Breast tissue characterization with photon-counting spectral CT imaging: a postmortem breast study.

PURPOSE: To investigate the feasibility of breast tissue characterization in terms of water, lipid, and protein contents with a spectral computed tomographic (CT) system based on a cadmium zinc telluride (CZT) photon-counting detector by using postmortem breasts. MATERIALS AND METHODS: Nineteen pairs of postmortem breasts were imaged with a CZT-based photon-counting spectral CT system with beam energy of 100 kVp. The mean glandular dose was estimated to be in the range of 1.8-2.2 mGy. The images were corrected for pulse pile-up and other artifacts by using spectral distortion corrections. Dual-energy decomposition was then applied to characterize each breast into water, lipid, and protein contents. The precision of the three-compartment characterization was evaluated by comparing the composition of right and left breasts, where the standard error of the estimations was determined. The results of dual-energy decomposition were compared by using averaged root mean square to chemical analysis, which was used as the reference standard. RESULTS: The standard errors of the estimations of the right-left correlations obtained from spectral CT were 7.4%, 6.7%, and 3.2% for water, lipid, and protein contents, respectively. Compared with the reference standard, the average root mean square error in breast tissue composition was 2.8%. CONCLUSION: Spectral CT can be used to accurately quantify the water, lipid, and protein contents in breast tissue in a laboratory study by using postmortem specimens.

Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system.

PURPOSE: To investigate the feasibility of breast tissue composition in terms of water, lipid, and protein with a cadmium-zinc-telluride (CZT) based computed tomography (CT) system to help better characterize suspicious lesions. METHODS: Simulations and experimental studies were performed using a spectral CT system equipped with a CZT-based photon-counting detector with energy resolution. Simulations of the figure-of-merit (FOM), the signal-to-noise ratio (SNR) of the dual energy image with respect to the square root of mean glandular dose (MGD), were performed to find the optimal configuration of the experimental acquisition parameters. A calibration phantom 3.175 cm in diameter was constructed from polyoxymethylene plastic with cylindrical holes that were filled with water and oil. Similarly, sized samples of pure adipose and pure lean bovine tissues were used for the three-material decomposition. Tissue composition results computed from the images were compared to the chemical analysis data of the tissue samples. RESULTS: The beam energy was selected to be 100 kVp with a splitting energy of 40 keV. The tissue samples were successfully decomposed into water, lipid, and protein contents. The RMS error of the volumetric percentage for the three-material decomposition, as compared to data from the chemical analysis, was estimated to be approximately 5.7%. CONCLUSIONS: The results of this study suggest that the CZT-based photon-counting detector may be employed in the CT system to quantify the water, lipid, and protein mass densities in tissue with a relatively good agreement.

Volumetric lean percentage measurement using dual energy mammography.

PURPOSE: Currently, there is no accepted standard for measuring breast density. Dual energy mammography, which has demonstrated accurate measurement in phantoms, has been proposed as one possible method. To examine the use of chemical analysis as a possible means to validate breast density measurements from dual energy mammography, a bovine tissue model was investigated. Known quantities of lean and adipose tissue were compared with composition values measured from dual energy images and chemical analysis. METHODS: Theoretical simulations were performed to assess the impact variations in breast composition would have on measurement of breast density from a single calibration. Fourteen ex-vivo tissue samples composed of varying amounts of pure lean tissue and pure adipose tissue (lean percentage) from 0 to 100%, in increments of 10%, were imaged using dual energy mammography. This was followed by chemical analysis based on desiccation, trituration, and fat extraction with petroleum ether to determine water, lipid, and protein content. The volumetric lean percentage (VLP) as measured from images (VLP(I)) and as derived from chemical analysis data (VLP(CA)) were compared with the VLP calculated from measurements of sample mass with a scale (VLP(M)). Finally, data from the bovine tissue model in this study were compared to compositional data from a previous report of human tissue composition. RESULTS: The results from simulation suggest a substantial impact on measuring breast density is likely due to changes in anatomical breast composition. VLP(I) was related to the VLP(M) by VLP(I) = 1.53 VLP(M) + 10.0 (r2 > 0.99). VLP(CA) was related to VLP(M) by VLP(CA) = 0.76 VLP(M) + 22.8 (r2 > 0.99). VLP(I) was related to VLP(CA) by VLP(I) = 2.00 VLP(CA) - 35.6 (r2 > 0.99). Bovine adipose tissue was shown to be very similar to human adipose tissue in terms of water, lipid, and protein content with RMS differences of 1.2%. Bovine lean tissue was shown to be very similar to human skeletal muscle tissue and somewhat similar to human mammary gland tissue with RMS differences of 0.4 and 22.2%, respectively. CONCLUSIONS: The results of this study show strong linear relationships between volumetric lean percentage measurements using dual energy mammography, chemical analysis and the actual mass. Determining the existence of a relationship between VLP(I) and VLP(CA) was necessary before comparing density results from the dual energy technique to composition data from chemical analysis for samples of unknown composition.

Quantification of breast density with dual energy mammography: an experimental feasibility study.

PURPOSE: Breast density, the percentage of glandular breast tissue, has been shown to be a strong indicator of breast cancer risk. A quantitative method to measure breast density with dual energy mammography was investigated using physical phantoms. METHODS: The dual energy mammography system used a tungsten anode x-ray tube with a 50 microm rhodium beam filter for low energy images and a 300 microm copper beam filter for high energy images. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Four different phantom studies were used to evaluate the technique. The first study consisted of phantoms with thicknesses of 2.5-8.5 cm in 0.5 cm steps with variable densities centered at a mean of 28%. The second study consisted of phantoms at a fixed thickness of 4.0 cm, which ranged in densities from 0% to 100% in increments of 12.5%. The third study consisted of 4.0 cm thick phantoms at densities of 25%, 50% and 75% each imaged at three areal sizes, approximately 62.5, 125, and 250 cm2, in order to assess the effect of breast size on density measurement. The fourth study consisted of step phantoms designed to more closely mimic the shape of a female breast with maximal thicknesses from 3.0 to 7.0 cm at a fixed density of 50%. All images were corrected for x-ray scatter. RESULTS: The RMS errors in breast density measurements were 0.44% for the variable thickness phantoms, 0.64% for the variable density phantoms, 2.87% for the phantoms of different areal sizes, and 4.63% for step phantoms designed to closely resemble the shape of a breast. CONCLUSIONS: The results of the phantom studies indicate that dual energy mammography can be used to measure breast density with an RMS error of approximately 5%.

Radiation dose reduction using a CdZnTe-based computed tomography system: comparison to flat-panel detectors.

PURPOSE: Although x-ray projection mammography has been very effective in early detection of breast cancer, its utility is reduced in the detection of small lesions that are occult or in dense breasts. One drawback is that the inherent superposition of parenchymal structures makes visualization of small lesions difficult. Breast computed tomography using flat-panel detectors has been developed to address this limitation by producing three-dimensional data while at the same time providing more comfort to the patients by eliminating breast compression. Flat panels are charge integrating detectors and therefore lack energy resolution capability. Recent advances in solid state semiconductor x-ray detector materials and associated electronics allow the investigation of x-ray imaging systems that use a photon counting and energy discriminating detector, which is the subject of this article. METHODS: A small field-of-view computed tomography (CT) system that uses CdZnTe (CZT) photon counting detector was compared to one that uses a flat-panel detector for different imaging tasks in breast imaging. The benefits afforded by the CZT detector in the energy weighting modes were investigated. Two types of energy weighting methods were studied: Projection based and image based. Simulation and phantom studies were performed with a 2.5 cm polymethyl methacrylate (PMMA) cylinder filled with iodine and calcium contrast objects. Simulation was also performed on a 10 cm breast specimen. RESULTS: The contrast-to-noise ratio improvements as compared to flat-panel detectors were 1.30 and 1.28 (projection based) and 1.35 and 1.25 (image based) for iodine over PMMA and hydroxylapatite over PMMA, respectively. Corresponding simulation values were 1.81 and 1.48 (projection based) and 1.85 and 1.48 (image based). Dose reductions using the CZT detector were 52.05% and 49.45% for iodine and hydroxyapatite imaging, respectively. Image-based weighting was also found to have the least beam hardening effect. CONCLUSIONS: The results showed that a CT system using an energy resolving detector reduces the dose to the patient while maintaining image quality for various breast imaging tasks.

Quantification of breast density with dual energy mammography: a simulation study.

Breast density, the percentage of glandular breast tissue, has been identified as an important yet underutilized risk factor in the development of breast cancer. A quantitative method to measure breast density with dual energy imaging was investigated using a computer simulation model. Two configurations to measure breast density were evaluated: the usage of monoenergetic beams and an ideal detector, and the usage of polyenergetic beams with spectra from a tungsten anode x-ray tube with a detector modeled after a digital mammography system. The simulation model calculated the mean glandular dose necessary to quantify the variability of breast density to within 1/3%. The breast was modeled as a semicircle 10 cm in radius with equal homogenous thicknesses of adipose and glandular tissues. Breast thicknesses were considered in the range of 2-10 cm and energies in the range of 10-150 keV for the two monoenergetic beams, and 20-150 kVp for spectra with a tungsten anode x-ray tube. For a 4.2 cm breast thickness, the required mean glandular doses were 0.183 microGy for two monoenergetic beams at 19 and 71 keV, and 9.85 microGy for two polyenergetic spectra from a tungsten anode at 32 and 96 kVp with beam filtrations of 50 microm Rh and 300 microm Cu for the low and high energy beams, respectively. The results suggest that for either configuration, breast density can be precisely measured with dual energy imaging requiring only a small amount of additional dose to the breast. The possibility of using a standard screening mammogram as the low energy image is also discussed.

Dual-energy cardiac imaging: an image quality and dose comparison for a flat-panel detector and x-ray image intensifier.

This study presents a comparison of dual-energy imaging with an x-ray image intensifier and flat-panel detector for cardiac imaging. It also investigates if the wide dynamic range of the flat-panel detector can improve dual-energy image quality while reducing patient dose. Experimental contrast-to-noise (CNR) measurements were carried out in addition to simulation studies. Patient entrance exposure and system tube loading were also recorded. The studied contrast objects were calcium and iodine. System performance was quantified with a figure-of-merit (FOM) defined as the image CNR(2) over patient entrance exposure. The range of thickness studied was from 10 to 30 cm of Lucite (PMMA). Detector dose was initially set to 140 nGy (16 microR)/frame. The high-energy 120 kVp beam was filtered by an additional 0.8 mm silver filter. Keeping the same filament current, the kVp for the low-energy beam was adjusted as a function of thickness until 140 nGy was achieved. System performance was found to be similar for both systems, with the x-ray image intensifier performing better at lower thicknesses and the flat-panel detector performing better at higher thicknesses. This requirement of fixed detector entrance exposure was then relaxed and the kVp for the low-energy beam was allowed to vary while the mAs of the x-ray tube remained fixed to study changes in dual-energy image quality, patient dose and FOM with the flat-panel detector. It was found that as the kVp for the low-energy beam was reduced, system performance would rise until reaching a maximum while simultaneously lowering patient exposure. Suggested recommendations for optimal dual-energy imaging implementation are also provided.

Optimization of a flat-panel based real time dual-energy system for cardiac imaging.

A simulation study was conducted to evaluate the effects of high-energy beam filtration, dual-gain operation and noise reduction on dual-energy images using a digital flat-panel detector. High-energy beam filtration increases image contrast through greater beam separation and tends to reduce total radiation exposure and dose per image pair. It is also possible to reduce dual-energy image noise by acquiring low and high-energy images at two different detector gains. In addition, dual-energy noise reduction algorithms can further reduce image noise. The cumulative effect of these techniques applied in series was investigated in this study. The contrast from a small thickness of calcium was simulated over a step phantom of tissue equivalent material with a CsI phosphor as the image detector. The dual-energy contrast-to-noise ratio was calculated using values of energy absorption and energy variance. A figure-of-merit (FOM) was calculated from dual-energy contrast-to-noise ratio (CNR) and patient effective dose estimated from values of entrance exposure. Filter atomic numbers in the range of 1-100 were considered with thicknesses ranging from 0-2500 mg/cm2. The simulation examined combinations of the above techniques which maximized the FOM. The application of a filter increased image contrast by as much as 45%. Near maximal increases were seen for filter atomic numbers in the range of 40-60 and 85-100 with masses above 750 mg/cm2. Increasing filter thickness beyond 1000 mg/cm2 increased tube loading without further significant contrast enhancement. No additional FOM improvements were seen with dual gain before or after the application of any noise reduction algorithm. Narrow beam experiments were carried out to verify predictions. The measured FOM increased by more than a factor of 3.5 for a silver filter thickness of 800 microm, equal energy weighting and application of a noise clipping algorithm. The main limitation of dynamic high-energy filtration is increased tube loading. The results of this study can be used to help develop an optimal dual-energy imaging system.

Feasibility of real time dual-energy imaging based on a flat panel detector for coronary artery calcium quantification.

The feasibility of a real-time dual-energy imaging technique with dynamic filtration using a flat panel detector for quantifying coronary arterial calcium was evaluated. In this technique, the x-ray beam was switched at 15 Hz between 60 kVp and 120 kVp with the 120 kVp beam having an additional 0.8 mm silver filter. The performance of the dynamic filtration technique was compared with a static filtration technique (4 mm Al+0.2 mm Cu for both beams). The ability to quantify calcium mass was evaluated using calcified arterial vessel phantoms with 20-230 mg of hydroxylapatite. The vessel phantoms were imaged over a Lucite phantom and then an anthropomorphic chest phantom. The total thickness of Lucite phantom ranges from 13.5-26.5 cm to simulate patient thickness of 16-32 cm. The calcium mass was measured using a densitometric technique. The effective dose to patient was estimated from the measured entrance exposure. The effects of patient thickness on contrast-to-noise ratio (CNR), effective dose, and the precision of calcium mass quantification (i.e., the frame to frame variability) were studied. The effects of misregistration artifacts were also measured by shifting the vessel phantoms manually between low- and high-energy images. The results show that, with the same detector signal level, the dynamic filtration technique produced 70% higher calcium contrast-to-noise ratio with only 4% increase in patient dose as compared to the static filtration technique. At the same time, x-ray tube loading increased by 30% with dynamic filtration. The minimum detectability of calcium with anatomical background was measured to be 34 mg of hydroxyapatite. The precision in calcium mass measurement, determined from 16 repeated dual-energy images, ranges from 13 mg to 41 mg when the patient thickness increased from 16 to 32 cm. The CNR was found to decrease with the patient thickness linearly at a rate of (-7%/cm). The anatomic background produced measurement root-mean-square (RMS) errors of 13 mg and 18 mg when the vessel phantoms were imaged over a uniform (over the rib) and nonuniform (across the edge of rib) bone background, respectively. Misregistration artifacts due to motions of up to 1.0 mm between the low- and high-energy images introduce RMS error of less than 4.3 mg, which is much smaller than the frame to frame variability and the measurement error due to anatomic background. The effective dose ranged from 1.1 to 6.6 microSv for each dual-energy image, depending on patient thickness. The study shows that real-time dual-energy imaging can potentially be used as a low dose technique for quantifying coronary arterial calcium.

Real-time tumor tracking using implanted positron emission markers: concept and simulation study.

The delivery accuracy of radiation therapy for pulmonary and abdominal tumors suffers from tumor motion due to respiration. Respiratory gating should be applied to avoid the use of a large target volume margin that results in a substantial dose to the surrounding normal tissue. Precise respiratory gating requires the exact spatial position of the tumor to be determined in real time during treatment. Usually, fiducial markers are implanted inside or next to the tumor to provide both accurate patient setup and real-time tumor tracking. However, current tumor tracking systems require either substantial x-ray exposure to the patient or large fiducial markers that limit the value of their application for pulmonary tumors. We propose a real-time tumor tracking system using implanted positron emission markers (PeTrack). Each marker will be labeled with low activity positron emitting isotopes, such as 124I, 74As, or 84Rb. These isotopes have half-lives comparable to the duration of radiation therapy (from a few days to a few weeks). The size of the proposed PeTrack marker will be 0.5-0.8 mm, which is approximately one-half the size of markers currently employed in other techniques. By detecting annihilation gammas using position-sensitive detectors, multiple positron emission markers can be tracked in real time. A multimarker localization algorithm was developed using an Expectation-Maximization clustering technique. A Monte Carlo simulation model was developed for the PeTrack system. Patient dose, detector sensitivity, and scatter fraction were evaluated. Depending on the isotope, the lifetime dose from a 3.7 MBq PeTrack marker was determined to be 0.7-5.0 Gy at 10 mm from the marker. At the center of the field of view (FOV), the sensitivity of the PeTrack system was 240-320 counts/s per 1 MBq marker activity within a 30 cm thick patient. The sensitivity was reduced by 45% when the marker was near the edge of the FOV. The scatter fraction ranged from 12% (124I, 74As) to 16% (84Rb). In addition, four markers (labeled with 124I) inside a 30 cm diameter water phantom were simulated to evaluate the feasibility of the multimarker localization algorithm. Localization was considered successful if a marker was localized to within 2 mm from its true location. The success rate of marker localization was found to depend on the number of annihilation events used and the error in the initial estimate of the marker position. By detecting 250 positron annihilation events from 4 markers (average of 62 events per marker), the marker success rates for initial errors of +/-5, +/-10, and +/-15 mm were 99.9%, 99.6%, and 92.4%, respectively. Moreover, the average localization error was 0.55 (+/-0.27) mm, which was independent of initial error. The computing time for localizing four markers was less than 20 ms (Pentium 4, 2.8 GHz processor, 512 MB memory). In conclusion, preliminary results demonstrate that the PeTrack technique can potentially provide real-time tumor tracking with low doses associated with the marker's activity. Furthermore, the small size of PeTrack markers is expected to facilitate implantation and reduce patient risk.

Positron autoradiography for intravascular imaging: feasibility evaluation.

Approximately 70% of acute coronary artery disease is caused by unstable (vulnerable) plaques with an inflammation of the overlying cap and high lipid content. A rupturing of the inflamed cap of the plaque results in propagation of the thrombus into the lumen, blockage of the artery and acute ischaemic syndrome or sudden death. Morphological imaging such as angiography or intravascular ultrasound cannot determine inflammation status of the plaque. A radiotracer such as 18F-FDG is accumulated in vulnerable plaques due to higher metabolic activity of the inflamed cap and could be used to detect a vulnerable plaque. However, positron emission tomography (PET) cannot detect the FDG-labelled plaques because of respiratory and heart motions, small size and low activity of the plaques. Plaques can be detected using a miniature particle (positron) detector inserted into the artery. In this work, a new detector concept is investigated for intravascular imaging of the plaques. The detector consists of a storage phosphor tip bound to the end of an intravascular catheter. It can be inserted into an artery, absorb the 18F-FDG positrons from the plaques, withdrawn from the artery and read out. Length and diameter of the storage phosphor tip can be matched to the length and the diameter of the artery. Monte Carlo simulations and experimental evaluations of coronary plaque imaging with the proposed detector were performed. It was shown that the sensitivity of the storage phosphor detector to the positrons of 18F-FDG is sufficient to detect coronary plaques with 1 mm and 2 mm sizes and 590 Bq and 1180 Bq activities in the arteries with 2 mm and 3 mm diameters, respectively. An experimental study was performed using plastic tubes with 2 mm diameter filled with an FDG solution, which simulates blood. FDG spots simulating plaques were placed over the surface of the tube. A phosphor tip was inserted into the tube and imaged the plaques. Exposure time was 1 min in all simulations and experiments. Experiments showed that detecting the coronary plaques using the proposed technique is possible. The proposed technique has the potential for fast and accurate detection of vulnerable coronary and other intravascular plaques.

Automated technique for angiographic determination of coronary blood flow and lumen volume.

RATIONALE AND OBJECTIVES: Visual interpretation of angiographic images has been shown to be inadequate for assessing the severity of intermediate coronary stenoses. An approach for evaluating both the anatomic and functional impact of a stenosis is needed. An automated technique for determining both coronary blood flow and lumen volume based on a first-pass analysis (FPA) of coronary angiograms and a template matching algorithm was evaluated. MATERIALS AND METHODS: Coronary angiograms of a swine animal model were obtained during power injections of contrast material into the left coronary ostium. Background anatomy was subtracted with an automated phase matching program. A template matching algorithm and first-pass analysis were then used to quantify coronary blood flow and lumen volume. Coronary blood flow and lumen volume measurements were validated with a transit-time ultrasound flow probe and a polymer cast of the coronary arteries, respectively. RESULTS: In 14 independent comparisons, the mean coronary blood flow measured with FPA showed strong correlation with the mean flow measured with the ultrasound flow probe (Q(FPA) = 0.88Q(probe) - 1.99; r = 0.977; standard error of estimate = 3.23 mL/minute). The lumen volumes determined with FPA and cast measurements demonstrated excellent correlation and can be related to each other by V(FPA) = 0.95V(C) - 0.01 (r = 0.997; standard error of estimate = 0.01 mL). CONCLUSIONS: The proposed automated method for accurate determination of coronary blood flow and lumen volume can supplement visual evaluation of coronary anatomy with quantitative physiologic data. This automated technique potentially offers a clinically feasible method of quantifying coronary blood flow and lumen volume in conjunction with routine cardiac catheterization.

Postmortem validation of breast density using dual-energy mammography.

PURPOSE: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. METHODS: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. RESULTS: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. CONCLUSIONS: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.

Measurement of breast tissue composition with dual energy cone-beam computed tomography: a postmortem study.

PURPOSE: To investigate the feasibility of a three-material compositional measurement of water, lipid, and protein content of breast tissue with dual kVp cone-beam computed tomography (CT) for diagnostic purposes. METHODS: Simulations were performed on a flat panel-based computed tomography system with a dual kVp technique in order to guide the selection of experimental acquisition parameters. The expected errors induced by using the proposed calibration materials were also estimated by simulation. Twenty pairs of postmortem breast samples were imaged with a flat-panel based dual kVp cone-beam CT system, followed by image-based material decomposition using calibration data obtained from a three-material phantom consisting of water, vegetable oil, and polyoxymethylene plastic. The tissue samples were then chemically decomposed into their respective water, lipid, and protein contents after imaging to allow direct comparison with data from dual energy decomposition. RESULTS: Guided by results from simulation, the beam energies for the dual kVp cone-beam CT system were selected to be 50 and 120 kVp with the mean glandular dose divided equally between each exposure. The simulation also suggested that the use of polyoxymethylene as the calibration material for the measurement of pure protein may introduce an error of -11.0%. However, the tissue decomposition experiments, which employed a calibration phantom made out of water, oil, and polyoxymethylene, exhibited strong correlation with data from the chemical analysis. The average root-mean-square percentage error for water, lipid, and protein contents was 3.58% as compared with chemical analysis. CONCLUSIONS: The results of this study suggest that the water, lipid, and protein contents can be accurately measured using dual kVp cone-beam CT. The tissue compositional information may improve the sensitivity and specificity for breast cancer diagnosis.

Breast density quantification with cone-beam CT: a post-mortem study.

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The per cent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson's r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation.

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.

PURPOSE: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. METHODS: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. RESULTS: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. CONCLUSIONS: The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

Dynamic dual-energy chest radiography: a potential tool for lung tissue motion monitoring and kinetic study.

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat-panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual-energy system used in this study can acquire up to 15 frames of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1-3.0 frames per second). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy.

Reproducibility of breast arterial calcium mass quantification using digital mammography.

RATIONALE AND OBJECTIVES: Breast arterial calcification (BAC) detected on mammography is frequently not included in final reports. However, previous studies have indicated that BAC may be evidence of general atherosclerotic vascular disease, and it can potentially be a useful marker of coronary artery disease. In addition, there are currently no available techniques for the quantification of calcium mass using mammography. The purpose of this study was to evaluate the reproducibility and inter-reader agreement of a technique for the quantification of BAC using standard digital mammography. MATERIALS AND METHODS: BAC mass was measured in a convenient, consecutive sample of 39 women aged 49 to 82 years attending routine mammographic examinations. BAC mass measurements were performed in standard mediolateral oblique (MLO) and craniocaudal (CC) views. To assess reproducibility, the BAC measurements obtained in MLO and CC views were compared. RESULTS: The measured BAC masses in CC (M(CC)) and MLO (M(MLO)) projections were related by M(CC) = 0.82(M(MLO)) + 0.27 mg (r = 0.97; standard error of estimation [SEE], 3.44 mg). The measured BAC masses in the left (M(L)) and right (M(R)) breasts were related by M(L) = 0.86(M(R)) - 0.06 mg (r = 0.95; SEE, 4.30 mg). The intraclass correlation coefficients for the measurement of calcium mass ranged from 0.94 in the left CC view to 0.99 in the right CC view. CONCLUSION: A densitometry technique for the quantification of BAC mass was evaluated in patients using standard full-field digital mammography. The results demonstrated that this densitometric technique for the quantification of BAC mass is highly reproducible and has excellent inter-reader agreement. This technique may provide a quantitative metric for future studies relating the severity of BAC and cardiovascular risk.