48 research outputs found

    Early prediction of response to radiotherapy and androgen-deprivation therapy in prostate cancer by repeated functional MRI: a preclinical study

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    <p>Abstract</p> <p>Background</p> <p>In modern cancer medicine, morphological magnetic resonance imaging (MRI) is routinely used in diagnostics, treatment planning and assessment of therapeutic efficacy. During the past decade, functional imaging techniques like diffusion-weighted (DW) MRI and dynamic contrast-enhanced (DCE) MRI have increasingly been included into imaging protocols, allowing extraction of intratumoral information of underlying vascular, molecular and physiological mechanisms, not available in morphological images. Separately, pre-treatment and early changes in functional parameters obtained from DWMRI and DCEMRI have shown potential in predicting therapy response. We hypothesized that the combination of several functional parameters increased the predictive power.</p> <p>Methods</p> <p>We challenged this hypothesis by using an artificial neural network (ANN) approach, exploiting nonlinear relationships between individual variables, which is particularly suitable in treatment response prediction involving complex cancer data. A clinical scenario was elicited by using 32 mice with human prostate carcinoma xenografts receiving combinations of androgen-deprivation therapy and/or radiotherapy. Pre-radiation and on days 1 and 9 following radiation three repeated DWMRI and DCEMRI acquisitions enabled derivation of the apparent diffusion coefficient (ADC) and the vascular biomarker <it>K</it><sup>trans</sup>, which together with tumor volumes and the established biomarker prostate-specific antigen (PSA), were used as inputs to a back propagation neural network, independently and combined, in order to explore their feasibility of predicting individual treatment response measured as 30 days post-RT tumor volumes.</p> <p>Results</p> <p>ADC, volumes and PSA as inputs to the model revealed a correlation coefficient of 0.54 (p < 0.001) between predicted and measured treatment response, while <it>K</it><sup>trans</sup>, volumes and PSA gave a correlation coefficient of 0.66 (p < 0.001). The combination of all parameters (ADC, <it>K</it><sup>trans</sup>, volumes, PSA) successfully predicted treatment response with a correlation coefficient of 0.85 (p < 0.001).</p> <p>Conclusions</p> <p>We have in a preclinical investigation showed that the combination of early changes in several functional MRI parameters provides additional information about therapy response. If such an approach could be clinically validated, it may become a tool to help identifying non-responding patients early in treatment, allowing these patients to be considered for alternative treatment strategies, and, thus, providing a contribution to the development of individualized cancer therapy.</p

    MRI of the lung (3/3)-current applications and future perspectives

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    BACKGROUND: MRI of the lung is recommended in a number of clinical indications. Having a non-radiation alternative is particularly attractive in children and young subjects, or pregnant women. METHODS: Provided there is sufficient expertise, magnetic resonance imaging (MRI) may be considered as the preferential modality in specific clinical conditions such as cystic fibrosis and acute pulmonary embolism, since additional functional information on respiratory mechanics and regional lung perfusion is provided. In other cases, such as tumours and pneumonia in children, lung MRI may be considered an alternative or adjunct to other modalities with at least similar diagnostic value. RESULTS: In interstitial lung disease, the clinical utility of MRI remains to be proven, but it could provide additional information that will be beneficial in research, or at some stage in clinical practice. Customised protocols for chest imaging combine fast breath-hold acquisitions from a "buffet" of sequences. Having introduced details of imaging protocols in previous articles, the aim of this manuscript is to discuss the advantages and limitations of lung MRI in current clinical practice. CONCLUSION: New developments and future perspectives such as motion-compensated imaging with self-navigated sequences or fast Fourier decomposition MRI for non-contrast enhanced ventilation- and perfusion-weighted imaging of the lung are discussed. Main Messages • MRI evolves as a third lung imaging modality, combining morphological and functional information. • It may be considered first choice in cystic fibrosis and pulmonary embolism of young and pregnant patients. • In other cases (tumours, pneumonia in children), it is an alternative or adjunct to X-ray and CT. • In interstitial lung disease, it serves for research, but the clinical value remains to be proven. • New users are advised to make themselves familiar with the particular advantages and limitations

    Bias in MRI Measurements of Apparent Diffusion Coefficient and Kurtosis: Implications for Choice of Maximum Diffusion Encoding

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    Tissue water diffusion is non-Gaussian and the expressions used to calculate diffusion parameters are approximations which introduce systematic errors dependent on the maximum diffusion encoding, diffusion time, etc. This study aimed at characterizing biases in estimates of both apparent diffusion coefficient and kurtosis, and determines their dependence on these parameters. Similar to the approach of several previous studies, Taylor expansion of the diffusion signal was used to calculate biases. Predicted errors were compared with data from one volunteer. Predicted errors agreed well with the measured errors and also the published diffusion tensor imaging measurements. The equations derived predict biases in measured diffusion parameters and explain much of the discrepancy between measurements obtained with different acquisition protocols. The equations may also be used to choose appropriate diffusion encoding for diffusion weighted, tensor, and kurtosis imaging

    Supine posture changes lung volumes and increases ventilation heterogeneity in cystic fibrosis

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    INTRODUCTION: Lung Clearance Index (LCI) is recognised as an early marker of cystic fibrosis (CF) lung disease. The effect of posture on LCI however is important when considering longitudinal measurements from infancy and when comparing LCI to imaging studies. METHODS: 35 children with CF and 28 healthy controls (HC) were assessed. Multiple breath washout (MBW) was performed both sitting and supine in triplicate and analysed for LCI, Scond, Sacin, and lung volumes. These values were also corrected for the Fowler dead-space to create 'alveolar' indices. RESULTS: From sitting to supine there was a significant increase in LCI and a significant decrease in FRC for both CF and HC (p<0.01). LCI, when adjusted to estimate 'alveolar' LCI (LCIalv), increased the magnitude of change with posture for both LCIalv and FRCalv in both groups, with a greater effect of change in lung volume in HC compared with children with CF. The % change in LCIalv for all subjects correlated significantly with lung volume % changes, most notably tidal volume/functional residual capacity (Vtalv/FRCalv (r = 0.54,p<0.001)). CONCLUSION: There is a significant increase in LCI from sitting to supine, which we believe to be in part due to changes in lung volume and also increasing ventilation heterogeneity related to posture. This may have implications in longitudinal measurements from infancy to older childhood and for studies comparing supine imaging methods to LCI

    Neoadjuvant chemotherapy in breast cancer: early response prediction with quantitative MR imaging and spectroscopy.

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    A prospective study was undertaken in women undergoing neoadjuvant chemotherapy for locally advanced breast cancer in order to determine the ability of quantitative magnetic resonance imaging (MRI) and proton spectroscopy (MRS) to predict ultimate tumour response (percentage decrease in volume) or to detect early response. Magnetic resonance imaging and MRS were carried out before treatment and after the second of six treatment cycles. Pharmacokinetic parameters were derived from T1-weighted dynamic contrast-enhanced MRI, water apparent diffusion coefficient (ADC) was measured, and tissue water:fat peak area ratios and water T2 were measured using unsuppressed one-dimensional proton spectroscopic imaging (30 and 135 ms echo times). Pharmacokinetic parameters and ADC did not detect early response; however, early changes in water:fat ratios and water T2 (after cycle two) demonstrated substantial prognostic efficacy. Larger decreases in water T2 accurately predicted final volume response in 69% of cases (11/16) while maintaining 100% specificity and positive predictive value. Small/absent decreases in water:fat ratios accurately predicted final volume non-response in 50% of cases (3/6) while maintaining 100% sensitivity and negative predictive value. This level of accuracy might permit clinical application where early, accurate prediction of non-response would permit an early change to second-line treatment, thus sparing patients unnecessary toxicity, psychological morbidity and delay of initiation of effective treatment

    Genomic Sequence Analysis of Granulovirus Isolated from the Tobacco Cutworm, Spodoptera litura

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    Background: Spodoptera litura is a noctuid moth that is considered an agricultural pest. The larvae feed on a wide range of plants and have been recorded on plants from 40 plant families (mostly dicotyledons). It is a major pest of many crops. To better understand Spodoptera litura granulovirus (SpliGV), the nucleotide sequence of the SpliGV DNA genome was determined and analyzed. Methodology/Principal Findings: The genome of the SpliGV was completely sequenced. The nucleotide sequence of the SpliGV genome was 124,121 bp long with 61.2 % A+T content and contained 133 putative open reading frames (ORFs) of 150 or more nucleotides. The 133 putative ORFs covered 86.3 % of the genome. Among these, 31 ORFs were conserved in most completely sequenced baculovirus genomes, 38 were granulovirus (GV)-specific, and 64 were present in some nucleopolyhedroviruses (NPVs) and/or GVs. We proved that 9 of the ORFs were SpliGV specific. Conclusions/Significance: The genome of SpliGV is 124,121 bp in size. One hundred thirty-three ORFs that putatively encode proteins of 50 or more amino acid residues with minimal overlap were determined. No chitinase or cathepsin genes, which are involved in the liquefaction of the infected host, were found in the SpliGV genome, explaining why SpliGVinfected insects do not degrade in a typical manner. The DNA photolyase gene was first found in the genus Granulovirus. When phylogenic relationships were analyzed, the SpliGV was most closely related to Trichoplusia ni granulovirus (TnGV

    Somatosensory System Deficits in Schizophrenia Revealed by MEG during a Median-Nerve Oddball Task

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    Although impairments related to somatosensory perception are common in schizophrenia, they have rarely been examined in functional imaging studies. In the present study, magnetoencephalography (MEG) was used to identify neural networks that support attention to somatosensory stimuli in healthy adults and abnormalities in these networks in patient with schizophrenia. A median-nerve oddball task was used to probe attention to somatosensory stimuli, and an advanced, high-resolution MEG source-imaging method was applied to assess activity throughout the brain. In nineteen healthy subjects, attention-related activation was seen in a sensorimotor network involving primary somatosensory (S1), secondary somatosensory (S2), primary motor (M1), pre-motor (PMA), and paracentral lobule (PCL) areas. A frontal–parietal–temporal “attention network”, containing dorsal- and ventral–lateral prefrontal cortex (DLPFC and VLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), superior parietal lobule (SPL), inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and temporal lobe areas, was also activated. Seventeen individuals with schizophrenia showed early attention-related hyperactivations in S1 and M1 but hypo-activation in S1, S2, M1, and PMA at later latency in the sensorimotor network. Within this attention network, hypoactivation was found in SPL, DLPFC, orbitofrontal cortex, and the dorsal aspect of ACC. Hyperactivation was seen in SMG/IPL, frontal pole, and the ventral aspect of ACC in patients. These findings link attention-related somatosensory deficits to dysfunction in both sensorimotor and frontal–parietal–temporal networks in schizophrenia
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