Frigas Antonis, Kapsimalakou Smaragdo, Spyrou George, Koufopoulos Kostantinos, Vassilaros Stamatios, Chatzimichael Aikaterini, Mantas John, Ligomenides Panos
Academy of Athens, Informatics Laboratory.
Stud Health Technol Inform. 2006;124:631-6.
Mammography is accepted as the most effective method to detect breast cancer. However, interpreting a mammogram is not easy for not experienced radiologists. The aim of computer aided detection techniques in breast cancer is to improve the chance that a malignant region is detected and appropriately evaluated. Breast microcalcifications have been considered as a very useful index of malignancy, which helps in the early detection of breast cancer. A system of computer aided diagnosis has been developed that is based on detailed analysis and evaluation of related features of individual microcalcifications and of formed clusters helping the doctor to make risk estimation for each microcalcification cluster as well as for isolated microcalcifications. This information is considered to be very useful to radiologists, giving them extra input before making their estimation of each case. The aforementioned system has been thoroughly tested using a number of real life cases provided from collaborating doctors. Each case, apart from the mammograms, was accompanied by a biopsy test result, the patient's demographic data and medical history. A total of 200 cases (147 benign and 53 malignant) have been examined and the results are presented as the Receiver Operating Characteristic (ROC) performance and are quantified using the ROC curve. The system is showing high levels of sensitivity identifying correctly all malignant cases.
乳腺钼靶摄影被公认为检测乳腺癌最有效的方法。然而,对于经验不足的放射科医生来说,解读乳腺钼靶片并非易事。乳腺癌计算机辅助检测技术的目的是提高检测到恶性区域并进行适当评估的几率。乳腺微钙化被认为是一种非常有用的恶性指标,有助于早期发现乳腺癌。已经开发了一种计算机辅助诊断系统,该系统基于对单个微钙化以及形成的簇的相关特征进行详细分析和评估,帮助医生对每个微钙化簇以及孤立的微钙化进行风险评估。这些信息被认为对放射科医生非常有用,在他们对每个病例进行评估之前为他们提供额外的参考。上述系统已使用合作医生提供的大量实际病例进行了全面测试。每个病例除了乳腺钼靶片外,还伴有活检检测结果、患者的人口统计学数据和病史。总共检查了200个病例(147个良性和53个恶性),结果以接受者操作特征(ROC)性能呈现,并使用ROC曲线进行量化。该系统显示出很高的灵敏度,能够正确识别所有恶性病例。