Cornelis Francois, Grenier Nicolas
Department of Radiology, Pellegrin Hospital, Bordeaux, France.
Department of Radiology, Pellegrin Hospital, Bordeaux, France.
Semin Ultrasound CT MR. 2017 Feb;38(1):47-58. doi: 10.1053/j.sult.2016.08.009. Epub 2016 Sep 1.
Although preoperative classification of solid renal tumors was performed by percutaneous biopsy until now, research teams have demonstrated the potential interest of imaging to characterize noninvasively different renal tumor subtypes, in particular, with multiparametric magnetic resonance (MR) imaging. By combining all the imaging MR features successively reported in the literature and following a practical algorithm based on a step-by-step reading of the MR images, readers are now able to identify several imaging profiles, which appeared specific of each renal tumor subtypes. Although a large, prospective validation remains required to validate these findings in a clinical setting, this new imaging paradigm may help to overcome the traditional limitations of imaging for the characterization of renal tumors because of their overlapped morphologic imaging features. These imaging inputs would be helpful to better identify renal masses requiring surgery, without further invasive exploration such as biopsies, from where other options (ie, percutaneous ablation or active surveillance) may be proposed.
尽管迄今为止实体肾肿瘤的术前分类是通过经皮活检进行的,但研究团队已经证明了成像技术在无创性鉴别不同肾肿瘤亚型方面的潜在价值,特别是多参数磁共振(MR)成像。通过结合文献中相继报道的所有MR成像特征,并遵循基于对MR图像逐步解读的实用算法,读者现在能够识别出几种成像特征,这些特征似乎是每种肾肿瘤亚型所特有的。尽管仍需要大规模的前瞻性验证来在临床环境中验证这些发现,但这种新的成像模式可能有助于克服由于肾肿瘤形态学成像特征重叠而导致的传统成像在肾肿瘤特征描述方面的局限性。这些成像信息将有助于更好地识别需要手术的肾肿块,而无需进行诸如活检等进一步的侵入性探查,从而可以提出其他选择(即经皮消融或主动监测)。