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BackgroundNon-enhancing (NE) infiltrating tumor cells beyond the contrast-enhancing (CE) bulk of tumor are potential propagators of recurrence after gross total resection of high-grade glioma.MethodsWe leveraged single-nucleus RNA sequencing on 15 specimens from recurrent high-grade gliomas (n = 5) to compare prospectively identified biopsy specimens acquired from CE and NE regions. Additionally, 24 CE and 22 NE biopsies had immunohistochemical staining to validate RNA findings.ResultsTumor cells in NE regions are enriched in neural progenitor cell-like cellular states, while CE regions are enriched in mesenchymal-like states. NE glioma cells have similar proportions of proliferative and putative glioma stem cells relative to CE regions, without significant differences in % Ki-67 staining. Tumor cells in NE regions exhibit upregulation of genes previously associated with lower grade gliomas. Our findings in recurrent GBM paralleled some of the findings in a re-analysis of a dataset from primary GBM. Cell-, gene-, and pathway-level analyses of the tumor microenvironment in the NE region reveal relative downregulation of tumor-mediated neovascularization and cell-mediated immune response, but increased glioma-to-nonpathological cell interactions.ConclusionsThis comprehensive analysis illustrates differing tumor and nontumor landscapes of CE and NE regions in high-grade gliomas, highlighting the NE region as an area harboring likely initiators of recurrence in a pro-tumor microenvironment and identifying possible targets for future design of NE-specific adjuvant therapy. These findings also support the aggressive approach to resection of tumor-bearing NE regions.

Early life adversity (ELA) characterized by threat (e.g., abuse, witnessing violence) impacts neural and physiologic systems involved in emotion reactivity; however, research on how threat exposure impacts the interplay between these systems is limited. This study investigates ELA characterized by threat as a potential moderator of the association between (a) neural activity during a negative image processing fMRI task and (b) cortisol production following a modified Trier Social Stress Test (TSST). The sample is comprised of 117 young adolescent females (Mage = 11.90 years, SD = 1.69) at elevated risk for internalizing problems. Whole-brain analyses revealed a positive association between cortisol production and increased right lateral orbitofrontal cortex activity during the emotion reactivity task. In moderation models, threat exposure interacted with bilateral amygdala activation (b = -3.34, p = 0.021) and bilateral hippocampal activation (b = -4.14, p = 0.047) to predict cortisol response to the TSST. Specifically, participants with low, but not high, levels of threat exposure demonstrated a positive association between cortisol production and neural activity in these regions, while no significant association emerged for participants with high threat exposure. Findings contribute to the growing field of research connecting physiological and neural emotion processing and response systems, suggesting that dimensions of ELA may uniquely disrupt associations between neural activation and cortisol production.

BACKGROUND: The central vein sign (CVS) is a proposed magnetic resonance imaging (MRI) biomarker for multiple sclerosis (MS); the optimal method for abbreviated CVS scoring is not yet established. OBJECTIVE: The aim of this study was to evaluate the performance of a simplified approach to CVS assessment in a multicenter study of patients being evaluated for suspected MS. METHODS: Adults referred for possible MS to 10 sites were recruited. A post-Gd 3D T2*-weighted MRI sequence (FLAIR*) was obtained in each subject. Trained raters at each site identified up to six CVS-positive lesions per FLAIR* scan. Diagnostic performance of CVS was evaluated for a diagnosis of MS which had been confirmed using the 2017 McDonald criteria at thresholds including three positive lesions (Select-3*) and six positive lesions (Select-6*). Inter-rater reliability assessments were performed. RESULTS: Overall, 78 participants were analyzed; 37 (47%) were diagnosed with MS, and 41 (53%) were not. The mean age of participants was 45 (range: 19-64) years, and most were female (n = 55, 71%). The area under the receiver operating characteristic curve (AUROC) for the simplified counting method was 0.83 (95% CI: 0.73-0.93). Select-3* and Select-6* had sensitivity of 81% and 65% and specificity of 68% and 98%, respectively. Inter-rater agreement was 78% for Select-3* and 83% for Select-6*. CONCLUSION: A simplified method for CVS assessment in patients referred for suspected MS demonstrated good diagnostic performance and inter-rater agreement.

BackgroundObesity influences the development of osteoarthritis via low-grade inflammation. Progression of local inflammation (= synovitis) increased with weight gain in overweight and obese women compared to stable weight. Synovitis could be associated with subcutaneous fat (SCF) around the knee. Purpose of the study was to investigate the effect of weight loss on synovitis progression and to assess whether SCF around the knee mediates the relationship between weight loss and synovitis progression.MethodsWe included 234 overweight and obese participants (body mass index [BMI] ≥ 25 kg/m2) from the Osteoarthritis Initiative (OAI) with > 10% weight loss (n = 117) or stable overweight (

Sensory over-responsivity (SOR) is a prevalent cross-diagnostic condition that is often associated with anxiety. The biological mechanisms underlying the co-occurrence of SOR and anxiety symptoms are not well understood, despite having important implications for targeted intervention. We therefore investigated the unique associations of SOR and anxiety symptoms with physiological and neural responses to sensory stimulation for youth with anxiety disorders (ANX), autism spectrum disorder (ASD), or typical development (TD). Age/IQ-matched youth aged 8-18 years (22 ANX; 30 ASD; 22 TD) experienced mildly aversive tactile and auditory stimuli during functional magnetic resonance imaging and then during skin conductance response (SCR) and heart rate (HR) measurements. Caregivers reported on participants' SOR and anxiety symptoms. ASD/ANX youth had elevated SOR and anxiety symptoms compared to TD. ASD/ANX youth showed similar, heightened brain responses to sensory stimulation compared to TD youth, but brain responses were more highly related to SOR symptoms in ASD youth and to anxiety symptoms in ANX youth. Across ASD/ANX youth, anxiety symptoms uniquely related to greater SCR whereas SOR uniquely related to greater HR responses to sensory stimulation. Behavioral and neurobiological over-responsivity to sensory stimulation was shared across diagnostic groups. However, findings support SOR and anxiety as distinct symptoms with unique biological mechanisms, and with different relationships to neural over-reactivity dependent on diagnostic group. Results indicate a need for targeted treatment approaches.

IntroductionThere is no consensus on either the definition of successful cognitive aging (SA) or the underlying neural mechanisms.MethodsWe examined the agreement between new and existing definitions using: (1) a novel measure, the cognitive age gap (SA-CAG, cognitive-predicted age minus chronological age), (2) composite scores for episodic memory (SA-EM), (3) non-memory cognition (SA-NM), and (4) the California Verbal Learning Test (SA-CVLT).ResultsFair to moderate strength of agreement was found between the four definitions. Most SA groups showed greater cortical thickness compared to typical aging (TA), especially in the anterior cingulate and midcingulate cortices and medial temporal lobes. Greater hippocampal volume was found in all SA groups except SA-NM. Lower entorhinal 18 F-Flortaucipir (FTP) uptake was found in all SA groups.DiscussionThese findings suggest that a feature of SA, regardless of its exact definition, is resistance to tau pathology and preserved cortical integrity, especially in the anterior cingulate and midcingulate cortices.HighlightsDifferent approaches have been used to define successful cognitive aging (SA). Regardless of definition, different SA groups have similar brain features. SA individuals have greater anterior cingulate thickness and hippocampal volume. Lower entorhinal tau deposition, but not amyloid beta is related to SA. A combination of cortical integrity and resistance to tau may be features of SA.

Background and aimsRecently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies.Design and settingCross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years).CasesCases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected.MeasurementsGraph theory metrics of segregation and integration were used to summarize SCN.FindingsMirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar.ConclusionStructural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

INTRODUCTION: The fibrous posterior atlanto-occipital membrane (PAOM) at the craniocervical junction is typically removed during decompression surgery for Chiari malformation type I (CM-I); however, its importance and ultrastructural architecture have not been investigated in children. We hypothesized that there are structural differences in the PAOM of patients with CM-I and those without. METHODS: In this prospective study, blinded pathological analysis was performed on PAOM specimens from children who had surgery for CM-I and children who had surgery for posterior fossa tumors (controls). Clinical and radiographic data were collected. Statistical analysis included comparisons between the CM-I and control cohorts and correlations with imaging measures. RESULTS: A total of 35 children (mean age at surgery 10.7 years; 94.3% white) with viable specimens for evaluation were enrolled: 24 with CM-I and 11 controls. There were no statistical demographic differences between the two cohorts. Four children had a family history of CM-I and five had a syndromic condition. The cohorts had similar measurements of tonsillar descent, syringomyelia, basion to C2, and condylar-to-C2 vertical axis (all p>0.05). The clival-axial angle was lower in patients with CM-I (138.1 vs. 149.3 degrees, p = 0.016). Morphologically, the PAOM demonstrated statistically higher proportions of disorganized architecture in patients with CM-I (75.0% vs. 36.4%, p = 0.012). There were no differences in PAOM fat, elastin, or collagen percentages overall and no differences in imaging or ultrastructural findings between male and female patients. Posterior fossa volume was lower in children with CM-I (163,234 mm3 vs. 218,305 mm3, p

BackgroundProgression to cirrhosis in non-alcoholic steatohepatitis (NASH) is associated with a decrease in liver fat. However, the prognostic significance of liver fat content in NASH-related significant fibrosis and cirrhosis is unclear.AimTo investigate the risk of decompensation, hepatocellular carcinoma (HCC) and mortality stratified by liver fat content in NASH-related significant fibrosis and cirrhosis.MethodsIn this meta-analysis of individual participant data, 456 patients with both magnetic resonance elastography (MRE) and MRI-derived protein density fat fraction (MRI-PDFF) were enrolled, and 296 patients with longitudinal follow-up were analysed. MRE combined with fibrosis-4 (MEFIB-index), and MRI-PDFF were used to measure liver fibrosis and fat, respectively. MEFIB-negative, MEFIB-positive+ MRI-PDFF ≥5% and MEFIB-positive+ MRI-PDFF

BACKGROUND: Magnetic resonance image only (MRI-only) simulation for head and neck (H&N) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic computed tomography (sCT) is generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCT. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI-only RT planning or compensatory methods for accurate dosimetric calculation. PURPOSE: The aim of this study was to investigate if Hounsfield unit (HU) voxel misassignments from sCT images result in dosimetric errors in clinical treatment plans. METHODS: Fourteen H&N cancer patients undergoing same-day CT and 3T MRI simulation were retrospectively identified. MRI was deformed to the CT using multimodal deformable image registration. sCTs were generated from T1w DIXON MRIs using a commercially available deep learning-based generator (MRIplanner, Spectronic Medical AB, Helsingborg, Sweden). Tissue voxel assignment was quantified by creating a CT-derived HU threshold contour. CT/sCT HU differences for anatomical/target contours and tissue classification regions including air (500 HU) were quantified. t-test was used to determine if sCT/CT HU differences were significant. The frequency of structures that had a HU difference > 80 HU (the CT window-width setting for intra-cranial structures) was computed to establish structure classification accuracy. Clinical intensity modulated radiation therapy (IMRT) treatment plans created on CT were retrospectively recalculated on sCT images and compared using the gamma metric. RESULTS: The mean ratio of sCT HUs relative to CT for air, adipose tissue, soft tissue, spongy and cortical bone were 1.7 ± 0.3, 1.1 ± 0.1, 1.0 ± 0.1, 0.9 ± 0.1 and 0.8 ± 0.1 (value of 1 indicates perfect agreement). T-tests (significance set at t = 0.05) identified differences in HU values for air, spongy and cortical bone in sCT images compared to CT. The structures with sCT/CT HU differences > 80 HU of note were the left and right (L/R) cochlea and mandible (>79% of the tested cohort), the oral cavity (for 57% of the tested cohort), the epiglottis (for 43% of the tested cohort) and the L/R TM joints (occurring > 29% of the cohort). In the case of the cochlea and TM joints, these structures contain dense bone/air interfaces. In the case of the oral cavity and mandible, these structures suffer the additional challenge of being positionally altered in CT versus MRI simulation (due to a non-MR safe immobilizing bite block requiring absence of bite block in MR). Finally, the epiglottis HU assignment suffers from its small size and unstable positionality. Plans recalculated on sCT yielded global/local gamma pass rates of 95.5% ± 2% (3 mm, 3%) and 92.7% ± 2.1% (2 mm, 2%). The largest mean differences in D95, Dmean , D50 dose volume histogram (DVH) metrics for organ-at-risk (OAR) and planning tumor volumes (PTVs) were 2.3% ± 3.0% and 0.7% ± 1.9% respectively. CONCLUSIONS: In this cohort, HU differences of CT and sCT were observed but did not translate into a reduction in gamma pass rates or differences in average PTV/OAR dose metrics greater than 3%. For sites such as the H&N where there are many tissue interfaces we did not observe large scale dose deviations but further studies using larger retrospective cohorts are merited to establish the variation in sCT dosimetric accuracy which could help to inform QA limits on clinical sCT usage.

Background & aimsPathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease.MethodsUsing individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies.ResultsEligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology.ConclusionsHistological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values.Impact and implicationsMagnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.

Purpose To describe the design, conduct, and results of the Breast Multiparametric MRI for prediction of neoadjuvant chemotherapy Response (BMMR2) challenge. Materials and Methods The BMMR2 computational challenge opened on May 28, 2021, and closed on December 21, 2021. The goal of the challenge was to identify image-based markers derived from multiparametric breast MRI, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI, along with clinical data for predicting pathologic complete response (pCR) following neoadjuvant treatment. Data included 573 breast MRI studies from 191 women (mean age [±SD], 48.9 years ± 10.56) in the I-SPY 2/American College of Radiology Imaging Network (ACRIN) 6698 trial (ClinicalTrials.gov: NCT01042379). The challenge cohort was split into training (60%) and test (40%) sets, with teams blinded to test set pCR outcomes. Prediction performance was evaluated by area under the receiver operating characteristic curve (AUC) and compared with the benchmark established from the ACRIN 6698 primary analysis. Results Eight teams submitted final predictions. Entries from three teams had point estimators of AUC that were higher than the benchmark performance (AUC, 0.782 [95% CI: 0.670, 0.893], with AUCs of 0.803 [95% CI: 0.702, 0.904], 0.838 [95% CI: 0.748, 0.928], and 0.840 [95% CI: 0.748, 0.932]). A variety of approaches were used, ranging from extraction of individual features to deep learning and artificial intelligence methods, incorporating DCE and DWI alone or in combination. Conclusion The BMMR2 challenge identified several models with high predictive performance, which may further expand the value of multiparametric breast MRI as an early marker of treatment response. Clinical trial registration no. NCT01042379 Keywords: MRI, Breast, Tumor Response Supplemental material is available for this article. © RSNA, 2024.

The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain-cognition correlations revealed region-specific associations.

22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1-weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source-based morphometry (SBM) pipeline (SS-Detect) to generate structural brain patterns (SBPs) that capture co-varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV-SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel-based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism.

BackgroundHepatocellular carcinoma (HCC) is a common liver malignancy with limited treatment options. Previous studies expressed the potential synergy of sorafenib and NK cell immunotherapy as a promising approach against HCC. MRI is commonly used to assess response of HCC to therapy. However, traditional MRI-based metrics for treatment efficacy are inadequate for capturing complex changes in the tumor microenvironment, especially with immunotherapy. In this study, we investigated potent MRI radiomics analysis to non-invasively assess early responses to combined sorafenib and NK cell therapy in a HCC rat model, aiming to predict multiple treatment outcomes and optimize HCC treatment evaluations.MethodsSprague Dawley (SD) rats underwent tumor implantation with the N1-S1 cell line. Tumor progression and treatment efficacy were assessed using MRI following NK cell immunotherapy and sorafenib administration. Radiomics features were extracted, processed, and selected from both T1w and T2w MRI images. The quantitative models were developed to predict treatment outcomes and their performances were evaluated with area under the receiver operating characteristic (AUROC) curve. Additionally, multivariable linear regression models were constructed to determine the correlation between MRI radiomics and histology, aiming for a noninvasive evaluation of tumor biomarkers. These models were evaluated using root-mean-squared-error (RMSE) and the Spearman correlation coefficient.ResultsA total of 743 radiomics features were extracted from T1w and T2w MRI data separately. Subsequently, a feature selection process was conducted to identify a subset of five features for modeling. For therapeutic prediction, four classification models were developed. Support vector machine (SVM) model, utilizing combined T1w + T2w MRI data, achieved 96% accuracy and an AUROC of 1.00 in differentiating the control and treatment groups. For multi-class treatment outcome prediction, Linear regression model attained 85% accuracy and an AUC of 0.93. Histological analysis showed that combination therapy of NK cell and sorafenib had the lowest tumor cell viability and the highest NK cell activity. Correlation analyses between MRI features and histological biomarkers indicated robust relationships (r = 0.94).ConclusionsOur study underscored the significant potential of texture-based MRI imaging features in the early assessment of multiple HCC treatment outcomes.

Biodegradable tissue engineering scaffolds have garnered increasing interest for their role in providing mechanical support, promoting tissue regeneration, and eliminating the need for removal. However, the in vivo degradation processes remain challenging to track. Here, a novel biodegradable polymer, N‐methyldiethanolamine (MDEA) and Gadolinium(III) diethylenetriamine pentaacetate (Gd‐DTPA) modified biodegradable photoluminescent polymers (BPLPMGd), which combines near‐infrared (NIR) fluorescence and magnetic resonance (MR) dual‐modality imaging are introduced to monitor scaffold degradation in vivo. The chemical structure of BPLPMGd is characterized and its dual‐imaging properties in vitro are evaluated. Subsequently, non‐invasive dual‐modality imaging to track the degradation of implanted BPLPMGd scaffolds is performed in a rat model, comparing these results with histological data. This approach reveals that BPLPMGd enables reliable non‐invasive tracking of the degradation, where NIR fluorescence imaging offers a qualitative and quantitative analysis of scaffold mass loss, total volume and solid content changes, while magnetic resonance imaging (MRI) details structural and morphological changes, allowing for 5D monitoring of implant degradation, including 3D structure, location, mass, volume, and geometry. The combination of these imaging modalities provides a comprehensive view of scaffold degradation, where the synergistic use of both yields results greater than either modality alone, offering unprecedented 5D information of implantable devices. This innovative approach has potential applications in regenerative engineering and beyond. [ABSTRACT FROM AUTHOR]

The incorporation of multiple Fe(III) centers bridged by rigid ligands into a coordination cage represents a powerful approach for designing effective MRI contrast agents. In this context, an octahedral coordination cage with six high-spin Fe(III) centers is shown to be water soluble, robust towards dissociation and has effective relaxivity as a T1 MRI probe in solution and in mice. [ABSTRACT FROM AUTHOR]

BACKGROUND: Cervical neutral position magnetic resonance imaging is widely used for the diagnosis and treatment of cervical spondylotic myelopathy. However, it is not possible for patients to maintain the exact same position of the head and neck during repeated cervical magnetic resonance imaging examinations. The cervical spine undergoes minor flexion and extension movements in the sagittal plane, and the head may have a certain degree of variation in flexion and extension. Whether these changes in the neutral position of the cervical spine affect the volume of cervical discs herniation and cervical curvature is unclear. OBJECTIVE: Using artificial intelligence-assisted measurement, this study aimed to analyze the accuracy and reliability of magnetic resonance imaging examinations for measuring the volume of cervical discs herniation and cervical curvature in patients with cervical spondylotic myelopathy undergoing two consecutive cervical neutral positions in the short term. METHODS: A retrospective study was conducted on patients with cervical spondylotic myelopathy who underwent conservative treatment and underwent two consecutive cervical magnetic resonance imaging examinations within three months between June 2012 and June 2023. We proposed the use of occipitalthoracic distance and occipital-thoracic angle to evaluate the variation in flexion and extension of the head in the neutral position of the cervical spine. Based on the changes in occipital-thoracic angle, patients were divided into occipital-thoracic angle increase group and occipital-thoracic angle decrease group. Cervical discs herniation volume, C2-6 Cobb angle, and cervical (C3-C7) curvature were measured using artificial intelligence-assisted measurement software. Normal distribution data were represented by mean±SD, while non-normal distribution data were represented by the median (interquartile range). Spearman’s rank correlation coefficient was used to analyze the correlation between changes in Cobb angle, cervical (C3-C7) curvature, and cervical discs herniation volume. RESULTS AND CONCLUSION: (1) A total of 104 patients and 326 cervical discs herniation were included in the study. There were 47 patients in the occipitalthoracic angle increase group and 57 patients in the occipital-thoracic angle decrease group. (2) Extension and flexion index of the head: There were no significant differences in occipital-thoracic distance and occipital-thoracic angle during the initial diagnosis and follow-up examination. The variation of occipitalthoracic distance was 0.035 (3.23) mm, and the variation of occipital-thoracic angle was -0.31 (3.28)°. The deviation range of occipital-thoracic distance and occipital-thoracic angle was small, and there was no significant correlation. (3) Cervical curvature index: There were no significant differences in C2-6 Cobb angle and C3-C7 curvature during the initial diagnosis and follow-up examination. There were no significant differences in C2-6 Cobb angle and C3-C7 curvature between the occipital-thoracic angle increase group and occipital-thoracic angle decrease group. (4) There was no significant difference in volume of cervical discs herniation during the initial diagnosis and follow-up examination. There was no significant difference in volume of cervical discs herniation between the occipital-thoracic angle increase group and occipital-thoracic angle decrease group. There was no significant correlation between the change of cervical discs herniation volume and the change of C2-6 Cobb angle and the cervical (C3-C7) curvature. (5) These results indicate that in the neutral position of the cervical spine, there were negligible minor flexion and extension movements in the sagittal plane, and the head was limited to a specific position. Although the head has a certain range of flexion and extension variation, it does not affect the accuracy and reliability of parameters including cervical discs herniation volume, C2-6 Cobb angle, and cervical (C3-C7) curvature. [ABSTRACT FROM AUTHOR]

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to non-invasively image blood-brain barrier leakage, yet its clinical utility has been hampered by issues such as noise and partial volume artifacts. In this retrospective study involving 306 adult patients with diffuse glioma, we applied deep learning-based super-resolution and denoising (DLSD) techniques to enhance the signal-to-noise ratio (SNR) and resolution of DCE-MRI. Quantitative analysis comparing standard DCE-MRI (std-DCE) and DL-enhanced DCE-MRI (DL-DCE) revealed that DL-DCE achieved significantly higher SNR and contrast-to-noise ratio (CNR) compared to std-DCE (SNR, 52.09 vs 27.21; CNR, 9.40 vs 4.71; P < 0.001 for all). Diagnostic performance assessed by the area under the receiver operating characteristic curve (AUROC) showed improved differentiation of WHO grades based on a pharmacokinetic parameter (AUC, 0.88 vs 0.83, P = 0.02), while remaining comparable to std-DCE in other parameters. Analysis of arterial input function (AIF) reliability demonstrated that exhibited superior agreement compared to , as indicated by mostly higher intraclass correlation coefficients (Time to peak, 0.79 vs 0.43, P < 0.001). In conclusion, DLSD significantly enhances both the image quality and reliability of DCE-MRI in patients with diffuse glioma, while maintaining or improving diagnostic performance. [ABSTRACT FROM AUTHOR]

Medical image processing generally contains high components of noise produced by interference, compression and use of imperfect instrument during acquisition or transmission. An effective imaging devicei.e. Magnetic Resonance Imagingmay diagnose the disease by acute analysis of dissectional anatomical soft tisses of human. In general, MR images are of poor contrast in lieu of blurriness, out of focused and lack of brightness iside the machine. In this paper, hybridization approaches i.e. Median-Wiener filter (MW), Wiener-Median filter (WM) and other combinations like WMWM & MWMW are proposed for MR image enhancement. The results are further compared with various filtering algorithms i.e. Average filter, Median Filter, Wiener Filter &Gaussian filter and in terms of MSE, PSNR, RMSE, MAE. The proposed hybridization filtering technique gives better outcomes comparatively. [ABSTRACT FROM AUTHOR]

Brain tumour segmentation plays a critical role in the diagnosis, treatment planning, and monitoring of brain tumour patients. However, accurate and efficient segmentation remains challenging due to the complex and heterogeneous structure of brain tumour regions. The current CNN models have shown good performance in brain tumour segmentation and identification, but several research challenges, like limited generalizability, Adaptive Model Complexity, etc., still need to be addressed. In this research, we propose a novel approach that combines the progressively growing and One-Shot learning approaches with a semantic segmentation network to enhance the accuracy and generalization of brain tumour segmentation in MRI images. Our method joins the strengths of progressively growing and One-Shot learning techniques with a semantic segmentation network, enabling improved generalization, effective feature selection, and continuous integration of contextual information at the pixel level. Experimental results on benchmark Br35H MRI image datasets demonstrate the dominance of our approach over existing methods in terms of segmentation accuracy and adaptability to diverse brain tumour instances. A total of 3000 images (1500 tumorous and 1500 non-tumorous images) were used during the training and testing of the model. The evaluation metrics reveal the high performance of our proposed model for brain tumour segmentation. Achieving high Dice Similarity Coefficients (0.9849), Intersection over Union (0.9319), accuracy (0.9520), precision (0.9235), and recall (0.9572) across average training, validation, and test sets. These results demonstrate the model's efficiency in accurately segmenting both tumorous and non-tumorous regions in MRI images. [ABSTRACT FROM AUTHOR]

Purpose: (1) to investigate the consecutive changes in hip muscle volume in patients with femoroacetabular impingement syndrome (FAIS) during the initial postoperative period, and (2) to determine the potential effect of the early changes in hip muscle volume on clinical outcomes. Methods: Data between March 2021 and March 2022 was reviewed. Patients diagnosed with FAIS based on clinical symptoms and radiographic findings, and undergoing hip arthroscopic treatment were included. Exclusion criteria were incomplete MRI data, prior history of hip surgery, and concomitant hip conditions including hip osteoarthritis with a Tönnis grade > 1, avascular necrosis, Legg-Calvé-Perthes disease, osteoid osteoma, synovial chondromatosis, pigmented villonodular synovitis, and developmental dysplasia of the hip (DDH). MRI was performed preoperatively and 3, 6, 12-month postoperatively. Cross-sectional area (CSA) of hip muscles including rectus femoris (RF), iliocapsularis (IC), iliopsoas (IP), gluteus medius/minimus complex (G-med/min), and gluteus maximus (G-max) were collected on MRI. The CSA was corrected by body surface area (BSA). Preoperative and a minimum of 2-year postoperative patient-reported outcome (PRO) scores including Visual Analog pain Scale (VAS), modified Harris Hip Score (mHHS), and international Hip Outcome Tool, 12-component form (iHOT-12) were collected. A multivariate linear regression model was built to determine the influence of the potential factors on postoperative PROs. Results: A total of 76 patients were included in the study. Compared to the preoperative level, decreased volume of RF and G-max, and increased IC/RF ratio were observed at postoperative 3 months (all with P <.05). Both G-med/min and G-max presented decreased volume at postoperative 6 months (all with P <.05). G-med/min presented decreased volume (P =.001) at postoperative 12 months. Changes in RF at postoperative 3 months and 12 months were positively related to improvement of iHOT-12 (Beta = 0.371, P =.012 and Beta = 0.330, P =.026, respectively). Changes in IC at postoperative 6-month was positively related to improvement of mHHS (Beta = 0.367, P =.027) and iHOT-12 (Beta = 0.315, P =.044). Conclusion: During the initial first year following arthroscopic treatment for FAIS, decreased volume of the RF and gluteal muscles was observed. Early changes in volume of RF and IC were positively correlated to the improvement of minimum 2-year PROs. Level of evidence: Level IV; case series. [ABSTRACT FROM AUTHOR]

Background: Cryptococcus is an opportunistic infection acquired through inhalation from the environment, primarily affecting individuals with compromised immune systems. It typically leads to pneumonia upon passing through lung tissue. The infection can disseminate to various organs via the bloodstream, resulting in meningitis or encephalitis in the central nervous system. Disseminated Cryptococcus has been reported to involve the skin, liver, eyes, lymph nodes, bone marrow, spleen, kidneys, and intestines, significantly increasing morbidity and mortality. However, pancreatic involvement in Cryptococcus is relatively rare, and a few case reports have highlighted severe organ damage and high mortality rates. Case presentation: In this case report, we present the case of a 36-year-old Asian man who presented with a 2-week history of headaches and blurred vision in his right eye. Brain magnetic resonance imaging revealed multiple brain masses, along with a mass in the lower left lung field and a tumor in the pancreatic tail, as detected by chest computed tomography. Endoscopic ultrasound-guided fine needle biopsy and computed tomography-guided lung biopsy confirmed the diagnosis of disseminated cryptococcal infection involving the pancreas, lung, and brain. The patient's clinical condition improved following antifungal therapy. Additionally, we identified anti-granulocyte–macrophage colony-stimulating factor antibody as a risk factor for disseminated cryptococcal infection in this patient. Conclusion: Disseminated cryptococcosis can be a potentially lethal condition, as highlighted by previous literature. However, early diagnosis using contrast-enhanced harmonic endoscopic ultrasound and endoscopic ultrasound-guided biopsies, as well as prompt treatment as demonstrated in our case, can improve outcomes and prevent mortality. [ABSTRACT FROM AUTHOR]

Background Objective Animals Methods Results Conclusion and Clinical Importance Limited information is available regarding the clinical features, treatment, and prognosis of neosporosis in adult dogs.Describe the clinical signs, laboratory findings, magnetic resonance imaging (MRI) findings, treatment and outcome in adult dogs (>6 months) diagnosed with neosporosis based on consistent clinical signs and positive serology (titer ≥1 : 800) at a referral hospital in Sydney, Australia.Twenty‐one client‐owned dogs.Retrospective case series of affected dogs between 2010 and 2023. Survival times were determined from onset of clinical signs to date of death or censoring.Clinical signs varied, and were indicative of generalized myopathy (6 dogs), multifocal intracranial disease (7 dogs), myelopathy (4 dogs), polyneuropathy (2 dogs) and single cases of focal myopathy and cerebellar disease. Serum creatine kinase activity was markedly increased (median, 3369 U/L) in most dogs. The most common MRI abnormalities were multifocal intracranial abnormalities (7/13 dogs) and muscle changes (5/13 dogs) whereas T2‐weighted cerebellar abnormalities (2/13 dogs) and cerebellar atrophy (1/13) were less common. Treatment response was complete (resolution to normal) in 8 dogs, incomplete (persistent neurological deficits) in 6 dogs, but there was minimal response in 7 dogs. Thirteen dogs (62%) were alive after 6 months and 12 dogs (57%) alive after 1 year. Relapse was common, with 4 dogs experiencing at least 1 relapse event during the follow‐up period.Adult‐onset neosporosis is uncommon and has variable clinical presentations. Treatment response also is variable, and relapse can occur, even among patients that respond completely to initial treatment. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation Paramagnetic rim lesions (PRLs) are a biomarker of chronic active lesions (CALs), and an important driver of neurological disability in multiple sclerosis (MS). The reason subtending some acute lesions evolvement into CALs is not known. Here we ask whether a relatively lower oxygen content is linked to CALs.In this prospective cross‐sectional study, 64 people with multiple sclerosis (PwMS), clinically isolated syndrome and radiologically isolated syndrome underwent a 7.0 Tesla (7 T) brain magnetic resonance imaging (MRI). The scanning protocol included a T2‐w fluid‐attenuated inversion recovery (FLAIR), and a single echo gradient echo from which susceptibility‐weighted imaging (SWI) was derived. WM lesions were identified on the T2‐w‐FLAIR whilst PRLs were identified on the SWI sequence. T2‐lesions were classified as PRLs and rimless lesions (PRLs‐). We registered a universal vascular atlas to each subject's T2‐w‐FLAIR and classified each T2‐lesions according to its location into watershed‐ (ws), non‐watershed‐ (nws), and mixed‐lesion (m). Ws‐lesions were defined as lesions that were fully located in a region between the territories of two major arteries.Out of 1,975 T2‐lesions, 88 (4.5%) were PRLs. Ws‐regions had a higher number (p = 0.005) and proportion (p < 0.001) of PRLs‐ compared to nws‐regions. Ws‐PRL‐ were larger compared to nws‐ones (p = 0.009). The number (p = 0.043) and proportion (p < 0.001) of PRLs was higher in ws‐regions compared to nws‐ones. Ws‐PRLs were not significantly larger than nws‐ones (p = 0.195).We propose the novel concept of a link between arterial vascularization and chronic activity in MS by demonstrating a preferential localization of CALs in ws‐territories. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Methods Results Conclusions To evaluate the association of standardized prenatal imaging parameters and immediate neonatal variables with mortality prior to discharge in infants with isolated left congenital diaphragmatic hernia (LCDH), and to compare the performance of ultrasound‐ and magnetic resonance imaging (MRI)‐based severity grading for the prediction of neonatal mortality.This was a retrospective study of infants with prenatally diagnosed isolated LCDH referred to a single tertiary center between 2008 and 2020. Fetuses with right or bilateral congenital diaphragmatic hernia, additional major structural anomaly or known genetic condition, as well as cases that underwent fetal intervention or declined postnatal intervention, were excluded. Ultrasound and MRI images were reviewed retrospectively. Univariable and multivariable analyses were performed, incorporating prenatal and immediate neonatal factors to analyze the association with neonatal mortality prior to discharge, and a prediction calculator was generated. The performance of ultrasound and that of MRI for the prediction of neonatal mortality were compared.Of 253 pregnancies with fetal CDH, 104 met the inclusion criteria, of whom 77 (74%) neonates survived to discharge. Seventy‐five fetuses underwent both prenatal ultrasound and MRI. On multivariable analysis, observed/expected (o/e) lung‐to‐head ratio and o/e total fetal lung volume were associated independently with neonatal death (adjusted odds ratio, 0.89 (95% CI, 0.83–0.95) and 0.90 (95% CI, 0.84–0.97), respectively), whereas liver position was not. There was no significant difference in predictive performance between using ultrasound and MRI together (area under the receiver‐operating‐characteristics curve (AUC), 0.85 (95% CI, 0.76–0.93)) compared with using ultrasound alone (AUC, 0.81 (95% CI, 0.72–0.90); P = 0.19). The addition of neonatal parameters (gestational age at birth and small‐for‐gestational age) did not improve model performance (AUC, 0.87 (95% CI, 0.80–0.95)) compared with the combined ultrasound and MRI model (P = 0.22). There was poor agreement between severity assessment on ultrasound and MRI (Cohen's κ, 0.19). Most discrepancies were seen among cases deemed to be non‐severe on ultrasound and severe on MRI, and outcomes were more consistent with MRI‐based prognostication.In fetuses with prenatally diagnosed isolated LCDH, mortality prediction using standardized ultrasound and MRI measurements performed reasonably well. In cases classified as non‐severe on ultrasound, MRI is recommended, as it may provide more accurate prognostication and assist in the determination of candidacy for fetal intervention. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusion Level of Evidence Posterior elongation of the physiological terminal sulcus (TS) due to lateral femoral condyle impaction fracture (LFC‐IF) after an anterior cruciate ligament (ACL) tear could potentially decrease the weight‐bearing area of the tibiofemoral joint, decrease the tension on lateral meniscus and cause flattening of the LFC which would influence rotational knee motion and cause anisometry of the lateral and anterolateral stabilizers. Therefore, the purpose of the study was to assess if the LFC‐IF elongates the physiological TS posteriorly.One hundred patients magnetic resonance images (MRIs) (75 males, 25 females, mean age 32.2 years, SD = 8.2) were included with a 1:1 ratio between the full‐thickness ACL tear group and the control group (patients with knee MRI performed due to other reasons, with no tear of ACL on MRI and negative clinical tests). Two independent raters evaluated the sagittal T1‐weighted preselected MRI scans. The principal measurement of interest was the distance from the intersection of the Blumensaat line with subchondral bone to the posterior border of the TS/LFC‐IF.The median distance from the Blumensaat line to the posterior border of the TS/LFC‐IF was significantly higher in the ACL tear group: 14.3 mm, interquartile range (IQR) = 11.6–16.4 mm versus control group: 12.8 mm, IQR = 9.0–15.0 mm, p = 0.038. Intrarater and inter‐rater reliabilities were >0.90.LFC‐IF after full‐thickness ACL tear significantly elongates the physiological TS in the posterior direction.Level III. [ABSTRACT FROM AUTHOR]

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (n = 34,725; 45–82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bimodal distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex, and complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (n = 228; 21–36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes. [Display omitted] • A pipeline is provided to extract 5 phenotypes for each of 40 sulci from brain MRI • Sulcal phenotype networks consistently find an axis of linear to complex shape • Adult sulcal complexity is linked to heritability, function, and fetal sulcation • Linear sulci demarcate zones of expression for developmentally enriched genes Snyder et al. develop measures of human cortical folding, revealing an axis of linear to complex sulcal shape across the adult cortex. This axis predicts the phased emergence of sulci in utero and boundaries of cortical gene expression, implicating these processes in the formation of mature cortical geometry. [ABSTRACT FROM AUTHOR]

Background: Spontaneous subarachnoid hemorrhage (SAH) often results in altered cerebrospinal fluid (CSF) flow and secondary hydrocephalus, yet the mechanisms behind these phenomena remain poorly understood. This study aimed to elucidate the impact of SAH on individual CSF flow patterns and their association with secondary hydrocephalus. Methods: In patients who had experienced SAH, changes in CSF flow were assessed using cardiac-gated phase-contrast magnetic resonance imaging (PC-MRI) at the Sylvian aqueduct and cranio-cervical junction (CCJ). Within these regions of interest, volumetric CSF flow was determined for every pixel and net CSF flow volume and direction calculated. The presence of acute or chronic hydrocephalus was deemed from ventriculomegaly and need of CSF diversion. For comparison, we included healthy subjects and patients examined for different CSF diseases. Results: Twenty-four SAH patients were enrolled, revealing a heterogeneous array of CSF flow alterations at the Sylvian aqueduct. The cardiac-cycle-linked CSF net flow in Sylvian aqueduct differed from the traditional figures of ventricular CSF production about 0.30–0.40 mL/min. In 15 out of 24 patients (62.5%), net CSF flow was retrograde from the fourth to the third and lateral ventricles, while it was upward at the cranio-cervical junction in 2 out of 2 patients (100%). The diverse CSF flow metrics did not distinguish between individuals with acute or chronic secondary hydrocephalus. In comparison, 4/4 healthy subjects showed antegrade net CSF flow in the Sylvian aqueduct and net upward CSF flow in CCJ. These net CSF flow measures also showed interindividual variability among other patients with CSF diseases. Conclusions: There is considerable inter-individual variation in net CSF flow rates following SAH. Net CSF flow in the Sylvian aqueduct differs markedly from the traditional ventricular CSF production rates of 0.30–0.40 mL/min in SAH patients, but less so in healthy subjects. Furthermore, the cardiac-cycle-linked net CSF flow rates in Sylvian aqueduct and CCJ suggest an important role of extra-ventricular CSF production. [ABSTRACT FROM AUTHOR]

Background: Focal epilepsy is common in children and adults with mitochondrial disease. Seizures are often refractory to pharmacological treatment and, in this patient group, frequently evolve to refractory focal status epilepticus (also known as epilepsia partialis continua). Where this occurs, the long-term prognosis is poor. Transcranial DC stimulation (tDCS) is a promising, non-invasive, adjunctive treatment alternative to common surgical procedures. Limited recruitment of study participants with this rare disease and the ethical challenges of administering a treatment to one group and not another, while maintaining strict methodological rigour can pose challenges to the design of a clinical study. Method: We designed the first delayed start, double-blinded, sham-controlled study to evaluate the efficacy of tDCS as an adjunctive treatment for focal epilepsy. We will include participants with a genetically confirmed diagnosis of mitochondrial disease with drug-resistant focal epilepsy aged ≥ 2 years, aiming to collect 30 episodes of focal status epilepticus, each treated for a maximum period of 14 days. The early start intervention arm will receive tDCS from day 1. The delayed start intervention arm will receive sham stimulation until crossover on day 3. Our primary endpoint is a greater than 50% reduction from baseline (on day 0) in seizure frequency assessed by 3x daily reporting, accelerometery, and video monitoring. Changes in the underlying epileptogenic focus within the brain related to the tDCS intervention will be assessed by magnetic resonance imaging (MRI) and/or electroencephalography (EEG). Discussion: Study results in favour of treatment efficacy would support development of tDCS into a mainstream treatment option for focal epileptic seizures related to mitochondrial disease. Trials registration: ISRCTN: 18,241,112; registered on 16/11/2021. [ABSTRACT FROM AUTHOR]

Background: Medical imaging is an integral part of healthcare. Globalization has resulted in increased mobilization of migrants to new host nations. The association between migration status and utilization of medical imaging is unknown. Methods and findings: A retrospective population-based matched cohort study was conducted in Ontario, Canada from April 1, 1995 to December 31, 2016. A total of 1,848,222 migrants were matched 1:1 to nonmigrants in the year of migration on age, sex, and geography. Utilization of computed tomography (CT), magnetic resonance imaging (MRI), radiography, and ultrasonography was determined. Rate differences per 1,000 person-years comparing migrants to nonmigrants were calculated. Relative rates were calculated using a recurrent event framework, adjusting for age, sex, and time-varying socioeconomic status, comorbidity score, and access to a primary care provider. Estimates were stratified by migration age: children and adolescents (≤19 years), young adults (20 to 39), adults (40 to 59), and older adults (≥60). Utilization rates of CT, MRI, and radiography were lower for migrants across all age groups compared with Ontario nonmigrants. Increasing age at migration was associated with larger differences in utilization rates. Older adult migrants had the largest gap in imaging utilization. The longer the time since migration, the larger the gap in medical imaging use. In multivariable analysis, the relative rate of imaging was approximately 20% to 30% lower for migrants: ranging from 0.77 to 0.88 for CT and 0.72 to 0.80 for MRI imaging across age groups. Radiography relative rates ranged from 0.84 to 0.90. All migrant age groups, except older adults, had higher rates of ultrasonography. The indication for imaging was not captured, thus it was not possible to determine if the imaging was necessary. Conclusions: Migrants utilized less CT, MRI, and radiography but more ultrasonography. Older adult migrants used the least amount of imaging compared with nonmigrants. Future research should evaluate whether lower utilization is due to barriers in healthcare access or health-seeking behaviors within a universal healthcare system. Author summary: Why was this study done?: Globalization has led to an increasing number of migrants who must navigate a new healthcare system in the countries they migrate to. Migrants have been shown to use specific health services, such as cancer screening or general practitioner use, at a lower rate than those born in the host country. Limited studies have been performed which have evaluated the longitudinal usage patterns of medical imaging of migrants compared with nonmigrants. What did the researchers do and find?: A retrospective cohort study of 1,848,222 migrants to Ontario, Canada were matched to an equal number of nonmigrants and evaluated for the utilization rates of computerized tomography, magnetic resonance imaging, radiography, and ultrasonography medical imaging. Usage rates of medical imaging were 20% to 30% lower in migrants compared with nonmigrants. A longer time since migration resulted in larger disparities in imaging use, with the largest age-related differences in utilization patterns observed in older migrants. What do these findings mean?: Large disparities in the utilization of medical imaging within this universal healthcare system exist which warrants further investigation to uncover mechanisms of action. These data may be used by healthcare policymakers and practitioners in regions where migration plays a significant role in its population. [ABSTRACT FROM AUTHOR]

Background: Annual breast magnetic resonance imaging (MRI) is highly recommended to assist mammography for women at high risk of breast cancer (BC). This study explored the knowledge, attitude, and willingness toward breast MRI screening among women at high risk of BC. Methods: This cross-sectional study enrolled women at high risk of BC between August 2022 and January 2023 in Beijing, China. A structural equation model (SEM) was used to analyze the relationships among knowledge, attitude, and willingness. Results: A total of 596 questionnaires were collected, and 412 questionnaires (69.13%) were valid. The women's knowledge and attitude scores were 7.75 ± 2.79 (possible range: 0–12) and 48.53 ± 6.31 (possible range: 13–65). Among the women, 297 (72.09%) were willing to undergo regular breast MRI screening. The SEM showed that knowledge had direct effect on attitude [β = 0.77, 95% CI: (0.57, 0.98), P < 0.001], the attitude had direct effect on willingness [β = 0.02, 95% CI: (0.01, 0.02), P < 0.001], knowledge had an indirect effect on willingness through attitude [β = 0.01, 95% CI: (0.01,0.02), P < 0.001], and the direct effect of knowledge on practice was not significant. Conclusions: The women at high risk of BC had insufficient knowledge and a relatively positive attitude toward breast MRI screening. Most of them were willing to undergo regular breast MRI screening. Advertising and public health education programs should be designed to improve their knowledge and attitude, therefore improving their willingness and practice. [ABSTRACT FROM AUTHOR]

Background: Rice body formation is an uncommon, nonspecific inflammatory process. Certain clinical features, such as chronic synovitis associated with rheumatoid arthritis, tuberculous arthritis, and osteoarthritis, can induce a non-specific response that may lead to the development of rice bodies. Currently, the etiological and prognostic significance of rice bodies remains unknown. Magnetic resonance imaging (MRI) is the preferred diagnostic imaging modality for evaluating rice body formation. Case presentation: The patient, a 44-year-old female, presented with bursitis of the hip joint and the presence of numerous rice bodies. This case is exceptionally rare and unusual as it involves a combination of hip dysplasia and pelvic fracture. The patient underwent a one-stage resection of the rice body, internal fixation of the acetabular fracture, and two-stage total hip arthroplasty, resulting in an immediate improvement in her symptoms. We reviewed the relevant literature and observed that the majority of rice bodies were predominantly found within the capsules of the shoulder and knee joints, while instances of hip joint rice body bursitis were relatively infrequent. To our knowledge, there have been no previous reports documenting a case of hip joint rice body bursitis in conjunction with hip dysplasia and pelvic fracture. Conclusion: This paper presents the rare case of hip joint rice body bursitis combined with hip dysplasia and pelvic fracture, and is one of the highlights. [ABSTRACT FROM AUTHOR]

In this case, a 66‐year‐old female patient presented with the chief complaint of abdominal distention. Computed tomography and magnetic resonance imaging revealed no enlarged ovaries or obvious primary lesions; however, massive ascites and peritoneal disseminated nodules were observed. Ascites cytology revealed adenocarcinoma and immunohistochemical findings suggested serous carcinoma. The patient then underwent tumor reduction surgery after preoperative chemotherapy for suspected Stage IIIC primary peritoneal carcinoma. Postoperative histopathology revealed carcinoma consisting mainly of high‐grade serous carcinoma (HGSC) and sarcoma. In addition, serous intraepithelial carcinoma (STIC) of the fallopian tube was observed in the fimbriae of the left fallopian tube. Recently, it has been noted in the literature that most cases of peritoneal carcinoma are metastases or dissemination of carcinoma originating from the fimbriae of the fallopian tube. This is a rare case of peritoneal carcinosarcoma with STIC, and its report leads to a better understanding of the disease's features and possible therapeutic approaches. [ABSTRACT FROM AUTHOR]

Introduction: Cardiac amyloidosis is a rarely reported and potentially fatal variant of the systemic disease. Its early diagnosis could potentially lead to significantly improved clinical outcomes. Case presentation: A 56-year-old female presented with dyspnea and palpitations. Her physical exam and non-invasive evaluation with cardiac magnetic resonance imaging (CMRI) revealed restrictive cardiomyopathy, and the bone marrow biopsy results showed systemic amyloidosis. Discussion: The diagnosis of cardiac amyloidosis is not always straightforward, and delay can cause the progression of the disease and an increased risk of morbidity and mortality. Electrocardiograms, echocardiograms, cardiac magnetic resonance imaging, and histopathologic evaluation are the main methods for diagnosing cardiac amyloidosis. The treatment consists of controlling heart failure symptoms and disease-modifying interventions, including medical and surgical therapeutic methods. Clinical learning point (conclusion): Cardiac involvement is the main cause of death in systemic amyloidosis. Early suspicion, diagnosis, and treatment are crucial in improving patients' survival. CMRI can play an essential role in the diagnosis of cardiac Amyloidosis. A graphical abstract is provided for visual summary. [ABSTRACT FROM AUTHOR]

Background: Obesity is a predisposing risk factor for type 2 diabetes mellitus (T2DM). Actually, not only obese/overweight but also nonobese/lean individuals may be prone to T2DM. This study is aimed at identifying the contribution of adipose tissue to the development of nonobese diabetes (NOD) and obese diabetes (OD). Methods: Serum samples from the nonobese nondiabetes (NOND, n = 47, age = 46.8 ± 8.4, BMI ≤ 23.9 kg/m2) controls, NOD (n = 48, age = 50.7 ± 6.5, BMI ≤ 23.9 kg/m2) and OD (n = 65, age = 49.8 ± 10.2, BMI ≥ 28 kg/m2) patients were utilized to measure the expression of metabolic indicators, adipocytokines, inflammatory factors. Different adipose depots from offspring with corresponding blood glucose and obesity levels of a spontaneously diabetic gerbil line with various degrees of diabetic penetrance and body weights were examined for adipocytokines and inflammation factors detected by ELISA and western blot. Adipose tissue volume and fat cell size of the gerbils were evaluated by magnetic resonance imaging and immunohistochemistry, respectively. Results: The study yielded four key findings. Firstly, in comparison to the NOD group, the OD group exhibited more severe insulin resistance (IR) and metabolic dysfunction in both patients and gerbils, attributed to higher visceral adipose tissue mass and larger fat cell sizes. Secondly, in gerbils, gonadal fat deposition was linked to obesity development, whereas kidney fat deposition correlated with obesity and diabetes occurrence. Thirdly, in both patients and gerbils, the interplay between adiponectin and leptin levels in serum may significantly influence the development of obesity and diabetes. Lastly, heightened expression of MCP3 in gerbils' kidney adipose tissue may serve as a pivotal factor in initiating obesity‐associated diabetes. Conclusions: Our study, which may be considered a pilot investigation, suggests that the interaction of adipocytokines and inflammation factors in different adipose depots could play diverse roles in the development of diabetes or obesity. [ABSTRACT FROM AUTHOR]

Due to the development of magnetic resonance (MR) imaging processing technology, image-based identification of endolymphatic hydrops (EH) has played an important role in understanding inner ear illnesses, such as Meniere's disease or fluctuating sensorineural hearing loss. We segmented the inner ear, consisting of the cochlea, vestibule, and semicircular canals, using a 3D-based deep neural network model for accurate and automated EH volume ratio calculations. We built a dataset of MR cisternography (MRC) and HYDROPS-Mi2 stacks labeled with the segmentation of the perilymph fluid space and endolymph fluid space of the inner ear to devise a 3D segmentation deep neural network model. End-to-end learning was used to segment the perilymph fluid and the endolymph fluid spaces simultaneously using aligned pair data of the MRC and HYDROPS-Mi2 stacks. Consequently, the segmentation performance of the total fluid space and endolymph fluid space had Dice similarity coefficients of 0.9574 and 0.9186, respectively. In addition, the EH volume ratio calculated by experienced otologists and the EH volume ratio value predicted by the proposed deep learning model showed high agreement according to the interclass correlation coefficient (ICC) and Bland–Altman plot analysis. [ABSTRACT FROM AUTHOR]

Rehabilitation is the only current intervention that improves sensorimotor function in ischemic stroke patients, similar to task-specific intensive training in animal models of stroke. Bone marrow mesenchymal stem cells (BM-MSCs)-derived extracellular vesicles (EVs) are promising in restoring brain damage and function in stroke models. Additionally, the non-invasive intranasal route allows EVs to reach the brain and target specific ischemic regions. Yet unclear is how handling might enhance recovery or influence other therapies such as EVs after stroke. We used the transient middle cerebral artery occlusion (MCAO) model of stroke in rats to assess how intensive handling alone, in the form of sensorimotor behavioral tests, or in combination with an intranasal treatment of EVs restored neurological function and ischemic damage. Handled rats were exposed to a battery of sensorimotor tests, including the modified Neurological Severity Score (mNSS), beam balance, corner, grid walking, forelimb placement, and cylinder tests, together with Magnetic Resonance Imaging (MRI) at 2, 7, 14, 21, and 28 days post-stroke (dps). Handled MCAO rats were also exposed to an intranasal multidose or single dose of EVs. Non-handled rats were evaluated only by mNSS and MRI at 2, 28, and 56 dps and were treated with a single intranasal dose of EVs. Our results showed that handling animals after MCAO is necessary for EVs to work at the tested dose and frequency, and that a single cumulative dose of EVs further improves the neurological function recovered during handling. These results show the importance of rehabilitation in combination with other treatments such as EVs, and highlight how extensive behavioral testing might influence functional recovery after stroke. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion Magnetic resonance images (MRIs) are a valuable tool in the study of brain tumors, and multimodal sequences provide unique insights into different aspects of brain tumors. However, in clinical practice, missing modalities are often encountered due to various factors. This makes it difficult to obtain comprehensive and reliable information related to brain tumors.The purpose of this work is to develop an algorithm for the synthesis of missing MRI modality with high precision, and to center on generating accurate tumor‐related information to offer more data for clinical diagnosis.A novel weakly supervised MRI synthesis model named TAM‐DAM‐GAN has been proposed, which integrates tumor‐aware and detail adjustment mechanisms to enhance the quality of tumor generation. The tumor‐aware mechanism leverages weak label information to guide the network to classify images based on crucial information in local structures, thereby compelling the generative network to identify and highlight the learning of local tumor regions. The detail adjustment mechanism utilizes a discriminator to create attention maps at the pixel level in real‐time. These maps are then used to modify the loss weight, which in turn adjusts the details that are generated.Generation quality of four tasks (T1‐to‐T2, T2‐to‐T1, T1‐to‐FLAIR, and FLAIR‐to‐T1) was evaluated. Experiments on the BRATS2015 dataset show that the proposed approach is superior in both qualitative and quantitative measures. Taking FLAIR‐to‐T1 as an example, TAM‐DAM‐GAN improves PSNR of tumor region from 18.556 to 20.576 compared to baseline. Also, using real FLAIR data with generated T1 data boosts tumor segmentation accuracy by 10% compared to using only real FLAIR data.This finding will be conducive to enhancing the accuracy of cross‐modality synthesis in incomplete multimodal MRI, especially for tumor regions, thereby providing more dependable and comprehensive data for clinical diagnosis and scientific research. [ABSTRACT FROM AUTHOR]

Background Cases Conclusions The Powassan virus is a rare neurotropic, tick‐borne arbovirus associated with meningoencephalitis. Despite the virus's known predilection for the basal ganglia, there are no reports detailing the spectrum of movement disorders in children with Powassan meningoencephalitis.We present 3 cases of pediatric Powassan encephalitis, highlighting the diverse and evolving movement disorders associated with this disease. We observed subcortical myoclonus and progressive generalized dystonia (patient 1), transient dyskinesias and refractory focal dystonia (patient 2), and generalized dystonia evolving into chorea and lingual dyskinesias (patient 3). One patient exhibited multifocal vasculitis on magnetic resonance imaging angiography, a novel finding.Movement disorders were a primary source of the morbidity experienced by pediatric Powassan encephalitis patients throughout their disease course, underscoring the importance of regular monitoring and adaptable treatment strategies in this condition. Larger, prospective studies are necessary to fully delineate the spectrum of associated movement disorders in this rare and severe disease. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation To describe patient clinical characteristics associated with matched oligoclonal bands (OCB).A retrospective review at the University of Utah examined patients with matched OCB from 2015 to 2020. Clinical data, diagnosis, and outcomes were collected. Patients were classified with either multiple sclerosis (MS), other inflammatory neurologic disorder (other‐IND), or noninflammatory neurologic disorder (NIND).Of 539 identified patients, 436 (53.4% female) were matched‐only, while 103 (43.7% female) were matched + unique. Patients with matched‐only bands were older (57.4 ± 16 vs. 52 ± 14.2, p < 0.001) and more likely to have a history of autoimmune disease (40.1% vs. 28.2%, p = 0.024) and/or cancer (28.7% vs. 16.5%, p = 0.012). Patients with matched + unique bands were more likely to have CSF pleocytosis (52.4% vs. 25.9%, p < 0.001), high IgG index (52.2% vs. 7.6%, p < 0.001), and an abnormal MRI (86.9% vs. 63.1%, p < 0.001). More than two‐thirds of matched‐only patients had NIND, while 33% and 41.7% of matched + unique patients had MS and other‐IND, respectively. Patients exhibiting matched‐only bands and a high IgG index demonstrated a significantly higher incidence of other‐IND compared to those with matched‐only bands and a normal IgG index (55.6% vs. 30.4%, p = 0.013). While Kaplan–Meier survival curves demonstrated higher mortality in the matched‐only cohort compared to the matched + unique cohort (p = 0.02), multivariable Cox regression analysis showed this difference was not statistically significant when adjusting for various factors. A history of cancer was the significant predictor of increased mortality risk (Hazard ratio = 3.147, 95% CI [2.196, 4.51]).Patients with matched only versus matched + unique OCB have distinct clinical profiles. [ABSTRACT FROM AUTHOR]

Objective Methods Results Conclusion To determine the diagnostic test accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting seminal vesicle invasion (SVI).The Medical Literature Analysis and Retrieval System Online (MEDLINE), PubMed, the Excerpta Medica dataBASE (EMBASE) and Cochrane databases were search up to May 2023. We included studies that investigated the accuracy of mpMRI in detecting SVI when compared to radical prostatectomy specimens as the reference standard. Data extraction was performed by two independent reviewers to construct 2 × 2 tables, as well as patient and study characteristics. The methodological quality of the included studies was assessed with the Quality of Assessment of Diagnostic Accuracy Studies‐2 tool. Sensitivity and specificity were pooled and presented graphically with summary receiver operator characteristic (SROC) plots.A total of 27 articles with 4862 patients were included for analysis. The summary sensitivity and specificity were 0.57 (95% confidence interval [CI] 0.45–0.68) and 0.95 (95% CI 0.92–0.99), respectively. Meta‐regression indicated that there was no evidence that coil strength (P = 0.079), coil type (P = 0.589), year of publication (P = 0.503) or use of the Prostate Imaging‐Reporting and Data System (P = 0.873) significantly influenced these results. The summary diagnostic odds ratio was 28.3 (95% CI 15.0–48.8) and the area under the curve for the SROC curve was 0.87. The I2 statistic was a modest 11.9%. In general, methodological quality was good.The use of mpMRI in detecting SVI has excellent specificity but poor sensitivity. Both endorectal coils and magnetic field strength do not significantly impact the accuracy of MRI. These findings suggest that mpMRI cannot reliably rule out SVI in patients with prostate cancer. [ABSTRACT FROM AUTHOR]

ABSTRACT Premature ventricular contraction (PVC) is one of the most common arrhythmias, originating from ectopic beats in the ventricles. Precision in localizing the origin of PVCs has long been a focal point in electrophysiology research. Machine learning (ML) has developed rapidly in the past two decades with increasingly widespread applications. With the increase of clinical data such as electrocardiograms (ECGs), computed tomography (CT), and magnetic resonance imaging (MRI), ML and its subfields, deep learning (DL), have become powerful analytical tools, playing an increasingly important role in electrophysiological research. In this review, we mainly provide an overview of the development of ML in the localization of PVC origins, including its applications, advantages, disadvantages, and future research directions. This information is intended to serve as a reference for clinicians and researchers, aiding them in better‐utilizing ML techniques for the diagnosis and study of PVC origins. [ABSTRACT FROM AUTHOR]

Aim Method Results Interpretation To investigate the impact of cerebellar haemorrhage (CBH) and atrophy in infants born extremely preterm with intraventricular haemorrhage (IVH) on neurodevelopment at 2 years of age.This retrospective case–control study included infants born at less than 28 weeks' gestation with IVH over a 10‐year period. CBH, along with the assessment of cerebellar size, using magnetic resonance imaging, were studied. The impact of injuries on neurodevelopmental outcome at 2 years' corrected age was conducted, using multivariable regression analysis for comprehensive evaluation.In a cohort of 103 patients, 69 (67.0%) showed CBH with a median grade of 1 (interquartile range = 0–3). At the corrected age of 2 years, CBH was significantly associated with impaired cognitive and motor outcome. CBH emerged as an independent predictor of poor cognitive and motor development, as well as cerebral palsy. Cerebellar atrophy, affecting 30 (29.1%) infants, was linked to a significantly worse outcome across all domains. Conversely, an increase in cerebellar size was correlated with improved motor development.Infants born extremely preterm with IVH and concomitant CBH exhibited significant cognitive and motor impairment. The severity of developmental delay correlated with the grade of CBH. These findings hold potential to support the prediction of long‐term outcome and parental counselling. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion Large foundation models, such as the Segment Anything Model (SAM), have shown remarkable performance in image segmentation tasks. However, the optimal approach to achieve true utility of these models for domain‐specific applications, such as medical image segmentation, remains an open question. Recent studies have released a medical version of the foundation model MedSAM by training on vast medical data, who promised SOTA medical segmentation. Independent community inspection and dissection is needed.Foundation models are developed for general purposes. On the other hand, stable delivery of reliable performance is key to clinical utility. This study aims at elucidating the potential advantage and limitations of landing the foundation models in clinical use by assessing the performance of off‐the‐shelf medical foundation model MedSAM for the segmentation of anatomical structures in pelvic MR images. We also explore the simple remedies by evaluating the dependency on prompting scheme. Finally, we demonstrate the need and performance gain of further specialized fine‐tuning.MedSAM and its lightweight version LiteMedSAM were evaluated out‐of‐the‐box on a public MR dataset consisting of 589 pelvic images split 80:20 for training and testing. An nnU‐Net model was trained from scratch to serve as a benchmark and to provide bounding box prompts for MedSAM. MedSAM was evaluated using different quality bounding boxes, those derived from ground truth labels, those derived from nnU‐Net, and those derived from the former two but with 5‐pixel isometric expansion. Lastly, LiteMedSAM was refined on the training set and reevaluated on this task.Out‐of‐the‐box MedSAM and LiteMedSAM both performed poorly across the structure set, especially for disjoint or non‐convex structures. Varying prompt with different bounding box inputs had minimal effect. For example, the mean Dice score and mean Hausdorff distances (in mm) for obturator internus using MedSAM and LiteMedSAM were {0.251 ± 0.110, 0.101 ± 0.079} and {34.142 ± 5.196, 33.688 ± 5.306}, respectively. Fine‐tuning of LiteMedSAM led to significant performance gain, improving Dice score and Hausdorff distance for the obturator internus to 0.864 ± 0.123 and 5.022 ± 10.684, on par with nnU‐Net with no significant difference in evaluation of most structures. All segmentation structures benefited significantly from specialized refinement, at varying improvement margin.While our study alludes to the potential of deep learning models like MedSAM and LiteMedSAM for medical segmentation, it highlights the need for specialized refinement and adjudication. Off‐the‐shelf use of such large foundation models is highly likely to be suboptimal, and specialized fine‐tuning is often necessary to achieve clinical desired accuracy and stability. [ABSTRACT FROM AUTHOR]

The upper cervical spine has a complex anatomical structure, making anterior surgical approaches challenging and prone to complications. This study aims to explore the use of bilateral submandibular incisions to provide safer and more convenient exposure of the upper cervical spine and to assess the feasibility of this approach for anterior surgical treatment of complex upper cervical diseases. From November 2019 to August 2021, three patients with malignant tumors of the upper cervical spine were subjected to an anterior–posterior combined approach for cervical tumor resection. The cohort consisted of one male and two females, aged between 41 and 51 years. The anterior approach began with a submandibular incision, followed by blunt dissection through the prevertebral muscles to expose the diseased vertebra. Subsequently, the diseased vertebra was excised, and either a titanium cage or a pre‐customized 3D‐printed artificial vertebral body was implanted anteriorly. Then, posterior fixation of the cervical spine was performed using pedicle screws to provide additional stability. Follow‐up ranged from 8 to 34 months. All patients experienced varying degrees of pain relief within 24 hours post‐operation. Frankel grading showed improvement by at least one grade in all three cases. Regular X‐ray and magnetic resonance imaging examinations revealed no tumor recurrence or involvement of adjacent vertebrae in the surgical area. The anterior bilateral submandibular horizontal incision approach offers comprehensive exposure of the anatomical structures of the upper cervical spine. This approach introduces a new option for the anterior treatment of upper cervical spine diseases. [ABSTRACT FROM AUTHOR]

Real‐time visualization of metabolic processes in vivo provides crucial insights into conditions like cancer and metabolic disorders. Metabolic magnetic resonance imaging (MRI), by amplifying the signal of pyruvate molecules through hyperpolarization, enables non‐invasive monitoring of metabolic fluxes, aiding in understanding disease progression and treatment response. Signal Amplification By Reversible Exchange (SABRE) presents a simpler, cost‐effective alternative to dissolution dynamic nuclear polarization, eliminating the need for expensive equipment and complex procedures. We present the first in vivo demonstration of metabolic sensing in a human pancreatic cancer xenograft model compared to healthy mice. A novel perfluorinated Iridium SABRE catalyst in a fluorinated solvent and methanol blend facilitated this breakthrough with a 1.2‐fold increase in [1‐13C]pyruvate SABRE hyperpolarization. The perfluorinated moiety allowed easy separation of the heavy‐metal‐containing catalyst from the hyperpolarized [1‐13C]pyruvate target. The perfluorinated catalyst exhibited recyclability, maintaining SABRE‐SHEATH activity through subsequent hyperpolarization cycles with minimal activity loss after the initial two cycles. Remarkably, the catalyst retained activity for at least 10 cycles, with a 3.3‐fold decrease in hyperpolarization potency. This proof‐of‐concept study encourages wider adoption of SABRE hyperpolarized [1‐13C]pyruvate MR for studying in vivo metabolism, aiding in diagnosing stages and monitoring treatment responses in cancer and other diseases. [ABSTRACT FROM AUTHOR]

Objective. Given the different noise distribution information of global and local magnetic resonance (MR) images, this study aims to extend the current work on convolutional neural networks that preserve global structure and local details in MR image denoising tasks. Approach. This study proposed a parallel and serial network for denoising 3D MR images, called 3D-PSNet. We use the residual depthwise separable convolution block to learn the local information of the feature map, reduce the network parameters, and thus improve the training speed and parameter efficiency. In addition, we consider the feature extraction of the global image and utilize residual dilated convolution to process the feature map to expand the receptive field of the network and avoid the loss of global information. Finally, we combine both of them to form a parallel network. What's more, we integrate reinforced residual convolution blocks with dense connections to form serial network branches, which can remove redundant information and refine features to further obtain accurate noise information. Main results. The peak signal-to-noise ratio, structural similarity index measure, and root mean square error metrics of 3D-PSNet are as high as 47.79%, 99.81%, and 0.40%, respectively, achieving competitive denoising effect on three public datasets. The ablation experiments demonstrated the effectiveness of all the designed modules regarding all the evaluated metrics in both datasets. Significance. The proposed 3D-PSNet takes advantage of multi-scale receptive fields, local feature extraction and residual dense connections to more effectively restore the global structure and local fine features in MR images, and is expected to help doctors quickly and accurately diagnose patients' conditions. [ABSTRACT FROM AUTHOR]

Objective. To develop a 2D MR acceleration method utilizing principal component analysis (PCA) in a hybrid fashion for rapid real-time applications. Approach. Retrospective testing was performed on 10 lung, 10 liver and 10 prostate 3T MRI data sets for image quality and target contourability. Sampling of k-space is performed by acquiring central (low-frequency) data in every frame while the high-frequency data is incoherently undersampled such that all of k-space is acquired in a pre-determined number of frames. Firstly, principal components (PCs) representative of intra-frame correlations between central and outer k-space data are used to estimate unsampled data in the frame of interest. Then to add further stability, PCs representative of time-domain fluctuations within a reconstruction window of the most recent frames are fit to outer k-space data (including above estimations) to obtain final estimates in the frame of interest. Accelerated reconstructions between 3x and 8x were tested for image quality and contourability along with the optimal number of PCs for fitting. Main results. It was found that at higher acceleration rates, image quality did not deteriorate significantly. Similarly, it was found that the images were of sufficient quality to contour a target using auto-contouring software at all tested acceleration rates and sites. SSIM values were found to be ⩾0.91 at all accelerations tested. Similarly dice coefficients at the different sites were found to be ⩾0.89 even at 8x accelerations which is on par with or better than intra-observer variation. Significance. This method appears to produce improved image quality and contourability compared to previous PCA methods while also allowing a greater number of PCs to be used in reconstruction. The method can be run using a simple single-channel coil and does not require significant computing power to meet real-time interventional standards (reconstruction times ∼60 ms/frame on Intel i5 CPU). [ABSTRACT FROM AUTHOR]

Deep learning-based segmentation models often struggle to achieve optimal performance when encountering new, unseen semantic classes. Their effectiveness hinges on vast amounts of annotated data and high computational resources for training. However, a promising solution to mitigate these challenges is the adoption of few-shot segmentation (FSS) networks, which can train models with reduced annotated data. The inherent complexity of medical images limits the applicability of FSS in medical imaging, despite its potential. Recent advancements in self-supervised label-efficient FSS models have demonstrated remarkable efficacy in medical image segmentation tasks. This paper presents a novel FSS architecture that enhances segmentation accuracy by utilising fewer features than existing methodologies. Additionally, this paper proposes a novel self-supervised learning approach that utilises supervoxel and augmented superpixel images to further enhance segmentation accuracy. This paper assesses the efficacy of the proposed model on two different datasets: abdominal magnetic resonance imaging (MRI) and cardiac MRI. The proposed model achieves a mean dice score and mean intersection over union of 81.62% and 70.38% for abdominal images, and 79.38% and 65.23% for cardiac images. [ABSTRACT FROM AUTHOR]