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Desmoid tumor of the breast (DTB), also referred to as desmoid-type fibromatosis, is a rare tumor with an unknown etiology, imaging findings of which are often confused with breast cancer. The aim of this report is to present a case of DTB with its clinical, radiological, and pathological features. A 42-year-old woman with Turner syndrome, who had undergone bilateral saline-filled breast implantation surgery, presented with a complaint of a lump in her left breast. The patient underwent mammography (MG), ultrasound (US), and dynamic contrast-enhanced magnetic resonance imaging (MRI). The MG examination revealed afocal asymmetric density in the upper middle quadrant of the left breast. A core biopsy was performed on the irregularly shaped spiculated mass identified on US, and the results indicated either cellular fibroadenoma or a phyllodes tumor. On MRI, the mass was hypointense on T1-weighted and short tau inversion recovery (STIR) sequences. The dynamic MRI scan revealed a type 1 enhancement curve, while the apparent diffusion coefficient (ADC), fractional anisotropy (FA) and mean diffusivity (MD) values obtained from diffusion and diffusion tensor imaging were similar to those of the surrounding parenchyma. The mass was removed while preserving the implant, and the pathology results confirmed a diagnosis of DTB.The pathology report indicated microscopic proximity to the cauterized edge, but there was no evidence of recurrent mass detected on the follow-up US performed six months later. This is the first case of DTB reported in a patient with Turner syndrome. DTB is a rare tumor that can often be confused with breast cancer based on clinical and radiological findings, and it may not be accurately diagnosed by core biopsy alone. In cases where a clean surgical margin cannot be achieved, close follow-up and intervention may be considered when recurrence is observed.

Background Becker muscular dystrophy (BMD) is an X‐linked disorder characterized by slow, progressive muscle damage and muscle weakness. Hallmarks include fibre‐size variation and replacement of skeletal muscle with fibrous and adipose tissues, after repeated cycles of regeneration. Muscle histology can detect these features, but the required biopsies are invasive, are difficult to repeat and capture only small muscle volumes. Diffusion‐tensor magnetic resonance imaging (DT‐MRI) is a potential non‐invasive alternative that can calculate muscle fibre diameters when applied with the novel random permeable barrier model (RPBM). In this study, we assessed muscle fibre diameters using DT‐MRI in BMD patients and healthy controls and compared these with histology. Methods We included 13 BMD patients and 9 age‐matched controls, who underwent water‐fat MRI and DT‐MRI at multiple diffusion times, allowing RPBM parameter estimation in the lower leg muscles. Tibialis anterior muscle biopsies were taken from the contralateral leg in 6 BMD patients who underwent DT‐MRI and from an additional 32 BMD patients and 15 healthy controls. Laminin and Sirius‐red stainings were performed to evaluate muscle fibre morphology and fibrosis. Twelve ambulant patients from the MRI cohort underwent the North Star ambulatory assessment, and 6‐min walk, rise‐from‐floor and 10‐m run/walk functional tests. Results RPBM fibre diameter was significantly larger in BMD patients (P = 0.015): mean (SD) = 68.0 (25.3) μm versus 59.4 (19.2) μm in controls. Inter‐muscle differences were also observed (P ≤ 0.002). Both inter‐ and intra‐individual RPBM fibre diameter variability were similar between groups. Laminin staining agreed with the RPBM, showing larger median fibre diameters in patients than in controls: 72.5 (7.9) versus 63.2 (6.9) μm, P = 0.006. However, despite showing similar inter‐individual variation, patients showed more intra‐individual fibre diameter variability than controls—mean variance (SD) = 34.2 (7.9) versus 21.4 (6.9) μm, P < 0.001—and larger fibrosis areas: median (interquartile range) = 21.7 (5.6)% versus 14.9 (3.4)%, P < 0.001. Despite good overall agreement of RPBM and laminin fibre diameters, they were not associated in patients who underwent DT‐MRI and muscle biopsy, perhaps due to lack of colocalization of DT‐MRI with biopsy samples. Conclusions DT‐MRI RPBM metrics agree with histology and can quantify changes in muscle fibre size that are associated with regeneration without the need for biopsies. They therefore show promise as imaging biomarkers for muscular dystrophies.

Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter (e.g., local fibre architecture, axon morphology, and myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametric data for a comprehensive assessment of white matter properties. The present work exploits that framework to characterise the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, with the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterising the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, showing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts. •We report an atlas of key white matter pathways in standard space.•CHARMED provide more specific measures of axonal properties than DT-MRI metrics.•Crossing fibres explain the correlation between myelin and diffusion indices.•DT-MRI metrics need the smallest sample size to detect differences between groups.

ObjectivesTo assess the ability of quantitative T2, diffusion tensor imaging (DTI) and radiologist’s scores to detect muscle changes following acute muscle tear in soccer and rugby players. To assess the ability of these parameters to predict return to play times.MethodsIn this prospective, longitudinal study, 13 male athletes (age 19 to 34 years; mean 25 years) underwent MRI within 1 week of suffering acute muscle tear. Imaging included measurements of T2 and DTI parameters. Images were also assessed using modified Peetrons and British athletics muscle injury classification (BAMIC) scores. Participants returned for a second scan within 1 week of being determined fit to return to play. MRI measurements were compared between visits. Pearson’s correlation between visit 1 measurements and return to play times was assessed.ResultsThere were significant differences between visits in BAMIC scores (Z = − 2.088; p = 0.037), modified Peetrons (Z = − 2.530; p = 0.011) and quantitative MRI measurements; T2, 13.12 ms (95% CI, 4.82 ms, 21.42 ms; p = 0.01); mean diffusivity (0.22 (0.04, 0.39); p = 0.02) and fractional anisotropy (0.07 (0.01, 0.14); p = 0.03). BAMIC scores showed a significant correlation with return to play time (Rs = 0.64; p = 0.02), but modified Peetrons scores and quantitative parameters did not.ConclusionsT2 and DTI measurements in muscle can detect changes due to healing following muscle tear. Although BAMIC scores correlated well with return to play times, in this small study, quantitative MRI values did not, suggesting that T2 and DTI measurements are inferior predictors of return to play time compared with visual scoring.Key Points• Muscle changes following acute muscle tear can be measured using T2 and diffusion measurements on MRI.• Measurements of T2 and diffusion using MRI are not as good as a radiologist’s visual report at predicting return to play time after acute muscle tear.

Tensors are nowadays a common source of geometric information. In this paper, we propose to endow the tensor space with an affine-invariant Riemannian metric. We demonstrate that it leads to strong theoretical properties: the cone of positive definite symmetric matrices is replaced by a regular and complete manifold without boundaries (null eigenvalues are at the infinity), the geodesic between two tensors and the mean of a set of tensors are uniquely defined, etc. We have previously shown that the Riemannian metric provides a powerful framework for generalizing statistics to manifolds. In this paper, we show that it is also possible to generalize to tensor fields many important geometric data processing algorithms such as interpolation, filtering, diffusion and restoration of missing data. For instance, most interpolation and Gaussian filtering schemes can be tackled efficiently through a weighted mean computation. Linear and anisotropic diffusion schemes can be adapted to our Riemannian framework, through partial differential evolution equations, provided that the metric of the tensor space is taken into account. For that purpose, we provide intrinsic numerical schemes to compute the gradient and Laplace-Beltrami operators. Finally, to enforce the fidelity to the data (either sparsely distributed tensors or complete tensors fields) we propose least-squares criteria based on our invariant Riemannian distance which are particularly simple and efficient to solve.[PUBLICATION ABSTRACT]

Restorative cell-based therapies for experimental brain injury, such as stroke and traumatic brain injury,substantially improve functional outcome. We discuss and review state of the art magnetic resonance imaging methodologies and their applications related to cell-based treatment after brain injury. We focus on the potential of magnetic resonance imaging technique and its associated challenges to obtain useful new information related to cell migration, distribution, and quantitation, as well as vascular and neuronal remodeling in response to cell-based therapy after brain injury. The noninvasive nature of imaging might more readily help with translation of cell-based therapy from the laboratory to the clinic.

In diffusion tensor magnetic resonance imaging (DT-MRI), limitations concerning complex fiber architecture (when an image voxel contains fiber populations with more than one dominant orientation) are well-known. Fractional anisotropy (FA) values are lower in such areas because of a lower directionality of diffusion on the voxel-scale, which makes the interpretation of FA less straightforward. Moreover, the interpretation of the axial and radial diffusivities is far from trivial when there is more than one dominant fiber orientation within a voxel. In this work, using (i) theoretical considerations, (ii) simulations, and (iii) experimental data, it is demonstrated that the mean diffusivity (or the trace of the diffusion tensor) is lower in complex white matter configurations, compared with tissue where there is a single dominant fiber orientation within the voxel. We show that the magnitude of this reduction depends on various factors, including configurational and microstructural properties (e.g., the relative contributions of different fiber populations) and acquisition settings (e.g., the b-value). These results increase our understanding of the quantitative metrics obtained from DT-MRI and, in particular, the effect of the microstructural architecture on the mean diffusivity. More importantly, they reinforce the growing awareness that differences in DT-MRI metrics need to be interpreted cautiously. ► The mean diffusivity (MD) in diffusion tensor MRI is affected by crossing fibers. ► MD values are lower in complex fiber architecture than in single fiber voxels. ► This is shown using theoretical considerations, simulations and in vivo experiments. ► In vivo, mean diffusivity values decrease when fibers cross at larger angles.

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

The application of structural and functional magnetic resonance imaging (MRI) techniques in patients with multiple sclerosis (MS) has certainly helped to improve our understanding of the mechanisms responsible for clinical disability and cognitive impairment in this condition. The numerous studies performed in MS patients have also provided many lessons on the structure-function relationships in the human brain, which could be applied to healthy subjects and to patients affected by other neurological conditions. The findings have allowed a better understanding of the processes involved in the loss of function after central nervous system (CNS) damage, and clarified the substrates of specific symptoms (e.g., cognitive impairment and fatigue), which should aid clinical recovery and help in the monitoring of disease progression. In this review, important examples of how the application of different MRI techniques in MS might provide relevant information on the human brain are discussed. These include how damage to strategic white matter tracts can cause symptoms due to a disconnection mechanism and how involvement of a specific brain network, independent of the underlying pathological substrate, might determine certain symptoms. The role of functional and structural plasticity in clinical recovery (following an acute relapse or promoted by rehabilitation) and the mechanisms that might become the target of treatment aimed at function recovery are also considered. The ways in which network- and system-based analysis can reshape current understanding of the brain structure-function relationships are discussed. Finally, there is speculation about the relevance of inherited or acquired factors, such as age, comorbidity, brain reserve and cognitive reserve, which are likely to influence the relation between CNS damage and disease clinical manifestations. •A disconnection syndrome can determine clinical impairment in neurological diseases.•Central fatigue may arise from damage to frontal cortico-subcortical connections.•Neuroplasticity occurs in neurological diseases, mitigating brain damage effects.•MRI advances are improving our understanding of brain structure-function correlation.•Several factors influence relations between brain damage and clinical manifestations.

The brain of mammals differs from that of all other vertebrates, in having a six-layered neocortex that is extensively interconnected within and between hemispheres. Interhemispheric connections are conveyed through the anterior commissure in egg-laying monotremes and marsupials, whereas eutherians evolved a separate commissural tract, the corpus callosum. Although the pattern of interhemispheric connectivity via the corpus callosum is broadly shared across eutherian species, it is not known whether this pattern arose as a consequence of callosal evolution or instead corresponds to a more ancient feature ofmammalian brain organization. Here we show that, despite cortical axons using an ancestral commissural route, monotremes and marsupials share features of interhemi-spheric connectivity with eutherians that likely predate the origin of the corpus callosum. Based on ex vivo magnetic resonance imaging and tractography, we found that connections through the anterior commissure in both fat-tailed dunnarts (Marsupialia) and duck-billed platypus (Monotremata) are spatially segregated according to cortical area topography. Moreover, cell-resolution retrograde and anterograde interhemispheric circuit mapping in dunnarts revealed several features shared with callosal circuits of eutherians. These include the layered organization of commissural neurons and terminals, a broad map of connections between similar (homotopic) regions of each hemisphere, and regions connected to different areas (heterotopic), including hyperconnected hubs along the medial and lateral borders of the cortex, such as the cingulate/motor cortex and claustrum/insula. We therefore propose that an interhemispheric connectome originated in early mammalian ancestors, predating the evolution of the corpus callosum. Because these features have been conserved throughout mammalian evolution, they likely represent key aspects of neocortical organization.