Search

Background: Diffusion-weighted imaging (DWI) is a functional modality that indirectly represents the biological characteristics of cancer. However, the correlation of apparent diffusion coefficients (ADCs) to HPV type in patients with cervical cancer is still unknown. Purpose: To explore the relationship between apparent diffusion coefficients calculated by DW-magnetic resonance imaging (MRI) and high-risk human papilloma virus (HR-HPV) infection in cervical squamous cell carcinoma (CSCC) patients. Material and Methods: A total of 315 patients with histologically proven CSCC and who underwent pretreatment MRI were retrospectively analyzed. ADCs on the primary tumor were calculated. Receiver operating characteristic (ROC) curves were employed to determine the cut-off values of ADCmean and accuracy of prediction. Pearson correlation and multivariate logistic regression models were adopted to show the association of HR-HPV infection with clinical and imaging variables. Results: ADCmean for HR-HPV+ CSCC was significantly lower than those for HR-HPV- CSCC. The area under the curve was 0.805 for predicting HR-HPV+ infection using mean ADCs. A cut-off value of 0.885 × 10−3 mm2/s for mean ADCS could distinguish HR-HPV+ from HR-HPV- CSCC with 83.3% sensitivity, 73.9% specificity, and 80.8% accuracy. Regression analysis revealed that the HR-HPV infection was closely associated with tumor ADC value (odds ratio [OR] = 5.588, 95% confidence interval [CI] = 3.371–9.262), FIGO stage (OR = 2.789, 95% CI = 1.631–4.769), and histological grade (OR = 2.333, 95% CI = 1.676–3.247). Conclusion: ADC value is related with the HR-HPV infection in patients with CSCC and DWI may be used for predicting HR-HPV infection in patients with CSCC. [ABSTRACT FROM AUTHOR]

Abstract Purpose To perform a meta-analysis for assessing the accuracy of diffusion kurtosis imaging (DKI)-derived quantitative parameters (kurtosis values, K ; and corrected diffusion coefficients non-Gaussian bias, D) in separating malignant cancers from benign lesions. Methods Relevant studies were searched in PubMed and Cochrane Library databases and were analyzed by Meta-DiSc software. Results Fourteen eligible studies involving 1847 lesions in 1107 patients (895 were benign and 952 were malignant) were included. Pooled analysis showed the sensitivity, specificity, positive likelihood ratio (LR), and negative LR were respectively 0.83 (95% CI, 0.79–0.85), 0.83 (95% CI, 0.80–0.86), 4.61 (95% CI, 2.98–7.14), and 0.22 (95% CI, 0.18–0.28) for K , with the overall area under curve (AUC) of 0.89. The sensitivity, specificity, positive LR, and negative LR were 0.85 (95% CI, 0.80–0.88), 0.85 (95% CI, 0.79–0.89), 6.39 (95% CI, 3.14–12.99), and 0.18 (95% CI, 0.14–0.23) for D , with the overall AUC of 0.92. The sensitivity, specificity, positive LR, and negative LR for apparent diffusion coefficient (ADC) derived from standard diffusion-weighted imaging (DWI) were 0.82 (95% CI, 0.79–0.84), 0.85 (95% CI, 0.82–0.88), 4.75 (95% CI, 3.38–6.68), and 0.24 (95% CI, 0.19–0.29), with the overall AUC of 0.89. The superiority of D to K and ADC was also confirmed by the subgroup analysis of prostate cancer. Conclusion Our findings suggest that DKI should be added to the routine imaging protocol for screening cancer, with the highest diagnostic accuracy of diffusion coefficients. Highlights • The first meta-analysis to explore the accuracy of DKI parameters for cancer diagnosis • Diagnostic accuracy of D and K were 0.9162 and 0.8908 • Diagnostic accuracy of D superior to apparent diffusion coefficient [ABSTRACT FROM AUTHOR]

Abstract Purpose To investigate the role of apparent diffusion coefficient (ADC) as an imaging biomarker for invasive ductal carcinoma (IDC) in the breast. Methods Seventy-one patients undergoing 3.0 Tesla DWI were retrospectively enrolled. Correlations between the ADC values and prognostic factors were evaluated. Results Multivariate regression analyses showed that Ki67 expression and molecular subtype were independently associated with the ADC. Discriminant analysis excluded the ADC as a good biomarker for subtype, but the mean ADC significantly distinguished Ki67-positive (low ADC) from Ki67-negative (high ADC) lesions, as observed in the in ROC curves, with a diagnostic sensitivity of 1.00 and a cut-off value of 0.97 × 10−3 mm2/s. Conclusion The ADC may be helpful for predicting Ki67 expression in IDC preoperatively. Highlights • The power of Ki67 and subtype was >0.8 by sample size estimation. • The ADC at 3.0 T was associated with Ki67 under a diagnostic test. • ADC was not a good grouping variable for subtype by discriminant analysis. [ABSTRACT FROM AUTHOR]

Background: Diffusion weighted magnetic resonance imaging (DWI) and dynamic contrast-enhanced (DCE) MRI have been considered useful for pathological staging and histological grading in bladder cancer. To our knowledge, no study has combined the two imaging modalities together to assess aggressiveness of bladder cancer. Objective: To assess the clinical aggressiveness of bladder cancer with DCE MRI and DWI at 3.0T. Materials and Methods: A total of 59 patients with 69 pathologically confirmed tumor lesions were included in this study. All patients underwent MR examination at 3.0T basing on DWI and DCE imaging. Tumor staging and histological grade were evaluated. The aggressiveness of bladder cancer was classified as low-, intermediate-, or high-aggressiveness according to its pathological phenotype. Apparent diffusion coefficient (ADC) value and semi-quantitative parameters (wash-in rate and wash-out rate) were determined. The correlation between clinical aggressiveness and ADC value, wash-in rate and wash-out rate were analyzed. In addition, the diagnostic accuracy of the diffusion and semi-quantitative parameters were estimated using receiver operating characteristic curve (ROC). Results: Aggressiveness of bladder cancer is negatively correlated with ADC value (r=-0.705, p<0.0001) and wash-out rate (r=-0.719, p<0.0001). The tumor ADC value is positively correlated with wash-out rate (r=0.555, p<0.0001). The diagnostic specificity and accuracy using tumor ADC value and wash-out for the tumor with size <24mm were better than that tumors with size ≥24mm. The sensitivity, specificity and accuracy of ADC and wash-out rate in combination in diagnosis of bladder cancer aggressiveness were 96.7%, 94.9% and 95.7%, respectively. ROC curve revealed the diagnostic performance of aggressiveness of bladder cancer using ADC value and wash-out rate were 0.928 (cut-off value: 0.905×10(-3)mm(2)/s) and 0.891 (cut-off value: 0.685min(-1)), respectively. Conclusion: ADC and wash-out rate derived from DWI and DCE-MRI at 3.0T have good potential to assess the aggressiveness of bladder cancer and the accuracy was greater for ADC than for semi-quantitative parameters. [ABSTRACT FROM AUTHOR]

Background Diffusion weighted magnetic resonance imaging (DWI) and dynamic contrast-enhanced (DCE) MRI have been considered useful for pathological staging and histological grading in bladder cancer. To our knowledge, no study has combined the two imaging modalities together to assess aggressiveness of bladder cancer. Objective To assess the clinical aggressiveness of bladder cancer with DCE MRI and DWI at 3.0 T. Materials and methods A total of 59 patients with 69 pathologically confirmed tumor lesions were included in this study. All patients underwent MR examination at 3.0 T basing on DWI and DCE imaging. Tumor staging and histological grade were evaluated. The aggressiveness of bladder cancer was classified as low-, intermediate-, or high-aggressiveness according to its pathological phenotype. Apparent diffusion coefficient (ADC) value and semi-quantitative parameters (wash-in rate and wash-out rate) were determined. The correlation between clinical aggressiveness and ADC value, wash-in rate and wash-out rate were analyzed. In addition, the diagnostic accuracy of the diffusion and semi-quantitative parameters were estimated using receiver operating characteristic curve (ROC). Results Aggressiveness of bladder cancer is negatively correlated with ADC value ( r = −0.705, p < 0.0001) and wash-out rate ( r = −0.719, p < 0.0001). The tumor ADC value is positively correlated with wash-out rate ( r = 0.555, p < 0.0001). The diagnostic specificity and accuracy using tumor ADC value and wash-out for the tumor with size <24 mm were better than that tumors with size ≥24 mm. The sensitivity, specificity and accuracy of ADC and wash-out rate in combination in diagnosis of bladder cancer aggressiveness were 96.7%, 94.9% and 95.7%, respectively. ROC curve revealed the diagnostic performance of aggressiveness of bladder cancer using ADC value and wash-out rate were 0.928 (cut-off value: 0.905 × 10 −3 mm 2 /s) and 0.891 (cut-off value: 0.685 min −1 ), respectively. Conclusion ADC and wash-out rate derived from DWI and DCE-MRI at 3.0 T have good potential to assess the aggressiveness of bladder cancer and the accuracy was greater for ADC than for semi-quantitative parameters. [ABSTRACT FROM AUTHOR]

Electrochemical nanochannel sensors have attracted extensive interest due to their potential applications in biosensing systems. In this work, porous anodized aluminum oxide (AAO) nanochannels are coupled with gold nanoparticles (AuNPs) through a polydopamine (PDA)-induced in situ growth process. It is found that the resulting hybrid nanochannel (denoted as Au-PDA-AAO) can act as both glucose oxidase- and peroxidase-like nanozymes to catalyze the cascade reaction involving glucose. To the best of our knowledge, this is the first report on the synthesis of nanozymes in an AAO nanochannel. Moreover, apart from the nanozyme-catalyzed colorimetric reaction, the Au-PDA-AAO nanochannel could simultaneously serve as a sensitive signal reporter for an electrochemical sensing platform. In such an approach, the glucose oxidation reaction boosts the resistance of the Au-PDA-AAO nanochannel towards ion transport based on the H2O2-mediated size enlargement of AuNPs, resulting in the varied transmembrane ionic current signal of the Au-PDA-AAO nanochannel. On the basis of the changed current–potential properties, the label-free detection of glucose can be achieved with a low detection limit, good reproducibility, and high stability. This work demonstrates the feasibility of the incorporation of versatile nanozymes into AAO nanochannels for mimicking multi-enzymatic catalysis reactions and detecting target analytes. [ABSTRACT FROM AUTHOR]

Herein, an electrochemical biosensing platform with acetylcholinesterase (AChE)-catalyzed silver deposition was developed for the ultrasensitive detection of organophosphorus pesticides (OPs). The biosensing mechanism is based on the fact that AChE can catalyze the rapid hydrolysis of indoxyl acetate to form hydroxyindole, which in turn reduces silver ions to metallic silver, resulting in the deposition of silver on the gold electrode. Upon sweeping positive voltages on the gold electrode using linear sweep voltammetry (LSV), the deposited silver on the gold electrode surface undergoes a rapid electrochemical oxidation reaction. Due to its lower oxidation potential under facile conditions with a relatively sharp peak, a small amount of deposited silver generated from AChE-catalysis could result in a significant change in the LSV response. In the presence of OPs, the AChE-catalyzed hydrolysis of indoxyl acetate is blocked, and then the silver deposition on the gold electrode declines, leading to a remarkable decrease in the LSV response and, thus producing a large signal output for the ultrasensitive detection of chlorpyrifos, a proof-of-concept OP in this work. The change in the LSV peak current intensity is linearly correlated with the logarithmic value of the chlorpyrifos concentration ranging from 10 pM to 10 nM with a low detection limit of 4.0 pM. To the best of our knowledge, this is the first example of a biosensing platform for ultrasensitive OP assay using AChE-controlled silver deposition to enhance the output of electronic signals. [ABSTRACT FROM AUTHOR]

Background and Purpose: Imaging studies of traumatic brain injury demonstrate that the cerebellum is often affected. We aim to examine fractional anisotropy alteration in acute-phase mild traumatic brain injury patients in cerebellum-related white matter tracts. Materials and Methods: This prospective study included 47 mild traumatic brain injury patients in the acute stage and 37 controls. MR imaging and neurocognitive tests were performed in patients within 7 days of injury. White matter integrity was examined by using diffusion tensor imaging. We used three approaches, tract-based spatial statistics, graphical-model-based multivariate analysis, and region-of-interest analysis, to detect altered cerebellar white matter integrity in mild traumatic brain injury patients. Results: Results from three analysis methods were in accordance with each other, and suggested fractional anisotropy in the middle cerebellar peduncle and the pontine crossing tract was changed in the acute-phase mild traumatic brain injury patients, relative to controls (adjusted p-value < 0.05). Higher fractional anisotropy in the middle cerebellar peduncle was associated with worse performance in the fluid cognition composite (r = -0.289, p-value = 0.037). Conclusion: Altered cerebellar fractional anisotropy in acute-phase mild traumatic brain injury patients is localized in specific regions and statistically associated with cognitive deficits detectable on neurocognitive testing. [ABSTRACT FROM AUTHOR]