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The objective of this study was to assess the performance of the chemometric model to predict the proportion of the recrystallized polymorphs of nimodipine from the cosolvent formulations. Ranging from 100% to 0% (w/w) of polymorph I, the two polymorphs mixtures were prepared and characterized spectroscopically using Fourier transformed infrared spectroscopy (FTIR), near-infrared spectroscopy (NIR), and Raman spectroscopy. Instrumental responses were treated to construct multivariate calibration model using principal component regression (PCR) and partial least square regression approaches. Treated data showed better model fitting than without treatment, which demonstrated higher correlation coefficient (R2) and lower root mean square of standard error (RMSE) and standard error (SE). Multiple scattering correction and standard normal variate exhibited higher R2 and lower RMSE and SE values than second derivative. Goodness of fit for FTIR and NIR (R2 ~ 0.99) data was better than Raman (R2 ~ 0.95). Furthermore, the models were applied on the recrystallized polymorphs obtained by storing nimodipine-cosolvent formulations at selected stability conditions. The relative composition of the polymorphs differed with storage conditions. NIR-chemical imaging on recrystallized sample of nimodipine at 15°C qualitatively corroborated the model-based prediction of the two polymorphs. Therefore, these studies strongly suggest the importance of the potential utility of the chemometric model in predicting nimodipine polymorphs.  相似文献   
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BACKGROUND AND PURPOSE:Head motion causes image degradation in brain MR imaging examinations, negatively impacting image quality, especially in pediatric populations. Here, we used a retrospective motion correction technique in children and assessed image quality improvement for 3D MR imaging acquisitions.MATERIALS AND METHODS:We prospectively acquired brain MR imaging at 3T using 3D sequences, T1-weighted MPRAGE, T2-weighted TSE, and FLAIR in 32 unsedated children, including 7 with epilepsy (age range, 2–18 years). We implemented a novel motion correction technique through a modification of k-space data acquisition: Distributed and Incoherent Sample Orders for Reconstruction Deblurring by using Encoding Redundancy (DISORDER). For each participant and technique, we obtained 3 reconstructions as acquired (Aq), after DISORDER motion correction (Di), and Di with additional outlier rejection (DiOut). We analyzed 288 images quantitatively, measuring 2 objective no-reference image quality metrics: gradient entropy (GE) and MPRAGE white matter (WM) homogeneity. As a qualitative metric, we presented blinded and randomized images to 2 expert neuroradiologists who scored them for clinical readability.RESULTS:Both image quality metrics improved after motion correction for all modalities, and improvement correlated with the amount of intrascan motion. Neuroradiologists also considered the motion corrected images as of higher quality (Wilcoxon z = −3.164 for MPRAGE; z = −2.066 for TSE; z = −2.645 for FLAIR; all P < .05).CONCLUSIONS:Retrospective image motion correction with DISORDER increased image quality both from an objective and qualitative perspective. In 75% of sessions, at least 1 sequence was improved by this approach, indicating the benefit of this technique in unsedated children for both clinical and research environments.

Head motion is a common cause of image degradation in brain MR imaging. Motion artifacts negatively impact MR image quality and therefore radiologists’ capacity to read the images, ultimately affecting patient clinical care.1 Motion artifacts are more common in noncompliant patients,2 but even in compliant adults, intrascan movement is reported in at least 10% of cases.3 For children who require high-resolution MR images, obtaining optimal image quality can be challenging, owing to the requirement to stay still over long durations needed for acquisition.4 Sedation can be an option, but it carries higher risks, costs, and preparation and recovery time.5In conditions such as intractable focal epilepsy, identification of an epileptogenic lesion is clinically important to guide surgical treatment. However, these lesions can be visually subtle, particularly in children in whom subtle cortical dysplasias are more common.6 Dedicated epilepsy MR imaging protocols use high-resolution 3D sequences to allow better cortical definition and free reformatting of orientation but involve acquisition times in the order of minutes, so data collection becomes more sensitive to motion.7For children in particular, multiple strategies are available for minimizing motion during MR examinations. Collaboration with play specialists using mock scanners and training or projecting a cartoon are good approaches to reduce anxiety.8,9 These tools are not always available in clinical radiology and, even with these strategies, motion can still be an issue.10 Different scanning approaches to correct for intrascan motion have been proposed. Broadly, prospective methods track head motion in real time and modify the acquisition directions accordingly.11 These approaches are applicable to a wide range of sequences but require optical systems with external tracking markers, sometimes uncomfortable or impractical, and extra setup can ultimately result in longer examinations. Furthermore, these approaches may also not be robust to continuous motion.11-13 Retrospective techniques have also been proposed, in some cases relying on imaging navigators that are not compatible with all standard sequences or contrasts.12Here, we use a more general retrospective motion correction technique: Distributed and Incoherent Sample Orders for Reconstruction Deblurring by using Encoding Redundancy (DISORDER). In this method, k-space samples are reordered to enable retrospective motion correction during image reconstruction.14 Our hypothesis is that DISORDER improves clinical MR imaging quality and readability. To assess its use for clinical sequences, we acquired a dedicated epilepsy MR imaging protocol in 32 children across a wide age range. We used both objective image quality metrics and expert neuroradiologist ratings to evaluate the outcome after motion correction.  相似文献   
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