CT-Based Radiomics Models for Differentiation of Benign and Malignant Thyroid Nodules: A Multicenter Development and Validation Study.

BACKGROUND. CT is increasingly detecting thyroid nodules. Prior studies indicated a potential role of CT-based radiomics models in characterizing thyroid nodules, although these studies lacked external validation. OBJECTIVE. The purpose of this study was to develop and validate a CT-based radiomics model for the differentiation of benign and malignant thyroid nodules. METHODS. This retrospective study included 378 patients (mean age, 46.3 ± 13.9 [SD] years; 86 men, 292 women) with 408 resected thyroid nodules (145 benign, 263 malignant) from two centers (center 1: 293 nodules, January 2018 to December 2022; center 2: 115 nodules, January 2020 to December 2022) who underwent preoperative multiphase neck CT (noncontrast, arterial, and venous phases). Nodules from center 1 were divided into training (n = 206) and internal validation (n = 87) sets; all nodules from center 2 formed an external validation set. Radiologists assessed nodules for morphologic CT features. Nodules were manually segmented on all phases, and radiomic features were extracted. Conventional (clinical and morphologic CT), noncontrast CT radiomics, arterial phase CT radiomics, venous phase CT radiomics, multiphase CT radiomics, and combined (clinical, morphologic CT, and multiphase CT radiomics) models were established using feature selection methods and evaluated by ROC curve analysis, calibration-curve analysis, and decision-curve analysis. RESULTS. The combined model included patient age, three morphologic features (cystic change, "edge interruption" sign, abnormal cervical lymph nodes), and 28 radiomic features (from all three phases). In the external validation set, the combined model had an AUC of 0.923, and, at an optimal threshold derived in the training set, sensitivity of 84.0%, specificity of 94.1%, and accuracy of 87.0%. In the external validation set, the AUC was significantly higher for the combined model than for the conventional model (0.827), noncontrast CT radiomics model (0.847), arterial phase CT radiomics model (0.826), venous phase CT radiomics model (0.773), and multiphase CT radiomics model (0.824) (all p < .05). In the external validation set, the calibration curves indicated the lowest (i.e., best) Brier score for the combined model; in the decision-curve analysis, the combined model had the highest net benefit for most of the range of threshold probabilities. CONCLUSION. A combined model incorporating clinical, morphologic CT, and multiphase CT radiomics features exhibited robust performance in differentiating benign and malignant thyroid nodules. CLINICAL IMPACT. The combined radiomics model may help guide further management for thyroid nodules detected on CT.

Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors.

Purpose: To develop a point-based scoring system (PSS) based on contrast-enhanced computed tomography (CT) qualitative and quantitative features to differentiate gastric schwannomas (GSs) from gastrointestinal stromal tumors (GISTs). Methods: This retrospective study included 51 consecutive GS patients and 147 GIST patients. Clinical and CT features of the tumors were collected and compared. Univariate and multivariate logistic regression analyses using the stepwise forward method were used to determine the risk factors for GSs and create a PSS. Area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic efficiency of PSS. Results: The CT attenuation value of tumors in venous phase images, tumor-to-spleen ratio in venous phase images, tumor location, growth pattern, and tumor surface ulceration were identified as predictors for GSs and were assigned scores based on the PSS. Within the PSS, GS prediction probability ranged from 0.60% to 100% and increased as the total risk scores increased. The AUC of PSS in differentiating GSs from GISTs was 0.915 (95% CI: 0.874-0.957) with a total cutoff score of 3.0, accuracy of 0.848, sensitivity of 0.843, and specificity of 0.850. Conclusions: The PSS of both qualitative and quantitative CT features can provide an easy tool for radiologists to successfully differentiate GS from GIST prior to surgery.

Development and validation of a point-based scoring system for predicting axillary lymph node metastasis and disease outcome in breast cancer using clinicopathological and multiparametric MRI features.

BACKGROUND: Axillary lymph node (ALN) metastasis is used to select treatment strategies and define the prognosis in breast cancer (BC) patients and is typically assessed using an invasive procedure. Noninvasive, simple, and reliable tools to accurately predict ALN status are desirable. We aimed to develop and validate a point-based scoring system (PSS) for stratifying the ALN metastasis risk of BC based on clinicopathological and quantitative MRI features and to explore its prognostic significance. METHODS: A total of 219 BC patients were evaluated. The clinicopathological and quantitative MRI features of the tumors were collected. A multivariate logistic regression analysis was used to create the PSS. The performance of the models was evaluated using receiver operating characteristic curves, and the area under the curve (AUC) of the models was calculated. Kaplan-Meier curves were used to analyze the survival outcomes. RESULTS: Clinical features, including the American Joint Committee on Cancer (AJCC) stage, T stage, human epidermal growth factor receptor-2, estrogen receptor, and quantitative MRI features, including maximum tumor diameter, Kep, Ve, and TTP, were identified as risk factors for ALN metastasis and were assigned scores for the PSS. The PSS achieved an AUC of 0.799 in the primary cohort and 0.713 in the validation cohort. The recurrence-free survival (RFS) and overall survival (OS) of the high-risk (> 19.5 points) groups were significantly shorter than those of the low-risk (≤ 19.5 points) groups in the PSS. CONCLUSION: PSS could predict the ALN metastasis risk of BC. A PSS greater than 19.5 was demonstrated to be a predictor of short RFS and OS.

Increased glymphatic system activity in patients with mild traumatic brain injury.

Purpose: This study aims to investigate the glymphatic system activity changes in patients with mild traumatic brain injury (mTBI), particularly in MRI-negative patients, using analysis along the perivascular space (ALPS) technology. Methods: A total of 161 mTBI patients (age: 15-92 years old) and 28 healthy controls (age: 15-84 years old) were included in this retrospective study. The mTBI patients were divided into MRI-negative and MRI-positive groups. ALPS index was calculated automatically using whole-brain T1-MPRAGE imaging and diffusion tensor imaging. The Student's t and chi-squared tests were performed to compare the ALPS index, age, gender, course of disease, and Glasgow Coma Scale (GCS) score between groups. Correlations among ALPS index, age, course of disease and GCS score were computed using Spearman's correlation analysis. Results: Increased activity of the glymphatic system was suggested in mTBI patients based on ALPS index analysis, including the MRI-negative patients. There was a significant negative correlation between the ALPS index and age. In addition, a weak positive correlation between the ALPS index and course of disease was also observed. On the contrary, there was no significant correlation between the ALPS index and sex nor between the ALPS index and GCS score. Conclusion: Our study demonstrated that the activity level of the glymphatic system was enhanced in mTBI patients, even when their brain MRI scans were negative. These findings may provide novel insights for understanding the pathophysiology of mild TBI.

Dual-phase contrast-enhanced multislice computed tomography scans play a key role in the diagnosis of abdominal wall desmoid-type fibromatoses.

BACKGROUND: Abdominal wall desmoid-type fibromatoses (AWDF) are occasionally encountered in clinical work, but related CT reports are rare, and most cases were misdiagnosed as malignant tumors. OBJECTIVE: We aimed to determine the diagnostic value of multislice computed tomography (MSCT) in relation to the clinical diagnosis of AWDF. METHODS: The medical records of 14 patients whose pathology results provided initial confirmation of AWDF were reviewed, and data describing their clinical characteristics, tumors' MSCT characteristics, and the condition of the surrounding tissues were analyzed and summarized retrospectively. Intraobserver and interobserver reproducibilities were evaluated. RESULTS: AWDF tended to occur in women of childbearing age (24-32 years). They occurred more frequently during the first year following pregnancy. The mean disease duration was 5.64 ± 3.78 months. All isolated tumors were growing along the musculoaponeurotic layer, and their maximum diameters were between 32 and 76 mm. Tumors' capsules were incomplete, and although the tumors infiltrated the surrounding muscles, the surrounding fat tissue and vessels were not infiltrated. None of the patients' tumors showed cystic degeneration, calcification, necrosis, or peritumoral edema. The tumors had slightly lower densities on the pre-contrast enhancement scans and mild-to-moderate enhancement after contrast enhancement. All tumors contained ribbon-like structures, and approximately 65% of the tumors encircled vascular structures. CONCLUSION: Dual-phase contrast-enhanced MSCT scans were associated with a high level of diagnostic efficacy for AWDF. The abdominal wall masses grew along the musculoaponeurotic layer, which, together with the ribbon-like structures within the tumors, should prompt clinicians to consider the presence of AWDF.

Bone marrow stromal cells-derived exosomes reduce neurological damage in traumatic brain injury through the miR-124-3p/p38 MAPK/GLT-1 axis.

BACKGROUND: Mounting evidence indicates that stem cell-derived exosomal miRNAs have therapeutic effects on traumatic brain injury (TBI). This research is focused on exploring the molecular processes of miR-124-3p obtained from bone marrow stromal cells-derived exosomes (BMSCs-Exos) in attenuating posttraumatic glutamate-mediated excitotoxicity. METHODS: We created a TBI rat model and analyzed the expression profile of miRNA through miRNA microarray. The miR-124-3p and p38 MAPK levels were analyzed utilizing RT-qPCR and western blotting. Dual-luciferase reporter (DLR) assay showed the targeting relationship between miR-124-3p and p38 MAPK. We subsequently conducted a TUNEL assay and flow cytometry to evaluate the neuronal apoptotic rate in an in vitro glutamate-mediated excitotoxicity model treated with BMSCs-Exos enriched with miR-124-3p (BMSCs-ExosmiR-124-3p). Moreover, the levels of p38 MAPK and glutamate transporter-1 (GLT-1) were measured by western blotting. Furthermore, BMSCs-ExosmiR-124-3p were administered to the TBI rats, and their neuroprotective effects were observed using western blotting, immunohistochemistry, histological staining, magnetic resonance imaging (MRI), and Morris water maze (MWM). RESULTS: The results revealed that the brains of TBI rats exhibited lowered miR-124-3p and enhanced p38 MAPK levels. DLR assay demonstrated miR-124-3p's role in targeting p38 MAPK and negatively regulating its expression. In vitro and in vivo studies confirmed that BMSCs-ExosmiR-124-3p attenuated glutamate-mediated excitotoxicity by downregulating p38 MAPK and upregulating GLT-1 expressions via transferring exosomal miR-124-3p. Moreover, histopathological evaluation and MRI results showed that BMSCs-ExosmiR-124-3p remarkably alleviated neuronal cell death and minimized the lesion volumes post-TBI. MWM outcomes illustrated that BMSCs-ExosmiR-124-3p treatment could substantially improve neurological function post-TBI. Furthermore, the effects of treatment with p38 MAPK inhibitor SB203580 were similar to BMSCs-ExosmiR-124-3p. CONCLUSION: Overall, the outcomes of the current report highlighted that BMSCs-ExosmiR-124-3p can lead to the upregulation of GLT-1 in TBI rat models by inhibiting the p38 MAPK signaling pathway, hence alleviating glutamate-mediated excitotoxicity and attenuating neurological damage post-TBI.

Combined fine-needle aspiration with core needle biopsy for assessing thyroid nodules: a more valuable diagnostic method?

PURPOSE: This study aimed to evaluate the diagnostic value of combined fine-needle aspiration (FNA) with core needle biopsy (CNB) in thyroid nodules. METHODS: FNA and CNB were performed simultaneously on 703 nodules. We compared the proportions of inconclusive results and the diagnostic performance for malignancy among FNA, CNB, and combined FNA/CNB for different nodule sizes. RESULTS: Combined FNA/CNB showed lower proportions of inconclusive results than CNB for all nodules (2.8% vs. 5.7%, P<0.001), nodules ≤1.0 cm (4.9% vs. 7.3%, P=0.063), nodules >1.0 cm (2.0% vs. 5.0 %, P<0.001), nodules ≤1.5 cm (3.8% vs. 7.9 %, P<0.001), and nodules >1.5 cm (2.1% vs. 3.9 %, P=0.016). The sensitivity of combined FNA/CNB in predicting malignancy was significantly higher than that of CNB (89.0% vs. 80.0%, P<0.001) and FNA (89.0% vs. 58.1%, P<0.001) for all nodules. Within American College of Radiology Thyroid and Imaging Reporting and Data System grades 4-5, in the subgroup of nodules ≤1.5 cm, combined FNA/ CNB showed the best sensitivity in predicting malignancy (91.4%), significantly higher than that of CNB (81.0%, P<0.001) and FNA (57.8%, P<0.001). However, in the subgroup of nodules >1.5 cm, the difference between combined FNA/CNB and CNB was not significant (84.2% vs. 78.9%, P=0.500). CONCLUSION: Regardless of nodule size, combined FNA/CNB tended to yield lower proportions of inconclusive results than CNB or FNA alone and exhibited higher performance in diagnosing malignancy. The combined FNA/CNB technique may be a more valuable diagnostic method for nodules ≤1.5 cm and nodules with a risk of malignancy than CNB and FNA alone.

The aging of glymphatic system in human brain and its correlation with brain charts and neuropsychological functioning.

This study aimed to investigate the aging of the glymphatic system in healthy adults, and to determine whether this change is correlated with the brain charts and neuropsychological functioning. Two independent brain 3.0 T MRI datasets were analyzed: a public dataset and our hospital-own dataset from two hospitals. The function of the glymphatic system was quantified by diffusion analysis along the perivascular space (ALPS) index via an automatic method. Brain charts were calculated online. Correlations of the ALPS index with the brain charts, age, gender, and neuropsychological functioning, as well as differences in ALPS index across age groups, were assessed. A total of 161 healthy volunteers ranging in age from 20 to 87 years were included. ALPS index was negatively correlated with the age in both independent datasets. Compared with that of the young group, the ALPS index was significantly lower in the elderly group. No significant difference was found in the ALPS index between different genders. In addition, the ALPS index was not significantly correlated with the brain charts and neuropsychological functioning. In conclusion, the aging of glymphatic system exists in healthy adults, which is not correlated with the changes of brain charts and neuropsychological functioning.

The value of quantitative plaque analysis based on coronary computed tomography angiography in predicting the percutaneous coronary intervention outcome of chronic total occlusion lesions.

Background: Due to the uncertainty of the success of percutaneous coronary intervention (PCI) and the complexity of selecting suitable treatment cases, the interventional outcome of coronary chronic total occlusion (CTO) remains challenging. The purpose of this study was to evaluate the role of quantitative plaque analysis based on coronary computed tomography angiography (CCTA) in predicting the CTO-PCI outcome. Methods: We retrospectively included 78 patients with CTO (80 lesions) confirmed by invasive coronary angiography from July 2016 to December 2018. All patients underwent PCI treatment according to standard practice. A total of 47 lesions in 47 patients were successfully treated with PCI. PCI failed in the remaining 33 lesions in 31 patients. The following conventional CCTA morphologic parameters were evaluated and compared between the PCI-success and PCI-failure groups: stump morphology; occlusion length, tortuous course; CTO lesion calcium; bridging collateral vessel; retrograde collateral vessel; the appearance of the occluded distal segment; and quantitative CTO plaque characteristics, including total plaque volume, calcified plaque (CP) volume, noncalcified plaque (NCP) volume, low-density noncalcified plaque (LDNCP) volume, and plaque length. Univariate and multivariate logistic regression analyses were performed to determine independent parameters predictive of CTO-PCI outcomes. The predictive performances were assessed using receiver operating characteristic curve analysis. Results: The blunt stump was the only independent CCTA morphologic parameter to predict the outcome of CTO-PCI [odds ratio (OR): 10.807; P<0.001]. NCP volume (OR: 1.018; P<0.001), CP volume (OR: 1.026; P=0.049), and plaque length (OR: 1.058; P=0.037) were independent quantitative CTO plaque characteristics predictive of CTO-PCI outcomes. The plaque-based model combining NCP volume with CP volume and plaque length had a higher area under the curve (AUC =0.96) than did the morphology-based model that included blunt stump (AUC 0.68) in predicting the outcomes of CTO-PCI (P<0.001). Conclusions: The CCTA-based plaque characteristics, including NCP volume, CP volume, and plaque length, outperformed morphologic parameters in predicting the CTO-PCI outcomes.

Gemstone Spectral CT Virtual Noncontrast Images and Iodine Maps for the Characterization of Thyroid Lesions and Distinguishing Thyroid Papillary Carcinoma from Nodular Goiter.

Background: Gemstone spectral contrast-enhanced CT with virtual noncontrast (VNC) images and iodine maps can potentially reduce the number of required CT scans for thyroid lesions. However, data regarding the clinical utility of VNC images and iodine maps in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter are still limited. Purpose: To determine whether VNC images and iodine density could reliably aid in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter compared with true noncontrast (TNC) images. Methods: This retrospective study included patients with thyroid papillary carcinoma or nodular goiter who underwent TNC and contrast-enhanced gemstone spectral CT scans. The consistency of qualitative parameters, including intralesional calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis, between TNC and VNC images, was analyzed using the kappa statistic. TNC attenuation, VNC attenuation, absolute attenuation between TNC and VNC, and iodine density were compared between thyroid papillary carcinoma and nodular goiter by using Student's t-test. The diagnostic performance for distinguishing papillary carcinoma from nodular goiter was evaluated by using the area under the receiver operating characteristic curve (AUC) value, sensitivity, and specificity. Results: VNC and TNC imaging showed comparable performance in delineating calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis (all k > 0.75). Papillary carcinoma showed significantly lower absolute attenuation between VNC and TNC than nodular goiter (7.86 ± 6.74 vs. 13.43 ± 10.53, P=0.026), which was similarly observed for iodine density (31.45 ± 8.51 vs. 37.27 ± 10.34, P=0.016). The iodine density showed higher diagnostic performance (AUC = 0.727), accuracy (0.773 vs. 0.667), sensitivity (0.750 vs. 0.708), and specificity (0.786 vs. 0.643) than the absolute attenuation between TNC and VNC images (AUC = 0.683). Conclusions: VNC imaging, a promising substitute for TNC imaging, has comparable diagnostic efficacy for reliably characterizing thyroid lesions. Iodine density could be valuable for distinguishing thyroid papillary carcinoma from nodular goiter.

Ultrasound features affecting the sample adequacy after fine-needle aspiration of thyroid nodules with different risk stratification.

BACKGROUND: The inadequacy samples caused by the internal characteristic structure of thyroid nodules are difficult to be solved. OBJECTIVE: To evaluate the ultrasound features affecting the sample adequacy after fine-needle aspiration (FNA) of thyroid nodules with different risk stratification. METHODS: 592 thyroid nodules that underwent ultrasound-guided FNA were included in this retrospective study. The sample obtained by FNA were classified as inadequacy and adequacy according to the cytopathological results. Ultrasound features (ie., size, position, cystic predominance, composition, echo, shape, margin, and superficial annular calcification status) of the nodules were recorded and compared between the inadequacy sample group and adequacy sample group. RESULTS: Multiple logistic regression shows that preponderant cystic proportion (OR, 0.384; P = 0.041), extremely hypoechogenicity and hypoechogenicity (OR, 6.349; P = 0.006) were the independent influencing factors of inadequate samples after FNA in benign expected nodules. In addition, nodule size ≤10 mm (OR, 1.960; P = 0.010) and superficially annular calcification (OR, 4.600; P < 0.001) were independent influencing factors for inadequate samples after FNA in malignant expected nodules. CONCLUSION: The ultrasound features of hypoechogenicity or high cystic proportion in benign expected nodules and that of small size or annular calcification in malignant expected nodules were the risk factors for inadequacy samples by US-guided FNA.

Quantitative morphometric changes in vascular mild cognitive impairment patients: early diagnosis of dementia.

Vascular mild cognitive impairment (VMCI) is an early and reversible stage of dementia. Volume differences in regional gray matter may reveal the development and prognosis of VMCI. This study selected 2 of the most common types of VMCI, namely, periventricular white matter hyperintensities (PWMH, n = 14) and strategic single infarctions (SSI, n = 10), and used the voxel-based morphometry method to quantify their morphological characteristics. Meanwhile, age- and sex-matched healthy volunteers were included (n = 16). All the participants were neuropsychologically tested to characterize their cognitive function and underwent whole-brain magnetic resonance imaging scanning. Our results showed that the volumes of the bilateral temporal lobes and bilateral frontal gray matter were obviously diminished in the PWMH group. The atrophy volume difference was 4,086 voxels in the left temporal lobe, 4,154 voxels in the right temporal lobe, 1,718 voxels in the left frontal lobe, and 1,141 voxels in the right frontal lobe (P ≤ 0.001). Moreover, the characteristics of the gray matter atrophy associated with the PWMH were more similar to those associated with Alzheimer's disease than SSI, which further revealed the susceptibility for escalation from PWMH to dementia. In conclusion, PWMH patients and SSI patients have different morphological characteristics, which explain the different prognoses of VMCI.

Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer.

INTRODUCTION: Improving the early prediction of neoadjuvant chemotherapy (NAC) efficacy in breast cancer can lead to an improved prediction of the final prognosis of patients, which would be useful for promoting individualized treatment. This study aimed to explore the value of the combination of dynamic contrast-enhanced (DCE)-MRI parameters and apparent diffusion coefficient (ADC) values in the early prediction of pathological complete response (pCR) to NAC for breast cancer. METHODS: A total of 119 (range, 28-69 years) patients with biopsy-proven breast cancer who received two cycles of NAC before breast surgery were retrospectively enrolled from our hospital database. Patients were divided into pCR and non pCR groups according to their pathological responses; a total of 24 patients achieved pCR, while 95 did not. The quantitative (Ktrans; Kep; Ve; IAUC) and semiquantitative parameters (W-in; W-out; TTP) of DCE-MRI that were significantly different between groups were combined with ADC values to explore their value in the early prediction of pCR to NAC for breast cancer. The independent T test was performed to compare the differences in DCE-MRI parameters and ADC values between the two groups. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC), sensitivity and specificity were calculated to evaluate the performance of the prediction. RESULTS: The Ktrans, Kep, IAUC, ADC, W-in and TTP values were significantly different between the pCR and non pCR groups after NAC. The AUC (0.845) and specificity (95.79%) of the combined Ktrans, Kep, IAUC and ADC values were both higher than those of the individual parameters. The combination of W-in, TTP and ADC values had the highest AUC value (0.886) in predicting pCR, with a sensitivity and specificity of 87.5% and 82.11%, respectively. CONCLUSIONS: The results suggested that the combination of ADC values and quantitative and semiquantitative DCE-MRI parameters, especially the combination of W-in, TTP, and ADC values, may improve the early prediction of pCR in breast cancer.

Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging to predict lymphovascular invasion and survival outcome in breast cancer.

BACKGROUND: Lymphovascular invasion (LVI) predicts a poor outcome of breast cancer (BC), but LVI can only be postoperatively diagnosed by histopathology. We aimed to determine whether quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can preoperatively predict LVI and clinical outcome of BC patients. METHODS: A total of 189 consecutive BC patients who underwent multiparametric MRI scans were retrospectively evaluated. Quantitative (Ktrans, Ve, Kep) and semiquantitative DCE-MRI parameters (W- in, W- out, TTP), and clinicopathological features were compared between LVI-positive and LVI-negative groups. All variables were calculated by using univariate logistic regression analysis to determine the predictors for LVI. Multivariate logistic regression was used to build a combined-predicted model for LVI-positive status. Receiver operating characteristic (ROC) curves evaluated the diagnostic efficiency of the model and Kaplan-Meier curves showed the relationships with the clinical outcomes. Multivariate analyses with a Cox proportional hazard model were used to analyze the hazard ratio (HR) for recurrence-free survival (RFS) and overall survival (OS). RESULTS: LVI-positive patients had a higher Kep value than LVI-negative patients (0.92 ± 0.30 vs. 0.81 ± 0.23, P = 0.012). N2 stage [odds ratio (OR) = 3.75, P = 0.018], N3 stage (OR = 4.28, P = 0.044), and Kep value (OR = 5.52, P = 0.016) were associated with LVI positivity. The combined-predicted LVI model that incorporated the N stage and Kep yielded an accuracy of 0.735 and a specificity of 0.801. The median RFS was significantly different between the LVI-positive and LVI-negative groups (31.5 vs. 34.0 months, P = 0.010) and between the combined-predicted LVI-positive and LVI-negative groups (31.8 vs. 32.0 months, P = 0.007). The median OS was not significantly different between the LVI-positive and LVI-negative groups (41.5 vs. 44.0 months, P = 0.270) and between the combined-predicted LVI-positive and LVI-negative groups (42.8 vs. 43.5 months, P = 0.970). LVI status (HR = 2.40), N2 (HR = 3.35), and the combined-predicted LVI model (HR = 1.61) were independently associated with disease recurrence. CONCLUSION: The quantitative parameter of Kep could predict LVI. LVI status, N stage, and the combined-predicted LVI model were predictors of a poor RFS but not OS.

Automated detection of intracranial artery stenosis and occlusion in magnetic resonance angiography: A preliminary study based on deep learning.

BACKGROUND AND OBJECTIVES: Intracranial atherosclerotic stenosis of a major intracranial artery is the common cause of ischemic stroke. We evaluate the feasibility of using deep learning to automatically detect intracranial arterial steno-occlusive lesions from time-of-flight magnetic resonance angiography. METHODS: In a retrospective study, magnetic resonance images with radiological reports of intracranial arterial stenosis and occlusion were extracted. The images were randomly divided into a training set and a test set. The manual annotation of lesions with a bounding box labeled "moderate stenosis," "severe stenosis," "occlusion," and "absence of signal" was considered as ground truth. A deep learning algorithm based on you only look once version 5 (YOLOv5) detection model was developed with the training set, and its sensitivity and positive predictive values to detect lesions were evaluated in the test set. RESULTS: A dataset of 200 examinations consisted of a total of 411 lesions-242 moderate stenoses, 84 severe stenoses, 70 occlusions, and 15 absence of signal. The magnetic resonance images contained 291 lesions in the training set and 120 lesions in the test set. The sensitivity and positive predictive values were 64.2 and 83.7%, respectively. The detection sensitivity in relation to the location was greatest in the internal carotid artery (86.2%). CONCLUSIONS: Applying deep learning algorithms in the automated detection of intracranial arterial steno-occlusive lesions from time-of-flight magnetic resonance angiography is feasible and has great potential.

Exosomes derived from bone marrow mesenchymal stem cells attenuate neurological damage in traumatic brain injury by alleviating glutamate-mediated excitotoxicity.

BACKGROUND: Traumatic brain injury (TBI) is one of the major contributors to disability and death worldwide. Glutamate-mediated excitotoxicity, one of the secondary injuries occurring after TBI, leads to extreme neuronal apoptosis, and can be a potential target for intervention. Bone marrow mesenchymal stem cells-derived exosomes (BMSCs-Exos) have demonstrated neuroprotective effects on TBI. However, their precise role and the underlying mechanism by which they regulate glutamate-mediated excitotoxicity have not yet been determined. Therefore, this study aimed to determine whether BMSCs-Exos alleviate glutamate excitotoxicity post-TBI and their associated mechanism. METHODS: BMSCs-Exos were extracted from the BMSCs incubation medium and identified by transmission electron microscopy, nanoparticle trafficking analysis, and western blotting. The neuroprotective effects of BMSCs-Exos on glutamate excitotoxicity were investigated in the glutamate-mediated excitotoxicity neuronal cell model and the TBI rat model (TBI induced by controlled cortical impact) using western blotting and TUNEL assay. Cortical lesion samples were collected post-TBI on day-1 and day-14 to study histology. In addition, cortical lesion volume on days 1, 3 and 7 following TBI was determined using T2-weighted magnetic resonance imaging (MRI), and cognitive function was assessed at 4 weeks following TBI using the Morris water maze (MWM) test. RESULTS: BMSCs-Exos were observed to be spherical with a mean diameter of 109.9 nm, and expressed exosomal markers CD9, CD81 and TSG101. BMSCs-Exos were efficiently endocytosed by astrocytes after co-incubation for 24 h. In vitro studies revealed that 125 µM of glutamate significantly induced neuronal apoptosis, which was attenuated by BMSCs-Exos in astrocyte-neuron co-cultures. This attenuation was mediated by the upregulation of glutamate transporter-1 (GLT-1) level and the downregulation of p-p38 MAPK level in astrocytes. Similar results were obtained in vivo, wherein we verified that PKH67-labeled BMSCs-Exos administered intravenously could reach the perilesional cortex crossing the blood-brain barrier and significantly reduce glutamate levels in the perilesional cortex of the TBI rat, accompanied by increased GLT-1 level and downregulation in p-p38 MAPK level. Additionally, western blotting and TUNEL staining also revealed that BMSCs-Exos significantly downregulated the expression of pro-apoptosis markers, including cleaved caspase-3 and cleaved caspase-9, and attenuated neuronal apoptosis following TBI. Immunohistochemical analysis and Nissl staining showed that BMSCs-Exos significantly increased GLT-1-positive cells, and the number of apoptotic neurons decreased in the perilesional cortex. Moreover, MRI and MWM results revealed that BMSCs-Exos significantly minimized cortical lesion volume and ameliorated cognitive function after TBI. The underlying neuroprotective mechanism of BMSCs-Exos may be due to an increase in GLT-1 level in astrocytes by blocking the p38 MAPK signaling pathway. CONCLUSION: Taken together, our findings demonstrate that the implementation of BMSCs-Exos may be an effective prospective therapy for attenuating post-TBI neurological damage.

Distinguishing COVID-19 From Influenza Pneumonia in the Early Stage Through CT Imaging and Clinical Features.

Background: Both coronavirus disease 2019 (COVID-19) and influenza pneumonia are highly contagious and present with similar symptoms. We aimed to identify differences in CT imaging and clinical features between COVID-19 and influenza pneumonia in the early stage and to identify the most valuable features in the differential diagnosis. Methods: Seventy-three patients with COVID-19 confirmed by real-time reverse transcription-polymerase chain reaction (RT-PCR) and 48 patients with influenza pneumonia confirmed by direct/indirect immunofluorescence antibody staining or RT-PCR were retrospectively reviewed. Clinical data including course of disease, age, sex, body temperature, clinical symptoms, total white blood cell (WBC) count, lymphocyte count, lymphocyte ratio, neutrophil count, neutrophil ratio, and C-reactive protein, as well as 22 qualitative and 25 numerical imaging features from non-contrast-enhanced chest CT images were obtained and compared between the COVID-19 and influenza pneumonia groups. Correlation tests between feature metrics and diagnosis outcomes were assessed. The diagnostic performance of each feature in differentiating COVID-19 from influenza pneumonia was also evaluated. Results: Seventy-three COVID-19 patients including 41 male and 32 female with mean age of 41.9 ± 14.1 and 48 influenza pneumonia patients including 30 male and 18 female with mean age of 40.4 ± 27.3 were reviewed. Temperature, WBC count, crazy paving pattern, pure GGO in peripheral area, pure GGO, lesion sizes (1-3 cm), emphysema, and pleural traction were significantly independent associated with COVID-19. The AUC of clinical-based model on the combination of temperature and WBC count is 0.880 (95% CI: 0.819-0.940). The AUC of radiological-based model on the combination of crazy paving pattern, pure GGO in peripheral area, pure GGO, lesion sizes (1-3 cm), emphysema, and pleural traction is 0.957 (95% CI: 0.924-0.989). The AUC of combined model based on the combination of clinical and radiological is 0.991 (95% CI: 0.980-0.999). Conclusion: COVID-19 can be distinguished from influenza pneumonia based on CT imaging and clinical features, with the highest AUC of 0.991, of which crazy-paving pattern and WBC count play most important role in the differential diagnosis.

Readout-Segmented Echo-Planar Diffusion-Weighted MR Imaging Improves the Differentiation of Breast Cancer Receptor Statuses Compared With Conventional Diffusion-Weighted Imaging.

BACKGROUND: Readout-segmented echo-planar diffusion-weighted imaging (RS-EPI) can improve image quality and signal-to-noise ratio, the resulting apparent diffusion coefficient (ADC) value acts as a more sensitive biomarker to characterize tumors. However, data regarding the differentiation of breast cancer (BC) receptor statuses using RS-EPI are limited. PURPOSE: To determine whether RS-EPI improves the differentiation of receptor statuses compared with conventional single-shot (SS) EPI in breast MRI. STUDY TYPE: Retrospective. POPULATION: A total of 151 BC women with the mean age of 50.6 years. FIELD STRENGTH/SEQUENCE: A 3 T/ RS-EPI and SS-EPI. ASSESSMENT: The ADCs of the lesion and normal background tissue from the two sequences were collected by two radiologists with 15 years of experience working of breast MRI (M.H.Z. and X.F.C.), and a normalized ADC was calculated by dividing the mean ADC value of the lesion by the mean ADC value of the normal background tissue. STATISTICAL TESTS: Agreement between the ADC measurements from the two sequences was assessed using the Pearson correlation coefficient and Bland-Altman plots. One-way analysis of variance, Kruskal-Wallis test, and median difference were used to compare the ADC measurements for all lesions and different receptor statuses. A P value less than 0.05 indicated a significant result. RESULTS: The ADC measurements of all lesions and normal background tissues were significantly higher on RS-EPI than on SS-EPI (1.82 ± 0.33 vs. 1.55 ± 0.30 and 0.83 ± 0.11 vs. 0.79 ± 0.10). The normalized ADC was lower on RS-EPI than on SS-EPI (0.47 ± 0.11 vs. 0.53 ± 0.12, a median difference of -0.04 [95% CI: -0.256 to 0.111]). For both diffusion methods, only the ADC measurement of RS-EPI was higher for human epidermal growth factor receptor-2 (HER-2)-positive tumors than for HER-2-negative tumors (0.87 ± 0.10 vs. 0.81 ± 0.11), and this measurement was associated with HER-2 positive status (adjusted odds ratio [OR] = 654.4); however, similar results were not observed for the ADC measurement of SS-EPI (0.80 ± 0.10 vs. 0.78 ± 0.11 with P = 0.199 and adjusted OR = 0.21 with P = 0.464, respectively). DATA CONCLUSION: RS-EPI can improve the distinction between HER-2-positive and HER-2-negative breast cancer, complementing the clinical application of diffusion imaging. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes.

OBJECTIVES: To assess breast cancer receptor status and molecular subtypes by using the CAIPIRINHA-Dixon-TWIST-VIBE and readout-segmented echo-planar diffusion weighted imaging techniques. METHODS: A total of 165 breast cancer patients were retrospectively recruited. Patient age, estrogen receptor, progesterone receptor, human epidermal growth factorreceptor-2 (HER-2) status, and the Ki-67 proliferation index were collected for analysis. Quantitative parameters (Ktrans, Ve, Kep), semiquantitative parameters (W-in, W-out, TTP), and apparent diffusion coefficient (ADC) values were compared in relation to breast cancer receptor status and molecular subtypes. Statistical analysis were performed to compare the parameters in the receptor status and molecular subtype groups.Multivariate analysis was performed to explore confounder-adjusted associations, and receiver operating characteristic curve analysis was used to assess the classification performance and calculate thresholds. RESULTS: Younger age (<49.5 years, odds ratio (OR) =0.95, P=0.004), lower Kep (<0.704,OR=0.14, P=0.044),and higher TTP (>0.629 min, OR=24.65, P=0.011) were independently associated with progesterone receptor positivity. A higher TTP (>0.585 min, OR=28.19, P=0.01) was independently associated with estrogen receptor positivity. Higher Kep (>0.892, OR=11.6, P=0.047), lower TTP (<0.582 min, OR<0.001, P=0.004), and lower ADC (<0.719 ×10-3 mm2/s, OR<0.001, P=0.048) had stronger independent associations with triple-negative breast cancer (TNBC) compared to luminal A, and those parameters could differentiate TNBC from luminal A with the highest AUC of 0.811. CONCLUSIONS: Kep and TTP were independently associated with hormone receptor status. In addition, the Kep, TTP, and ADC values had stronger independent associations with TNBC than with luminal A and could be used as imaging biomarkers for differentiate TNBC from Luminal A.

Reduced Cerebral Glucose Uptake in an Alzheimer's Rat Model With Glucose-Weighted Chemical Exchange Saturation Transfer Imaging.

A correlation between the abnormal cerebral glucose metabolism and the progression of Alzheimer's disease (AD) has been found in previous studies, suggesting that glucose alterations may be used to predict the histopathological diagnosis in AD. In this study, we investigated the dynamic changes of cerebral glucose uptake in vivo using MR glucose chemical exchange saturation transfer (glucoCEST) imaging in a rat model of AD with an intracerebroventricular (i.c.v) injection of amyloid Aß-protein (25-35), confirmed by Morris water maze and Nissl staining. In total, 6 rats in the AD group and 6 rats in the control group that were given an injection of sterile normal saline were included. At 28 days after injection, all rats performed a 7.0 T MR exanimation, including glucoCEST, diffusion tensor imaging (DTI) and hippocampus magnetic resonance spectra (MRS), to detect the possible metabolic and structural changes in the rat brain. A significantly elevated brain glucoCEST signal in the brain of AD rats was observed, and a decreased brain glucose uptake was also explored during the progression of glucose infusion compared with those in rats of the control group. In addition, there is a significant positive correlation between glucoCEST enhancement (GCE) and myo-Inosito (Ins) in the AD group and the control group (P < 0.05). A significantly reduced number of neurons in the cortex and hippocampus in AD rats combined with the significantly longer escape and a decreased number of crossings were verified at 28 days after Aß25-35 injection by Nissl staining and Morris water maze, respectively. Our results indicated that an abnormal brain glucose mechanism in AD rats could be detected by glucoCEST imaging, suggesting a new method to explore the occurrence and progress of diabetes-related AD or dementia.