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We herein report the construction of a robust MRI peptide contrast agent Gd-ICTP with superior selectivity for type I collagen, enabling the accurate and non-invasive detection of hepatic fibrosis in vivo .

To mitigate systematic errors in magnetic resonance fingerprinting (MRF), the precomputed dictionary is usually computed with minimal granularity across the entire range of tissue parameters. However, the dictionary grows exponentially with the number of parameters increase, posing significant challenges to the computational efficiency and matching accuracy of pattern-matching algorithms. Existing works, primarily based on convolutional neural networks (CNN), focus solely on local information to reconstruct multiple parameter maps, lacking in-depth investigations on the MRF mechanism. These methods may not exploit long-distance redundancies and the contextual information within voxel fingerprints introduced by the Bloch equation dynamics, leading to limited reconstruction speed and accuracy. To overcome these limitations, we propose a novel end-to-end neural network called the Local and Global Vision Transformer (LG-ViT) for MRF parameter reconstruction. Our proposed LG-ViT employs a multi-stage architecture that effectively reduces the computational overhead associated with the high-dimensional MRF data and the transformer model. Specifically, a local Transformer encoder is proposed to capture contextual information embedded within voxel fingerprints and local correlations introduced by the interconnected human tissues. Additionally, a global Transformer encoder is proposed to leverage long-distance dependencies arising from shared characteristics among different tissues across various spatial regions. By incorporating MRF physics-based data priors and effectively capturing local and global correlations, our proposed LG-ViT can achieve fast and accurate MRF parameter reconstruction. Experiments on both simulation and in vivo data demonstrate that the proposed method enables faster and more accurate MRF parameter reconstruction compared to state-of-the-art deep learning-based methods., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yue Hu reports financial support was provided by National Natural Science Foundation of China. Yue Hu reports financial support was provided by Natural Science Foundation of Heilongjiang Province., (Copyright © 2024. Published by Elsevier B.V.)

Objective. We aim to: (1) quantify the benefits of lung sparing using non-adaptive magnetic resonance guided stereotactic body radiotherapy (MRgSBRT) with advanced motion management for peripheral lung cancers compared to conventional x-ray guided SBRT (ConvSBRT); (2) establish a practical decision-making guidance metric to assist a clinician in selecting the appropriate treatment modality. Approach. Eleven patients with peripheral lung cancer who underwent breath-hold, gated MRgSBRT on an MR-guided linear accelerator (MR linac) were studied. Four-dimensional computed tomography (4DCT)-based retrospective planning using an internal target volume (ITV) was performed to simulate ConvSBRT, which were evaluated against the original MRgSBRT plans. Metrics analyzed included planning target volume (PTV) coverage, various lung metrics and the generalized equivalent unform dose (gEUD). A dosimetric predictor for achievable lung metrics was derived to assist future patient triage across modalities. Main results. PTV coverage was high (median V100% > 98%) and comparable for both modalities. MRgSBRT had significantly lower lung doses as measured by V20 (median 3.2% versus 4.2%), mean lung dose (median 3.3 Gy versus 3.8 Gy) and gEUD. Breath-hold, gated MRgSBRT resulted in an average reduction of 47% in PTV volume and an average increase of 19% in lung volume. Strong correlation existed between lung metrics and the ratio of PTV to lung volumes (R PTV/Lungs ) for both modalities, indicating that R PTV/Lungs may serve as a good predictor for achievable lung metrics without the need for pre-planning. A threshold value of R PTV/Lungs < 0.035 is suggested to achieve V20 < 10% using ConvSBRT. MRgSBRT should otherwise be considered if the threshold cannot be met. Significance. The benefits of lung sparing using MRgSBRT were quantified for peripheral lung tumors; R PTV/Lungs was found to be an effective predictor for achievable lung metrics across modalities. R PTV/Lungs can assist a clinician in selecting the appropriate modality without the need for labor-intensive pre-planning, which has significant practical benefit for a busy clinic., (© 2024 IOP Publishing Ltd.)

Objective: We aim to construct a magnetic resonance imaging (MRI)-based multi-sequence multi-regional radiomics model that will improve the preoperative prediction ability of lymph node metastasis (LNM) in T3 rectal cancer., Methods: Multi-sequence MRI data from 190 patients with T3 rectal cancer were retrospectively analyzed, with 94 patients in the LNM group and 96 patients in the non-LNM group. The clinical factors, subjective imaging features, and the radiomic features of tumor and peritumoral mesorectum region of patients were extracted from T2WI and ADC images. Spearman's rank correlation coefficient, Mann-Whitney's U test, and the least absolute shrinkage and selection operator were used for feature selection and dimensionality reduction. Logistic regression was used to construct six models. The predictive performance of each model was evaluated by the receiver operating characteristic curve (ROC). The differences of each model were characterized by area under the curve (AUC) via the DeLong test., Results: The AUCs of T2WI, ADC single-sequence radiomics model and multi-sequence radiomics model were 0.73, 0.75, and 0.78, respectively. The multi-sequence multi-regional radiomics model with improved performance was created by combining the radiomics characteristics of the peritumoral mesorectum region with the multi-sequence radiomics model (AUC, 0.87; p < 0.01). The AUC of the clinical model was 0.68, and the MRI-clinical composite evaluation model was obtained by incorporating the clinical data with the multi-sequence multi-regional radiomics features, with an AUC of 0.89., Conclusion: The MRI-based multi-sequence multi-regional radiomics model significantly improved the prediction ability of LNM for T3 rectal cancer and could be applied to guide surgical decision-making in patients with T3 rectal cancer., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The tensor low-rank prior has attracted considerable attention in dynamic MR reconstruction. Tensor low-rank methods preserve the inherent high-dimensional structure of data, allowing for improved extraction and utilization of intrinsic low-rank characteristics. However, most current methods are still confined to utilizing low-rank structures either in the image domain or predefined transformed domains. Designing an optimal transformation adaptable to dynamic MRI reconstruction through manual efforts is inherently challenging. In this paper, we propose a deep unrolling network that utilizes the convolutional neural network (CNN) to adaptively learn the transformed domain for leveraging tensor low-rank priors. Under the supervised mechanism, the learning of the tensor low-rank domain is directly guided by the reconstruction accuracy. Specifically, we generalize the traditional t-SVD to a transformed version based on arbitrary high-dimensional unitary transformations and introduce a novel unitary transformed tensor nuclear norm (UTNN). Subsequently, we present a dynamic MRI reconstruction model based on UTNN and devise an efficient iterative optimization algorithm using ADMM, which is finally unfolded into the proposed T 2 LR-Net. Experiments on two dynamic cardiac MRI datasets demonstrate that T 2 LR-Net outperforms the state-of-the-art optimization-based and unrolling network-based methods., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yue Hu reports financial support was provided by National Natural Science Foundation of China. Yue Hu reports financial support was provided by Natural Science Foundation of Heilongjiang., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background and Objective: In clinical applications, there is an increasing demand for rapid acquisition and automated analysis of magnetic resonance imaging (MRI) data. However, most existing methods focus on either MR image reconstruction from undersampled data or segmentation using fully sampled data, hardly considering MR image segmentation in fast imaging scenarios. Consequently, it is imperative to investigate a multi-task approach that can simultaneously achieve high scanning acceleration and accurate segmentation results., Methods: In this paper, we propose a novel end-to-end multi-task interaction network, termed as the Cooperative-Net, which integrates accelerated MR imaging and multi-class tissue segmentation into a unified framework. The Cooperative-Net consists of alternating reconstruction modules and segmentation modules. To facilitate effective interaction between the two tasks, we introduce the spatial-adaptive semantic guidance module, which leverages the semantic map as a structural prior to guide MR image reconstruction. Furthermore, we propose a novel unrolling network with a multi-path shrinkage structure for MR image reconstruction. This network consists of parallel learnable shrinkage paths to handle varying degrees of degradation across different frequency components in the undersampled MR image, effectively improving the quality of the recovered image., Results: We use two publicly available datasets, including the cardiac and knee MR datasets, to validate the efficacy of our proposed Cooperative-Net. Through qualitative and quantitative analysis, we demonstrate that our method outperforms existing state-of-the-art multi-task approaches for joint MR image reconstruction and segmentation., Conclusions: The proposed Cooperative-Net is capable of achieving both high accelerated MR imaging and accurate multi-class tissue segmentation., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yue Hu reports financial support was provided by National Natural Science Foundation of China. Yue Hu reports financial support was provided by Natural Science Foundation of Heilongjiang., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Four-dimensional magnetic resonance imaging (4D-MRI) is becoming increasingly important in radiotherapy treatment planning for its ability to simultaneously provide 3D structural information and temporal profiles of the examined tissues in a non-ionizing manner. However, the relatively long acquisition time and the resulting motion artifacts severely limit the further application of 4D-MRI. In this paper, we propose a novel motion-aligned reconstruction method based on higher degree total variation and locally low-rank regularization (maHDTV-LLR) to recover 4D MR images from the highly undersampled Fourier coefficients. Specifically, we propose a two-stage reconstruction framework alternating between a motion alignment step and a regularized optimization reconstruction step. Moreover, we incorporate the 3D-HDTV and the locally low-rank penalties into a unified framework to simultaneously exploit the spatial and temporal correlation of the 4D-MRI data. A fast alternating minimization algorithm based on variable splitting is utilized to solve the optimization problem efficiently. The performance of the proposed method is demonstrated in the context of 4D cardiac and abdominal MR images reconstruction with high undersampling factors. Numerical results show that the proposed method enables accelerated 4D-MRI with improved image quality and reduced artifacts., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Ribose plays an important role in the process of life. Excessive ribose in the human cerebrospinal fluid or urine can be used as an early diagnostic marker of leukoencephalopathy. Fluorinated phenylboronic acid combined with 19 F NMR spectroscopy was a powerful method for molecular recognition. However, phenylboronic acid-based sensors for selective detection of ribose are rarely reported in the literature. In this study, the rapid and highly selective recognition of ribose was studied by 19 F NMR and 2-fluorophenylboric acid. It was found that 2-fluoro-phenylboric acid was an appropriate 19 F NMR-based sensor molecule for the determination of ribose under physiological conditions with high selectivity and robust anti-interference ability. When 2-fluorophenylboric acid was used for the detection of ribose in human urine without any sample pretreatment, a limit of detection of 78 μM was obtained at room temperature under given 19 F NMR experimental conditions (400 MHz, 512 scans, ca. 12 min), which can well meet the needs of practical application.

Purpose: The study aimed to investigate whether isocitrate dehydrogenase 1 (IDH1) mutation status in gliomas can be estimated by volume-based histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)., Materials and Methods: Preoperative DCE-MRI data of 85 pathologically confirmed glioma patients including 33 carrying IDH1 mutant type (IDH1 mut ) and 52 with IDH1 wildtype (IDH1 wt ) were reviewed in a retrospective approach. Regions of interest (ROI) covering entire tumor volume were manually delineated using O.K. software (OmniKinetics, GE Healthcare, China). Histogram parameters of volume transfer constant (K trans ) and volume of extravascular /extracellular space per unit volume of tissue (V e ) derived from DCE-MRI were obtained. Mann-Whitney U tests were made to compare the differences in histogram parameters of K trans and V e between IDH1 mut and IDH1 wt in all gliomas and high-grade gliomas (HGGs, grade III and IV). Receiver operator characteristic (ROC) analysis were implemented to assess the diagnostic performance., Results: In histogram parameters of K trans and V e , pairwise comparisons demonstrated statistically significant differences in mean, standard deviation (SD), 90th and 95th percentiles (90%, 95%) values between IDH1 mut and IDH1 wt in all cases of gliomas and HGGs (P < 0.05, respectively). The ROC analysis revealed that the cut-off values of 95% value of K trans (0.097 min -1 ) and mean value of V e (0.099) provided the best combination of sensitivity and specificity to distinguish all gliomas with IDH1 mut from IDH1 wt . In HGGs, the cut-off values of mean value of K trans and V e (0.044 min -1 , 0.099) played similar role., Conclusion: Volume-based histogram analysis of DCE-MRI performs well in identification of IDH1 mut gliomas., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Multicore iron oxide nanoparticles, also known as colloidal nanocrystal clusters, are magnetic materials with diverse applications in biomedicine and photonics. Here, we examine how both of their characteristic dimensional features, the primary particle and sub-micron colloid diameters, influence their magnetic properties and performance in two different applications. The characterization of these basic size-dependent properties is enabled by a synthetic strategy that provides independent control over both the primary nanocrystal and cluster dimensions. Over a wide range of conditions, electron microscopy and X-ray diffraction reveal that the oriented attachment of smaller nanocrystals results in their crystallographic alignment throughout the entire superstructure. We apply a sulfonated polymer with high charge density to prevent cluster aggregation and conjugate molecular dyes to particle surfaces so as to visualize their collection using handheld magnets. These libraries of colloidal clusters, indexed both by primary nanocrystal dimension ( d p ) and overall cluster diameter ( D c ), form magnetic photonic crystals with relatively weak size-dependent properties. In contrast, their performance as MRI T 2 contrast agents is highly sensitive to cluster diameter, not primary particle size, and is optimized for materials of 50 nm diameter ( r 2 = 364 mM -1 s -1 ). These results exemplify the relevance of dimensional control in developing applications for these versatile materials.

Background: Migraine is a severe and disabling brain disorder, and the exact neurological mechanisms remain unclear. Migraineurs have altered pain perception, and headache attacks disrupt their sensory information processing and sensorimotor integration. The altered functional connectivity of sub-regions of sensorimotor brain areas with other brain cortex associated with migraine needs further investigation., Methods: Forty-eight migraineurs without aura during the interictal phase and 48 age- and sex-matched healthy controls underwent resting-state functional magnetic resonance imaging scans. We utilized seed-based functional connectivity analysis to investigate whether patients exhibited abnormal functional connectivity between sub-regions of sensorimotor brain areas and cortex regions., Results: We found that patients with migraineurs without aura exhibited disrupted functional connectivities between the sensorimotor areas and the visual cortex, temporal cortex, posterior parietal lobule, prefrontal areas, precuneus, cingulate gyrus, sensorimotor areas proper and cerebellum areas compared with healthy controls. In addition, the clinical data of the patients, such as disease duration, pain intensity and HIT-6 score, were negatively correlated with these impaired functional connectivities., Conclusion: In patients with migraineurs without aura, the functional connectivities between the sensorimotor brain areas and other brain regions was reduced. These disrupted functional connectivities might contribute to abnormalities in visual processing, multisensory integration, nociception processing, spatial attention and intention and dysfunction in cognitive evaluation and modulation of pain. Recurrent headache attacks might lead to the disrupted network between primary motor cortex and temporal regions and between primary somatosensory cortex and temporal regions. Pain sensitivity and patient quality of life are closely tied to the abnormal functional connectivity between sensorimotor regions and other brain areas.

Recent theory of mapping an image into a structured low-rank Toeplitz or Hankel matrix has become an effective method to restore images. In this paper, we introduce a generalized structured low-rank algorithm to recover images from their undersampled Fourier coefficients using infimal convolution regularizations. The image is modeled as the superposition of a piecewise constant component and a piecewise linear component. The Fourier coefficients of each component satisfy an annihilation relation, which results in a structured Toeplitz matrix. We exploit the low-rank property of the matrices to formulate a combined regularized optimization problem. In order to solve the problem efficiently and to avoid the high-memory demand resulting from the large-scale Toeplitz matrices, we introduce a fast and a memory-efficient algorithm based on the half-circulant approximation of the Toeplitz matrix. We demonstrate our algorithm in the context of single and multi-channel MR images recovery. Numerical experiments indicate that the proposed algorithm provides improved recovery performance over the state-of-the-art approaches.

Parkinson's disease (PD) is a progressive neurological degenerative disorder characterized by impaired motor function and non-motor dysfunctions. While recent studies have highlighted the role of the cerebellum in PD, our understanding of its role in PD remains limited. In the present study, we used resting-state fMRI to evaluate dysfunctions within the cerebellum in PD patients treated with medication and drug-naïve PD patients. We applied amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) analysis methods. Thirty-one patients with early stage PD (22 drug-naïve and 9 medicated patients) and 31 gender- and age-matched healthy controls were recruited in this study. ALFFs increased in the left cerebellar areas (lobules VI/VIIb/CruI/CruII and the dentate gyrus) and right cerebellar areas (lobules VI/VIIb/VIIIa/CruI/CruII and the dentate gyrus) of all PD patients and in the left and right cerebellar areas (lobules VI/VIIb/CruI and the dentate gyrus) of drug-naive PD patients but were not significantly changed in medicated PD patients. DC increased in the right cerebellar areas of all PD patients and medicated PD patients. All PD patients and all drug-naive PD patients showed significantly weaker functional connectivity (FC) between the left cerebellum and the left medial frontal gyrus. However, FC was significantly stronger between the right cerebellum and the left precentral and right middle occipital gyri in the medicated PD patients than in controls. Furthermore, a correlation analyses revealed that ALFF z scores in the left cerebellum (lobule VI) and right cerebellum (lobule VI/CruI and dentate gyrus) were negatively correlated with Mini-Mental State Examination (MMSE) scores in all PD patients and drug-naive patients. These results indicate that the cerebellum plays an important role in PD, mainly by exerting a compensatory effect in early stage PD. Additionally, antiparkinsonian medication would modified PD-induced changes in local neural activity and FC in PD patients. The results of this study offer novel insights into the roles of the cerebellum in early stage drug-naïve PD.

Background: Medicare expenditures for high-cost diagnostic imaging have risen faster than those for total cancer care and have been targeted for potential cost reduction. We sought to determine recent and long-term patterns in high-cost diagnostic imaging use among elderly (aged ≥65 years) patients with stage IV cancer., Methods: We identified claims within the Surveillance, Epidemiology, and End Results (SEER)-Medicare database with computed tomography, magnetic resonance imaging, positron emission tomography, and nuclear medicine scans between January 1994 and December 2009 for patients diagnosed with stage IV breast, colorectal, lung, or prostate cancer between January 1995 and December 2006 (N = 100,594 patients). The proportion of these patients imaged and rate of imaging per-patient per-month of survival were calculated for each phase of care in patients diagnosed between January 2002 and December 2006 (N = 55,253 patients). Logistic regression was used to estimate trends in imaging use in stage IV patients diagnosed between January 1995 and December 2006, which were compared with trends in imaging use in early-stage (stages I and II) patients with the same tumor types during the same period (N = 192,429 patients)., Results: Among the stage IV patients diagnosed between January 2002 and December 2006, 95.9% underwent a high-cost diagnostic imaging procedure, with a mean number of 9.79 (SD = 9.77) scans per patient and 1.38 (SD = 1.24) scans per-patient per-month of survival. After the diagnostic phase, 75.3% were scanned again; 34.3% of patients were scanned in the last month of life. Between January 1995 and December 2006, the proportion of stage IV cancer patients imaged increased (relative increase = 4.6%, 95% confidence interval [CI] = 3.7% to 5.6%), and the proportion of early-stage cancer patients imaged decreased (relative decrease = -2.5%, 95% CI = -3.2% to -1.9%)., Conclusions: Diagnostic imaging is used frequently in patients with stage IV disease, and its use increased more rapidly over the decade of study than that in patients with early-stage disease.

We introduce a novel algorithm to recover sparse and low-rank matrices from noisy and undersampled measurements. We pose the reconstruction as an optimization problem, where we minimize a linear combination of data consistency error, nonconvex spectral penalty, and nonconvex sparsity penalty. We majorize the nondifferentiable spectral and sparsity penalties in the criterion by quadratic expressions to realize an iterative three-step alternating minimization scheme. Since each of these steps can be evaluated either analytically or using fast schemes, we obtain a computationally efficient algorithm. We demonstrate the utility of the algorithm in the context of dynamic magnetic resonance imaging (MRI) reconstruction from sub-Nyquist sampled measurements. The results show a significant improvement in signal-to-noise ratio and image quality compared with classical dynamic imaging algorithms. We expect the proposed scheme to be useful in a range of applications including video restoration and multidimensional MRI., (© 2011 IEEE)

We herein report the construction of a robust MRI peptide contrast agent Gd-ICTP with superior selectivity for type I collagen, enabling the accurate and non-invasive detection of hepatic fibrosis in vivo. [ABSTRACT FROM AUTHOR]

Background: Lung metastasis (LM) status is critical for making treatment decisions in soft‐tissue sarcoma (STS) patients, yet magnetic resonance imaging (MRI)‐based prediction of LM in STSs has not been thoroughly investigated. Purpose: This study aimed to develop MRI‐based radiomics models for identifying LM in STSs. Methods: We enrolled 122 STS patients from our hospital to form a primary cohort. Thirty‐two patients from another hospital were included as an external validation cohort. All patients underwent T1‐weighted contrast‐enhanced (T1‐CE) MRI scans before treatment. Radiomics features were extracted from T1‐CE MRI sequence and selected by least absolute shrinkage and selection operator (LASSO) to build the radiomics signature. Clinical factors were evaluated using the univariate and multivariate analyses. Multivariable logistic regression analysis was used to construct a clinical‐radiomics nomogram incorporating the radiomics signature with margin. Receiver operating characteristic (ROC), calibration and decision curve analysis (DCA) curves were plotted and area under the ROC curves (AUCs) were calculated to assess the predictive performance of nomogram, radiomics signature and margin. Results: A total of five features was finally identified highly related to the LM status to develop the radiomics signature. The nomogram integrating the radiomics signature and margin achieved the best prediction performance in the training (AUCs, nomogram vs. radiomics signature vs. margin, 0.918 vs. 0.894 vs. 0.609), internal validation (AUCs, nomogram vs. radiomics signature vs. margin, 0.864 vs. 0.841 vs. 0.666) and external validation (AUCs, nomogram vs. radiomics signature vs. margin, 0.843 vs. 0.800 vs. 0.643) sets. Conclusions: The developed nomogram was a promising tool to help make preoperative treatment strategies for STSs. [ABSTRACT FROM AUTHOR]

Retraction of 'A robust collagen-targeting MRI peptide contrast agent for in vivo imaging of hepatic fibrosis' by Zhao Liu et al., Chem. Commun., 2023, 59, 6068–6071, https://doi.org/10.1039/D3CC01096A. [ABSTRACT FROM AUTHOR]

Due to the capability of fast multiparametric quantitative imaging, magnetic resonance fingerprinting (MRF) is becoming a promising quantitative magnetic resonance imaging approach. However, the artifacts caused by the highly undersampled data acquisition lead to inaccurate estimation of the tissue parameter maps. Based on the assumption that the 3-D MRF data can be modeled as a piecewise smooth signal, with the discontinuities localized to the zero sets of a bandlimited function, we exploit the low-rank property of the structured Toeplitz matrix constructed from the Fourier measurements. In addition, we adopt the subspace projection scheme to improve the accuracy of parameter estimation. In order to efficiently solve the regularized problem, we propose an iterative two-stage algorithm, which alternately updates the ${k}$ -space data and projects the space-time matrix into the dictionary space. Numerical experiments demonstrate that the proposed algorithm shows significant improvement in MRF time-series images reconstruction and can provide more accurate parameter maps over the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Objectives: To investigate whether glioma isocitrate dehydrogenase (IDH) 1 mutation and vascular endothelial growth factor (VEGF) expression can be estimated by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods: Chinese Glioma Genome Atlas (CGGA) database was wined for differential expression of VEGF in gliomas with different IDH genotypes. The VEGF expression and IDH1 genotypes of 56 glioma samples in our hospital were assessed by immunohistochemistry. Preoperative DCE-MRI data of glioma samples were reviewed. Regions of interest (ROIs) covering tumor parenchyma were delineated. Histogram parameters of volume transfer constant (Ktrans) and volume of extravascular extracellular space per unit volume of tissue (Ve) derived from DCE-MRI were obtained. Histogram parameters of Ktrans , Ve and VEGF expression of IDH1 mutant type (IDH1mut) gliomas were compared with the IDH1 wildtype (IDH1wt) gliomas. Receiver operating characteristic (ROC) curve analysis was performed to differentiate IDH1mut from IDH1wt gliomas. The correlation coefficients were determined between histogram parameters of Ktrans , Ve and VEGF expression in gliomas. Results: In CGGA database, VEGF expression in IDHmut gliomas was lower as compared to wildtype counterpart. The immunohistochemistry of glioma samples in our hospital also confirmed the results. Comparisons demonstrated statistically significant differences in histogram parameters of Ktrans and Ve [mean, standard deviation (SD), 50th, 75th, 90th. and 95th percentile] between IDH1mut and IDH1wt gliomas (P < 0.05, respectively). ROC curve analysis revealed that 50th percentile of Ktrans (0.019 min−1) and Ve (0.039) provided the perfect combination of sensitivity and specificity in differentiating gliomas with IDH1mut from IDH1wt. Irrespective of IDH1 mutation, histogram parameters of Ktrans and Ve were correlated with VEGF expression in gliomas (P < 0.05, respectively). Conclusions: VEGF expression is significantly lower in IDH1mut gliomas as compared to the wildtype counterpart, and it is non-invasively predictable with histogram analysis of DCE-MRI. [ABSTRACT FROM AUTHOR]

Breast fibromatosis is a rare histologically benign tumor with local aggressive potential, and imaging and clinical findings of breast fibromatosis require attention. We retrospectively evaluated the images of 20 patients with histologically proven breast fibromatosis on mammography, magnetic resonance imaging (MRI), and ultrasonography. The lesions were assessed concerning the location, fascia involvement, imaging characteristics, and follow‐up outcomes. Altogether, there were 22 lesions: 10 lesions involved the superficial fascia system including four lesions additionally involving the deep fascia and pectoralis major, and 12 lesions were inside the glandular parenchyma with two lesions originated from the prior surgery site. The detection rates of mammography, ultrasound, and MRI for breast fibromatosis were 33.3% (3/9), 90% (18/20), and 100% (3/3), respectively. We found that fascia involvement may be a characteristic of breast fibromatosis. The lesion located inside glandular parenchyma is prone to be underestimated, whereas combined MR with ultrasound is recommended for the diagnosis. The complete excision with negative margins is important for a good prognosis. [ABSTRACT FROM AUTHOR]

Background: Encapsulated papillary carcinoma (EPC) of the breast is a rare entity. EPC can be underappreciated on percutaneous biopsy, which may require additional procedures if invasion is not recognized preoperatively. We aimed to investigate the magnetic resonance imaging (MRI) phenotypes correlated with preoperative pathological risk stratification for clinical guidance. Materials and Methods: The preoperative MRI scans of 30 patients diagnosed with 36 EPCs in multiple centers between August 2015 and February 2020 were reviewed by two breast radiologists. According to the WHO classification published in 2019, EPCs were classified into two pathological subtypes: encapsulated papillary carcinoma and encapsulated papillary carcinoma with invasion. Clinicopathological analysis of the two subtypes and MR feature analysis were performed. Results: Evaluation of the MRI phenotypes and pathological subtype information revealed that not circumscribed (P=0.04) was more common in EPCs with invasion than in EPCs. There was a significant difference in the age of patients (P=0.05), and the risk increased with age. The maximum diameter of the tumor increased with tumor risk, but there was no significant difference (P=0.36). Nearly half of the EPC with invasion patients showed hyperintensity on T1WI (P=0.19). A total of 63.6% of the EPC with invasion group showed non-mass enhancement surrounding (P=0.85). In addition, 29 patients (96.7%) had no axillary lymph node metastasis, and only one patient with EPC with invasion had axillary lymph node metastasis. Further pathological information analysis of EPCs showed that higher Ki-67 levels were more common in patients with EPCs with invasion (P=0.04). A total of 29 patients (96.7%) had the luminal phenotype, and one patient with EPC with invasion had the Her-2-positive phenotype. Conclusion: The margin, age and Ki-67 level were the key features for EPC risk stratification. In addition, these MRI signs, including a larger tumor, non-mass enhancement surrounding and axillary lymph node metastasis, may be suggestive of a high-risk stratification. Therefore, MRI phenotypes may provide additional information for the risk stratification of EPCs. [ABSTRACT FROM AUTHOR]

Background: Achilles sleeve avulsion usually occurs from pre-existing insertional Achilles tendinopathy, leaving a calcific spur at the insertional site. The purpose of this study was to introduce a new technique using the spur base on the insertional site to drill the suture tunnel to repair Achilles sleeve avulsion. Methods: In total, 11 patients diagnosed with Achilles sleeve avulsion underwent this new surgical technique and were followed for a mean time of 40 months. Clinical outcomes were measured using the visual analog scale (VAS), American Orthopaedic Foot and Ankle Society (AOFAS) score, Victorian Institute of Sports Assessment-Achilles (VISA-A) score, Tegner score, and time taken to return to activities. Preoperative and postoperative MRI, the ability to perform heel rise, and complications were also evaluated. Results: All cases (11/11) had insertional Achilles tendinopathy with calcific spur formation on the tendon's insertion. At final follow-up, the average VAS score improved from 5.3 to 0.1, AOFAS score improved from 44.8 to 97.9, VISA-A score improved from 23.6 to 96.6, and Tegner score improved from 0.9 to 4.9. Tendinopathy symptoms were eliminated. Patients returned to daily activities, work, and sports 3.5 months, 2.8 months, and 12.3months after operation, respectively. Patients took an average of 18.1 weeks after operation to perform the single heel rise test. No severe complications such as infection and rerupture were observed. Conclusion: Our new transosseous suture technique is a promising alternative option in treating Achilles sleeve avulsion. More cases and longer follow up are needed in order to find the best reconstructive option for this pathology. Levels of evidence: Level IV [ABSTRACT FROM AUTHOR]

We introduce a novel algorithm to reconstruct dynamic magnetic resonance imaging (MRI) data from under-sampled k-t space data. In contrast to classical model based cine MRI schemes that rely on the sparsity or banded structure in Fourier space, we use the compact representation of the data in the Karhunen Louve transform (KLT) domain to exploit the correlations in the dataset. The use of the data-dependent KL transform makes our approach ideally suited to a range of dynamic imaging problems, even when the motion is not periodic. In comparison to current KLT-based methods that rely on a two-step approach to first estimate the basis functions and then use it for reconstruction, we pose the problem as a spectrally regularized matrix recovery problem. By simultaneously determining the temporal basis functions and its spatial weights from the entire measured data, the proposed scheme is capable of providing high quality reconstructions at a range of accelerations. In addition to using the compact representation in the KLT domain, we also exploit the sparsity of the data to further improve the recovery rate. Validations using numerical phantoms and in vivo cardiac perfusion MRI data demonstrate the significant improvement in performance offered by the proposed scheme over existing methods. [ABSTRACT FROM AUTHOR]

• Radiomics is a rapidly growing discipline, which combines the advantages of high throughput and noninvasiveness. • Isocitrate dehydrogenase (IDH) has been shown to have both diagnostic and prognostic implications in gliomas. Angiogenesis is a major histological feature and closely related to the degree of aggressiveness in gliomas. • The radiomics model based on DCE-MRI and DWI has an efficient performance in estimating IDH1 mutation and angiogenesis in gliomas. To investigate the value of a radiomics model based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion weighted imaging (DWI) in estimating isocitrate dehydrogenase 1 (IDH1) mutation and angiogenesis in gliomas. One hundred glioma patients with DCE-MRI and DWI were enrolled in this study (training and validation groups with a ratio of 7:3). The IDH1 genotypes and expression of vascular endothelial growth factor (VEGF) in gliomas were assessed by immunohistochemistry. Radiomics features were extracted by an open source software (3DSlicer) and reduced using Least absolute shrinkage and selection operator (Lasso). The support vector machine (SVM) model was developed based on the most useful predictive radiomics features. The conventional model was built by the selected clinical and morphological features. Finally, a combined model including radiomics signature, age and enhancement degree was established. Receiver operator characteristic (ROC) curve was implemented to assess the diagnostic performance of the three models. For IDH1 mutation, the combined model achieved the highest area under curve (AUC) in comparison with the SVM and conventional models (training group, AUC = 0.967, 0.939 and 0.906; validation group, AUC = 0.909, 0.880 and 0.842). Furthermore, the SVM model showed good diagnostic performance in estimating gliomas VEGF expression (validation group, AUC = 0.919). The radiomics model based on DCE-MRI and DWI can have a considerable effect on the evaluation of IDH1 mutation and angiogenesis in gliomas. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence has suggested that the cerebellum is associated with pain and migraine. In addition, the descending pain system of the brainstem is the major site of trigeminal pain processing and modulation and has been discussed as a main player in the pathophysiology of migraine. Cerebellar and brainstem structural changes associated with migraineurs remain to be further investigated. Methods: Voxel-based morphometry (VBM) (50 controls, 50 migraineurs without aura (MWoAs)) and diffusion tensor imaging (DTI) (46 controls, 46 MWoAs) were used to assess cerebellum and brainstem anatomical alterations associated with MWoAs. We utilized a spatially unbiased infratentorial template toolbox (SUIT) to perform cerebellum and brainstem optimized VBM and DTI analysis. We extracted the average diffusion values from a probabilistic cerebellar white matter atlas to investigate whether MWoAs exhibited microstructure alterations in the cerebellar peduncle tracts. Results: MWoAs showed decreased fractional anisotropy (FA) in the vermis VI extending to the bilateral lobules V and VI of the cerebellum. We also found higher axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) in the right inferior cerebellum peduncle tract in MWoAs. MWoAs exhibited both reduced gray matter volume and increased AD, MD and RD in the spinal trigeminal nucleus (SpV). Conclusion: MWoAs exhibited microstructural changes in the cerebellum and the local brainstem. These structural differences might contribute to dysfunction of the transmission and modulation of noxious information, trigeminal nociception, and conduction and integration of multimodal information in MWoAs. These findings further suggest involvement of the cerebellum and the brainstem in the pathology of migraine without aura. [ABSTRACT FROM AUTHOR]

• The current study involved 212 CWE from some major southwestern provinces of China. • SQ was used as a mediator in an attempt to discover the relationships of some clinical characteristics with SQ and QOL. • Assessment and improvement of SQ are necessary for interventions in epilepsy. • Factors with direct or mediated effects on the QOL of CWE need more exploration. Although sleep quality (SQ) reportedly affects the health-related quality of life (QOL) of patients with epilepsy, little is known about the potential association between SQ and QOL, particularly in children with epilepsy (CWE). Our study aimed to investigate the mediating effect of SQ on the QOL of CWE to obtain more information for the prevention and treatment of epilepsy in children. We collected general demographic and clinical data of 212 CWE and 79 controls (children who visited the Health Examination Department), and their guardians were instructed to answer the Children's Sleep Habits Questionnaire (CSHQ) and the optimized Quality of Life in Childhood Epilepsy Questionnaire-16 (QOLCE-16). The t -test, analysis of variance, chi-square test, and Fisher's exact test were used for between group comparisons. The Pearson correlation was used to analyze the correlation between variables. The direct, indirect, and total effects of predictors on the QOL of CWE were estimated based on an adjusted mediation model. CWE had significantly smaller long-term urban residence rates, less educated guardians, higher total CSHQ score, higher incidence of poor SQ, higher bedtime resistance, more sleep anxiety, worse sleep-disordered breathing, increased parasomnia, more daytime sleepiness, more frequent night waking, and greater sleep onset delay than controls (P < 0.05 for all). The univariable analysis showed significant differences in total CSHQ scores between CWE with different seizure frequency in the last month, whether or not drug-resistant epilepsy (DRE), and with different video electroencephalogram (VEEG) findings (P < 0.05 for all). Differences in QOLCE-16 scores between CWE with different guardian's employment status, age at diagnosis, number of anti-seizure medication (ASM) types, seizure frequency in the last month, DRE status, seizure type, VEEG findings, neuropsychological evaluation findings, magnetic resonance imaging (MRI) findings, and etiology were statistically significant (P < 0.05 for all). The correlation study indicated that the total CSHQ score was negatively correlated with the QOLCE-16 score (P < 0.05). The mediation analysis showed that DRE and VEEG abnormalities had a standardized direct effect on the QOL. Seizure frequency in the last month, DRE, and VEEG abnormalities had an indirect effect on the QOL through SQ, and their mediating effect values of SQ were 31.61 %, 13.45 %, and 14.35 %, respectively. Our findings uncovered the relationship of some clinical characteristics with SQ and QOL and characterized the nature of factors affecting the QOL of CWE. SQ could be a key factor in the prognosis of CWE experiencing epileptic seizures, and more attention should be paid on the management of SQ in interventions for epilepsy. [ABSTRACT FROM AUTHOR]