TY - JOUR
T1 - CT and MR imaging for solid renal mass characterization
AU - Sasaguri, Kohei
AU - Takahashi, Naoki
PY - 2018/2
Y1 - 2018/2
N2 - As our understanding has expanded that relatively large fraction of incidentally discovered renal masses, especially in small size, are benign or indolent even if malignant, there is growing acceptance of more conservative management including active surveillance for small renal masses. As for advanced renal cell carcinomas (RCCs), nonsurgical and subtype specific treatment options such as immunotherapy and targeted therapy is developing. On these backgrounds, renal mass characterization including differentiation of benign from malignant tumors, RCC subtyping and prediction of RCC aggressiveness is receiving much attention and a variety of imaging techniques and analytic methods are being investigated. In addition to conventional imaging techniques, integration of texture analysis, functional imaging (i.e. diffusion weighted and perfusion imaging) and multivariate diagnostic methods including machine learning have provided promising results for these purposes in research fields, although standardization and external, multi-institutional validations are needed.
AB - As our understanding has expanded that relatively large fraction of incidentally discovered renal masses, especially in small size, are benign or indolent even if malignant, there is growing acceptance of more conservative management including active surveillance for small renal masses. As for advanced renal cell carcinomas (RCCs), nonsurgical and subtype specific treatment options such as immunotherapy and targeted therapy is developing. On these backgrounds, renal mass characterization including differentiation of benign from malignant tumors, RCC subtyping and prediction of RCC aggressiveness is receiving much attention and a variety of imaging techniques and analytic methods are being investigated. In addition to conventional imaging techniques, integration of texture analysis, functional imaging (i.e. diffusion weighted and perfusion imaging) and multivariate diagnostic methods including machine learning have provided promising results for these purposes in research fields, although standardization and external, multi-institutional validations are needed.
KW - Angiomyolipoma
KW - CT
KW - MR
KW - Oncocytoma
KW - Renal cell carcinoma
KW - Renal mass
UR - http://www.scopus.com/inward/record.url?scp=85038245044&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85038245044&partnerID=8YFLogxK
U2 - 10.1016/j.ejrad.2017.12.008
DO - 10.1016/j.ejrad.2017.12.008
M3 - Review article
C2 - 29362150
AN - SCOPUS:85038245044
VL - 99
SP - 40
EP - 54
JO - European Journal of Radiology
JF - European Journal of Radiology
SN - 0720-048X
ER -