Noise power properties of a cone-beam CT system for breast cancer detection

Noise power spectrum (NPS) in computed tomography: Enabling local NPS measurement without stationarity and ergodicity assumptions

BACKGROUND

Conventional methods for estimating the noise power spectrum (NPS) often necessitate multiple computed tomography (CT) data acquisitions and are required to satisfy stringent stationarity and ergodicity conditions, which prove challenging in CT imaging systems.

PURPOSE

The aim was to revisit the conventional NPS estimation method, leading to a new framework that estimates local NPS without relying on stationarity or ergodicity, thus facilitating experimental NPS estimations.

METHODS

The scientific foundation of the conventional CT NPS measurement method, based on the Wiener-Khintchine theorem, was reexamined, emphasizing the critical conditions of stationarity and ergodicity. This work proposes an alternative framework, characterized by its independence from stationarity and ergodicity, and its ability to facilitate local NPS estimations. A spatial average of local NPS over a Region of Interest (ROI) yields the conventional NPS for that ROI. The connections and differences between the proposed alternative method and the conventional method are discussed. Experimental studies were conducted to validate the new method.

RESULTS

(1) The NPS estimated using the conventional method was demonstrated to correspond to the spatial average of pointwise NPS from the proposed NPS estimation framework. (2) The NPS estimated over an ROI with the conventional method was shown to be the sum of the NPS estimated from the proposed method and a contribution from measurement uncertainty. (3) Local NPS estimations from the proposed method in this work elucidate the impact of surrounding image content on local NPS variations.

CONCLUSION

The NPS estimation method proposed in this work allows for the estimation of local NPS without relying on stationarity and ergodicity conditions, offering local NPS estimations with significantly improved precision.

Experimental measurement of local noise power spectrum (NPS) in photon counting detector-CT (PCD-CT) using a single data acquisition

BACKGROUND

Accurate noise power spectra (NPS) measurement in clinical X-ray CT exams is challenging due to the need for repeated scans, which expose patients to high radiation risks. A reliable method for single CT acquisition NPS estimation is thus highly desirable.

PURPOSE

To develop a method for estimating local NPS from a single photon counting detector-CT (PCD-CT) acquisition.

METHODS

A novel nearly statistical bias-free estimator was constructed from the raw counts data of PCD-CT scan to estimate the variance of sinogram projection data. An analytical algorithm is employed to reconstruct point-wise covariancecov ( x i , x j ) $\text{cov}({\bf x}_i,{\bf x}_j)$ between any two image pixel/voxel locationsx i ${\bf x}_i$ andx j ${\bf x_j}$ . A Fourier transform is applied to obtain the desired point-wise NPS for any chosen locationx i ${\bf x}_i$ . The method was validated using experimental data acquired from a benchtop PCD-CT system with various physical phantoms, and the results were compared with the conventional local NPS measurement method using repeated scans and statistical ensemble averaging.

RESULTS

The experimental results demonstrate that (1) the proposed method can achieve pointwise/local NPS measurement for a region of interest (ROI) located at any chosen position, accurately characterizing the NPS with spatial structures resulting from image content heterogeneity; (2) the local NPS measured using the proposed method show a higher precision in the measured NPS compared to the conventional measurement method; (3) spatial averaging of the local NPS yields the conventional NPS for a given local ROI.

CONCLUSION

A new method was developed to enable local NPS from a single PCD-CT acquisition.

Microwave Imaging and Sensing Techniques for Breast Cancer Detection

Medical imaging techniques, including X-ray mammography, ultrasound, and magnetic resonance imaging, play a crucial role in the timely identification and monitoring of breast cancer. However, these conventional imaging modalities have their limitations, and there is a need for a more accurate and sensitive alternative. Microwave imaging has emerged as a promising technique for breast cancer detection due to its non-ionizing, non-invasive, and cost-effective nature. Recent advancements in microwave imaging and sensing techniques have opened up new possibilities for the early diagnosis and treatment of breast cancer. By combining microwave sensing with machine learning techniques, microwave imaging approaches can rapidly and affordably identify and classify breast tumors. This manuscript provides a comprehensive overview of the latest developments in microwave imaging and sensing techniques for the early detection of breast cancer. It discusses the principles and applications of microwave imaging and highlights its advantages over conventional imaging modalities. The manuscript also delves into integrating machine learning algorithms to enhance the accuracy and efficiency of microwave imaging in breast cancer detection.

AI Denoising Significantly Enhances Image Quality and Diagnostic Confidence in Interventional Cone-Beam Computed Tomography

(1) To investigate whether interventional cone-beam computed tomography (cbCT) could benefit from AI denoising, particularly with respect to patient body mass index (BMI); (2) From 1 January 2016 to 1 January 2022, 100 patients with liver-directed interventions and peri-procedural cbCT were included. The unenhanced mask run and the contrast-enhanced fill run of the cbCT were reconstructed using weighted filtered back projection. Additionally, each dataset was post-processed using a novel denoising software solution. Place-consistent regions of interest measured signal-to-noise ratio (SNR) per dataset. Corrected mixed-effects analysis with BMI subgroup analyses compared objective image quality. Multiple linear regression measured the contribution of “Radiation Dose”, “Body-Mass-Index”, and “Mode” to SNR. Two radiologists independently rated diagnostic confidence. Inter-rater agreement was measured using Spearman correlation (r); (3) SNR was significantly higher in the denoised datasets than in the regular datasets (p < 0.001). Furthermore, BMI subgroup analysis showed significant SNR deteriorations in the regular datasets for higher patient BMI (p < 0.001), but stable results for denoising (p > 0.999). In regression, only denoising contributed positively towards SNR (0.6191; 95%CI 0.6096 to 0.6286; p < 0.001). The denoised datasets received overall significantly higher diagnostic confidence grades (p = 0.010), with good inter-rater agreement (r ≥ 0.795, p < 0.001). In a subgroup analysis, diagnostic confidence deteriorated significantly for higher patient BMI (p < 0.001) in the regular datasets but was stable in the denoised datasets (p ≥ 0.103).; (4) AI denoising can significantly enhance image quality in interventional cone-beam CT and effectively mitigate diagnostic confidence deterioration for rising patient BMI.

Determination of the optimal range for virtual monoenergetic images in dual-energy CT based on physical quality parameters

PURPOSE

Virtual monoenergetic images (VMI) obtained from Dual-Energy Computed Tomography (DECT) with iodinated contrast are used in radiotherapy of the Head and Neck to improve the delineation of target volumes and organs at-risk (OAR). The energies used to vary from 40 to 70 keV, but noise at low keV and the use of Single Energy CT (SECT) at low kV_p settings may shrink this interval. There is no guide about how to find out the optimal range where VMI has a significant improvement related to SECT images. Our study proposes a procedure to determine this optimal range, based on common image quality parameters, and establishes this range in a Siemens Somatom Confidence and a Head and Neck protocol.

METHODS

We compared the quality of the VMI series at 40-60 keV versus single X-ray tube voltage computed tomography (SECT) at 80 and 120 kV_p . Our reference was 120 kV_p . DECT images were sequentially acquired using the Siemens Somatom Confidence RT Pro CT according to the head and neck protocol in our department. VMI series were constructed using the Syngo Via software Monoenergetic+ algorithm. Quality parameters were: image uniformity, high- and low-contrast resolution, noise, and sensitivity to the iodinated contrast. We used the Catphan 604 phantom for quality control, except when assessing iodine sensitivity. To evaluate high contrast resolution, we calculated the modulation transfer function (MTF) using the point spread function estimation of a point bead and the slanted edge methods. For the low-contrast resolution, we used a statistical method for assessing differences between contrast structures and local noise. To measure the absolute value of noise and compare its texture, we used the standard deviation and the noise power spectrum. We measured iodine sensitivity by dissolving the Optiray Ultraject iodinated contrast in water in concentrations of 0 to 4500 mg/l and then compared the contrast to noise ratio (CNR) and analyzed the linear correlation between concentration and HU.

RESULTS

The entire series met the minimum quality requirements. However, the one at 40 keV presented uniformity at the limits of acceptability. The high- and low-contrast resolutions were similar between series. The noise of the VMI series decreased with increasing energy, while sensitivity to the contrast displayed the opposite behavior. All series showed linearity of HUs from very low iodine concentrations. Images at 60 keV presented lower iodine sensitivity than SECT at 80 kV_p , while those at 55 keV were similar to them.

CONCLUSIONS

Our method of image comparison based on standard quality parameters in phantom gave clear results about the optimal range and can be used as a guide to characterize any other DECT imaging protocols. The optimal range for using VMI images in iodinated contrasts in the Siemens system was 45-55 keV. Lower energies lacked noise and uniformity, while higher ones could be substituted by SECT images at low kilovoltage (80 kV_p ).

Multi-pass approach to reduce cone-beam artifacts in a circular orbit cone-beam CT system

We propose a multi-pass approach to reduce cone-beam artifacts in a circular orbit cone-beam computed tomography (CT) system. Employing a large 2D detector array reduces the scan time but produces cone-beam artifacts in the Feldkamp, Davis, and Kress (FDK) reconstruction because of insufficient sampling for exact reconstruction. While the two-pass algorithm proposed by Hsieh is effective at reducing cone-beam artifacts, the correction performance is degraded when the bone density is moderate and the cone angle is large. In this work, we treated the cone-beam artifacts generated from bone and soft tissue as if they were from less dense bone objects and corrected them iteratively. The proposed method was validated using a numerical Defrise phantom, XCAT phantom data, and experimental data from a pediatric phantom followed by image quality assessment for FDK, the two-pass algorithm, the proposed method, and the total variation minimization-based iterative reconstruction (TV-IR). The results show that the proposed method was superior to the two-pass algorithm in cone-beam artifact reduction and effectively reduced the overcorrection by the two-pass algorithm near bone regions. It can also be observed that the proposed method produced better correction performance with fewer iterations than the TV-IR algorithm. A qualitative evaluation with mean-squared error, structural similarity, and structural dissimilarity demonstrated the effectiveness of the proposed method.

Characterization of CT Hounsfield Units for 3D acquisition trajectories on a dedicated breast CT system

Hounsfield Units (HU) are used clinically in differentiating tissue types in a reconstructed CT image, and therefore the HU accuracy of a system is important, especially when using multiple sources, novel detector and non-traditional trajectories. Dedicated clinical breast CT (BCT) systems therefore should be similarly evaluated. In this study, uniform cylindrical phantoms filled with various uniform density fluids were used to characterize differences in HU values between simple circular and complex 3D (saddle) orbits. Based on ACR recommendations, the HU accuracy, center-to-edge variability within a slice, and overall variability within the reconstructed volume were characterized for simple and complex acquisitions possible on a single versatile BCT system. Results illustrate the statistically significantly better performance of the saddle orbit, especially close to the chest and nipple regions of what would clinically be a pendant breast volume. The incomplete cone beam acquisition of a simple circular orbit causes shading artifacts near the nipple, due to insufficient sampling, rendering a major portion of the scanned phantom unusable, whereas the saddle orbit performs exceptionally well and provides a tighter distribution of HU values throughout the reconstructed volumes. This study further establishes the advantages of using 3D acquisition trajectories for breast CT as well as other applications by demonstrating the robustness of HU values throughout large reconstructed volumes.

Noise Power Characteristics of a Micro-Computed Tomography System

OBJECTIVE

The aim of this study was to investigate the noise power properties of a micro-computed tomography (micro-CT) system under different operating conditions.

METHODS

A commercial micro-CT was used in the study that used a flat panel detector with a 127-μm-pixel pitch and a micro-focus x-ray tube. Conical tubes of various diameters were used under different acquisition conditions. Multidimensional noise power spectrums were used as a metric to investigate the noise properties of the system. Noise power spectrum was calculated from the difference data generated by subtraction of 2 identical scans. The noise properties with respect to various parameters that include the impact of number of projections, x-ray spectra, milliampere-second, slice location, object diameter, voxel size, geometric magnification (M), back-projection filters, and reconstruction magnification (Mrecon) were studied.

RESULTS

At a same isocentric exposure rate of 270 mR/s, the noise power was much lower for the image reconstructed with 3672 views (122 seconds) as compared with the 511 views (17 seconds), whereas at a fixed isocentric exposure of 4600 mR, the noise power levels were almost similar. Image noise with a 50-kV beam was higher as compared with the 90-kV beam at a same isocentric exposure. Image noise from a 16-mm-diameter conical tube was much lower as compared with the 28- and 56-mm tubes under identical isocentric exposures. The choice of back-projection filter influences noise power spectrum curves in terms of width and amplitudes. Reconstruction magnification applied during the reconstruction process increased the noise power at lower spatial frequencies but reduced the noise power at higher spatial frequencies. It can be established that, for small details corresponding to high spatial frequencies, reconstruction magnification can provide an improved signal-to-noise ratio. At all spatial frequencies, the in-plane images had lower noise power levels as compared with the z-plane images.

CONCLUSIONS

The noise power properties investigated in this study provide important image quality references for refined cone beam system development, optimization, and operations.

Impact of bowtie filter and object position on the two-dimensional noise power spectrum of a clinical MDCT system

PURPOSE

Noise characteristics of clinical multidetector CT (MDCT) systems can be quantified by the noise power spectrum (NPS). Although the NPS of CT has been extensively studied in the past few decades, the joint impact of the bowtie filter and object position on the NPS has not been systematically investigated. This work studies the interplay of these two factors on the two dimensional (2D) local NPS of a clinical CT system that uses the filtered backprojection algorithm for image reconstruction.

METHODS

A generalized NPS model was developed to account for the impact of the bowtie filter and image object location in the scan field-of-view (SFOV). For a given bowtie filter, image object, and its location in the SFOV, the shape and rotational symmetries of the 2D local NPS were directly computed from the NPS model without going through the image reconstruction process. The obtained NPS was then compared with the measured NPSs from the reconstructed noise-only CT images in both numerical phantom simulation studies and experimental phantom studies using a clinical MDCT scanner. The shape and the associated symmetry of the 2D NPS were classified by borrowing the well-known atomic spectral symbols s, p, and d, which correspond to circular, dumbbell, and cloverleaf symmetries, respectively, of the wave function of electrons in an atom. Finally, simulated bar patterns were embedded into experimentally acquired noise backgrounds to demonstrate the impact of different NPS symmetries on the visual perception of the object.

RESULTS

(1) For a central region in a centered cylindrical object, an s-wave symmetry was always present in the NPS, no matter whether the bowtie filter was present or not. In contrast, for a peripheral region in a centered object, the symmetry of its NPS was highly dependent on the bowtie filter, and both p-wave symmetry and d-wave symmetry were observed in the NPS. (2) For a centered region-ofinterest (ROI) in an off-centered object, the symmetry of its NPS was found to be different from that of a peripheral ROI in the centered object, even when the physical positions of the two ROIs relative to the isocenter were the same. (3) The potential clinical impact of the highly anisotropic NPS, caused by the interplay of the bowtie filter and position of the image object, was highlighted in images of specific bar patterns oriented at different angles. The visual perception of the bar patterns was found to be strongly dependent on their orientation.

CONCLUSIONS

The NPS of CT depends strongly on the bowtie filter and object position. Even if the location of the ROI with respect to the isocenter is fixed, there can be different symmetries in the NPS, which depend on the object position and the size of the bowtie filter. For an isolated off-centered object, the NPS of its CT images cannot be represented by the NPS measured from a centered object.

Temporal subtraction contrast-enhanced dedicated breast CT

The development of a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, intensity difference adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using normalized cross correlation (NCC), symmetric uncertainty coefficient, normalized mutual information (NMI), mean square error (MSE) and target registration error (TRE). The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE (0-16%), NCC (0-6%), NMI (0-13%) and TRE (0-34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake.

Evolution of spatial resolution in breast CT at UC Davis

PURPOSE

Dedicated breast computed tomography (bCT) technology for the purpose of breast cancer screening has been a focus of research at UC Davis since the late 1990s. Previous studies have shown that improvement in spatial resolution characteristics of this modality correlates with greater microcalcification detection, a factor considered a potential limitation of bCT. The aim of this study is to improve spatial resolution as characterized by the modulation transfer function (MTF) via changes in the scanner hardware components and operational schema.

METHODS

Four prototypes of pendant-geometry, cone-beam breast CT scanners were designed and developed spanning three generations of design evolution. To improve the system MTF in each bCT generation, modifications were made to the imaging components (x-ray tube and flat-panel detector), system geometry (source-to-isocenter and detector distance), and image acquisition parameters (technique factors, number of projections, system synchronization scheme, and gantry rotational speed).

RESULTS

Characterization of different generations of bCT systems shows these modifications resulted in a 188% improvement of the limiting MTF properties from the first to second generation and an additional 110% from the second to third. The intrinsic resolution degradation in the azimuthal direction observed in the first generation was corrected by changing the acquisition from continuous to pulsed x-ray acquisition. Utilizing a high resolution detector in the third generation, along with modifications made in system geometry and scan protocol, resulted in a 125% improvement in limiting resolution. An additional 39% improvement was obtained by changing the detector binning mode from 2 × 2 to 1 × 1.

CONCLUSIONS

These results underscore the advancement in spatial resolution characteristics of breast CT technology. The combined use of a pulsed x-ray system, higher resolution flat-panel detector and changing the scanner geometry and image acquisition logic resulted in a significant fourfold improvement in MTF.

Task-based optimization of dedicated breast CT via Hotelling observer metrics

PURPOSE

The purpose of this work is to develop and demonstrate a set of practical metrics for CT systems optimization. These metrics, based on the Hotelling observer (HO) figure of merit, are task-based. The authors therefore take the specific example of optimizing a dedicated breast CT system, including the reconstruction algorithm, for two relevant tasks, signal detection and Rayleigh discrimination.

METHODS

A dedicated breast CT system is simulated using specifications in the literature from an existing prototype. The authors optimize configuration and image reconstruction algorithm parameters for two tasks: the detection of simulated microcalcifications and the discrimination of two adjacent, high-contrast signals, known as the Rayleigh discrimination task. The effects on task performance of breast diameter, signal location, image grid size, projection view number, and reconstruction filter were all investigated. Two HO metrics were evaluated: the percentage of correct decisions in a two-alternative forced choice experiment (equivalent to area under the ROC curve or AUC), and the HO efficiency, defined as the squared ratio of HO signal-to-noise ratio (SNR) in the reconstructed image to HO SNR in the projection data.

RESULTS

The ease and efficiency of the HO metric computation allows a rapid high-resolution survey of many system parameters. Optimization of a range of system parameters using the HO results in images that subjectively appear optimal for the tasks investigated. Further, the results of assessment through the HO reproduce closely many existing results in the literature regarding the impact of parameter selection on image quality.

CONCLUSIONS

This study demonstrates the utility of a task-based approach to system design, evaluation, and optimization. The methodology presented is equally applicable to determining the impact of a wide range of factors, including patient parameters, system and acquisition design, and the reconstruction algorithm. The results demonstrate the versatility of the proposed HO formalism by not only generating a set of parameters that are optimal for a given task but also by qualitatively reproducing many existing results from the breast CT literature. Meanwhile, the implementation of the proposed methodology is straightforward and entirely simulation-based. This is an attractive feature for many system optimization problems, where the goal is to analyze the individual system components such as the image reconstruction algorithm. Final assessment of the system as a whole should be based also on real data studies.

Characteristic performance evaluation of a photon counting Si strip detector for low dose spectral breast CT imaging

PURPOSE

The possible clinical applications which can be performed using a newly developed detector depend on the detector's characteristic performance in a number of metrics including the dynamic range, resolution, uniformity, and stability. The authors have evaluated a prototype energy resolved fast photon counting x-ray detector based on a silicon (Si) strip sensor used in an edge-on geometry with an application specific integrated circuit to record the number of x-rays and their energies at high flux and fast frame rates. The investigated detector was integrated with a dedicated breast spectral computed tomography (CT) system to make use of the detector's high spatial and energy resolution and low noise performance under conditions suitable for clinical breast imaging. The aim of this article is to investigate the intrinsic characteristics of the detector, in terms of maximum output count rate, spatial and energy resolution, and noise performance of the imaging system.

METHODS

The maximum output count rate was obtained with a 50 W x-ray tube with a maximum continuous output of 50 kVp at 1.0 mA. A109Cd source, with a characteristic x-ray peak at 22 keV from Ag, was used to measure the energy resolution of the detector. The axial plane modulation transfer function (MTF) was measured using a 67 μm diameter tungsten wire. The two-dimensional (2D) noise power spectrum (NPS) was measured using flat field images and noise equivalent quanta (NEQ) were calculated using the MTF and NPS results. The image quality parameters were studied as a function of various radiation doses and reconstruction filters. The one-dimensional (1D) NPS was used to investigate the effect of electronic noise elimination by varying the minimum energy threshold.

RESULTS

A maximum output count rate of 100 million counts per second per square millimeter (cps/mm2) has been obtained (1 million cps per 100×100 μm pixel). The electrical noise floor was less than 4 keV. The energy resolution measured with the 22 keV photons from a 109Cd source was less than 9%. A reduction of image noise was shown in all the spatial frequencies in 1D NPS as a result of the elimination of the electronic noise. The spatial resolution was measured just above 5 line pairs per mm (lp/mm) where 10% of MTF corresponded to 5.4 mm(-1). The 2D NPS and NEQ shows a low noise floor and a linear dependence on dose. The reconstruction filter choice affected both of the MTF and NPS results, but had a weak effect on the NEQ.

CONCLUSIONS

The prototype energy resolved photon counting Si strip detector can offer superior imaging performance for dedicated breast CT as compared to a conventional energy-integrating detector due to its high output count rate, high spatial and energy resolution, and low noise characteristics, which are essential characteristics for spectral breast CT imaging.

Dose and image quality of cone-beam computed tomography as compared with conventional multislice computed tomography in abdominal imaging

OBJECTIVES

Recent technical developments have facilitated the application of cone-beam computed tomography (CBCT) for interventional and intraoperative imaging. The aim of this study was to compare the radiation doses and image quality in CBCT with those of conventional multislice spiral computed tomography (MSCT) for abdominal and genitourinary imaging.

METHODS

Different CBCT and MSCT protocols for imaging soft tissues and hard-contrast objects at different dose levels were investigated in this study. Local skin and organ doses were measured with thermoluminescent dosimeters placed in an anthropomorphic phantom. Moreover, the contrast-to-noise ratio, the noise-power spectrum, and the high-contrast resolution derived from the modulation transfer function were determined in a phantom with the same absorption properties as those of anthropomorphic phantom.

RESULTS

The effective dose of the examined abdominal/genitourinary CBCT protocols ranged between 0.35 mSv and 18.1 mSv. As compared with MSCT, the local skin dose of CBCT examinations could locally reach much higher doses up to 190 mGy. The effective dose necessary to realize the same contrast-to-noise ratio with CBCT and MSCT depended on the MSCT convolution kernel: the MSCT dose was smaller than the corresponding CBCT dose for a soft kernel but higher than that for a hard kernel. The noise-power spectrum of the CBCT images at tube voltages of 85/90 kV(p) is at least half of that of images measured at 103/115 kV(p) at any arbitrarily chosen spatial frequency. Although the pixel size and slice thickness of CBCT were half of those of the MSCT images, high-contrast resolution was inferior to the MSCT images reconstructed with a hard convolution kernel.

CONCLUSIONS

As compared with MSCT using a medium-hard convolution kernel, CBCT produces images at medium noise levels and, simultaneously, medium spatial resolution at approximately the same dose. It is well suited for visualizing hard-contrast objects in the abdomen with relatively low image noise and patient dose. For the detection of low-contrast objects at standard tube voltages of approximately 120 kV(p), however, MSCT should be preferred.

A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom

PURPOSE

To develop an easily-implemented technique with free publicly-available analysis software to measure the modulation transfer function (MTF) and noise-power spectrum (NPS) of a clinical computed tomography (CT) system from images acquired using a widely-available and standardized American College of Radiology (ACR) CT accreditation phantom.

METHODS

Images of the ACR phantom were acquired on a Siemens SOMATOM Definition Flash system using a standard adult head protocol: 120 kVp, 300 mAs, and reconstructed voxel size of 0.49 mm × 0.49 mm × 4.67 mm. The radial (axial) MTF was measured using an edge method where the boundary of the third module of the ACR phantom, originally designed to measure uniformity and noise, was used as a circular edge. The 3D NPS was measured using images from this same module and using a previously-described methodology that quantifies noise magnitude and 3D noise correlation.

RESULTS

The axial MTF was radially symmetrical and had a value of 0.1 at 0.62 mm(-1). The 3D NPS shape was consistent with the filter-ramp function of filtered-backprojection reconstruction algorithms and previously reported values. The radial NPS peak value was ∼115 HU(2)mm(3) at ∼0.25 mm(-1) and dropped to 0 HU(2)mm(3) by 0.8 mm(-1).

CONCLUSIONS

The authors have developed an easily-implementable technique to measure the axial MTF and 3D NPS of clinical CT systems using an ACR phantom. The widespread availability of the phantom along with the free software the authors have provided will enable many different institutions to immediately measure MTF and NPS values for comparison of protocols and systems.

Anatomical complexity in breast parenchyma and its implications for optimal breast imaging strategies

PURPOSE

The purpose of this investigation was to assess the anatomical noise in breast images using a mathematically derived parameter β as a surrogate for detection performance, across the same patient cohort but in different imaging modalities including mammography, tomosynthesis, and breast CT.

METHODS

Women who were scheduled for breast biopsy were approached for participation in this IRB and HIPPA-compliant investigation. A total of 23 women had all views of each modality and represent the cohort studied in this investigation. Image data sets across all modalities were analyzed using 1000 regions of interest per image data set, and the anatomical noise power spectrum, NPS(a)(f), was computed and averaged for each breast image data set. After windowing the total noise power spectrum NPS(t)(f) to a specific frequency range corresponding to anatomical noise, the power-law slope (β) of the NPS(a)(f) was computed where NPS(a)(f) = α f(-) (β).

RESULTS

The value of β was determined for breast CT data sets, and they were 1.75 (0.424), 1.83 (0.352), and 1.79 (0.397), for the coronal, sagittal, and axial views, respectively. For tomosynthesis, β was 3.06 (0.361) and 3.10 (0.315) for the craniocaudal (CC) and medial lateral oblique (MLO) views, respectively. For mammography, these values were 3.17 (0.226) and 3.30 (0.236), for the CC and MLO views, respectively. The values of β for breast CT were significantly different than those for tomosynthesis and mammography (p < 0.001, all 12 comparisons).

CONCLUSIONS

Based on the parameter β which is thought to describe anatomical noise in breast images, breast CT was shown to have a statistically significant lower β than mammography or tomosynthesis. It has been suggested in the literature that a lower β may correspond to increased cancer detection performance; however, this has yet to be demonstrated unequivocally.

Comprehensive assessment of the slice sensitivity profiles in breast tomosynthesis and breast CT

PURPOSE

This study experimentally evaluated the slice sensitivity profile (SSP) and its relationship between acquisition angle, object size, and cone angle. The sensitivity profile metric was used to characterize a breast tomosynthesis system's resolution in the z-axis. The SSP was also measured on a prototype breast computed tomography (bCT) system.

METHODS

The SSP was measured using brass disks placed within adipose tissue-equivalent breast phantoms. The digital tomosynthesis system (Selenia Dimensions, Hologic Corporation, Bedford, MA) acquires projection images over a 15° angular range and the bCT scanner acquires projection images over a 360° angular range. Angular ranges between 15° and 360° were studied by using a subset of the projection images acquired on the bCT scanner. The SSP was determined by measuring a background-corrected mean gray scale value as a function of the z-position (axis normal to the plane of the detector).

RESULTS

The results show that SSP improves when the angular acquisition range is increased and the SSP approaches a delta function for angles greater than 180°. Smaller objects have a narrower SSP and the SSP is not significantly dependent on the cone angle. For a 2.5, 5, 10 mm disk, the full width at half maximum of the SSP was 35, 61, 115 mm, respectively, on the tomosynthesis system (at 15°) and was 0.5 mm for all disk diameters on the bCT scanner (at 360°).

CONCLUSIONS

The SSP is dependent on object size and angular acquisition range. These dependencies are overcome once the angular acquisition range is increased beyond 180°.

Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities

Previous research has demonstrated that a parameter extracted from a power function fit to the anatomical noise power spectrum, β, may be predictive of breast mass lesion detectability in x-ray based medical images of the breast. In this investigation, the value of β was compared with a number of other more widely used parameters, in order to determine the relationship between β and these other parameters. This study made use of breast CT data sets, acquired on two breast CT systems developed in our laboratory. A total of 185 breast data sets in 183 women were used, and only the unaffected breast was used (where no lesion was suspected). The anatomical noise power spectrum computed from two-dimensional region of interests (ROIs), was fit to a power function (NPS(f) = α f(-β)), and the exponent parameter (β) was determined using log/log linear regression. Breast density for each of the volume data sets was characterized in previous work. The breast CT data sets analyzed in this study were part of a previous study which evaluated the receiver operating characteristic (ROC) curve performance using simulated spherical lesions and a pre-whitened matched filter computer observer. This ROC information was used to compute the detectability index as well as the sensitivity at 95% specificity. The fractal dimension was computed from the same ROIs which were used for the assessment of β. The value of β was compared to breast density, detectability index, sensitivity, and fractal dimension, and the slope of these relationships was investigated to assess statistical significance from zero slope. A statistically significant non-zero slope was considered to be a positive association in this investigation. All comparisons between β and breast density, detectability index, sensitivity at 95% specificity, and fractal dimension demonstrated statistically significant association with p < 0.001 in all cases. The value of β was also found to be associated with patient age and breast diameter, parameters both related to breast density. In all associations between other parameters, lower values of β were associated with increased breast cancer detection performance. Specifically, lower values of β were associated with lower breast density, higher detectability index, higher sensitivity, and lower fractal dimension values. While causality was not and probably cannot be demonstrated, the strong, statistically significant association between the β metric and the other more widely used parameters suggest that β may be considered as a surrogate measure for breast cancer detection performance. These findings are specific to breast parenchymal patterns and mass lesions only.

Effect of slice thickness on detectability in breast CT using a prewhitened matched filter and simulated mass lesions

PURPOSE

Dedicated breast CT (bCT) is an emerging technology with the potential to improve the detection of breast cancer in screening and diagnostic capacities. Typically, the 3D volume reconstructed from the scanner is displayed as sectional images. The purpose of this study was to evaluate the effect of section thickness on the detectability of simulated masses using a prewhitened matched filter (PWMF) as a model observer.

METHODS

A breast CT scanner has been designed and fabricated in the authors' laboratory with more than 200 women imaged in IRB-approved phase I and phase II trials to date. Of these, 151 bilateral data sets were selected on the basis of low artifact content, sufficient breast coverage, and excluding cases with breast implants. BIRADS breast density ratings were available for 144 of these patients. Spherical mass lesions of diameter 1, 2, 3, 5, 11, and 15 mm were mathematically generated and embedded at random locations within the parenchymal region of each bCT volume. Microcalcifications were not simulated in this study. For each viewing plane (sagittal, axial, and coronal) and section thickness (ranging from 0.3 to 44 mm), section images of the breast parenchyma containing the lesion were generated from the reconstructed bCT data sets by averaging voxels over the length of the section. Using signal known exactly (SKE) model observer methodology, receiver operating characteristic (ROC) curve analysis was performed on each generated projected image using a PWMF based model observer. ROC curves were generated for each breast data set, and the area under the ROC curve (AUC) was evaluated as well as the sensitivity at 95% specificity.

RESULTS

For all lesion sizes, performance rises modestly to a peak before falling off substantially as section thickness increases over the range of the study. We find that the optimal section thickness tracks the size of the lesion to be detected linearly with a small positive offset and slopes ranging from 0.27 to 0.44. No significant differences were observed between left and right breasts. Performance measures are negatively correlated with measures of breast density, with an average correlation coefficient of -0.48 for the BIRADS breast density score and -0.81 for the proportion of glandular tissue in the breast interior.

CONCLUSIONS

This study shows quantitatively how PWMF detection performance of a known lesion size is influenced by section thickness in dedicated breast CT. While the optimal section thickness is tuned to the size of the lesion being detected, overall performance is more robust for thin section images compared to thicker images.

Development of a patient-specific two-compartment anthropomorphic breast phantom

The purpose of this paper is to develop a technique for the construction of a two-compartment anthropomorphic breast phantom specific to an individual patient's pendant breast anatomy. Three-dimensional breast images were acquired on a prototype dedicated breast computed tomography (bCT) scanner as part of an ongoing IRB-approved clinical trial of bCT. The images from the breast of a patient were segmented into adipose and glandular tissue regions and divided into 1.59 mm thick breast sections to correspond to the thickness of polyethylene stock. A computer-controlled water-jet cutting machine was used to cut the outer breast edge and the internal regions corresponding to glandular tissue from the polyethylene. The stack of polyethylene breast segments was encased in a thermoplastic 'skin' and filled with water. Water-filled spaces modeled glandular tissue structures and the surrounding polyethylene modeled the adipose tissue compartment. Utility of the phantom was demonstrated by inserting 200 µm microcalcifications as well as by measuring point dose deposition during bCT scanning. Affine registration of the original patient images with bCT images of the phantom showed similar tissue distribution. Linear profiles through the registered images demonstrated a mean coefficient of determination (r(2)) between grayscale profiles of 0.881. The exponent of the power law describing the anatomical noise power spectrum was identical in the coronal images of the patient's breast and the phantom. Microcalcifications were visualized in the phantom at bCT scanning. The real-time air kerma rate was measured during bCT scanning and fluctuated with breast anatomy. On average, point dose deposition was 7.1% greater than the mean glandular dose. A technique to generate a two-compartment anthropomorphic breast phantom from bCT images has been demonstrated. The phantom is the first, to our knowledge, to accurately model the uncompressed pendant breast and the glandular tissue distribution for a specific patient. The modular design of the phantom allows for studies of a single breast segment and the entire breast volume. Insertion of other devices, materials and tissues of interest into the phantom provide a robust platform for future breast imaging and dosimetry studies.

Iterative reconstruction methods in two different MDCT scanners: physical metrics and 4-alternative forced-choice detectability experiments--a phantom approach

This paper characterizes and evaluates the potential of three commercial CT iterative reconstruction methods (ASIR™, VEO™ and iDose⁴(™)) for dose reduction and image quality improvement. We measured CT number accuracy, standard deviation (SD), noise power spectrum (NPS) and modulation transfer function (MTF) metrics on Catphan phantom images while five human observers performed four-alternative forced-choice (4AFC) experiments to assess the detectability of low- and high-contrast objects embedded in two pediatric phantoms. Results show that 40% and 100% ASIR as well as iDose⁴ levels 3 and 6 do not affect CT number and strongly decrease image noise with relative SD constant in a large range of dose. However, while ASIR produces a shift of the NPS curve apex, less change is observed with iDose⁴ with respect to FBP methods. With second-generation iterative reconstruction VEO, physical metrics are even further improved: SD decreased to 70.4% at 0.5 mGy and spatial resolution improved to 37% (MTF(50%)). 4AFC experiments show that few improvements in detection task performance are obtained with ASIR and iDose⁴, whereas VEO makes excellent detections possible even at an ultra-low-dose (0.3 mGy), leading to a potential dose reduction of a factor 3 to 7 (67%-86%). In spite of its longer reconstruction time and the fact that clinical studies are still required to complete these results, VEO clearly confirms the tremendous potential of iterative reconstructions for dose reduction in CT and appears to be an important tool for patient follow-up, especially for pediatric patients where cumulative lifetime dose still remains high.

An open environment CT-US fusion for tissue segmentation during interventional guidance

Therapeutic ultrasound (US) can be noninvasively focused to activate drugs, ablate tumors and deliver drugs beyond the blood brain barrier. However, well-controlled guidance of US therapy requires fusion with a navigational modality, such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT). Here, we developed and validated tissue characterization using a fusion between US and CT. The performance of the CT/US fusion was quantified by the calibration error, target registration error and fiducial registration error. Met-1 tumors in the fat pads of 12 female FVB mice provided a model of developing breast cancer with which to evaluate CT-based tissue segmentation. Hounsfield units (HU) within the tumor and surrounding fat pad were quantified, validated with histology and segmented for parametric analysis (fat: −300 to 0 HU, protein-rich: 1 to 300 HU, and bone: HU>300). Our open source CT/US fusion system differentiated soft tissue, bone and fat with a spatial accuracy of ∼1 mm. Region of interest (ROI) analysis of the tumor and surrounding fat pad using a 1 mm² ROI resulted in mean HU of 68±44 within the tumor and −97±52 within the fat pad adjacent to the tumor (p<0.005). The tumor area measured by CT and histology was correlated (r² = 0.92), while the area designated as fat decreased with increasing tumor size (r² = 0.51). Analysis of CT and histology images of the tumor and surrounding fat pad revealed an average percentage of fat of 65.3% vs. 75.2%, 36.5% vs. 48.4%, and 31.6% vs. 38.5% for tumors <75 mm³, 75–150 mm³ and >150 mm³, respectively. Further, CT mapped bone-soft tissue interfaces near the acoustic beam during real-time imaging. Combined CT/US is a feasible method for guiding interventions by tracking the acoustic focus within a pre-acquired CT image volume and characterizing tissues proximal to and surrounding the acoustic focus.

Local and global 3D noise power spectrum in cone-beam CT system with FDK reconstruction

PURPOSE

The authors examine the nonstationary noise behavior of a cone-beam CT system with FDK reconstruction.

METHODS

To investigate the nonstationary noise behavior, an analytical expression for the NPS of local volumes and an entire volume was derived and quantitatively compared to the NPS estimated from experimental air and water images.

RESULTS

The NPS of local volumes at different locations along the z-axis showed radial symmetry in the f(x)-f(y) plane and different missing cone regions in the f(z) direction depending on the tilt angle of rays through the local volumes. For local volumes away from the z-axis, the NPS of air and water images showed sharp transitions in the f(x)-f(y) and f(y)-f(z) planes and lack of radial symmetry in the f(x)-f(y) plane. These effects are mainly caused by varying magnification and different noise levels from view to view. In the NPS of the entire volume, the f(x)-f(y) plane showed radial symmetry because the nonstationary noise behaviors of local volumes were averaged out. The nonstationary sharp transitions were manifested as a high-frequency roll-off.

CONCLUSIONS

The results from noise power analysis for local volumes and an entire volume demonstrate the spatially varying noise behavior in the reconstructed cone-beam CT images.

A GMM-based breast cancer risk stratification using a resonance-frequency electrical impedance spectroscopy

PURPOSE

The authors developed and tested a multiprobe-based resonance-frequency-based electrical impedance spectroscopy (REIS) system. The purpose of this study was to preliminarily assess the performance of this system in classifying younger women into two groups, those ultimately recommended for biopsy during imaging-based diagnostic workups that followed screening and those rated as negative during mammography.

METHODS

A seven probe-based REIS system was designed, assembled, and is currently being tested in the breast imaging facility. During an examination, contact is made with the nipple and six concentric points on the breast skin. For each measurement channel between the center probe and one of the six external probes, a set of electrical impedance spectroscopy (EIS) signal sweeps is performed and signal outputs ranging from 200 to 800 kHz at 5 kHz interval are recorded. An initial subset of 174 examinations from an ongoing prospective clinical study was selected for this preliminary analysis. An initial set of 35 features, 33 of which represented the corresponding EIS signal differences between the left and right breasts, was established. A Gaussian mixture model (GMM) classifier was developed to differentiate between "positive" (biopsy recommended) cases and "negative" (nonbiopsy) cases. Selecting an optimal feature set was performed using genetic algorithms with an area under a receiver operating characteristic curve (AUC) as the fitness criterion.

RESULTS

The recorded EIS signal sweeps showed that, in general, negative (nonbiopsy) examinations have a higher level of electrical impedance symmetry between the two breasts than positive (biopsy) examinations. Fourteen features were selected by genetic algorithm and used in the optimized GMM classifier. Using a leave-one-case-out test, the GMM classifier yielded a performance level of AUC = 0.78, which compared favorably to other three widely used classifiers including support vector machine, classification tree, and linear discriminant analysis. These results also suggest that the REIS signal based GMM classifier could be used as a prescreening tool to correctly identify a fraction of younger women at higher risk of developing breast cancer (i.e., 47% sensitivity at 90% specificity).

CONCLUSIONS

The study confirms that asymmetry in electrical impedance characteristics between two breasts provides valuable information regarding the presence of a developing breast abnormality; hence, REIS data may be useful in classifying younger women into two groups of "average" and "significantly higher than average" risk of having or developing a breast abnormality that would ultimately result in a later imaging-based recommendation for biopsy.

Experimentally determined spectral optimization for dedicated breast computed tomography

PURPOSE

The current study aimed to experimentally identify the optimal technique factors (x-ray tube potential and added filtration material/thickness) to maximize soft-tissue contrast, microcalcification contrast, and iodine contrast enhancement using cadaveric breast specimens imaged with dedicated breast computed tomography (bCT). Secondarily, the study aimed to evaluate the accuracy of phantom materials as tissue surrogates and to characterize the change in accuracy with varying bCT technique factors.

METHODS

A cadaveric breast specimen was acquired under appropriate approval and scanned using a prototype bCT scanner. Inserted into the specimen were cylindrical inserts of polyethylene, water, iodine contrast medium (iodixanol, 2.5 mg/ml), and calcium hydroxyapatite (100 mg/ml). Six x-ray tube potentials (50, 60, 70, 80, 90, and 100 kVp) and three different filters (0.2 mm Cu, 1.5 mm Al, and 0.2 mm Sn) were tested. For each set of technique factors, the intensity (linear attenuation coefficient) and noise were measured within six regions of interest (ROIs): Glandular tissue, adipose tissue, polyethylene, water, iodine contrast medium, and calcium hydroxyapatite. Dose-normalized contrast to noise ratio (CNRD) was measured for pairwise comparisons among the six ROIs. Regression models were used to estimate the effect of tube potential and added filtration on intensity, noise, and CNRD.

RESULTS

Iodine contrast enhancement was maximized using 60 kVp and 0.2 mm Cu. Microcalcification contrast and soft-tissue contrast were maximized at 60 kVp. The 0.2 mm Cu filter achieved significantly higher CNRD for iodine contrast enhancement than the other two filters (p = 0.01), but microcalcification contrast and soft-tissue contrast were similar using the copper and aluminum filters. The average percent difference in linear attenuation coefficient, across all tube potentials, for polyethylene versus adipose tissue was 1.8%, 1.7%, and 1.3% for 0.2 mm Cu, 1.5 mm Al, and 0.2 mm Sn, respectively. For water versus glandular tissue, the average percent difference was 2.7%, 3.9%, and 4.2% for the three filter types.

CONCLUSIONS

Contrast-enhanced bCT, using injected iodine contrast medium, may be optimized for maximum contrast of enhancing lesions at 60 kVp with 0.2 mm Cu filtration. Soft-tissue contrast and microcalcification contrast may also benefit from lower tube potentials (60 kVp). The linear attenuation coefficients of water and polyethylene slightly overestimate the values of their corresponding tissues, but the reported differences may serve as guidance for dosimetry and quality assurance using tissue equivalent phantoms.

A preliminary evaluation of multi-probe resonance-frequency electrical impedance based measurements of the breast

RATIONALE AND OBJECTIVES

The aim of this study was to preliminarily assess the performance of a new, resonance-frequency electrical impedance spectroscopy (REIS) system in identifying young women who were recommended to undergo breast biopsy following imaging.

MATERIALS AND METHODS

A seven-probe REIS system was designed and assembled and is currently being prospectively tested. During examination, contact is made with the nipple and six concentric points on the breast skin. Signal sweeps are performed, and outputs ranging from 200 to 800 kHz at 5-kHz intervals are recorded. An initial set of 140 patients, including 56 who eventually had biopsies, 63 who had negative results on screening mammography, and 21 recalled for additional imaging but later determined to have negative results, was used. An initial set of 35 features, 33 representing impedance signal differences between breasts and two representing participant age and average breast density, was assembled and reduced by a genetic algorithm to 14. The performance of an artificial neural network-based classifier was assessed using a case-based leave-one-out method.

RESULTS

The substantially greater asymmetry between signals of mirror-matched regions ascertained from biopsy ("positive") compared to nonbiopsy ("negative") cases resulted in an artificial neural network classifier performance (area under the curve) of 0.830 ± 0.023. At 90% specificity, this classifier, optimized for "recommendation for biopsy" rather than "cancer," detected 30 REIS-positive cases (54%), including six of nine (67%) actual cancer cases and six of nine women (67%) recommended for surgical excision of high-risk lesions.

CONCLUSIONS

Asymmetry in impedance measurements between bilateral breasts may provide valuable discriminatory information regarding the presence of highly suspicious imaging-based findings.

Noise variance analysis using a flat panel x-ray detector: a method for additive noise assessment with application to breast CT applications

PURPOSE

A simplified linear model approach was proposed to accurately model the response of a flat panel detector used for breast CT (bCT).

METHODS

Individual detector pixel mean and variance were measured from bCT projection images acquired both in air and with a polyethylene cylinder, with the detector operating in both fixed low gain and dynamic gain mode. Once the coefficients of the linear model are determined, the fractional additive noise can be used as a quantitative metric to evaluate the system's efficiency in utilizing x-ray photons, including the performance of different gain modes of the detector.

RESULTS

Fractional additive noise increases as the object thickness increases or as the radiation dose to the detector decreases. For bCT scan techniques on the UC Davis prototype scanner (80 kVp, 500 views total, 30 frames/s), in the low gain mode, additive noise contributes 21% of the total pixel noise variance for a 10 cm object and 44% for a 17 cm object. With the dynamic gain mode, additive noise only represents approximately 2.6% of the total pixel noise variance for a 10 cm object and 7.3% for a 17 cm object.

CONCLUSIONS

The existence of the signal-independent additive noise is the primary cause for a quadratic relationship between bCT noise variance and the inverse of radiation dose at the detector. With the knowledge of the additive noise contribution to experimentally acquired images, system modifications can be made to reduce the impact of additive noise and improve the quantum noise efficiency of the bCT system.

Noise aliasing and the 3D NEQ of flat-panel cone-beam CT: effect of 2D/3D apertures and sampling

The ability to tune an imaging system to be optimal for a specific task is an essential component of image quality. This article discusses the ability to tune the noise-equivalent quanta (NEQ) of cone-beam computed tomography (CBCT) by managing noise aliasing through binning of data at different points in the reconstruction cascade. The noise power spectrum, modulation transfer function, and NEQ for CBCT are calculated using cascaded systems analysis. Binning is treated as a modular process, insertable between any two stages (in both the 2D projection domain and in the 3D reconstruction domain), consisting of the application of an aperture, followed by the resampling of data (which introduces noise aliasing). Several conditions were examined to demonstrate the validity of the model and to describe the effect on the image quality of some common reconstruction and visualization techniques. It was found that when downsampling data for increased reconstruction speed, binning in 2D results in a superior low-frequency NEQ, while binning in 3D results in a superior high-frequency NEQ. Furthermore, visualization procedures such as slice averaging were found not to degrade the NEQ provided the sampling interval is unchanged. Finally methods for reducing noise aliasing by oversampling are examined, and a method to eliminate noise aliasing without increasing reconstruction time is proposed. These results demonstrate the ease with which the NEQ of CBCT can be modified and thus optimized for specific tasks and show how such analysis can be used to improve image quality.