Survival analysis of 97 cats with nasal lymphoma: a multi-institutional retrospective study (1986-2006).

BACKGROUND: Feline nasal lymphoma (NLSA) is a condition for which no standard of care exists. HYPOTHESIS: There is no difference in survival times of cats with NLSA treated with single or multimodality therapy. ANIMALS: Records from 97 cats diagnosed with NLSA were examined. METHODS: The purpose of this retrospective study was to compare the survival times of cats with NLSA treated with radiation therapy (RT) alone, chemotherapy alone, or RT + chemotherapy and identify potential prognostic variables that affected survival. Cats were grouped according to therapy: RT + chemotherapy (n = 60), RT alone (n = 19), or chemotherapy alone (n = 18). RESULTS: Survival was calculated with 2 methods. The 1st survival analysis (method A) included all cats, but counted only deaths caused by progressive NLSA. The median survival time (MST), regardless of therapy modality, was 536 days. The 2nd survival analysis (method B) also included all cats and counted all deaths, regardless of cause, as events. The overall MST calculated for all deaths was 172 days. A negative independent prognostic variable identified was anemia (P < .001), and positive independent prognostic variables were a complete response to therapy (P < .001) and total radiation dose >32 Gy (P= .03). CONCLUSIONS AND CLINICAL IMPORTANCE: There were no significant differences in survival times among the 3 treatment groups but these results suggest that the addition of higher doses of RT to a cat's treatment protocol may control local disease and therefore influence survival.

Mapping therapeutic response in a patient with malignant glioma.

Short-interval scanning of patients offers a detailed understanding of the natural progression of tumor tissue, as revealed through imaging markers such as contrast enhancement and edema, prior to therapy. Following treatment, short-interval scanning can also provide evidence of attenuation of growth rates. We present a longitudinal imaging study of a patient with glioblastoma multiforme (GBM) scanned 15 times in 104 days on a 3 T MR scanner. Images were analyzed independently by two automated algorithms capable of creating detailed maps of tumor changes as well as volumetric analysis. The algorithms, a nearest-neighbor-based tissue segmentation and a surface-modeling algorithm, tracked the patient's response to temozolomide, showing an attenuation of growth. The need for surrogate imaging end-points, of which growth rates are an example, is discussed. Further, the strengths of these algorithms, the insight gained by short-interval scanning, and the need for a better understanding of imaging markers are also described.

Tracking tumor growth rates in patients with malignant gliomas: a test of two algorithms.

BACKGROUND AND PURPOSE: Two 3D image analysis algorithms, nearest-neighbor tissue segmentation and surface modeling, were applied separately to serial MR images in patients with glioblastoma multiforme (GBM). Rates of volumetric change were tracked for contrast-enhancing tumor tissue. Our purpose was to compare the two image analysis algorithms in their ability to track tumor volume relative to a manually defined standard of reference. METHODS: Three-dimensional T2-weighted and contrast-enhanced T1-weighted spoiled gradient-echo MR volumes were acquired in 10 patients with GBM. One of two protocols was observed: 1) a nearest-neighbor algorithm, which used manually determined or propagated tags and automatically segmented tissues into specific classes to determine tissue volume; or 2) a surface modeling algorithm, which used operator-defined contrast-enhancing boundaries to convert traced points into a parametric mesh model. Volumes were automatically calculated from the mesh models. Volumes determined by each algorithm were compared with the standard of reference, generated by manual segmentation of contrast-enhancing tissue in each cross section of a scan. RESULTS: Nearest-neighbor algorithm enhancement volumes were highly correlated with manually segmented volumes, as were growth rates, which were measured in terms of halving and doubling times. Enhancement volumes generated by the surface modeling algorithm were also highly correlated with the standard of reference, although growth rates were not. CONCLUSION: The nearest-neighbor tissue segmentation algorithm provides significant power in quantifying tumor volume and in tracking growth rates of contrast-enhancing tissue in patients with GBM. The surface modeling algorithm is able to quantify tumor volume reliably as well.

Spontaneous expression of fra(10)(q25) in bone marrow from a patient with agranulocytosis.

We report on the spontaneous expression of fra(10)(q25) in bone marrow from a patient with agranulocytosis. Expression of this fragile site in both bone marrow and leukocytes was enhanced by bromodeoxyuridine (BrdU), while folic-acid-deficient medium enhanced the expression of fra(10)(q25) only in leukocytes. Variability in the expression of fra(10)(q25) in bone marrow and leukocyte cultures over an 18-month period was also found.

Brief clinical report: neural tube defects in dup(11q).

We describe clinically and cytogenetically a fetus with multiple congenital anomalies and partial dup(11q) born to a phenotypically normal mother with a 3:1 translocation. Fetal anomalies included complete cleft of lip and palate, small penis, myelomenigocele, and abnormal palmar creases. We think chromosome analysis should be performed when neural tube defects are observed in otherwise dysmorphic neonates, stillbirths, and abortuses.