Novel kidney segmentation system to describe tumour location for nephron-sparing surgery

Skill Transfer from Laparoscopic Partial Nephrectomy to the Hugo™ RAS System: A Novel Proficiency Score to Assess Surgical Quality during the Learning Curve

Background/Objectives: The absence of validated tools to assess the skill transfer from laparoscopy to robotic surgery remains an unsolved issue in the context of robot-assisted partial nephrectomy (RAPN). We aimed to describe and validate a novel proficiency score to critically evaluate the surgical quality of RAPN with the Hugo™ RAS System (Medtronic, Minneapolis, MN, USA). Methods: Between October 2022 and September 2023, 27 consecutive patients underwent off-clamp RAPN for localized renal tumors at our institution. To analyze the learning curve (LC), the cohort was chronologically divided into two phases of 6 months each. Proficiency was defined as the achievement of trifecta while maintaining a comparable intraoperative time in the interquartile range of laparoscopic partial nephrectomy performed by the same surgeon. A logistic binary regression model was built to identify predictors of proficiency achievement. Results: A proficiency score was achieved in 14 patients (74.1%). At univariable analysis, number of consecutive procedures > 12 (OR 13.7; 95%CI 2.05-21.1, p = 0.007), pathological tumor size (OR 0.92; 95%CI 0.89-0.99, p = 0.04) and essential blood hypertension (OR 0.16; 95%CI 0.03-0.82, p = 0.02) were found to be predictors of proficiency score. At multivariable analysis, after adjusting for potential confounding factors, number of consecutive procedures > 12 (OR 8.1; 95%CI 1.44-14.6, p = 0.03) was the only independent predictor of proficiency score achievement. Conclusions: Our results showed that the skills of an experienced laparoscopic surgeon are transferrable to the novel Hugo™ RAS System in the context of nephron-sparing surgery. Improved surgical quality may be expected after completing the first 12 consecutive procedures.

Trifecta Outcomes of Robot-Assisted Partial Nephrectomy Using the New Hugo™ RAS System Versus Laparoscopic Partial Nephrectomy

(1) Background: Laparoscopic partial nephrectomy (LPN) is still performed in many referred urological institutions, representing a valid alternative to robot-assisted partial nephrectomy (RAPN). We aimed to compare trifecta outcomes of LPN and RAPN with the Hugo™ RAS System. (2) Methods: Between October 2022 and September 2023, eighty-nine patients underwent minimally invasive partial nephrectomy (group A, RAPN = 27; group B, Laparoscopic PN = 62) for localized renal tumors at our Institution. Continuous variables were presented as median and IQR and compared by means of the Mann-Whitney U test, while categorical variables were presented as frequencies (%) and compared by means of the χ2 test. (3) Results: Group A showed a higher rate of male patients (81.5% vs. 59.7%, p = 0.04) and a higher trend towards larger clinical tumor size (34 vs. 29 mm, p = 0.14). All the other baseline variables were comparable between the two groups (all p > 0.05). Regarding post-operative data, group A displayed a lower operative time (92 vs. 149.5 min, p = 0.005) and a shorter hospital stay (3 vs. 5, p = 0.002). A higher rate of malignant pathology was evidenced in group A (77.8% vs. 58.1%, p = 0.07) as well as a lower trend towards positive surgical margins (3.7% vs. 4.8%, p = 0.82), even if not statistically significant. (4) Conclusions: The rate of trifecta achievement was 92.6% and 82.3% for group A and B (p = 0.10), respectively. In terms of trifecta outcomes, RAPN using the Hugo™ RAS System showed comparable results to LPN performed by the same experienced surgeon.

Preclinical optimization of a diode laser-based clamp-free partial nephrectomy in a large animal model

Kidney cancer is a common urologic malignancy with either laparoscopic (LPN) or robotic partial nephrectomy as therapeutic options of choice for localized tumors. However, renal resection and suturing are challenging steps of the procedure that can lead to complications such as prolonged warm ischemia, bleeding, and urinary fistulas. LPN with a diode laser is an efficient technique due to its cutting and/or coagulation attributes. Surprisingly, key laser features such as wavelength and power remain undefined. Using a large porcine model, we evaluated the laser range of wavelength and power in a clamp-free LPN and compared it to the established gold-standard LPN technique (i.e., cold-cutting and suturing). By analyzing surgery duration, bleeding, presence of urine leak, tissue damage related to the resected renal fragment and the remaining organ, hemoglobin levels, and renal function, we show that an optimized experimental diode laser clamp-free LPN (wavelength, 980 nm; power, 15 W) had shorter surgery time with less bleeding, and better postoperative renal function recovery when compared to the well-established technique. Together, our data indicate that partial nephrectomy with a diode laser clamp-free LPN technique is an improved alternative to the gold-standard technique. Therefore, translational clinical trials towards human patient applications are readily feasible.

Tumorous kidney segmentation in abdominal CT images using active contour and 3D-UNet

BACKGROUND AND PURPOSE

The precise segmentation of the kidneys in computed tomography (CT) images is vital in urology for diagnosis, treatment, and surgical planning. Medical experts can get assistance through segmentation, as it provides information about kidney malformations in terms of shape and size. Manual segmentation is slow, tedious, and not reproducible. An automatic computer-aided system is a solution to this problem. This paper presents an automated kidney segmentation technique based on active contour and deep learning.

MATERIALS AND METHODS

In this work, 210 CTs from the KiTS 19 repository were used. The used dataset was divided into a train set (168 CTs), test set (21 CTs), and validation set (21 CTs). The suggested technique has broadly four phases: (1) extraction of kidney regions using active contours, (2) preprocessing, (3) kidney segmentation using 3D U-Net, and (4) reconstruction of the segmented CT images.

RESULTS

The proposed segmentation method has received the Dice score of 97.62%, Jaccard index of 95.74%, average sensitivity of 98.28%, specificity of 99.95%, and accuracy of 99.93% over the validation dataset.

CONCLUSION

The proposed method can efficiently solve the problem of tumorous kidney segmentation in CT images by using active contour and deep learning. The active contour was used to select kidney regions and 3D-UNet was used for precisely segmenting the tumorous kidney.

Automatic Detection and Scoring of Kidney Stones on Noncontrast CT Images Using S.T.O.N.E. Nephrolithometry: Combined Deep Learning and Thresholding Methods

PURPOSE

To develop and validate a deep learning and thresholding-based model for automatic kidney stone detection and scoring according to S.T.O.N.E. nephrolithometry.

PROCEDURES

Abdominal noncontrast computed tomography (NCCT) images were retrospectively archived from February 2018 to April 2019 for three parts: a segmentation dataset (n = 167), a hydronephrosis classification dataset (n = 282), and test dataset (n = 117). The model consisted of four steps. First, the 3D U-Nets for kidney and renal sinus segmentation were developed. Second, the deep 3D dual-path networks for hydronephrosis grading were developed. Third, the thresholding methods were used to detect and segment stones in the renal sinus region. The stone size, CT attenuation, and tract length were calculated from the segmented stone region. Fourth, the stone's location was determined. The stone detection performance was estimated with sensitivity and positive predictive value (PPV). The hydronephrosis grading and stone size, tract length, number of involved calyces, and essence grading were estimated with the area under the curve (AUC) method and linear-weighted κ statistics, respectively.

RESULTS

The stone detection algorithm reached a sensitivity of 95.9 % (236/246) and a PPV of 98.7 % (236/239). The hydronephrosis classification algorithm achieved an AUC of 0.97. The scoring model results showed good agreement with radiologist results for the stone size, tract length, number of involved calyces, and essence grading (κ = 0.95, 95 % confidence interval [CI]: 0.92, 0.98; κ = 0.97, 95 % CI: 0.95, 1.00; κ = 0.95, 95 % CI: 0.92, 0.98; and κ = 0.97, 95 % CI: 0.94, 1.00), respectively.

CONCLUSIONS

The scoring model was constructed that can automatically detect and score stones in NCCT images.

Comparison of three dimensional reconstruction and conventional computer tomography angiography in patients undergoing zero-ischemia laparoscopic partial nephrectomy

Background

With the development of three dimensional (3D) reconstruction and printing technology, it has been widely using in the field of urology. However, there have been few studies reporting the role of 3D reconstruction in zero-ischemia partial nephrectomy (PN). The aim of this study was to assess the role of 3D reconstruction and conventional computer tomography angiography (CTA) in zero-ischemia laparoscopic partial nephrectomy (LPN).

Methods

A total of 60 consecutive patients undergoing zero-ischemia LPN between October 2017 and March 2018 who underwent CTA (CTA group including 30 patients) and 3D reconstruction (3D group including the remaining 30 patients) preoperatively were included. 3D reconstruction and CTA images were prepared which were used to demonstrate the number and spatial interrelationships of the location of renal tumors and tumor feeding arteries. These radiological findings were directly correlated with intraoperative surgical findings at laparoscopy. Baseline, perioperative variables and the rate of accurate tumor feeding artery orientation were compared between groups.

Results

All LPNs were completed without conversion to renal hilar clamping or open surgery. Preoperative 3D reconstruction identified that 15 patients had only one tumor feeding artery, 12 had two, and another 3 had three, while the conventional CTA revealed that 22 patients had one tumor feeding artery, 8 had two (P > 0.05). The mean operation time was shorter and estimated blood loss was less in the 3D group (P < 0.05) and the rate of accurate tumor feeding artery dissection was higher in the 3D group (91.7%) in comparison with the CTA group (84.2%). The baseline characteristics and renal function outcomes had no statistical differences between groups.

Conclusions

3D reconstruction can provide comprehensive information for the preoperative evaluation and intraoperative orientation about tumor feeding arteries that may facilitate tumor resection during zero-ischemia LPN for renal tumors.

Volumetric assessment of unaffected parenchyma and Wilms' tumours: analysis of response to chemotherapy and surgery using a semi-automated segmentation algorithm in children with renal neoplasms

OBJECTIVE

To present our proof of concept with semi-automatic image recognition/segmentation technology for calculation of tumour/parenchyma volume.

METHODS

We reviewed Wilms' tumours (WTs) between 2000 and 2018, capturing computed tomography images at baseline, after neoadjuvant chemotherapy (NaC) and postoperatively. Images were uploaded into MATLAB-3-D volumetric image processing software. The program was trained by two clinicians who supervised the demarcation of tumour and parenchyma, followed by automatic recognition and delineation of tumour margins on serial imaging, and differentiation from uninvolved renal parenchyma. Volume was automatically calculated for both.

RESULTS

During the study period, 98 patients were identified. Of these, based on image quality and availability, 32 (38 affected moieties) were selected. Most patients (65%) were girls, diagnosed at age 50 ± 37 months of age. NaC was employed in 64% of patients. Surgical management included 27 radical and 11 partial nephrectomies. Automated volume assessment demonstrated objective response to NaC for unilateral and bilateral tumours (68 ± 20% and 53 ± 39%, respectively), as well as preservation on uninvolved parenchyma with partial nephrectomy (70 ± 46 cm³ at presentation to 57 ± 41 cm³ post-surgery).

CONCLUSION

Volumetric analysis is feasible and allows objective assessment of tumour and parenchyma volume in response to chemotherapy and surgery. Our data show changes after therapy that may be otherwise difficult to quantify. Use of such technology may improve surgical planning and quantification of response to treatment, as well as serving as a tool to predict renal reserve and long-term changes in renal function.

Initial Evaluation of Computer-Assisted Radiologic Assessment for Renal Mass Edge Detection as an Indication of Tumor Roughness to Predict Renal Cancer Subtypes

Objective

To develop software to assess the potential aggressiveness of an incidentally detected renal mass using images.

Methods

Thirty randomly selected patients who underwent nephrectomy for renal cell carcinoma (RCC) had their images independently reviewed by engineers. Tumor “Roughness” was based on image algorithm of tumor topographic features visualized on computed tomography (CT) scans. Univariant and multivariant statistical analyses are utilized for analysis.

Results

We investigated 30 subjects that underwent partial or radical nephrectomy. After excluding poor image-rendered images, 27 patients remained (benign cyst = 1, oncocytoma = 2, clear cell RCC = 15, papillary RCC = 7, and chromophobe RCC = 2). The mean roughness score for each mass is 1.18, 1.16, 1.27, 1.52, and 1.56 units, respectively (p < 0.004). Renal masses were correlated with tumor roughness (Pearson's, p=0.02). However, tumor size itself was larger in benign tumors (p=0.1). Linear regression analysis noted that the roughness score is the most influential on the model with all other demographics being equal including tumor size (p=0.003).

Conclusion

Using basic CT imaging software, tumor topography (“roughness”) can be quantified and correlated with histologies such as RCC subtype and could lead to determining aggressiveness of small renal masses.

[Retrospective comparison of the reproducibility and the performances of R.E.N.A.L. score, 12 segments score and UPRCC score for the partial nephrectomy]

INTRODUCTION

Compare three morphometrics scores of the kidney on the reproductibility and the predictability of complications per- and post-partial nephrectomy.

MATERIALS AND METHODS

This comparative study analyzed a monocentric retrospective cohort of 47 patients affected by a unique renal tumor and operated by partial nephrectomy by lumbotomy excluding the genetic diseases from January till December, 2014. The preoperative scanners were reviewed in double-blind by a radiologist and an internal surgeon who classified each tumor according to the three classifications: R.E.N.A.L. score, score in 12 segments and the University Paris Renal Cancer Classification (UPRCC). The judging criteria were the operative and ischemic duration, the blood loss, the preoperative injuries, the length of the hospital stay, the postoperative complications according to the Clavien-Dindo classification. The Cohen's kappa coefficient and the one-way analysis of variance were used respectively to compare the inter-observer reproducibility and the predictability of the complications for each classification.

RESULTS

Forty-four tumors of which 30 (64%) were on the left kidney, with an average size of 55.19mm with 17 (39%) on the upper pole, 12 (27%) on the lower pole and 15 (34%) medio-renal. The UPRCC was the most reproductible classification with 90% inter-observer concordance against 84% for the R.E.N.A.L. score and 72% for the score in 12 segments. The most predictable classification of complications was the score in 12 segments in particular thanks to the subgroup including the number of segments reached which allows to predict significantly the risk of a duration of intervention, prolonged ischemia and the risk of blood loss (P=0.03, 0.06 and <0.001).

CONCLUSION

The main result of this study is that, as in the majority of the previous studies on morphometrics scores, no score allows to predict the postoperative complications.

LEVEL OF EVIDENCE

4.

Multidimensional Interactive Radiology Report and Analysis: Standardization of workflow and reporting for renal mass tracking and quantification

A conventional radiology report primarily consists of a large amount of unstructured text, and lacks clear, concise, consistent and content-rich information. Hence, an area of unmet clinical need consists of developing better ways to communicate radiology findings and information specific to each patient. Here, we design a new workflow and reporting system that combines and integrates advances in engineering technology with those from the medical sciences, the Multidimensional Interactive Radiology Report and Analysis (MIRRA). Until recently, clinical standards have primarily relied on 2D images for the purpose of measurement, but with the advent of 3D processing, many of the manually measured metrics can be automated, leading to better reproducibility and less subjective measurement placement. Hence, we make use this newly available 3D processing in our workflow. Our pipeline is used here to standardize the labeling, tracking, and quantifying of metrics for renal masses.

Robotic unclamped "minimal-margin" partial nephrectomy: ongoing refinement of the anatomic zero-ischemia concept

BACKGROUND

Anatomic partial nephrectomy (PN) techniques aim to decrease or eliminate global renal ischemia.

OBJECTIVE

To report the technical feasibility of completely unclamped "minimal-margin" robotic PN. We also illustrate the stepwise evolution of anatomic PN surgery with related outcomes data.

DESIGN, SETTING, AND PARTICIPANTS

This study was a retrospective analysis of 179 contemporary patients undergoing anatomic PN at a tertiary academic institution between October 2009 and February 2013. Consecutive consented patients were grouped into three cohorts: group 1, with superselective clamping and developmental-curve experience (n = 70); group 2, with superselective clamping and mature experience (n = 60); and group 3, which had completely unclamped, minimal-margin PN (n = 49).

SURGICAL PROCEDURE

Patients in groups 1 and 2 underwent superselective tumor-specific devascularization, whereas patients in group 3 underwent completely unclamped minimal-margin PN adjacent to the tumor edge, a technique that takes advantage of the radially oriented intrarenal architecture and anatomy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Primary outcomes assessed the technical feasibility of robotic, completely unclamped, minimal-margin PN; short-term changes in estimated glomerular filtration rate (eGFR); and development of new-onset chronic kidney disease (CKD) stage >3. Secondary outcome measures included perioperative variables, 30-d complications, and histopathologic outcomes.

RESULTS AND LIMITATIONS

Demographic data were similar among groups. For similarly sized tumors (p = 0.13), percentage of kidney preserved was greater (p = 0.047) and margin width was narrower (p = 0.0004) in group 3. In addition, group 3 had less blood loss (200, 225, and 150ml; p = 0.04), lower transfusion rates (21%, 23%, and 4%; p = 0.008), and shorter hospital stay (p = 0.006), whereas operative time and 30-d complication rates were similar. At 1-mo postoperatively, median percentage reduction in eGFR was similar (7.6%, 0%, and 3.0%; p = 0.53); however, new-onset CKD stage >3 occurred less frequently in group 3 (23%, 10%, and 2%; p = 0.003). Study limitations included retrospective analysis, small sample size, and short follow-up.

CONCLUSIONS

We developed an anatomically based technique of robotic, unclamped, minimal-margin PN. This evolution from selective clamped to unclamped PN may further optimize functional outcomes but requires external validation and longer follow-up.

PATIENT SUMMARY

The technical evolution of partial nephrectomy surgery is aimed at eliminating global renal damage from the cessation of blood flow. An unclamped minimal-margin technique is described and may offer renal functional advantage but requires long-term follow-up and validation at other institutions.