Place de l’urétérorénoscopie souple en première intention pour le traitement des calculs du rein. Résultats de l’enquête de pratique du comité lithiase de l’AFU réalisée en 2011

Estrade, V.; Bensalah, Karim; Bringer, J.; Chabannes, É.; Carpentier, Xavier; Conort, Pierre; Denis, É.; Doré, B.; Gautier, Jean-Romain; Hadjadj, H.; Hubet, J; Hoznek, Andràs; Lechevallier, É.; Mozer, Pierre; Saussine, C.; Yonneau, Laurent; Traxer, Olivier; l’AFU, Comité lithiase de

doi:10.1016/j.purol.2012.09.003

Cited by 14 publications

(9 citation statements)

References 11 publications

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“…Indeed, despite the variety of compositions and morphologies observed in urinary calculi, about 90% are composed of a limited number of crystalline species and morphological characteristics that are easily recognised through an endoscopic examination Estrade et al (2013Estrade et al ( , 2017. The study in Estrade et al (2020) showed a high concordance between endoscopic and microscopic typing of the kidney stones.…”

Section: Database Constructionmentioning

confidence: 88%

“…Therefore, identifying the kidney stone types is crucial to avoid relapses Kartha et al (2013); Friedlander et al (2015) through personalized treatments (diet adaptation, surgery, etc.) is considered of utmost importance by many practitioners Estrade et al (2013). For this purpose, several guidelines for visually recognizing some of the more common types of kidney stones (see Table 1) have been proposed in recent years Frochot and Daudon (2016); Estrade et al (2017) to be applied in the clinical practice.…”

Section: Introductionmentioning

confidence: 99%

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On the in vivo recognition of kidney stones using machine learning

Ochoa-Ruiz¹,

Estrade²,

López³

et al. 2022

Preprint

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Determining the type of kidney stones allows urologists to prescribe a treatment to avoid recurrence of renal lithiasis. An automated in-vivo image-based classification method would be an important step towards an immediate identification of the kidney stone type required as a first phase of the diagnosis. In the literature it was shown on ex-vivo data (i.e., in very controlled scene and image acquisition conditions) that an automated kidney stone classification is indeed feasible. This pilot study compares the kidney stone recognition performances of six shallow machine learning methods and three deep-learning architectures which were tested with in-vivo images of the four most frequent urinary calculi types acquired with an endoscope during standard ureteroscopies. This contribution details the database construction and the design of the tested kidney stones classifiers. Even if the best results were obtained by the Inception v3 architecture (weighted precision, recall and F1-score of 0.97, 0.98 and 0.97, respectively), it is also shown that choosing an appropriate colour space and texture features allows a shallow machine learning method to approach closely the performances of the most promising deep-learning methods (the XGBoost classifier led to weighted precision, recall and F1-score values of 0.96). This paper is the first one that explores the most discriminant features to be extracted from images acquired during ureteroscopies.

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Section: Database Constructionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

On the in vivo recognition of kidney stones using machine learning

Ochoa-Ruiz¹,

Estrade²,

López³

et al. 2022

Preprint

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“…De par sa nature endoscopique et parce que la lithotritie se déroule par vaporisation LASER holmium de contact, elle répond au traitement de tous les types de calcul; aucun calcul ne résistant au laser [ 5 ]. Les indications de l'URSS-L en première intention dans le traitement des calculs du haut appareil urinaire sont bien établies par Le comité de lithiase de l'AFU et d'autres sociétés savantes [ 6 ]. Dans la série de B.…”

Section: Discussionunclassified

Urétéroscopie souple laser dans le traitement des calculs du haut appareil urinaire: résultats a propos de 166 interventions

Padja¹,

Ibarra²,

Lmezguidi³

et al. 2015

Pan Afr Med J

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L’évolution de la technique opératoire fait de l'urétéroscopie souple –Laser (URSS-L) une méthode efficace et sure dans le traitement des calculs du haut appareil urinaire (HAU). Elle apparait comme une option salvatrice après échec des autres options thérapeutiques. Son coût limite son accessibilité et restreint ses indications dans certains contextes socio-économiques. Nous rapportons l'expérience du service sur les indications, les résultats et les complications de l'URSS-L dans le traitement des calculs du HAU. C'est une étude rétrospective sur 4ans concernant 130 patients ayant des calculs du HAU. Un scanner permettait de déterminer les caractéristiques des calculs avant l'intervention et de faire un contrôle après afin de juger de l'efficacité du traitement. Une analyse statistique évaluait l'influence des différents paramètres des calculs sur l'efficacité de l'intervention. Un suivi était réalisé afin de détecter les complications. L’âge moyen des patients était de 52 ± 17ans. 166 interventions étaient faites en 3 séries. Les indications étaient de première intention dans 50.32% suivi des échecs de LEC. La durée moyenne de l'intervention était de 73min ± 25min pour une taille moyenne des calculs de 13.78mm ± 5mm. Le taux de succès global était de 78.91% (78.71%; 80%; 100%) respectivement après la 1ère, la 2ème et la 3ème série. Aucun paramètre n'influençait significativement le taux de succès. 14.45% de complications était enregistré. L'URSS-L est une méthode aussi efficace que sure dans le traitement des calculs du HAU nous motivant malgré son coût, à élargir ses indications en première intention lorsque les calculs répondent aux critères de choix.

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“…A prospective comparative study come from India [26] showed that stone clearance in both modalities was high and complications were low in the mini-percutaneous and RIRS groups. Estrade et al [27] recommended RIRS as a first-line treatment regardless of size and number of kidney stones if extracorporeal shock wave lithotripsy and PCNL are contraindicated or if their predictable results are poor (hard stones, morbid obesity, lower pole stones) or if stone access is difficult (intradiverticular).…”

Section: Discussionmentioning

confidence: 99%

Retrograde Intrarenal Surgery versus Percutaneous Nephrolithotomy for Treatment of Renal Stones >2 cm: A Meta-Analysis

et al. 2014

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Objective: To systematically review the efficacy and safety of retrograde intrarenal surgery (RIRS) versus percutaneous nephrolithotomy (PCNL) for the treatment of renal calculi >2 cm. Methods: We searched PubMed, Cochrane Library, Embase and the Chinese Biomedical Literature Database about RIRS and PCNL for the treatment of renal stones. The retrieval time ended in December 2013. All clinical trials were retrieved and their included references investigated. Two reviewers independently assessed the quality of all included studies, and the eligible studies were included and analyzed using the RevMan 5.2 software. Results: Two randomized controlled trials and six clinical controlled trials were included, involving a total of 590 patients. Our meta-analysis showed that there were not significant differences in stone-free rate (relative risk [RR] = 0.95, 95% confidence interval (CI) 0.88-1.02, p = 0.11) and fever (RR = 0.95, 95% CI 0.54-1.67, p = 0.85) between RIRS and PCNL. We found that hospital stay (weighted mean difference [WMD] = -2.10, 95% CI -3.08 to -1.11, p < 0.10) and bleeding (RR = 0.20, 95% CI 0.06-0.68, p = 0.01) were lower and operation time was longer (WMD = 19.11, 95% CI 7.83-30.39, p < 0.10) for RIRS. Conclusion: RIRS is a safe and effective procedure. It can successfully treat patients with stones >2 cm with a high stone-free rate and significantly reduce hospital stay without increasing complications. RIRS can be used as an alternative treatment to PCNL in selected cases with larger renal stones. However, further randomized trials are needed to confirm these findings.

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Place de l’urétérorénoscopie souple en première intention pour le traitement des calculs du rein. Résultats de l’enquête de pratique du comité lithiase de l’AFU réalisée en 2011

Cited by 14 publications

References 11 publications

On the in vivo recognition of kidney stones using machine learning

On the in vivo recognition of kidney stones using machine learning

Urétéroscopie souple laser dans le traitement des calculs du haut appareil urinaire: résultats a propos de 166 interventions

Retrograde Intrarenal Surgery versus Percutaneous Nephrolithotomy for Treatment of Renal Stones >2 cm: A Meta-Analysis

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