Impact of resolution and noise characteristics of digital radiographic detectors on the detectability of lung nodules

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.

How does c-view image quality compare with conventional 2D FFDM?

PURPOSE

The FDA approved the use of digital breast tomosynthesis (DBT) in 2011 as an adjunct to 2D full field digital mammography (FFDM) with the constraint that all DBT acquisitions must be paired with a 2D image to assure adequate interpretative information is provided. Recently manufacturers have developed methods to provide a synthesized 2D image generated from the DBT data with the hope of sparing patients the radiation exposure from the FFDM acquisition. While this much needed alternative effectively reduces the total radiation burden, differences in image quality must also be considered. The goal of this study was to compare the intrinsic image quality of synthesized 2D c-view and 2D FFDM images in terms of resolution, contrast, and noise.

METHODS

Two phantoms were utilized in this study: the American College of Radiology mammography accreditation phantom (ACR phantom) and a novel 3D printed anthropomorphic breast phantom. Both phantoms were imaged using a Hologic Selenia Dimensions 3D system. Analysis of the ACR phantom includes both visual inspection and objective automated analysis using in-house software. Analysis of the 3D anthropomorphic phantom includes visual assessment of resolution and Fourier analysis of the noise.

RESULTS

Using ACR-defined scoring criteria for the ACR phantom, the FFDM images scored statistically higher than c-view according to both the average observer and automated scores. In addition, between 50% and 70% of c-view images failed to meet the nominal minimum ACR accreditation requirements-primarily due to fiber breaks. Software analysis demonstrated that c-view provided enhanced visualization of medium and large microcalcification objects; however, the benefits diminished for smaller high contrast objects and all low contrast objects. Visual analysis of the anthropomorphic phantom showed a measureable loss of resolution in the c-view image (11 lp/mm FFDM, 5 lp/mm c-view) and loss in detection of small microcalcification objects. Spectral analysis of the anthropomorphic phantom showed higher total noise magnitude in the FFDM image compared with c-view. Whereas the FFDM image contained approximately white noise texture, the c-view image exhibited marked noise reduction at midfrequency and high frequency with far less noise suppression at low frequencies resulting in a mottled noise appearance.

CONCLUSIONS

Their analysis demonstrates many instances where the c-view image quality differs from FFDM. Compared to FFDM, c-view offers a better depiction of objects of certain size and contrast, but provides poorer overall resolution and noise properties. Based on these findings, the utilization of c-view images in the clinical setting requires careful consideration, especially if considering the discontinuation of FFDM imaging. Not explicitly explored in this study is how the combination of DBT + c-view performs relative to DBT + FFDM or FFDM alone.

Impact of breast structure on lesion detection in breast tomosynthesis, a simulation study

This study aims to characterize the effect of background tissue density and heterogeneity on the detection of irregular masses in breast tomosynthesis, while demonstrating the capability of the sophisticated tools that can be used in the design, implementation, and performance analysis of virtual clinical trials (VCTs). Twenty breast phantoms from the extended cardiac-torso (XCAT) family, generated based on dedicated breast computed tomography of human subjects, were used to extract a total of 2173 volumes of interest (VOIs) from simulated tomosynthesis images. Five different lesions, modeled after human subject tomosynthesis images, were embedded in the breasts and combined with the lesion absent condition yielded a total of [Formula: see text] VOIs. Effects of background tissue density and heterogeneity on the detection of the lesions were studied by implementing a composite hypothesis signal detection paradigm with location known exactly, lesion known exactly or statistically, and background known statistically. Using the area under the receiver operating characteristic curve, detection performance deteriorated as density was increased, yielding findings consistent with clinical studies. A human observer study was performed on a subset of the simulated tomosynthesis images, confirming the detection performance trends with respect to density and serving as a validation of the implemented detector. Performance of the implemented detector varied substantially across the 20 breasts. Furthermore, background tissue density and heterogeneity affected the log-likelihood ratio test statistic differently under lesion absent and lesion present conditions. Therefore, considering background tissue variability in tissue models can change the outcomes of a VCT and is hence of crucial importance. The XCAT breast phantoms have the potential to address this concern by offering realistic modeling of background tissue variability based on a wide range of human subjects, comprising various breast shapes, sizes, and densities.

Optimization of dual-energy subtraction chest radiography by use of a direct-conversion flat-panel detector system

We aimed to optimize the exposure conditions in the acquisition of soft-tissue images using dual-energy subtraction chest radiography with a direct-conversion flat-panel detector system. Two separate chest images were acquired at high- and low-energy exposures with standard or thick chest phantoms. The high-energy exposure was fixed at 120 kVp with the use of an auto-exposure control technique. For the low-energy exposure, the tube voltages and entrance surface doses ranged 40-80 kVp and 20-100 % of the dose required for high-energy exposure, respectively. Further, a repetitive processing algorithm was used for reduction of the image noise generated by the subtraction process. Seven radiology technicians ranked soft-tissue images, and these results were analyzed using the normalized-rank method. Images acquired at 60 kVp were of acceptable quality regardless of the entrance surface dose and phantom size. Using a repetitive processing algorithm, the minimum acceptable doses were reduced from 75 to 40 % for the standard phantom and to 50 % for the thick phantom. We determined that the optimum low-energy exposure was 60 kVp at 50 % of the dose required for the high-energy exposure. This allowed the simultaneous acquisition of standard radiographs and soft-tissue images at 1.5 times the dose required for a standard radiograph, which is significantly lower than the values reported previously.

Towards optimized acquisition scheme for multiprojection correlation imaging of breast cancer

RATIONALE AND OBJECTIVES

Correlation imaging (CI) is a form of multiprojection imaging in which multiple images of a patient are acquired from slightly different angles. Information from these images is combined to make the final diagnosis. A critical factor affecting the performance of CI is its data acquisition scheme, because nonoptimized acquisition may distort pathologic indicators. The authors describe a computer-aided detection (CADe) methodology to optimize the acquisition scheme of CI for superior diagnostic accuracy.

MATERIALS AND METHODS

Images from 106 subjects were used. For each subject, 25 angular projections of a single breast were acquired. Projection images were supplemented with a simulated 3-mm three-dimensional lesion. Each projection was then processed using a traditional CADe algorithm at high sensitivity, followed by the reduction of false-positives by combining the geometric correlation information available from the multiple images. The performance of the CI system was determined in terms of free-response receiver-operating characteristic curves and the areas under receiver-operating characteristic curves. For optimization, the components of acquisition, such as the number of projections and their angular span, were systematically changed to investigate which of the many possible combinations maximized the obtainable CADe sensitivity and specificity.

RESULTS

The performance of the CI system was improved by increasing the angular span. Increasing the number of angular projections beyond a certain number did not improve performance. Maximum performance was obtained between 7 and 10 projections spanning a maximum angular arc of 45 degrees .

CONCLUSION

The findings suggest the existence of an optimum acquisition scheme for CI of the breast. CADe results confirmed earlier predictions on the basis of observer models. An optimized CI system may be an important diagnostic tool for improved breast cancer detection.

A mathematical model platform for optimizing a multiprojection breast imaging system

Multiprojection imaging is a technique in which a plurality of digital radiographic images of the same patient are acquired within a short interval of time from slightly different angles. Information from each image is combined to determine the final diagnosis. Projection data are either reconstructed into slices as in the case of tomosynthesis or analyzed directly as in the case of multiprojection correlation imaging technique, thereby avoiding reconstruction artifacts. In this study, the authors investigated the optimum geometry of acquisitions of a multiprojection breast correlation imaging system in terms of the number of projections and their total angular span that yield maximum performance in a task that models clinical decision. Twenty-five angular projections of each breast from 82 human subjects in our breast tomosynthesis database were each supplemented with a simulated 3 mm mass. An approach based on Laguerre-Gauss channelized Hotelling observer was developed to assess the detectability of the mass in terms of receiver operating characteristic (ROC) curves. Two methodologies were developed to integrate results from individual projections into one combined ROC curve as the overall figure of merit. To optimize the acquisition geometry, different components of acquisitions were changed to investigate which one of the many possible configurations maximized the area under the combined ROC curve. Optimization was investigated under two acquisition dose conditions corresponding to a fixed total dose delivered to the patient and a variable dose condition, based on the number of projections used. In either case, the detectability was dependent on the number of projections used, the total angular span of those projections, and the acquisition dose level. In the first case, the detectability approximately followed a bell curve as a function of the number of projections with the maximum between 8 and 16 projections spanning angular arcs of about 23 degrees-45 degrees, respectively. In the second case, the detectability increased with the number of projections approaching an asymptote at 11-17 projections for an angular span of about 45 degrees. These results indicate the inherent information content of the multi-projection image data reflecting the relative role of quantum and anatomical noise in multiprojection breast imaging. The optimization scheme presented here may be applied to any multiprojection imaging modalities and may be extended by including reconstruction in the case of digital breast tomosynthesis and breast computed tomography.

Digital mammography: comparative performance of color LCD and monochrome CRT displays

RATIONALE AND OBJECTIVES

To evaluate the comparative performance of high-fidelity liquid crystal display (LCD) and cathode ray tube (CRT) devices for mammography applications, and to assess the impact of LCD viewing angle on detection accuracy.

MATERIALS AND METHODS

Ninety 1 k x 1 k images were selected from a database of digital mammograms: 30 without any abnormality present, 30 with subtle masses, and 30 with subtle microcalcifications. The images were used with waived informed consent, Health Insurance Portability and Accountability Act compliance, and Institutional Review Board approval. With postprocessing presentation identical to those of the commercial mammography system used, 1 k x 1 k sections of images were viewed on a monochrome CRT and a color LCD in native grayscale, and with a grayscale representative of images viewed from a 30 degrees or 50 degrees off-normal viewing angle. Randomized images were independently scored by four experienced breast radiologists for the presence of lesions using a 0-100 grading scale. To compare diagnostic performance of the display modes, observer scores were analyzed using receiver operating characteristic (ROC) and analysis of variance.

RESULTS

For masses and microcalcifications, the detection rate in terms of the area under the ROC curve (A(z)) showed a 2% increase and a 4% decrease from CRT to LCD, respectively. However, differences were not statistically significant (P > .05). The viewing angle data showed better microcalcification detection but lower mass detection at 30 degrees viewing orientation. The overall results varied notably from observer to observer yielding no statistically discernible trends across all observers, suggesting that within the 0-50 degrees viewing angle range and in a controlled observer experiment, the variation in the contrast response of the LCD has little or no impact on the detection of mammographic lesions.

CONCLUSIONS

Although CRTs and LCDs differ in terms of angular response, resolution, noise, and color, these characteristics seem to have little influence on the detection of mammographic lesions. The results suggest comparable performance in clinical applications of the two devices.

Simulation of mammographic lesions

RATIONALE AND OBJECTIVES

This study presents a method for generating breast masses and microcalcifications in mammography via simulation. This simulation method allows for the creation of large image datasets with particular lesions, which may serve as a useful tool for perception studies measuring imaging system performance.

MATERIALS AND METHODS

The study first characterized the radiographic appearance of both masses and microcalcifications, examining the following five properties: contrast, edge gradient profile of masses, edge characteristics of masses, shapes of individual microcalcifications, and shapes of microcalcification distributions. The characterization results then guided the development of routines that created simulated masses and microcalcifications. The quality of the simulations was verified by experienced breast imaging radiologists who evaluated simulated and real lesions and rated whether a given lesion had a realistic appearance.

RESULTS

The radiologists rated real and simulated lesions to have similarly realistic appearances. Using receiver operating characteristic analysis to characterize the degree of similarity, the results showed an A(z) of 0.68 +/- 0.07 for benign masses, 0.65 +/- 0.07 for malignant masses, and 0.62 +/- 0.07 for microcalcifications, thus showing notable overlap in the simulated and real lesion ratings.

CONCLUSION

This research introduced a new approach for simulating breast masses and microcalcifications that relied on anatomic characteristics measured from real lesions. Results from an observer performance experiment indicate that our simulation routine produced realistic simulations of masses and microcalcifications as judged by expert radiologists.

Simulation of Liver Lesions for Pediatric CT

PURPOSE

To develop and validate a technique based on characteristics of real lesions for simulating realistic small liver lesions on pediatric computed tomographic (CT) images.

MATERIALS AND METHODS

The institutional review board provided exempt status for this study, determined that it was not subject to HIPAA compliance, and did not require informed consent. Patient identification information was removed from clinical images from contrast material-enhanced multi-detector row CT examinations performed in 10 children. Patients were infants or children up to 18 years old. Information about sex was not available. Children had one or more liver lesions of 2-6 mm in maximum transverse diameter. Images with more than one lesion were rendered multiple times, and each time, all but one of the lesions were digitally removed in sequence. This process provided images (n = 19) with a single real lesion. For consistency, the same image backgrounds (images with all real lesions removed) were used to create an identical number of images (n = 19), each with a single simulated lesion. Subsequently, three radiologists independently assessed images of real and simulated lesions that were presented in random order with a score on a continuous scale of 0 (definitely simulated) to 100 (definitely real). Mixed-model analysis of variance was used to test the null hypothesis that the difference in population mean scores between the two lesion types was zero.

RESULTS

The observer study did not reveal a significant difference in the ability of any radiologist to discriminate between real and simulated lesions (P > .31). The differences in mean scores for discrimination between real and simulated lesions for the three observers were -6, 9, and -7, respectively. The estimated overall difference was -1.

CONCLUSION

Mathematic simulation of liver lesions is a feasible technique for creating realistic lesions for image quality or dose reduction studies in pediatric CT.

Resolution and noise measurements of five CRT and LCD medical displays

The performance of soft-copy displays plays a significant role in the overall image quality of a digital radiographic system. In this work, we discuss methods to characterize the resolution and noise of both cathode ray tube (CRT) and liquid crystal display (LCD) devices. We measured the image quality of five different commercial display devices, representing both CRT and LCD technologies, using a high-quality charge-coupled device (CCD) camera. The modulation transfer function (MTF) was calculated using the line technique, correcting for the MTF of the CCD camera and the display pixel size. The normalized noise power spectrum (NPS) was computed from two-dimensional Fourier analysis of uniform images. To separate the effects of pixel structure from interpixel luminance variations, we created structure-free images by eliminating the pixel structures of the display device. The NPS was then computed from these structure-free images to isolate interpixel luminance variations. We found that the MTF of LCDs remained close to the theoretical limit dictated by their inherent pixel size (0.85 +/- 0.08 at Nyquist frequency), in contrast to the MTF for the two CRT displays, which dropped to 0.15 +/- 0.08 at the Nyquist frequency. However, the NPS of LCDs showed significant peaks due to the subpixel structure, while the NPS of CRT displays exhibited a nearly flat power spectrum. After removing the pixel structure, the structured noise peaks for LCDs were eliminated and the overall noise magnitude was significantly reduced. The average total noise-to-signal ratio for CRT displays was 6.55% +/- 0.59%, of which 6.03% +/- 0.24% was due to interpixel luminance variations, while LCD displays had total noise to signal ratios of 46.1% +/- 5.1% of which 1.50% +/- 0.41% were due to interpixel luminance variations. Depending on the extent of the blurring and prewhitening processes of the human visual system, the magnitude of the display noise (including pixel structure) potentially perceived by the observer was reduced to 0.43% +/- 0.01% (accounting for blurring only) and 0.40 +/- 0.01% (accounting for blurring and prewhitening) for CRTs, and 1.02% +/- 0.22% (accounting for blurring only) and 0.36% +/- 0.08% (accounting for blurring and prewhitening) for LCDs.