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The QT Scanner 2000 Model A is for use as an ultrasonic imaging system to provide reflection-mode and transmissionmode images of a patient's breast. The QT Scanner 2000 Model A software also calculates the breast fibroglandular tissue volume (FGV) value and the ratio of FGV to total breast volume (TBV) value as determined from reflection-mode and transmission-mode ultrasound images of a patient's breast. The device is not intended to be used as a replacement for screening mammography. The QT Scanner 2000 Model A is indicated for use by trained healthcare professionals in environments where healthcare is provided to enable breast imaging in adult patients.

The QT Scanner 2000 Model A ("QT Scanner") is an automated, software-controlled ultrasound imaging system which performs a standardized scan of the whole breast without the use of ionizing radiation, compression, or contrast injection; and generates both reflection-mode and transmission-mode breast images. The QT Scanner consists of a Patient Scanning System, an Operator Console, an optional offboard image processor, and the OTviewer software. The Patient Scanning System contains the necessary electronics which perform acquisition and initial processing of the breast images and further provides a support table which allows the patient to rest comfortably while the scanning takes place. The scan tank is centered below a patient's breast and contains the ultrasound transducer arrays. The transducer arrays include a set of three reflection transducers that transmit pulsed ultrasound plane waves into targeted tissues using the water bath in the scan tank as a coupling medium. An additional transmitter and receiver array pair collect the ultrasound energy to provide speed of sound values. During scanning, a patient lies prone on the examination table with the breast suspended in a warm water bath maintained near skin temperature. Images are automatically acquired on a pendant breast positioned with the nipple as a point of reference. The transducer arrays rotate about a vertical axis to circle the breast in the coronal plane. The array is then translated vertically, and the scanning process is repeated until the entire breast is scanned, allowing B-scan images to be constructively combined into tomographic, speed of sound and reflection ultrasound images. The QT Scanner outputs the images to a server which allows the images to be stored until they are reviewed on a Viewer Console running the QTviewer™ software. Alternatively, raw data files can be output to a server and remotely constructively combined into tomographic, speed of sound and reflection ultrasound images. Coronal, axial and sagittal images are generated for review by the radiologist. The QTviewer software also provides a number of analytics capabilities, such as biometric measurement, manual segmentation, and Region of Interest calculations. The QTviewer software also provides the "Fibroglandular Volume" (FGV) which is display of calculated fibroglandular tissue volume within a breast, expressed in dimensions of volume, as well as a ratio of the volume of fibroglandular tissue within the breast volume to the total breast volume, from QT Scanner breast images. The QTviewer software also provides the "Fibroglandular Volume" (FGV) which is display of calculated fibroglandular tissue volume within a breast, expressed in dimensions of volume, as well as a ratio of the volume of fibroglandular tissue within the breast volume to the total breast volume (TBV), provided as FGV/TBV. The process for calculating FGV and FGV/TBV is based on image segmentation methods. The first step is segmentation of the whole breast from the surrounding water. Attenuation images are used to identify the boundary of the breast assuming that attenuation anywhere outside the breast (within water) is essentially zero. From skin inward, every pixel is labelled as breast tissue. The next step identifies the pixels in the vicinity of the boundary as border pixels and which constitute the skin of the breast. The pixels labelled as surrounding water and skin are removed from the breast and the remaining breast volume is deemed as TBV. In the next step, pixel values from the segmented speed of sound image are provided to a one-dimensional fuzzy c-means (FCM) algorithm to partition of data set into two clusters: fibroglandular tissue and fat. Once FCM is trained, a membership map of fibroglandular tissue is generated and an empirically chosen threshold is applied to binarize the fibroglandular tissue membership map which constitutes fibroglandular tissue volume (FGV). The ratio of FGV to TBV (FGV/TBV) is then calculated by dividing the volume of the fibroglandular tissue by the volume of the whole breast.