ABSTRACT
Over a period of 3 years, 13 patients with Macrophage Activation Syndrome were seen. Most had underlying connective tissue disease or malignancy. High-grade fever, cytopenia and elevated transaminases were the common presenting manifestations. Elevated LDH and ferritin were characteristic. Due to low index of suspicion the diagnosis was delayed in majority of cases. Five of the 13 expired. Macrophage Activation Syndrome is associated with a high mortality and should be considered in the differential diagnosis of unexplained pancytopenia in-patients with connective tissue disease and malignancy.
Subject(s)
Lymphohistiocytosis, Hemophagocytic/diagnosis , Macrophage Activation , Adolescent , Adult , Aged , Bone Marrow/pathology , Child , Female , Humans , Male , Middle Aged , Retrospective Studies , SyndromeABSTRACT
Differential interference contrast (DIC) microscopy is a powerful visualization tool used to study live biological cells. Its use, however, has been limited to qualitative observations. The inherent nonlinear relationship between the object properties and the image intensity makes quantitative analysis difficult. Toward quantitatively measuring optical properties of objects from DIC images, we develop a method to reconstruct the specimen's optical properties over a three-dimensional (3-D) volume. The method is a nonlinear optimization which uses hierarchical representations of the specimen and data. As a necessary tool, we have developed and validated a computational model for the DIC image formation process. We test our algorithm by reconstructing the optical properties of known specimens.
ABSTRACT
Differential Interference Contrast (DIC) microscopy is a powerful visualization tool used to study live biological cells. Its use, however, has been limited to qualitative observations. The inherent non-linear relation between the object properties and the image intensity makes quantitative analysis difficult. As a first step towards measuring optical properties of objects from DIC images, we develop a model for the image formation process using methods consistent with energy conservation laws. We verify our model by comparing real image data of manufactured specimens to simulated images of virtual objects. As the next step, we plan to use this model to reconstruct the three-dimensional properties of unknown specimens.
