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Objectives: To evaluate whether lung perfusion continues to be reduced in 10-year-old children after congenital diaphragmatic hernia (CDH) and whether lung perfusion values correlate with spirometric lung function measurements. Methods: Fifty-four patients after CDH repair received dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI)-based lung perfusion measurements at the age of 10 years (10.2 ± 1.0 years). Additionally, a control group of 10 children has been examined according to the same protocol. Lung spirometry was additionally available in 43 patients of the CDH group. A comparison of ipsilateral and contralateral parameters was performed. Results: Pulmonary blood flow (PBF) was reduced on the ipsilateral side in CDH patients (60.4 ± 23.8 vs. 93.3 ± 16.09 mL/100 mL/min; p < 0.0001). In comparison to the control group, especially the ratio of ipsilateral to contralateral, PBF was reduced in CDH patients (0.669 ± 0.152 vs. 0.975 ± 0.091; p < 0.0001). There is a positive correlation between ipsilateral pulmonary blood flow, and spirometric forced 1-s volume (r = 0.45; p = 0.0024). Conclusions: Pulmonary blood flow impairment persists during childhood and correlates with spirometric measurements. Without the need for ionizing radiation, MRI measurements seem promising as follow-up parameters after CDH. Key Points: • Ten-year-old children after congenital diaphragmatic hernia continue to show reduced perfusion of ipsilateral lung. • Lung perfusion values correlate with lung function tests after congenital diaphragmatic hernia. [ABSTRACT FROM AUTHOR]

Nasal septum defects can currently only be reconstructed using autologous cartilage grafts. In this study, we examine the reconstruction of septal cartilage defects in a rabbit model using porcine decellularized nasal septal cartilage (DNSC) functionalized with recombinant platelet-derived growth factor-BB (PDFG-BB). The supportive function of the transplanted DNSC was estimated by the degree of septum deviation and shrinkage using magnetic resonance imaging (MRI). The biocompatibility of the transplanted scaffolds was evaluated by histology according to international standards. A study group with an autologous septal transplant was used as a reference. In situ regeneration of cartilage defects was assessed by histological evaluation 4 and 16 weeks following DNSC transplantation. A study group with non-functionalized DNSC was introduced for estimation of the effects of PDFG-BB functionalization. DNSC scaffolds provided sufficient structural support to the nasal septum, with no significant shrinkage or septal deviations as evaluated by the MRI. Biocompatibility analysis after 4 weeks revealed an increased inflammatory reaction of the surrounding tissue in response to DNSC as compared to the autologous transplants. The inflammatory reaction was, however, significantly attenuated after 16 weeks in the PDGF-BB group whereas only a slight improvement of the biocompatibility score was observed in the untreated group. In situ regeneration of septal cartilage, as evidenced by the degradation of the DNSC matrix and production of neocartilage, was observed in both experimental groups after 16 weeks but was more pronounced in the PDFG-BB group. Overall, DNSC provided structural support to the nasal septum and stimulated in situ regeneration of the cartilage tissue. Furthermore, PDFG-BB augmented the regenerative potential of DNSC and enhanced the healing process, as demonstrated by reduced inflammation after 16 weeks. [ABSTRACT FROM AUTHOR]

Objectives: To assess the risks for implant users with copper-containing intrauterine devices (IUDs) during MR and CT examinations.Methods: A tissue-mimicking phantom suitable for all experiments within this study was developed. Seven different types of copper IUDs were evaluated. Heating and dislocation of each IUD were investigated at two clinically relevant positions in 1.5 T and 3 T MR scanners. Artifacts in the field of view caused by each tested IUD were determined for clinical MR and CT imaging.Results: No significant heating of any tested IUD was detected during MR measurements. The temperature increase was less than 0.6 K for all IUDs. Neither angular deflection nor translation of any IUD was detected. Artifacts in MR images were limited to the very vicinity of the IUDs except for one IUD containing a steel-visualizing element. Streaking artifacts in CT were severe (up to 75.5%) in the slices including the IUD.Conclusion: No significant risk possibly harming the patient was determined during this phantom study, deeming MR examinations safe for women with an implanted copper IUD. Image quality was more impaired for CT than for MR imaging and needs careful consideration during diagnosis.Key Points: • Risk assessment of copper-containing IUDs with regard to heating, dislocation, and artifacts during MR and CT imaging. • Neither significant heating nor dislocation was determined in MR; image quality was more impaired for CT than for MR imaging and needs careful consideration during diagnosis. • The tested IUDs pose no additional risks for implant users during MR and CT examinations. [ABSTRACT FROM AUTHOR]

Background Functional techniques like diffusion-weighted imaging (DWI) are gaining more and more importance in liver magnetic resonance imaging (MRI). Diffusion kurtosis imaging (DKI) is an advanced technique that might help to overcome current limitations of DWI. Purpose To evaluate DKI for the differentiation of hepatic lesions in comparison to conventional DWI at 3 Tesla. Material and Methods Fifty-six consecutive patients were examined using a routine abdominal MR protocol at 3 Tesla which included DWI with b-values of 50, 400, 800, and 1000 s/mm2. Apparent diffusion coefficient maps were calculated applying a standard mono-exponential fit, while a non-Gaussian kurtosis fit was used to obtain DKI maps. ADC as well as Kurtosis-corrected diffusion ( D) values were quantified by region of interest analysis and compared between lesions. Results Sixty-eight hepatic lesions (hepatocellular carcinoma [HCC] [n = 25]; hepatic adenoma [n = 4], cysts [n = 18]; hepatic hemangioma [HH] [n = 18]; and focal nodular hyperplasia [n = 3]) were identified. Differentiation of malignant and benign lesions was possible based on both DWI ADC as well as DKI D-values ( P values were in the range of 0.04 to < 0.0001). Conclusion In vivo abdominal DKI calculated using standard b-values is feasible and enables quantitative differentiation between malignant and benign liver lesions. Assessment of conventional ADC values leads to similar results when using b-values below 1000 s/mm2 for DKI calculation. [ABSTRACT FROM AUTHOR]

Purpose To retrospectively evaluate the performance of an automatic support vector machine (SVM) routine in combination with perfusion-based dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) for preoperative survival associations in patients with gliomas and compare our results to traditional MRI. Materials and Methods The study was approved by the Ethics Committee and informed consent was signed. Structural, diffusion- and perfusion-weighted MRI was performed at 1.5-T preoperatively in 94 adult patients (49 males, 45 females, 23-82 years; mean 51 years) later diagnosed with a primary glioma. Patients were randomly assigned in training and test datasets and the resulting DSC-based survival associations by SVM were compared to traditional MRI features including contrast-agent enhancement, perfusion- and diffusion-weighted imaging, tumor size, and location. The results were adjusted for age, neurological status, and postoperative factors associated with survival, including surgery and adjuvant therapy. Results For 1- (26/33 alive, 11/14 deceased), 2- (15/21, 21/26), 3- (12/16, 27/31) and 4- (12/15, 28/32) year survival associations in the test dataset (47 patients), the SVM routine was the only biomarker to consistently associate with survival (Cox; P < 0.001). Conclusion The automatic machine learning routine presented in our study may provide the operator with a reliable instrument for assessing survival in patients with glioma. J. Magn. Reson. Imaging 2014;40:47-54. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The advantages of predictive modeling in glioma grading from MR perfusion images have not yet been explored. The aim of the current study was to implement a predictive model based on support vector machines (SVM) for glioma grading using tumor blood volume histogram signatures derived from MR perfusion images and to assess the diagnostic accuracy of the model and the sensitivity to sample size. A total of 86 patients with histologically-confirmed gliomas were imaged using dynamic susceptibility contrast (DSC) MRI at 1.5T. Histogram signatures from 53 of the 86 patients were analyzed independently by four neuroradiologists and used as a basis for the predictive SVM model. The resulting SVM model was tested on the remaining 33 patients and analyzed by a fifth neuroradiologist. At optimal SVM parameters, the true positive rate (TPR) and true negative rate (TNR) of the SVM model on the 33 patients was 0.76 and 0.82, respectively. The interobserver agreement and the TPR increased significantly when the SVM model was based on an increasing sample size ( P < 0.001). This result suggests that a predictive SVM model can aid in the diagnosis of glioma grade from MR perfusion images and that the model improves with increasing sample size. Magn Reson Med 60:945-952, 2008. © 2008 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]