[The basis of endoscopic stones recognition, a prospective monocentric study]

Surgical Artificial Intelligence: Endourology

Endourology is ripe with information that includes patient factors, laboratory tests, outcomes, and visual data, which is becoming increasingly complex to assess. Artificial intelligence (AI) has the potential to explore and define these relationships; however, humans might not be involved in the input, analysis, or even determining the methods of analysis. Herein, the authors present the current state of AI in endourology and highlight the need for urologists to share their proposed AI solutions for reproducibility outside of their institutions and prepare themselves to properly critique this new technology.

2022 Recommendations of the AFU Lithiasis Committee: Laser - utilization and settings

Endocorporeal lithotripsy has progressed thanks to the development of lasers. Two laser sources are currently available: Holmium:YAG (Ho:YAG) and more recently Thulium Fiber Laser (TFL). The settings generally used are dusting, fragmentation, and "pop-corning". These are the first recommendations on laser use for stone management and their settings. Settings must be modulated and can be changed during the treatment according to the expected and obtained effects, the location and stone type that is treated. METHODOLOGY: These recommendations have been developed using two methods: the Clinical Practice Recommendation (CPR) method and the ADAPTE method, depending on whether or not the question was considered in the European Association of Urology (EAU) recommendations (https://uroweb.org/guidelines/urolithiasis [EAU Guidelines on urolithiasis. 2022]) and their adaptability to the French context.

Prospective Comparison of Thulium and Holmium Laser Lithotripsy for the Treatment of Upper Urinary Tract Lithiasis

Background

Lithotripsy with holmium:yttrium-aluminum-garnet (Ho:YAG) laser is the current gold standard for treating stones of the upper urinary tract (UUT). The recently introduced thulium fiber laser (TFL) has the potential to be more efficient and as safe as Ho:YAG.

Objective

To compare the performance and complications between Ho:YAG and TFL for UUT lithotripsy.

Design setting and participants

This was a prospective single-center study of 182 patients treated between February 2021 and February 2022. In a consecutive approach, laser lithotripsy was performed via ureteroscopy with Ho:YAG for 5 mo, and then with TFL for 5 mo.

Outcome measurements and statistical analysis

Our primary outcome was stone-free (SF) status at 3 mo after ureteroscopy with Ho:YAG versus TFL lithotripsy. Secondary outcomes were complication rates and results regarding the cumulative stone size. Patients were followed at 3 mo with abdominal imaging (ultrasound or computed tomography).

Results and limitations

The study cohort comprised 76 patients treated with Ho:YAG laser and 100 patients treated with TFL. Cumulative stone size was significantly higher in the TFL than in the Ho:YAG group (20.4 vs 14.8 mm; p = 0.01). SF status was similar in both groups (68.4% vs 72%; p = 0.06). Complication rates were comparable. In subgroup analysis, the SF rate was significantly higher (81.6% vs 62.5%; p = 0.04) and the operative time was shorter for stones measuring 1-2 cm, whereas the results were similar for stones <1 cm and >2 cm. The lack of randomization and single-center design are the main limitations of the study.

Conclusions

TFL and Ho:YAG lithotripsy are comparable in terms of the SF rate and safety for the treatment of UUT lithiasis. According to our study, for a cumulative stone size of 1-2 cm, TFL is more effective than Ho:YAG.

Patient summary

We compared the efficiency and safety of two laser types for the treatment of stones in the upper urinary tract. We found that stone-free status at 3 months did not significantly differ between the holmium and thulium lasers.

Deep morphological recognition of kidney stones using intra-operative endoscopic digital videos

Objective. To assess the performance and added value of processing complete digital endoscopic video sequences for the automatic recognition of stone morphological features during a standard-of-care intra-operative session.Approach. A computer-aided video classifier was developed to predict in-situ the morphology of stone using an intra-operative digital endoscopic video acquired in a clinical setting. Using dedicated artificial intelligence (AI) networks, the proposed pipeline selects adequate frames in steady sequences of the video, ensures the presence of (potentially fragmented) stones and predicts the stone morphologies on a frame-by-frame basis. The automatic endoscopic stone recognition (A-ESR) is subsequently carried out by mixing all collected morphological observations.Main results. The proposed technique was evaluated on pure (i.e. include one morphology) and mixed (i.e. include at least two morphologies) stones involving ‘Ia/Calcium Oxalate Monohydrate’ (COM), ‘IIb/Calcium Oxalate Dihydrate’ (COD) and ‘IIIb/Uric Acid’ (UA) morphologies. The gold standard ESR was provided by a trained endo-urologist and confirmed by microscopy and infra-red spectroscopy. For the AI-training, 585 static images were collected (349 and 236 observations of stone surface and section, respectively) and used. Using the proposed video classifier, 71 digital endoscopic videos were analyzed: 50 exhibited only one morphological type and 21 displayed two. Taken together, both pure and mixed stone types yielded a mean diagnostic performances as follows: balanced accuracy = [88 ± 6] (min = 81)%, sensitivity = [80 ± 13] (min = 69)%, specificity = [95 ± 2] (min = 92)%, precision = [78 ± 12] (min = 62)% and F1-score = [78 ± 7] (min = 69)%.Significance. These results demonstrate that AI applied on digital endoscopic video sequences is a promising tool for collecting morphological information during the time-course of the stone fragmentation process without resorting to any human intervention for stone delineation or the selection of adequate steady frames.

How reliable is endoscopic stone recognition? A comparison between visual stone identification and formal stone analysis

OBJECTIVE

To assess the diagnostic accuracy and intra-observer agreement of endoscopic stone recognition compared with formal stone analysis.

INTRODUCTION

Stone analysis is a corner stone in the prevention of stone recurrence. Although X-ray diffraction and infrared spectroscopy are the recommended techniques for reliable formal stone analysis, this is not always possible, and the process takes time and is costly. Endoscopic stone recognition could be an alternative as it would give immediate information on stone composition.

MATERIAL AND METHODS

Fifteen endourologists predicted stone composition based on 100 videos from ureterorenoscopy. Diagnostic accuracy was evaluated by comparing the prediction from visual assessment with stone analysis by X-ray diffraction. After 30 days, the videos were reviewed again in a random order to assess intra-observer agreement.

RESULTS

The median diagnostic accuracy for calcium oxalate monohydrate was of 54% in questionnaire 1 (Q1) and 59% in questionnaire 2 (Q2), whereas calcium oxalate dihydrate had a median diagnostic accuracy of 75% in Q1 and 50% in Q2. The diagnostic accuracy for calcium hydroxyphosphate was 10% in Q1 and 13% in Q2. The median diagnostic accuracy for calcium hydrogen phosphate dihydrate and calcium magnesium phosphate was 0% in both questionnaires. The median diagnostic accuracy for magnesium ammonium phosphate was in 20% in Q1 and 40% in Q2. The median diagnostic accuracy for uric acid was 22% in both questionnaires. Finally, there was a diagnostic accuracy of 60% in Q1 and 80% in Q2 for cystine. The intra-observer agreement ranged between 45-72%.

CONCLUSION

Diagnostic accuracy of endoscopic stone recognition is limited and intra-observer agreement is below the threshold of acceptable agreement.

Endoscopic Papillary Abnormalities and Stone Recognition (EPSR) during Flexible Ureteroscopy: A Comprehensive Review

Introduction: The increasing efficiency of the different lasers and the improved performance of endoscopic devices have led to smaller stone fragments that impact the accuracy of microscopic evaluation (morphological and infrared). Before the stone destruction, the urologist has the opportunity to analyze the stone and the papillary abnormalities endoscopically (endoscopic papillary recognition (EPR) and endoscopic stone recognition (ESR)). Our objective was to evaluate the value for those endoscopic descriptions. Methods: The MEDLINE and EMBASE databases were searched in February 2021 for studies on endoscopic papillary recognition and endoscopic stone recognition. Results: If the ESR provided information concerning the main crystallization process, EPR provided information concerning the origin of the lithogenesis and its severity. Despite many actual limitations, those complementary descriptions could support the preventive care of the stone formers in improving the diagnosis of the lithogenesis mechanism and in identifying high-risk stone formers. Conclusion: Until the development of an Artificial Intelligence recognition, the endourologist has to learn EPSR to minimize the distortion effect of the new lasers on the stone analysis and to improve care efficiency of the stone formers patients.

Towards automatic recognition of pure and mixed stones using intra-operative endoscopic digital images

OBJECTIVE

To assess automatic computer-aided in situ recognition of the morphological features of pure and mixed urinary stones using intra-operative digital endoscopic images acquired in a clinical setting.

MATERIALS AND METHODS

In this single-centre study, a urologist with 20 years' experience intra-operatively and prospectively examined the surface and section of all kidney stones encountered. Calcium oxalate monohydrate (COM) or Ia, calcium oxalate dihydrate (COD) or IIb, and uric acid (UA) or IIIb morphological criteria were collected and classified to generate annotated datasets. A deep convolutional neural network (CNN) was trained to predict the composition of both pure and mixed stones. To explain the predictions of the deep neural network model, coarse localization heat-maps were plotted to pinpoint key areas identified by the network.

RESULTS

This study included 347 and 236 observations of stone surface and stone section, respectively; approximately 80% of all stones exhibited only one morphological type and approximately 20% displayed two. A highest sensitivity of 98% was obtained for the type 'pure IIIb/UA' using surface images. The most frequently encountered morphology was that of the type 'pure Ia/COM'; it was correctly predicted in 91% and 94% of cases using surface and section images, respectively. Of the mixed type 'Ia/COM + IIb/COD', Ia/COM was predicted in 84% of cases using surface images, IIb/COD in 70% of cases, and both in 65% of cases. With regard to mixed Ia/COM + IIIb/UA stones, Ia/COM was predicted in 91% of cases using section images, IIIb/UA in 69% of cases, and both in 74% of cases.

CONCLUSIONS

This preliminary study demonstrates that deep CNNs are a promising method by which to identify kidney stone composition from endoscopic images acquired intra-operatively. Both pure and mixed stone composition could be discriminated. Collected in a clinical setting, surface and section images analysed by a deep CNN provide valuable information about stone morphology for computer-aided diagnosis.

Toward improved endoscopic examination of urinary stones: a concordance study between endoscopic digital pictures vs microscopy

Objective

To improve endoscopic recognition of the most frequently encountered urinary stone morphologies for a better aetiological approach in lithiasis by urologists.

Materials and Methods

An expert urologist intraoperatively and prospectively (between June 2015 and June 2018) examined the surface, the section, and the nucleus of all encountered kidney stones. Fragmented stones were subsequently analysed by a biologist based on both microscopic morphological (i.e. binocular magnifying glass) and infrared (i.e. Fourier transform‐infrared spectroscopy) examinations (microscopists were blinded to the endoscopic data). Morphological criteria were collected and classified for the endoscopic and microscopic studies. The Wilcoxon–Mann–Whitney test was used to detect differences between the endoscopic and microscopic diagnoses. A diagnosis for a given urinary stone was considered ‘confirmed’ for a non‐statistically significant difference.

Results

A total of 399 urinary stones were included in this study: 51.4% of the stones had only one morphological type, while 48.6% were mixed stones (41% had at least two morphologies and 7.6% had three morphologies). The overall matching rate was 81.6%. Diagnostics were confirmed for the following morphologies: whewellite (Ia or Ib), weddellite (IIa or IIb), uric acid (IIIa or IIIb), carbapatite‐struvite association (IVb), and brushite (IVd).

Conclusions

Our preliminary study demonstrates the feasibility of using endoscopic morphology for the most frequently encountered urinary stones and didactic boards of confirmed endoscopic images are provided. The present study constitutes the first step toward endoscopic stone recognition, which is essential in lithiasis. We provide didactic boards of confirmed endoscopic images that pave the way for automatic computer‐aided in situ recognition.

Classification of Stones According to Michel Daudon: A Narrative Review

CONTEXT

Morphoconstitutional analysis of urinary stones is perhaps the most important examination in the evaluation of a patient with urolithiasis.

OBJECTIVE

A comprehensive stone classification system was developed in the early 1990s by Michel Daudon, which included the main types of stones and their possible physiopathogenic origin.

EVIDENCE ACQUISITION

A narrative review of the articles published about this classification was conducted, without time limit.

EVIDENCE SYNTHESIS

Two analytical steps are needed for the classification process: the microscopic examination, which gives the stone morphology, and the physical analysis, which provides the stone constitution. Upon completion of a full analysis, knowledge of the principal crystal species of the stone is acquired. In addition, this analysis highlights the possible causes of the lithogenic process, taking in account less frequent, but severe, pathologies.

CONCLUSIONS

The aim of this report is to summarize the principal etiological causes for urinary stone formation thanks to the morphoconstitutional analysis and to present its contribution in the field of urinary stones.

PATIENT SUMMARY

We looked at all types of stones and found that their origin varies according to the underlying pathology of the patient.