Using functional magnetic resonance imaging (fMRI) we have evaluated the anatomical location of the motor hand area. The segment of the precentral gyrus that most often contained motor hand function was a knob-like structure, that is shaped like an omega or epsilon in the axial plane and like a hook in the sagittal plane. On the cortical surface of cadaver specimens this precentral knob corresponded precisely to the characteristic 'middle knee' of the central sulcus that has been described by various anatomists in the last century. We were then able to show that this knob is a reliable landmark for identifying the precentral gyrus directly. We therefore conclude that neural elements involved in motor hand function are located in a characteristic 'precentral knob' which is a reliable landmark for identifying the precentral gyrus under normal and pathological conditions. It faces and forms the 'middle knee' of the central sulcus, is located just at the cross point between the precentral sulcus and the central sulcus, and is therefore also visible on the cortical surface.

Radiomics is a quantitative approach to medical imaging, which aims at enhancing the existing data available to clinicians by means of advanced mathematical analysis. Through mathematical extraction of the spatial distribution of signal intensities and pixel interrelationships, radiomics quantifies textural information by using analysis methods from the field of artificial intelligence. Various studies from different fields in imaging have been published so far, highlighting the potential of radiomics to enhance clinical decision-making. However, the field faces several important challenges, which are mainly caused by the various technical factors influencing the extracted radiomic features. The aim of the present review is twofold: first, we present the typical workflow of a radiomics analysis and deliver a practical "how-to" guide for a typical radiomics analysis. Second, we discuss the current limitations of radiomics, suggest potential improvements, and summarize relevant literature on the subject.

Aims The aim of our study was to investigate the accuracy of 64-slice computed tomography (CT) for assessing haemodynamically significant stenoses of coronary arteries. Methods and results CT angiography was performed in 67 patients (50 male, 17 female; mean age 60.1 + 10.5 years) with suspected coronary artery disease and compared with invasive coronary angiography. All vessels !1.5 mm were considered for the assessment of significant coronary artery stenosis (diameter reduction .50%). Forty-seven patients were identified as having significant coronary stenoses on invasive angiography with 18% (176/1005) affected segments. None of the coronary segments needed to be excluded from analysis. CT correctly identified all 20 patients having no significant stenosis on invasive angiography. Overall sensitivity for classifying stenoses was 94%, specificity was 97%, positive predictive value was 87%, and negative predictive value was 99%. Conclusion Sixty-four-slice CT provides a high diagnostic accuracy in assessing coronary artery stenoses.

Our results suggest that the Diamond-Forrester model overestimates the probability of CAD especially in women. We updated the predictive effects of age, sex, type of chest pain, and hospital setting which improved model performance and we extended it to include patients of 70 years and older.