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Biomedical subjects

S K Plevritis

Publications and source records attributed to S K Plevritis.

2 recordsLinked to original sources

Breast disease: dynamic spiral MR imaging.

PURPOSE: To compare various subjective, empiric, and pharmacokinetic methods for interpreting findings at dynamic magnetic resonance (MR) imaging of the breast. MATERIALS AND METHODS: Dynamic spiral breast MR imaging was performed in 52 women suspected of having or with known breast disease. Gadolinium-enhanced images were obtained at 12 locations through the whole breast every 7.8 seconds for 8.5 minutes after bolus injection of contrast material. Time-signal intensity curves from regions of interest corresponding to 57 pathologically proved lesions were analyzed by means of a two-compartment pharmacokinetic model, and the diagnostic performance of various parameters was analyzed. RESULTS: Findings included invasive carcinoma in 17 patients, isolated ductal carcinoma in situ (DCIS) in six, and benign lesions in 34. Although some overlap between carcinomas and benign diagnoses was noted for all parameters, receiver operating characteristic analysis indicated that the exchange rate constant had the greatest overall ability to discriminate benign and malignant disease. The elimination rate constant and washout were the most specific parameters. The exchange rate constant, wash-in, and extrapolation point were the most sensitive parameters. DCIS was not consistently distinguished from benign disease with any method. CONCLUSION: Dynamic spiral breast MR imaging proved an excellent method with which to collect contrast enhancement data rapidly enough that accurate comparisons can be made between many analytic methods.

Breast

MRS imaging using anatomically based k-space sampling and extrapolation.

A comprehensive strategy for the acquisition, reconstruction, and postprocessing of MR spectroscopic images is presented. The reconstruction algorithm is the most critical component of this strategy. It is assumes that the desired image is spatially bounded, meaning that the desired image contains an object that is surrounded by a background of zeros. The reconstruction algorithm relies on prior knowledge of the background zeros for k-space extrapolation. This algorithm is a good candidate for proton MR spectroscopic image reconstruction because these images are often spatially bounded and prior knowledge of the zeros is easily obtained from a rapidly acquired high resolution conventional MRI. Although the reconstruction algorithm can be used with the standard 3DFT k-space distribution, a distribution that relies on anatomical features that are likely to occur in the spectroscopic image can produce better results. Prior knowledge of these anatomical features is also obtained from a conventional MRI. Finally, the postprocessing component of this strategy is valuable for reducing subcutaneous lipid contamination. Overall, the comprehensive approach presented here produces images that are better resolved than standard approaches without increasing acquisition time or reducing SNR. Examples using NAA data are provided.

Algorithms