Current Issue : January - March Volume : 2016 Issue Number : 1 Articles : 7 Articles
Background: Parkinson�s disease (PD) is a common neurodegenerative disease. Most studies have found that the\nhistopathological lesion is not only localized at the extrapyramidal area (basal ganglia) but also at the cortex in PD\npatients. Voxel-based morphometry (VBM) based on the voxel as a unit is described for quantitative detection of\ndensity and volume of brain tissue. In this study, VBM was used to investigate the brain gray matter changes\nassociated with motor symptoms in PD patients.\nMethods: Twelve outpatients with PD and 12 healthy controls were recruited in our hospital from September 2013\nto March 2014. VBM was performed on the whole brain of all subjects. Image processing and statistical analysis\nwere performed using SPM8. A two-sample t test and multiple regression analysis were performed. Results were\ndisplayed with a threshold of P < 0.01, corrected by false discovery rate (FDR) correction and cluster size >30 voxels.\nResults: Comparing control healthy subjects with the patients, the data showed that PD patients had reduced gray\nmatter volume in the postcentral gyrus, the right supramarginal center, superior temporal gyrus, precentral gyrus,\nBrodmann area 41, transverse temporal gyrus, Brodmann area 3, and inferior parietal lobule. The data also found\nthat between gray matter volume and UPDRSIII in PD patients, there were negative correlations in the right middle\nfrontal gyrus, BA06, right precentral gyrus, right superior frontal gyrus, and medial frontal gyrus, and between gray\nmatter volume and Hoehn-Yahr (HY) in PD patients, there were negative correlations in the right middle frontal\ngyrus, right superior frontal gyrus, BA6, and right precentral gyrus.\nConclusions: These data supported that extensive changes associated with motor symptoms in the gray matter\nvolume was mainly located in the related area of movement, which had obvious relevance with the progression\nof PD...
Purpose: Comparison of imaging measurement devices in the absence of a gold-standard comparator remains a\nvexing problem; especially in scenarios where multiple, non-paired, replicated measurements occur, as in\nimage-guided radiotherapy (IGRT). As the number of commercially available IGRT presents a challenge to determine\nwhether different IGRT methods may be used interchangeably, an unmet need conceptually parsimonious and\nstatistically robust method to evaluate the agreement between two methods with replicated observations.\nConsequently, we sought to determine, using an previously reported head and neck positional verification dataset,\nthe feasibility and utility of a Comparison of Measurement Methods with the Mixed Effects Procedure Accounting for\nReplicated Evaluations (COM3PARE), a unified conceptual schema and analytic algorithm based upon Royââ?¬â?¢s linear\nmixed effects (LME) model with Kronecker product covariance structure in a doubly multivariate set-up, for IGRT\nmethod comparison.\nMethods: An anonymized dataset consisting of 100 paired coordinate (X/ measurements from a sequential series of\nhead and neck cancer patients imaged near-simultaneously with cone beam CT (CBCT) and kilovoltage X-ray (KVX)\nimaging was used for model implementation. Software-suggested CBCT and KVX shifts for the lateral (X), vertical (Y)\nand longitudinal (Z) dimensions were evaluated for bias, inter-method (between-subject variation), intra-method\n(within-subject variation), and overall agreement using with a script implementing COM3PARE with the MIXED\nprocedure of the statistical software package SAS (SAS Institute, Cary, NC, USA).\nResults: COM3PARE showed statistically significant bias agreement and difference in inter-method between CBCT\nand KVX was observed in the Z-axis (both pâË?â??value < 0.01). Intra-method and overall agreement differences were\nnoted as statistically significant for both the X- and Z-axes (all pâË?â??value < 0.01). Using pre-specified criteria, based on\nintra-method agreement, CBCT was deemed preferable for X-axis positional verification, with KVX preferred for\nsuperoinferior alignment.\nConclusions: The COM3PARE methodology was validated as feasible and useful in this pilot head and neck cancer\npositional verification dataset. COM3PARE represents a flexible and robust standardized analytic methodology for IGRT\ncomparison. The implemented SAS script is included to encourage other groups to implement COM3PARE in other\nanatomic sites or IGRT platforms....
Background: We aimed to investigate the efficacy of computer-aided detection (CAD) for MRI in the assessment\nof tumor extent, lymph node status, and multifocality in invasive breast cancers in comparison with other breast\nimaging modalities.\nMethods: Two radiologists measured the maximum tumor size, as well as, analyzed lymph node status and\nmultifocality in 86 patients with invasive breast cancers using mammography, ultrasound, CT, MRI with and\nwithout CAD, and 18-fludeoxyglucose positron emission tomography (FDG-PET). The assessed data were compared\nwith pathology.\nResults: For tumor extent, there were no significant differences between pathological size and measured size using\nmammography, ultrasound, CT, or MRI with and without CAD (P > 0.05). For evaluation of lymph node status,\nultrasound had the best kappa coefficients (0.522) for agreement between imaging and pathology, and diagnostic\nperformance with 92.1% specificity and 90.0% positive predictive value. For multifocality, MRI with CAD had the\nhighest area under the receiver operating characteristic curve (AUC = 0.888).\nConclusions: CAD for MRI is feasible to assess tumor extent and multifocality in invasive breast cancer patients.\nHowever, CAD is not effective in evaluation of nodal status....
Background: Biomedical imaging research increasingly involves acquiring, managing and processing large\namounts of distributed imaging data. Integrated systems that combine data, meta-data and workflows are crucial\nfor realising the opportunities presented by advances in imaging facilities.\nMethods: This paper describes the design, implementation and operation of a multi-modality research imaging\ndata management system that manages imaging data obtained from biomedical imaging scanners operated at\nMonash Biomedical Imaging (MBI), Monash University in Melbourne, Australia. In addition to Digital Imaging and\nCommunications in Medicine (DICOM) images, raw data and non-DICOM biomedical data can be archived and\ndistributed by the system. Imaging data are annotated with meta-data according to a study-centric data model\nand, therefore, scientific users can find, download and process data easily.\nResults: The research imaging data management system ensures long-term usability, integrity inter-operability and\nintegration of large imaging data. Research users can securely browse and download stored images and data, and\nupload processed data via subject-oriented informatics frameworks including the Distributed and Reflective\nInformatics System (DaRIS), and the Extensible Neuroimaging Archive Toolkit (XNAT)....
Quantitative Transmission Ultrasound (QTUS) is a tomographic transmission ultrasound modality that is capable of generating\n3D speed-of-sound maps of objects in the field of view. It performs this measurement by propagating a plane wave through the\nmedium from a transmitter on one side of a water tank to a high resolution receiver on the opposite side. This information is then\nused via inverse scattering to compute a speed map. In addition, the presence of reflection transducers allows the creation of a\nhigh resolution, spatially compounded reflection map that is natively coregistered to the speed map. A prototype QTUS system was\nevaluated for measurement and geometric accuracy as well as for the ability to correctly determine speed of sound....
Background: Post processing for brain spectra has a great influence on the fit quality of individual spectra, as well\nas on the reproducibility of results from comparable spectra. This investigation used pairs of spectra, identical in\nsystem parameters, position and time assumed to differ only in noise. The metabolite amplitudes of fitted time\ndomain spectroscopic data were tested on reproducibility for the main brain metabolites.\nMethods: Proton spectra of white matter brain tissue were acquired with a short spin echo time of 30 ms and a\nmoderate repetition time of 1500 ms at 1.5 T. The pairs were investigated with one time domain post-processing\nalgorithm using different parameters. The number of metabolites, the use of prior knowledge, base line parameters\nand common or individual damping were varied to evaluate the best reproducibility.\nResults: The protocols with most reproducible amplitudes for N-acetylaspartate, creatine, choline, myo-inositol and\nthe combined Glx line of glutamate and glutamine in lesion free white matter have the following common\nfeatures: common damping of the main metabolites, a baseline using only the points of the first 10 ms, no\nadditional lipid/macromolecule lines and Glx is taken as the sum of separately fitted glutamate and glutamine. This\nparameter set is different to the one delivering the best individual fit results.\nDiscussion: All spectra were acquired in ââ?¬Å?lesion freeââ?¬Â (no lesion signs found in MR imaging) white matter. Spectra\nof brain lesions, for example tumors, can be drastically different. Thus the results are limited to lesion free brain\ntissue. Nevertheless the application to studies is broad, because small alterations in brain biochemistry of lesion free\nareas had been detected nearby tumors, in patients with multiple sclerosis, drug abuse or psychiatric disorders.\nConclusion: Main metabolite amplitudes inside healthy brain can be quantified with a normalized root mean\nsquare deviation around 5 % using CH3 of creatine as reference. Only the reproducibility of myo-inositol is roughly\ntwice as bad. The reproducibility should be similar using other references like internal or external water for an\nabsolute concentration evaluation and are not influenced by relaxation corrections with literature values....
Objective. The aim of this work was to develop a fast and robust (semi)automatic segmentation technique of the aortic valve\narea (AVA) MDCT datasets. Methods.The algorithm starts with detection and cropping of Sinus of Valsalva on MPR image. The\ncropped image is then binarized and seed points aremanually selected to create an initial contour.Thecontourmoves automatically\ntowards the edge of aortic AVA to obtain a segmentation of the AVA. AVA was segmented semiautomatically and manually by two\nobservers in multiphase cardiac CT scans of 25 patients. Validation of the algorithm was obtained by comparing to Transthoracic\nEchocardiography (TTE). Intra- and interobserver variability were calculated by relative differences. Differences between TTE\nand MDCT manual and semiautomatic measurements were assessed by Bland-Altman analysis. Time required for manual and\nsemiautomatic segmentations was recorded. Results.Mean differences fromTTE were âË?â??0.19 (95% CI: âË?â??0.74 to 0.34) cm2 formanual\nand âË?â??0.10 (95% CI: âË?â??0.45 to 0.25) cm2 for semiautomatic measurements. Intra- and interobserver variabilitywere 8.4 Ã?± 7.1% and 27.6\nÃ?± 16.0% for manual, and 5.8 Ã?± 4.5% and 16.8 Ã?± 12.7% for semiautomatic measurements, respectively. Conclusion. Newly developed\nsemiautomatic segmentation provides an accurate, more reproducible, and faster AVA segmentation result....
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