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.
To investigate the CT imaging and clinical features of three atypical presentations of coronavirus disease 2019 (COVID-19), namely (1) asymptomatic, (2) CT imaging-negative, and (3) re-detectable positive (RP), during all disease stages.A consecutive cohort of 79 COVID-19 patients was retrospectively recruited from five independent institutions. For each presentation type, all patients were classified into atypical vs. typical groups (i.e., asymptomatic vs.symptomatic, CT imaging-negative vs. CT imaging-positive, and RP and non-RP,respectively). The chi-square test, Student's t test, and Kruskal-Wallis H test were performed to compare CT imaging and clinical features of atypical vs. typical patients for all three presentation categories.In our COVID-19 cohort, we found 12.7% asymptomatic patients, 13.9% CT imaging-negative patients, and 8.9% RP patients. The asymptomatic patients had fewer hospitalization days (P=0.043), lower total scores for bilateral lung involvement (P< 0.001), and fewer ground-glass opacities (GGOs) in the peripheral area (P< 0.001) than symptomatic patients. The CT imaging-negative patients were younger (P=0.002), had a higher lymphocyte count (P=0.038), had a higher lymphocyte rate (P=0.008), and had more asymptomatic infections (P=0.002) than the CT imaging-positive patients. The RP patients with moderate COVID-19 had lower total scores of for bilateral lung involvement (P=0.030) and a smaller portion of the left lung affected (P=0.024) than non-RP patients. Compared to their first hospitalization, RP patients had a shorter hospitalization period (P< 0.001) and fewer days from the onset of illness to last RNA negative conversion (P< 0.001) at readmission.Significant CT imaging and clinical feature differences were found between atypical and typical COVID-19 patients for all three atypical presentation categories investigated in this study, which may help provide complementary information for the effective management of COVID-19.
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.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).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.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.
Keywords: Extracellular pH, Ioversol, CEST MRI, Hepatic carcinoma, Hepatic hemangioma. Purpose: In this study, we aimed to use 3T magnetic resonance imaging (MRI), which is clinically available, to determine the extracellular pH (pHe) of liver tumors and prospectively evaluate the ability of chemical exchange saturation transfer (CEST) MRI to distinguish between benign and malignant liver tumors. Methods: Different radiofrequency irradiation schemes were assessed for ioversol-based pH measurements at 3T. CEST effects were quantified in vitro using the asymmetric magnetization transfer ratio (MTRasym) at 4.3 ppm from the corrected Z spectrum. Generalized ratiometric analysis was conducted by rationing resolved ioversol CEST effects at 4.3 ppm at a flip angle of 60°and 350°. Fifteen patients recently diagnosed with hepatic carcinoma and five patients diagnosed with hepatic hemangioma (1 male; mean age, 48.6 [range, 37–59] years) were assessed. Results: By conducting CEST pH MRI, the pH of ioversol was determined to be 6.0–7.2 at 3T in vitro. In vivo, ioversol signal intensities in the tumor region in patients with hepatic carcinoma were attenuated (mean ± standard deviation, 6.66 ± 0.19), whereas they were stabilized (mean ± standard deviation, 7.34 ± 0.09) among patients with hepatic hemangioma. The lesion size was similar between CEST pH MRI and T2-weighted imaging. In liver cancer, Conclusion: Ioversol CEST pH MRI can detect extracellular pH in human liver tumors and can provide molecular-level diagnostic tools for benign and malignant liver tumors at 3T.
Abstract Objectives Rapid and accurate diagnosis of coronavirus disease 2019 (COVID-19) is critical during the epidemic. We aim to identify differences in CT imaging and clinical manifestations between pneumonia patients with and without COVID-19, and to develop and validate a diagnostic model for COVID-19 based on radiological semantic and clinical features alone. Methods A consecutive cohort of 70 COVID-19 and 66 non-COVID-19 pneumonia patients were retrospectively recruited from five institutions. Patients were divided into primary ( n = 98) and validation ( n = 38) cohorts. The chi-square test, Student’s t test, and Kruskal-Wallis H test were performed, comparing 1745 lesions and 67 features in the two groups. Three models were constructed using radiological semantic and clinical features through multivariate logistic regression. Diagnostic efficacies of developed models were quantified by receiver operating characteristic curve. Clinical usage was evaluated by decision curve analysis and nomogram. Results Eighteen radiological semantic features and seventeen clinical features were identified to be significantly different. Besides ground-glass opacities ( p = 0.032 ) and consolidation ( p = 0.001 ) in the lung periphery, the lesion size (1–3 cm) is also significant for the diagnosis of COVID-19 ( p = 0.027 ). Lung score presents no significant difference ( p = 0.417 ). Three diagnostic models achieved an area under the curve value as high as 0.986 (95% CI 0.966~1.000). The clinical and radiological semantic models provided a better diagnostic performance and more considerable net benefits. Conclusions Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. A model composed of radiological semantic and clinical features has an excellent performance for the diagnosis of COVID-19. Key Points • Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. • A diagnostic model for COVID-19 was developed and validated using radiological semantic and clinical features, which had an area under the curve value of 0.986 (95% CI 0.966~1.000) and 0.936 (95% CI 0.866~1.000) in the primary and validation cohorts, respectively.
Chemical exchange saturation transfer (CEST) is an emerging MRI contrast mechanism that is capable of noninvasively imaging dilute CEST agents and local properties such as pH and temperature, augmenting the routine MRI methods. However, the routine CEST MRI includes a long RF saturation pulse followed by fast image readout, which is associated with high specific absorption rate and limited spatial resolution. In addition, echo planar imaging (EPI)-based fast image readout is prone to image distortion, particularly severe at high field. To address these limitations, we evaluated magnetization transfer (MT) prepared gradient echo (GRE) MRI for CEST imaging. We proved the feasibility using numerical simulations and experiments in vitro and in vivo. Then we optimized the sequence by serially evaluating the effects of the number of saturation steps, MT saturation power (B1), GRE readout flip angle (FA), and repetition time (TR) upon the CEST MRI, and further demonstrated the endogenous amide proton CEST imaging in rats brains (n = 5) that underwent permanent middle cerebral artery occlusion. The CEST images can identify ischemic lesions in the first 3 hours after occlusion. In summary, our study demonstrated that the readily available MT-prepared GRE MRI, if optimized, is CEST-sensitive and remains promising for translational CEST imaging.
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.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.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.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).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.
Glutamate (GLU) is one of the most important excitatory neurotransmitters in central nervous system (CNS). GLU is involved in many CNS diseases, which is well reported that it is closely related to the infectious diseases in CNS. Brain abscess is a common disease in CNS. GLU chemical exchange saturation transfer MRI (GLUCEST) is used to explore the changes of glutamate concentration in the brain abscess models. Firstly, a SD rat brain abscess model was established by using Staphylococcus aureus in the right frontal lobe of SD rats. Secondly, imaging of normal SD rats and brain abscess rats were obtained in Agilent 7.0T animal magnetic resonance scanner respectively. Finally, all data are processed on Matlab. GLUCEST clearly delineated brain abscess at Z spectra. The CEST map of the brain abscess rats showed that the glutamate CEST effect in the lesions was significantly higher than that in the normal SD rats (p < 0.05). GLUCEST may provide new insight into brain abscess and help to improve the differential diagnosis.
In the progression of ischemia, pH is important and is essential in elucidating the association between metabolic disruption, lactate formation, acidosis and tissue damage. Chemical exchange‑dependent saturation transfer (CEST) imaging can be used to detect tissue pH and, in particular, a specific form of CEST magnetic resonance imaging (MRI), termed amide proton transfer (APT) MRI, which is sensitive to pH and can detect ischemic lesions, even prior to diffusion abnormalities. The critical parameter governing the ability of CEST to detect pH is the sequence. In the present study, a novel strategy was used, based on the gradient echo sequence (GRE), which involved the insertion of a magnetization transfer pulse in each repetition time (TR) and minimizing the TR for in vivo APT imaging. The proposed GRE‑APT MRI method was initially verified using a tissue‑like pH phantom and optimized MRI parameters for APT imaging. In order to assess the range of acute cerebral infarction, rats (n=4) were subjected to middle cerebral artery occlusion (MCAO) and MRI scanning at 7 telsa (T). Hyperacute ischemic tissue damage was characterized using multiparametric imaging techniques, including diffusion, APT and T2‑Weighted MRI. By using a magnetization transfer pulse and minimizing TR, GRE‑APT provided high spatial resolution and a homogeneous signal, with clearly distinguished cerebral anatomy. The GRE‑APT and diffusion MRI were significantly correlated with lactate content and the area of cerebral infarction in the APT and apparent diffusion coefficient (ADC) maps matched consistently during the hyperacute period. In addition, compared with the infarction area observed on the ADC MRI map, the APT map contained tissue, which had not yet been irreversibly damaged. Therefore, GRE‑APT MRI waa able to detect ischemic lactic acidosis with sensitivity and spatiotemporal resolution, suggesting the potential use of pH MRI as a surrogate imaging marker of impaired tissue metabolism for the diagnosis and prognosis of hyperacute stroke.
Aim We utilized single‐voxel 1 H magnetic resonance spectroscopy to determine biochemical abnormalities related to major depressive disorder ( MDD ) in the bilateral dorsolateral prefrontal cortex, anterior cingulate cortex ( ACC ), and cerebellar hemisphere before and after antidepressant treatment. Methods Fifteen adult MDD patients and 15 age‐ and sex‐matched healthy controls were involved. Magnetic resonance spectroscopy of the brain was conducted in all subjects at the beginning of the study and the depressed subjects were reassessed after 8 weeks of antidepressant treatment. Results At baseline, N‐acetyl aspartate ( NAA ), total glutamine plus glutamate ( Glx ) and myo‐inositol ( MI ) levels in the bilateral ACC were significantly lower in MDD patients than in controls ( P < 0.05/3). MI in the bilateral cerebellar hemisphere were also decreased in patients compared with controls. After the treatment, the lower NAA , G lx and MI in ACC were normalized in MDD patients and the NAA and G lx increased compared to baseline values. The MI levels in the bilateral cerebellar hemisphere were also normalized in patients. MI and choline levels in the right cerebellar hemisphere were elevated compared to those at baseline. Conclusion Our study suggests that metabolic abnormalities in the ACC and cerebellar hemisphere are implicated in MDD . Antidepressants may alter the local metabolic abnormalities in these areas.
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