A comprehensive review of MR imaging changes following radiosurgery to 500 brain metastases.

BACKGROUND AND PURPOSE: Stereotactic radiosurgery is known to control 85%-95% of intracranial metastatic lesions during a median survival of 6-8 months. However, with the advent of newer systemic cancer therapies, survival is improving; this change mandates a longitudinal quantitative analysis of the radiographic response of brain metastases to radiosurgery. MATERIALS AND METHODS: MR imaging of 516 metastases in 120 patients treated with GK-SRS from June 2006 to December 2009 was retrospectively reviewed. Lesion volume at initial treatment and each follow-up was calculated by using the following formula: length × width × height / 2. Volume changes were correlated with patient demographics, histopathology, and radiation treatment variables. RESULTS: Thirty-two percent of lesions increased in volume following radiosurgery. Clinically, this translated into 54% of patients having ≥1 of their lesions increase in size. This increase begins at 6 weeks and can last beyond 15 months' post-SRS. Male sex (P = .002), mean voxel dose <37 Gy (P = .009), and initial treatment volume >500 mm(3) (P < .001) are associated with posttreatment increases in tumor size. Median survival following radiosurgery was 9.5 months for patients with all lesions exhibiting stable/decreased volumes, >18.4 months for patients with all lesions exhibiting increased volumes, and 16.4 months for patients with mixed lesional responses. CONCLUSIONS: Most metastatic lesions are stable or smaller in size during the first 36 months post-SRS. However, a transient increase in volume is seen in approximately one-third of lesions. Sex, treatment dose, initial lesion size, and histopathology all correlate with variations in lesion volume post-SRS. The longer the patient survives, the more likely an increase in lesion size will be seen on follow-up imaging.

Detection of mycobacterial lipoarabinomannan with an antigen-capture ELISA in unprocessed urine of Tanzanian patients with suspected tuberculosis.

A direct antigen-capture ELISA based on the detection of mycobacterial lipoarabinomannan (LAM) in unprocessed urine was evaluated for its usefulness in clinical practice. In Tanzania, 231 patients with suspected pulmonary tuberculosis (TB) and 103 healthy volunteers were screened with standard TB tests and with the new LAM-ELISA. Of 132 patients with confirmed pulmonary mycobacterial disease (positive sputum culture), 106 were positive using the LAM-ELISA (sensitivity 80.3%). In comparison, the sensitivity of acid-fast bacilli (AFB) sputum microscopy was 62.1% (82 of 132 confirmed cases). Of the 231 patients, 17 were both culture- and AFB-negative, but had typical radiographic signs of pulmonary mycobacterial infection and did not respond to antibiotic treatment. Of these 17 patients, 13 (76.5%) had positive LAM-ELISA test results. To define the specificity of the assay, urine samples from 103 healthy volunteers were also screened using LAM-ELISA. All but one had an optical density below the cut-off (specificity 99%). Of interest was a significant correlation between level of microscopic density of mycobacteria in sputum and LAM antigen concentration in urine (chi2=8.44). The LAM-ELISA is a field-adapted tool that can improve screening standards in countries with a high incidence of TB.

Effect of environmental factors and of the proportion of Holstein blood on the milk yield and lactation length of crossbred dairy cattle on smallholder farms in north-east Tanzania.

A study was carried out on the lactation performance of crossbred dairy cattle in a smallholder farming system in north-east Tanzania. Data were collected from the records for 6 years and the factors considered were district, proportion of Holsteins, season of calving, year of calving and herd size. The data were considered separately for animals with a single lactation record. The least-square means for first lactation length and yield were 331 days (SD 77.0) and 2332 L (SD 283.0), respectively, while for cows with data on more than one lactation record the yield was 2477 L (SD 840.1) in 324 days (SD 74.0). First lactation yield was significantly affected by year of calving. For repeated records, the lactation yield was significantly affected by district, proportion of Holsteins and herd size, while lactation length was significantly affected by district and herd size. The calculated repeatabilities for lactation yield and length were 0.27 and 0.12, respectively. For the pooled data, the correlation between lactation length and yield gave r = 0.569 (p < 0.0001).

HIV type 1 V3 serotyping of Tanzanian samples: probable reasons for mismatching with genetic subtyping.

HIV-1 V3 serotyping is used to classify immunodeficiency viruses on the basis of antibody binding to V3 peptides derived from env genetic subtypes. Although it shows a reasonable overlap, it has been reported to be distinct from viral genetic subtypes. The aim of this study is to determine the feasibility of HIV-1 serotyping to predict genetic subtypes in an East African setting, where multiple HIV-1 subtypes have coexisted for many years. HIV-1 genetic subtypes of 86 AIDS patients in Mbeya Town, southwest Tanzania, were determined, using env nucleic acid sequencing as the basis for comparison. Those data were compared with V3 serotyping results obtained by four different methodologies. Four HIV-1 genetic subtypes were identified, including A (25, 29%), C (47, 55%), D (13, 15%), and G (1, 1%). The sensitivity and specificity of those serotyping assays varied considerably: sensitivity for genetic subtype A (40-48%), C (52-96%), and D (9-31%); and specificity for genetic subtype A (77-95%), C (46-63%), and D (97-100%). We further tried to identify reasons for the discrepancies between serotyping results and genetic subtypes. By means of logistic regression analysis three amino acid residues within the V3 loop (positions 12, 13, and 19; V, H, and A for serotype A, I, R, and T for serotype C) were found to be most important for antibody binding; a deviation from the subtype-specific amino acids was highly related to mismatched results. In addition, we have shown that phenetic analysis of V3 amino acid sequence data could be used to predict the majority of V3 serotypes (93-94%). Our data demonstrated that for the majority of specimens HIV-1 V3 serotyping results closely match the subtype of the analyzed sample as revealed by the V3 loop amino acid sequence. However, our data demonstrate that HIV-1 serotyping is not sufficiently accurate to predict genetic subtypes in Tanzania, where subtypes A, C, D, and G are circulating. This was due to highly similar amino acid sequences throughout the prevalent genetic subtypes, which caused the inability of HIV-1 V3 serotyping to differentiate subtype A from C as well as D from C. Instead, the serotyping results reflect the frequency distribution of V3 serotypes. To investigate HIV-1 genetic subtypes in population-based studies in this African setting additional or modified algorithms are needed.

PIP: HIV-1 V3 serotyping is used to classify immunodeficiency viruses on the basis of antibody binding to V3 peptides derived from env genetic subtypes. Findings are reported from a study conducted to determine whether HIV-1 serotyping could be effectively used to predict genetic subtypes in an East African setting, where multiple HIV-1 subtypes have coexisted for many years. The HIV-1 genetic subtypes of 86 people with AIDS in Mbeya Town, southwest Tanzania, were determined, using env nucleic acid sequencing as the basis for comparison. Those data were then compared with V3 serotyping results obtained by analysis with tests manufactured by Behring and the Pettenkofer Institute, tests conducted by St. Mary's Hospital Medical School, tests conducted by Georg-Speyer-Haus, and tests conducted by Universite Francois Rabelais. The following HIV-1 genetic subtypes were identified: 25 cases of A (29%), 47 of C (55%), 13 of D (15%), and 1 of G (1%). The sensitivity and specificity of the serotyping assays varied considerably. These data indicate that HIV-1 serotyping is not accurate enough to predict genetic subtypes in Tanzania. This conclusion was reached based upon the highly similar amino acid sequences throughout the prevalent genetic subtypes, which caused the inability of HIV-1 V3 serotyping to differentiate subtype A from C as well as D from C. The serotyping results instead reflect the frequency distribution of V3 serotypes.