CT-based preoperative risk assessment of prolonged urine leak in patients undergoing partial nephrectomy.

OBJECTIVES: This study aims to evaluate risk factors of prolonged urine leak following partial nephrectomy (PN) to identify objective imaging characteristics on preoperative CT. METHODS: A total of 865 patients who underwent PN and had preoperative CT and postoperative imaging were included. We set a twofold size-matched control group without urine leak, with all tumors located ≤ 4 mm to the collecting system to identify imaging parameters that increase the risk of urine leak other than tumor size and location. Four CT parameters that show the relationship of the tumor and collecting system, namely, curvilinear border length, protruding distance, margin at the interface, and pelvicalyceal contact, were analyzed. Multivariate logistic regression analyses were performed to identify significant predictors of urine leak. The diagnostic performance of the significant parameters was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: Fifty-three of 865 patients (6.1%) demonstrated urine leak. Compared with the control group, urine leak group showed longer curvilinear border length, longer protruding distance, frequent non-smooth contact interface, and frequent direct pelvicalyceal contact (p < 0.05 for all). In the multivariate analysis, pelvicalyceal contact was the independent predictor of urine leak (OR = 2.62; 95% C.I 1.02-6.63). Combining four CT parameters, an AUC of 0.70 with a sensitivity of 58.5% and a specificity of 79.2% for identifying urine leak after PN could be obtained. CONCLUSIONS: The four CT features that describe the relationship between the tumor and collecting system might be useful for evaluating the risk of urine leak before PN. KEY POINTS: • Four CT parameters (curvilinear border length, protruding distance, margin at the interface, and pelvicalyceal contact) were significantly associated with postoperative urine leak after partial nephrectomy. • A comprehensive preoperative imaging evaluation of the relationship between the tumor and renal sinus may help in selecting the optimal surgical options and afford better patient counseling of complication risk.

Utilization of virtual low-keV monoenergetic images generated using dual-layer spectral detector computed tomography for the assessment of peritoneal seeding from ovarian cancer.

This study aimed to compare the quality of virtual low-keV monoenergetic images vs conventional images reconstructed from dual-layer spectral detector computed tomography (SDCT) for the detection of peritoneal implants of ovarian cancer.Fifty ovarian cancer patients who underwent abdominopelvic SDCT scans were included in this retrospective study. Virtual monoenergetic images at 40 (VMI40) and 50 keV (VMI50), and two conventional images were reconstructed using filtered back projection (FBP) and iterative model reconstruction (IMR) protocols. The mean attenuation of the peritoneal implant, signal-to-noise ratio (SNR), contrast-to-noise ratio relative to ascites (CNRA) and adjacent reference tissues (e.g., bowel wall, hepatic, or splenic parenchyma [CNRB]) were calculated and compared using paired t tests. Qualitative image analysis regarding overall image quality, image noise, image blurring, lesion conspicuity, was performed by two radiologists. A subgroup analysis according to the peritoneal implant region was also conducted.VMI40 yielded significantly higher mean attenuation (183.35) of SNR and CNR values (SNR 11.69, CNRA 7.39, CNRB 2.68), compared to VMI50, IR, and FBP images (P < .001). The mean attenuation (129.65), SNR and CNR values (SNR 9.37, CNRA 5.72, CNRB 2.02) of VMI50 were also significantly higher than those of IR and FBP images (P < .001). In the subgroup analysis, all values were significantly higher on VMI40 regardless of the peritoneal implant region (P < .05). In both readers, overall image quality and image blurring showed highest score in VMI50, while image noise and lesion conspicuity showed best score in IMR and VMI40 respectively. Inter-reader agreements are moderate to almost perfect in every parameter.The low-keV VMIs improved both quantitative assessment and lesion conspicuity of peritoneal implants from ovarian cancer compared to conventional images.