Girijesh Yadava

Towards task-based assessment of CT performance: System and object MTF across different reconstruction algorithms

PURPOSE To investigate a measurement method for evaluating the resolution properties of CT imaging systems across reconstruction algorithms, dose, and contrast. METHODS An algorithm was developed to extract the task-based modulation transfer function (MTF) from disk images generated from the rod inserts in the ACR phantom (model 464 Gammex, WI). These inserts are conventionally employed for HU accuracy assessment. The edge of the disk objects was analyzed to determine the edge-spread function, which was differentiated to yield the line-spread function and Fourier-transformed to generate the object-specific MTF for task-based assessment, denoted MTFTask . The proposed MTF measurement method was validated against the conventional wire technique and further applied to measure the MTF of CT images reconstructed with an adaptive statistical iterative algorithm (ASIR) and a model-based iterative (MBIR) algorithm. Results were further compared to the standard filtered back projection (FBP) algorithm. Measurements were performed and compared across different doses and contrast levels to ascertain the MTFTask dependencies on those factors. RESULTS For the FBP reconstructed images, the MTFTask measured with the inserts were the same as the MTF measured from the wire-based method. For the ASIR and MBIR data, the MTFTask using the high contrast insert was similar to the wire-based MTF and equal or superior to that of FBP. However, results for the MTFTask measured using the low-contrast inserts, the MTFTask for ASIR and MBIR data was lower than for the FBP, which was constant throughout all measurements. Similarly, as a function of mA, the MTFTask for ASIR and MBIR varied as a function of noise--with MTFTask being proportional to mA. Overall greater variability of MTFTask across dose and contrast was observed for MBIR than for ASIR. CONCLUSIONS This approach provides a method for assessing the task-based MTF of a CT system using conventional and iterative reconstructions. Results demonstrated that the object-specific MTF can vary as a function of dose and contrast. The analysis highlighted the paradigm shift for iterative reconstructions when compared to FBP, where iterative reconstructions generally offer superior noise performance but with varying resolution as a function of dose and contrast. The MTFTask generated by this method is expected to provide a more comprehensive assessment of image resolution across different reconstruction algorithms and imaging tasks.PURPOSE To investigate a measurement method for evaluating the resolution properties of CT imaging systems across reconstruction algorithms, dose, and contrast. METHODS An algorithm was developed to extract the task-based modulation transfer function (MTF) from disk images generated from the rod inserts in the ACR phantom (model 464 Gammex, WI). These inserts are conventionally employed for HU accuracy assessment. The edge of the disk objects was analyzed to determine the edge-spread function, which was differentiated to yield the line-spread function and Fourier-transformed to generate the object-specific MTF for task-based assessment, denoted MTF(Task). The proposed MTF measurement method was validated against the conventional wire technique and further applied to measure the MTF of CT images reconstructed with an adaptive statistical iterative algorithm (ASIR) and a model-based iterative (MBIR) algorithm. Results were further compared to the standard filtered back projection (FBP) algorithm. Measurements were performed and compared across different doses and contrast levels to ascertain the MTF(Task) dependencies on those factors. RESULTS For the FBP reconstructed images, the MTF(Task) measured with the inserts were the same as the MTF measured from the wire-based method. For the ASIR and MBIR data, the MTF(Task) using the high contrast insert was similar to the wire-based MTF and equal or superior to that of FBP. However, results for the MTF(Task) measured using the low-contrast inserts, the MTF(Task) for ASIR and MBIR data was lower than for the FBP, which was constant throughout all measurements. Similarly, as a function of mA, the MTF(Task) for ASIR and MBIR varied as a function of noise--with MTF(Task) being proportional to mA. Overall greater variability of MTF(Task) across dose and contrast was observed for MBIR than for ASIR. CONCLUSIONS This approach provides a method for assessing the task-based MTF of a CT system using conventional and iterative reconstructions. Results demonstrated that the object-specific MTF can vary as a function of dose and contrast. The analysis highlighted the paradigm shift for iterative reconstructions when compared to FBP, where iterative reconstructions generally offer superior noise performance but with varying resolution as a function of dose and contrast. The MTF(Task) generated by this method is expected to provide a more comprehensive assessment of image resolution across different reconstruction algorithms and imaging tasks.

Quantification of head and body CTDIVOL of dual‐energy x‐ray CTwith fast‐kVp switching

PURPOSE Recently, a fast-kVp switching (FKS) dual-energy method has been presented with clinical and phantom results to demonstrate its efficacy. Patient dose concern has been raised on FKS dual-energy since it involves higher energy acquisition at 140 kVp and slower gantry rotation time (e.g., 0.9-1 s) as opposed to 0.5 s as used in routine single-energy exams. The purpose of our study was to quantitatively compare the CTDI(VOL) of FKS and routine CT exams under the body and head conditions. METHODS For a fair comparison, we have to overcome the difficulty of unmatched protocols between FKS and routine CT exams. In this paper, we propose to match the low contrast detectability (LCD), a critical image quality metric impacting diagnostic quality, before measuring CTDI(VOL). The kVp pair, flux ratio, and optimal monochromatic energy have been carefully optimized for FKS protocols prior to the comparison. Our baseline single-energy protocols were per IEC-61223-3-5 under head and body conditions except for mA, which was iteratively adjusted to match the LCD of FKS. CTDI(VOL) was measured using either a 16 cm (for head scanning) or a 32 cm (for body scanning) PMMA phantom of at least 14 cm in length. The LCD was measured using the uniform section of Catphan 600. To make the study repeatable, the automated statistical LCD measurement tool available on GE Discovery CT750 scanner was used in this work. A visual LCD phantom and a Gammex tissue characterization phantom were also employed to verify the statistical LCD measurements and to introduce various patient sizes and contrast levels. RESULTS The mean CTDI(VOL) for the head and body single-energy acquisitions was 57.5 and 29.2 mGy, respectively. The LCD was measured at 0.45% and 0.42%, respectively. The average CTDI(VOL) for FKS head and body scans was 70.4 and 33.4 mGy, respectively. The corresponding LCD was measured at 0.45% and 0.43%, respectively. The results from the visual LCD phantom and Gammex phantom supported the statistical LCD measurements. CONCLUSIONS For equal image quality as measured by low contrast detectability, the CTDI(VOL) of a FKS head and body exam is roughly 22% and 14% higher than that of a routine single-energy head and body exam, respectively, for the phantom measured.

Predictive models for observer performance in CT: applications in protocol optimization

The relationship between theoretical descriptions of imaging performance (Fourier-based) and the performance of real human observers was investigated for detection tasks in multi-slice CT. The detectability index for the Fisher-Hotelling model observer and non-prewhitening model observer (with and without internal noise and eye filter) was computed using: 1) the measured modulation transfer function (MTF) and noise-power spectrum (NPS) for CT; and 2) a Fourier description of imaging task. Based upon CT images of human patients with added simulated lesions, human observer performance was assessed via an observer study in terms of the area under the ROC curve (Az). The degree to which the detectability index correlated with human observer performance was investigated and results for the non-prewhitening model observer with internal noise and eye filter (NPWE) were found to agree best with human performance over a broad range of imaging conditions. Results provided initial validation that CT image acquisition and reconstruction parameters can be optimized for observer performance rather than system performance (i.e., contrast-to-noise ratio, MTF, and NPS). The NPWE model was further applied for the comparison of FBP with a novel modelbased iterative reconstruction algorithm to assess its potential for dose reduction.

TU‐A‐201B‐03: Dose Reduction and Image Quality Benefits Using Model Based Iterative Reconstruction (MBIR) Technique for Computed Tomography

Purpose: To demonstrate the image‐quality benefits and potential for significant dose reduction with Model‐Based Iterative Reconstruction (MBIR) technique incorporating physical model of computed tomography(CT) systems. Method and Materials: A model based iterative reconstruction (MBIR), a maximum a posteriori (MAP) estimate with edge‐preserving prior, has been developed for x‐ray CTimage reconstruction. It utilizes a more accurate physical model of the imaging chain accounting for system‐optics, noise and non‐idealities in the data, hence improves image quality compared to conventional filtered backprojection (FBP) at significantly reduced dose levels. In this work, a GE multi‐slice CT system was used to acquire a set of multi‐dose data and standard FBP reconstruction. For resolution assessment, a Catphan600® phantom was scanned at three dose levels (40, 20, and 10 mGy with 120kVp spectrum), and images were reconstructed using two methods: FBP with ASiR, and the MBIR. For artifact and image‐quality evaluations, an anthropomorphic CT abdomen phantom (Kyoto Kagaku Co., Ltd) was scanned at four dose levels (120kVp spectrum with 225, 112, 54, and 27 mAs), and a comparative image‐quality study between standard FBP and MBIR in slice and multi‐planar reformat (MPR) modes was made. In addition, few clinical case studies were also used to compare the imaging performance in actual clinical data. Results: From the resolution study, we found that even at 1/4th dose, MBIR images have improved resolution at significantly reduced noise compared to standard state‐of‐the‐art FBP with ASiR. Use of ASIR provides up to 50% dose reduction with equivalent FBP image‐quality. For anthropomorphic phantom, even below 1/8th dose, MBIR images outperformed the corresponding FBP images in both, slice and MPR modes, demonstrating immense potential for dose reduction, yet improved image quality, in clinical CT.Conclusion: Results of the MBIR method demonstrated significant potential for dose reduction and image‐quality improvements in clinical CT.

Image quality evaluation of iterative CT reconstruction algorithms: a perspective from spatial domain noise texture measures

Non-linear iterative reconstruction (IR) algorithms have shown promising improvements in image quality at reduced dose levels. However, IR images sometimes may be perceived as having different image noise texture than traditional filtered back projection (FBP) reconstruction. Standard linear-systems-based image quality evaluation metrics are limited in characterizing such textural differences and non-linear image-quality vs. dose trade-off behavior, hence limited in predicting potential impact of such texture differences in diagnostic task. In an attempt to objectively characterize and measure dose dependent image noise texture and statistical properties of IR and FBP images, we have investigated higher order moments and Haralicks Gray Level Co-occurrence Matrices (GLCM) based texture features on phantom images reconstructed by an iterative and a traditional FBP method. In this study, the first 4 central order moments, and multiple texture features from Haralick GLCM in 4 directions at 6 different ROI sizes and four dose levels were computed. For resolution, noise and texture trade-off analysis, spatial frequency domain NPS and contrastdependent MTF were also computed. Preliminary results of the study indicate that higher order moments, along with spatial domain measures of energy, contrast, correlation, homogeneity, and entropy consistently capture the textural differences between FBP and IR as dose changes. These metrics may be useful in describing the perceptual differences in randomness, coarseness, contrast, and smoothness of images reconstructed by non-linear algorithms.

Head and body CTDIw of dual-energy x-ray CT with fast-kVp switching

Dual-energy CT has attracted much attention in recent years. Most recently, a fast-kVp switching (FKS) dual-energy method has been presented with clinical and phantom results to demonstrate its efficacy. The purpose of our study was to quantitatively compare the CTDIW of FKS and routine CT exams under the body and head conditions. For a fair comparison, the low contrast detectability (LCD) was matched before measuring dose. In FKS protocols, an x-ray generator switch rapidly between 140kVp and 80kVp in adjacent views, and the effective tube current is around 600mA. In addition to the tube voltage and current, the flux ratio between high and low kVp is optimized by asymmetric sampling of 35%-65%. The head and body protocols further differ by the gantry speed (0.9sec/1.0sec) and type of bowtie filter (head/body). For baseline single-energy, we followed the IEC standard head and body protocols (120kV, 1sec, 5mm) but iteratively adjusted the tube current (mA) in order to match the LCD. CTDIW was measured using either a 16 cm (for head scanning) or a 32 cm (for body scanning) PMMA phantom of at least 14 cm in length. The LCD was measured using the water section of Catphan 600. To make the study repeatable, the automated statistical LCD measurement tool available on GE Discovery CT750 scanner was used in this work. The mean CTDIW for the head and body single-energy acquisitions were 57.5mGy and 29.2mGy, respectively. The LCD was measured at 0.45% and 0.42% (slice thickness=5mm, object size=3mm, central 4 images), respectively. The average CTDIW for FKS head and body scans was 70.4mGy and 33.4mGy, respectively, at the optimal monochromatic energy of 65 keV. The corresponding LCD was measured at 0.45% and 0.43%, respectively. This demonstrates that, with matching LCD, CTDIW of FKS is comparable to that of routine CT exams under head and body conditions.

Reduction of metal artifacts: beam hardening and photon starvation effects

The presence of metal-artifacts in CT imaging can obscure relevant anatomy and interfere with disease diagnosis. The cause and occurrence of metal-artifacts are primarily due to beam hardening, scatter, partial volume and photon starvation; however, the contribution to the artifacts from each of them depends on the type of hardware. A comparison of CT images obtained with different metallic hardware in various applications, along with acquisition and reconstruction parameters, helps understand methods for reducing or overcoming such artifacts. In this work, a metal beam hardening correction (BHC) and a projection-completion based metal artifact reduction (MAR) algorithms were developed, and applied on phantom and clinical CT scans with various metallic implants. Stainless-steel and Titanium were used to model and correct for metal beam hardening effect. In the MAR algorithm, the corrupted projection samples are replaced by the combination of original projections and in-painted data obtained by forward projecting a prior image. The data included spine fixation screws, hip-implants, dental-filling, and body extremity fixations, covering range of clinically used metal implants. Comparison of BHC and MAR on different metallic implants was used to characterize dominant source of the artifacts, and conceivable methods to overcome those. Results of the study indicate that beam hardening could be a dominant source of artifact in many spine and extremity fixations, whereas dental and hip implants could be dominant source of photon starvation. The BHC algorithm could significantly improve image quality in CT scans with metallic screws, whereas MAR algorithm could alleviate artifacts in hip-implants and dentalfillings.

Analysis of noise power spectrum for linear and non-linear reconstruction algorithms for CT

With the advent of iterative reconstruction algorithms for CT, there is a significant need to develop analysis tools to characterize the behaviour of such algorithms. The mean and variance are the standard measures to capture the first order and second order moment of CT images. However they fail to capture the complete behaviour of the images when the noise is correlated. The noise in the projection data may be very well approximated to be independant and uncorrelated, however the reconstruction process introduces correlation in the images. Auto-correlation is a good measure to capture the second order moments of an image in the presence of correlated noise. In case of a wide-sense stationary process, the noise power spectrum is the discrete Fourier transform of the covariance matrix. We compare the auto-correlation function and local noise power spectrum of images reconstructed with filtered back-projection (FBP) using a standard kernel, FBP followed by post-processing, and a penalized weighted least square (PWLS) algorithm. A 20 cm uniform water phantom is scanned multiple times in GE Discovery HD750 system and the corresponding 3D auto-correlation function is compared for all three algorithms. The 3D NPS is computed using Welchs periodogram [1] approach and compared for all three algorithms. The PWLS images display auto-correlation function with a longer tail than other algorithms in both axial and coronal planes. The NPS in the axial plane exhibits characteristics of a high-pass filter with all three algorithms sharing the same low-frequency slope. The NPS in the reformatted plane exhibits low-pass filter characteristics with the PWLS algorithm behaving as the best low-pass filter. This may lead to a better detectability in the reformatted planes [2] for images reconstructed with PWLS. The NPS and auto-correlation function is well characterized for three different algorithms and can be utilized for computing detectability using Fourier metrics [2].

Relative dose in dual energy fast-kVp switching and conventional kVp imaging: spatial frequency dependent noise characteristics and low contrast imaging

Dual energy computed tomography offers unique diagnostic value by enabling access to material density, effective atomic number, and energy specific spectral characteristics, which remained indeterminate with conventional kVp imaging. Gemstone Spectral Imaging (GSI) is one of the dual energy methods based on fast kVp switching between two x-ray spectra, 80 kVp and 140 kVp nominal, in adjacent projections. The purpose of this study was to compare relative dose between GSI monochromatic and conventional kVp imaging for equivalent image noise characteristics. A spatialfrequency domain noise power spectrum (NPS) was used as a more complete noise descriptor for the comparison of the two image types. Uniform 20cm water phantom images from GSI and conventional 120 kVp scans were used for NPS calculation. In addition, a low contrast imaging study of the two image types with equivalent noise characteristics was conducted for contrast-to-noise-ratio (CNR) and low contrast detectability (LCD) in the Catphan600® phantom. From three GSI presets ranging from medium to low dose, we observed that conventional 120kVp scan requires ~ 7% - 18% increase in dose to match the noise characteristics in optimal noise GSI monochromatic image; and that the 65 keV monochromatic image CNR for a 0.5% contrast object is 22% higher compared to corresponding 120 kVp scan. Optimal use of the two energy spectra within GSI results in reduced noise and improved CNR in the monochromatic images, indicating the potential for use of this image type in routine clinical applications.

Evaluation of low contrast detectability performance using two-alternative forced choice method on computed tomography dose reduction algorithms

Today lowering patient radiation dose while maintaining image quality in Computed Tomography has become a very active research field. Various iterative reconstruction algorithms have been designed to improve/maintain image quality for low dose patient scans. Typically radiation dose variation will result in detectability variation for low contrast objects. This paper assesses the low contrast detectability performance of the images acquired at different dose levels and obtained using different image generation algorithms via two-alterative forced choice human observer method. Filtered backprojection and iterative reconstruction algorithms were used in the study. Results showed that for the objects and scan protocol used, the iterative algorithm employed in this study has similar low contrast detectability performance compared to filtered backprojection algorithm at a 4 times lower dose level. It also demonstrated that well controlled human observer study is feasible to assess the image quality of a CT system.