Microcalcification detection in full-field digital mammograms: A fully automated computer-aided system.

BACKGROUND: Microcalcification clusters in mammograms can be considered as early signs of breast cancer. However, their detection is a very challenging task because of different factors: large variety of breast composition, highly textured breast anatomy, impalpable size of microcalcifications in some cases, as well as inherent low contrast of mammograms. Thus, the need to support the clinicians' work with an automatic tool. METHODS: In this work a three-phases approach for clustered microcalcification detection is presented. Specifically, it is made up of a pre-processing step, aimed at highlighting potentially interesting breast structures, followed by a single microcalcification detection step, based on Hough transform, that is able to grasp the innate characteristic shape of the structures of interest. Finally, a cluster identification step to group microcalcifications is carried out by means of a clustering algorithm able to codify expert domain rules. RESULTS: The detection performance of the proposed method has been evaluated on 364 mammograms of 182 patients obtaining a true positive ratio of 91.78% with 2.87 false positives per image. CONCLUSIONS: Experimental results demonstrated that the proposed method is able to detect microcalcification clusters in digital mammograms showing performance comparable to different methodologies exploited in the state-of-art approaches, with the advantage that it does not require any training phase and a large set of data. The performance of the proposed approach remains high even for more difficult clinical cases of mammograms of young women having high-density breast tissue thus resulting in a reduced contrast between microcalcifications and surrounding dense tissues.

A Gradient-Based Approach for Breast DCE-MRI Analysis.

Breast cancer is the main cause of female malignancy worldwide. Effective early detection by imaging studies remains critical to decrease mortality rates, particularly in women at high risk for developing breast cancer. Breast Magnetic Resonance Imaging (MRI) is a common diagnostic tool in the management of breast diseases, especially for high-risk women. However, during this examination, both normal and abnormal breast tissues enhance after contrast material administration. Specifically, the normal breast tissue enhancement is known as background parenchymal enhancement: it may represent breast activity and depends on several factors, varying in degree and distribution in different patients as well as in the same patient over time. While a light degree of normal breast tissue enhancement generally causes no interpretative difficulties, a higher degree may cause difficulty to detect and classify breast lesions at Magnetic Resonance Imaging even for experienced radiologists. In this work, we intend to investigate the exploitation of some statistical measurements to automatically characterize the enhancement trend of the whole breast area in both normal and abnormal tissues independently from the presence of a background parenchymal enhancement thus to provide a diagnostic support tool for radiologists in the MRI analysis.

Towards breast tomography with synchrotron radiation at Elettra: first images.

The aim of the SYRMA-CT collaboration is to set-up the first clinical trial of phase-contrast breast CT with synchrotron radiation (SR). In order to combine high image quality and low delivered dose a number of innovative elements are merged: a CdTe single photon counting detector, state-of-the-art CT reconstruction and phase retrieval algorithms. To facilitate an accurate exam optimization, a Monte Carlo model was developed for dose calculation using GEANT4. In this study, high isotropic spatial resolution (120 µm)(3) CT scans of objects with dimensions and attenuation similar to a human breast were acquired, delivering mean glandular doses in the range of those delivered in clinical breast CT (5-25 mGy). Due to the spatial coherence of the SR beam and the long distance between sample and detector, the images contain, not only absorption, but also phase information from the samples. The application of a phase-retrieval procedure increases the contrast-to-noise ratio of the tomographic images, while the contrast remains almost constant. After applying the simultaneous algebraic reconstruction technique to low-dose phase-retrieved data sets (about 5 mGy) with a reduced number of projections, the spatial resolution was found to be equal to filtered back projection utilizing a four fold higher dose, while the contrast-to-noise ratio was reduced by 30%. These first results indicate the feasibility of clinical breast CT with SR.

Luminosity-independent measurement of the proton-proton total cross section at √s=8 TeV.

The TOTEM collaboration has measured the proton-proton total cross section at √s=8 TeV using a luminosity-independent method. In LHC fills with dedicated beam optics, the Roman pots have been inserted very close to the beam allowing the detection of ~90% of the nuclear elastic scattering events. Simultaneously the inelastic scattering rate has been measured by the T1 and T2 telescopes. By applying the optical theorem, the total proton-proton cross section of (101.7±2.9) mb has been determined, well in agreement with the extrapolation from lower energies. This method also allows one to derive the luminosity-independent elastic and inelastic cross sections: σ(el)=(27.1±1.4) mb; σ(inel)=(74.7±1.7) mb.

Double diffractive cross-section measurement in the forward region at the LHC.

The first double diffractive cross-section measurement in the very forward region has been carried out by the TOTEM experiment at the LHC with a center-of-mass energy of sqrt[s]=7 TeV. By utilizing the very forward TOTEM tracking detectors T1 and T2, which extend up to |η|=6.5, a clean sample of double diffractive pp events was extracted. From these events, we determined the cross section σDD=(116±25) µb for events where both diffractive systems have 4.7<|η|min<6.5.

Quantitative phase retrieval with picosecond X-ray pulses from the ATF Inverse Compton Scattering source.

Quantitative phase retrieval is experimentally demonstrated using the Inverse Compton Scattering X-ray source available at the Accelerator Test Facility (ATF) in the Brookhaven National Laboratory. Phase-contrast images are collected using in-line geometry, with a single X-ray pulse of approximate duration of one picosecond. The projected thickness of homogeneous samples of various polymers is recovered quantitatively from the time-averaged intensity of transmitted X-rays. The data are in good agreement with the expectations showing that ATF Inverse Compton Scattering source is suitable for performing phase-sensitive quantitative X-ray imaging on the picosecond scale. The method shows promise for quantitative imaging of fast dynamic phenomena.

MAGIC-5: an Italian mammographic database of digitised images for research.

The implementation of a database of digitised mammograms is discussed. The digitised images were collected beginning in 1999 by a community of physicists in collaboration with radiologists in several Italian hospitals as a first step in developing and implementing a computer-aided detection (CAD) system. All 3,369 mammograms were collected from 967 patients and classified according to lesion type and morphology, breast tissue and pathology type. A dedicated graphical user interface was developed to visualise and process mammograms to support the medical diagnosis directly on a high-resolution screen. The database has been the starting point for developing other medical imaging applications, such as a breast CAD, currently being upgraded and optimised for use in a distributed environment with grid services, in the framework of the Instituto Nazionale di Fisicia Nucleare (INFN)-funded Medical Applications on a Grid Infrastructure Connection (MAGIC)-5 project.

Comparison of two portable solid state detectors with an improved collimation and alignment device for mammographic x-ray spectroscopy.

We describe a portable system for mammographic x-ray spectroscopy, based on a 2 X 2 X 1 mm3 cadmium telluride (CdTe) solid state detector, that is greatly improved over a similar system based on a 3 X 3 X 2 mm3 cadmium zinc telluride (CZT) solid state detector evaluated in an earlier work. The CdTe system utilized new pinhole collimators and an alignment device that facilitated measurement of mammographic x-ray spectra. Mammographic x-ray spectra acquired by each system were comparable. Half value layer measurements obtained using an ion chamber agreed closely with those derived from the x-ray spectra measured by either detector. The faster electronics and other features of the CdTe detector allowed its use with a larger pinhole collimator than could be used with the CZT detector. Additionally, the improved pinhole collimator and alignment features of the apparatus permitted much more rapid setup for acquisition of x-ray spectra than was possible on the system described in the earlier work. These improvements in detector technology, collimation and ease of alignment, as well as low cost, make this apparatus attractive as a tool for both laboratory research and advanced mammography quality control.

A completely automated CAD system for mass detection in a large mammographic database.

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing second-order spatial statistics information on the pixel gray level intensity. As the images under study were recorded in different centers and with different machine settings, eight GTSDM features were selected so as to be invariant under monotonic transformation. In this way, the images do not need to be normalized, as the adopted features depend on the texture only, rather than on the gray tone levels, too. (c) ROI classification by means of a neural network, with supervision provided by the radiologist's diagnosis. The CAD system was evaluated on a large database of 3369 mammographic images [2307 negative, 1062 pathological (or positive), containing at least one confirmed mass, as diagnosed by an expert radiologist]. To assess the performance of the system, receiver operating characteristic (ROC) and free-response ROC analysis were employed. The area under the ROC curve was found to be Az = 0.783 +/- 0.008 for the ROI-based classification. When evaluating the accuracy of the CAD against the radiologist-drawn boundaries, 4.23 false positives per image are found at 80% of mass sensitivity.

GPCALMA: a Grid-based tool for mammographic screening.

OBJECTIVES: The next generation of high energy physics (HEP) experiments requires a GRID approach to a distributed computing system: the key concept is the Virtual ORGANISATION (VO), a group of distributed users with a common goal and the will to share their resources. METHODS: A similar approach, applied to a group of hospitals that joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. The application code makes use of neural networks for the image analysis and is useful in improving the radiologists' diagnostic performance. GRID services allow remote image analysis and interactive online diagnosis, with a potential for a relevant reduction of the delays presently associated with screening programs. RESULTS AND CONCLUSIONS: A prototype of the system, based on AliEn GRID Services [1], is already available, with a central server running common services [2] and several clients connecting to it. Mammograms can be acquired in any location; the related information required to select and access them at any time is stored in a common service called Data Catalogue, which can be queried by any client. Thanks to the PROOF facility [3], the result of a query can be used as input for analysis algorithms, which are executed on the nodes where the input images are stored,. The selected approach avoids data transfers for all the images with a negative diagnosis and allows an almost real time diagnosis for the set of images with high cancer probability.

Direct analysis of molybdenum target generated x-ray spectra with a portable device.

In routine applications, information about the photon flux of x-ray tubes is obtained from exposure measurements and cataloged spectra. This approach relies mainly on the assumption that the real spectrum is correctly approximated by the cataloged one, once the main characteristics of the tube such as voltage, target material, anode angle, and filters are taken account of. In practice, all this information is not always available. Moreover, x-ray tubes with the same characteristics may have different spectra. We describe an apparatus that should be useful for quality control in hospitals and for characterizing new radiographic systems. The apparatus analyzes the spectrum generated by an x-ray mammographic unit. It is based on a commercial CZT produced by AMPTEK Inc. and a set of tungsten collimator disks. The electronics of the CZT are modified so as to obtain a faster response. The signal is digitized using an analog to digital converter with a sampling frequency of up to 20 MHz. The whole signal produced by the x-ray tube is acquired and analyzed off-line in order to accurately recognize pile-up events and reconstruct the emitted spectrum. The energy resolution has been determined using a calibrated x-ray source. Spectra were validated by comparison of the HVL measured using an ionization chamber.

[Application of a computer-aided detection (CAD) system to digitalized mammograms for identifying microcalcifications]. / Applicazione di un sistema di Computer Aided Detection (CAD) a mammografie digitalizzate nell-individuazione di microcalcificazioni.

PURPOSE: It is estimated that during mammographic screening programs radiologists fail to detect approximately 25% of breast cancers visible on retrospective review; this percentage rises to 50% if minimal signs are considered. Independent double reading is now strongly recommended as it allows to reduce the rate of false negative examinations by 5-15%. Recent technological progress has allowed to develop a number of computer-aided detection (CAD) systems. The aim of CAD is to help radiologists interpret lesions by serving as a second reader. In this study the authors developed and applied a CAD system to measure its ability to microcalcifications detect and compare its performance with that of a human observer. MATERIAL AND METHODS: The study was performed as part of the CALMA (computer-aided library for mammography) project of the Pisa section of the National Institute of Nuclear Physics. The aim of this project is to set up a large database of digital mammograms and to develop a CAD system. Our study series consisted of 802 mammograms - corresponding to 213 patients - digitalized between March and June 2000. We performed traditional mammography and then digitalized the mammograms using a CCD linear scanner (pixel size of 85 x 85 microm2, 12 bits). The images were evaluated by two radiologists with similar experience and then by the CAD system. This CAD system searches for microcalcifications by using ad hoc algorithms and an artificial neural network (Sanger type). RESULTS: The number of clusters in our database was 141 corresponding to 140 images; 692 images were non pathological. The CAD system identified a variable number of clusters depending on the threshold values. The threshold value is a number over which the probability of finding a lesion is highest. With thresholds of 0.13 and 0.14 the CAD system identified 140/141 clusters (99.3%); with a threshold of 0.15 it identified 139/141 clusters (98.6%); with a threshold of 0.16, 137/141 (97.2%); with a threshold of 0.18, 133/141 (94.3%); with thresholds of 0.18 and 0.20, 130/141 (92.2%). With threshold values of 0.13, 0.14, 0.15, 0.16 and 0.17 the system's sensitivity was greater than 82%, whereas with values of 0.18 and 0.20 it was greater than 80%. The number of false positive region of interest (ROI) / image was greater with low threshold values: in particular, thresholds of 0.13 and 0.14 yielded 16 false positives /image, thresholds of 0.15 and 0.16 yielded 9 and 7 false positives/image, and both 0.18 and 0.20 only 5/image. DISCUSSION: ROC curve shows how the use of high threshold values determined a very high specificity despite very low sensitivity rates. Conversely, low threshold values allowed to have a high sensitivity and a very low specificity. The best performance of our CAD system was obtained with threshold values at 0.15 and 0.16. In fact these thresholds resulted in a high sensitivity (greater than 82%) with an acceptable number of false positives/image, 9 and 7/image, respectively. It is not yet known how radiologists can deal with large numbers of false positives in screening programmes but in our opinion the most important feature of a good CAD system is a high sensitivity. CONCLUSIONS: In the near future the use of CAD systems will be widespread and easier to apply to everyday practice above all in centers where digital mammography is performed. Mammograms could be directly shown to radiologists after the CAD system has selected the ROI and analysed the images. Thanks to its high sensitivity and despite its low specificity CAD represents a concrete aid for radiologists.

Correlation between hydroperoxide-induced chemiluminescence of the heart and its function.

The isolated perfused rat heart emits a spontaneous ultraweak chemiluminescence. When the perfusion is stopped, light emission decreases, indicating the dependency of this phenomenon on aerobic metabolism. Emitted chemiluminescence was markedly enhanced following perfusion with 0.05 mM H2O2 or cumene hydroperoxide or tert-butyl hydroperoxide; substitution of O2 for N2 in the gassing mixture of the perfusion media significantly lowered photon emission. Lipid peroxidation, which is known to be associated with chemiluminescence, was evaluated by HPLC analysis of peroxidized and unperoxidized heart phosphatidylcholines. During hydroperoxide perfusion, coronary flow and heart rate progressively decreased, while lactic dehydrogenase was released after complete cardiac arrest. The resultant morphology of this damage corresponds to the so-called 'stone heart', a pattern already described in both human and experimental pathology.