Biomedical subjects

Karen K Lindfors

Publications and source records attributed to Karen K Lindfors.

7 recordsLinked to original sources

PubMed2006

Computer-aided detection of breast cancer: a cost-effectiveness study.

PURPOSE: To analyze the cost-effectiveness of adding computer-aided detection (CAD) to a screening mammography program. MATERIALS AND METHODS: A Markov model was developed to compare three hypothetical groups of women aged 40-79 years. The first group was composed of women undergoing mammographic screening without CAD; the second, of women undergoing mammographic screening with CAD; and the third, of women undergoing observation without screening. Cost-effectiveness was expressed as the marginal cost per year of life saved (MCYLS). MCYLS was calculated for screening mammography with CAD compared with screening mammography alone and for screening mammography alone compared with observation. Sensitivity analyses were performed by varying the cost of CAD, the rates of cancer detection with CAD, and the stage distribution of breast cancers diagnosed with CAD. RESULTS: Adding CAD to a mammographic screening program resulted in a MCYLS of $19,058. The MCYLS of screening mammography alone compared with observation was $16,023. CAD increases the marginal effectiveness of screening by 29%; however, the marginal cost of screening is also increased by 34%. Varying the cost of CAD yields a linear increase in MCYLS from $8937 with CAD at $9 per case to $24,924 with CAD at $25 per case. The cost-effectiveness of CAD is dependent on the magnitude of the increase in cancer detection rates with CAD but is also affected by the stage distribution of cancers diagnosed with CAD. CONCLUSION: The MCYLS is 19% greater for CAD added to screening versus screening mammography alone but is still within the accepted range for cost-effectiveness.

Adult↗

PubMed2006

Computed tomography for imaging the breast.

Despite the success of screening mammography contributing to the reduction of cancer mortality, a number of other imaging techniques are being studied for breast cancer screening. In our laboratory, a dedicated breast computed tomography (CT) system has been developed and is currently undergoing patient testing. The breast CT system is capable of scanning the breast with the woman lying prone on a tabletop, with the breast in the pendant position. A 360 degrees scan currently requires 16.6 s, and a second scanner with a 9-second scan time is nearly operational. Extensive effort was placed on computing the radiation dose to the breast under CT geometry, and the scan parameters are selected to utilize the same radiation dose levels as two-view mammography. A total of 55 women have been scanned, ten healthy volunteers in a Phase I trial, and 45 women with a high likelihood of having breast cancer in a Phase II trial. The breast CT process leads to the production of approximately three hundred 512 x 512 images for each breast. Subjective evaluation of the breast CT images reveals excellent anatomical detail, good depiction of microcalcifications, and exquisite visualization of the soft tissue components of the tumor when contrasted against adipose tissues. The use of iodine contrast injection dramatically enhances the visualization of tumors. While a thorough scientific investigation based upon observer performance studies is in progress, initial breast CT images do appear promising and it is likely that breast CT will play some role in breast cancer imaging.

Breast↗

PubMed2006

Observer efficiency in discrimination tasks simulating malignant and benign breast lesions imaged with ultrasound.

We investigate and extend the ideal observer methodology developed by Smith and Wagner to detection and discrimination tasks related to breast sonography. We provide a numerical approach for evaluating the ideal observer acting on radio frequency (RF) frame data, which involves inversion of large nonstationary covariance matrices, and we describe a power-series approach to computing this inverse. Considering a truncated power series suggests that the RF data be Wiener-filtered before forming the final envelope image. We have compared human performance for Wiener-filtered and conventional B-mode envelope images using psychophysical studies for 5 tasks related to breast cancer classification. We find significant improvements in visual detection and discrimination efficiency in four of these five tasks. We also use the Smith-Wagner approach to distinguish between human and processing inefficiencies, and find that generally the principle limitation comes from the information lost in computing the final envelope image.

Algorithms↗

PubMed2006

Breast CT: potential for breast cancer screening and diagnosis.

Although screening mammography has been shown to be effective in reducing breast cancer mortality, a new technique called breast computed tomography (CT) is being studied in the hope that breast cancer can be detected even earlier. A prototype unit has been designed, fabricated and tested at the University of California, Davis, USA, and is currently being used in a Phase II clinical trial to study the feasibility of breast CT for breast cancer detection and diagnosis. A total of 46 volunteers and patients have been imaged, and the breast CT images show impressive anatomical detail of the breast that is not appreciated in mammography. The radiation dose levels needed to produce excellent image quality are equal to two-view mammography. Further study of breast CT is needed to better understand its potential role in breast cancer screening and diagnosis.

Breast↗

PubMed2005

Technique factors and their relationship to radiation dose in pendant geometry breast CT.

The use of breast computed tomography (CT) as an alternative to mammography in some patients is being studied at several institutions. However, the radiation dosimetry issues associated with breast CT are markedly different than in the case of mammography. In this study, the spectral properties of an operational breast CT scanner were characterized both by physical measurement and computer modeling of the kVp-dependent spectra, from 40 to 110 kVp (Be window W anode with 0.30 mm added Cu filtration). Previously reported conversion factors, normalized glandular dose for CT-DgN(ct), derived from Monte Carlo methods, were used in concert with the output spectra of the breast scanner to compute the mean glandular dose to the breast based upon different combinations of x-ray technique factors (kVp and mAs). The mean glandular dose (MGD) was measured as a function of the compressed breast thickness (2-8 cm) and three different breast compositions (0%, 50%, and 100% glandular fractions) in four clinical mammography systems in our institution. The average MGD from these four systems was used to compute the technique factors for breast CT systems that would match the two-view mammographic dose levels. For a 14 cm diameter breast (equivalent to a 5 cm thick compressed breast in mammography), air kerma levels at the breast CT scanner's isocenter (468 mm from the source) of 4.4, 6.4, and 9.0 mGy were found to deliver equivalent mammography doses for 0%, 50%, and 100% glandular breasts (respectively) at 80 kVp. At 80 kVp (where air kerma was 11.3 mGy/100 mAs at the isocenter), 57 mAs (integrated over the entire scan) was required to match the mammography dose for a 14 cm 50% glandular breast. At 50 kVp, 360 mAs is required to match mammographic dose levels. Tables are provided for both air kerma at the isocenter and mAs for 0%, 50%, and 100% glandular breasts. Other issues that impact breast CT technique factors are also discussed.

Biophysical Phenomena↗

PubMed2004

Viscoelastic imaging of breast tumor microenvironment with ultrasound.

Imaging systems are most effective for detection and classification when they exploit contrast mechanisms specific to particular disease processes. A common example is mammography, where the contrast depends on local changes in cell density and the presence of microcalcifications. Unfortunately the specificity for classifying malignant breast disease is relatively low for many current diagnostic techniques. This paper describes a new ultrasonic technique for imaging the viscoelastic properties of breast tissue. The mechanical properties of glandular breast tissue, like most biopolymers, react to mechanical stimuli in a manner specific to the microenvironment of the tissue. Elastic properties allow noninvasive imaging of desmoplasia while viscous properties describe metabolism-dependent features such as pH. These ultrasonic methods are providing new tools for studying disease mechanisms as well as improving diagnosis.

Animals↗

PubMedDate not supplied

Determining sensitivity of mammography from screening data, cancer incidence, and receiver-operating characteristic curve parameters.

OBJECTIVES: A mathematical model is presented that allows the computation of the sensitivity and specificity of breast screening based on receiver-operating characteristic (ROC) curve shape, the positive predictive value (PPV) of screening mammography, and the cancer incidence, f. METHODS: The normal and cancer populations are modeled as normal distributions with independent means and standard deviations. The distributions are scaled such that the area of the normal population is equal to 1-f and that of the cancer population is f. The PPV for screening mammography is used to determine the operating point on the ROC curve. Knowing this leads directly to the computation of sensitivity and specificity. The derivation is general and is applicable to both symmetrical and asymmetrical ROC curves. RESULTS: For symmetric ROC curves and typical values for the PPV of mammography (about 8%) and cancer incidence (f= 0.003), an A(z) value of 0.95 was required to achieve 63% sensitivity and an A. value of 0.98 led to 86% sensitivity. CONCLUSION: A model was developed that should allow researchers to deduce sensitivity and specificity for screening mammography based on ROC curve measurements and using realistic values of PPV and f. This model allows A. values to be related to the probability of breast cancer detection.

Breast Neoplasms↗