Microvascular Ultrasonic Imaging of Angiogenesis Identifies Tumors in a Murine Spontaneous Breast Cancer Model

The purpose of this study is to determine if microvascular tortuosity can be used as an imaging biomarker for the presence of tumor-associated angiogenesis and if imaging this biomarker can be used as a specific and sensitive method of locating solid tumors. Acoustic angiography, an ultrasound-based microvascular imaging technology, was used to visualize angiogenesis development of a spontaneous mouse model of breast cancer (n=48). A reader study was used to assess visual discrimination between image types, and quantitative methods utilized metrics of tortuosity and spatial clustering for tumor detection. The reader study resulted in an area under the curve of 0.8, while the clustering approach resulted in the best classification with an area under the curve of 0.95. Both the qualitative and quantitative methods produced a correlation between sensitivity and tumor diameter. Imaging of vascular geometry with acoustic angiography provides a robust method for discriminating between tumor and healthy tissue in a mouse model of breast cancer. Multiple methods of analysis have been presented for a wide range of tumor sizes. Application of these techniques to clinical imaging could improve breast cancer diagnosis, as well as improve specificity in assessing cancer in other tissues. The clustering approach may be beneficial for other types of morphological analysis beyond vascular ultrasound images

Microvascular Ultrasonic Imaging of Angiogenesis Identifies Tumors in a Murine Spontaneous Breast Cancer Model

The purpose of this study is to determine if microvascular tortuosity can be used as an imaging biomarker for the presence of tumor-associated angiogenesis and if imaging this biomarker can be used as a specific and sensitive method of locating solid tumors. Acoustic angiography, an ultrasound-based microvascular imaging technology, was used to visualize angiogenesis development of a spontaneous mouse model of breast cancer (n=48). A reader study was used to assess visual discrimination between image types, and quantitative methods utilized metrics of tortuosity and spatial clustering for tumor detection. The reader study resulted in an area under the curve of 0.8, while the clustering approach resulted in the best classification with an area under the curve of 0.95. Both the qualitative and quantitative methods produced a correlation between sensitivity and tumor diameter. Imaging of vascular geometry with acoustic angiography provides a robust method for discriminating between tumor and healthy tissue in a mouse model of breast cancer. Multiple methods of analysis have been presented for a wide range of tumor sizes. Application of these techniques to clinical imaging could improve breast cancer diagnosis, as well as improve specificity in assessing cancer in other tissues. The clustering approach may be beneficial for other types of morphological analysis beyond vascular ultrasound images

TOWARD CLINICAL TRANSLATION OF MICROVASCULAR ULTRASOUND IMAGING: ADVANCEMENTS IN SUPERHARMONIC ULTRASOUND TECHNOLOGY

Ultrasound imaging is perhaps the safest, most affordable, and most available biomedical imaging modality. However, it suffers from poor specificity for cancer detection, particularly in breast cancer, which affects one in eight women and leads to a high incidence of unnecessary biopsies from inconclusive screening. It is well-known that malignant cancers are accompanied by abnormal angiogenesis, leading to tortuous and disorganized vasculature. Acoustic angiography, a microvascular contrast-enhanced ultrasound technique, was developed to visualize and harness this aberrant vasculature as a biomarker of malignancy. This technique applies a dual-frequency superharmonic strategy to isolate intravascular microbubble contrast from the surrounding tissue with low-frequency transmit and high-frequency receive, resulting in high-resolution microvascular maps. Preclinically, acoustic angiography has been a valuable tool for differentiating tumors from healthy tissue by quantifying vascular features like tortuosity. The preclinical success of this technique is attributed to the single-element dual-frequency transducers used, which provide contrast sensitivity and focal depth best suited for imaging small animals at high microbubble doses. In an exploratory clinical study in which these transducers were used to image the human breast, imaging depth, low sensitivity, and motion artifacts significantly degraded image quality. For acoustic angiography to be successfully translated to clinical use, the technique must be optimized for clinical imaging. In this dissertation, we explore three ways in which acoustic angiography may be improved for the clinic. First, we evaluate microbubble contrast agents to determine the composition that maximizes superharmonic generation. The results indicate that lipid-shelled microbubbles with perfluorocarbon cores, like the commercial agent, DEFINITY, produce the greatest superharmonic signal. Then, we present a novel transducer, a stacked dual-frequency array, as the next-generation device for acoustic angiography and demonstrate improvements in imaging depth and sensitivity up to 10 mm and 13 dB, respectively. We go on to apply this device in a clinical pilot study and elucidate the challenges that remain to be overcome for clinical acoustic angiography. Finally, we propose custom simulations for superharmonic imaging and identify optimal frequency combinations for imaging at depths up to 8 cm, which can be used to design dedicated clinical dual-frequency arrays in the future.Doctor of Philosoph