Young adult cardiovascular diseases: a single center coronary computed tomography angiography study.

PURPOSE AND BACKGROUND: Cardiovascular disease (CVD) is one of the leading causes of death. However, the prevalence of CVD in young adults (<40 years of age) has not been well documented. We conducted this study to determine the proportion of CVD in both symptomatic and asymptomatic young adults. MATERIALS AND METHODS: Coronary CT angiography images obtained from April 2015 to July 2017 in our institution was retrospectively reviewed. Young adults were separated into two groups according to whether they had experienced chest discomfort. The diagnosis was classified as normal, coronary artery disease (CAD), myocardial bridging (MB), congenital coronary anomaly, congenital cardiac anomaly, cardiomyopathy, and aortic anomaly. The proportion of different diagnoses in two groups and cardiovascular risk factors were analyzed. RESULTS: Totally 107 patients (mean age, 35.6 ±â€¯3.55 years) were grouped into 36 cases of symptomatic group and 71 patients of asymptomatic group. Cardiovascular anomalies were found in 61 cases (41%). No significant difference in the occurrence rates of CAD (14% vs 11%, p = 0.53), MB (31% vs 42%, p = 0.51), and congenital coronary anomaly (7% vs 3%, p = 0.26) between groups. Mild arterial stenosis was implied in most CAD cases. Hypertension was the only risk factor significantly correlated with CAD. CONCLUSIONS: Although young adults are conventionally identified as low-risk, more than 60% of the cases in our cohort were proved to present cardiovascular anomalies, with no significant relation to cardiac symptoms. Early interventions should be conducted for aggressive CVD subtypes to prevent future acute events.

Secondary pallidonigral degeneration mimicking recurrent acute stroke in clinical presentation and magnetic resonance imaging: a case report.

BACKGROUND: Secondary pallidonigral transneuronal degeneration after a remote primary cerebral infarct can mimic recurrent stroke at clinical presentation. We describe a patient with secondary pallidonigral degeneration following a previous putaminal infarct, which was diagnosed through diffusion-weighted (DWI) and T2-weighted imaging (T2WI). CASE PRESENTATION: A 64-year-old man complained of an acute relapse of right-lower-limb weakness following a cerebral infarction 2 months before presentation. Recurrent cerebral stroke was initially diagnosed in the emergency room. DWI of the brain revealed a subacute to chronic infarct in the left putamen and new acute cytotoxic edema in the left substantia nigra (SN) and globus pallidus while T2WI also showed hyperintensity in the same regions. The SN was outside the aforementioned middle cerebral arterial territory, which includes the putamen. These findings are compatible with the diagnosis of acute pallidonigral injury secondary to striatal infarction. The patient had fully recovered from his right-lower-limb weakness after 1 month. CONCLUSIONS: Secondary pallidonigral degeneration may mimic recurrent stroke. DWI along with T2WI facilitates elucidation of this clinicopathological entity, and thus unnecessary treatment can be avoided.

Effect of a computer-aided diagnosis system on radiologists' performance in grading gliomas with MRI.

The effects of a computer-aided diagnosis (CAD) system based on quantitative intensity features with magnetic resonance (MR) imaging (MRI) were evaluated by examining radiologists' performance in grading gliomas. The acquired MRI database included 71 lower-grade gliomas and 34 glioblastomas. Quantitative image features were extracted from the tumor area and combined in a CAD system to generate a prediction model. The effect of the CAD system was evaluated in a two-stage procedure. First, a radiologist performed a conventional reading. A sequential second reading was determined with a malignancy estimation by the CAD system. Each MR image was regularly read by one radiologist out of a group of three radiologists. The CAD system achieved an accuracy of 87% (91/105), a sensitivity of 79% (27/34), a specificity of 90% (64/71), and an area under the receiver operating characteristic curve (Az) of 0.89. In the evaluation, the radiologists' Az values significantly improved from 0.81, 0.87, and 0.84 to 0.90, 0.90, and 0.88 with p = 0.0011, 0.0076, and 0.0167, respectively. Based on the MR image features, the proposed CAD system not only performed well in distinguishing glioblastomas from lower-grade gliomas but also provided suggestions about glioma grading to reinforce radiologists' confidence rating.