Although conventional cytology is useful when diagnosing oral PML (better sensitivity and predictive positive value if compared with the cervical smear test with similar specificity) and can improve the accuracy of histological diagnosis, liquid-based cytology gives better results, as it not only enhances both sensitivity and specificity, but also provides material for further investigation (AgNORs, DNA, microbiopsies, etc.).

The negative predictive value (97.33%) suggests that micro-biopsy may well be an effective first-level diagnostic procedure for PMLs (especially in follow-ups and multiple lesions); moreover, in carcinoma (17% of cases) a definitive diagnosis could be made without further investigation.

A strict plaque control program play a pivotal role in the management of transplant patients exhibiting cyclosporin A-GO.

Introduction Better methods are needed to determine the course of intervention in patients with atherosclerosis; therefore, plaque characterization is increasing in importance. Current guidelines suggest that the degree of stenosis and symptoms are the only criteria for the selection of the surgical intervention. However, there remain some challenges. The characterization of plaque morphology may help determine the best course of therapy. Magnetic resonance imaging and computed tomography are current standard techniques to evaluate plaque morphology, but they are expensive and unsuitable for long term surveillance and monitoring. Objective In this research, an ultrasound-based methodology for the characterization of carotid plaques is shown. This technique requires the injection of a small volume (approximately 1.5 mL) of contrast agent and the acquisition of postcontrast images. The rationale of this technique is that poorly perfused tissues (such as lipids) show a lower contrast enhancement with respect to highly perfused tissues (such as fibrous and muscular tissue). Methods The technique consists of two steps. First, the plaque region is automatically segmented by a completely user-independent algorithm. Then, the portion of the wall corresponding to the plaque is analyzed and color-coded intensity is assigned to a specific tissue. Performance evaluation was performed against histology. Twenty plaque specimens were sent to pathology for reporting. Correlation of the histology report and of the contrast-enhanced ultrasound analysis was performed. Results Plaque components that could be effectively identified were thrombi, lipids, fibrous/muscular tissue, and calcium. Overall the errors on 20 plaques between automated classification and histology were: 3.1 ± 1.1% for thrombus, 4.2 ± 1.5% for lipids, 5 ± 3.4% for fibrous/muscular tissue, and 3.2 ± 1.0% for calcium. Conclusion Despite the need for further investigation and a quantitative evaluation of the results, this methodology showed encouraging results. This analysis architecture is undergoing validation in a neurology division and is aimed at being used for the follow-up of patients and quantification of drug therapy effects.

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