Developing a quantitative ultrasound breast scanner for identifying early response of breast cancer to chemotherapy

开发定量超声乳腺扫描仪来识别乳腺癌对化疗的早期反应

• 批准号: 10686414
• 负责人: Gregory Jan Czarnota
• 金额: $ 49.1万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-18 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10686414
• 关键词: 3-Dimensional; Address; Adjuvant Chemotherapy; Anatomy; Breast Cancer Patient; Breast Cancer therapy; Clinical; Clinical Data; Contrast Media; Data; Detection; Devices; Disease-Free Survival; Early identification; Early treatment; Feedback; Frequencies; Health Sciences; Human; Image; In complete remission; Institution; Ionizing radiation; Knowledge; Magnetic Resonance Imaging; Malignant Neoplasms; Mammary Ultrasonography; Mammography; Marketing; Marriage; Measures; Monitor; Neoadjuvant Therapy; Operative Surgical Procedures; Outcome; Pathologic; Patient-Focused Outcomes; Patients; Performance; Physical assessment; Process; Prognosis; Radiation; Resolution; Savings; Scanning; Signal Transduction; Speed; Techniques; Technology; Testing; Time; Tissues; Translating; attenuation; breast imaging; breast scanner; cancer therapy; chemotherapy; cohort; cost; data acquisition; improved; individual patient; malignant breast neoplasm; patient response; personalized medicine; quantitative imaging; quantitative ultrasound; response; sound; success; tomography; transmission process; treatment response; tumor; ultrasound

PROJECT SUMMARY In this proposal, we will develop new images modes on the QT Ultrasound® tomographic breast scanner and demonstrate that the scanner with the new image modes can accurately identify the response of breast cancer patients to chemotherapy. A poorly met clinical need in breast cancer therapy is providing inexpensive and accurate ways to identify patient responses to chemotherapy early during the course of therapy. For many breast cancers, lack of patient response to initial therapy is predictive of poor outcome, whereas pathological complete response strongly correlates with extended survival. Conventional clinical surrogates of response based on anatomical information such as physical assessments, mammography and standard clinical ultrasound provide poor early assessments of treatment response. We demonstrated that quantitative analysis of ultrasound backscatter (QUSB) using conventional hand-held clinical scanners can provide promising metrics of response of breast cancer to neoadjuvant chemotherapy (NAC/AC) within one week of therapy initiation. These QUSB results would benefit greatly from improved volumetric accuracy that conventional scanning platforms do not support, such as transmission and attenuation losses in the signals. We propose to solve these issues by integrating QUSB with the newly available QT Ultrasound® breast scanner. This FDA cleared and marketed scanner delivers 3D quantitative images of the breast including sound speed, (SOS) reflectivity (R) and attenuation (A) values. The QT Ultrasound® breast scanner corrects refractive and interface attenuation losses. It also provides compounding of multiple angles of view that will further improve QUSB variance. The scanner’s parameters of SOS, R, A, and mm3 volume measuring accuracy provide supplementary quantitative features likely to contribute robustness to early identification of response. We believe that the QUSB+QT Ultrasound® breast scanner can identify response at a level better than MRI. Even if response identification is only comparable, QUSB+QT Ultrasound® savings in costs, ease of use, noninvasive native contrast, and patient acceptance would markedly simplify management of breast cancer therapy and deliver considerable practical advantage and increased accuracy. Therefore, our scientific premise is that QUSB integrated on the QT Ultrasound® breast scanner will provide improved identification of early response of breast cancer patients to NAC. Our preliminary data demonstrate that QUSB techniques can identify nonresponders and predict patient outcomes. Our preliminary results also demonstrate that QUSB techniques integrate with the QT Ultrasound® platform and benefit from improved QUSB bias and variance. Therefore, the proposal consists of three aims. The first specific aim is to implement, test and validate QUSB techniques on the latest QT Ultrasound® breast scanner for clinical data acquisition. The second specific aim is to quantify the capacity of QUSB+QT Ultrasound® quantitative data to identify nonresponders. The final specific aim is to quantify the capacity of QUSB+QT Ultrasound® quantitative data to predict patient outcomes.

项目总结