Image Quality Improvement and Performance Assessment of Dedicated Breast CT

 描述（由申请人提供）：乳腺癌早期检测的诊断阶段目前远非完美。目前的临床成像技术用于诊断乳腺癌筛查中发现的可疑病变，大约六分之一的乳腺癌被遗漏。这是在乳腺癌筛查阶段已经错过的六分之一的乳腺癌之外。此外，假阳性诊断检查率导致三分之二以上的活检结果为阴性。显然，这一非常重要的临床诊断程序仍有改进的余地。在为乳腺癌成像而开发的许多新型成像技术中，专用乳腺计算机断层扫描（BCT）是极少数能够产生具有高对比度分辨率的真实乳腺断层扫描图像且不需要注射造影剂或放射性药物的技术之一。这使得它非常适合用作一线成像技术，用于在乳腺癌筛查或临床乳腺检查期间检测到可疑病变。在这个项目中，我们建议进行一项前瞻性临床试验，比较BCT的准确性，目前的标准成像技术诊断乳腺癌的患者在乳腺癌筛查过程中发现的可疑病变。为了最大限度地提高BCT的图像质量，我们将应用于BCT的新算法，我们已经开发的结果更准确，更高质量的图像与真正的定量特征。这些算法涉及由于X射线散射的存在而对所采集的BCT投影的校正，以及将图像采集过程正确地表示为涉及X射线能量谱而不是单能量X射线的图像采集过程的新颖的重建算法。该项目的成功完成将有助于通过表征其在乳腺癌诊断阶段的真正潜力或影响将BCT引入临床领域，我们预计它将导致更少的乳腺癌漏诊和阴性活检。

 DESCRIPTION (provided by applicant): The diagnostic stage of early detection of breast cancer is currently far from perfect. With the current clinical imaging technology used for diagnostic work-up of suspicious lesions detected at breast cancer screening, approximately one out of six breast cancers are missed. This is in addition to the one out of six breast cancers already missed at the breast cancer screening stage. In addition, the rate of false positive diagnostic work-ups results in more than two out of three biopsies yielding a negative result. Clearly there is room for improvement in this very important clinical diagnostic procedure. Of the many novel imaging technologies being developed for breast cancer imaging, dedicated breast computed tomography (BCT) is one of very few that results in a true tomographic image of the breast with high contrast resolution and does not require the injection of a contrast agent or radiopharmaceutical. This makes it ideal for use as the frontline imaging technology for working up suspicious lesions detected during breast cancer screening or during clinical breast examination. In this project we propose to perform a prospective clinical trial to compare the accuracy of BCT to the current standard imaging technologies for diagnosis of breast cancer in patients with a suspicious lesion identified during breast cancer screening. To maximize the image quality of BCT we will apply to the BCT novel algorithms we have developed that result in more accurate, higher quality images with true quantitative characteristics. These algorithms involve the correction of the acquired BCT projections due to the presence of x-ray scatter, and a novel reconstruction algorithm that correctly represents the image acquisition process as one involving a spectrum of x-ray energy, rather than mono-energetic x-rays. Successful completion of this project will help introduce BCT to the clinical realm by characterizing its true potential or impact in the breast cancer diagnosis stage, where we expect it will result in fewer missed breast cancers and negative biopsies.