Diagnostic accuracy of preoperative computed tomography used alone to detect lymph-node involvement at radical nephrectomy.
2015
OBJECTIVE:
The aim of this study was to compare preoperative computed tomography (CT) with pathological findings in patients undergoing lymphadenectomy at the time of nephrectomy for renal cancer-associated lymphadenopathy.
MATERIALS AND METHODS:
Data from 515 consecutive nephrectomy surgeries (2004-2012) in a single university-affiliated centre were analysed to identify patients who had undergone lymph-node dissection concomitant with nephrectomy. Preoperative CT imaging was subjected to multiple repeated independent blinded reviews (two radiologists and one surgeon, each individually and on two separate occasions). Retroperitoneal lymph-node status was subjectively categorized (in a manner not based purely on size criteria) at each review as: 1 = unequivocally positive, 2 = equivocally positive, 3 = equivocally negative, or 4 = unequivocally negative. These findings were compared with pathological analysis, and interobserver and intraobserver agreement was assessed using non-weighted kappa () statistics.
RESULTS:
In total, 71 patients were stratified as category 1 (n = 18), 2 (n = 14), 3 (n = 31) and 4 (n = 8); pathological lymph-node metastasis was present in 14 (78%), four (28%), four (13%) and zero patients, respectively. Sensitivity, specificity, positive and negative predictive values for preoperative CT were 82%, 71%, 56% and 90%, respectively. Intraobserver agreement was greater for the radiologists (values 0.490, 0.540) than for the surgeon (value 0.393). Interobserver agreement was strongest for radiological category 1 (unequivocally positive; value 0.75). Receiver operating characteristics curves did not reveal significant differences in any observer accuracy.
CONCLUSION:
Contrary to concerns about a high false-positive rate, metastasis within regional lymph nodes can be predicted with reasonable accuracy by preoperative CT imaging alone.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
29
References
8
Citations
NaN
KQI