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Context.--Amyloidosis represents a group of diseases with extracellular deposition of congophilic fibrils of similar morphology but differing chemical composition. The types commonly involving the kidney are AL (light chain amyloid) and AA (serum amyloid A). Familial amyloidosis can also affect the kidney, but we have not encountered such a case during the study period. Distinguishing between the AL and AA forms of amyloid is clinically important because of the different treatments and outcomes. The classification of amyloidosis is made by immunostaining with antibodies to [kappa] and [lambda] immunoglobulin light chains and for serum amyloid A protein. Objective.--To draw attention to the nonspecific immunofluorescence staining patterns in renal biopsies with amyloidosis, causing potential diagnostic pitfalls. Design.--Renal biopsies from 15 patients, including 13 cases of AL and 2 cases of AA amyloidosis, were studied. Immunofluorescence staining with routine antibody panel and immunoperoxidase staining for amyloid A were performed. Results.--Of the 13 cases of AL amyloidosis, 2 cases showed little difference in staining intensity between [kappa] and [lambda] light chains (2+ and 3 + , respectively) and 4 cases showed only moderate intensity (2+) of the predominant light chain. The 2 cases diagnosed as AA amyloidosis also exhibited staining for light chains. One case had strong (3+) signal for [kappa] and moderate (2+) for [lambda] light chain, while the other showed weaker staining. Conclusions.--Immunofluorescence staining for immunoglobin light chains on renal biopsy, as the first step to differentiate between AL and AA amyloidosis, may sometimes be inconclusive or even misleading. Applying amyloid A immunostain on a routine basis and detailed clinical history are essential to avoid misclassification. (Arch Pathol Lab Med. 2007;131:917-922), Amyloidosis is a generic term for a group of diseases that have in common tissue deposits of extracellular fibrillar proteins of similar ultrastructure, different chemical composition, and different etiologies. Amyloidosis [...]

Breast cancer is the most common malignancy among women, constituting a major health problem. Different MRI techniques have been investigated in the past in order to improve the detection and diagnosis of breast tumors. One such technique is the dynamic contrast-enhanced T1-weighted magnetic resonance imaging (DCE-MRI), using diffusible CM (contrast media), such as Gd-DTPA. Here we employ a two compartment CM kinetics model (blood plasma and surrounding interstitial space being the two compartments), where the exchange of contrast agent between these compartments is bidirectionally linear. In this study we use images from 29 suspected breast carcinoma patients who underwent whole breast DCE-MRI. Each of these studies has 64 coronal sections of the whole breast, taken at 6 or 7 time points (the sampling period being about 2 minutes). Subsequent histo-pathological analysis of these patients reveal: 22 intraductal carcinomas (IDC), 3 intralobular carcinomas (ILC), 2 ductal carcinomas in-situ (DCIS) and 3 benign tumors.

Cancer is the second leading cause of death among Americans. It is estimated that 1.28 million new Americans are diagnosed with cancer annually (1). The estimated overall annual cost of cancer being $171 Billion (1). Decreasing the costs of the screening and diagnostic tests will automatically decrease the total cost of cancer by limiting not only the direct medical costs but also by containing the indirect costs of morbidity and mortality. New screening and diagnostic tests are obviously needed. Screening methods are emerging in the evaluation of proteomic patterns. In proteomic pattern analysis, we can screen for not only one cancer but a chip may be able to screen for multiple cancers. New screening and diagnostic methods (2) investigated by NCI and FDA (3) (4) are correlating gene and protein expression patterns for early detection of cancer. Many papers have been published in the last 12 months (3) (4) (5) utilizing this new technique of molecular analysis in screening and diagnosing cancers with high sensitivity and specificity.

An order set is a predefined template that has been utilized in the standard care of hospitals for many years. While in the past, it took the form of pen and paper, today, it is, indeed, electronic. Within order sets are distinct ordering patterns that may yield fruitful results for clinicians and informaticians, alike. Protocols like there electronic counterpart, order sets, provide an 'indication' identifying the clinical scenario of the patient's condition when the ordering event occurred. This 'indication' is rarely captured by individual orders, and provides difficult challenges to developers of information systems. While mandating an 'indication' be entered for every medication or lab order makes the job much more tasking on the physician provider, it is appealing to researchers and accountants. We have attempted to bypasses that consideration by identifying ordering patterns that predict diagnostic related codes (DRGs) and diagnostic codes which would greatly facilitate the information gathering process and still provide a flexible and user friendly physician interface.