No abstract

We describe a novel 3D ultrasound technology, the Quantitative Transmission Ultrasound (QT Ultrasound® system and algorithm to image a pendent breast in a water bath. Quantitative accuracy is verified using phantoms. Morphological accuracy is verified using cadaveric breast and in vivo images, and spatial resolution is estimated. This paper generalizes an earlier 2D algorithm to a full 3D inversion algorithm and shows the importance of such a 3D algorithm for artifact suppression as compared with the 2D algorithm. The resultant high resolution ultrasound images, along with quantitative information regarding tissue speed-of-sound/stiffness, provide a more accurate depiction of the breast anatomy and lesions, contributing to improved breast care.

We present here a quantitative ultrasound tomographic method yielding a sub-mm resolution, quantitative 3D representation of tissue characteristics in the presence of high contrast media. This result is a generalization of previous work where high impedance contrast was not present and may provide a clinically and laboratory relevant, relatively inexpensive, high resolution imaging method for imaging in the presence of bone. This allows tumor, muscle, tendon, ligament or cartilage disease monitoring for therapy and general laboratory or clinical settings. The method has proven useful in breast imaging and is generalized here to high-resolution quantitative imaging in the presence of bone. The laboratory data are acquired in ~ 12 min and the reconstruction in ~ 24 min—approximately 200 times faster than previously reported simulations in the literature. Such fast reconstructions with real data require careful calibration, adequate data redundancy from a 2D array of 2048 elements and a paraxial approximation. The imaging results show that tissue surrounding the high impedance region is artifact free and has correct speed of sound at sub-mm resolution.

Quantitative Transmission Ultrasound (QT) is a powerful and emerging imaging paradigm which has the potential to perform true three-dimensional image reconstruction of biological tissue. Breast imaging is an important application of QT and allows non-invasive, non-ionizing imaging of whole breasts in vivo. Here, we report the first demonstration of breast tissue image classification in QT imaging. We systematically assess the ability of the QT images’ features to differentiate between normal breast tissue types. The three QT features were used in Support Vector Machines (SVM) classifiers, and classification of breast tissue as either skin, fat, glands, ducts or connective tissue was demonstrated with an overall accuracy of greater than 90%. Finally, the classifier was validated on whole breast image volumes to provide a color-coded breast tissue volume. This study serves as a first step towards a computer-aided detection/diagnosis platform for QT.

Three patients with acute myelogenous leukemia and adequate granulocyte reserves developed fever and painful indurated erythematous plaques on their extremities and faces. The plaques became studded with vesicles or bullae and occasionally became necrotic. Histologic examination revealed dermal edema, infiltration with granulocytes, and formation of intraepidermal vesicles. Efforts to relate the skin reaction to infiltration of leukemic cells, microorganisms, or allergic phenomena were unsuccessful. Empiric antibiotic therapy was without effect. The symptoms and signs responded dramatically to systemic administration of corticosteroids. These lesions, which may cause diagnostic confusion and needless therapy with potent antibiotics, may represent another previously uncharacterized nonspecific skin reaction in patients with acute myelogenous leukemia.