Blood Transfusion Requirements for Patients With Sarcomas Undergoing Combined Radio- and Chemotherapy

Patients with bony and soft tissue sarcomas may require intensive treatment with chemotherapy and radiotherapy, which often leads to a fall in haemoglobin levels, requiring blood transfusion. There may be advantages in predicting which patients will require transfusion, partly because anaemia and hypoxia may worsen the response of tumours to chemotherapy and radiotherapy. Between 1997 and 2003, a total of 26 patients who received intensive treatment with curative intent were identified. Transfusions were given to maintain the haemoglobin at 10g/dl or above during chemotherapy, and at 12 g/dl or above during radiotherapy. Eighteen (69%) required a transfusion, the majority as a result of both the chemotherapy and RT criteria. There were 78 transfusion episodes, and 181 units of blood given. In the 18 patients who required transfusion, the average number of units was 10.1, but seven patients required more blood than this. The most significant factor influencing blood transfusion was choice of intensive chemotherapy. Intensive chemotherapy and presenting Hb less than 11.6 g/dl identified 13 out of 18 patients who needed transfusion. Adding a drop in haemoglobin of greater than 1.7 g/dl after one cycle of chemotherapy identified 16 out of 18 patients who required transfusion. The seven patients who had heavy transfusion requirements were identified by age 32 or less, intensive chemotherapy and a presenting Hb of 12 g/dl or less. Erythropoietin might be a useful alternative to transfusion in selected patient groups, especially those with heavy transfusion requirements

Assessment of Cervical Cancer with a Parameter-Free Intravoxel Incoherent Motion Imaging Algorithm

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MRI texture features may predict differentiation and nodal stage of cervical cancer: a pilot study

BACKGROUND: Texture analysis in oncological magnetic resonance imaging (MRI) may yield surrogate markers for tumor differentiation and staging, both of which are important factors in the treatment planning for cervical cancer. PURPOSE: To identify texture features which may predict tumor differentiation and nodal status in diffusion-weighted imaging (DWI) of cervical carcinoma. MATERIAL AND METHODS: Twenty-three patients were enrolled in this prospective, institutional review board (IRB)-approved study. Pelvic MRI was performed at 3-T including a DWI echo-planar sequence with b-values 40, 300, and 800 s/mm2. Apparent diffusion coefficient (ADC) maps were used for region of interest (ROI)-based texture analysis (32 texture features) of tumor, muscle, and fat based on histogram and gray-level matrices (GLM). All features confounded by the ROI size (linear model) were excluded. The remaining features were examined for correlations with histological differentiation (Spearman) and nodal status (Kruskal-Wallis). Hierarchical cluster analysis was used to identify correlations between features. A P value < 0.05 was considered statistically significant. RESULTS: Mean age was 55 years (range = 37-78 years). Biopsy revealed two well-differentiated, eight moderately differentiated, two moderately to poorly differentiated tumors, and five poorly differentiated tumors. Six tumors could not be graded. Lymph nodes were involved in 11 patients. Three GLM features correlated with the differentiation: LRHGE (ϱ = 0.53, P = 0.03), ZP (ϱ = -0.49, P < 0.05), and SZE (ϱ = -0.51, P = 0.04). Two histogram features, skewness (0.65 vs. 1.08, P = 0.04) and kurtosis (0.53 vs. 1.67, P = 0.02), were higher in patients with positive nodal status. Cluster analysis revealed several co-correlations. CONCLUSION: We identified potentially predictive GLM features for histological tumor differentiation and histogram features for nodal cancer stage