Detection, staging and surveillance in renal cell carcinoma

[Imaging renal cell carcinoma]

Renal cell carcinoma is the eighth most common malignancy in adults and the most common malignancy in the kidney. It is thus a very common disease for radiologists. This review aims to provide a general overview of the imaging techniques used to diagnose, characterize, and help plan the treatment of renal cell carcinoma as well as to review basic aspects related to staging, imaging-guided percutaneous treatment, and follow-up in the most common clinical scenarios.

The value of "liver windows" settings in the detection of small renal cell carcinomas on unenhanced computed tomography

OBJECTIVE

To assess if "liver window" settings improve the conspicuity of small renal cell carcinomas (RCC).

METHODS

Patients were analysed from our institution's pathology-confirmed RCC database that included the following: (1) stage T1a RCCs, (2) an unenhanced computed tomography (CT) abdomen performed ≤ 6 months before histologic diagnosis, and (3) age ≥ 17 years. Patients with multiple tumours, prior nephrectomy, von Hippel-Lindau disease, and polycystic kidney disease were excluded. The unenhanced CT was analysed, and the tumour locations were confirmed by using corresponding contrast-enhanced CT or magnetic resonance imaging studies. Representative single-slice axial, coronal, and sagittal unenhanced CT images were acquired in "soft tissue windows" (width, 400 Hounsfield unit (HU); level, 40 HU) and liver windows (width, 150 HU; level, 88 HU). In addition, single-slice axial, coronal, and sagittal unenhanced CT images of nontumourous renal tissue (obtained from the same cases) were acquired in soft tissue windows and liver windows. These data sets were randomized, unpaired, and were presented independently to 3 blinded radiologists for analysis. The presence or absence of suspicious findings for tumour was scored on a 5-point confidence scale.

RESULTS

Eighty-three of 415 patients met the study criteria. Receiver operating characteristics (ROC) analysis, t test analysis, and kappa analysis were used. ROC analysis showed statistically superior diagnostic performance for liver windows compared with soft tissue windows (area under the curve of 0.923 vs 0.879; P = .0002). Kappa statistics showed "good" vs "moderate" agreement between readers for liver windows compared with soft tissue windows.

CONCLUSION

Use of liver windows settings improves the detection of small RCCs on the unenhanced CT.