Barbara G. Steinbach

Use of a modified polysaccharide gel in developing a realistic breast phantom for MRI

A polysaccharide material, TX-151, has been used together with water, NaCl, and Al powder to create a tissue equivalent gel to make a realistic, inexpensive, conveniently moldable, temporally stable tissue equivalent MRI phantom. Various phantom compositions were studied for variations in gelling time and relaxation times. Gd-DTPA added as a T1 (and T2) modifier and aluminum powder added to decrease T2 permitted phantoms to be made with a range of relaxation times comparable to human tissues. We have used this polysaccharide gel to create breast phantoms for testing breast coils and evaluating different MRI imaging sequences available for diagnosis. The breast phantoms consisted of a layer of Crisco, a good model for adipose tissue, surrounding the TX-151 gel. Some of these phantoms were created with a silicone implant encapsulated in the gel to simulate an augmented breast. More sophisticated phantoms can easily be developed by additions of other materials to this polysaccharide gel.

Hexagonal wavelet processing of digital mammography

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms and used to enhance features of importance to mammography within a continuum of scale-space. We present a method of contrast enhancement based on an overcomplete, non-separable multiscale representation: The hexagonal wavelet transform.

Adaptive multiscale processing for contrast enhancement

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Mammographic image processing using wavelet processing techniques

Mammograms with masses corresponding to biopsy-proven cancer were processed using algorithms based on the wavelet transform. Five radiologists assessed the visibility of malignant masses in ten processed mammograms as compared with the original film images. Mammograms processed using these algorithms demonstrated some improvement in feature visualization. Wavelet-based methods of image enhancement could prove to be useful in mammography and merit further study.

Metastatic cervical carcinoma to the breast

Metastatic disease to the breast is often an unexpected diagnosis in a female who presents with a breast mass. The most important factor suggesting the appropriate diagnosis is a history of cancer. Correlation of mammographic and ultrasonographic findings may also raise the possibility of a metastatic mass. A well-defined, noncalcified dense mass on film-screen mammography, which also shows low-level homogeneous echoes without posterior acoustic enhancement, suggests the diagnosis. It is important that the diagnosis be made by fine needle aspiration or excisional biopsy so as to expedite appropriate therapy.

Mammography: Breast implants—types, complications, and adjacent breast pathology

Approximately 1.5 million women in the United States currently have breast implants. The majority were placed for cosmetic augmentation, but 20% were placed for reconstruction after the loss or deformity of a breast. The augmented breast is a challenge to the mammographer. Many of the palpable and mammographically detected abnormalities in these patients are related to the implant itself. Since, however, there is breast tissue present with cosmetic augmentation, the full range of fibrocystic and neoplastic conditions that can affect the breast may be seen. The presence of the implant makes imaging the breast more difficult because the implant obscures the nearby breast tissue. This paper reviews the history and evolution of various breast prostheses. The surgical approaches to placement of implants and complications associated with their use will be discussed. Examples of concomitant pathologies and a review of imaging strategies will be given.

How does observer training affect imaging performance in digital mammography

Simulated mass lesions, superimposed onto an anthropomorphic breast phantom, were x-rayed using a small field of view digital mammography system. Eight radiologists and four scientists viewed the phantom images on a display monitor in a darkened room. Five readers had prior experience of reading these type of images. Readers assessed the probability of a simulated mass being present in each ROI, with the resultant data used to plot the corresponding Receiver Operating Characteristic (ROC) curves, and determine the corresponding area under the ROC curve (Az). Readers viewed the same set of images five successive times in a single session, and the time taken to read each image was recorded. The average time to complete the study for all twelve observers was 24 minutes (71 seconds/image). Experienced readers were quicker than novices, and radiologists were quicker than the scientists. The average Az value for the twelve readers for this detection task was 0.842 +/- 0.037 with coefficient of variations for individual readers ranging from 2.1% to 7.7%. Differences in imaging performance between the radiologists and scientists were very small. Analysis of the trends in measured imaging performance for each reader viewing successive (repeat) images showed that there was no improvement in imaging performance with increasing experience.

OPTIMAL TECHNIQUE FACTORS FOR MAGNIFICATION MAMMOGRAPHY

RATIONALE AND OBJECTIVES Use of small focal spots with low x-ray tube currents may result in very long exposure times and thus result in motion blur in magnification mammography. The authors investigated the reduction in exposure time with increasing x-ray tube kVp and the corresponding decrease in perceived visibility of low-contrast objects in phantom images. METHODS Exposure times required to radiograph an RMI 156 phantom in a magnification geometry were measured as a function of x-ray tube kVp when operated under automatic exposure control. Magnification images of the RMI 156 phantom were obtained at x-ray tube voltages ranging from 28 to 34 kVp. Five radiology residents ranked the visibility of two borderline fibers and six borderline microcalcification specks using a 5-point scale ranging from excellent to barely visible. RESULTS Between 28 and 34 kVp, the density of the RMI phantom images was nearly constant with a mean value of 1.32 +/- 0.04. Increasing the x-ray tube voltage from 28 kVp to 34 kVp reduced the exposure time from 1.27 seconds to 0.66 seconds. Image quality at 30 and 32 kVp was not significantly worse than that achieved at 28 kVp. Increasing the x-ray tube voltage to 34 kVp, however, resulted in a statistically significant (P < 0.001) deterioration in the relative visibility of fibers and microcalcification specks. CONCLUSIONS Magnification mammography performed at 32 kVp will decrease exposure times significantly and result in a microcalcification and fiber visibility that is similar to that achieved at 28 kVp.

ROC comparison between digital mammography and screen-film using an anthropomorphic breast phantom

Mass lesion detection performance of a LoRAD Digital Spot Mammography (DSM) system was compared with a Kodak Min R screen-film combination exposed either in front of the DSM, or in the Bucky of a GE 600T mammography unit. Low-contrast objects simulating small masses were superimposed on an RMI 165 anthropomorphic breast phantom and radiographs obtained at 28 kVp and an mAs value, which resulted in a mean film density of approximately 1.1. DSM images were obtained at the same radiation exposure as used with screen-film. Fully masked radiographs were viewed on a mammography light box, and the DSM images were viewed on the DSM monitor in a darkened room. Of the 64 regions of interest (ROI) in each type of image, 28 (44%) contained the test object. For each imaging modality, six radiologists and six scientists assessed the probability of a simulated mass being present in each ROI. The resultant data were used to plot receiver operating characteristic (ROC) curves of twelve readers for each of the three imaging modalities investigated. There was no significant difference in reader performance between the screen-film combination exposed in front of the DSM system and exposed in the GE 600T system. Both screen-film imaging systems resulted in the same average area under the ROC curve, Az, of 0.78. At the same level of radiation exposure, the DSM had an average ROC area, Az, of 0.71 which was significantly inferior to the average performance achieved using screen-film (p less than 0.005). For this detection task, there were no significant differences in performance between the radiologists and scientists. Reader performance was found to improve with the number of images read, demonstrating an observer learning curve for this specific detection task.

Comparison of a dyadic wavelet image enhancement algorithm with unsharp masking and median filtering for mammography

Image processing techniques using wavelet signal analysis techniques have shown promise in mammography. Wavelet algorithms are compared with traditional image enhancement techniques of unsharp masking and median filtering. Computer simulated phantom images were generated containing lesions mimicking masses and microcalcifications. The degree of image enhancement was evaluated by comparing processed and original signal-to-noise (SNR) ratios in such phantom images. Results obtained in this study suggest that image processing algorithms based on the wavelet transform are likely to enhance the visibility of low-contrast features in mammograms.