The S.T.O.N.E. Score: a new assessment tool to predict stone free rates in ureteroscopy from pre-operative radiological features.

OBJECTIVE: To develop a user friendly system (S.T.O.N.E. Score) to quantify and describe stone characteristics provided by computed axial tomography scan to predict ureteroscopy outcomes and to evaluate the characteristics that are thought to affect stone free rates. MATERIALS AND METHODS: The S.T.O.N.E. score consists of 5 stone characteristics: (S) ize, (T)opography (location of stone), (O)bstruction, (N)umber of stones present, and (E)valuation of Hounsfield Units. Each component is scored on a 1-3 point scale. The S.T.O.N.E. Score was applied to 200 rigid and flexible ureteroscopies performed at our institution. A logistic model was applied to evaluate our data for stone free rates (SFR). RESULTS: SFR were found to be correlated to S.T.O.N.E. Score. As S.T.O.N.E. Score increased, the SFR decreased with a logical regression trend (p < 0.001). The logistic model found was SFR=1/(1+e^(-z)), where z=7.02-0.57•Score with an area under the curve of 0.764. A S.T.O.N.E. Score ≤ 9 points obtains stone free rates > 90% and typically falls off by 10% per point thereafter. CONCLUSIONS: The S.T.O.N.E. Score is a novel assessment tool to predict SFR in patients who require URS for the surgical therapy of ureteral and renal stone disease. The features of S.T.O.N.E. are relevant in predicting SFR with URS. Size, location, and degree of hydronephrosis were statistically significant factors in multivariate analysis. The S.T.O.N.E. Score establishes the framework for future analysis of the treatment of urolithiasis.

The S.T.O.N.E. Score: A new assessment tool to predict stone free rates in ureteroscopy from pre-operative radiological features

Objective: To develop a user friendly system (S.T.O.N.E. Score) to quantify and describe stone characteristics provided by computed axial tomography scan to predict ureteroscopy outcomes and to evaluate the characteristics that are thought to affect stone free rates. Materials and Methods: The S.T.O.N.E. score consists of 5 stone characteristics: (S)ize, (T)opography (location of stone), (O)bstruction, (N)umber of stones present, and (E)valuation of Hounsfield Units. Each component is scored on a 1-3 point scale. The S.T.O.N.E. Score was applied to 200 rigid and flexible ureteroscopies performed at our institution. A logistic model was applied to evaluate our data for stone free rates (SFR). Results: SFR were found to be correlated to S.T.O.N.E. Score. As S.T.O.N.E. Score increased, the SFR decreased with a logical regression trend (p < 0.001). The logistic model found was SFR=1/(1+e.

Robotic partial adrenalectomy using indocyanine green dye with near-infrared imaging: the initial clinical experience.

OBJECTIVE: To present the initial clinical experience with robot-assisted partial adrenalectomy using indocyanine green dye with near-infrared fluorescence (ICG-NIRF) imaging. METHODS: Three consecutive patients with solitary adrenal masses with worrisome features were referred for treatment. The preoperative workup included dedicated axial imaging and adrenal function studies. All patients underwent purely robotic partial adrenalectomy with ICG-NIRF guidance. Relevant steps of the technique included a transperitoneal approach, gross identification of the adrenal gland, administration of 5 mg intravenous ICG, and finally, mass resection guided by ICG-NIRF and white light visualization in an effort to completely excise the mass while sparing uninvolved adrenal tissue. RESULTS: Robotic partial adrenalectomy was successfully performed with negative margins in all patients. All masses were hypofluorescent relative to normal adrenal tissue with ICG-NIRF and included a pheochromocytoma, lipoadenoma, and follicular lymphoid hyperplasia. CONCLUSION: Robotic partial adrenalectomy with intraoperative ICG-NIRF is safe and feasible. The addition of ICG-NIRF may help mass identification, excision, and promote the use adrenal-sparing surgery.

Cell-free plasma DNA as biochemical biomarker for the diagnosis and follow-up of prostate cancer patients.

The aim of this study was to evaluate the diagnostic and potential prognostic value of cell-free plasma DNA (CF-pDNA) in patients with suspected or histologically proven prostate cancer (PCa). We included 133 men with a diagnosis of PCa and 33 controls. PCa patients had blood samples prospectively drawn every 3 months for 2 years. CF-pDNA was measured by spectrophotometry. Considering a cut-off value of 140 ng/mL of CF-pDNA the area under the curve was of 0.824(0.757-0.879 with a sensitivity = 66.2 % and a specificity = 87.9 %) and the positive and negative likelihood ratio were of 5.46 and 0.39, respectively. CF-pDNA tends to decrease slightly and return to baseline values in about a week after biopsy. There was no statistical significant correlation between CF-pDNA levels at study entry with PSA, Gleason score, stage and biochemical recurrence free survival (BRFS). However, with a mean follow-up of 13.5 months, we could observe a significant shorter BRFS for patients with at least one value above 140 ng/mL of CF-pDNA during follow-up (p = 0.048). CF-pDNA is a potentially valuable biomarker for PCa diagnosis and a potential tool for the follow-up of patients with PCa.