Metabolomic insights into the profile, bioaccessibility, and transepithelial transport of polyphenols from germinated quinoa during in vitro gastrointestinal digestion/Caco-2 cell transport, and their prebiotic effects during colonic fermentation.

The health-promoting activities of polyphenols and their metabolites originating from germinated quinoa (GQ) are closely related to their digestive behavior, absorption, and colonic fermentation; however, limited knowledge regarding these properties hinder further development. The aim of this study was to provide metabolomic insights into the profile, bioaccessibility, and transepithelial transport of polyphenols from germinated quinoa during in vitro gastrointestinal digestion and Caco-2 cell transport, whilst also investigating the changes in the major polyphenol metabolites and the effects of prebiotics during colonic fermentation. It was found that germination treatment increased the polyphenol content of quinoa by 21.91%. Compared with RQ group, 23 phenolic differential metabolites were upregulated and 47 phenolic differential metabolites were downregulated in GQ group. Compared with RQ group after simulated digestion, 7 kinds of phenolic differential metabolites were upregulated and 17 kinds of phenolic differential metabolites were downregulated in GQ group. Compared with RQ group after cell transport, 7 kinds of phenolic differential metabolites were upregulated and 9 kinds of phenolic differential metabolites were downregulated in GQ group. In addition, GQ improved the bioaccessibilities and transport rates of various polyphenol metabolites. During colonic fermentation, GQ group can also increase the content of SCFAs, reduce pH value, and adjust gut microbial populations by increasing the abundance of Actinobacteria, Bacteroidetes, Verrucomicrobiota, and Spirochaeota at the phylum level, as well as Bifidobacterium, Megamonas, Bifidobacterium, Brevundimonas, and Bacteroides at the genus level. Furthermore, the GQ have significantly inhibited the activity of α-amylase and α-glucosidase. Based on these results, it was possible to elucidate the underlying mechanisms of polyphenol metabolism in GQ and highlight its beneficial effects on the gut microbiota.

Hawthorn Proanthocyanidin Extract Inhibits Colorectal Carcinoma Metastasis by Targeting the Epithelial-Mesenchymal Transition Process and Wnt/ß-Catenin Signaling Pathway.

Colorectal carcinoma (CRC) is a major global health concern, with cancer metastasis being the main cause of patient mortality, and current CRC treatments are challenged by drug resistance. Although natural compounds, especially in foods like hawthorn proanthocyanidin extract (HPOE), have good anticancer activity, their effects on CRC metastasis remain unknown. Therefore, our objective was to investigate the impact and potential mechanisms of HPOE on the movement and infiltration of cells in the HCT116 CRC cells. Firstly, scratch-healing experiments confirmed the anti-migratory and anti-invasive capabilities of HPOE. Then, network pharmacology identified 16 possible targets, including MMP-9. Subsequently, RT-qPCR and Western blotting experiments confirmed that HPOE downregulated epithelial-mesenchymal transition-related factors (N-cadherin and MMP-9) and inhibited Wnt/ß-catenin pathway activation. Finally, these results were experimentally validated using the Wnt pathway activator Licl and inhibitor XAV939. It was confirmed that HPOE had a certain inhibitory effect on the activation of the Wnt signaling pathway caused by the activator Licl and could enhance the inhibitory effect of the inhibitor XAV939. Our findings provide a basis for developing functional foods or dietary supplements, especially positioning HPOE as a functional food raw material for adjuvant treatment of CRC, given its ability to inhibit metastasis through the Wnt/ß-catenin pathway.

Artificial intelligence for segmentation and classification of lobar, lobular, and interstitial pneumonia using case-specific CT information.

Background: Pneumonia can be anatomically classified into lobar, lobular, and interstitial types, with each type associated with different pathogens. Utilizing artificial intelligence (AI) to determine the anatomical classifications of pneumonia and assist in refining the differential diagnosis may offer a more viable and clinically relevant solution. This study aimed to develop a multi-classification model capable of identifying the occurrence of pneumonia in patients by utilizing case-specific computed tomography (CT) information, categorizing the pneumonia type (lobar, lobular, and interstitial pneumonia), and performing segmentation of the associated lesions. Methods: A total of 61 lobar pneumonia patients, 60 lobular pneumonia patients, and 60 interstitial pneumonia patients were consecutively enrolled at our local hospital from June 2020 and May 2022. All selected cases were divided into a training cohort (n=135) and an independent testing cohort (n=46). To generate the ground truth labels for the training process, manual segmentation and labeling were performed by three junior radiologists. Subsequently, the segmentations were manually reviewed and edited by a senior radiologist. AI models were developed to automatically segment the infected lung regions and classify the pneumonia. The accuracy of pneumonia lesion segmentation was analyzed and evaluated using the Dice coefficient. Receiver operating characteristic curves were plotted, and the area under the curve (AUC), accuracy, precision, sensitivity, and specificity were calculated to assess the efficacy of pneumonia classification. Results: Our AI model achieved a Dice coefficient of 0.743 [95% confidence interval (CI): 0.657-0.826] for lesion segmentation in the training set and 0.723 (95% CI: 0.602-0.845) in the test set. In the test set, our model achieved an accuracy of 0.927 (95% CI: 0.876-0.978), precision of 0.889 (95% CI: 0.827-0.951), sensitivity of 0.889 (95% CI: 0.827-0.951), specificity of 0.946 (95% CI: 0.902-0.990), and AUC of 0.989 (95% CI: 0.969-1.000) for pneumonia classification. We trained the model using labels annotated by senior physicians and compared it to a model trained using labels annotated by junior physicians. The Dice coefficient of the model's segmentation improved by 0.014, increasing from 0.709 (95% CI: 0.589-0.830) to 0.723 (95% CI: 0.602-0.845), and the AUC improved by 0.042, rising from 0.947 to 0.989. Conclusions: Our study presents a robust multi-task learning model with substantial promise in enhancing the segmentation and classification of pneumonia in medical imaging.

Tracheobronchial Amyloidosis Accompanied with Asthma: A Case Report and a Mini-Review.

Tracheobronchial amyloidosis is a rare disease characterized by amyloid deposits on the tracheal and bronchial tissue. Patients with tracheobronchial amyloidosis are asymptomatic or exhibit symptoms, such as chronic wheezing, dyspnea, and cough, that are common manifestations of other disorders, including asthma. A bronchoscopic tissue biopsy using Congo red staining is the key standard for diagnosing tracheobronchial amyloidosis. Treatment strategies vary depending on the degree of airway obstruction. If the obstruction is significant and the patient is symptomatic, repeated bronchoscopic treatment, including local resection, laser therapy, stent placement, and radiation therapy, is considered a safer and better option. It is often misdiagnosed as asthma, but cases of tracheobronchial amyloidosis accompanied with asthma have not been reported. We report a case of intermittent wheezing, cough for 33 years, and shortness of breath on exertion for 7 years, which had aggravated in the previous 22 days. A pulmonary examination revealed diffuse wheezing. Pulmonary function testing revealed an obstructive ventilation dysfunction. Computerized tomography (CT) imaging revealed circumferential and irregular thickening of the tracheobronchial wall tissue with calcification and atelectasis of the right middle and lower lobe of the lung. Bronchoscopy revealed diffuse thickening of the mucosa of the trachea and bilateral main bronchi, with multiple nodular protuberances and relatively narrow lumens. The bronchial biopsies revealed massive amyloid deposits under the bronchial mucosa. The deposits exhibited a green birefringence under crossed polarized light after Congo red positive staining. The patient received standard treatment for asthma, and remains in good general condition without wheezing. It is not difficult to distinguish tracheobronchial amyloidosis through chest CT examination for patients with wheezing as long as this disease was considered. It was interesting that we present a rarer case of patient with tracheobronchial amyloidosis accompanied with asthma which both can cause symptoms such as wheezing.

Clinical and Radiological Features Between Patients with Stable COPD from Plateau and Flatlands: A Comparative Study.

Background: COPD patients living in Tibet are exposed to specific environments and different risk factors and probably have different characteristics of COPD from those living in flatlands. We aimed to describe the distinction between stable COPD patients permanently residing at the Tibet plateau and those in flatlands. Methods: We conducted an observational cross-sectional study that enrolled stable COPD patients from Tibet Autonomous Region People's Hospital (Plateau Group) and Peking University Third Hospital (Flatland Group), respectively. Their demographic information, clinical features, spirometry test, blood routine and high-resolution chest CT were collected and evaluated. Results: A total of 182 stable COPD patients (82 from plateau and 100 from flatland) were consecutively enrolled. Compared to those in flatlands, patients in plateau had a higher proportion of females, more biomass fuel use and less tobacco exposure. CAT score and frequency of exacerbation in the past year were higher in plateau patients. The blood eosinophil count was lower in plateau patients, with fewer patients having an eosinophil count ≥300/µL. On CT examination, the proportions of previous pulmonary tuberculosis and bronchiectasis were higher in plateau patients, but emphysema was less common and milder. The ratio of diameters of pulmonary artery to aorta ≥1 was more often in plateau patients. Conclusion: Patients with COPD living at Tibet Plateau had a heavier respiratory burden, lower blood eosinophil count, less emphysema but more bronchiectasis and pulmonary hypertension. Biomass exposure and previous tuberculosis were more common in these patients.

Construction and Evaluation of Nomogram for Hematological Indicators to Predict Pathological Response after Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

OBJECTIVE: A retrospective study was conducted by developing prediction models to evaluate the association between hematological indexes, their changes during neoadjuvant chemoradiotherapy (NCRT), and tumor pathological response in patients with locally advanced rectal cancer. METHODS: The clinical data of 202 patients who received NCRT and radical surgery in Sichuan Cancer Hospital were retrospectively analyzed. Univariate and logistic multivariate regression analyses were used to identify hematological indexes with predictive significance. The independent risk factors were imported into the R software, and a nomogram prediction model was developed. The bootstrap method and ROC curve were used to evaluate the discriminative degree of the model. RESULTS: Univariate analysis demonstrated age, tumor diameter, preoperative T, distance from tumor to the anal verge, CEA before NCRT, preoperative CEA, lymphocyte changes, platelet changes, and pathology of rectal cancer after NCRT were associated. Multivariate analysis demonstrated that age, tumor distance from the anus, preoperative CEA, lymphocyte changes, and platelet changes were independent risk factors. The independent risk factors were imported into the R software to construct a nomogram model. The area under the ROC was 0.76, and the slope of the calibration curve of the nomogram was close to 1. CONCLUSION: A low preoperative CEA level, a young age, a high tumor from the anal verge, the maintenance of circulating lymphocyte level, and a decreased platelet level after NCRT are important factors for favorable outcomes after NCRT. Developing a nomogram prediction model with good discrimination and consistency can provide some guidance for predicting pathological responses after NCRT.

Hawthorn Juice Simulation System for Pectin and Polyphenol Adsorption Behavior: Kinetic Modeling Properties and Identification of the Interaction Mechanism.

The interaction between polyphenols and polysaccharides plays an important role in increasing the turbidity stability of fruit juice and improving unpleasant sensory experiences. The binding adsorption behavior between hawthorn pectin (HP) and polyphenols (epicatechin and chlorogenic acid) accorded with the monolayer adsorption behavior driven by chemical action and were better fitted by pseudo-second order dynamic equation and Langmuir model. The HP binding sites (Qm) and adsorption capacity (Qe) to epicatechin were estimated at 75.188 and 293.627 µg/mg HP, respectively, which was about nine and twelve times higher than that of chlorogenic acid. The interaction between HP and polyphenols exhibited higher turbidity characteristics, particle size and lower zeta potential than epicatechin and chlorogenic acid alone. Meanwhile, according to Fourier Transform Infrared Spectroscopy (FT-IR) analysis, it could be speculated that the interaction between HP and polyphenols resulted in chemical combination. Moreover, ΔH < 0 and TΔS < 0, which indicated that the interaction between HP and polyphenols was mainly driven by hydrogen bonds and van der Waals forces.

Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model.

Objective: To explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and establish a nomogram prediction model. Methods: Clinical and surgical data of patients who underwent AR of rectal cancer at Sichuan Cancer Hospital from January 2017 to December 2020 were retrospectively collected. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AL after AR. A nomogram risk prediction model was established based on the selected independent risk factors and the predictive performance of nomogram was evaluated. Results: A 1013 patients undergoing laparoscopic AR were included, of which 67 had AL, with an incidence of 6.6%. Univariate and multivariate logistic regression analyses showed that male gender, tumors distance from the anus verge of ≤ 5cm, tumors distance from the anus verge of 5-10cm, circumferential tumor growth, operation time ≥ 240min, and no diverting stoma were independent risk factors for AL after AR. A nomogram prediction model was established based on these results. The calibration curve showed that the predicted occurrence probability of the nomogram model was in good agreement with the actual occurrence probability. The area under the receiver operating characteristic (ROC) curve was 0.749. Conclusion: The nomogram prediction model based on the independent risk factors of patients undergoing AL after AR can effectively predict the probability of AL.

YAP Promotes Cell Proliferation and Epithelium-Derived Cytokine Expression via NF-κB Pathway in Nasal Polyps.

BACKGROUND: Hippo-Yes-associated protein (YAP) pathway plays an important role in epithelial cell proliferation and inflammation development in chronic rhinosinusitis with nasal polyps (CRSwNP). However, the underlying mechanisms remain unclear. OBJECTIVE: This study intends to investigate the role of YAP and the nuclear factor kappa-B (NF-κB) pathway in cell proliferation and the expression of epithelium-derived cytokines in nasal polyps (NP). METHODS: The expression levels of YAP, TEA domain family member 1 (TEAD1), Ki-67, and NF-κB as well as interleukin (IL-) 33, IL-25 and thymic stromal lymphopoietin (TSLP) in sinonasal mucosa, primary nasal epithelial cells (NPECs), and human nasal epithelial RPMI 2650 cells were detected. NPECs were cultured and treated with verteporfin (VP), YAP shRNA or BAY 11-7082. RESULTS: The hippo pathway effector YAP, Ki-67, p65 NF-κB, and cyclin D1 were significantly increased in NP compared with control mucosa, which was accompanied by overexpression of IL-33, IL-25, and TSLP. Pharmaceutical inhibition of YAP by VP suppressed cell proliferation of RPMI 2650 cells by blocking cell cycle progression at G0/G1 without inducing obvious cell apoptosis. Furthermore, lentiviral transfection-mediated knockdown of hippo pathway activity reduced the expression of IL-33, IL-25, TSLP as well as p65 NF-κB in RPMI 2650 cells. Downregulation of NF-κB pathway with BAY 11-7082 in NPECs could decrease the mRNA level of TSLP, IL-33 and IL-25 accordingly. CONCLUSION: Inhibition of hippo pathway suppressed nasal epithelial cell proliferation and declined the expression of epithelium-derived cytokines via the NF-κB pathway in NPECs.

A feasibility study of pulmonary nodule detection by ultralow-dose CT with adaptive statistical iterative reconstruction-V technique.

PURPOSE: To evaluate the clinical value of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) in the detection of pulmonary nodules in a Chinese population. METHOD: One hundred eighty-eight patients (16.41 ≤ BMI ≤ 29.87 kg/m2) with pulmonary nodules detected on low-dose chest CT (LDCT) underwent local ULDCT at the center of the chosen nodule with a scan length of 3 cm. LDCT was performed using the Assist kV (120/100 kV)/Smart mA mode and at 120 kV/2.8 mAs for ULDCT. After scanning, CT images were reconstructed with ASiR-V 50%. For both scans, nodule diameters were measured and reference standards were established for the presence and types of lung nodules found on LDCT. The sensitivity of ULDCT was compared against the standard, and logistic regression analysis was used to determine the independent predictors for nodule detection. RESULTS: Compared with LDCT (0.93 ±â€¯0.32 mSv), a 89.7% dose decrease was seen with ULDCT, for which the calculated effective dose was 0.096 ±â€¯0.006 mSv (P < 0.001). LDCT showed 188 nodules, including 123 solid and 65 subsolid nodules. The overall sensitivity for nodule detection in ULDCT was 90.4% (170/188), and 98.2% (54/55) for nodules ≥ 6 mm. In multivariate analysis, nodule types and diameters were independent predictors of sensitivity (P < 0.05). However, patients' BMI had no effect on nodule detection (P > 0.05). CONCLUSIONS: ULDCT can be used in the management of pulmonary nodules for people with BMI ≤ 30 kg/m2 at 10% radiation dose of LDCT.

Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.

PURPOSE: To explore the feasibility and performance of machine learning-based radiomics classifier to predict the cell proliferation(Ki-67)in non-small cell lung cancer (NSCLC). METHODS: 245 histopathological confirmed NSCLC patients who underwent CT scans were retrospectively included. The Ki-67 proliferation index (Ki-67 PI) were measured within 2 weeks after CT scans. A lesion volume of interest (VOI) was manually delineated and radiomics features were extracted by MaZda software from CT images. A random forest feature selection algorithm (RFFS) was used to reduce features. Six kinds of machine learning methods were used to establish radiomics classifiers, subjective imaging feature classifiers and combined classifiers, respectively. The performance of these classifiers was evaluated by the receiver operating characteristic curve (ROC) and compared with Delong test. RESULTS: 103 radiomics features were extracted and 20 optimal features were selected using RFFS. Among the radiomics classifiers established by six machine learning methods, random forest-based radiomics classifier achieved the best performance (AUC = 0.776) in predicting the Ki-67 expression level with sensitivity and specificity of 0.726 and 0.661, which was better than that of subjective imaging classifiers (AUC = 0.625, P < 0.05). However, the combined classifiers did not improve the predictive performance (AUC = 0.780, P > 0.05), with sensitivity and specificity of 0.752 and 0.633. CONCLUSIONS: The machine learning-based CT radiomics classifier in NSCLC can facilitate the prediction of the expression level of Ki-67 and provide a novel non-invasive strategy for assessing the cell proliferation.

The hippo pathway effector Yes-associated protein promotes epithelial proliferation and remodeling in chronic rhinosinusitis with nasal polyps.

BACKGROUND: Hippo-Yes-associated protein (YAP) pathway plays an important role in epithelial cell proliferation and development. However, its possible role in chronic rhinosinusitis with nasal polyps (CRSwNP) remains unknown. We aim to investigate it on nasal epithelial proliferation and remodeling in CRSwNP. METHODS: The expressions of hippo pathway components as well as Ki-67 and E-cadherin in the sinonasal mucosa and nasal epithelial cells were analyzed in 14 controls, 14 eosinophilic CRSwNP, and 14 noneosinophilic CRSwNP. Nasal epithelial cells from 6 controls, 6 eosinophilic CRSwNP, and 6 noneosinophilic CRSwNP were cultured and treated with lipopolysaccharide (LPS), Poly(I:C), or a selective YAP inhibitor verteporfin (VP). RESULTS: The hippo pathway components MST1, LATS1/2, YAP, and TEAD1 were increased in both eosinophilic and noneosinophilic CRSwNP, particularly in nasal epithelial cells, along with upregulation of Ki-67 and downregulation of E-cadherin. The mRNA levels of YAP positively correlated with the Ki-67 mRNA levels, and negatively associated with the E-cadherin mRNA levels in polyp tissues and epithelial cells from nasal polyps (NPECs). LPS and Poly(I:C) upregulated the YAP expression in nasal epithelial cells accompanied by increased TEAD1 and Ki-67 expression. Conversely, YAP inhibition by VP decreased TEAD1 and Ki-67 expression in NPECs. CONCLUSIONS: Hippo pathway components are abnormally upregulated in NPECs, and its effector YAP promotes nasal epithelial cells proliferation and remodeling in CRSwNP. It provides a rationale to explore inhibition of YAP as a novel therapeutic strategy for reducing the epithelial proliferation and remodeling in CRSwNP.

[Development of a radiomics signature to predict Ki-67 expression level in non-small cell lung cancer].

OBJECTIVE: To develop a radiomics signature based on CT image features to estimate the expression level of Ki-67 in non-small cell lung cancer (NSCLC).
 Methods: A total of 108 NSCLC patients, who underwent non-enhanced and contrast-enhanced CT scan in our hospital from January 2014 to November 2017, were retrospectively analyzed. They were confirmed by histopathological examination and undergone Ki-67 expression level test within 2 weeks after CT examination. The non-enhanced and contrast-enhanced CT three-dimensional structural images of the lesions were manually delineated by MaZda software, and the texture features of the region of interest were extracted. Combination of feature selection and classification methods were used to build radiomics signatures, and the classification were assessed using misclassification rates. The MaZda software provides texture feature selection methods including mutual information (MI), Fisher coefficients (Fisher), classification error probability combined with average correlation coefficients (POE+ACC), and Fisher+POE+ACC+MI (FPM), and texture feature analysis including raw data analysis (RDA), principal component analysis (PCA), linear classification analysis (LDA) and nonlinear classification analysis (NDA).
 Results: Among the 108 patients, 50 cases were at high levels of Ki-67 expression and 58 cases were at low levels of Ki-67 expression, respectively. The differences of gender, age and pathological type between the two groups were statistically significant (P<0.05). The radiomics signature built by FPM feature selection combined with NDA feature analysis based on non-enhanced CT images achieved the best performance for predicting the level of Ki-67 with a misclassification rate of 14.81%. However, radiomics signature based on contrast-enhanced CT images did not reduce the misclassification rate.
 Conclusion: The radiomics signature based on conventional CT image texture features is helpful to predict the expression of Ki-67 in NSCLC lesions, which can provide a non-invasive technique for assessing the invasiveness and prognosis for NSCLC.

Comparative Study of Recessive Spherical Headed Silicone Intubation and Endonasal Dacryocystorhinostomy under Nasal Endoscopy for Nasolacrimal Duct Obstruction.

Between July 2014 and November 2015, we compared the curative effects and cost-effectiveness of two kinds of nasal endoscopic surgery for nasolacrimal duct obstruction (NLDO) in a single-centre, two-armed clinical trial with a 1-year follow-up. We included two groups: a recessive spherical headed silicone intubation (RSHSI) group and an endonasal dacryocystorhinostomy (En-DCR) group; both received nasal endoscopy. Patients were recruited from the Otorhinolaryngology and Ophthalmology departments. The main outcome measures were epiphora improvement (classified as cure, effective, or invalid), cost-effectiveness, visual analogue scale (VAS) intraoperative pain score, bleeding volume, operating time, hospitalisation time, total cost, and VAS postoperative epiphora score. No significant group difference was identified in postoperative epiphora VAS scores (P > 0.050) or success rate (P = 0.406). However, average VAS intraoperative pain score, operating time, bleeding volume, hospitalisation time and total cost in the RSHSI group were clearly lower to those in the En-DCR group (P = 0.000). In conclusion, RSHSI under nasal endoscopy can provide similar treatment outcomes to En-DCR. RSHSI has advantages including minimal invasiveness, reduced risk, shorter duration of surgery and hospitalisation, reduced intraoperative discomfort, and lower financial burden, which is more acceptable to patients. Thus, RSHSI may be the preferred option for NLDO.

Diagnostic value of gadobutrol versus gadopentetate dimeglumine in enhanced MRI of brain metastases.

PURPOSE: To compare gadobutrol and gadopentetate dimeglumine (Gd-DTPA) contrast-enhanced magnetic resonance imaging (MRI) at 3T for visualizing brain metastases. MATERIALS AND METHODS: The present randomized study included 60 consecutive patients with known or suspected brain metastases from systemic malignancies. Two enhanced cerebral MR scans were performed in each patient within an interval of 2-5 days using different contrast agents (gadobutrol or Gd-DTPA) at 3T. The dose of the contrast agents (0.1 mmol/kg Gd) was also identical. The axial T1 FLAIR images at 3, 7, and 10 minutes after the injection of the contrast agent were obtained for evaluation. Two experienced radiologists performed subjective evaluation of the image quality, made the choice of the optimal images, and performed an objective evaluation including: signal-to-noise ratio (SNR) of the brain metastases, contrast-to-noise ratio (CNR), contrast enhancement (CE), contrast-to-brain ratio (CBR), and contrast enhancement ratio (CER) of the brain metastases. RESULTS: Subjective evaluation showed that at 3, 7, and 10 minutes gadobutrol elicited higher scores (margin score: 3.56 ± 0.74 vs. 3.33 ± 0.93, 3.68 ± 0.57 vs. 3.45 ± 0.81, 3.58 ± 0.71 vs. 3.43 ± 0.76; interior score: 2.83 ± 0.42 vs. 2.63 ± 0.61, 2.86 ± 0.38 vs. 2.73 ± 0.52, 2.80 ± 0.42 vs. 2.69 ± 0.53; and overall score: 4.42 ± 0.98 vs. 4.09 ± 1.19, 4.57 ± 0.75 vs. 4.26 ± 1.05, 4.48 ± 0.83 vs. 4.21 ± 1.03, respectively) in displaying the details and overall lesions than Gd-DTPA (repeated measures analysis of variance [ANOVA], margin score: P = 0.001, < 0.0001, 0.006; interior score: P < 0.0001, 0.004, 0.009; and overall score: P = 0.001, < 0.0001, < 0.0001, respectively). Subjective optimal image evaluation showed that the percentage of image assessed as "gadobutrol was better than Gd-DTPA (41.2-44.1%)" was greater than that assessed as "Gd-DTPA was better than gadobutrol (5.9-26.5%)." Objective evaluation showed that at 3, 7, and 10 minutes the SNR (214.17 ± 85.70 vs. 199.57 ± 85.08, 214.80 ± 86.03 vs. 199.19 ± 84.74, and 213.83 ± 82.46 vs. 193.68 ± 79.59, respectively), CNR (68.64 ± 50.18 vs. 57.88 ± 51.06, 75.42 ± 53.19 vs. 63.74 ± 53.91, and 77.13 ± 51.86 vs. 63.21 ± 51.71, respectively), CE (101.76 ± 63.31 vs. 87.61 ± 64.85, 99.85 ± 61.56 vs. 85.08 ± 64.98, and 100.33 ± 58.63 vs. 82.73 ± 61.73, respectively), CBR (0.48 ± 0.32 vs. 0.40 ± 0.33, 0.54 ± 0.34 vs. 0.46 ± 0.35, and 0.56 ± 0.34 vs. 0.47 ± 0.34, respectively), and CER (0.99 ± 0.69 vs. 0.88 ± 0.81, 0.97 ± 0.68 vs. 0.86 ± 0.84, and 0.98 ± 0.65 vs. 0.85 ± 0.80, respectively) were all higher when using gadobutrol compared with Gd-DTPA in the enhanced MR (repeated measures ANOVA, all P < 0.0001). On Gd-DTPA enhanced images, 289, 292, and 292 lesions at 3, 7, and 10 minutes were detected by the two radiologists, while 295, 301, and 301 lesions were detected on gadobutrol-enhanced images, respectively. CONCLUSION: Using a 3T T1 FLAIR sequence, gadobutrol (0.1 mmol/kg body weight)-enhanced MR resulted in more conspicuous brain metastases, and more metastases compared with the same dose of Gd-DTPA. A delay time of 7 minutes for postcontrast MRI in patients with brain metastases is suggested in clinical practice. LEVEL OF EVIDENCE: 2 J. MAGN. RESON. IMAGING 2017;45:1827-1834.