News

MyStone will be present at the XXV Lithiasis and Endoscopy, Laparoscopy and Robotics Groups Meeting in Bilbao. The meeting is going to take place on 29th and 30th of January 2015 at Palacio de Congresos y de la Música Euskalduna, Bilbao, Spain. All attendees will be able to visit our stand and test the device. In the following lines you can find the abstract of our project.

 

myStone an Innovative Medical Device for Analysis and Classification of Kidney Stones

Nathaly Segovia1, Montserrat López-Mesas1, Manuel Valiente1, Felipe Lumbreras2, Joan Serrat2, Gemma Rotger2 

1 Grup de Técniques de Separació (GTS), Biomaterials Laboratory, Universitat Autònoma de Barcelona (UAB), Edifici C, Campus UAB, 08193 Cerdanyola del Vallès, Barcelona, Spain.

2 Computer Vision Center (CVC),  Universitat Autònoma de Barcelona (UAB), Edifici O, Campus UAB, 08193 Cerdanyola del Vallès, Barcelona, Spain.

Urinary stone disease is a condition that affects more than 10% of the world population. As well high rates of recurrence near 50% affects patients in the five following years after a stone episode [1,2]. A proper analysis of the calculi will allow us to identify the disorder causes that leads to stone event,providing information with great clinical and diagnostic utility. The most commonly used methods are: chemical elemental analysis, infrared spectrometry (EIR) and stereoscopic microscopy (MEST) [3]. The latter gives essential information about the formation conditions of the kidney stone during the different stages [4]. However, this characterization results in a specialized, slow, and analyst dependent [5,6].

We have developed a medical device that gives to urologists a description of the structure and chemical components of the stone in a few seconds, it also returns specific clinical recomendations for the patient.

myStone is an optical device comprising a camera, which allows a visual analysis of samples illuminating them with different ranges of light. This device is able to recognize and classify kidney stones using image recognition in a few minutes automatically, giving deeper causes of calculus formation information. The device has been tested with over 300 samples and showed superior efficacy to 75-80% in classifying the type of calculation, including calculations consist of different compounds. Today we continue to work on improving these preliminary results with the addition of more samples to expand the database and optimize the sorting process.

Significantly, this device generates a report with specific recommendations for each patient, which will reduce recurrence and improve the quality of life of patients.

References

[1] V. Lorenzo, A. Torres, D. Hernández, J. . Ayus, Manual de Nefrología, Elsevier España, Madrid, 2002.

[2] H.-G. Tiselius, Eur. Urol. Suppl. 2011, 10, 408.

[3] M. Ramis, V. Montesinos, F. Grases, A. Costa-bauza, A. Conte, 2002, 322, 29.

[4] S. Gràcia-Garcia, F. Millán-Rodríguez, F. Rousaud-Barón, R. Montañés-Bermúdez, O. Angerri-Feu, F. Sánchez-Martín, H. Villavicencio-Mavrich, a Oliver-Samper, Actas Urol. españolas 2011, 35, 354.

[5] D. R. Basavaraj, C. S. Biyani, A. J. Browning, J. J. Cartledge, EAU-EBU Updat. Ser. 2007, 5, 126.

[6] A. Nayir, Pediatr. Nephrol. 2002, 17, 425.

 


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