TY - JOUR
T1 - Computer-Aided Nodule Assessment and Risk Yield Risk Management of Adenocarcinoma
T2 - The Future of Imaging?
AU - Foley, Finbar
AU - Rajagopalan, Srinivasan
AU - Raghunath, Sushravya M.
AU - Boland, Jennifer M.
AU - Karwoski, Ronald A.
AU - Maldonado, Fabien
AU - Bartholmai, Brian J.
AU - Peikert, Tobias
N1 - Publisher Copyright:
© 2016 Elsevier Inc.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - Increased clinical use of chest high-resolution computed tomography results in increased identification of lung adenocarcinomas and persistent subsolid opacities. However, these lesions range from very indolent to extremely aggressive tumors. Clinically relevant diagnostic tools to noninvasively risk stratify and guide individualized management of these lesions are lacking. Research efforts investigating semiquantitative measures to decrease interrater and intrarater variability are emerging, and in some cases steps have been taken to automate this process. However, many such methods currently are still suboptimal, require validation and are not yet clinically applicable. The computer-aided nodule assessment and risk yield software application represents a validated tool for the automated, quantitative, and noninvasive tool for risk stratification of adenocarcinoma lung nodules. Computer-aided nodule assessment and risk yield correlates well with consensus histology and postsurgical patient outcomes, and therefore may help to guide individualized patient management, for example, in identification of nodules amenable to radiological surveillance, or in need of adjunctive therapy.
AB - Increased clinical use of chest high-resolution computed tomography results in increased identification of lung adenocarcinomas and persistent subsolid opacities. However, these lesions range from very indolent to extremely aggressive tumors. Clinically relevant diagnostic tools to noninvasively risk stratify and guide individualized management of these lesions are lacking. Research efforts investigating semiquantitative measures to decrease interrater and intrarater variability are emerging, and in some cases steps have been taken to automate this process. However, many such methods currently are still suboptimal, require validation and are not yet clinically applicable. The computer-aided nodule assessment and risk yield software application represents a validated tool for the automated, quantitative, and noninvasive tool for risk stratification of adenocarcinoma lung nodules. Computer-aided nodule assessment and risk yield correlates well with consensus histology and postsurgical patient outcomes, and therefore may help to guide individualized patient management, for example, in identification of nodules amenable to radiological surveillance, or in need of adjunctive therapy.
KW - lung adenocarcinoma
KW - lung cancer screening
KW - pulmonary nodule
KW - quantitative image analytics
KW - risk stratification
UR - http://www.scopus.com/inward/record.url?scp=84957916527&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84957916527&partnerID=8YFLogxK
U2 - 10.1053/j.semtcvs.2015.12.015
DO - 10.1053/j.semtcvs.2015.12.015
M3 - Article
C2 - 27568149
AN - SCOPUS:84957916527
SN - 1043-0679
VL - 28
SP - 120
EP - 126
JO - Seminars in Thoracic and Cardiovascular Surgery
JF - Seminars in Thoracic and Cardiovascular Surgery
IS - 1
ER -