Correction for fast pseudo-diffusive fluid motion contaminations in diffusion tensor imaging

In this prospective study, we quantified the fast pseudo-diffusion contamination by blood perfusion or cerebrospinal fluid (CSF) intravoxel incoherent movements on the measurement of the diffusion tensor metrics in healthy brain tissue. Diffusion-weighted imaging (TR/TE = 4100 ms/90 ms; b-values: 0, 5, 10, 20, 35, 55, 80, 110, 150, 200, 300, 500, 750, 1000, 1300 s/mm2, 20 diffusion-encoding directions) was performed on a cohort of five healthy volunteers at 3 Tesla. The projections of the diffusion tensor along each diffusion-encoding direction were computed using a two b-value approach (2b), by fitting the signal to a monoexponential curve (mono), and by correcting for fast pseudo-diffusion compartments using the biexponential intravoxel incoherent motion model (IVIM) (bi). Fractional Anisotropy (FA) and Mean Diffusivity (MD) of the diffusion tensor were quantified in regions of interest drawn over white matter areas, gray matter areas, and the ventricles. A significant dependence of the MD from the evaluation method was found in all selected regions. A lower MD was computed when accounting for the fast-diffusion compartments. A larger dependence was found in the nucleus caudatus (bi: median 0.86 10-3 mm2/s, Δ2b: -11.2%, Δmono: -14.4%; p = 0.007), in the anterior horn (bi: median 2.04 10-3 mm2/s, Δ2b: -9.4%, Δmono: -11.5%, p = 0.007) and in the posterior horn of the lateral ventricles (bi: median 2.47 10-3 mm2/s, Δ2b: -5.5%, Δmono: -11.7%; p = 0.007). Also for the FA, the signal modeling affected the computation of the anisotropy metrics. The deviation depended on the evaluated region with significant differences mainly in the nucleus caudatus (bi: median 0.15, Δ2b: +39.3%, Δmono: +14.7%; p = 0.022) and putamen (bi: median 0.19, Δ2b: +3.1%, Δmono: +17.3%; p = 0.015). Fast pseudo-diffusive regimes locally affect diffusion tensor imaging (DTI) metrics in the brain. Here, we propose the use of an IVIM-based method for correction of signal contaminations through CSF or perfusion

Systematic analysis of changes in radiomics features during dynamic breast-MRI: Evaluation of specific biomarkers

OBJECTIVES In this retrospective, single-center study we investigate the changes of radiomics features during dynamic breast-MRI for healthy tissue compared to benign and malignant lesions. METHODS 60 patients underwent breast-MRI using a dynamic 3D gradient-echo sequence. Changes of 34 texture features (TF) in 30 benign and 30 malignant lesions were calculated for 5 dynamic datasets and corresponding 4 subtraction datasets. Statistical analysis was performed with ANOVA, and systematic changes in features were described by linear and polynomial regression models. RESULTS ANOVA revealed significant differences (p < 0.05) between normal tissue and lesions in 13 TF, compared to 9 TF between benign and malignant lesions. Most TF showed significant differences in early dynamic and subtraction datasets. TF associated with homogeneity were suitable to discriminate between healthy parenchyma and lesions, whereas run-length features were more suitable to discriminate between benign and malignant lesions. Run length nonuniformity (RLN) was the only feature able to distinguish between all three classes with an AUC of 88.3%. Characteristic changes were observed with a systematic increase or decrease for most TF with mostly polynomial behavior. Slopes showed earlier peaks in malignant lesions, compared to benign lesions. Mean values for the coefficient of determination were higher during subtraction sequences, compared to dynamic sequences (benign: 0.98 vs 0. 72; malignant: 0.94 vs 0.74). CONCLUSIONS TF of breast lesions follow characteristic patterns during dynamic breast-MRI, distinguishing benign from malignant lesions. Early dynamic and subtraction datasets are particularly suitable for texture analysis in breast-MRI. Features associated with tissue homogeneity seem to be indicative of benign lesions

Differential functional benefits of ultra highfield MR systems within the language network

Several investigations have shown limitations of fMRI reliability with the current standard field strengths. Improvement is expected from ultra highfield systems but studies on possible benefits for cognitive networks are lacking. Here we provide an initial investigation on a prominent and clinically highly-relevant cognitive function: language processing in individual brains. 26 patients evaluated for presurgical language localization were investigated with a standardized overt language fMRI paradigm on both 3T and 7T MR scanners. During data acquisition and analysis we made particular efforts to minimize effects not related to static magnetic field strength differences. Six measures relevant for functional activation showed a large dissociation between essential language network nodes: although in Wernicke's area 5/6 measures indicated a benefit of ultra highfield, in Broca's area no comparison was significant. The most important reason for this discrepancy was identified as being an increase in susceptibility-related artifacts in inferior frontal brain areas at ultra high field. We conclude that functional UHF benefits are evident, however these depend crucially on the brain region investigated and the ability to control local artifacts

Erythropoietin, uncertainty principle and cancer related anaemia

BACKGROUND: This study was designed to evaluate if erythropoietin (EPO) is effective in the treatment of cancer related anemia, and if its effect remains unchanged when data are analyzed according to various clinical and methodological characteristics of the studies. We also wanted to demonstrate that cumulative meta-analysis (CMA) can be used to resolve uncertainty regarding clinical questions. METHODS: Systematic Review (SR) of the published literature on the role of EPO in cancer-related anemia. A cumulative meta-analysis (CMA) using a conservative approach was performed to determine the point in time when uncertainty about the effect of EPO on transfusion-related outcomes could be considered resolved. Participants: Patients included in randomized studies that compared EPO versus no therapy or placebo. Main outcome measures: Number of patients requiring transfusions. RESULTS: Nineteen trials were included. The pooled results indicated a significant effect of EPO in reducing the number of patients requiring transfusions [odds ratio (OR) = 0.41; 95%CI: 0.33 to 0.5; p < 0.00001;relative risk (RR) = 0.61; 95% CI: 0.54 to 0.68]. The results remain unchanged after the sensitivity analyses were performed according to the various clinical and methodological characteristics of the studies. The heterogeneity was less pronounced when OR was used instead of RR as the measure of the summary point estimate. Analysis according to OR was not heterogeneous, but the pooled RR was highly heterogeneous. A stepwise metaregression analysis did point to the possibility that treatment effect could have been exaggerated by inadequacy in allocation concealment and that larger treatment effects are seen at hb level > 11.5 g/dl. We identified 1995 as the point in time when a statistically significant effect of EPO was demonstrated and after which we considered that uncertainty about EPO efficacy was resolved. CONCLUSION: EPO is effective in the treatment of anemia in cancer patients. This could have already been known in 1995 if a CMA had been performed at that time

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

Analysis of renal diffusion-weighted imaging (DWI) using apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models

Analysis of renal diffusion-weighted imaging (DWI) data to derive markers of tissue properties requires careful consideration of the type, extent, and limitations of the acquired data. Alongside data quality and general suitability for quantitative analysis, choice of diffusion model, fitting algorithm, and processing steps can have consequences for the precision, accuracy, and reliability of derived diffusion parameters. Here we introduce and discuss important steps for diffusion-weighted image processing, and in particular give example analysis protocols and pseudo-code for analysis using the apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models. Following an overview of general principles, we provide details of optional steps, and steps for validation of results. Illustrative examples are provided, together with extensive notes discussing wider context of individual steps, and notes on potential pitfalls.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure