Magnetic Resonance Imaging Variables Research Articles

MRI variables and peripheral inflammatory response biomarkers predict severity and prognosis in patients with acute cervical traumatic spinal cord injury.

Traumatic spinal cord injury (TSCI) stands as one of the most profoundly damaging and debilitating conditions. This study aims to explore the potential of magnetic resonance imaging (MRI) variables and peripheral inflammatory indicators as promising biomarkers. It aims to understand their significance in evaluating the severity and predicting the prognosis of TSCI. Furthermore, the study aims to ascertain whether combining these indicators could enhance the accuracy of injury assessment and predictive prognostic ability. A multicentre retrospective cohort study was conducted to assess the severity and prognostic value of MRI variables and peripheral inflammatory response biomarkers in patients with acute cervical TSCI. The study involved 374 patients with acute cervical TSCI drawn from the First Affiliated Hospital of Nanchang University and the Second Affiliated Hospital of Nanchang University. The severity and prognosis of patients with acute cervical TSCI were assessed using the American Spinal Injury Association Impairment Scale (AIS). The correlation between MRI variables, peripheral inflammatory response biomarkers, admission severity, and the 1-year follow-up prognosis was analysed. After the initial assessment using the AIS grade system, 169 (49.2%) patients fell into the severe category for cervical TSCI (AIS A-B), while 205 (50.8%) patients were classified as non-severe cases (AIS C-E). The MRI variables (intramedullary lesion length [IMLL], Brain and Spinal Injury Centre [BASIC], maximum spinal cord compression [MSCC], and maximum canal compromise [MCC]) and inflammatory response biomarkers (white blood cells [WBCs], neutrophils, and C-reactive protein [CRP]) exhibited a consistent decrease correlating with the severity grades noted upon admission. Among the 374 patients assessed, 147 (39.3%) experienced a poor prognosis, as indicated by the AIS grade during the 1-year follow-up. MRI variables and peripheral inflammatory response biomarkers declined in correspondence with the follow-up AIS grades. Sex (p < 0.001), IMLL (p < 0.001), MSCC (p < 0.001), MCC (p < 0.001), BASIC (p < 0.001), WBC (p < 0.001), neutrophils (p < 0.001), and CRP (p < 0.001) were statistically significant in predicting poor outcomes. Through multivariate logistic regression analysis, BASIC score and CRP emerged as independent predictors of poor prognosis. Notably, the model combining the BASIC score and CRP yielded a larger area under the curve compared to models using only the BASIC score or CRP individually. The BASIC score and CRP are crucial biomarkers for evaluating the severity of cervical TSCI and predicting prognosis. Their combination proved to be a more robust determinant of injury severity and a better predictor of neurological recovery.

Mediation analysis of brain magnetic resonance imaging variables with all-cause and cardiovascular disease-specific mortalities in persons with type 2 diabetes.

Glucose variation (GV) has emerged as a predictor of morbidity and mortality in persons with diabetes. However, no study has examined whether brain magnetic resonance imaging (MRI) variables mediated the association between mortality and GV. This study was a retrospective cohort comprising 3,961 individuals with type 2 diabetes (T2D), whose electronic medical records were retrieved from a medical center between January 2001 and October 2021. GV was quantified using coefficient of variation of fasting plasma glucose (FPG-CV) and glycated hemoglobin (HbA1c). The MRI variables included the presence or absence of cerebrovascular abnormality and white matter hyperintensity (WMH). All deaths and deaths resulting from expanded cardiovascular disease (CVD) were identified through annual record linkage with National Death Datasets. Cox proportional hazards models were applied to evaluate associations of MRI variable or GV with mortality. Mediation analyses were performed to assess the relative contributions of MRI variables for GV on mortality. Among 3,961 patients, 2,114 patients (53.4%) had cerebrovascular abnormality and 1,888 patients (47.7%) had WMH. The results showed cerebrovascular abnormality and WMHs were significantly associated with all-cause and expanded CVD mortality after considering GV. The largest mediated effects of GV on all-cause and expanded CVD mortality were observed by cerebrovascular abnormality (5.26% and 8.49%, respectively). Our study suggests cerebrovascular abnormality and WMHs are important predictors of mortality in patients with T2D after considering GV. In addition, MRI variables of cerebrovascular abnormality expressed weak but significant mediation effect on the associations between GV and mortality.

A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables.

Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET composites from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded the most accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study uncovers current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.

The value of cesarean scar diverticulum in diagnosis of adverse events during dilatation and curettage in patient with cesarean scar pregnancy.

The aim of the present study was to explore the relationship between the size of cesarean scar diverticulum (CSD) measured on preoperative magnetic resonance imaging (MRI) and adverse events during dilatation and curettage (D&C) procedure in patients with cesarean scar pregnancy (CSP). The MRI of 197 CSP patients from October 2019 to August 2023 were retrospectively reviewed. The volume, area, and depth of CSD, residual myometrium thickness (RMT), and gestational sac diameter were recorded and tested for correlation with intraoperative estimated blood loss (EBL), and operation time and for any association with the intraoperative adverse events (intraoperative massive hemorrhage [39 cases] and D&C procedure failure [15 cases]). The Spearman test was used to characterize the correlation between the five MRI variables and both the EBL and operation time. The correlation between the five MRI variables and intraoperative adverse events was evaluated with student's t test and Mann-Whitney U test. Diagnostic power of the MRI variables was evaluated by the area under receiver operating characteristic curve (AUC). The volume, area, and depth of CSD and gestational sac diameter were positively correlated with both EBL and operation time, with the CSD volume having the highest correlation with them (r = 0.543 and 0.461, respectively). Conversely, the RMT displayed a negative correlation with the EBL and operation time. All five MRI variables were significantly associated with both intraoperative massive hemorrhage and D&C failure (all P < 0.001). The CSD volume demonstrated the highest AUC for diagnosing intraoperative massive hemorrhage and D&C failure at 0.893 (95% CI: 0.82-0.92) and 0.901 (95% CI: 0.85-0.94), respectively. The optimal cutoff values for CSD volume in predicting massive hemorrhage and D&C failure were determined to be 5.41 and 8.92 cm3, respectively, with corresponding sensitivities/specificities of 92.31/74.68 and 93.33/82.42, respectively. Quantifying the size of CSD based on preoperative MRI could aid in evaluating risk during D&C in CSP patients, with CSD volume possessing higher diagnostic efficacy than the other four MRI indicators.

Multitrait Analysis to Decipher the Intertwined Genetic Architecture of Neuroanatomical Phenotypes and Psychiatric Disorders

BackgroundThere is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven to be challenging, and new approaches are needed to infer the genetic structures that may underlie those phenotypes. Multivariate analyses are a meaningful approach to reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches. MethodsFirst, we conducted univariate and multivariate genome-wide association studies for 9 MRI-derived brain volume phenotypes in 20,000 UK Biobank participants. Next, we performed various complementary enrichment analyses to assess whether and how univariate and multitrait approaches could distinguish disorder-associated and non–disorder-associated variants from 6 psychiatric disorders: bipolar disorder, attention-deficit/hyperactivity disorder, autism, schizophrenia (SCZ), obsessive-compulsive disorder, and major depressive disorder. Finally, we conducted a clustering analysis of top associated variants based on their MRI multitrait association using an optimized k-medoids approach. ResultsA univariate MRI genome-wide association study revealed only negligible genetic correlations with psychiatric disorders, while a multitrait genome-wide association study identified multiple new associations and showed significant enrichment for variants related to both attention-deficit/hyperactivity disorder and SCZ. Clustering analyses also detected 2 clusters that showed not only enrichment for association with attention-deficit/hyperactivity disorder and SCZ but also a consistent direction of effects. Functional annotation analyses of those clusters pointed to multiple potential mechanisms, suggesting a role of neurotrophin pathways in particular in both MRI and SCZ. ConclusionsOur results show that multitrait association signature can be used to infer genetically driven latent MRI variables associated with psychiatric disorders, thereby opening paths for future biomarker development.

MRI and Clinical Variables for Prediction of Outcomes After Pediatric Severe Traumatic Brain Injury

Traumatic brain injury (TBI) is a leading cause of death and disability in children, and predicting functional outcome after TBI is challenging. Magnetic resonance imaging (MRI) is frequently conducted after severe TBI; however, the predictive value of MRI remains uncertain. To identify early MRI measures that predict long-term outcome after severe TBI in children and to assess the added predictive value of MRI measures over well-validated clinical predictors. This preplanned prognostic study used data from the Approaches and Decisions in Acute Pediatric TBI (ADAPT) prospective observational comparative effectiveness study. The ADAPT study enrolled 1000 consecutive children (aged <18 years) with severe TBI between February 1, 2014, and September 30, 2017. Participants had a Glasgow Coma Scale (GCS) score of 8 or less and received intracranial pressure monitoring. Magnetic resonance imaging scans performed as part of standard clinical care within 30 days of injury were collected at 24 participating sites in the US, UK, and Australia. Summary imaging measures were correlated with the Glasgow Outcome Scale-Extended for Pediatrics (GOSE-Peds), and the predictive value of MRI measures was compared with the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) core clinical predictors. Data collection, image analysis, and data analyses were completed in July 2023. Pediatric severe TBI with an MRI scan performed as part of clinical care. All measures were selected a priori. Magnetic resonance imaging measures included contusion, ischemia, diffuse axonal injury, intracerebral hemorrhage, and brainstem injury. Clinical predictors included the IMPACT core measures (GCS motor score and pupil reactivity). All models adjusted for age and sex. Outcome measures included the GOSE-Peds score obtained at 3, 6, and 12 months after injury. This study included 233 children with severe TBI who were enrolled at participating sites and had an MRI scan and preselected clinical predictors available. Their median age was 6.9 (IQR, 3.0-13.3) years, and more than half of participants (134 [57.5%]) were male. In a multivariable model including MRI measures and IMPACT core clinical variables, contusion volume (odds ratio [OR], 1.13; 95% CI, 1.02-1.26), brain ischemia (OR, 2.11; 95% CI, 1.58-2.81), brainstem lesions (OR, 5.40; 95% CI, 1.90-15.35), and pupil reactivity were each independently associated with GOSE-Peds score. Adding MRI measures to the IMPACT clinical predictors significantly improved model fit and discrimination between favorable and unfavorable outcomes compared with IMPACT predictors alone (area under the receiver operating characteristic curve, 0.77; 95% CI, 0.72-0.85 vs 0.67; 95% CI, 0.61-0.76 for GOSE-Peds score >3 at 6 months after injury). In this prognostic study of children with severe TBI, the addition of MRI measures significantly improved outcome prediction over well-established and validated clinical predictors. Magnetic resonance imaging should be considered in children with severe TBI to inform prognosis and may also promote stratification of patients in future clinical trials.

Prognostic Value of Magnetic Resonance Imaging Variables Combined with Neutrophil-to-Lymphocyte Ratio in Patients with Cervical Traumatic Spinal Cord Injury

We aimed to explore the prognostic significance of preoperative magnetic resonance imaging (MRI) variables and novel inflammatory indicators in predicting neurological recovery post-cervical traumatic spinal cord injury (TSCI) in the study. We enrolled a total of 244 patients diagnosed with acute cervical TSCI from two hospitals and evaluated the prognostic value of MRI variables (intramedullary hemorrhage, intramedullary lesion length (IMLL), maximum spinal cord compression (MSCC), and maximum canal compromise (MCC)) and novel inflammatory indicators (neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammatory index (SII)) in patients with acute cervical TSCI. Among the 244 patients, 140 (57.38%) exhibited improved AIS grade conversion at 1-year follow-up. The results revealed intramedullary hemorrhage, IMLL, MCC, neutrophils, and NLR were significantly different compared with follow-up AIS grade. Furthermore, IMLL, MCC, WBCs, neutrophils, NLR, and LMR correlated with the follow-up AIS grade by Spearman’s correlation analysis. Multivariate analysis showed IMLL, intramedullary hemorrhage, NLR and admission AIS grade emerged as independent predictors of AIS grade conversion. The receiver operating characteristic curve (ROC) analysis showed that the novel model (combination of MRI variables, NLR and admission AIS grade) produced a larger area under the curve compared with using only intramedullary hemorrhage, IMLL, NLR or admission AIS grade individually. In conclusion, intramedullary hemorrhage and IMLL and NLR are predictors of AIS grade conversion after cervical TSCI. Therefore, we suggest the combination of MRI variables and NLR for the prognostic prediction of AIS grade conversion in patients with cervical TSCI.

Distal Tibiofibular Syndesmosis Injuries in the National Football League (NFL): A Spectrum of Pathology That Correlates With Time to Return to Full Participation.

Studies routinely evaluate high ankle sprains in isolation, but recent data suggest that these injuries are often associated with concomitant pathology, potentially influencing return to full participation. In National Football League (NFL) players, isolated high ankle sprains are rare and syndesmosis injuries with concomitant pathology will result in increased time to return to full participation. Cross-sectional study. Level 3. Distal tibiofibular syndesmosis injuries sustained by NFL players between 2017 and 2019 were identified through NFL Injury Surveillance Database queries and verified with video analysis. Each injury underwent a comprehensive magnetic resonance imaging (MRI) review. Regression modeling was utilized to explore the influence of numerous imaging findings on time to return to full participation. There were 83 external rotation ankle injuries involving the syndesmosis. Isolated distal tibiofibular syndesmosis injuries were rare (n = 11; 13%) and more often associated with other ligamentous injury (deltoid ligament and lateral ligamentous complex) and/or fractures. Regression modeling resulted in clustering of 3 injury pattern groups for time to return to full participation across numerous imaging findings: syndesmosis injury-fracture combinations (250 days [interquartile range [IQR,] 142-266 days]), syndesmosis injury with complete deep deltoid tear or acute diastasis (175 days [IQR, 20-248 days]), and all other syndesmosis injuries (27 days [IQR, 18-46 days]). In NFL athletes with external rotation ankle injuries, isolated distal tibiofibular syndesmosis injuries were rare and more often associated with concomitant pathology. Time to return to full participation was affected by an associated fracture and complete deep deltoid ligament tear or diastasis but no other relevant MRI variables such as lateral ligament complex involvement or the presence of osteochondral lesions or bone contusions.

A predictive model using MRI and clinicopathologic features for breast cancer recurrence in young women treated with upfront surgery.

To identify preoperative breast MR imaging and clinicopathological variables related to recurrence and develop a risk prediction model for recurrence in young women with breast cancer treated with upfront surgery. This retrospective study analyzed 438 consecutive women with breast cancer aged 35 years or younger between January 2007 and December 2016. Breast MR images before surgery were independently reviewed by breast radiologists blinded to patient outcomes. The clinicopathological data including patient demographics, clinical features, and tumor characteristics were reviewed. Univariate and multivariate logistic regression analyses were used to identify the independent factors associated with recurrence. The risk prediction model for recurrence was developed, and the discrimination and calibration abilities were assessed. Of 438 patients, 95 (21.7%) developed recurrence after a median follow-up of 65 months. Tumor size at MR imaging (HR = 1.158, p = 0.006), multifocal or multicentric disease (HR = 1.676, p = 0.017), and peritumoral edema on T2WI (HR = 2.166, p = 0.001) were identified as independent predictors of recurrence, while adjuvant endocrine therapy (HR = 0.624, p = 0.035) was inversely associated with recurrence. The prediction model showed good discrimination ability in predicting 5-year recurrence (C index, 0.707 in the development cohort; 0.686 in the validation cohort) and overall recurrence (C index, 0.699 in the development cohort; 0.678 in the validation cohort). The calibration plot demonstrated an excellent correlation (concordance correlation coefficient, 0.903). A prediction model based on breast MR imaging and clinicopathological features showed good discrimination to predict recurrence in young women with breast cancer treated with upfront surgery, which could contribute to individualized risk stratification. Our prediction model, incorporating preoperative breast MR imaging and clinicopathological features, predicts recurrence in young women with breast cancer undergoing upfront surgery, facilitating personalized risk stratification and informing tailored management strategies. Younger women with breast cancer have worse outcomes than those diagnosed at more typical ages. The described prediction model showed good discrimination performance in predicting 5-year and overall recurrence. Incorporating better risk stratification tools in this population may help improve outcomes.

Correlation between rCBV Delineation Similarity and Overall Survival in a Prospective Cohort of High-Grade Gliomas Patients: The Hidden Value of Multimodal MRI?

The accuracy of target delineation in radiation treatment planning of high-grade gliomas (HGGs) is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Magnetic resonance imaging (MRI) represents the standard imaging modality for delineation of gliomas with inherent limitations in accurately determining the microscopic extent of tumors. The purpose of this study was to assess the survival impact of multi-observer delineation variability of multiparametric MRI (mpMRI) and [18F]-FET PET/CT. Thirty prospectively included patients with histologically confirmed HGGs underwent a PET/CT and mpMRI including diffusion-weighted imaging (DWI: b0, b1000, ADC), contrast-enhanced T1-weighted imaging (T1-Gado), T2-weighted fluid-attenuated inversion recovery (T2Flair), and perfusion-weighted imaging with computation of relative cerebral blood volume (rCBV) and K2 maps. Nine radiation oncologists delineated the PET/CT and MRI sequences. Spatial similarity (Dice similarity coefficient: DSC) was calculated between the readers for each sequence. Impact of the DSC on progression-free survival (PFS) and overall survival (OS) was assessed using Kaplan-Meier curves and the log-rank test. The highest DSC mean values were reached for morphological sequences, ranging from 0.71 +/- 0.18 to 0.84 +/- 0.09 for T2Flair and T1Gado, respectively, while metabolic volumes defined by PET/CT achieved a mean DSC of 0.75 +/- 0.11. rCBV variability (mean DSC0.32 +/- 0.20) significantly impacted PFS (p = 0.02) and OS (p = 0.002). Our data suggest that the T1-Gado and T2Flair sequences were the most reproducible sequences, followed by PET/CT. Reproducibility for functional sequences was low, but rCBV inter-reader similarity significantly impacted PFS and OS.

Siamese network to assess scanner-related contrast variability in MRI

Magnetic Resonance Imaging (MRI) stands as a noninvasive tool for diagnosing and monitoring various diseases. The flexibility of MRI configuration parameters allows for adaptable imaging sequences, and at the same time poses challenges in terms of reproducibility, as variability in imaging sequences leads to significant differences in image contrast. This is one of the major causes that compromise the reliability of deep learning methods. Since the majority of the literature is focused on documenting the effects of this issue rather than delving into its underlying causes, this work follows a different approach. A Siamese Neural Network (SNN) has been trained to identify the scanner that acquired the input image. Experimental results include the use of Euclidean Distance (ED) and machine learning algorithms trained and tested using the feature vectors generated with the SNN. The results have shown that the proposed method is capable of distinguishing the scanner used for the acquisition with high accuracy. For a comprehensive interpretation of the results, the feature vectors have been dimensionality reduced and visualized with a 3D plot. Finally, the proposed method is sensitive to MR image contrast variability and could be used to detect data-related inconsistencies and provide a mechanism to make users aware of potential issues.

Long-term outcomes prediction in diabetic heart failure with preserved ejection fraction by cardiac MRI.

We aimed to explore imaging features including tissue characterization and myocardial deformation in diabetic heart failure with preserved ejection fraction (HFpEF)patients by magnetic resonance imaging (MRI) and investigate its prognostic value for adverse outcomes. Patients with HFpEF who underwent cardiac MRI between January 2010 and December 2016 were enrolled. Feature-tracking (FT) analysis and myocardial fibrosis were assessed by cardiac MRI. Cox proportional regression analysis was performed to determine the association between MRI variables and primary outcomes. Primary outcomes were all-cause death or heart failure hospitalization during the follow-up period. Of the 335 enrolled patients with HFpEF, 191 had diabetes mellitus (DM) (mean age: 58.7years ± 10.8; 137 men). During a median follow-up of 10.2years, 91 diabetic HFpEF and 56 non-diabetic HFpEF patients experienced primary outcomes. DM was a significant predictor of worse prognosis in HFpEF. In diabetic HFpEF, the addition of conventional imaging variables (left ventricular ejection fraction, left atrial volume index, extent of late gadolinium enhancement (LGE)) and global longitudinal strain (GLS) resulted in a significant increase in the area under the receiver operating characteristic curve (from 0.693 to 0.760, p < 0.05). After adjustment for multiple clinical and imaging variables, each 1% worsening in GLS was associated with a 9.8% increased risk of adverse events (p = 0.004). Diabetic HFpEF is characterized by more severely impaired strains and myocardial fibrosis, which is identified as a high-risk HFpEF phenotype. In diabetic HFpEF, comprehensive cardiac MRI provides incremental value in predicting prognosis. Particularly, MRI-FT measurement of GLS is an independent predictor of adverse outcome in diabetic HFpEF. Our findings suggested that MRI-derived variables, especially global longitudinal strain, played a crucial role in risk stratification and predicting worse prognosis in diabetic heart failure with preserved ejection fraction, which could assist in identifying high-risk patients and guiding therapeutic decision-making. • Limited data are available on the cardiac MRI features of diabetic heart failure with preserved ejection fraction, including myocardial deformation and tissue characterization, as well as their incremental prognostic value. • Diabetic heart failure with preserved ejection fraction patients was characterized by more impaired strains and myocardial fibrosis. Comprehensive MRI, including tissue characterization and global longitudinal strain, provided incremental value for risk prediction. • MRI served as a valuable tool for identifying high-risk patients and guiding clinical management in diabetic heart failure with preserved ejection fraction.

Magnetic resonance imaging prognostic factors for survival and relapse in dogs with meningoencephalitis of unknown origin.

Canine meningoencephalitis of unknown origin (MUO) is a debilitating disease associated with high mortality. The prognostic value of magnetic resonance imaging (MRI) findings for predicting survival at 12 months and long-term relapse remains uncertain. This was a retrospective cohort study evaluating the prognostic value of different MRI variables using multivariable logistic regression and Cox proportional hazards analysis. In total, 138 dogs were presumptively diagnosed with MUO. The most common location for lesions identified on MRI were the white matter tracts of the corona radiata and corpus callosum, followed by the frontal, sensorimotor and temporal cortices. Lower T2 lesion load (p = 0.006, OR = 0.942, CI = 0.902-0.983) was associated with longer survival and higher T1 post-contrast lesion load (p = 0.023, OR = 1.162, CI = 1.021-1.322) was associated with relapse. This study has identified prognostic factors that may help identify dogs at higher risk of death and relapse and therefore guide treatment recommendations.

Behavioral disinhibition in stroke.

Post-stroke behavioral disinhibition (PSBD) is common in stroke survivors and often presents as impulsive, tactless or vulgar behavior. However, it often remains undiagnosed and thus untreated, even though it can lead to a longer length of stay in a rehabilitation facility. The proposed study will aim to evaluate the clinical, neuropsychological and magnetic resonance imaging (MRI) correlates of PSBD in a cohort of stroke survivors and describe its 12-month course. This prospective cohort study will recruit 237 patients and will be conducted at the Neurology Unit of the Prince of Wales Hospital. The project duration will be 24 months. The patients will be examined by multiple MRI methods, including diffusion-weighted imaging, within 1 week after stroke onset. The patients and their caregivers will receive a detailed assessment at a research clinic at 3, 9 and 15 months after stroke onset (T1, T2 and T3, respectively). The disinhibition subscale of the Frontal Systems Behavior Scale (FrSBe) will be completed by each subject and caregiver, and scores ≥65 will be considered to indicate PSBD.A stepwise logistic regression will be performed to assess the importance of lesions in the regions of interest (ROIs), together with other significant variables identified in the univariate analyses. For patients with PSBD at T1, the FrSBe disinhibition scores will be compared between the groups of patients with and without ROI infarcts, using covariance analysis. The demographic, clinical and MRI variables of remitters and non-remitters will be examined again at T2 and T3 by logistic regression. This project will be the first MRI study on PSBD in stroke survivors. The results will shed light on the associations of lesions in the orbitofrontal cortex, anterior temporal lobe and subcortical brain structures with the risk of PSBD. The obtained data will advance our understanding of the pathogenesis and clinical course of PSBD in stroke, as well as other neurological conditions. The findings are thus likely to be applicable to the large population of patients with neurological disorders at risk of PSBD and are expected to stimulate further research in this field.

Lobular Neoplasia Diagnosed by MRI-Guided Breast Biopsy: Identifying Upgrade Rate to Malignancy and Outcomes of Clinical and Surgical Management.

The aim of this study was to determine surgical and clinical outcomes of lobular neoplasia (LN) diagnosed by magnetic resonance imaging (MRI) biopsy, including upgrade to malignancy, and to assess for characteristics associated with upgrade. A single-institution retrospective study, between 2013 and 2022, of patients with histopathological findings of LN via MRI-guided biopsy was performed using an institutional database and review of the electronic medical records. Decision for excision or surveillance was made by a multidisciplinary team per institutional practice. Patient demographics and imaging characteristics were summarized using descriptive analyses. Upgrade was defined as upgrade to cancer on surgical pathology for patients treated with excision or the development of cancer at the biopsy site during surveillance. The Wilcoxon rank-sum test and Fisher's exact test were used to compare features of the upgraded cohort with the remainder of the group. Ninety-four MRI biopsies diagnosing LN were included. Median age was 57 years (range 37-78years). Forty-six lesions underwent excision while 48 lesions were surveilled. The upgrade rate was 7.4% (7/94). Upgrades in the excised cohort consisted of pleomorphic lobular carcinoma in situ (LCIS; n=1), ductal carcinoma in situ (DCIS; n=3) and invasive lobular carcinoma (ILC; n=2), while one interval development of DCIS was observed at the site of biopsy in the surveillance cohort. No MRI or patient variables were associated with upgrade. In this contemporary cohort of MRI-detected LNs, the upgrade rate was low. Omission of surgery for MRI-detected LNs in carefully selected patients may be considered in a shared decision-making capacity between the patient and the treatment team. Larger cohorts are needed to determine factors predictive of upgrade risk.

Prediction of pathological complete response of breast cancer patients who received neoadjuvant chemotherapy with a nomogram based on clinicopathologic variables, ultrasound, and MRI.

To establish a nomogram for predicting the pathologic complete response (pCR) in breast cancer (BC) patients after NAC by applying magnetic resonance imaging (MRI) and ultrasound (US). A total of 607 LABC women who underwent NAC before surgery between January 2016 and June 2022 were retrospectively enrolled, and then were randomly divided into the training (n = 425) and test set (n = 182) with the ratio of 7:3. MRI and US variables were collected before and after NAC, as well as the clinicopathologic features. Univariate and multivariate logistic regression analyses were applied to confirm the potentially associated predictors of pCR. Finally, a nomogram was developed in the training set with its performance evaluated by the area under the receiver operating characteristics curve (ROC) and validated in the test set. Of the 607 patients, 108 (25.4%) achieved pCR. Hormone receptor negativity (odds ratio [OR], 0.3; P < .001), human epidermal growth factor receptor 2 positivity (OR, 2.7; P = .001), small tumour size at post-NAC US (OR, 1.0; P = .031), tumour size reduction ≥50% at MRI (OR, 9.8; P < .001), absence of enhancement in the tumour bed at post-NAC MRI (OR, 8.1; P = .003), and the increase of ADC value after NAC (OR, 0.3; P = .035) were all significantly associated with pCR. Incorporating the above variables, the nomogram showed a satisfactory performance with an AUC of 0.884. A nomogram including clinicopathologic variables and MRI and US characteristics shows preferable performance in predicting pCR. A nomogram incorporating MRI and US with clinicopathologic variables was developed to provide a brief and concise approach in predicting pCR to assist clinicians in making treatment decisions early.

Clinical Manifestations.

A delay in the detection of Mild Cognitive Impairment (MCI) in the community delays the opportunity for early intervention. Accurate tools to detect MCI in the community are lacking. The Visual Cognitive Assessment Test (VCAT) is a visual based cognitive test useful for multilingual populations without the need for translation. Here, we evaluate the usefulness of VCAT in detecting MCI in a community population in Singapore. We recruited 469 participants from the community who completed a detailed neuropsychological assessment and 261 of them completed a 3T Magnetic Resonance Imaging (MRI) brain scan. We performed a ROC analysis to test the diagnostic performance of VCAT compared to MoCA in distinguishing mild cognitive impairment (MCI) from cognitively normal (CN) by measuring area under the curve (AUC). To test for the association of VCAT with structural MRI, we performed a Pearson's correlation analysis for VCAT and MRI variables. We recruited 39 CN, 168 subjective cognitive decline and 262 MCI participants from Dementia Research Centre (Singapore). Mean age of the cohort was 62.77, SD = 9.57, mean education years was 13.97, SD = 3.41 and majority were women (57.8%). VCAT was effective in detecting MCI from CN with an AUC of 0.794 (95% CI 0.723-0.865) which was slightly higher than MOCA 0.699 (95% CI 0.621-0.777). Among subjects with MCI, VCAT was associated with medial temporal lobe atrophy (MTA) (ρ = -0.265, p = 0.001). The VCAT is useful in detecting MCI in the community in Singapore and may be an effective measure of neurodegeneration.

Magnetic resonance imaging predicts the days lost from training and competition: evaluation of 56 indirect muscle injuries in professional football players.

Lower limb muscle injuries have a strong impact in training and official competitions stoppage for professional football players. This study aimed to explore the relationship between oedema-like changes found on magnetic resonance imaging (MRI) in acute indirect thigh injuries muscles and the time required for the athlete to return to individual training - "return to training" (RTT) and for full availability for official competitions - "return to play" (RTP). Professional football players from 2017/2018 to 2021/2022 seasons top league team with clinical and ultrasound (US) diagnosis of acute hamstrings or quadriceps muscle injury, confirmed on 48/72h subsequent MRI, were included. MRI images were retrospectively re-evaluated. MRI parameters evaluated were cross-sectional area (CSA), cranio-caudal extension (CCE), distance to nearest insertion (DI) and volume (V). Univariate and multivariate analysis was performed to find factors related to RTT, RTP, and episodes of reinjuries. Thirty-four first traumatic muscle injuries met the inclusion criteria. The mean time to RTT and RTP was 22 (4-49) and 25 (4-55) days, respectively. CCE and V resulted as independent predictive MRI variables for the time to RTT (P=0.012) and RTP (P=0.02), respectively. Thresholds of CCE≥11.31 cm and V ≥19.5cc can predict a time to RTT≥22 days (Odds Ratio [OR] 9.5) and RTP≥25 days (OR 4.583), respectively. The decision on the time required for RTP is based on clinic and imaging evaluation; CCE and V of the MRI oedema-like changes help to define the prognosis of the injury.

Cardiac function, myocardial fat deposition, and lipid profile in young smokers: a cross-sectional study.

There is a possibility that cardiac morphometric characteristics are associated with the lipid profile, that is, the composition and concentration of triglycerides, total cholesterol, HDL, LDL, and others lipoproteins in young smokers without comorbidities. Thus, this study aimed to evaluate the association of cardiac morphometric characteristics, myocardial fat deposition, and smoking cessation with the lipid profile of young smokers. A clinical and laboratory evaluation of lipids and the smoking status was performed on 57 individuals, including both a smoker group and a control group. Cardiac magnetic resonance imaging (MRI) with proton spectroscopy was performed to identify cardiac changes and triglyceride (TG) deposition in myocardial tissue. No differences were observed between the groups (control vs. smokers) in relation to the amount of myocardial TG deposition (p = 0.47); however, when TG deposition was correlated with cardiac MRI variables, a positive correlation was identified between smoking history and myocardial TG deposition [hazard ratio (95% CI), 0.07 (0.03-0.12); p = 0.002]. Furthermore, it was observed that the smoking group had lower high-density lipoprotein cholesterol [51 (45.5-59.5) mg/dl vs. 43 (36-49.5) mg/dl, p = 0.003] and higher TG [73 (58-110) mg/dl vs. 122 (73.5-133) mg/dl, p = 0.01] and very-low-density lipoprotein cholesterol [14.6 (11.6-22.2) mg/dl vs. 24.4 (14.7-26.6) mg/dl, p = 0.01] values. In the control and smoking groups, a negative correlation between TGs and the diameter of the aortic root lumen and positive correlation with the thickness of the interventricular septum and end-diastolic volume (EDV) of both the right ventricle (RV) and left ventricle (LV) were noted. Moreover, in the RV, positive correlations with the end-systolic volume (ESV) index (ESVI), stroke volume (SV), ESV, and EDV were observed. Regarding serum free fatty acids, we found a negative correlation between their values and the diameter of the lumen of the ascending aortic vessel. Lipoprotein lipase showed a positive correlation with the SV index of the RV and negative correlation with the diameter of the lumen of the ascending aortic vessel. Several associations were observed regarding cardiac morphometric characteristics, myocardial fat deposition, and smoking cessation with the lipid profile of young smokers.

Intimal predominant calcification is associated with plaque instability in the vertebrobasilar artery by vessel wall magnetic resonance imaging and computed tomography

Background and aimsIt remains unknown about the relationship between vertebrobasilar artery (VBA) calcification and plaque instability. We aimed to investigate the characteristics of VBA calcification using vessel wall magnetic resonance imaging (MRI) and computed tomography (CT) and its association with acute cerebral infarction (ACI). MethodsNine hundred and thirty patients with VBA stenosis who underwent vessel wall MRI and CT examinations were evaluated retrospectively. Calcification morphology was classified as either intimal or non-intimal predominant using a CT-pathology-validated grading method. Qualitative and quantitative plaque MRI variables and calcification characteristics were compared between culprit and non-culprit lesions. The association between VBA calcification and the occurrence of culprit lesions was investigated using multivariate logistic regression. ResultsA total of 150 patients with ACI and 142 patients without ACI were eligible for subsequent analyses, respectively. In the qualitative analysis, T1 hyperintensity (p < 0.001) and intimal predominant calcification (p = 0.021) were more frequently observed in the culprit than non-culprit lesions. In the quantitative analyses, culprit lesions had a larger stenosis degree, plaque length, normal wall index, contrast enhancement ratio, lower calcification density and smaller calcification volume than non-culprit lesions (p all < 0.05). Intimal predominant calcification (odds ratio [OR], 2.51; 95 % confident interval [CI], 1.31–4.82, p = 0.006) and calcification density (OR, 0.53; 95 % CI, 0.35–0.78, p = 0.001) were independently associated with the presence of ACI after adjusting for clinical risk factors and plaque variables. ConclusionsIntimal predominant calcification in vertebrobasilar atherosclerosis is associated with the likelihood of having caused acute cerebral infarction. The morphology and density of VBA calcification may provide insight into stroke risk stratification in the posterior circulation.