Paramagnetic rims are a promising diagnostic imaging biomarker in multiple sclerosis.

BACKGROUND: White matter lesions (WMLs) on brain magnetic resonance imaging (MRI) in multiple sclerosis (MS) may contribute to misdiagnosis. In chronic active lesions, peripheral iron-laden macrophages appear as paramagnetic rim lesions (PRLs). OBJECTIVE: To evaluate the sensitivity and specificity of PRLs in differentiating MS from mimics using clinical 3T MRI scanners. METHOD: This retrospective international study reviewed MRI scans of patients with MS (n = 254), MS mimics (n = 91) and older healthy controls (n = 217). WMLs, detected using fluid-attenuated inversion recovery MRI, were analysed with phase-sensitive imaging. Sensitivity and specificity were assessed for PRLs. RESULTS: At least one PRL was found in 22.9% of MS and 26.1% of clinically isolated syndrome (CIS) patients. Only one PRL was found elsewhere. The identification of ⩾1 PRL was the optimal cut-off and had high specificity (99.7%, confidence interval (CI) = 98.20%-99.99%) when distinguishing MS and CIS from mimics and healthy controls, but lower sensitivity (24.0%, CI = 18.9%-36.6%). All patients with a PRL showing a central vein sign (CVS) in the same lesion (n = 54) had MS or CIS, giving a specificity of 100% (CI = 98.8%-100.0%) but equally low sensitivity (21.3%, CI = 16.4%-26.81%). CONCLUSION: PRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnostic biomarker, especially when used in conjunction with the CVS.

Multi-Antigen Imaging Reveals Inflammatory DC, ADAM17 and Neprilysin as Effectors in Keloid Formation.

Keloid is an aberrant scarring process of the skin, characterized by excessive extracellular matrix synthesis and deposition. The pathogenesis of this prevalent cutaneous disorder is not fully understood; however, a persistent inflammatory process is observed. To obtain more insight into this process, we analyzed lesional, perilesional and healthy tissue using multi-antigen-analysis (MAA) in conjunction with a data mining approach. Here, we demonstrate that monocyte-derived inflammatory dendritic cells (CD1a+, CD11c+, CD14+) and activated CD4+ T lymphocytes (CD45 RO+) dominated the immune infiltration in keloids while associating with fibroblasts. In perilesional tissue, precursor immune cells were dominant in the perivascular area, suggesting that they were attracted by an immune process, potentially in the lesional area. Supporting this hypothesis, only in keloid lesions, high levels of ADAM10/17 and Neprilysin (CD10) were observed in both fibroblasts and leukocytes. The spatial proximity of these two cell types, which could be confirmed by image analysis only in lesional tissue, could be a potential factor leading to the activation of fibroblasts. Our findings provide new insight into the pathogenesis of keloid formation and reveal metalloproteinases as a target for therapeutical intervention.

Single Test to ARrive at Multiple Sclerosis (STAR-MS) diagnosis: A prospective pilot study assessing the accuracy of the central vein sign in predicting multiple sclerosis in cases of diagnostic uncertainty.

BACKGROUND: Misdiagnosis is common in multiple sclerosis (MS) as a proportion of patients present with atypical clinical/magnetic resonance imaging (MRI) findings. The central vein sign has the potential to be a non-invasive, MS-specific biomarker. OBJECTIVE: To test the accuracy of the central vein sign in predicting a diagnosis of MS in patients with diagnostic uncertainty at disease presentation using T2*-weighted, 3 T MRI. METHODS: In this prospective pilot study, we recruited individuals with symptoms unusual for MS but with brain MRI consistent with the disease, and those with a typical clinical presentation of MS whose MRI did not suggest MS. We calculated the proportion of lesions with central veins for each patient and compared the results to the eventual clinical diagnoses. The optimal central vein threshold for diagnosis was established. RESULTS: Thirty-eight patients were scanned, 35 of whom have received a clinical diagnosis. Median percentage of lesions with central veins was 51% in MS and 28% in non-MS. A threshold of 40.7% lesions with central veins resulted in 100% sensitivity and 73.9% specificity. CONCLUSION: The central vein sign assessed with a clinically available T2* scan can successfully diagnose MS in cases of diagnostic uncertainty. The central vein sign should be considered as a diagnostic biomarker in MS.

Tumour parcellation and quantification (TuPaQ): a tool for refining biomarker analysis through rapid and automated segmentation of tumour epithelium.

BACKGROUND AND AIMS: Immunohistochemistry (IHC) is an essential component of biomarker research in cancer. Automated biomarker quantification is hampered by the failure of computational algorithms to discriminate 'negative' tumour cells from 'negative' stromal cells. We sought to develop an algorithm for segmentation of tumour epithelium in colorectal cancer (CRC), irrespective of the biomarker expression in the cells. METHODS AND RESULTS: We developed tumour parcellation and quantification (TuPaQ) to segment tumour epithelium and parcellate sections into 'epithelium' and 'non-epithelium'. TuPaQ comprises image pre-processing, extraction of regions of interest (ROIs) and quantification of tumour epithelium (total area occupied by epithelium and number of nuclei in the occupied area). A total of 286 TMA cores from CRC were manually annotated and analysed using the commercial halo software to provide ground truth. The performance of TuPaQ was evaluated against the ground truth using a variety of metrics. The image size of each core was 7000 × 7000 pixels and each core was analysed in a matter of seconds. Pixel × pixel analysis showed a sensitivity of 84% and specificity of 95% in detecting epithelium. The mean tumour area obtained by TuPaQ was very close to the area quantified after manual annotation (r = 0.956, P < 0.001). Moreover, quantification of tumour nuclei by TuPaQ correlated very strongly with that of halo (r = 0.891, P < 0.001). CONCLUSION: TuPaQ is a very rapid and accurate method of separating the epithelial and stromal compartments of colorectal tumours. This will allow more accurate and objective analysis of immunohistochemistry.

Imaging gray matter with concomitant null point imaging from the phase sensitive inversion recovery sequence.

PURPOSE: To present an improved three-dimensional (3D) interleaved phase sensitive inversion recovery (PSIR) sequence including a concomitantly acquired new contrast, null point imaging (NPI), to help detect and classify abnormalities in cortical gray matter. METHODS: The 3D gradient echo PSIR images were acquired at 0.6 mm isotropic resolution on 11 multiple sclerosis (MS) patients and 9 controls subjects using a 7 Tesla (T) MRI scanner, and 2 MS patients at 3T. Cortical abnormalities were delineated on the NPI/PSIR data and later classified according to position in the cortex. RESULTS: The NPI helped detect cortical lesions within the cortical ribbon with increased, positive contrast compared with the PSIR. It also provided improved intrinsic delineation of the ribbon, increasing confidence in classifying the lesions' locations. CONCLUSION: The proposed PSIR facilitates the classification of cortical lesions by providing two T1 -weighted 3D datasets with isotropic resolution, including the NPI showing cortical lesions with clear delineation of the gray/white matter boundary and minimal partial volume effects. Magn Reson Med 76:1512-1516, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

High-resolution imaging of magnetisation transfer and nuclear Overhauser effect in the human visual cortex at 7 T.

The aim of this study was to optimise a pulse sequence for high-resolution imaging sensitive to the effects of conventional macromolecular magnetisation transfer (MT(m)) and nuclear Overhauser enhancement (NOE), and to use it to investigate variations in these parameters across the cerebral cortex. A high-spatial-resolution magnetisation transfer-prepared turbo field echo (MT-TFE) sequence was designed to have high sensitivity to MT(m) and NOE effects, whilst being robust to B0 and B1 inhomogeneities, and producing a good point spread function across the cortex. This was achieved by optimising the saturation and imaging components of the sequence using simulations based on the Bloch equations, including exchange and an image simulator. This was used to study variations in these parameters across the cortex. Using the sequence designed to be sensitive to NOE and MT(m), a variation in signals corresponding to a variation in MT(m) and NOE across the cortex, consistent with a reduction in myelination from the white matter surface to the pial surface of the cortex, was observed. In regions in which the stria was visible on T2*-weighted images, it could also be detected in signals sensitive to MT(m) and NOE. There was greater variation in signals sensitive to NOE, suggesting that the NOE signal is more sensitive to myelination. A sequence has been designed to image variations in MT(m) and NOE at high spatial resolution and has been used to investigate variations in contrast in these parameters across the cortex.

Stress during puberty boosts metabolic activation associated with fear-extinction learning in hippocampus, basal amygdala and cingulate cortex.

Adolescence is characterized by major developmental changes that may render the individual vulnerable to stress and the development of psychopathologies in a sex-specific manner. Earlier we reported lower anxiety-like behavior and higher risk-taking and novelty seeking in rats previously exposed to peri-pubertal stress. Here we studied whether peri-pubertal stress affected the acquisition and extinction of fear memories and/or the associated functional engagement of various brain regions, as assessed with 2-deoxyglucose. We showed that while peri-pubertal stress reduced freezing during the acquisition of fear memories (training) in both sexes, it had a sex-specific effect on extinction of these memories. Moreover hippocampus, basal amygdala and cingulate and motor cortices showed higher metabolic rates during extinction in rats exposed to peri-pubertal stress. Interestingly, activation of the infralimbic cortex was negatively correlated with freezing during extinction only in control males, while only males stressed during puberty showed a significant correlation between behavior during extinction and metabolic activation of hippocampus, amygdala and paraventricular nucleus. No correlations between brain activation and behavior during extinction were observed in females (control or stress). These results indicate that exposure to peri-pubertal stress affects behavior and brain metabolism when the individual is exposed to an additional stressful challenge. Some of these effects are sex-specific.

Smoothness-guided 3-D reconstruction of 2-D histological images.

This paper tackles two problems: (1) the reconstruction of 3-D volumes from 2-D post-mortem slices (e.g., histology, autoradiography, immunohistochemistry) in the absence of external reference, and (2) the quantitative evaluation of the 3-D reconstruction. We note that the quality of a reconstructed volume is usually assessed by considering the smoothness of some reconstructed structures of interest (e.g., the gray-white matter surfaces in brain images). Here we propose to use smoothness as a means to drive the reconstruction process itself. From a pair-wise rigid reconstruction of the 2-D slices, we first extract the boundaries of structures of interest. Those are then smoothed with a min-max curvature flow confined to the 2-D planes in which the slices lie. Finally, for each slice, we estimate a linear or flexible transformation from the sparse displacement field computed from the flow, which we apply to the original 2-D slices to obtain a smooth volume. In addition, we present a co-occurrence matrix-based technique to quantify the smoothness of reconstructed volumes. We discuss and validate the application of both our reconstruction approach and the smoothness measure on synthetic examples as well as real histological data.

Ratlas-LH: An MRI template of the Lister hooded rat brain with stereotaxic coordinates for neurosurgical implantations.

There is currently no brain atlas available to specifically determine stereotaxic coordinates for neurosurgery in Lister hooded rats despite the popularity of this strain for behavioural neuroscience studies in the United Kingdom and elsewhere. We have created a dataset, which we refer to as 'Ratlas-LH' (for Lister hooded). Ratlas-LH combines in vivo magnetic resonance images of the brain of young adult male Lister hooded rats with ex vivo micro-computed tomography images of the ex vivo skull, as well as a set of delineations of brain regions, adapted from the Waxholm Space Atlas of the Sprague Dawley Rat Brain. Ratlas-LH was produced with an isotropic resolution of 0.15 mm. It has been labelled in such a way as to provide a stereotaxic coordinate system for the determination of distances relative to the skull landmark of bregma. We have demonstrated that the atlas can be used to determine stereotaxic coordinates to accurately target brain regions in the Lister hooded rat brain. Ratlas-LH is freely available to facilitate neurosurgical procedures in the Lister hooded rat.

The timing mega-study: comparing a range of experiment generators, both lab-based and online.

Many researchers in the behavioral sciences depend on research software that presents stimuli, and records response times, with sub-millisecond precision. There are a large number of software packages with which to conduct these behavioral experiments and measure response times and performance of participants. Very little information is available, however, on what timing performance they achieve in practice. Here we report a wide-ranging study looking at the precision and accuracy of visual and auditory stimulus timing and response times, measured with a Black Box Toolkit. We compared a range of popular packages: PsychoPy, E-Prime®, NBS Presentation®, Psychophysics Toolbox, OpenSesame, Expyriment, Gorilla, jsPsych, Lab.js and Testable. Where possible, the packages were tested on Windows, macOS, and Ubuntu, and in a range of browsers for the online studies, to try to identify common patterns in performance. Among the lab-based experiments, Psychtoolbox, PsychoPy, Presentation and E-Prime provided the best timing, all with mean precision under 1 millisecond across the visual, audio and response measures. OpenSesame had slightly less precision across the board, but most notably in audio stimuli and Expyriment had rather poor precision. Across operating systems, the pattern was that precision was generally very slightly better under Ubuntu than Windows, and that macOS was the worst, at least for visual stimuli, for all packages. Online studies did not deliver the same level of precision as lab-based systems, with slightly more variability in all measurements. That said, PsychoPy and Gorilla, broadly the best performers, were achieving very close to millisecond precision on several browser/operating system combinations. For response times (measured using a high-performance button box), most of the packages achieved precision at least under 10 ms in all browsers, with PsychoPy achieving a precision under 3.5 ms in all. There was considerable variability between OS/browser combinations, especially in audio-visual synchrony which is the least precise aspect of the browser-based experiments. Nonetheless, the data indicate that online methods can be suitable for a wide range of studies, with due thought about the sources of variability that result. The results, from over 110,000 trials, highlight the wide range of timing qualities that can occur even in these dedicated software packages for the task. We stress the importance of scientists making their own timing validation measurements for their own stimuli and computer configuration.

Growth of white matter in the adolescent brain: role of testosterone and androgen receptor.

The growth of white matter during human adolescence shows a striking sexual dimorphism; the volume of white matter increases with age slightly in girls and steeply in boys. Here, we provide evidence supporting the role of androgen receptor (AR) in mediating the effect of testosterone on white matter. In a large sample of typically developing adolescents (n = 408, 204 males), we used magnetic resonance imaging and acquired T1-weighted and magnetization transfer ratio (MTR) images. We also measured plasma levels of testosterone and genotyped a functional polymorphism in the AR gene, namely the number of CAG repeats in exon 1 believed to be inversely proportional to the AR transcriptional activity. We found that the testosterone-related increase of white-matter volume was stronger in male adolescents with the lower versus higher number of CAG repeats in the AR gene, with testosterone explaining, respectively, 26 and 8% of variance in the volume. The MTR results suggest that this growth is not related to myelination; the MTR decreased with age in male adolescents. We speculate that testosterone affects axonal caliber rather than the thickness of the myelin sheath.

Handedness, motor skills and maturation of the corticospinal tract in the adolescent brain.

With anatomical magnetic resonance imaging, the signal intensity of the corticospinal tract (CST) at the level of the internal capsule is often paradoxically similar to that of grey matter. As shown previously in histological studies, this is likely due to the presence of very large axons. We measured the apparent grey-matter density (aGMd) of the putative CST (pCST) in a large cohort of adolescents (n = 409, aged 12-18 years). We tested the following hypotheses: (1) The aGMd in the pCST shows a hemispheric asymmetry that is, in turn, related to hand preference; (2) the maturation of the CST during adolescence differs between both sexes, due to the influence of testosterone; (3) variations in aGMd in the pCST reflect inter-individual differences in manual skills. We confirmed the first two predictions. Thus, we found a strong left > right hemispheric asymmetry in aGMd that was, on average, less marked in the 40 left-handed subjects. Apparent GMd in the pCST increased with age in adolescent males but not females, and this was particularly related to rising plasma levels of testosterone in male adolescents. This finding is compatible with the idea that testosterone influences axonal calibre rather than myelination. The third prediction, namely that of a relationship between age-related changes in manual skills and maturation of the pCST, was not confirmed. We conclude that the leftward asymmetry of the pCST may reflect an early established asymmetry in the number of large corticomotoneuronal fibres in the pCST.

What is the difference between irony and sarcasm? An fMRI study.

Verbal irony is a figure of speech that communicates the opposite of what is said, while sarcasm is a form of irony that is directed at a person, with the intent to criticise. The current study used functional magnetic resonance imaging (fMRI) with the aim of mapping the neural networks involved in the processing of sarcastic and non-sarcastic irony. Participants read short texts describing an interaction between two characters, which ended in either a literal, sarcastic, or non-sarcastic ironic comment. Results showed that the mentalising network (mPFC) and semantic network (IFG) were more activated for non-sarcastic irony than for literal controls. This would suggest that interpreting this kind of language involves understanding that the speaker does not mean what they literally say, as well as processes involved in conflict detection and resolution. Sarcastic irony recruited more of the semantic network, as well as areas associated with humour appreciation and subcortical structures, indicating that more complex neural mechanisms underlie the comprehension of sarcastic versus non-sarcastic irony.

Fusing fine-tuned deep features for skin lesion classification.

Malignant melanoma is one of the most aggressive forms of skin cancer. Early detection is important as it significantly improves survival rates. Consequently, accurate discrimination of malignant skin lesions from benign lesions such as seborrheic keratoses or benign nevi is crucial, while accurate computerised classification of skin lesion images is of great interest to support diagnosis. In this paper, we propose a fully automatic computerised method to classify skin lesions from dermoscopic images. Our approach is based on a novel ensemble scheme for convolutional neural networks (CNNs) that combines intra-architecture and inter-architecture network fusion. The proposed method consists of multiple sets of CNNs of different architecture that represent different feature abstraction levels. Each set of CNNs consists of a number of pre-trained networks that have identical architecture but are fine-tuned on dermoscopic skin lesion images with different settings. The deep features of each network were used to train different support vector machine classifiers. Finally, the average prediction probability classification vectors from different sets are fused to provide the final prediction. Evaluated on the 600 test images of the ISIC 2017 skin lesion classification challenge, the proposed algorithm yields an area under receiver operating characteristic curve of 87.3% for melanoma classification and an area under receiver operating characteristic curve of 95.5% for seborrheic keratosis classification, outperforming the top-ranked methods of the challenge while being simpler compared to them. The obtained results convincingly demonstrate our proposed approach to represent a reliable and robust method for feature extraction, model fusion and classification of dermoscopic skin lesion images.

Evaluation of the Central Vein Sign as a Diagnostic Imaging Biomarker in Multiple Sclerosis.

Importance: The central vein sign has been proposed as a specific imaging biomarker for distinguishing between multiple sclerosis (MS) and not MS, mainly based on findings from ultrahigh-field magnetic resonance imaging (MRI) studies. The diagnostic value of the central vein sign in a multicenter setting with a variety of clinical 3 tesla (T) MRI protocols, however, remains unknown. Objective: To evaluate the sensitivity and specificity of various central vein sign lesion criteria for differentiating MS from non-MS conditions using 3T brain MRI with various commonly used pulse sequences. Design, Setting, and Participants: This large multicenter, cross-sectional study enrolled participants (n = 648) of ongoing observational studies and patients included in neuroimaging research databases of 8 neuroimaging centers in Europe. Patient enrollment and MRI data collection were performed between January 1, 2010, and November 30, 2016. Data analysis was conducted between January 1, 2016, and April 30, 2018. Investigators were blinded to participant diagnosis by a novel blinding procedure. Main Outcomes and Measures: Occurrence of central vein sign was detected on 3T T2*-weighted or susceptibility-weighted imaging. Sensitivity and specificity were assessed for these MRI sequences and for different central vein sign lesion criteria, which were defined by the proportion of lesions with central vein sign or by absolute numbers of lesions with central vein sign. Results: A total of 606 participants were included in the study after exclusion of 42 participants. Among the 606 participants, 413 (68.2%) were women. Patients with clinically isolated syndrome and relapsing-remitting MS (RRMS) included 235 women (66.6%) and had a median (range) age of 37 (14.7-61.4) years, a median (range) disease duration of 2 (0-33) years, and a median (range) Expanded Disability Status Scale score of 1.5 (0-6.5). Patients without MS included 178 women (70.4%) and had a median (range) age of 54 (18-83) years. A total of 4447 lesions were analyzed in a total of 487 patients: 690 lesions in 98 participants with clinically isolated syndrome, 2815 lesions in 225 participants with RRMS, 54 lesions in 13 participants with neuromyelitis optica spectrum disorder, 54 lesions in 14 participants with systemic lupus erythematosus, 121 lesions in 29 participants with migraine or cluster headache, 240 lesions in 20 participants with diabetes, and 473 lesions in 88 participants with other types of small-vessel disease. The sensitivity was 68.1% and specificity was 82.9% for distinguishing MS from not MS using a 35% central vein sign proportion threshold. The 3 central vein sign lesion criteria had a sensitivity of 61.9% and specificity of 89.0%. Sensitivity was higher when an optimized T2*-weighted sequence was used. Conclusions and Relevance: In this study, use of the central vein sign at 3T MRI yielded a high specificity and a moderate sensitivity in differentiating MS from not MS; international, multicenter studies may be needed to ascertain whether the central vein sign-based criteria can accurately detect MS.

The MRI central vein marker; differentiating PPMS from RRMS and ischemic SVD.

OBJECTIVE: To determine whether the assessment of brain white matter lesion (WML) central veins differentiate patients with primary progressive MS (PPMS) from relapsing-remitting MS (RRMS) and ischemic small vessel disease (SVD) using 3T MRI. METHODS: In this cross-sectional study, 71 patients with PPMS, RRMS, and SVD were imaged using a T2*-weighted sequence. Two blinded raters identified the total number of WMLs, proportion of WMLs in periventricular, deep white matter (DWM) and juxtacortical regions, and proportion of WMLs with central veins in all patient groups. The proportions were compared between disease groups, including effect sizes. MS or SVD was categorized using a threshold of ≥40% WMLs with central veins as indicative of MS. Interrater and intrarater reproducibility was calculated. RESULTS: The mean proportion of WMLs with central veins was 68.4% in PPMS, 74.3% in RRMS, and 4.7% in SVD. The difference in proportions between PPMS and SVD groups was significant (p < 0.0005; effect size: 3.8) but not significant between MS subtypes (p = 0.3; effect size: 0.29). Distribution of WMLs was similar across both MS groups, but despite SVD patients having more DWM lesions than PPMS patients, proportions of WMLs with central veins remained low (2.75% in SVD; 62.5% in PPMS). Interrater and intrarater reproducibility comparing proportions of WMLs with central veins across all patients was 0.86 and 0.90, respectively. Level of agreement between the proportion of WML central veins and established diagnosis was 0.84 and 0.82 for each rater. CONCLUSIONS: WML central veins could be used to differentiate PPMS from SVD but not between MS subtypes.

Night and day variations of sleep in patients with disorders of consciousness.

Brain injuries substantially change the entire landscape of oscillatory dynamics and render detection of typical sleep patterns difficult. Yet, sleep is characterized not only by specific EEG waveforms, but also by its circadian organization. In the present study we investigated whether brain dynamics of patients with disorders of consciousness systematically change between day and night. We recorded ~24 h EEG at the bedside of 18 patients diagnosed to be vigilant but unaware (Unresponsive Wakefulness Syndrome) and 17 patients revealing signs of fluctuating consciousness (Minimally Conscious State). The day-to-night changes in (i) spectral power, (ii) sleep-specific oscillatory patterns and (iii) signal complexity were analyzed and compared to 26 healthy control subjects. Surprisingly, the prevalence of sleep spindles and slow waves did not systematically vary between day and night in patients, whereas day-night changes in EEG power spectra and signal complexity were revealed in minimally conscious but not unaware patients.

Piecewise affine registration of biological images for volume reconstruction.

This manuscript tackles the reconstruction of 3-D volumes via mono-modal registration of series of 2-D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover's distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise.

Adaptive elastic segmentation of brain MRI via shape-model-guided evolutionary programming.

This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequent quantitative analysis. We propose a new hybrid strategy that combines a general elastic template matching approach and an evolutionary heuristic. The evolutionary algorithm uses prior statistical information about the shape of the target structure to control the behavior of a number of deformable templates. Each template, modeled in the form of a B-spline, is warped in a potential field which is itself dynamically adapted. Such a hybrid scheme proves to be promising: by maintaining a population of templates, we cover a large domain of the solution space under the global guidance of the evolutionary heuristic, and thoroughly explore interesting areas. We address key issues of automated image segmentation systems. The potential fields are initially designed based on the spatial features of the edges in the input image, and are subjected to spatially adaptive diffusion to guarantee the deformation of the template. This also improves its global consistency and convergence speed. The deformation algorithm can modify the internal structure of the templates to allow a better match. We investigate in detail the preprocessing phase that the images undergo before they can be used more effectively in the iterative elastic matching procedure: a texture classifier, trained via linear discriminant analysis of a learning set, is used to enhance the contrast of the target structure with respect to surrounding tissues. We show how these techniques interact within a statistically driven evolutionary scheme to achieve a better tradeoff between template flexibility and sensitivity to noise and outliers. We focus on understanding the features of template matching that are most beneficial in terms of the achieved match. Examples from simulated and real image data are discussed, with considerations of algorithmic efficiency.

Visualization of nigrosome 1 and its loss in PD: pathoanatomical correlation and in vivo 7 T MRI.

OBJECTIVE: This study assessed whether high-resolution 7 T MRI allowed direct in vivo visualization of nigrosomes, substructures of the substantia nigra pars compacta (SNpc) undergoing the greatest and earliest dopaminergic cell loss in Parkinson disease (PD), and whether any disease-specific changes could be detected in patients with PD. METHODS: Postmortem (PM) midbrains, 2 from healthy controls (HCs) and 1 from a patient with PD, were scanned with high-resolution T2*-weighted MRI scans, sectioned, and stained for iron and neuromelanin (Perl), TH, and calbindin. To confirm the identification of nigrosomes in vivo on 7 T T2*-weighted scans, we assessed colocalization with neuromelanin-sensitive T1-weighted scans. We then assessed the ability to depict PD pathology on in vivo T2*-weighted scans by comparing data from 10 patients with PD and 8 age- and sex-matched HCs. RESULTS: A hyperintense, ovoid area within the dorsolateral border of the otherwise hypointense SNpc was identified in the HC brains on in vivo and PM T2*-weighted MRI. Location, size, shape, and staining characteristics conform to nigrosome 1. Blinded assessment by 2 neuroradiologists showed consistent bilateral absence of this nigrosome feature in all 10 patients with PD, and bilateral presence in 7/8 HC. CONCLUSIONS: In vivo and PM MRI with histologic correlation demonstrates that high-resolution 7 T MRI can directly visualize nigrosome 1. The absence of nigrosome 1 in the SNpc on MRI scans might prove useful in developing a neuroimaging diagnostic test for PD.