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Daniel Cowden

Publications and source records attributed to Daniel Cowden.

3 recordsLinked to original sources

Comparative study for the detection of peritubular capillary C4d deposition in human renal allografts using different methodologies.

Detection of peritubular capillary (PTC) C4d deposition in tissue sections of renal allograft biopsies became an important aid in the diagnosis of antibody-mediated rejection. Pathologists in many major transplant centers now routinely stain renal allograft biopsies for C4d. Currently, there are 3 commercially available antibodies. Two of these antibodies are monoclonal and are usually used with either a 3- or a 2-step indirect immunofluorescence (IF) methodology on frozen sections. A polyclonal antibody is used on formalin-fixed, paraffin-embedded tissue section with an immunoperoxidase detection system. The goal of our study was to compare these antibodies and methodologies in our renal allograft biopsy material. Twenty renal allograft biopsies with diffuse or focal PTC C4d staining, using immunofluorescence methods on frozen sections, were selected for this study. These biopsies were tested with the 3 commercially available anti-C4d antibodies (Biogenesis, Brentwood, Calif, cat no. 222-8004; Quidel Corporation, Santa Clara, Calif, cat no. A213; and ALPCO Diagnostic, Windham, NH, cat no. 004-BI-RC4D). Both monoclonal antibodies (Biogenesis and Quidel) were tested with a 3- and a 2-step indirect IF method on frozen sections. The polyclonal antibody (ALPCO) was applied to formalin-fixed paraffin sections using immunoperoxidase methodology. In selected cases, the polyclonal antibody was tested on frozen sections with a 3-step indirect IF method. To exclude possible false-negative staining with the IF method, we selected 10 additional biopsies that showed PTC margination of inflammatory cells, but were C4d-negative or only focally positive, and tested them with the ALPCO antibody on paraffin sections. We have found that all methodologies and antibodies tested provided adequate results with only minor differences between them. Perhaps the most sensitive method is the 3-step indirect IF on frozen sections using one of the monoclonal antibodies. We prefer the 2-step indirect IF method with the Quidel monoclonal antibody because of its simplicity, quick turnaround time, and relatively low cost. The advantages and disadvantages of the individual methodologies are discussed.

Antibodies↗

Pharmacokinetic mapping of breast tumors: a new statistical analysis technique for dynamic magnetic resonance imaging.

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.

Breast Neoplasms↗

Order sets utilization in a clinical order entry system.

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.

Forms and Records Control↗