928 resultados para Image analysis
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BACKGROUND: Reproducibility of basic research investigations in homeopathy is challenging. This study investigated if formerly observed effects of homeopathically potentised gibberellic acid (GA3) on growth of duckweed (Lemna gibba L.) were reproducible. METHODS: Duckweed was grown in potencies (14x-30x) of GA3 and one time succussed and unsuccussed water controls. Outcome parameter area-related growth rate was determined by a computerised image analysis system. Three series including five independent blinded and randomised potency experiments (PE) each were carried out. System stability was controlled by three series of five systematic negative control (SNC) experiments. Gibbosity (a specific growth state of L. gibba) was investigated as possibly essential factor for reactivity of L. gibba towards potentised GA3 in one series of potency and SNC experiments, respectively. RESULTS: Only in the third series with gibbous L. gibba L. we observed a significant effect (p = 0.009, F-test) of the homeopathic treatment. However, growth rate increased in contrast to the former study, and most biologically active potency levels differed. Variability in PE was lower than in SNC experiments. The stability of the experimental system was verified by the SNC experiments. CONCLUSIONS: Gibbosity seems to be a necessary condition for reactivity of L. gibba to potentised GA3. Further still unknown conditions seem to govern effect direction and the pattern of active and inactive potency levels. When designing new reproducibility studies, the physiological state of the test organism must be considered. Variability might be an interesting parameter to investigate effects of homeopathic remedies in basic research.
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BACKGROUND AND PURPOSE Reproducible segmentation of brain tumors on magnetic resonance images is an important clinical need. This study was designed to evaluate the reliability of a novel fully automated segmentation tool for brain tumor image analysis in comparison to manually defined tumor segmentations. METHODS We prospectively evaluated preoperative MR Images from 25 glioblastoma patients. Two independent expert raters performed manual segmentations. Automatic segmentations were performed using the Brain Tumor Image Analysis software (BraTumIA). In order to study the different tumor compartments, the complete tumor volume TV (enhancing part plus non-enhancing part plus necrotic core of the tumor), the TV+ (TV plus edema) and the contrast enhancing tumor volume CETV were identified. We quantified the overlap between manual and automated segmentation by calculation of diameter measurements as well as the Dice coefficients, the positive predictive values, sensitivity, relative volume error and absolute volume error. RESULTS Comparison of automated versus manual extraction of 2-dimensional diameter measurements showed no significant difference (p = 0.29). Comparison of automated versus manual segmentation of volumetric segmentations showed significant differences for TV+ and TV (p<0.05) but no significant differences for CETV (p>0.05) with regard to the Dice overlap coefficients. Spearman's rank correlation coefficients (ρ) of TV+, TV and CETV showed highly significant correlations between automatic and manual segmentations. Tumor localization did not influence the accuracy of segmentation. CONCLUSIONS In summary, we demonstrated that BraTumIA supports radiologists and clinicians by providing accurate measures of cross-sectional diameter-based tumor extensions. The automated volume measurements were comparable to manual tumor delineation for CETV tumor volumes, and outperformed inter-rater variability for overlap and sensitivity.
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With a steadily increasing impact of oral implant placement in daily practice, the number of reported surgical complications has also been growing. Recent studies reveal significant variation in the occurrence and morphology of neurovascular canal structures in the jaw bone. All those structures contain a neurovascular bundle, the diameter of which may be large enough to cause clinically significant damage. Therefore, it has become obvious that presurgical radiographic planning of jaw-bone surgery should pay attention to the neurovascular structures and their likely variations, in addition to examining many other factors, such as jaw-bone morphology and volume, bone trabecular structure and the absence of bone or tooth pathology. A critical review is accomplished to explore the potential risks for neurovascular complications after implant placement, with evidence derived from histologic, anatomic, clinical and radiologic studies. In this respect, cross-sectional imaging can often be advocated, as it is obvious that the inherent three-dimensional nature of jaw-bone anatomy may clearly benefit from a detailed spatial image analysis. Although this could initially be realized by conventional computed tomography, in current practice, dentomaxillofacial cone beam computed tomography might be used, as it offers high-quality images at low radiation dose levels and costs.
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The integrin antagonist cilengitide has been explored as an adjunct with anti-angiogenic properties to standard of care temozolomide chemoradiotherapy (TMZ/RT → TMZ) in newly diagnosed glioblastoma. Preclinical data as well as anecdotal clinical observations indicate that anti-angiogenic treatment may result in altered patterns of tumor progression. Using a standardized approach, we analyzed patterns of progression on MRI in 21 patients enrolled onto a phase 2 trial of cilengitide added to TMZ/RT → TMZ in newly diagnosed glioblastoma. Thirty patients from the experimental treatment arm of the EORTC/NCIC pivotal TMZ trial served as a reference. MRIcro software was used to map location and extent of initial preoperative and recurrent tumors on MRI of both groups into the same stereotaxic space which were then analyzed using an automated tool of image analysis. Clinical and outcome data of the cilengitide-treated patients were similar to those of the EORTC/NCIC trial except for a higher proportion of patients with a methylated O(6)-methylguanyl-DNA-methyltransferase gene promoter. Analysis of recurrence pattern revealed neither a difference in the size of the recurrent tumor nor in the distance of the recurrences from the preoperative tumor location between groups. Overall frequencies of distant recurrences were 20 % in the reference group and 19 % (4/21 patients) in the cilengitide group. Compared with TMZ/RT → TMZ alone, the addition of cilengitide does not alter patterns of progression. This analysis does not support concerns that integrin antagonism by cilengitide may induce a more aggressive phenotype at progression, but also provides no evidence for an anti-invasive activity of cilengitide in patients with newly diagnosed glioblastoma.
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Several studies have linked overexpression of the LIM and SH3 domain protein 1 (LASP1) to progression of breast, colon, liver, and bladder cancer. However, its expression pattern and role in human prostate cancer (PCa) remained largely undefined. Analysis of published microarray data revealed a significant overexpression of LASP1 in PCa metastases compared to parental primary tumors and normal prostate epithelial cells. Subsequent gene-set enrichment analysis comparing LASP1-high and -low PCa identified an association of LASP1 with genes involved in locomotory behavior and chemokine signaling. These bioinformatic predictions were confirmed in vitro as the inducible short hairpin RNA-mediated LASP1 knockdown impaired migration and proliferation in LNCaP prostate cancer cells. By immunohistochemical staining and semi-quantitative image analysis of whole tissue sections we found an enhanced expression of LASP1 in primary PCa and lymph node metastases over benign prostatic hyperplasia. Strong cytosolic and nuclear LASP1 immunoreactivity correlated with PSA progression. Conversely, qRT-PCR analyses for mir-203, which is a known translational suppressor of LASP1 in matched RNA samples revealed an inverse correlation of LASP1 protein and mir-203 expression. Collectively, our results suggest that loss of mir-203 expression and thus uncontrolled LASP1 overexpression might drive progression of PCa.
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PURPOSE To prospectively assess the diagnostic performance of diffusion-weighted (DW) magnetic resonance (MR) imaging in the detection of pelvic lymph node metastases in patients with prostate and/or bladder cancer staged as N0 with preoperative cross-sectional imaging. MATERIALS AND METHODS This study was approved by an independent ethics committee. Written informed consent was obtained from all patients. Patients with no enlarged lymph nodes on preoperative cross-sectional images who were scheduled for radical resection of the primary tumor and extended pelvic lymph node dissection were enrolled. All patients were examined with a 3-T MR unit, and examinations included conventional and DW MR imaging of the entire pelvis. Image analysis was performed by three independent readers blinded to any clinical information. Metastases were diagnosed on the basis of high signal intensity on high b value DW MR images and morphologic features (shape, border). Histopathologic examination served as the standard of reference. Sensitivity and specificity were calculated, and bias-corrected 95% confidence intervals (CIs) were obtained with the bootstrap method. The Fleiss and Cohen κ and median test were applied for statistical analyses. RESULTS A total of 4846 lymph nodes were resected in 120 patients. Eighty-eight lymph node metastases were found in 33 of 120 patients (27.5%). Short-axis diameter of these metastases was less than or equal to 3 mm in 68, more than 3 mm to 5 mm in 13, more than 5 mm to 8 mm in five; and more than 8 mm in two. On a per-patient level, the three readers correctly detected metastases in 26 (79%; 95% CI: 64%, 91%), 21 (64%; 95% CI: 45%, 79%), and 25 (76%; 95% CI: 60%, 90%) of the 33 patients with metastases, with respective specificities of 85% (95% CI: 78%, 92%), 79% (95% CI: 70%, 88%), and 84% (95% CI: 76%, 92%). Analyzed according to hemipelvis, lymph node metastases were detected with histopathologic examination in 44 of 240 pelvic sides (18%); the three readers correctly detected these on DW MR images in 26 (59%; 95% CI: 45%, 73%), 19 (43%; 95% CI: 27%, 57%), and 28 (64%; 95% CI: 47%, 78%) of the 44 cases. CONCLUSION DW MR imaging enables noninvasive detection of small lymph node metastases in normal-sized nodes in a substantial percentage of patients with prostate and bladder cancer diagnosed as N0 with conventional cross-sectional imaging techniques.
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PURPOSE To develop a method for computing and visualizing pressure differences derived from time-resolved velocity-encoded three-dimensional phase-contrast magnetic resonance imaging (4D flow MRI) and to compare pressure difference maps of patients with unrepaired and repaired aortic coarctation to young healthy volunteers. METHODS 4D flow MRI data of four patients with aortic coarctation either before or after repair (mean age 17 years, age range 3-28, one female, three males) and four young healthy volunteers without history of cardiovascular disease (mean age 24 years, age range 20-27, one female, three males) was acquired using a 1.5-T clinical MR scanner. Image analysis was performed with in-house developed image processing software. Relative pressures were computed based on the Navier-Stokes equation. RESULTS A standardized method for intuitive visualization of pressure difference maps was developed and successfully applied to all included patients and volunteers. Young healthy volunteers exhibited smooth and regular distribution of relative pressures in the thoracic aorta at mid systole with very similar distribution in all analyzed volunteers. Patients demonstrated disturbed pressures compared to volunteers. Changes included a pressure drop at the aortic isthmus in all patients, increased relative pressures in the aortic arch in patients with residual narrowing after repair, and increased relative pressures in the descending aorta in a patient after patch aortoplasty. CONCLUSIONS Pressure difference maps derived from 4D flow MRI can depict alterations of spatial pressure distribution in patients with repaired and unrepaired aortic coarctation. The technique might allow identifying pathophysiological conditions underlying complications after aortic coarctation repair.
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The majority of people who sustain hip fractures after a fall to the side would not have been identified using current screening techniques such as areal bone mineral density. Identifying them, however, is essential so that appropriate pharmacological or lifestyle interventions can be implemented. A protocol, demonstrated on a single specimen, is introduced, comprising the following components; in vitro biofidelic drop tower testing of a proximal femur; high-speed image analysis through digital image correlation; detailed accounting of the energy present during the drop tower test; organ level finite element simulations of the drop tower test; micro level finite element simulations of critical volumes of interest in the trabecular bone. Fracture in the femoral specimen initiated in the superior part of the neck. Measured fracture load was 3760 N, compared to 4871 N predicted based on the finite element analysis. Digital image correlation showed compressive surface strains as high as 7.1% prior to fracture. Voxel level results were consistent with high-speed video data and helped identify hidden local structural weaknesses. We found using a drop tower test protocol that a femoral neck fracture can be created with a fall velocity and energy representative of a sideways fall from standing. Additionally, we found that the nested explicit finite element method used allowed us to identify local structural weaknesses associated with femur fracture initiation.
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Cephalometric analysis is an essential clinical and research tool in orthodontics for the orthodontic analysis and treatment planning. This paper presents the evaluation of the methods submitted to the Automatic Cephalometric X-Ray Landmark Detection Challenge, held at the IEEE International Symposium on Biomedical Imaging 2014 with an on-site competition. The challenge was set to explore and compare automatic landmark detection methods in application to cephalometric X-ray images. Methods were evaluated on a common database including cephalograms of 300 patients aged six to 60 years, collected from the Dental Department, Tri-Service General Hospital, Taiwan, and manually marked anatomical landmarks as the ground truth data, generated by two experienced medical doctors. Quantitative evaluation was performed to compare the results of a representative selection of current methods submitted to the challenge. Experimental results show that three methods are able to achieve detection rates greater than 80% using the 4 mm precision range, but only one method achieves a detection rate greater than 70% using the 2 mm precision range, which is the acceptable precision range in clinical practice. The study provides insights into the performance of different landmark detection approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.
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Morphogenesis emerges from complex multiscale interactions between genetic and mechanical processes. To understand these processes, the evolution of cell shape, proliferation and gene expression must be quantified. This quantification is usually performed either in full 3D, which is computationally expensive and technically challenging, or on 2D planar projections, which introduces geometrical artifacts on highly curved organs. Here we present MorphoGraphX (www.MorphoGraphX.org), a software that bridges this gap by working directly with curved surface images extracted from 3D data. In addition to traditional 3D image analysis, we have developed algorithms to operate on curved surfaces, such as cell segmentation, lineage tracking and fluorescence signal quantification. The software’s modular design makes it easy to include existing libraries, or to implement new algorithms. Cell geometries extracted with MorphoGraphX can be exported and used as templates for simulation models, providing a powerful platform to investigate the interactions between shape, genes and growth.DOI: http://dx.doi.org/10.7554/eLife.05864.001Author keywordsResearch organism
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Mercury (Hg) contamination is a global issue due to its anthropogenic release, long-range transport, and deposition in remote areas. In Kejimkujik National Park and National Historic Site, Nova Scotia, Canada, high concentrations of total mercury (THg) were found in tissues of yellow perch (Perca flavescens). The aim of this study was to evaluate a possible relationship between THg concentrations and the morphology of perch liver as a main site of metal storage and toxicity. Yellow perch were sampled from five lakes known to contain fish representing a wide range in Hg concentrations in fall 2013. The ultrastructure of hepatocytes and the distribution of Hg within the liver parenchyma were analyzed by transmission electron microscopy (TEM) and electron energy loss spectrometry (EELS). The relative area of macrophage aggregates (MAs) in the liver was determined using image analysis software and fluorescence microscopy. No relation between general health indicators (Fulton's condition index) and THg was observed. In line with this, TEM examination of the liver ultrastructure revealed no prominent pathologies related to THg accumulation. However, a morphological parameter that appeared to increase with muscle THg was the relative area of MAs in the liver. The hepatic lysosomes appeared to be enlarged in samples with the highest THg concentrations. Interestingly, EELS analysis revealed that the MAs and hepatic lysosomes contained Hg.
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Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.
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Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.
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AIMS Transcatheter mitral valve replacement (TMVR) is an emerging technology with the potential to treat patients with severe mitral regurgitation at excessive risk for surgical mitral valve surgery. Multimodal imaging of the mitral valvular complex and surrounding structures will be an important component for patient selection for TMVR. Our aim was to describe and evaluate a systematic multi-slice computed tomography (MSCT) image analysis methodology that provides measurements relevant for transcatheter mitral valve replacement. METHODS AND RESULTS A systematic step-by-step measurement methodology is described for structures of the mitral valvular complex including: the mitral valve annulus, left ventricle, left atrium, papillary muscles and left ventricular outflow tract. To evaluate reproducibility, two observers applied this methodology to a retrospective series of 49 cardiac MSCT scans in patients with heart failure and significant mitral regurgitation. For each of 25 geometrical metrics, we evaluated inter-observer difference and intra-class correlation. The inter-observer difference was below 10% and the intra-class correlation was above 0.81 for measurements of critical importance in the sizing of TMVR devices: the mitral valve annulus diameters, area, perimeter, the inter-trigone distance, and the aorto-mitral angle. CONCLUSIONS MSCT can provide measurements that are important for patient selection and sizing of TMVR devices. These measurements have excellent inter-observer reproducibility in patients with functional mitral regurgitation.
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This paper addresses the issue of fully automatic segmentation of a hip CT image with the goal to preserve the joint structure for clinical applications in hip disease diagnosis and treatment. For this purpose, we propose a Multi-Atlas Segmentation Constrained Graph (MASCG) method. The MASCG method uses multi-atlas based mesh fusion results to initialize a bone sheetness based multi-label graph cut for an accurate hip CT segmentation which has the inherent advantage of automatic separation of the pelvic region from the bilateral proximal femoral regions. We then introduce a graph cut constrained graph search algorithm to further improve the segmentation accuracy around the bilateral hip joint regions. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 15-fold cross validation. When the present approach was compared to manual segmentation, an average surface distance error of 0.30 mm, 0.29 mm, and 0.30 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. A further look at the bilateral hip joint regions demonstrated an average surface distance error of 0.16 mm, 0.21 mm and 0.20 mm for the acetabulum, the left femoral head, and the right femoral head, respectively.