tion cohorts, respectively). CT radiomics features could help predict the LNM status of advanced ESCC patients and effectively discriminate ESCC between RLNM and NRLNM.CT radiomics features could help predict the LNM status of advanced ESCC patients and effectively discriminate ESCC between RLNM and NRLNM. Rapid-kilovoltage-switching dual-energy computed tomography (RDECT) is a non-invasive, alternative technique for quantitative diagnosis. This study aimed to investigate the value of RDECT for differentiating spinal osteolytic metastases (SOM) from spinal infections (SIs). RDECT was performed on 29 patients with SOM and 18 patients with SIs. Both iodine-based and water-based material decomposition images were generated from the spectral CT scan. The iodine/water densities of lesions on iodine/water material-decomposition images and the CT attenuation values on traditional CT images were measured three times at different image levels, and the averages were calculated. The lesion-to-muscle ratio (LMR) and lesion-to-artery ratio (LAR) for iodine density measurements were calculated. All parameters were compared between the two groups using the two-tailed Student's -test. A P value <0.05 was considered statistically significant. Adenine sulfate The sensitivity and specificity for differentiating SOM from SIs were determined using receiver operating characteristic curves (ROC). Iodine density, LMR, and LAR during the arterial phase (AP) and venous phase (VP) were all significantly higher for SOM than for SIs (all P<0.05). The water densities and traditional CT attenuation values during the AP and VP were not significantly different between the two groups. For ROC analysis, LAR during the VP (LAR ) showed the best diagnostic performance, with an area under the ROC curve (AUC) value of 0.862. When the LARVP was 0.54, the sensitivity was 82.80% and the specificity was 77.80% for differentiating SOM from SIs. RDECT can provide additional information that may be useful for differentiating atypical SOM from SIs.RDECT can provide additional information that may be useful for differentiating atypical SOM from SIs. The aim of this study was to determine the relationship between blood oxygen level dependent (BOLD) cerebrovascular reactivity (CVR) and cerebral blood flow (CBF) obtained from arterial spin labeling (ASL) using different post labeling delays (PLD). Forty-two patients with steno-occlusive diseases and impaired CVR were divided into two groups, one scanned with a 1.5-second (1.5-s) and the other with a 2.5-second (2.5-s) PLD ASL protocol. For all patients, a region of interest (ROI) was drawn around the CVR impairment. This affected ROI was then left-right flipped across the brain midline to obtain the control ROI. For both groups, the difference in grey matter CVR between affected and control ROI was first tested to confirm significance. The average grey matter CBF of affected and control ROIs were then compared. The same analysis method was used to compare affected and control hemispheres. In both groups of 1.5-s and 2.5-s PLD, CVR values in the affected ROI (-0.049±0.055 and -0.042±0.074%/mmHg, respecr study reveals and highlights the value of a shorter-PLD ASL protocol, which is able to reflect CVR impairment. At the same time, we offer a better understanding of the relationship between BOLD CVR and CBF obtained from ASL. Previous studies have hypothesized that intracranial aneurysm (IA) morphology interacts with hemodynamic conditions. Magnetic resonance imaging (MRI) provides a single image modality solution for both morphological and hemodynamic measurements for IA. This study aimed to explore the interaction between the morphology and hemodynamics of IA using black-blood MRI (BB-MRI) and 4D flow MRI. A total of 97 patients with unruptured IA were recruited for this study. The IA size, size ratio (SR), and minimum wall thickness (mWT) were measured using BB-MRI. Velocity, blood flow, pulsatility index (PI), and wall shear stress (WSS) were measured with 4D flow MRI. The relationship between hemodynamic parameters and morphological indices was investigated by linear regression analysis and unpaired two-sample -test. To determine the independent interaction, multiple linear regression analysis was further performed. The findings showed that mWT was negatively correlated with IA size (r=-0.665, P<0.001). Maximum blomprehensive understanding of the mechanism of IA. Osteoporosis is a highly prevalent multifactorial osteometabolic disease, classically diagnosed, , by dual energy X-ray absorptiometry (DXA). This study evaluated osteoporosis, , using vibro-acoustography (VA), an elastographic technique based on ultrasound radiation force. Three groups of mice femurs were used (I) control group (CG), (II) osteoporosis group (OG) and (III) treated osteoporosis group (TOG), in which the animals received pamidronate, an antiresorptive drug. Evaluation was performed in an acoustic tank, using two high frequency focused beams produced by a confocal ultrasonic transducer. A hydrophone registered the low frequency acoustic response (AR) of bone samples. We used micro-computed tomography (microCT) as the reference standard and evaluated the correlation between VA and microCT parameters. The spectral analyses of the ARs with estimated area under the curve (AUC) values (mean; st. dev.) were, respectively, 1.29e and 9.32e for the CG, 3.25e and 2.16e for the OG, and 1.50e and 8.37e for the TOG. VA differentiated the experimental groups (P<0.01) and the results were reproducible [interclass correlation coefficient (ICC) 0.43 (95% CI 0.15-0.71)]. There was also a statistically significant association between VA and microCT connectivity (Conn.) (r=0.80; P<0.01) and connectivity density (Conn. D) (r=0.76; P<0.01). These results encourage further studies aimed at evaluating the potential use of VA for the diagnosis of osteoporosis as a relatively low-cost and radiation-free alternative to DXA.These results encourage further studies aimed at evaluating the potential use of VA for the diagnosis of osteoporosis as a relatively low-cost and radiation-free alternative to DXA.