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Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

JOURNAL OF INSTRUMENTATION 2009年第07期4卷 P07014-P07014页

作者： Karahaliou, A. Vassiou, K. Skiadopoulos, S. Kanavou, T. Yiakoumelos, A. Costaridou, L. Univ Patras Dept Med Phys Fac Med Patras 26500 Greece Univ Thessaly Dept Anat Fac Med Larisa 41110 Greece Univ Thessaly Dept Radiol Fac Med Larisa 41110 Greece

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960 +/- 0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

关键词： data processing methods Pattern recognition, cluster finding, calibration and fitting methods MRI (whole body, cardiovascular, breast, others), MR-angiography (MRA)

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Commissioning of the CMS High Level Trigger

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JOURNAL OF INSTRUMENTATION 2009年第10期4卷 P10005-P10005页

作者： Agostino, L. Bauer, G. Beccati, B. Behrens, U. Berryhil, J. Biery, K. Bose, T. Brett, A. Branson, J. Cano, E. Cheung, H. Ciganek, M. Cittolin, S. Coarasa, J. A. Dahmes, B. Deldicque, C. Dusinberre, E. Erhan, S. Gigi, D. Glege, F. Gomez-Reino, R. Gutleber, J. Hatton, D. Laurens, J. Loizides, C. Ma, F. Meijers, F. Meschi, E. Meyer, A. Mommsen, R. K. Moser, R. O'Dell, V. Oh, A. Orsini, L. Patras, V. Paus, C. Petrucci, A. Pieri, M. Racz, A. Sakulin, H. Sani, M. Schieferdecker, P. Schwick, C. Margaleff, J. F. S. Shpakov, D. Simon, S. Sumorok, K. Yoon, A. S. Wittich, P. Zanetti, M. CERN Geneva Switzerland Cornell Univ Ithaca NY USA MIT Cambridge MA 02139 USA DESY D-2000 Hamburg Germany FNAL Chicago IL USA Boston Univ Boston MA 02215 USA Univ Calif San Diego San Diego CA 92103 USA Lawrence Livermore Natl Lab Livermore CA USA Univ Calif Los Angeles Los Angeles CA USA Univ Minnesota Minneapolis MN USA Vienna Univ Technol A-1060 Vienna Austria Univ Manchester Manchester Lancs England Univ Karlsruhe Karlsruhe Germany

The CMS experiment will collect data from the proton-proton collisions delivered by the Large Hadron Collider (LHC) at a centre-of-mass energy up to 14 TeV. The CMS trigger system is designed to cope with unprecedented luminosities and LHC bunch-crossing rates up to 40 MHz. The unique CMS trigger architecture only employs two trigger levels. The Level-1 trigger is implemented using custom electronics, while the High Level Trigger (HLT) is based on software algorithms running on a large cluster of commercial processors, the Event Filter Farm. We present the major functionalities of the CMS High Level Trigger system as of the starting of LHC beams operations in September 2008. The validation of the HLT system in the online environment with Monte Carlo simulated data and its commissioning during cosmic rays data taking campaigns are discussed in detail. We conclude with the description of the HLT operations with the first circulating LHC beams before the incident occurred the 19(th) September 2008.

关键词： Online farms and online filtering Trigger concepts and systems (hardware and software) data acquisition concepts data processing methods

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Quantitative proton magnetic resonance spectroscopy without water suppression

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JOURNAL OF INSTRUMENTATION 2009年第06期4卷 P06014-P06014页

作者： Ozdemir, M. S. De Deene, Y. Fieremans, E. Lemahieu, I. Univ Ghent IBBT IBiTech MEDISIP Dept Elect & Informat Syst B-9000 Ghent Belgium Ghent Univ Hosp Dept Radiotherapy B-9000 Ghent Belgium

The suppression of the abundant water signal has been traditionally employed to decrease the dynamic range of the NMR signal in proton MRS ((1)H MRS) in vivo. When using this approach, if the intent is to utilize the water signal as an internal reference for the absolute quantification of metabolites, additional measurements are required for the acquisition of the water signal. This can be prohibitively time-consuming and is not desired clinically. Additionally, traditional water suppression can lead to metabolite alterations. This can be overcome by performing quantitative 1H MRS without water suppression. However, the non-water-suppressed spectra suffer from gradient-induced frequency modulations, resulting in sidebands in the spectrum. Sidebands may overlap with the metabolites, which renders the spectral analysis and quantification problematic. In this paper, we performed absolute quantification of metabolites without water suppression. Sidebands were removed by utilizing the phase of an external reference signal of single resonance to observe the time-varying the static field fluctuations induced by gradient-vibration and deconvolving this phase contamination from the desired NMR signal. The quantification of metabolites was determined after sideband correction by calibrating the metabolite signal intensities against the recorded water signal. The method was evaluated by phantom and in vivo measurements in human brain. The maximum systematic error for the quantified metabolite concentrations was found to be 10.8%, showing the feasibility of the quantification after sideband correction.

关键词： data processing methods Simulation methods and programs MRI (whole body, cardiovascular, breast, others), MR-angiography (MRA) Medical-image reconstruction methods and algorithms, computer-aided so

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Exploiting unsupervised and supervised classification for segmentation of the pathological lung in CT

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JOURNAL OF INSTRUMENTATION 2009年第7期4卷 P07013-P07013页

作者： Korfiatis, P. Kalogeropoulou, C. Daoussis, D. Petsas, T. Adonopoulos, A. Costaridou, L. Univ Patras Sch Med Dept Med Phys Patras 26500 Greece Univ Hosp Patras Dept Radiol Patras 26500 Greece Univ Hosp Patras Dept Rheumatol Patras 26500 Greece

Delineation of lung fields in presence of diffuse lung diseases (DLPDs), such as interstitial pneumonias (IP), challenges segmentation algorithms. To deal with IP patterns affecting the lung border an automated image texture classification scheme is proposed. The proposed segmentation scheme is based on supervised texture classification between lung tissue ( normal and abnormal) and surrounding tissue ( pleura and thoracic wall) in the lung border region. This region is coarsely defined around an initial estimate of lung border, provided by means of Markov Radom Field modeling and morphological operations. Subsequently, a support vector machine classifier was trained to distinguish between the above two classes of tissue, using textural feature of gray scale and wavelet domains. 17 patients diagnosed with IP, secondary to connective tissue diseases were examined. Segmentation performance in terms of overlap was 0.924 +/- 0.021, and for shape differentiation mean, rms and maximum distance were 1.663 +/- 0.816, 2.334 +/- 1.574 and 8.0515 +/- 6.549 mm, respectively. An accurate, automated scheme is proposed for segmenting abnormal lung fields in HRC affected by IP

关键词： data processing methods Pattern recognition, cluster finding, calibration and fitting methods Computerized Tomography (CT) and Computed Radiography (CR)

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Track parameter propagation through the application of a new adaptive Runge-Kutta-Nystrom method in the ATLAS experiment

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JOURNAL OF INSTRUMENTATION 2009年第4期4卷 P04001-P04001页

作者： Lund, E. Bugge, L. Gavrilenko, I. Strandlie, A. Univ Oslo N-0316 Oslo Norway CERN European Org Nucl Res CH-1211 Geneva 23 Switzerland PN Lebedev Phys Inst Moscow 117924 Russia Gjovik Univ Coll N-2802 Gjovik Norway

In this paper we study several fixed step and adaptive Runge-Kutta methods suitable for transporting track parameters through an inhomogeneous magnetic field. Moreover, we present a new adaptive Runge-Kutta-Nystrom method which estimates the local error of the extrapolation without introducing extra stages to the original Runge-Kutta-Nystrom method. Furthermore, these methods are compared for propagation accuracy and computing cost efficiency in the simultaneous track and error propagation (STEP) algorithm of the common ATLAS tracking software. The tests show the new adaptive Runge-Kutta-Nystrom method to be the most computing cost efficient.

关键词： Simulation methods and programs Pattern recognition cluster finding calibration and fitting methods data processing methods

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Transport of covariance matrices in the inhomogeneous magnetic field of the ATLAS experiment by the application of a semi-analytical method

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JOURNAL OF INSTRUMENTATION 2009年第4期4卷 P04016-P04016页

In this paper we study the transport of track parameter covariance matrices - the so-called error propagation - in the inhomogeneous magnetic field of the ATLAS experiment. The Jacobian elements are transported in parallel with the track parameters, avoiding the inherent need of any purely numerical scheme of propagating a set of auxiliary tracks. We evaluate the quality of the transported Jacobians by a very thorough, purely numerical approach of obtaining the same derivatives, providing a quantitative understanding of the effects of including gradients of energy loss and the magnetic field on the accuracy of the error propagation. Irrespective of the accuracy of the underlying track parameter propagation, the method of parallel integration of the derivatives is demonstrated to be significantly faster than even the simplest numerical scheme. The error propagation presented in this paper is part of the simultaneous track and error propagation ( STEP) algorithm of the common ATLAS tracking software.

关键词： Pattern recognition, cluster finding, calibration and fitting methods Simulation methods and programs data processing methods

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Automated detection of arterial input function in DSC perfusion MRI in a stroke rat model

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JOURNAL OF INSTRUMENTATION 2009年第5期4卷 P05021-P05021页

作者： Yeh, M. -Y. Lee, T. -H. Yang, S. -T. Kuo, H. -H. Chyi, T. -K. Liu, H. -L. Chang Gung Univ Grad Inst Med Phys & Imaging Sci Tao Yuan Taiwan Chang Gung Mem Hosp MRI Ctr Tao Yuan Taiwan Chang Gung Mem Hosp Stroke Sect Dept Neurol Tao Yuan Taiwan Chang Gung Mem Hosp Mol Imaging Ctr Tao Yuan Taiwan

Quantitative cerebral blood flow (CBF) estimation requires deconvolution of the tissue concentration time curves with an arterial input function (AIF). However, image-based determination of AIF in rodent is challenged due to limited spatial resolution. We evaluated the feasibility of quantitative analysis using automated AIF detection and compared the results with commonly applied semi-quantitative analysis. Permanent occlusion of bilateral or unilateral common carotid artery was used to induce cerebral ischemia in rats. The image using dynamic susceptibility contrast method was performed on a 3-T magnetic resonance scanner with a spin-echo echo-planar-image sequence (TR/TE= 700/80 ms, FOV=41 mm, matrix=64, 3 slices, SW=2 mm), starting from 7 s prior to contrast injection (1.2ml/kg) at four different time points. For quantitative analysis, CBF was calculated by the AIF which was obtained from 10 voxels with greatest contrast enhancement after deconvolution. For semi-quantitative analysis, relative CBF was estimated by the integral divided by the first moment of the relaxivity time curves. We observed if the AIFs obtained in the three different ROIs (whole brain, hemisphere without lesion and hemisphere with lesion) were similar, the CBF ratios (lesion/normal) between quantitative and semi-quantitative analyses might have a similar trend at different operative time points. If the AIFs were different, the CBF ratios might be different. We concluded that using local maximum one can define proper AIF without knowing the anatomical location of arteries in a stroke rat model.

关键词： data processing methods MRI (whole body, cardiovascular, breast, others) MR-angiography (MRA)

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Fast iterative reconstructions for animal CT

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JOURNAL OF INSTRUMENTATION 2009年第06期4卷 P06017-P06017页

作者： Huang, H. -M. Hsiao, I. -T. Jan, M. -L. Chang Gung Univ Dept Med Imaging & Radiol Sci Tao Yuan 333 Taiwan Case Western Reserve Univ Dept Biomed Engn Cleveland OH 44106 USA Chang Gung Mem Hosp Mol Imaging Ctr Kwei Shan Taoyuan 333 Taiwan INER Div Phys Tao Yuan 32546 Taiwan

For iterative x-ray computed tomography (CT) reconstruction, the convex algorithm combined with ordered subset (OSC) [1] is a relatively fast algorithm and has shown its potential for low-dose situations. But it needs one forward projection and two backprojections per iteration. Unlike convex algorithm, the gradient algorithm only requires one forward projection and one backprojection per iteration. Here, we applied ordered subsets of projection data to a modified gradient algorithm. In order to further reduce computation time, the new algorithm, the ordered subset gradient (OSG) algorithm, can be adjusted with a step size. We also implemented another OS-type algorithm called OSTR. The OSG algorithm is compared with OSC algorithm and OSTR algorithm using three-dimensional simulated helical cone-beam CT data. The performance is evaluated in terms of log-likelihood, contrast recovery, and bias-variance studies. Results show that images of OSG has compatible visual image quality to those of OSC and OSTR, but in the resolution and bias-variance studies, OSG seems to reach stable values with faster speed. In particular, OSTR has better recovery in a smoother region, but both OSG and OSC have better recovery in the high-frequency regions. Moreover, in terms of log likelihood with respect to computation time, OSG has faster convergence rate than that of OSC and similar to that of OSTR. We conclude that OSG has potential to provide comparable image quality and is more computationally efficient, and thus could be suitable for low-dose, helical cone-beam CT image reconstruction.

关键词： Image reconstruction in medical imaging data processing methods

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Absorbing systematic effects to obtain a better background model in a search for new physics

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JOURNAL OF INSTRUMENTATION 2009年第10期4卷 P10009-P10009页

作者： Caron, S. Cowan, G. Gross, E. Horner, S. Sundermann, J. E. Univ Freiburg Inst Phys D-79104 Freiburg Germany Univ London Egham TW20 0EX Surrey England Weizmann Inst Sci IL-76100 Rehovot Israel

This paper presents a novel approach to estimate the Standard Model backgrounds based on modifying Monte Carlo predictions within their systematic uncertainties. The improved background model is obtained by altering the original predictions with successively more complex correction functions in signal-free control selections. Statistical tests indicate when sufficient compatibility with data is reached. In this way, systematic effects are absorbed into the new background model. The same correction is then applied on the Monte Carlo prediction in the signal region. Comparing this method to other background estimation techniques shows improvements with respect to statistical and systematic uncertainties. The proposed method can also be applied in other fields beyond high energy physics.

关键词： Analysis and statistical methods data processing methods

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Multivariate side-band subtraction using probabilistic event weights

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JOURNAL OF INSTRUMENTATION 2009年第10期4卷 P10003-P10003页

作者： Williams, M. Bellis, M. Meyer, C. A. Carnegie Mellon Univ Pittsburgh PA 15213 USA

A common situation in experimental physics is to have a signal which can not be separated from a non-interfering background through the use of any selection criteria. In this paper, we describe a procedure for determining, on an event-by-event basis, a quality factor (Q-factor) that a given signal candidate originated from the signal sample. This procedure generalizes the "side-band" subtraction method to higher dimensions without requiring the data to be divided into bins. The Q-factors can then be used as event weights in subsequent analysis procedures, allowing one to more directly access the true spectrum of the signal.

关键词： Analysis and statistical methods data processing methods

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