Recent Patents on Medical Imaging (Discontinued) - Volume 3, Issue 1, 2013

Stroke is the 3rd leading cause of death in the developed countries. It will rank the 2nd among the four leading causes of death globally by 2030 according to the World Health Organization. Carotid atherosclerotic disease is a predominant cause of stroke resulting from carotid plaque rupture. Degree of stenosis, which is the current criterion for assessment of atherosclerotic disease severity, has been observed to be insufficient. Atherosclerotic plaque is composed of various components, such as lipid-rich necrotic core, haemorrhage and calcium, covered by fibrous cap. Increasing evidence has shown that plaque vulnerability has a close relationship with these morphological features. Moreover, under physiological conditions plaque experiences mechanical loading due to blood pressure and blood flow. From the mechanical view point, rupture possibly occurs when the extra loading exceeds the material strength of the plaque. Therefore, anatomical and mechanical features should be considered in an integrated way for a more accurate assessment of plaque vulnerability. This review focuses on (1) the emerging high-risk morphological features and their association with clinical symptoms. Some related patents have been summarized; and (2) translational clinical application of biomechanical analysis in plaque vulnerability assessment. For completeness, the basis of atherosclerotic plaque, magnetic resonance imaging and finite element analysis will be introduced briefly.

Whereas atheroma progression/regression studies have focused on luminal narrowing or atheroma burden, the current notion that inflammation and immune response may contribute to the development of plaque rupture has garnered increased interest. As the disease process has become increasingly defined, this provides a range of potential targets to be employed by emerging imaging techniques. With ongoing developments in vascular imaging to visualize compositional and biological features in atherosclerotic plaque, there is considerable interest in the incremental information that can be ascertained. A selective overview of emerging modalities and patents to image the artery wall and the potential target is summarized.

Cardiovascular ischemic diseases, such as myocardial infarction and stroke, are the leading causes of death and disability worldwide. Atherosclerotic plaque is one of the main reasons for such ischemic events. Major systemic atherosclerotic risk factors, such as hypertension, smoking, hyperlipidemia, diabetes mellitus and a sedentary lifestyle, fail to explain the focal nature of atheroma. Local hemodynamic conditions are thought to be closely associated with such a phenomenon. Shear stress has been widely accepted as an important factor in the development of atherosclerosis plaques. Recent advances in medical imaging and computational modeling techniques have enabled patients-specific hemodynamics to be visualized in vivo. Shear stress can be computed using direct flow imaging techniques, such as Doppler ultrasound and phase-contrast magnetic resonance imaging (PC-MRI), or image-based computational fluid dynamics (CFD) simulations. Due to the important role of geometry in determining local flow patterns, it is also relevant to study geometric risk factors, which could potentially be used as a surrogate for hemodynamic conditions, to avoid expensive flow imaging and computations. This patent review focuses on: (1) current approaches of in vivo quantification of patient-specific shear stress conditions, including both direct flow imaging techniques and image-based CFD simulations; and (2) clinical evidence of shear stress conditions and geometric risk factors in the development of atherosclerosis.

The current clinical management of abdominal aortic aneurysm (AAA) disease is based to a great extent on measuring the aneurysm maximum diameter to decide when timely intervention is required. Decades of clinical evidence show that aneurysm diameter is positively associated with the probability of rupture, but that other parameters may also play a role in causing or predisposing the AAA to rupture. Biological factors associated with smooth muscle apoptosis are implicated in AAA expansion while geometric and biomechanical factors identified by means of computational modeling techniques have been positively correlated with rupture risk with a higher accuracy and sensitivity than maximum diameter alone. The objective of this review is to examine the factors found to influence AAA disease progression, clinical management and rupture, as well as a patent review that highlights developments in this arena in the past few years.

Cardiac applications of SPECT or PET imaging and Gated technique have a wide area of use in the field of nuclear cardiology. Throughout the last decade, rapid technological developments have occurred, and additional contributions to the patient administration and the cost-effectiveness of these radionuclide imaging methods have been shown. Regarding single or hybride cardiac imaging, including SPECT and PET methods with or without ECG-gated technique in field of nuclear cardiology with an extensive review, this article presents the current status in the technical background of nuclear tomographic imaging and in the areas of clinical practice, and intends to predict future developments on related patent forms.

Breast cancer is the most frequently diagnosed cancer in women all over the world. Patents have shown that cancer is the fifth cause of death worldwide, among other leading cancers, such as lung cancer, stomach cancer, liver cancer and colon cancer. In this paper, we present a method for extraction of the morphological and texture information and attribute selection for mass classification using the fusion of information from CC and MLO views. In the extraction stage, the wavelets coefficients and the singular value decomposition (SVD) technique were applied to reduce the number of texture attributes. From the segmented mass regions, we construct the mass morphological features set. The application of analysis of variance (ANOVA) also contributes to the reduction of the textural and morphological information. In the final stage, we used the Random Forest and Support Vector Machine algorithms for classifying masses in mammograms. The overall performances of the methods were evaluated by means of the area under the ROC curve (AUC). The experiments showed that the fusion of information of views contributed to increase of values of AUC. These results demonstrate that the proposed fusion of information and combination of descriptors contribute in the classification of breast lesions.