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1.
J Athl Train ; 2021 Mar 31.
Artigo em Inglês | MEDLINE | ID: mdl-33787883

RESUMO

CONTEXT: Hypertrophy of the Infrapatellar Fat Pad (IFP) in idiopathic knee osteoarthritis has been linked to deleterious synovial changes and joint pain related to mechanical tissue impingement; yet, little is known regarding the IFP's volumetric changes following anterior cruciate ligament reconstruction (ACLR). OBJECTIVE: To examine changes in IFP volume between 6 and 12 months following ACLR and determine associations between patient-reported outcomes and IFP volume at each time point, as well as volume change over time. In a subset of individuals, we examined inter-limb IFP volume differences 12 months post-ACLR. STUDY DESIGN: Prospective cohort study Setting: Laboratory Patients or Other Participants: We included 26 participants (13 females, 13 males, 21.88±3.58 years, 23.82±2.21 kg/m2) for our primary aims and 13 of those participants (8 females, 5 males, 21.15±3.85 years, 23.01±2.01 kg/m2) for our exploratory aim. MAIN OUTCOME MEASURE(S): Using magnetic resonance imaging, we evaluated IFP volume change between 6 and 12 months post-ACLR in the ACLR limb and between-limb differences at 12 months in a subset of participants. International Knee Documentation Committee subjective knee evaluation (IKDC) scores were collected at 6-month and 12-month follow-ups and associations between IFP volume and patient-reported outcomes were determined. RESULTS: IFP volume in the ACLR limb significantly increased from 6 (19.67±6.30 cm3) to 12 (21.26±6.91 cm3) months post-ACLR. Greater increases of IFP volume between 6 and 12 months significantly associated with better 6-month IKDC scores (r=0.44, P=0.03). IFP volume was significantly greater in the uninjured limb (22.71±7.87 cm3) compared to the ACLR limb (20.75±9.03 cm3) 12 months post-ACLR. CONCLUSIONS: IFP volume increased between 6 and 12 months post-ACLR; however, the IFP volume of the ACLR limb remained smaller than the uninjured limb at 12-months. Additionally, those with better knee function 6 months post-ACLR demonstrated greater increases in IFP volume between 6 and 12 months post-ACLR. This suggests greater IFP volumes may play a role in long-term joint health following ACLR.

2.
IEEE Trans Med Imaging ; 40(5): 1363-1376, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33507867

RESUMO

To better understand early brain development in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods have achieved state-of-the-art performance; h owever, one of the major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners. To promote methodological development in the community, the iSeg-2019 challenge (http://iseg2019.web.unc.edu) provides a set of 6-month infant subjects from multiple sites with different protocols/scanners for the participating methods. T raining/validation subjects are from UNC (MAP) and testing subjects are from UNC/UMN (BCP), Stanford University, and Emory University. By the time of writing, there are 30 automatic segmentation methods participated in the iSeg-2019. In this article, 8 top-ranked methods were reviewed by detailing their pipelines/implementations, presenting experimental results, and evaluating performance across different sites in terms of whole brain, regions of interest, and gyral landmark curves. We further pointed out their limitations and possible directions for addressing the multi-site issue. We find that multi-site consistency is still an open issue. We hope that the multi-site dataset in the iSeg-2019 and this review article will attract more researchers to address the challenging and critical multi-site issue in practice.

3.
Neuroimage ; 218: 116978, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32447015

RESUMO

Perivascular spaces (PVSs) are fluid-filled spaces surrounding penetrating blood vessels in the brain and are an integral pathway of the glymphatic system. A PVS and the enclosed blood vessel are commonly visualized as a single vessel-like complex (denoted as PVSV) in high-resolution MRI images. Quantitative characterization of the PVSV morphology in MRI images in healthy subjects may serve as a reference for detecting disease related PVS and/or blood vessel alterations in patients with brain diseases. To this end, we evaluated the age dependences, spatial heterogeneities, and dynamic properties of PVSV morphological features in 45 healthy subjects (21-55 years old), using an ultra-high-resolution three-dimensional transverse relaxation time weighted MRI sequence (0.41 â€‹× â€‹0.41 â€‹× â€‹0.4 â€‹mm3) at 7T. Quantitative PVSV parameters, including apparent diameter, count, volume fraction (VF), and relative contrast to noise ratio (rCNR) were calculated in the white matter and subcortical structures. Dynamic changes were induced by carbogen breathing which are known to induce vasodilation and increase the blood oxygenation level in the brain. PVSV count and VF significantly increased with age in basal ganglia (BG), so did rCNR in BG, midbrain, and white matter (WM). Apparent PVSV diameter also showed a positive association with age in the three brain regions, although it did not reach statistical significance. The PVSV VF and count showed large inter-subject variations, with coefficients of variation ranging from 0.17 to 0.74 after regressing out age and gender effects. Both apparent diameter and VF exhibited significant spatial heterogeneity, which cannot be explained solely by radio-frequency field inhomogeneities. Carbogen breathing significantly increased VF in BG and WM, and rCNR in thalamus, BG, and WM compared to air breathing. Our results are consistent with gradual dilation of PVSs with age in healthy adults. The PVSV morphology exhibited spatial heterogeneity and large inter-subject variations and changed during carbogen breathing compared to air breathing.

4.
J Comput Assist Tomogr ; 44(1): 43-46, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31789683

RESUMO

OBJECTIVE: The objective of this study was to investigate the frequency of hippocampal sulcus remnants (HSRs) in nonelderly adults using ultra-high-resolution 7T magnetic resonance (MR) images and their imaging features. METHODS: A total of 33 healthy adults underwent 7T MR, and multiplanar images of 66 temporal lobes were reviewed independently by 2 neuroradiologists. The detectability of the HSR was calculated. In addition, the interobserver agreement on the rating scale was evaluated using the κ statistic. RESULTS: Both observers identified HSRs with 7T MR images in all subjects. Excellent interobserver agreement was shown (κ = 1.0). The shape of HSRs was variable (spot-like, curvilinear, ovoid, or beaded appearance). Volumes of the HSRs were not correlated with age. CONCLUSIONS: Hippocampal sulcus remnants are commonly seen in healthy nonelderly adults using 7T MR imaging. Accurate diagnosis of HSR based on the microanatomy of hippocampus makes it easier to differentiate them from lesions, and it may help prevent unnecessary treatment.


Assuntos
Hipocampo/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Adulto , Algoritmos , Feminino , Voluntários Saudáveis , Humanos , Masculino , Pessoa de Meia-Idade , Variações Dependentes do Observador , Adulto Jovem
5.
J Bone Miner Res ; 35(1): 106-115, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-31509274

RESUMO

Marrow adipose tissue (MAT) and its relevance to skeletal health during caloric restriction (CR) is unknown: It remains unclear whether exercise, which is anabolic to bone in a calorie-replete state, alters bone or MAT in CR. We hypothesized that response of bone and MAT to exercise in CR differs from the calorie-replete state. Ten-week-old female B6 mice fed a regular diet (RD) or 30% CR diet were allocated to sedentary (RD, CR, n = 10/group) or running exercise (RD-E, CR-E, n = 7/group). After 6 weeks, CR mice weighed 20% less than RD, p < 0.001; exercise did not affect weight. Femoral bone volume (BV) via 3D MRI was 20% lower in CR versus RD (p < 0.0001). CR was associated with decreased bone by µCT: Tb.Th was 16% less in CR versus RD, p < 0.003, Ct.Th was 5% less, p < 0.07. In CR-E, Tb.Th was 40% less than RD-E, p < 0.0001. Exercise increased Tb.Th in RD (+23% RD-E versus RD, p < 0.003) but failed to do so in CR. Cortical porosity increased after exercise in CR (+28%, p = 0.04), suggesting exercise during CR is deleterious to bone. In terms of bone fat, metaphyseal MAT/ BV rose 159% in CR versus RD, p = 0.003 via 3D MRI. Exercise decreased MAT/BV by 52% in RD, p < 0.05, and also suppressed MAT in CR (-121%, p = 0.047). Histomorphometric analysis of adipocyte area correlated with MAT by MRI (R2 = 0.6233, p < 0.0001). With respect to bone, TRAP and Sost mRNA were reduced in CR. Intriguingly, the repressed Sost in CR rose with exercise and may underlie the failure of CR-bone quantity to increase in response to exercise. Notably, CD36, a marker of fatty acid uptake, rose 4088% in CR (p < 0.01 versus RD), suggesting that basal increases in MAT during calorie restriction serve to supply local energy needs and are depleted during exercise with a negative impact on bone. © 2019 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.

6.
Proc IEEE Int Symp Biomed Imaging ; 2019: 999-1002, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31681456

RESUMO

Skull stripping for brain MR images is a basic segmentation task. Although many methods have been proposed, most of them focused mainly on the adult MR images. Skull stripping for infant MR images is more challenging due to the small size and dynamic intensity changes of brain tissues during the early ages. In this paper, we propose a novel CNN based framework to robustly extract brain region from infant MR image without any human assistance. Specifically, we propose a simplified but more robust flattened residual network architecture (FRnet). We also introduce a new boundary loss function to highlight ambiguous and low contrast regions between brain and non-brain regions. To make the whole framework more robust to MR images with different imaging quality, we further introduce an artifact simulator for data augmentation. We have trained and tested our proposed framework on a large dataset (N=343), covering newborns to 48-month-olds, and obtained performance better than the state-of-the-art methods in all age groups.

7.
Neuroimage ; 195: 463-474, 2019 07 15.
Artigo em Inglês | MEDLINE | ID: mdl-30935910

RESUMO

Pathological changes of penetrating arteries (PA) within the centrum semiovale is an important contributing factor of cerebral small vessel disease (SVD). However, quantitative characterization of the PAs remains challenging due to their sub-voxel sizes. Here, we proposed a Model-based Analysis of Complex Difference images (MACD) of phase contrast MRI capable of measuring the mean velocities (vmean), diameters (D), and volume flow rates (VFR) of PAs without contamination from neighboring static tissues at 7 T. Simulation, phantom and in vivo studies were performed to evaluate the reproducibility and errors of the proposed method. For comparison, a Model-based Analysis of Phase difference images (MAP) was also carried out in the simulation. The proposed MACD analysis approach was applied in vivo to study the age dependence of PA properties in healthy subjects between 21 and 55 years old. Simulation showed that our proposed MACD approach yielded smaller errors than MAP, with errors increasing at lower velocities and diameters for both methods. In the phantom study, errors of the MACD-derived vmean, D, and VFR were ≤20% of their true values when vmean≥1cm/s and similar at different spatial resolutions. On the other hand, errors of the uncorrected apparent velocities were 24-60% and depended strongly on voxel size. The MACD errors linearly increased with the angle (α) between the vessel and slice normal direction at α ≤ 2° but remained almost constant at larger α. Results of the in vivo studies showed that the coefficients of repeatability for vmean, D, and VFR for PAs with α = 0° were 0.67 cm/s, 0.060 mm, and 0.067 mm3/s, respectively. No significant age dependence was found for the number, vmean, D, and VFR of PAs. The mean vmean, D, and VFR over all PAs with α = 0° were 1.79 ±â€¯0.62 cm/s, 0.17 ±â€¯0.05 mm, and 0.36 ±â€¯0.18 mm3/s, respectively. Quantitative measurements of PAs with the MACD method may serve as a useful tool for illuminating the vascular pathology in cerebral SVD.


Assuntos
Doenças de Pequenos Vasos Cerebrais/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , Imagem por Ressonância Magnética/métodos , Adulto , Artérias/diagnóstico por imagem , Artérias/patologia , Doenças de Pequenos Vasos Cerebrais/patologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Adulto Jovem
8.
IEEE Access ; 7: 18382-18391, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30956927

RESUMO

Perivascular spaces (PVS) in the human brain are related to various brain diseases. However, it is difficult to quantify them due to their thin and blurry appearance. In this paper, we introduce a deep-learning-based method, which can enhance a magnetic resonance (MR) image to better visualize the PVS. To accurately predict the enhanced image, we propose a very deep 3D convolutional neural network that contains densely connected networks with skip connections. The proposed networks can utilize rich contextual information derived from low-level to high-level features and effectively alleviate the gradient vanishing problem caused by the deep layers. The proposed method is evaluated on 17 7T MR images by a twofold cross-validation. The experiments show that our proposed network is much more effective to enhance the PVS than the previous PVS enhancement methods.

10.
Med Image Anal ; 46: 106-117, 2018 05.
Artigo em Inglês | MEDLINE | ID: mdl-29518675

RESUMO

Accurate segmentation of perivascular spaces (PVSs) is an important step for quantitative study of PVS morphology. However, since PVSs are the thin tubular structures with relatively low contrast and also the number of PVSs is often large, it is challenging and time-consuming for manual delineation of PVSs. Although several automatic/semi-automatic methods, especially the traditional learning-based approaches, have been proposed for segmentation of 3D PVSs, their performance often depends on the hand-crafted image features, as well as sophisticated preprocessing operations prior to segmentation (e.g., specially defined regions-of-interest (ROIs)). In this paper, a novel fully convolutional neural network (FCN) with no requirement of any specified hand-crafted features and ROIs is proposed for efficient segmentation of PVSs. Particularly, the original T2-weighted 7T magnetic resonance (MR) images are first filtered via a non-local Haar-transform-based line singularity representation method to enhance the thin tubular structures. Both the original and enhanced MR images are used as multi-channel inputs to complementarily provide detailed image information and enhanced tubular structural information for the localization of PVSs. Multi-scale features are then automatically learned to characterize the spatial associations between PVSs and adjacent brain tissues. Finally, the produced PVS probability maps are recursively loaded into the network as an additional channel of inputs to provide the auxiliary contextual information for further refining the segmentation results. The proposed multi-channel multi-scale FCN has been evaluated on the 7T brain MR images scanned from 20 subjects. The experimental results show its superior performance compared with several state-of-the-art methods.


Assuntos
Encéfalo/diagnóstico por imagem , Imageamento Tridimensional/métodos , Sistema Linfático/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Redes Neurais de Computação , Reconhecimento Automatizado de Padrão/métodos , Algoritmos , Humanos , Aumento da Imagem/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade
11.
Sci Rep ; 7(1): 8569, 2017 08 17.
Artigo em Inglês | MEDLINE | ID: mdl-28819140

RESUMO

Perivascular spaces (PVSs) in brain have a close relationship with typical neurological diseases. The quantitative studies of PVSs are meaningful but usually difficult, due to their thin and weak signals and also background noise in the 7 T brain magnetic resonance images (MRI). To clearly distinguish the PVSs in the 7 T MRI, we propose a novel PVS enhancement method based on the Haar transform of non-local cubes. Specifically, we extract a certain number of cubes from a small neighbor to form a cube group, and then perform Haar transform on each cube group. The Haar transform coefficients are processed using a nonlinear function to amplify the weak signals relevant to the PVSs and to suppress the noise. The enhanced image is reconstructed using the inverse Haar transform of the processed coefficients. Finally, we perform a block-matching 4D filtering on the enhanced image to further remove any remaining noise, and thus obtain an enhanced and denoised 7 T MRI for PVS segmentation. We apply two existing methods to complete PVS segmentation, i.e., (1) vesselness-thresholding and (2) random forest classification. The experimental results show that the PVS segmentation performances can be significantly improved by using the enhanced and denoised 7 T MRI.


Assuntos
Encéfalo/diagnóstico por imagem , Aumento da Imagem/métodos , Processamento de Imagem Assistida por Computador/métodos , Imagem por Ressonância Magnética/métodos , Algoritmos , Encéfalo/irrigação sanguínea , Humanos , Imageamento Tridimensional/métodos , Reprodutibilidade dos Testes
12.
J Bone Miner Res ; 32(8): 1692-1702, 2017 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-28436105

RESUMO

The relationship between marrow adipose tissue (MAT) and bone health is poorly understood. We used running exercise to ask whether obesity-associated MAT can be attenuated via exercise and whether this correlates with gains in bone quantity and quality. C57BL/6 mice were divided into diet-induced obesity (DIO, n = 14) versus low-fat diet (LFD, n = 14). After 3 months, 16-week-old mice were allocated to an exercise intervention (LFD-E, DIO-E) or a control group (LFD, DIO) for 6 weeks (4 groups, n = 7/group). Marrow adipocyte area was 44% higher with obesity (p < 0.0001) and after exercise 33% lower in LFD (p < 0.0001) and 39% lower in DIO (p < 0.0001). In LFD, exercise did not affect adipocyte number; however, in DIO, the adipocyte number was 56% lower (p < 0.0001). MAT was 44% higher in DIO measured by osmium-µCT, whereas exercise associated with reduced MAT (-23% in LFD, -48% in DIO, p < 0.05). MAT was additionally quantified by 9.4TMRI, and correlated with osmium-µCT (r = 0.645; p < 0.01). Consistent with higher lipid beta oxidation, perilipin 3 (PLIN3) rose with exercise in tibial mRNA (+92% in LFD, +60% in DIO, p < 0.05). Tibial µCT-derived trabecular bone volume (BV/TV) was not influenced by DIO but responded to exercise with an increase of 19% (p < 0.001). DIO was associated with higher cortical periosteal and endosteal volumes of 15% (p = 0.012) and 35% (p < 0.01), respectively, but Ct.Ar/Tt.Ar was lower by 2.4% (p < 0.05). There was a trend for higher stiffness (N/m) in DIO, and exercise augmented this further. In conclusion, obesity associated with increases in marrow lipid-measured by osmium-µCT and MRI-and partially due to an increase in adipocyte size, suggesting increased lipid uptake into preexisting adipocytes. Exercise associated with smaller adipocytes and less bone lipid, likely invoking increased ß-oxidation and basal lipolysis as evidenced by higher levels of PLIN3. © 2017 American Society for Bone and Mineral Research.


Assuntos
Adipócitos/metabolismo , Tecido Adiposo/metabolismo , Células da Medula Óssea/metabolismo , Lipólise , Obesidade/metabolismo , Condicionamento Físico Animal , Microtomografia por Raio-X , Tecido Adiposo/diagnóstico por imagem , Animais , Gorduras na Dieta/efeitos adversos , Gorduras na Dieta/farmacologia , Feminino , Camundongos , Obesidade/induzido quimicamente , Obesidade/diagnóstico por imagem , Obesidade/fisiopatologia
13.
IEEE Trans Biomed Eng ; 64(12): 2803-2812, 2017 12.
Artigo em Inglês | MEDLINE | ID: mdl-28362579

RESUMO

OBJECTIVE: The goal of this paper is to automatically segment perivascular spaces (PVSs) in brain from high-resolution 7T magnetic resonance (MR) images. METHODS: We propose a structured-learning-based segmentation framework to extract the PVSs from high-resolution 7T MR images. Specifically, we integrate three types of vascular filter responses into a structured random forest for classifying voxels into two categories, i.e., PVS and background. In addition, we propose a novel entropy-based sampling strategy to extract informative samples in the background for training an explicit classification model. Since the vascular filters can extract various vascular features, even thin and low-contrast structures can be effectively extracted from noisy backgrounds. Moreover, continuous and smooth segmentation results can be obtained by utilizing patch-based structured labels. RESULTS: The performance of our proposed method is evaluated on 19 subjects with 7T MR images, with the Dice similarity coefficient reaching 66%. CONCLUSION: The joint use of entropy-based sampling strategy, vascular features, and structured learning can improve the segmentation accuracy. SIGNIFICANCE: Instead of manual annotation, our method provides an automatic way for PVS segmentation. Moreover, our method can be potentially used for other vascular structure segmentation because of its data-driven property.


Assuntos
Encéfalo/diagnóstico por imagem , Imageamento Tridimensional/métodos , Imagem por Ressonância Magnética/métodos , Árvores de Decisões , Humanos , Aprendizado de Máquina
14.
Magn Reson Med ; 78(5): 1933-1943, 2017 11.
Artigo em Inglês | MEDLINE | ID: mdl-28097689

RESUMO

PURPOSE: To evaluate the magnetic susceptibility properties of different anatomical structures within the knee joint using quantitative susceptibility mapping (QSM). METHODS: A collagen tissue model was simulated and ex vivo animal cartilage experiments were conducted at 9.4 Tesla (T) to evaluate the B0 orientation-dependent magnetic susceptibility contrast observed in cartilage. Furthermore, nine volunteers (six healthy subjects without knee pain history and three patients with known knee injury, between 29 and 58 years old) were scanned using gradient-echo acquisitions on a high-field 7T MR scanner. Susceptibility values of different tissues were quantified and diseased cartilage and meniscus were compared against that of healthy volunteers. RESULTS: Simulation and ex vivo animal cartilage experiments demonstrated that collagen fibrils exhibit an anisotropic susceptibility. A gradual change of magnetic susceptibility was observed in the articular cartilage from the superficial zone to the deep zone, forming a multilayer ultrastructure consistent with anisotropy of collagen fibrils. Meniscal tears caused a clear reduction of susceptibility contrast between the injured meniscus and surrounding cartilage illustrated by a loss of the sharp boundaries between the two. Moreover, QSM showed more dramatic contrast in the focal degenerated articular cartilage than R2* mapping. CONCLUSION: The arrangement of the collagen fibrils is significant, and likely the most dominant source of magnetic susceptibility anisotropy. Quantitative susceptibility mapping offers a means to characterize magnetic susceptibility properties of tissues in the knee joint. It is sensitive to collagen damage or degeneration and may be useful for evaluating the status of knee diseases, such as meniscal tears and cartilage disease. Magn Reson Med 78:1933-1943, 2017. © 2017 International Society for Magnetic Resonance in Medicine.


Assuntos
Articulação do Joelho/diagnóstico por imagem , Articulação do Joelho/fisiologia , Imagem por Ressonância Magnética/métodos , Adulto , Algoritmos , Animais , Anisotropia , Cartilagem Articular/diagnóstico por imagem , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos Biológicos
15.
PLoS One ; 11(8): e0161392, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27560146

RESUMO

PURPOSE: To investigate the aberrant functional connectivity of the default mode network (DMN) in patients with end-stage renal disease (ESRD) and their clinical relevance. MATERIALS AND METHODS: Resting-state functional MRI data were collected from 31 patients with ESRD (24 men, 24-61 years) and 31 age- and gender-matched healthy controls (HCs, 21 men, 26-61years). A whole-brain seed-based functional connectivity analysis of these collected R-fMRI data was performed by locating the seeds in the posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC) to investigate the functional connectivity of the posterior and anterior DMN over the whole brain, respectively. RESULTS: Compared to the HCs, the patients exhibited significantly decreased functional connectivity with the PCC in the left middle temporal gyrus, the right anterior cingulate gyrus, and the bilateral medial superior frontal gyrus. For the vmPFC seed, only the right thalamus showed significantly decreased functional connectivity in the patients with ESRD compared to HCs. Interestingly, functional connectivity between the PCC and right medial superior frontal gyrus exhibited a significantly positive correlation with the hemoglobin level in the patients. CONCLUSION: Our findings suggest a spatially specific disruption of functional connectivity in the DMN in patients with ESRD, thereby providing novel insights into our understanding of the neurophysiology mechanism that underlies the disease.


Assuntos
Encéfalo/fisiopatologia , Falência Renal Crônica/fisiopatologia , Vias Neurais/fisiopatologia , Adulto , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Estudos de Casos e Controles , Feminino , Lobo Frontal , Giro do Cíngulo/fisiopatologia , Humanos , Processamento de Imagem Assistida por Computador , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Descanso
16.
IEEE Trans Med Imaging ; 35(9): 2085-97, 2016 09.
Artigo em Inglês | MEDLINE | ID: mdl-27046894

RESUMO

In the recent MRI scanning, ultra-high-field (7T) MR imaging provides higher resolution and better tissue contrast compared to routine 3T MRI, which may help in more accurate and early brain diseases diagnosis. However, currently, 7T MRI scanners are more expensive and less available at clinical and research centers. These motivate us to propose a method for the reconstruction of images close to the quality of 7T MRI, called 7T-like images, from 3T MRI, to improve the quality in terms of resolution and contrast. By doing so, the post-processing tasks, such as tissue segmentation, can be done more accurately and brain tissues details can be seen with higher resolution and contrast. To do this, we have acquired a unique dataset which includes paired 3T and 7T images scanned from same subjects, and then propose a hierarchical reconstruction based on group sparsity in a novel multi-level Canonical Correlation Analysis (CCA) space, to improve the quality of 3T MR image to be 7T-like MRI. First, overlapping patches are extracted from the input 3T MR image. Then, by extracting the most similar patches from all the aligned 3T and 7T images in the training set, the paired 3T and 7T dictionaries are constructed for each patch. It is worth noting that, for the training, we use pairs of 3T and 7T MR images from each training subject. Then, we propose multi-level CCA to map the paired 3T and 7T patch sets to a common space to increase their correlations. In such space, each input 3T MRI patch is sparsely represented by the 3T dictionary and then the obtained sparse coefficients are used together with the corresponding 7T dictionary to reconstruct the 7T-like patch. Also, to have the structural consistency between adjacent patches, the group sparsity is employed. This reconstruction is performed with changing patch sizes in a hierarchical framework. Experiments have been done using 13 subjects with both 3T and 7T MR images. The results show that our method outperforms previous methods and is able to recover better structural details. Also, to place our proposed method in a medical application context, we evaluated the influence of post-processing methods such as brain tissue segmentation on the reconstructed 7T-like MR images. Results show that our 7T-like images lead to higher accuracy in segmentation of white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and skull, compared to segmentation of 3T MR images.


Assuntos
Imagem por Ressonância Magnética , Encéfalo , Humanos
17.
Neuroimage ; 134: 223-235, 2016 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-27046107

RESUMO

Quantitative study of perivascular spaces (PVSs) in brain magnetic resonance (MR) images is important for understanding the brain lymphatic system and its relationship with neurological diseases. One of the major challenges is the accurate extraction of PVSs that have very thin tubular structures with various directions in three-dimensional (3D) MR images. In this paper, we propose a learning-based PVS segmentation method to address this challenge. Specifically, we first determine a region of interest (ROI) by using the anatomical brain structure and the vesselness information derived from eigenvalues of image derivatives. Then, in the ROI, we extract a number of randomized Haar features which are normalized with respect to the principal directions of the underlying image derivatives. The classifier is trained by the random forest model that can effectively learn both discriminative features and classifier parameters to maximize the information gain. Finally, a sequential learning strategy is used to further enforce various contextual patterns around the thin tubular structures into the classifier. For evaluation, we apply our proposed method to the 7T brain MR images scanned from 17 healthy subjects aged from 25 to 37. The performance is measured by voxel-wise segmentation accuracy, cluster-wise classification accuracy, and similarity of geometric properties, such as volume, length, and diameter distributions between the predicted and the true PVSs. Moreover, the accuracies are also evaluated on the simulation images with motion artifacts and lacunes to demonstrate the potential of our method in segmenting PVSs from elderly and patient populations. The experimental results show that our proposed method outperforms all existing PVS segmentation methods.


Assuntos
Algoritmos , Artérias Cerebrais/diagnóstico por imagem , Veias Cerebrais/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Angiografia por Ressonância Magnética/métodos , Reconhecimento Automatizado de Padrão/métodos , Adulto , Angiografia Cerebral/métodos , Artérias Cerebrais/anatomia & histologia , Veias Cerebrais/anatomia & histologia , Feminino , Humanos , Aumento da Imagem/métodos , Aprendizado de Máquina , Masculino , Reprodutibilidade dos Testes , Sensibilidade e Especificidade
18.
Mach Learn Med Imaging ; 10019: 61-68, 2016 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-28603789

RESUMO

Quantitative analysis of perivascular spaces (PVSs) is important to reveal the correlations between cerebrovascular lesions and neurodegenerative diseases. In this study, we propose a learning-based segmentation framework to extract the PVSs from high-resolution 7T MR images. Specifically, we integrate three types of vascular filter responses into a structured random forest for classifying voxels into PVS and background. In addition, we also propose a novel entropy-based sampling strategy to extract informative samples in the background for training the classification model. Since various vascular features can be extracted by the three vascular filters, even thin and low-contrast structures can be effectively extracted from the noisy background. Moreover, continuous and smooth segmentation results can be obtained by utilizing the patch-based structured labels. The segmentation performance is evaluated on 19 subjects with 7T MR images, and the experimental results demonstrate that the joint use of entropy-based sampling strategy, vascular features and structured learning improves the segmentation accuracy, with the Dice similarity coefficient reaching 66 %.

19.
Neuroimage ; 125: 895-902, 2016 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-26520772

RESUMO

Noninvasive imaging of perivascular spaces (PVSs) may provide useful insights into their role in normal brain physiology and diseases. Fast MRI sequences with sub-millimeter spatial resolutions and high contrast-to-noise ratio (CNR) are required for accurate delineation of PVS in human. To achieve the optimal condition for PVS imaging at 7T, we carried out detailed simulation and experimental studies to characterize the dependence of CNR on imaging sequences (T1 versus T2-weighted) and sequence parameters. In addition, PVSs were segmented semi-automatically, which revealed much larger numbers of PVSs in young healthy subjects (age 21-37years) than previously reported. To the best of our knowledge, our study provides, for the first time, detailed length, volume, and diameter distributions of PVS in the white matter and subcortical nuclei, which can serve as a reference for future studies of PVS abnormalities under diseased conditions.


Assuntos
Mapeamento Encefálico/métodos , Encéfalo/anatomia & histologia , Espaço Extracelular , Adulto , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Adulto Jovem
20.
Med Image Comput Comput Assist Interv ; 9350: 659-666, 2015 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30101232

RESUMO

Advancements in 7T MR imaging bring higher spatial resolution and clearer tissue contrast, in comparison to the conventional 3T and 1.5T MR scanners. However, 7T MRI scanners are less accessible at the current stage due to higher costs. Through analyzing the appearances of 7T images, we could improve both the resolution and quality of 3T images by properly mapping them to 7T-like images; thus, promoting more accurate post-processing tasks, such as segmentation. To achieve this method based on an unique dataset acquired both 3T and 7T images from same subjects, we propose novel multi-level Canonical Correlation Analysis (CCA) method and group sparsity as a hierarchical framework to reconstruct 7T-like MRI from 3T MRI. First, the input 3T MR image is partitioned into a set of overlapping patches. For each patch, the local coupled 3T and 7T dictionaries are constructed by extracting the patches from a neighboring region from all aligned 3T and 7T images in the training set. In the training phase, we have both 3T and 7T MR images scanned from each training subject. Then, these two patch sets are mapped to the same space using multi-level CCA. Next, each input 3T MRI patch is sparsely represented by the 3T dictionary and then the obtained sparse coefficients are utilized to reconstruct the 7T patch with the corresponding 7T dictionary. Group sparsity is further utilized to maintain the consistency between neighboring patches. Such reconstruction is performed hierarchically with adaptive patch size. The experiments were performed on 10 subjects who had both 3T and 7T MR images. Experimental results demonstrate that our proposed method is capable of recovering rich structural details and outperforms other methods, including the sparse representation method and CCA method.

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