Feasibility of CT in high risk breast cancer patients

乳房X光检查用于筛查无症状的女性乳腺癌，使用乳房X光检查发现的典型乳腺癌直径约为11毫米。在这种小尺寸下，切除病变可以治愈大多数女性的乳腺癌。然而，有一小部分女性(约占所有乳腺癌的5%)在基因上易患乳腺癌(BRCA1和BCRA2基因)，在这些女性中，需要更积极的检测方法。除了BRCA1和BRCA2携带者有极高的乳腺癌风险外，乳房极其致密的女性患乳腺癌的风险也更高(因为她们的乳房致密，优势比从4到6)，而乳房X光检查在这些女性中不那么敏感。对于这些高危类别的女性来说，她们中的大多数都有致密的乳房，而乳房X光检查的成像效果很差，需要一种具有更好的病变检测性能(对比分辨率)的成像方式。虽然超声波依赖的造影剂机制不如X射线造影剂可靠，但这就是为什么它们不被用于筛查。然而，计算机断层摄影(CT)确实依赖于X射线对比机制，但其对比分辨率大约是投影乳房X光摄影的10倍。CT非常有能力识别3-5 mm范围内的软组织病变--这种病变的体积比乳房X光检查发现的平均11 mm病变小10到50倍。因此，对于高危患者来说，CT在乳腺癌的早期发现方面比钼靶摄影有更大的潜力。在这项可行性研究中，我们建议使用计算机模拟技术结合身体乳房和乳房切除标本的CT来全面研究专用乳房CT的潜力。蒙特卡罗研究将用于全面评估乳腺CT的腺体剂量，成像研究将用于确定最佳CT采集的要求。利用对大约10个乳房切除标本的乳腺病变进行CT扫描，将建立一个乳房肿瘤模型。该肿瘤模型将用于一系列约20具身体的乳腺CT数据集，以进行广泛的ROC研究。计算机观察者将被用来定义CT和乳房X光检查的Az与肿瘤直径的关系曲线。人类观察者将被用于验证和校准更广泛的计算机观察者结果。这项调查的结果应该会让人们清楚地了解，乳腺CT作为一种工具，在乳腺癌风险极高的女性人群中降低乳腺癌死亡率的潜力。

Mammography is used to screen asymptomatic women for breast cancer, and typical breast cancer found using mammography is approximately 11 mm in diameter. At this small size, removal of lesion results in breast cancer cure in the majority of women. However, there is a small class of women (about 5% of all breast cancers) who are genetically predisposed to breast cancer (BRCA1 and BCRA2 genes), and in these women, more aggressive detection methods are needed. In addition to BRCA1 and BRCA2 carriers who are at extraordinary risk of breast cancer, women with extremely dense breasts are at higher risk from breast cancer (by virtue of their dense breasts with odds ratio from 4 to 6), and mammography is less sensitive in these women. For women in these high-risk categories, most of whom have dense breasts that are poorly imaged by mammography, an imaging modality with better lesion detectability performance (contrast resolution) is needed. While ultrasound rely on contrast mechanisms that are less reliable than X-ray contrast-that is why they are not used for screening. However, computed tomography (CT) does depend upon x-ray contrast mechanisms, but has about 10 times the contrast resolution as projection mammography. CT is very capable of identifying soft tissue lesions in the 3-5mm range- Such lesions are 10 to 50 times smaller in volume than the average 11mm lesion found by mammography. Therefore, CT has great potential for much earlier detection of breast cancer than mammography for high-risk patients. In this feasibility study, we propose to throughly investigate the potential of dedicated breast CT using computer simulation techniques coupled with CT of cadaver breasts and mastectomy specimens. Monte Carlo studies will be used to fully evaluate the glandular dose of breast CT, and imaging studies will be used to define the requirements of optimal CT acquisition. Using CT scans of breast lesions from about 10 mastectomy specimens, a breast tumor model will be developed. The tumor model will be used with a series of about 20 cadaver breast CT data sets to conduct extensive ROC studies. Computer observers will be used to define the Az versus tumor diameter curves for both CT and mammography. Human observers will be used to validate and calibrate the more extensive computer observer results. The results of this investigation should provide a clear understanding of the potential of breast CT as a tool to reduce breast cancer mortality in the population of women with dire risk of breast cancer.