Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate.

BACKGROUND: There is an overlap comparing transition zone prostate cancer (TZ PCa) and benign prostatic hyperplasia (BPH) on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI), creating additional challenges for assessment of TZ tumors on MRI. PURPOSE: To evaluate whether amide proton transfer-weighted (APTw) imaging provides new diagnostic ideas for TZ PCa. STUDY TYPE: Prospective. POPULATION: A total of 51 TZ PCa patients (age, 49-89), 44 stromal BPH (age, 57-92), and 45 glandular BPH patients (age, 56-92). FIELD STRENGTH/SEQUENCE: A 3 T; T2WI turbo spin echo (TSE), quantitative T2*-weighted imaging, DWI echo planar imaging, 3D APTw TSE. ASSESSMENT: Differences in APTw, apparent diffusion coefficient (ADC), and T2* among three lesions were compared by one-way analysis of variance (ANOVA). Regions of interest were drawn by two radiologists (X.Q.Z. and X.Y.Q., with 21 and 15 years of experience, respectively). STATISTICAL TESTS: Multivariable logistic regression analyses; ANOVA with post hoc testing; receiver operator characteristic curve analysis; Delong test. Significance level: P < 0.05. RESULTS: APTw among TZ PCa, stromal BPH, and glandular BPH (3.48% ± 0.83% vs. 2.76% ± 0.49% vs. 2.72% ± 0.45%, respectively) were significantly different except between stromal BPH and glandular BPH (P > 0.99). Significant differences were found in ADC (TZ PCa 0.76 ± 0.16 × 10-3  mm2 /sec vs. stromal BPH 0.91 ± 0.14 × 10-3  mm2 /sec vs. glandular BPH 1.08 ± 0.18 × 10-3  mm2 /sec) among three lesions. APTw (OR = 12.18, 11.80, respectively) and 1/ADC (OR = 703.87, 181.11, respectively) were independent predictors of TZ PCa from BPH and stromal BPH. The combination of APTw and ADC had better diagnostic performance in the identification of TZ PCa from BPH and stromal BPH. DATA CONCLUSION: APTw imaging has the potential to be of added value to ADC in differentiating TZ PCa from BPH and stromal BPH. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Amide Proton Transfer MRI Could Be Used to Evaluate the Pathophysiological Status of White Matter Hyperintensities.

BACKGROUND: The pathophysiology of white matter hyperintensities (WMH) remains unclear, investigations of amide proton transfer (APT) signals in WMH disease may provide relevant pathophysiological information. PURPOSE: To evaluate the APT signals differences and heterogeneity of WMH and adjacent normal-appearing white matter (NAWM) at different Fazekas grades and different locations. STUDY TYPE: Prospective. POPULATION: In all, 180 WMH patients (age, 40-76; male/female, 77/103) and 59 healthy controls (age, 42-70; male/female, 23/36). FIELD STRENGTH/SEQUENCE: A 3 T; 3D fluid-attenuated inversion recovery (FLAIR), 3D APT-weighted (APTw). ASSESSMENT: The mean APTw values (APTwmean ) and the APTw signals heterogeneity (APTwmax-min ) among different grades WMH and NAWM and the APTwmean of the same grade deep WMH (DWMH) and paraventricular WMH (PWMH) were calculated and compared. Regions of interests were delineated on WMH lesions, NAWM and healthy white matter. STATISTICAL TESTS: One-way analysis of variance (ANOVA); independent sample t test; Chi-square test. Significance level: P < 0.05. RESULTS: APTwmean among different grade WMH (from grade 0 to 3, 0.58 ± 0.14% vs. 0.29 ± 0.23% vs. 0.37 ± 0.24% vs. 0.61 ± 0.22%, respectively) were significantly different except between grade 1 and 2 (P = 0.27) and between grade 0 and 3 (P = 0.97). The differences in APTwmean between WMH and NAWM were significant (WMH vs. NAWM from grade 1 to 3, 0.29% ± 0.23% vs. 0.55% ± 0.27%; 0.37% ± 0.24% vs. 0.59% ± 0.22%; 0.61% ± 0.22% vs. 0.42% ± 0.24%, respectively). Lower APTwmean values were found only in grade 3 NAWM than other grades NAWM and controls. The APTwmax-min values of grade 1-3 WMH (0.38% ± 0.27% vs. 0.51% ± 0.31% vs. 0.67% ± 0.34%, respectively) were significantly different. Higher APTmean values were found only in grade 2 PWMH (0.47% ± 0.22% vs. 0.32% ± 0.24%). DATA CONCLUSION: Significant differences of APT signals were found in WMH of different Fazekas grades and different locations. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Derivation and application of a parameter for denitrification rates in the Taihu Lake model based on an isotope-labeled denitrification experiment.

In recent years, the total nitrogen concentration in Taihu Lake has decreased significantly. Denitrification, as the main nitrogen removal process, is the key reason for the decrease. Here, the denitrification parameter values in the Environmental Fluid Dynamic Code (EFDC) model were calculated based on isotope-labeled denitrification experiment instead of selecting the recommended values directly. This study further focused on EFDC denitrification parameter derivation with an experimental denitrification rate (Dtot) to reduce simulation errors. According to the EFDC nitrate deposition flux mechanism, the conversion equation between the denitrification rate of the first sediment layer ([Formula: see text]) in EFDC and Dtot was successfully derived. The results revealed a linear correlation between [Formula: see text] and (Dtot)1/2. The [Formula: see text] values of sampling points ranged from 0.25 to 0.27 m·day-1, within the range of model parameters. After substituting [Formula: see text] into the Taihu Lake EFDC model, the average percentage bias and determination coefficient of total nitrogen were 16.25% and 0.87, respectively. The average total nitrogen concentration reduction caused by denitrification at water quality calibration points ranged from 0.027 to 0.305 mg·L-1.

Aberrant baseline brain activity and disrupted functional connectivity in patients with vascular cognitive impairment due to cerebral small vessel disease.

Objective: This study aims to examine the alterations in aberrant brain activity and network connectivity between individuals with mild and major vascular cognitive impairment (VCI). Materials and methods: A total of 114 patients with cerebral small vessel disease (CSVD) were included in this study, comprising 61 individuals with mild VCI (mean age, 55.7 ± 6.9 years; male, 42.6%) and 53 cases with major VCI (mean age, 57.6 ± 5.5 years; male, 58.5%). Additionally, 53 age-, gender-, and education-matched healthy subjects were recruited as normal controls (NC) (mean age, 54.9 ± 7.9 years; male, 52.9%). All participants underwent neuropsychological assessments and magnetic resonance imaging scans. One-way analysis of variance was used to compare fractional amplitude of low-frequency fluctuation (fALFF) values among the three groups. Two-sample t-tests were conducted to assess functional connectivity matrices between different groups for each connection. Moreover, mediation analyses were performed to explore the mediating effect of aberrant brain activity on the relationship between cognitive impairment and CSVD total burden. Results: VCI patients exhibited aberrant brain activity in regions such as the right thalamus (THA_R), right cuneus (CUN_R), left postcentral gyrus (PoCG_L), right postcentral gyrus (PoCG_R), right median cingulate, paracingulate gyri (PCG_R), and left precuneus (PCUN_L). Reduced positive functional connectivity was predominantly observed among nodes including PCUN_L, CUN_R, PoCG_L, PoCG_R, right posterior cingulate (PCG_R), and left occipital gyrus (IOG_L) in VCI patients. The aberrant baseline brain activity and disrupted brain network were more pronounced with worsening cognitive function. Increased fALFF values in THA_R, CUN_R, and PoCG_L mediated cognitive impairment in CSVD patients. Conclusion: Abnormal brain activities in THA_R, CUN_R, and PoCG_L, along with their associated abnormal functional connections, play a significant role in VCI. The study revealed a progressive increase in aberrant brain activity and network connectivity with advancing stages of VCI.

Hippocampal amide proton transfer values are associated with cerebral small vessel disease imaging markers and total burden: a community-based cross-sectional study.

Background: Neurodegeneration has been suggested to be associated with cerebral small vessel disease (CSVD). The association between different CSVD imaging markers and the extent of neurodegeneration could be indirectly confirmed by examining the relationship between CSVD imaging markers and the hippocampal amide proton transfer (APT) values. The associations between hippocampal APT values with CSVD imaging markers and CSVD total load need to be further validated. The aim of this study was to investigate potential variations in hippocampal APT values among individuals with CSVD imaging markers and varying degrees of CSVD total burden. Methods: A cross-sectional study (retrospective analysis of prospectively-acquired data) was conducted at Nanxishan Hospital of Guangxi Zhuang Autonomous Region. From May 2020 to June 2021, 165 individuals (age, 40-76 years; male/female, 103/62) were included in this study. The inclusion criteria for the participants were as follows: The presence of lacunar infarction (LI), and/or cerebral microbleed (CMB); moderate-to-severe enlarged perivascular space (EPVS) (>20); deep white matter hyperintensity (WMH) > Fazekas 2 or periventricular WMH > Fazekas. The exclusion criteria comprised the following: History of craniocerebral operation; Cases with significant pathology incidentally identified during magnetic resonance (MR) scan; Drug or alcohol abuse. The differences of hippocampal APT values between CSVD imaging makers presence or absence groups and different CSVD total burden groups were compared using independent t-test and one-way analysis of variance (ANOVA). The correlations between APT values and CSVD imaging markers were analyzed using Pearson correlation analysis. A mediation analysis model was used to investigate the mediating effect of the hippocampal APT values in the association between CSVD total loads and Montreal Cognitive Assessment (MoCA) score was assessed. Results: The hippocampal APT values among different CSVD total load groups were significantly different (P<0.001). The hippocampal APT values were significantly different between the imaging markers presence and absence groups. The P values for the LI, WMH EPVS, and CMB presence or absence groups were <0.001, <0.001, 0.034, and 0.002, respectively. The hippocampal APT values were significantly correlated with CMB (P<0.01), LI (P<0.01) and WMH (P<0.01). The mediation models demonstrated that the APT values of the hippocampus partially mediated the association between CSVD total load and MoCA score, the proportion of mediation attributable was calculated as 17.50%. Conclusions: Hippocampal APT values were associated with CSVD imaging markers and total burden. Hippocampal APT values may serve as a biomarker for the early detection of neurodegeneration in CSVD patients.

Amide proton transfer imaging has added value for predicting extraprostatic extension in prostate cancer patients.

Background: Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans. Purpose: The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE. Method: This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed. Results: APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10-3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively. Data conclusion: Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity.

Comparison and combination of amide proton transfer magnetic resonance imaging and the apparent diffusion coefficient in differentiating the grades of prostate cancer.

Background: More effective risk stratification of prostate cancer (PCa) than that possible with current methods can reduce undertreatment and guard against overtreatment. The aim of this study is to validate the differences and combined effects of amide proton transfer (APT) imaging and apparent diffusion coefficient (ADC) in discriminating the PCa grade group (GG) ≤2 from GG ≥3 PCa. Methods: This is an ongoing prospective study conducted in the radiology department of Nanxishan Hospital of Guangxi Zhuang Autonomous Region. Patients pathologically diagnosed with PCa were enrolled consecutively according to the eligibility criteria. A total of 180 patients (age range, 42-92 years) were included in this study. Using histopathology as the reference standard, we placed 71 cases in GG ≤2 (mean age 67.03±8.696 years) and 109 cases in GG ≥3 (age 69.60±9.638 years). Magnetic resonance imaging (MRI) parameters, including APT and ADC values, were analyzed using an independent samples t-test and binary logistic regression analysis stratified with GG. Receiver operating characteristic curve was used to analyze the diagnostic performance for different parameters distinguishing GG ≤2 and GG ≥3. Results: APT [odds ratio (OR) for the transitional zone (TZ) PCa: 3.20, 95% CI: 1.14-8.98, P=0.02; OR for the peripheral zone (PZ) PCa: 86.32, 95% CI: 13.24-562.88, P=0.003] and ADC values (OR for TZ PCa: 89.79; 95% CI: 2.85-2,827.99, P=0.01; OR for PZ PCa: 39.92; 95% CI: 3.22-494.18, P=0.004) were independent predictors that differentiated the GG of patients. The sensitivity and specificity of the APT values were 61.1% and 81.0%, respectively, while the sensitivity and specificity of the ADC values were 83.3% and 61.9%, respectively. The optimal cutoff value of APT was 3.35% and which of ADC was 1.25×10-3 mm2/s in TZ origin PCa. At the optimal cutoff values of 3.31% (APT) and 0.79×10-3 mm2/s (ADC) in PZ PCa, the sensitivity and specificity of the APT values were 74.0% and 83.6%, respectively, while the sensitivity and specificity of the ADC values were 94.0% and 53.4%, respectively. The area under the curve of the combination of APT and ADC was significantly higher than either of APT or ADC alone in Delong test (TZ: P=0.002 and P=0.020; PZ: P=0.033 and P<0.001). Conclusions: APT and ADC have complementary effects on the sensitivity and specificity for identifying different PCa GGs. A combination model of APT and ADC could improve the diagnostic efficacy of PCa differentiation.

Textural features of the frontal white matter could be used to discriminate amnestic mild cognitive impairment patients from the normal population.

OBJECTIVE: We aim to develop a radiomics model based on 3-dimensional (3D)-T1WI images to discriminate amnestic mild cognitive impairment (aMCI) patients from the normal population by measuring changes in frontal white matter. METHODS: In this study, 126 patients with aMCI and 174 normal controls (NC) were recruited from the local community. All subjects underwent routine magnetic resonance imaging examination (including 3D-T1WI ). Participants were randomly divided into a training set (n = 242, aMCI:102, NC:140) and a testing set (n = 58, aMCI:24, NC:34). Texture features of the frontal lobe were extracted from 3D-T1WI images. The least absolute shrinkage and selection operator (LASSO) was used to reduce feature dimensions and develop a radiomics signature model. Diagnostic performance was assessed in the training and testing sets using the receiver operating characteristic (ROC) curve analysis. The area under the ROC curve (AUC), sensitivity, and specificity were also calculated. The efficacy of the radiomics model in discriminating aMCI patients from the normal population was assessed by decision curve analysis (DCA). RESULTS: A total of 108 frontal lobe texture features were extracted from 3D-T1WI images. LASSO selected 58 radiomic features for the final model, including log-sigma (n = 18), original (n = 8), and wavelet (n = 32) features. The performance of radiomic features extracted from 3D T1 imaging for distinguishing aMCI patients from controls was: in the training set, AUC was 1.00, and the accuracy, sensitivity, and specificity were 100%, 98%, and 100%, respectively. In the testing set, AUC was 0.82 (95% CI:0.69-0.95), and the accuracy, sensitivity, and specificity were 69%, 92%, and 55%, respectively. The DCA demonstrated that the model had favorable clinical predictive value. CONCLUSIONS: Textural features of white matter in the frontal lobe showed potential for distinguishing aMCI from the normal population, which could be a surrogate protocol to aid aMCI screening in clinical setting.

Spectral computed tomography parameters could be surrogate imaging markers to detect early perfusion changes in diabetic kidneys.

Background: Kidney microvasculopathy is the baseline pathophysiological feature of diabetic kidney disease (DKD). We aimed to evaluate the spectral computed tomography (CT) parameters for detecting renal perfusion changes among diabetic patients. Methods: From August 2020 to June 2022, 34 patients (age, 57.7±10.7 years; male, 20) clinically diagnosed with type 2 diabetes mellitus (DM) and 19 DM-free individuals (age, 48.1±16.9 years; male, 12) were selected for analysis. The series participants formed the DM group and control group, respectively. Spectral parameters, including effective atomic number (Zeff), iodine density (ID), normalized iodine density (NID) and the slope of the energy spectrum curves (λ), between the 2 groups were analyzed using independent samples t-test. Receiver operator characteristic (ROC) curves were used to evaluate the diagnostic performance of spectral parameters for detecting renal perfusion changes. Results: The results indicate that in both cortical and medullary phases, the values of Zeff, ID, NID, and λ40-70 for the renal cortex of the DM group were significantly higher than those in the control group (P<0.05). In the cortex phase, the diagnostic efficacy of cortical spectral CT parameters discriminating DM patients from controls was as follows: the area under ROC curve (AUC) of ID value was 0.816 [95% confidence interval (CI): 0.679-0.921] at the optimal cutoff value 4.14, the AUC of Zeff value was 0.800 (95% CI: 0.668-0.901) at the optimal cutoff value 9.26, the AUC of λ40-70 value was 0.822 (95% CI: 0.675-0.918) at the optimal cutoff value 8.26, and the AUC of NID value was 0.851 (95% CI: 0.684-0.926) at the optimal cutoff value 0.37. In medullary phase: the AUC of ID value was 0.769 (95% CI: 0.617-0.846) at the optimal cutoff value 5.08, the AUC of Zeff value was 0.763 (95% CI: 0.614-0.837) at the optimal cutoff value 9.58, the AUC of λ40-70 value was 0.766 (95% CI: 0.617-0.839) at the optimal cutoff value 10.07, and the AUC of NID value was 0.79 (95% CI: 0.623-0.855) at the optimal cutoff value 1.37. Conclusions: Spectral CT could serve as an alternative protocol for the early identification of kidney injury in diabetic patients.

Amide proton transfer could be a surrogate imaging marker for predicting vascular cognitive impairment.

BACKGROUD: Emerging evidence suggests an overlap in the underlying pathways contributing to both cerebral small vessel disease (CSVD) and the neurodegenerative disease. Studies investigating the progression of CSVD should incorporate markers that reflect neurodegenerative lesions. OBJECTIVE: We aim to investigate whether Amide proton transfer (APT) can serve as a potential marker for reflecting vascular cognitive impairment (VCI). METHOD: Participants were categorized into one of three groups based on their Montreal Cognitive Assessment (MoCA) scores: normal control group (age,54.9 ± 7.9; male, 52.9%), mild cognitive impairment (MCI) group (age,55.7 ± 6.9; male, 42.6%), or vascular dementia (VaD) group (age,57.6 ± 5.5, male, 58.5%). One way analysis of variance was performed to compare the demographic and APT variables between groups. Multiple logistic regression analysis wwas constructed to examine the relationship between APT values and VCI grouping. A hierarchical linear regression model was employed to examine the associations between patients' demographic factors, imaging markers, APT values, and MoCA. RESULTS: The APT values of frontal white matter, hippocampus, amygdala, and thalamus were significantly different among different groups (p < 0.05). The APT values of frontal white matter, amygdala, and thalamus indicate a significant positive effect on MCI grouping. the APT values of frontal white matter, amygdala, and thalamus indicate a significant positive effect on VaD grouping. The demographic data, CSVD imaging markers and APT values can account for 5.1%, 20.1% and 27.7% of the variation in MoCA, respectively. CONCLUSION: APT imaging can partially identifying and predicting the occurrence of VCI.

Parameters of Dual-layer Spectral Detector CT Could be Used to Differentiate Non-Small Cell Lung Cancer from Small Cell Lung Cancer.

BACKGROUND AND OBJECTIVE: Differentiating non-small cell lung cancer (NSCLC) from small cell lung cancer (SCLC) remains a substantial challenge. This study aimed at evaluating the performance of dual-layer spectral detector CT (DLCT) in differentiating NSCLC from SCLC. METHODS: Spectral images of 247 cancer patients confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP), including 197 cases of NSCLC and 50 cases of SCLC. Effective atomic number (Z-eff), Spectral CT-Mono Energetic (MonoE [40keV~90keV]), iodine density (ID) and thoracic aorta iodine density (IDaorta) in contrast-enhanced images were measured and compared between the SCLC and NSCLC subgroups of tumors. The slope of the spectral curve (λ, interval of 10 keV) and normalized iodine density (NID) were also calculated between the SCLC and NSCLC. Through the statistical analysis, the diagnostic efficiency of each spectral parameter was calculated, and the difference in their efficiency was analyzed. RESULTS: Both in NSCLS and SCLC, all parameters in VP were significantly higher than those in AP (p<0.001), except for λ90. There were significant differences in all spectral parameters between NSCLS and SCLC, both in AP and VP (p < 0.001). Except for VP-λ90, there was no significant difference in ROC curves of all spectral parameters. VP-NID exhibited the best diagnostic performance with an AUC value of 0.917 (95%[CI]: 0.870~0.965), sensitivity and specificity of 92.9% and 80%, and a diagnostic threshold of 0.217. CONCLUSION: All parameters of DLCT have high diagnostic efficiency in differentiating NSCLC from SCLC except for VP-λ90, and VP-NID has the highest diagnostic efficiency.

Diagnostic value of dual-layer spectral detector CT in differentiating lung adenocarcinoma from squamous cell carcinoma.

Background and objective: The pathological type of non-small cell lung cancer is considered to be an important factor affecting the treatment and prognosis. The purpose of this study was to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in determining efficacy to distinguish adenocarcinoma (AC) and squamous cell carcinoma (SC), and their combined diagnostic efficacy was also analyzed. Methods: This is a single-center prospective study, and we collected 70 patients with lung SC and 127 patients with lung AC confirmed by histopathological examination. Morphological parameters, plain scan CT value, biphasic enhanced CT value, and spectral parameters were calculated. The diagnostic efficiency of morphological parameters, spectral parameters, and spectral parameters combined with morphological parameters was obtained by statistical analysis. Results: In univariate analysis, seven morphological CT features differed significantly between SC and AC: tumor location (distribution), lobulation, spicule, air bronchogram, vacuole sign, lung atelectasis and/or obstructive pneumonia, and vascular involvement (all p < 0.05). In the arterial phase and the venous phase, the spectral parameters of AC were higher than those of SC (AP-Zeff: 8.07 ± 0.23 vs. 7.85 ± 0.16; AP-ID: 1.41 ± 0.47 vs. 0.94 ± 0.28; AP-NID: 0.13 ± 0.04 vs. 0.09 ± 0.03; AP-λ: 3.42 ± 1.10 vs. 2.33 ± 0.96; VP-Zeff: 8.26 ± 0.23 vs. 7.96 ± 0.16; VP-ID: 1.18 ± 0.51 vs. 1.16 ± 0.30; VP-NID: 0.39 ± 0.13 vs. 0.29 ± 0.08; VP-λ: 4.42 ± 1.28 vs. 2.85 ± 0.72; p < 0.001). When conducting multivariate analysis combining CT features and DLCT parameters with the best diagnostic efficacy, the independent predictors of AC were distribution on peripheral (OR, 4.370; 95% CI, 1.485-12.859; p = 0.007), presence of air bronchogram (OR, 5.339; 95% CI, 1.729-16.484; p = 0.004), and presence of vacuole sign ( OR, 7.330; 95% CI, 1.030-52.184; p = 0.047). Receiver operating characteristic curves of the SC and AC showed that VP-λ had the best diagnostic performance, with an area under the curve (AUC) of 0.864 and sensitivity and specificity rates of 85.8% and 74.3%, respectively; the AUC was increased to 0.946 when morphological parameters were combined, and sensitivity and specificity rates were 89.8% and 87.1%, respectively. Conclusion: The quantitative parameters of the DLCT spectrum are of great value in the diagnosis of SC and AC, and the combination of morphological parameters and spectral parameters is helpful to distinguish SC from AC.

Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading.

Background: It is difficult to distinguish the pathological grade of lung adenocarcinoma (LUAD) with traditional computed tomography (CT). The aim of this study was to assess tumor differentiation by dual-layer spectral detector CT combined with morphological parameters. Methods: In this prospective study, a total of 67 patients with pathologically diagnosed LUAD were enrolled: 39 patients in the well- and moderately-differentiated group (14 and 25 patients, respectively) and 28 patients in the poorly-differentiated group. Morphological parameters, non-enhanced CT number, double-enhanced CT number, effective atomic number, monoenergetic CT images (40 and 70 keV), iodine density, and thoracic aorta iodine density of tumors were measured. The slope of the spectral curve and normalized iodine density were calculated. The diagnostic efficiency of the spectral parameters alone, and the combined spectral and morphological parameters were obtained by statistical analysis. Results: The morphological signs of LUAD (the vessel convergence sign, bronchus encapsulated air sign, and liquefactive necrosis) were higher in the poorly-differentiated group than in the well-moderately-differentiated group (57.1% vs. 30.8%, 40.0%; 60.7% vs. 28.2%, 32.0%; 64.3% vs. 28.2%, 24.0%; all P<0.05). There were significant differences in normalized iodine density (arterial phase: 0.10±0.04 vs. 0.12±0.05, 0.13±0.04; venous phase: 0.31±0.07 vs. 0.39±0.17, 0.40±0.17) among the poorly-differentiated group and moderately-differentiated group as well as the well-differentiated group (all P<0.05). Receiver operating characteristic (ROC) curves of the poorly-differentiated group and well-moderately-differentiated group showed that the normalized iodine density had the best diagnostic efficiency in the arterial phase, with an area under the curve (AUC) of 0.817, sensitivity of 92.9%, and specificity of 82.1% (P<0.001). The AUC increased to 0.916 when the morphological parameters were included, and sensitivity and specificity were 96.4% and 82.1% (P<0.001), respectively. Conclusions: The parameters of dual-layer spectral detector CT can help discriminate the pathological grade of LUAD. Among the spectral parameters, the normalized iodine density in the arterial phase has the best diagnostic efficiency, and the combination of spectral and morphological parameters improves the pathological grading of LUAD.

Prevalence and Consequences of Cerebral Small Vessel Diseases: A Cross-Sectional Study Based on Community People Plotted Against 5-Year Age Strata.

Purpose: To study the variation tendency of cerebral small vessel disease (CSVD) imaging markers and total burden with aging and to research the relationship between aging, CSVD markers and cognitive function. Methods: Participants in local urban communities were recruited for neuropsychological and magnetic resonance imaging assessments. Montreal Cognitive Assessment (MoCA), Mini-mental State Examination (MMSE), Number Connection Test A (NCT-A) and Digital Symbol Test (DST) were adopted as neuropsychological scale. Age was stratified at 5-year intervals, and the variation tendency of imaging markers and variables of neuropsychological scales in different age groups was studied. We further studied the relationship between aging, image markers and neuropsychological scales by multi-linear regression. Results: Finally, a total of 401 stroke-free participants (age, 54.83±7.74y; 45.9% were male) were included in the present analysis. With the increase of age, the incidence of imaging markers of CSVD were increased with aging except cerebral microbleeds. The performance results of NCT-A and DST were significant difference in 6 age groups (P < 0.001). In addition, linear decline of the neuropsychological function reflected by NCT-A and DST variables was observed. Linear regression found that age was an independent factor affecting the neuropsychological function reflected by NCT-A and DST variables, and the standard correction coefficients among different age groups increased gradually with age. In addition, brain atrophy is an independent factor affecting neuropsychological variables (odds ratio: -2.929, 95% CI: [-5.094 to -0.765]). There was no correlation between the number of neuroimaging markers and neuropsychological variables after full adjustment. Conclusion: There are many CVSD markers even in younger people, the incidence rate and CVSD marker numbers increase with age. Aging and CSVD may eventually affect cognitive function through brain atrophy.

Amide Proton Transfer-Weighted MRI Might Help Distinguish Amnestic Mild Cognitive Impairment From a Normal Elderly Population.

Objectives: To evaluate whether 3D amide proton transfer weighted (APTw) imaging based on magnetization transfer analysis can be used as a novel imaging marker to distinguish amnestic mild cognitive impairment (aMCI) patients from the normal elderly population by measuring changes in APTw signal intensity in the hippocampus and amygdala. Materials and Methods: Seventy patients with aMCI and 74 age- and sex-matched healthy volunteers were recruited for routine MRI and APT imaging examinations. Magnetic transfer ratio asymmetry (MTRasym) of the amide protons (at 3.5 ppm), or APTw values, were measured in the bilateral hippocampus and amygdala on three consecutive cross-sectional APT images and were compared between the aMCI and control groups. The independent sample t-test was used to evaluate the difference in APTw values of the bilateral hippocampus and amygdala between the aMCI and control groups. Receiver operator characteristic analysis was used to assess the diagnostic performance of the APTw. The paired t-test was used to assess the difference in APTw values between the left and right hippocampus and amygdala, in both the aMCI and control groups. Results: The APTw values of the bilateral hippocampus and amygdala in the aMCI group were significantly higher than those in the control group (left hippocampus 1.01 vs. 0.77% p < 0.001; right hippocampus 1.02 vs. 0.74%, p < 0.001; left amygdala 0.98 vs. 0.70% p < 0.001; right amygdala 0.94 vs. 0.71%, p < 0.001). The APTw values of the left amygdala had the largest AUC (0.875) at diagnosis of aMCI. There was no significant difference in APTw values between the left and right hippocampus and amygdala, in either group. (aMCI group left hippocampus 1.01 vs. right hippocampus 1.02%, p = 0.652; healthy control group left hippocampus 0.77 vs. right hippocampus 0.74%, p = 0.314; aMCI group left amygdala 0.98 vs. right amygdala 0.94%, p = 0.171; healthy control group left amygdala 0.70 vs. right amygdala 0.71%, p = 0.726). Conclusion: APTw can be used as a new imaging marker to distinguish aMCI patients from the normal elderly population by indirectly reflecting the changes in protein content in the hippocampus and amygdala.

Synthesis of novel ternary heterogeneous anatase-TiO2 (B) biphase nanowires/Bi4O5I2 composite photocatalysts for the highly efficient degradation of acetaminophen under visible light irradiation.

Bi4O5I2 loaded anatase-TiO2 (B) biphase nanowires composite photocatalysts were fabricated by an in situ calcination method and exhibited outstanding photocatalytic activity. The microstructure, optical performance and band structure of the composite photocatalysts were investigated by relevant characterizations. The results demonstrated the successful formation of heterojunction between anatase-TiO2 (B) biphase nanowires and Bi4O5I2, which integrated the advantages of homojunction and heterojunction. Therefore, it definitely improved separation efficiency of photo-induced electron-holes because of the formation of multi-junctions. In order to test the enhanced photocatalytic activity, acetaminophen was chosen as target pollutant. The sample with 67% Bi4O5I2 (TiO2-Bi4O5I2-3) presented the highest photocatalytic activity on the degradation of acetaminophen and its reaction apparent rate constant was 10 and 25 times as that of Bi4O5I2 and TiO2 biphase nanowires, respectively. Through trapping experiments and LC-MS/MS analysis, OH was proved to be the key active specie during the photocatalytic process of acetaminophen degradation. Meanwhile a possible degradation pathway was proposed based on the detected intermediate products.