99) and 0.11 (95% CI: 0.06, 0.16), respectively. These two statistics strongly support the hypothesis that our proposed model outperforms the other models that we investigated (namely, models without either receptor information or voxel-level information). The contribution of the receptor information was manifested by an 8% to 15% increase in AUC and a 14% to 21% decrease in Brier score. These data indicate that combining multiparametric MRI with hormone receptor status has a high likelihood of improved prediction of pathologic response to NAT in breast cancer.

[Patterns of brain injury in neonatal hypoxic-ischemic encephalopathy on magnetic resonance imaging: recommendations on classification]

Although there are unified criteria for the clinical diagnosis and grading of neonatal hypoxic-ischemic encephalopathy (HIE), clinical features and neuropathological patterns vary considerably among the neonates with HIE due to birth asphyxia in the same classification. The patterns and progression of brain injury in HIE, which is closely associated with long-term neurodevelopment outcomes, can be well shown on magnetic resonance imaging (MRI), but different sequences may lead to different MRI findings at the same time. It is suggested that diffusion-weighted imaging sequence be selected at 2-4 days after birth, and the conventional MRI sequence at 4-8 days. The major patterns of brain injury in HIE on MRI are as follows: injury of the thalamus and basal ganglia and posterior limbs of the internal capsules; watershed injury involving the cortical and subcortical white matter; focal or multifocal minimal white matter injury; extensive whole brain injury. Severe acute birth asphyxia often leads to deep grey matter injury (thalamus and basal ganglia), and the brain stem may also be involved; the pyramidal tract is the most susceptible white matter fiber tract; repetitive or intermittent hypoxic-ischemic insults, with inflammation or hypoglycemia, usually cause injuries in the watershed area and deep white matter. It is worth noting that sometimes the pattern of brain injury among those described above cannot be determined exactly, but rather a predominant one is identified; not all cases of HIE have characteristic MRI findings.

Holistic segmentation of the lung in cine MRI

Duchenne muscular dystrophy (DMD) is a childhood-onset neuromuscular disease that results in the degeneration of muscle, starting in the extremities, before progressing to more vital areas, such as the lungs. Respiratory failure and pneumonia due to respiratory muscle weakness lead to hospitalization and early mortality. However, tracking the disease in this region can be difficult, as current methods are based on breathing tests and are incapable of distinguishing between muscle involvements. Cine MRI scans give insight into respiratory muscle movements, but the images suffer due to low spatial resolution and poor signal-to-noise ratio. Thus, a robust lung segmentation method is required for accurate analysis of the lung and respiratory muscle movement. We deployed a deep learning approach that utilizes sequence-specific prior information to assist the segmentation of lung in cine MRI. More specifically, we adopt a holistically nested network to conduct image-to-image holistic training and prediction. One frame of the cine MRI is used in the training and applied to the remainder of the sequence ([Formula: see text] frames). We applied this method to cine MRIs of the lung in the axial, sagittal, and coronal planes. Characteristic lung motion patterns during the breathing cycle were then derived from the segmentations and used for diagnosis. Our data set consisted of 31 young boys, age [Formula: see text] years, 15 of whom suffered from DMD. The remaining 16 subjects were age-matched healthy volunteers. For validation, slices from inspiratory and expiratory cycles were manually segmented and compared with results obtained from our method. The Dice similarity coefficient for the deep learning-based method was [Formula: see text] for the sagittal view, [Formula: see text] for the axial view, and [Formula: see text] for the coronal view. The holistic neural network approach was compared with an approach using Demon's registration and showed superior performance. These results suggest that the deep learning-based method reliably and accurately segments the lung across the breathing cycle.

Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted magnetic resonance imaging for predicting the response of locally advanced breast cancer to neoadjuvant therapy: a meta-analysis

This meta-analysis assesses the prognostic value of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) performed during neoadjuvant therapy (NAT) of locally advanced breast cancer. A systematic literature search was conducted to identify studies of quantitative DCE-MRI and DW-MRI performed during breast cancer NAT that report the sensitivity and specificity for predicting pathological complete response (pCR). Details of the study population and imaging parameters were extracted from each study for subsequent meta-analysis. Metaregression analysis, subgroup analysis, study heterogeneity, and publication bias were assessed. Across 10 studies that met the stringent inclusion criteria for this meta-analysis (out of 325 initially identified studies), we find that MRI had a pooled sensitivity of 0.91 [95% confidence interval (CI), 0.80 to 0.96] and specificity of 0.81(95% CI, 0.68 to 0.89) when adjusted for covariates. Quantitative DCE-MRI exhibits greater specificity for predicting pCR than semiquantitative DCE-MRI (p<0.001). Quantitative DCE-MRI and DW-MRI are able to predict, early in the course of NAT, the eventual response of breast tumors, with a high level of specificity and sensitivity. However, there is a high degree of heterogeneity in published studies highlighting the lack of standardization in the field.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is sensitive but not specific to determining treatment response in early stage triple-negative breast cancer (TNBC) patients. We propose an efficient computerized technique for assessing treatment response, specifically the residual tumor (RT) status and pathological complete response (pCR), in response to neoadjuvant chemotherapy. The proposed approach is based on Riesz wavelet analysis of pharmacokinetic maps derived from noninvasive DCE-MRI scans, obtained before and after treatment. We compared the performance of Riesz features with the traditional gray level co-occurrence matrices and a comprehensive characterization of the lesion that includes a wide range of quantitative features (e.g., shape and boundary). We investigated a set of predictive models ([Formula: see text]) incorporating distinct combinations of quantitative characterizations and statistical models at different time points of the treatment and some area under the receiver operating characteristic curve (AUC) values we reported are above 0.8. The most efficient models are based on first-order statistics and Riesz wavelets, which predicted RT with an AUC value of 0.85 and pCR with an AUC value of 0.83, improving results reported in a previous study by [Formula: see text]. Our findings suggest that Riesz texture analysis of TNBC lesions can be considered a potential framework for optimizing TNBC patient care.

Optimized b-value selection for the discrimination of prostate cancer grades, including the cribriform pattern, using diffusion weighted imaging

Multiparametric magnetic resonance imaging (MP-MRI), including diffusion-weighted imaging, is commonly used to diagnose prostate cancer. This radiology–pathology study correlates prostate cancer grade and morphology with common b-value combinations for calculating apparent diffusion coefficient (ADC). Thirty-nine patients undergoing radical prostatectomy were recruited for MP-MRI prior to surgery. Diffusion imaging was collected with seven b-values, and ADC was calculated. Excised prostates were sliced in the same orientation as the MRI using 3-D printed slicing jigs. Whole-mount slides were digitized and annotated by a pathologist. Annotated samples were aligned to the MRI, and ADC values were extracted from annotated peripheral zone (PZ) regions. A receiver operating characteristic (ROC) analysis was performed to determine accuracy of tissue type discrimination and optimal ADC b-value combination. ADC significantly discriminates Gleason (G) G4-5 cancer from G3 and other prostate tissue types. The optimal b-values for discriminating high from low-grade and noncancerous tissue in the PZ are 50 and 2000, followed closely by 100 to 2000 and 0 to 2000. Optimal ADC cut-offs are presented for dichotomized discrimination of tissue types according to each b-value combination. Selection of b-values affects the sensitivity and specificity of ADC for discrimination of prostate cancer.

Alterations in neurovascular coupling following acute traumatic brain injury

Following acute traumatic brain injury (TBI), timely transport to a hospital can significantly improve the prognosis for recovery. There is, however, a dearth of quantitative biomarkers for brain injury that can be rapidly acquired and interpreted in active, field environments in which TBIs are frequently incurred. We explored potential functional indicators for TBI that can be noninvasively obtained through portable detection modalities, namely optical and electrophysiological approaches. By combining diffuse correlation spectroscopy with colocalized electrophysiological measurements in a mouse model of TBI, we observed concomitant alterations in sensory-evoked cerebral blood flow (CBF) and electrical potentials following controlled cortical impact. Injury acutely reduced the peak amplitude of both electrophysiological and CBF responses, which mostly recovered to baseline values within 30 min, and intertrial variability for these parameters was also acutely altered. Notably, the postinjury dynamics of the CBF overshoot and undershoot amplitudes differed significantly; whereas the amplitude of the initial peak of stimulus-evoked CBF recovered relatively rapidly, the ensuing undershoot did not appear to recover within 30 min of injury. Additionally, acute injury induced apparent low-frequency oscillatory behavior in CBF ([Formula: see text]). Histological assessment indicated that these physiological alterations were not associated with any major, persisting anatomical changes. Several time-domain features of the blood flow and electrophysiological responses showed strong correlations in recovery kinetics. Overall, our results reveal an array of stereotyped, injury-induced alterations in electrophysiological and hemodynamic responses that can be rapidly obtained using a combination of portable detection techniques.

Abnormal white matter microstructure among early adulthood smokers: a tract-based spatial statistics study

Objectives Cigarette smoking is an important risk factor of central nervous system diseases. However, the white matter (WM) integrity of early adulthood chronic smokers has not been attached enough importance to as it deserves, and the relationship between the chronic smoking effect and the WM is still unclear. The purpose of this study was to investigate whole - brain WM microstructure of early adulthood smokers and explore the structural correlates of behaviorally relevant features of the disorder. Methods We compared multiple DTI-derived indices, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD), between early adulthood smokers (n = 19) and age-, education- and gender-matched controls (n = 23) using a whole-brain tract-based spatial statistics approach. We also explored the correlations of the mean DTI index values with pack-years and Fagerström Test for Nicotine Dependence. Results The smokers showed increased FA in left superior longitudinal fasciculus (SLF), left anterior corona radiate, left superior corona radiate, left posterior corona radiate, left external capsule (EC), left inferior fronto-occipital fasciculus and sagittal stratum (SS), and decreased RD in left SLF. There were significant negative correlations among the average FA in the left external capsule and pack-years in smokers. In addition, significant positive correlation was found between RD values in the left SLF and pack-years. Discussion These findings indicate that smokers show microstructural changes in several white-matter regions. The correlation between the cumulative effect and microstructural WM alternations suggests that WM properties may become the new biomarkers in practice.

Ex vivo tissue imaging for radiology-pathology correlation: a pilot study with a small bore 7-T MRI in a rare pigmented ganglioglioma exhibiting complex MR signal characteristics associated with melanin and hemosiderin

To advance magnetic resonance imaging (MRI) technologies further for in vivo tissue characterization with histopathologic validation, we investigated the feasibility of ex vivo tissue imaging of a surgically removed human brain tumor as a comprehensive approach for radiology–pathology correlation in histoanatomically identical fashion in a rare case of pigmented ganglioglioma with complex paramagnetic properties. Pieces of surgically removed ganglioglioma, containing melanin and hemosiderin pigments, were imaged with a small bore 7-T MRI scanner to obtain T1-, T2-, and T2*-weighted image and diffusion tensor imaging (DTI). Corresponding histopathological slides were prepared for routine hematoxylin and eosin stain and special stains for melanin and iron/hemosiderin to correlate with MRI signal characteristics. Furthermore, mean diffusivity (MD) maps were generated from DTI data and correlated with cellularity using image analysis. While the presence of melanin was difficult to interpret in in vivo MRI with certainty due to concomitant hemosiderin pigments and calcium depositions, ex vivo tissue imaging clearly demonstrated pieces of tissue exhibiting the characteristic MR signal pattern for melanin with pathologic confirmation in a histoanatomically identical location. There was also concordant correlation between MD and cellularity. Although it is still in an initial phase of development, ex vivo tissue imaging is a promising approach, which offers radiology–pathology correlation in a straightforward and comprehensive manner.

Flow visualisation study of spiral flow in the aorta-renal bifurcation

The aim of this study was to analyse the flow dynamics in an idealised model of the aorta-renal bifurcation using flow visualisation, with a particular focus on the effect of aorta-to-renal flow ratio and flow spirality. The recirculation length was longest when there was low flow in the renal artery and smaller in the presence of spiral flow. The results also indicate that patients without spiral flow or who have low flow in the renal artery due to the presence of stenosis may be susceptible to heightened development of atherosclerotic lesions.

Applicability of quantitative optical imaging techniques for intraoperative perfusion diagnostics: a comparison of laser speckle contrast imaging, sidestream dark-field microscopy, and optical coherence tomography

Patient morbidity and mortality due to hemodynamic complications are a major problem in surgery. Optical techniques can image blood flow in real-time and high-resolution, thereby enabling perfusion monitoring intraoperatively. We tested the feasibility and validity of laser speckle contrast imaging (LSCI), optical coherence tomography (OCT), and sidestream dark-field microscopy (SDF) for perfusion diagnostics in a phantom model using whole blood. Microvessels with diameters of 50, 100, and 400  μm were constructed in a scattering phantom. Perfusion was simulated by pumping heparinized human whole blood at five velocities (0 to 20  mm/s). Vessel diameter and blood flow velocity were assessed with LSCI, OCT, and SDF. Quantification of vessel diameter was feasible with OCT and SDF. LSCI could only visualize the 400-μm vessel, perfusion units scaled nonlinearly with blood velocity. OCT could assess blood flow velocity in terms of inverse OCT speckle decorrelation time. SDF was not feasible to measure blood flow; however, for diluted blood the measurements were linear with the input velocity up to 1  mm/s. LSCI, OCT, and SDF were feasible to visualize blood flow. Validated blood flow velocity measurements intraoperatively in the desired parameter (mL·min-1·g-1) remain challenging.

Aseptic lung and liver abscesses: a diagnostic challenge

A 67-year-old man known with systemic sarcoidosis was admitted to the department of internal medicine because of cough and chest pain for several weeks. Thoracic tomodensitometry demonstrated multiple pulmonary nodules. Biopsies revealed features compatible with abscesses. Cultures and serologic tests were negative and the patient was successfully treated with prednisone. Three years later, a thoraco-abdominal tomodensitometry showed a relapse in the lung and also the apparition of similar lesions in the liver. Blood test revealed elevated CRP level at 40 mg/L and mild cholestasis. Biopsies of the liver excluded neoplastic or infectious diseases and showed inflammatory granulation tissue with abscess formation. A diagnosis of sarcoidosis-associated aseptic abscesses syndrome was then made, which was successfully treated with corticosteroids.

Association of Plasma Neurofilament Light With Neurodegeneration in Patients With Alzheimer Disease

Question

What is the importance of plasma neurofilament light in Alzheimer disease?

Findings

In this case-control study of 193 cognitively healthy controls, 197 patients with mild cognitive impairment, and 180 patients with Alzheimer disease dementia, plasma neurofilament light was associated with Alzheimer disease and correlated with future progression of cognitive decline, brain atrophy, and brain hypometabolism.

Meaning

Plasma neurofilament light may be a promising noninvasive biomarker for Alzheimer disease.

Importance

Existing cerebrospinal fluid (CSF) or imaging (tau positron emission tomography) biomarkers for Alzheimer disease (AD) are invasive or expensive. Biomarkers based on standard blood test results would be useful in research, drug development, and clinical practice. Plasma neurofilament light (NFL) has recently been proposed as a blood-based biomarker for neurodegeneration in dementias.

Objective

To test whether plasma NFL concentrations are increased in AD and associated with cognitive decline, other AD biomarkers, and imaging evidence of neurodegeneration.

Design, Setting, and Participants

In this prospective case-control study, an ultrasensitive assay was used to measure plasma NFL concentration in 193 cognitively healthy controls, 197 patients with mild cognitive impairment (MCI), and 180 patients with AD dementia from the Alzheimer’s Disease Neuroimaging Initiative. The study dates were September 7, 2005, to February 13, 2012. The plasma NFL analysis was performed in September 2016.

Main Outcomes and Measures

Associations were tested between plasma NFL and diagnosis, Aβ pathologic features, CSF biomarkers of neuronal injury, cognition, brain structure, and metabolism.

Results

Among 193 cognitively healthy controls, 197 patients with mild cognitive impairment, and 180 patients with AD with dementia, plasma NFL correlated with CSF NFL (Spearman ρ = 0.59, P < .001). Plasma NFL was increased in patients with MCI (mean, 42.8 ng/L) and patients with AD dementia (mean, 51.0 ng/L) compared with controls (mean, 34.7 ng/L) (P < .001) and had high diagnostic accuracy for patients with AD with dementia vs controls (area under the receiver operating characteristic curve, 0.87, which is comparable to established CSF biomarkers). Plasma NFL was particularly high in patients with MCI and patients with AD dementia with Aβ pathologic features. High plasma NFL correlated with poor cognition and AD-related atrophy (at baseline and longitudinally) and with brain hypometabolism (longitudinally).

Conclusions and Relevance

Plasma NFL is associated with AD diagnosis and with cognitive, biochemical, and imaging hallmarks of the disease. This finding implies a potential usefulness for plasma NFL as a noninvasive biomarker in AD.

Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images

We describe a postacquisition, attribute-based quality assessment method for brain magnetic resonance imaging (MRI) images. It is based on the application of Bayes theory to the relationship between entropy and image quality attributes. The entropy feature image of a slice is segmented into low- and high-entropy regions. For each entropy region, there are three separate observations of contrast, standard deviation, and sharpness quality attributes. A quality index for a quality attribute is the posterior probability of an entropy region given any corresponding region in a feature image where quality attribute is observed. Prior belief in each entropy region is determined from normalized total clique potential (TCP) energy of the slice. For TCP below the predefined threshold, the prior probability for a region is determined by deviation of its percentage composition in the slice from a standard normal distribution built from 250 MRI volume data provided by Alzheimer's Disease Neuroimaging Initiative. For TCP above the threshold, the prior is computed using a mathematical model that describes the TCP-noise level relationship in brain MRI images. Our proposed method assesses the image quality of each entropy region and the global image. Experimental results demonstrate good correlation with subjective opinions of radiologists for different types and levels of quality distortions.

Morphologic and biometric evaluation of chick embryo eyes in ovo using 7 Tesla MRI

The purposes of this study were (1) to characterize embryonic eye development during incubation in ovo and (2) to analyze the putative influence of repetitive ultrahigh-field MRI (UHF-MRI) measurements on this development. A population of 38 fertilized chicken eggs was divided into two sub-groups: two eggs (Group A) were examined repeatedly during the developmental period from embryonic day 1 (E1) to embryonic day 20 (E20) to evaluate the influence of daily MRI scanning. A second larger group of 36 eggs was examined pairwise on one day only, from E3 to E20, and the embryos were sacrificed immediately after MR imaging (Group B). Fast T2-weighted MR sequences provided biometric data on the eye with an in-plane resolution of 74 μm. The data show rapid growth of the eye with a steep increase in intraocular dimensions in all axis directions and in eyeball volume during initial development up to E10, followed by a phase of reduced growth rate in later developmental stages. Comparison of the two groups revealed no differences in ocular development.

Post-Surgery Glioma Growth Modeling from Magnetic Resonance Images for Patients with Treatment

Reaction diffusion is the most common growth modelling methodology due to its simplicity and consistency with the biological tumor growth process. However, current extensions of the reaction diffusion model lack one or more of the following: efficient inclusion of treatments' effects, taking into account the viscoelasticity of brain tissues, and guaranteed stability of the numerical solution. We propose a new model to overcome the aforementioned drawbacks. Guided by directional information derived from diffusion tensor imaging, our model relates tissue heterogeneity with the absorption of the chemotherapy, adopts the linear-quadratic term to simulate the radiotherapy effect, employs Maxwell-Weichert model to incorporate brain viscoelasticity, and ensures the stability of the numerical solution. The performance is verified through experiments on synthetic and real MR images. Experiments on 9 MR datasets of patients with low grade gliomas undergoing surgery with different treatment regimens are carried out and validated using Jaccard score and Dice coefficient. The growth simulation accuracies of the proposed model are in ranges of [0.673 0.822] and [0.805 0.902] for Jaccard scores and Dice coefficients, respectively. The accuracies decrease up to 4% and 2.4% when ignoring treatment effects and the tensor information, while brain viscoelasticity has no significant impact on the accuracies.

MRI-based finite element modeling of facial mimics: a case study on the paired zygomaticus major muscles

Finite element simulation of facial mimics provides objective indicators about soft tissue functions for improving diagnosis, treatment and follow-up of facial disorders. There is a lack of in vivo experimental data for model development and validation. In this study, the contribution of the paired Zygomaticus Major (ZM) muscle contraction on the facial mimics was investigated using in vivo experimental data derived from MRI. Maximal relative differences of 7.7% and 37% were noted between MRI-based measurements and numerical outcomes for ZM and skin deformation behaviors respectively. This study opens a new direction to simulate facial mimics with in vivo data.

A Social Constructivism Decision-Making Approach to Managing Incidental Findings in Neuroimaging Research

Functional magnetic resonance imaging (fMRI) is a powerful tool used in cognitive neuroscientific research. fMRI is noninvasive, safe, and relatively accessible, making it an ideal method to draw inferences about the brain-behavior relationship. When conducting fMRI research, scientists must consider risks associated with brain imaging. In particular, the risk of potentially identifying an abnormal brain finding in an fMRI research scan poses a complex problem that researchers should be prepared to address. This article illustrates how a social constructivism decision-making model can be used as a framework to guide researchers as they develop protocols to address this issue.

Multi-component quantitative magnetic resonance imaging by phasor representation

Quantitative magnetic resonance imaging (qMRI) is a versatile, non-destructive and non-invasive tool in life, material, and medical sciences. When multiple components contribute to the signal in a single pixel, however, it is difficult to quantify their individual contributions and characteristic parameters. Here we introduce the concept of phasor representation to qMRI to disentangle the signals from multiple components in imaging data. Plotting the phasors allowed for decomposition, unmixing, segmentation and quantification of our in vivo data from a plant stem, a human and mouse brain and a human prostate. In human brain images, we could identify 3 main T₂ components and 3 apparent diffusion coefficients; in human prostate 5 main contributing spectral shapes were distinguished. The presented phasor analysis is model-free, fast and accurate. Moreover, we also show that it works for undersampled data.

Interaction of iron nanoparticles with nervous system: an in vitro study

Nanoparticles (NPs) are one of the interesting and widely studying issues mainly because of their particular physico-chemical features and broad applications in the field of biomedical sciences, such as diagnosis and drug delivery. In this study, the interaction of iron nanoparticles (Fe-NPs) with Tau protein and PC12 cell, as potential nervous system models, was investigated with a range of techniques including dynamic light scattering, intrinsic fluorescence spectroscopy, circular dichroism, [(3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium-bromid] assay, and acridine orange/ethidium bromide (AO/EB) dual staining method. An inverse correlation between Stern and Volmer constant (K_SV) and temperature indicated a probable static quenching mechanism occurred between Tau protein and Fe-NPs. The number of binding site (n = 0.86) showed that there is almost one binding site of Fe-NP per protein. The negative values of ∆H (-53.21 kJ/mol) and T∆S (-42.44 kJ/mol) revealed that Fe-NPs interacts with Tau protein with dominate role of hydrogen bonds and van der Waals interactions and this interaction was spontaneous (∆G = -10.77 kJ/mol). Also, Fe-NPs stabilized the random coil structure of Tau protein. Moreover, Fe-NPs reduced PC12 cells viability by fragmentation of DNA in an apoptotic manner. In conclusion, induced conformational changes of Tau protein and cytotoxicity of PC12 cells by Fe-NP were revealed to be in a concentration and time-dependent manner.

Diffuse fluorescence fiber probe for in vivo detection of circulating cells

There has been significant recent interest in the development of technologies for enumeration of rare circulating cells directly in the bloodstream in many areas of research, for example, in small animal models of circulating tumor cell dissemination during cancer metastasis. We describe a fiber-based optical probe that allows fluorescence detection of labeled circulating cells in vivo in a diffuse reflectance configuration. We validated this probe in a tissue-mimicking flow phantom model in vitro and in nude mice injected with fluorescently labeled multiple myeloma cells in vivo. Compared to our previous work, this design yields an improvement in detection signal-to-noise ratio of 10 dB, virtually eliminates problematic motion artifacts due to mouse breathing, and potentially allows operation in larger animals and limbs.

Robust phase unwrapping for phase images in Fourier domain Doppler optical coherence tomography

To solve the 2 ? phase ambiguity for phase-resolved Doppler images in Doppler optical coherence tomography, we present a modified network programming technique for the first time to the best of our knowledge. The proposed method assumes that error of the discrete derivatives between unwrapped phase image and wrapped phase image can be arbitrary values instead of integer-multiple of 2 ? , which makes the real-phase restoration accurate and robust against noise. We compared our proposed method with the network programming method. Parameters including root-mean-square-error and noise amplification degree were adopted for comparison. The experimental study on simulated images, phantom, and real-vessel OCT images were performed. The proposed method consistently achieves optimal results.

Comparison of Multi-Fiber Reproducibility of PAS-MRI and Q-ball With Empirical Multiple b-Value HARDI

Crossing fibers are prevalent in human brains and a subject of intense interest for neuroscience. Diffusion tensor imaging (DTI) can resolve tissue orientation but is blind to crossing fibers. Many advanced diffusion-weighted magnetic resolution imaging (MRI) approaches have been presented to extract crossing-fibers from high angular resolution diffusion imaging (HARDI), but the relative sensitivity and specificity of approaches remains unclear. Here, we examine two leading approaches (PAS and q-ball) in the context of a large-scale, single subject reproducibility study. A single healthy individual was scanned 11 times with 96 diffusion weighted directions and 10 reference volumes for each of five b-values (1000, 1500, 2000, 2500, 3000 s/mm2) for a total of 5830 volumes (over the course of three sessions). We examined the reproducibility of the number of fibers per voxel, volume fraction, and crossing-fiber angles. For each method, we determined the minimum resolvable angle for each acquisition. Reproducibility of fiber counts per voxel was generally high (~80% consensus for PAS and ~70% for q-ball), but there was substantial bias between individual repetitions and model estimated with all data (~10% lower consensus for PAS and ~15% lower for q-ball). Both PAS and q-ball predominantly discovered fibers crossing at near 90 degrees, but reproducibility was higher for PAS across most measures. Within voxels with low anisotropy, q-ball finds more intra-voxel structure; meanwhile, PAS resolves multiple fibers at greater than 75 degrees for more voxels. These results can inform researchers when deciding between HARDI approaches or interpreting findings across studies.

Maternal buffering beyond glucocorticoids: impact of early life stress on corticolimbic circuits that control infant responses to novelty

Maternal presence has a potent buffering effect on infant fear and stress responses in primates. We previously reported that maternal presence is not effective in buffering the endocrine stress response in infant rhesus monkeys reared by maltreating mothers. We have also reported that maltreating mothers show low maternal responsiveness and permissiveness/secure-base behavior. Although still not understood, it is possible that this maternal buffering effect is mediated, at least partially, through deactivation of amygdala response circuits when mothers are present. Here, we studied rhesus monkey infants that differed in the quality of early maternal care to investigate how this early experience modulated maternal buffering effects on behavioral responses to novelty during the weaning period. We also examined the relationship between these behavioral responses and structural connectivity in one of the underlying regulatory neural circuits: amygdala-prefrontal pathways. Our findings suggest that infant exploration in a novel situation is predicted by maternal responsiveness and structural integrity of amygdala-prefrontal white matter depending on maternal presence (positive relationships when mother is absent). These results provide evidence that maternal buffering of infant behavioral inhibition is dependent on the quality of maternal care and structural connectivity of neural pathways that are sensitive to early life stress.

[Value of diffusion-weighted imaging, 1H-magnetic resonance spectroscopy and 3D whole-brain arterial spin labeling in the diagnosis of medulloblastoma]

OBJECTIVE

To explore the value of diffusion-weighted imaging (DWI), ¹H-magnetic resonance spectroscopy (1H-MRS) and 3D whole-brain arterial spin labeling (3D ASL) in the diagnosis of medulloblastoma in the posterior cranial fossa.

METHODS

The magnetic resonance imaging (MRI) findings of 16 patients with pathologically confirmed medulloblastoma in the posterior cranial fossa were analyzed retrospectively. All the patients were examined with plane and enhanced brain MRI scans; 5 patients also underwent examinations with DWI, 12 with MRS, and 5 with 3D ASL.

RESULTS

Medulloblastomas were found in the vermis and the fourth ventricle in 9 cases, in the cerebellar hemisphere in 5 cases, and in the cerebellopontine angle in 1 case; in 1 case multiple lesions were detected. The tumors showed iso-intense or slightly hypo-intense signals on T₁WI, and iso-intense or hyper-intense signals on T₂WI and FLAIR. The lesions showed high signals in DWI and low signals in ADC. Intra-lesion cysts were common (n=12), and calcification and bleeding were rarely seen. Mild patchy enhancement (n=6) or significant enhancement (n=10) was seen after contrast agent administration. Obstructive hydrocephalus was found in 12 cases and the subarachnoid space was involved in 3 cases. In all the 12 patients receiving MRS examination, high Cho and low NAA were found with significantly increased Cho/Cr (≥3.5) and Cho/NAA (≥4.0) ratios; Tau peak was seen in 8 cases, and Lip peak was found in 4 cases. All the 5 patients receiving 3D ASL examination showed decreased cerebral blood flow (CBF).

CONCLUSION

The characteristic features of medulloblastomas in DWI, MRS and 3D ASL offer assistance to the diagnosis of atypical medulloblastoma.

Surgical planning for living donor liver transplant using 4D flow MRI, computational fluid dynamics and in vitro experiments

This study used magnetic resonance imaging (MRI), computational fluid dynamics (CFD) modeling, and in vitro experiments to predict patient-specific alterations in hepatic hemodynamics in response to partial hepatectomy in living liver donors. 4D Flow MRI was performed on three donors before and after hepatectomy and models of the portal venous system were created. Virtual surgery was performed to simulate (1) surgical resection and (2) post-surgery vessel dilation. CFD simulations were conducted using in vivo flow data for boundary conditions. CFD results showed good agreement with in vivo data, and in vitro experimental values agreed well with imaging and simulation results. The post-surgery models predicted an increase in all measured hemodynamic parameters, and the dilated virtual surgery model predicted post-surgery conditions better than the model that only simulated resection. The methods used in this study have potential significant value for the surgical planning process for the liver and other vascular territories.

Review of the potential of optical technologies for cancer diagnosis in neurosurgery: a step toward intraoperative neurophotonics

Advances in image-guided therapy enable physicians to obtain real-time information on neurological disorders such as brain tumors to improve resection accuracy. Image guidance data include the location, size, shape, type, and extent of tumors. Recent technological advances in neurophotonic engineering have enabled the development of techniques for minimally invasive neurosurgery. Incorporation of these methods in intraoperative imaging decreases surgical procedure time and allows neurosurgeons to find remaining or hidden tumor or epileptic lesions. This facilitates more complete resection and improved topology information for postsurgical therapy (i.e., radiation). We review the clinical application of recent advances in neurophotonic technologies including Raman spectroscopy, thermal imaging, optical coherence tomography, and fluorescence spectroscopy, highlighting the importance of these technologies in live intraoperative tissue mapping during neurosurgery. While these technologies need further validation in larger clinical trials, they show remarkable promise in their ability to help surgeons to better visualize the areas of abnormality and enable safe and successful removal of malignancies.

Patient-Specific Flow Descriptors and Normalized wall index in Peripheral Artery Disease: a Preliminary Study

BACKGROUND AND AIMS

MRI-based hemodynamics have been applied to study the relationship between time-averaged wall shear stresses (TAWSS), oscillatory shear index (OSI) and atherosclerotic lesions in the coronary arteries, carotid artery, and human aorta. However, the role of TAWSS and OSI are poorly understood in lower extremity arteries. The aim of this work was to investigate the feasibility of hemodynamic assessment of the superficial femoral artery (SFA) in patients with peripheral artery disease (PAD) and we hypothesized that there is an association between TAWSS and OSI, respectively, and atherosclerotic burden expressed as the normalized wall index (NWI).

METHODS

Six cases of 3D vascular geometries of the SFA and related inlet/outlet flow conditions were extracted from patient-specific MRI data including baseline, 12 and 24 months. Blood flow simulations were performed to compute flow descriptors, including TAWSS and OSI, and NWI.

RESULTS

NWI was correlated positively with TAWSS (correlation coefficient: r = 0.592; p < 0.05). NWI was correlated negatively with OSI (correlation coefficient: r = -0.310, p < 0.01). Spatially averaged TAWSS and average NWI increased significantly between baseline and 24-months, whereas OSI decreased over 2-years.

CONCLUSIONS

In this pilot study with a limited sample size, TAWSS was positively associated with NWI, a measure of plaque burden, whereas OSI showed an inverse relationship. However, our findings need to be verified in a larger prospective study. MRI-based study of hemodynamics is feasible in the superficial femoral artery.

Task-based optimization of flip angle for fibrosis detection in T1-weighted MRI of liver

Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. The current reference standard for diagnosing HF is biopsy followed by pathologist examination; however, this is limited by sampling error and carries a risk of complications. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically in the order of 1 to 5 mm, which approximates the resolution limit of in vivo gadolinium-enhanced magnetic resonance imaging in the delayed phase. We use MRI of formalin-fixed human ex vivo liver samples as phantoms that mimic the textural contrast of in vivo Gd-MRI. We have developed a local texture analysis that is applied to phantom images, and the results are used to train model observers to detect HF. The performance of the observer is assessed with the area-under-the-receiver-operator-characteristic curve (AUROC) as the figure-of-merit. To optimize the MRI pulse sequence, phantoms were scanned with multiple times at a range of flip angles. The flip angle that was associated with the highest AUROC was chosen as optimal for the task of detecting HF.

Patient-specific coronary blood supply territories for quantitative perfusion analysis

Myocardial perfusion imaging, coupled with quantitative perfusion analysis, provides an important diagnostic tool for the identification of ischaemic heart disease caused by coronary stenoses. The accurate mapping between coronary anatomy and under-perfused areas of the myocardium is important for diagnosis and treatment. However, in the absence of the actual coronary anatomy during the reporting of perfusion images, areas of ischaemia are allocated to a coronary territory based on a population-derived 17-segment (American Heart Association) AHA model of coronary blood supply. This work presents a solution for the fusion of 2D Magnetic Resonance (MR) myocardial perfusion images and 3D MR angiography data with the aim to improve the detection of ischaemic heart disease. The key contribution of this work is a novel method for the mediated spatiotemporal registration of perfusion and angiography data and a novel method for the calculation of patient-specific coronary supply territories. The registration method uses 4D cardiac MR cine series spanning the complete cardiac cycle in order to overcome the under-constrained nature of non-rigid slice-to-volume perfusion-to-angiography registration. This is achieved by separating out the deformable registration problem and solving it through phase-to-phase registration of the cine series. The use of patient-specific blood supply territories in quantitative perfusion analysis (instead of the population-based model of coronary blood supply) has the potential of increasing the accuracy of perfusion analysis. Quantitative perfusion analysis diagnostic accuracy evaluation with patient-specific territories against the AHA model demonstrates the value of the mediated spatiotemporal registration in the context of ischaemic heart disease diagnosis.

Quantification of MRI and MRS characteristics changes in a rat model at different stage of cerebral ischemia

BACKGROUND

A better understanding the mechanisms of cerebral ischemia is important both for diagnosis and treatment.

OBJECTIVE

The study aimed to quantify several characteristics of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to indicate the brain tissue changes at different stage of cerebral ischemia in rats.

METHODS

In the present study, a rat model of cerebral ischemia was established by middle cerebral artery occlusion (MCAO) in the left hemisphere. MRI and MRS were performed on 15 Sprague Dawley rats 4 H, 24 H, and 1 W after MCAO. Apparent diffusion coefficient (ADC), relative ADC including FNR, PNR, PNF, and metabolite ratio NCC were proposed to reflect the changes of water diffusion and metabolism in brain tissue.

RESULTS

ADCs of focal zone and penumbra zone from 1 W group were significantly larger than those from 4H group, respectively (both p < 0.05). PNR and PNF of 24H and 1 W groups were significantly less than 4H group (all p < 0.01). NCCs of focal zone and penumbra zone were significantly less than the normal zone within 4H, 24H, and 1 W groups, respectively (both p < 0.01). While NCCs of penumbra zone from 24H and 1 W groups were significantly larger than 4H group (both p < 0.01).

CONCLUSION

We conclude that combination of MRI and MRS characteristics can provide significant indicators for ischemic damage at different stage of cerebral ischemia in a rat model.

Cerebral blood flow and autoregulation: current measurement techniques and prospects for noninvasive optical methods

Cerebral blood flow (CBF) and cerebral autoregulation (CA) are critically important to maintain proper brain perfusion and supply the brain with the necessary oxygen and energy substrates. Adequate brain perfusion is required to support normal brain function, to achieve successful aging, and to navigate acute and chronic medical conditions. We review the general principles of CBF measurements and the current techniques to measure CBF based on direct intravascular measurements, nuclear medicine, X-ray imaging, magnetic resonance imaging, ultrasound techniques, thermal diffusion, and optical methods. We also review techniques for arterial blood pressure measurements as well as theoretical and experimental methods for the assessment of CA, including recent approaches based on optical techniques. The assessment of cerebral perfusion in the clinical practice is also presented. The comprehensive description of principles, methods, and clinical requirements of CBF and CA measurements highlights the potentially important role that noninvasive optical methods can play in the assessment of neurovascular health. In fact, optical techniques have the ability to provide a noninvasive, quantitative, and continuous monitor of CBF and autoregulation.

Influence of general anaesthesia on slow waves of intracranial pressure

OBJECTIVE

Slow vasogenic intracranial pressure (ICP) waves are spontaneous ICP oscillations with a low frequency bandwidth of 0.3-4 cycles/min (B-waves). B-waves reflect dynamic oscillations in cerebral blood volume associated with autoregulatory cerebral vasodilation and vasoconstriction. This study quantifies the effects of general anaesthesia (GA) on the magnitude of B-waves compared to natural sleep and conscious state.

MATERIALS AND METHODS

The magnitude of B-waves was assessed in 4 groups of 30 patients each with clinical indications for ICP monitoring. Normal pressure hydrocephalus patients undergoing Cerebrospinal Fluid (CSF) infusion studies in the conscious state (GROUP A) and under GA (GROUP B), and hydrocephalus patients undergoing overnight ICP monitoring during physiological sleep (GROUP C) were compared to deeply sedated traumatic brain injury (TBI) patients with well-controlled ICP during the first night of Intensive Care Unit (ICU) stay (GROUP D).

RESULTS

A total of 120 patients were included. During CSF infusion studies, the magnitude of slow waves was higher in conscious patients (

GROUP A

0.23+/-0.10 mm Hg) when compared to anaesthetised patients (

GROUP B

0.15+/-0.10 mm Hg; p = 0.011). Overnight magnitude of slow waves was higher in patients during natural sleep (GROUP C: 0.20+/-0.13 mm Hg) when compared to TBI patients under deep sedation (GROUP D: 0.11+/- 0.09 mm Hg; p = 0.002).

CONCLUSION

GA and deep sedation are associated with a reduced magnitude of B-waves. ICP monitoring carried out under GA is affected by iatrogenic suppression of slow vasogenic waves of ICP. Accounting for the effects of anaesthesia on vasogenic waves may prevent the misidentification of potential shunt-responders as non-responders.

Quantitative photoacoustic elastography in humans

We report quantitative photoacoustic elastography (QPAE) capable of measuring Young’s modulus of biological tissue in vivo in humans. By combining conventional PAE with a stress sensor having known stress–strain behavior, QPAE can simultaneously measure strain and stress, from which Young’s modulus is calculated. We first demonstrate the feasibility of QPAE in agar phantoms with different concentrations. The measured Young’s modulus values fit well with both the empirical expectation based on the agar concentrations and those measured in an independent standard compression test. Next, QPAE was applied to quantify the Young’s modulus of skeletal muscle in vivo in humans, showing a linear relationship between muscle stiffness and loading. The results demonstrated the capability of QPAE to assess the absolute elasticity of biological tissue noninvasively in vivo in humans, indicating its potential for tissue biomechanics studies and clinical applications.

In vivo imaging of melanoma-implanted magnetic nanoparticles using contrast-enhanced magneto-motive optical Doppler tomography

We conducted an initial feasibility study using real-time magneto-motive optical Doppler tomography (MM-ODT) with enhanced contrast to investigate the detection of superparamagnetic iron oxide (SPIO) magnetic nanoparticles implanted into in vivo melanoma tissue. The MM-ODT signals were detected owing to the phase shift of the implanted magnetic nanoparticles, which occurred due to the action of an applied magnetic field. An amplifier circuit-based solenoid was utilized for generating high-intensity oscillating magnetic fields. The MM-ODT system was confirmed as an effective in vivo imaging method for detecting melanoma tissue, with the performance comparable to those of conventional optical coherence tomography and optical Doppler tomography methods. Moreover, the optimal values of the SPIO nanoparticles concentration and solenoid voltage for obtaining the uppermost Doppler velocity were derived as well. To improve the signal processing speed for real-time imaging, we adopted multithread programming techniques and optimized the signal path. The results suggest that this imaging modality can be used as a powerful tool to identify the intracellular and extracellular SPIO nanoparticles in melanoma tissues in vivo.

Adult-onset phenylketonuria with rapidly progressive dementia and parkinsonism

Phenylketonuria (PKU) is an autosomal recessive metabolic disorder due to mutations in the phenylalanine hydroxylase (PAH) gene, which converts phenylalanine (PHE) to tyrosine. Although it is principally a childhood disorder, in rare cases, the first signs of PKU may develop in late adulthood resembling common neurological diseases. Here we report a 59-year-old, previously normal functioning man who was admitted with blurred vision, cognitive problems, and gait difficulty that began 8 months before. He had brisk reflexes and left side dominant parkinsonism. His Mini-Mental State Examination (MMSE) score was 25/30, and neuropsychological evaluation revealed a dysexecutive syndrome with simultanagnosia and constructional apraxia. His Clinical Dementia Rating score (CDR) was 1. Cranial MRI revealed bilateral diffuse hyperintense lesions in parietal and occipital white matter in T2, fluid-attenuated inversion recovery, and diffusion weighted images. Diagnostic workup for rapidly progressive dementias was all normal except PHE level which was found to be highly elevated (1075 μmol/L, normal 39-240 μmol/L) with normal tyrosine level (61.20 μmol/L, normal 35-100 μmol/L). Three months after PHE-restricted diet, his cognitive impairment and signs of parkinsonism significantly improved, with MRI scan unchanged. This case demonstrates that late-onset PKU is a rare, treatable cause of rapidly progressive dementia and parkinsonism with certain constellations such as consanguinity and white matter abnormalities (WMAs) in imaging.

Structure and variability in human tongue muscle anatomy

The human tongue has a complex architecture, consistent with its complex roles in eating, speaking and breathing. Tongue muscle architecture has been depicted in drawings and photographs, but not quantified volumetrically. This paper aims to fill that gap by measuring the muscle architecture of the tongue for 14 people captured in high-resolution 3D MRI volumes. The results show the structure, relationships and variability among the muscles, as well as the effects of age, gender and weight on muscle volume. Since the tongue consists of partially interdigitated muscles, we consider the muscle volumes in two ways. The functional muscle volume encompasses the region of the tongue served by the muscle. The structural volume halves the volume of the muscle in regions where it interdigitates with other muscles. Results show similarity of scaling across subjects, and speculate on functional effects of the anatomical structure.

Multi-site study of diffusion metric variability: effects of site, vendor, field strength, and echo time on regions-of-interest and histogram-bin analyses

It is now common for magnetic-resonance-imaging (MRI) based multi-site trials to include diffusion-weighted imaging (DWI) as part of the protocol. It is also common for these sites to possess MR scanners of different manufacturers, different software and hardware, and different software licenses. These differences mean that scanners may not be able to acquire data with the same number of gradient amplitude values and number of available gradient directions. Variability can also occur in achievable b-values and minimum echo times. The challenge of a multi-site study then, is to create a common protocol by understanding and then minimizing the effects of scanner variability and identifying reliable and accurate diffusion metrics. This study describes the effect of site, scanner vendor, field strength, and TE on two diffusion metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA) using two common analyses (region-of-interest and mean-bin value of whole brain histograms). The goal of the study was to identify sources of variability in diffusion-sensitized imaging and their influence on commonly reported metrics. The results demonstrate that the site, vendor, field strength, and echo time all contribute to variability in FA and MD, though to different extent. We conclude that characterization of the variability of DTI metrics due to site, vendor, field strength, and echo time is a worthwhile step in the construction of multi-center trials.

Quality Assurance using Outlier Detection on an Automatic Segmentation Method for the Cerebellar Peduncles

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method-supervised classification-was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers-linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)-were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

On the Fallacy of Quantitative Segmentation for T1-Weighted MRI

T1-weighted magnetic resonance imaging (MRI) generates contrasts with primary sensitivity to local T1 properties (with lesser T2 and PD contributions). The observed signal intensity is determined by these local properties and the sequence parameters of the acquisition. In common practice, a range of acceptable parameters is used to ensure "similar" contrast across scanners used for any particular study (e.g., the ADNI standard MPRAGE). However, different studies may use different ranges of parameters and report the derived data as simply "T1-weighted". Physics and imaging authors pay strong heed to the specifics of the imaging sequences, but image processing authors have historically been more lax. Herein, we consider three T1-weighted sequences acquired the same underlying protocol (MPRAGE) and vendor (Philips), but "normal study-to-study variation" in parameters. We show that the gray matter/white matter/cerebrospinal fluid contrast is subtly but systemically different between these images and yields systemically different measurements of brain volume. The problem derives from the visually apparent boundary shifts, which would also be seen by a human rater. We present and evaluate two solutions to produce consistent segmentation results across imaging protocols. First, we propose to acquire multiple sequences on a subset of the data and use the multi-modal imaging as atlases to segment target images any of the available sequences. Second (if additional imaging is not available), we propose to synthesize atlases of the target imaging sequence and use the synthesized atlases in place of atlas imaging data. Both approaches significantly improve consistency of target labeling.

Preoperative prediction of cerebral hyperperfusion after carotid endarterectomy using middle cerebral artery signal intensity in 1.5-tesla magnetic resonance angiography followed by cerebrovascular reactivity to acetazolamide using brain perfusion single-photon emission computed tomography

OBJECTIVE

The purpose of the present study was to determine whether the signal intensity of the middle cerebral artery (MCA) on preoperative 1.5-T magnetic resonance angiography (MRA) could identify patients at risk for hyperperfusion following carotid endarterectomy (CEA) as a clinical screening test and whether an additional measurement of preoperative cerebrovascular reactivity (CVR) to acetazolamide on brain perfusion single-photon emission computed tomography (SPECT) could increase the predictive accuracy for the development of hyperperfusion.

METHODS

In 301 patients, the signal intensity of the MCA ipsilateral to CEA on MRA was preoperatively graded according to the ability to visualize the MCA. For patients with reduced MCA signal intensity on the MRA study, CVR to acetazolamide was subsequently assessed using brain perfusion SPECT. Cerebral hyperperfusion was determined intraoperatively using transcranial regional cerebral oxygen saturation monitoring with near-infrared spectroscopy.

RESULTS

Preoperative reduced MCA signal intensity was significantly associated with the development of cerebral hyperperfusion (95% CI, 1.188-3.965; p = 0.0352). While the sensitivity and negative predictive value were 100% both for the preoperative MCA signal intensity alone and in combination with subsequent preoperative CVR to acetazolamide, the specificity and positive predictive value were significantly greater for the latter than for the former (p < 0.05).

CONCLUSIONS

Signal intensity of the MCA on preoperative 1.5-T MRA identifies patients at risk for hyperperfusion following CEA as a clinical screening test. An additional measurement of preoperative CVR to acetazolamide increases the predictive accuracy for the development of hyperperfusion.

Automated Detection of Retinal Cell Nuclei in 3D Micro-CT Images of Zebrafish using Support Vector Machine Classification

Our group is developing a method to examine biological specimens in cellular detail using synchrotron microCT. The method can acquire 3D images of tissue at micrometer-scale resolutions, allowing for individual cell types to be visualized in the context of the entire specimen. For model organism research, this tool will enable the rapid characterization of tissue architecture and cellular morphology from every organ system. This characterization is critical for proposed and ongoing "phenome" projects that aim to phenotype whole-organism mutants and diseased tissues from different organisms including humans. With the envisioned collection of hundreds to thousands of images for a phenome project, it is important to develop quantitative image analysis tools for the automated scoring of organism phenotypes across organ systems. Here we present a first step towards that goal, demonstrating the use of support vector machines (SVM) in detecting retinal cell nuclei in 3D images of wild-type zebrafish. In addition, we apply the SVM classifier on a mutant zebrafish to examine whether SVMs can be used to capture phenotypic differences in these images. The long-term goal of this work is to allow cellular and tissue morphology to be characterized quantitatively for many organ systems, at the level of the whole-organism.