naa a22 4500 510807259 CHVBK 20180411083424.0 cr unu---uuuuu 180411e20131101xx s 000 0 eng 10.1007/s11548-013-0829-3 doi (NATIONALLICENCE)springer-10.1007/s11548-013-0829-3 Quantitative ultrasound image analysis of axillary lymph node status in breast cancer patients [Elektronische Daten] [Karen Drukker, Maryellen Giger, Lina Meinel, Adam Starkey, Jyothi Janardanan, Hiroyuki Abe] Purpose: Ultrasonography has the potential to accurately stage breast cancer with automated analysis to detect axillary lymph node metastasis. The aim of this study was to develop and test automated quantitative ultrasound image analysis of axillary lymph nodes for breast cancer staging. Methods: Following an IRB-approved HIPAA compliant protocol, ultrasound images of 90 breast cancer patients presenting for lymph node assessment were retrospectively collected. There were 51 node-positive and 39 node-negative patients, yielding images of 223 lymph nodes (109 positive for metastasis and 114 negative for metastasis). The analysis was completely automated apart from the manual indication of the approximate center of each lymph node. Mathematical descriptors of the nodes, which served as image-based biomarkers, were computer-extracted and input to a classifier for the task of distinguishing between positive (i.e., metastatic) and negative lymph nodes. The performance of this task was assessed using receiver operating characteristic (ROC) analysis with evaluation by-node and by-patient using the area under the ROC curve (AUC) as the performance metric. Results: The AUC was 0.85 (standard error 0.03) for by-node evaluation when distinguishing between positive and negative lymph nodes. The AUC was 0.87 (0.04) for patient-based prognosis, i.e., assessing whether patients were lymph node-positive or lymph node-negative. Conclusion: Based on these classification results, we conclude that mathematical descriptors of sonographically imaged lymph nodes may be useful as prognostic biomarkers in breast cancer staging and demonstrate potential for predicting patient lymph node status. CARS, 2013 Quantitative image analysis nationallicence Breast cancer staging nationallicence Ultrasound nationallicence Axillary lymph nodes nationallicence Drukker Karen University of Chicago, Chicago, IL, USA aut Giger Maryellen University of Chicago, Chicago, IL, USA aut Meinel Lina University of Chicago, Chicago, IL, USA aut Starkey Adam University of Chicago, Chicago, IL, USA aut Janardanan Jyothi University of Chicago, Chicago, IL, USA aut Abe Hiroyuki University of Chicago, Chicago, IL, USA aut International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/6(2013-11-01), 895-903 1861-6410 8:6<895 2013 8 11548 https://doi.org/10.1007/s11548-013-0829-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-013-0829-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Drukker Karen University of Chicago, Chicago, IL, USA aut NATIONALLICENCE 700 1- Giger Maryellen University of Chicago, Chicago, IL, USA aut NATIONALLICENCE 700 1- Meinel Lina University of Chicago, Chicago, IL, USA aut NATIONALLICENCE 700 1- Starkey Adam University of Chicago, Chicago, IL, USA aut NATIONALLICENCE 700 1- Janardanan Jyothi University of Chicago, Chicago, IL, USA aut NATIONALLICENCE 700 1- Abe Hiroyuki University of Chicago, Chicago, IL, USA aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/6(2013-11-01), 895-903 1861-6410 8:6<895 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer