PubMed · 16750718
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Raymond J Kim. 2006-06-06. Diagnostic testing.. https://doi.org/10.1016/j.jacc.2006.04.046
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In most patients with heart disease left ventricular dysfunction is the principle physiologic disorder leading to heart failure and is an important prognostic factor. Various imaging methods have been developed for the evaluation of left ventricular function and a substantial body of literature is available describing these methods. The right ventricle (RV) may be predominantly involved in certain cardiac or pulmonary pathological conditions such as arrhythmogenic right ventricular cardiomyopathy or pulmonary hypertension. Also in many congenital or acquired cardiac diseases primarily affecting the left ventricle (LV), right heart involvement has an important role in disease prognosis. The RV is difficult to evaluate using two-dimensional (2D) cross-sectional imaging modalities due to its complex shape and orientation. Cardiovascular magnetic resonance imaging (CMR) is a virtually three-dimensional (3D) tomographic technique which has entered the mainstream of clinical cardiovascular imaging over the last decade. Compared to other imaging methods CMR allows the accurate quantification of RV volumes, myocardial mass, and transvalvular flow with the added benefit of tissue characterisation and without the use of ionising radiation. The manuscript presents a review of the contemporary use of CMR for the evaluation of right heart involvement in various cardio-pulmonary diseases.
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The completion of the Human Genome Project and the ongoing sequencing of mouse, rat, and other genomes have led to an explosion of genetics-related technologies that are finding their way into all areas of biological research in both basic sciences and clinical applications. High-throughput genomics and proteomics technology has been quickly adapted to develop tools for clinical and pharmacological applications. Because molecular alterations usually occur much earlier than histological, physiological, and clinical abnormality, researchers hope to extend the applications of genomics and/or proteomics technology to early diagnosis of diseases and clinical outcome prognosis. Recently, some successful attempts in molecular diagnosis or prognosis have been published. However, for such tests to be translated from the bench to the bed, they must meet some rigorous standards. To develop a clinically meaningful genomics-based diagnostic test, we must have good study design, appropriate statistical analyses, and valid assessment of its clinical efficacy. In this chapter, we discuss statistical considerations on the process of developing reliable and useful genomics- or proteomics-based tests.