Preprint Article Version 1 This version is not peer-reviewed

A Mechatronic Platform for Computer Aided Detection of Nodules in Anatomopathological Analyses via Stiffness and Ultrasound Measurements

Version 1 : Received: 30 March 2019 / Approved: 1 April 2019 / Online: 1 April 2019 (13:26:13 CEST)

A peer-reviewed article of this Preprint also exists.

Massari, L.; Bulletti, A.; Prasanna, S.; Mazzoni, M.; Frosini, F.; Vicari, E.; Pantano, M.; Staderini, F.; Ciuti, G.; Cianchi, F.; Messerini, L.; Capineri, L.; Menciassi, A.; Oddo, C.M. A Mechatronic Platform for Computer Aided Detection of Nodules in Anatomopathological Analyses via Stiffness and Ultrasound Measurements. Sensors 2019, 19, 2512. Massari, L.; Bulletti, A.; Prasanna, S.; Mazzoni, M.; Frosini, F.; Vicari, E.; Pantano, M.; Staderini, F.; Ciuti, G.; Cianchi, F.; Messerini, L.; Capineri, L.; Menciassi, A.; Oddo, C.M. A Mechatronic Platform for Computer Aided Detection of Nodules in Anatomopathological Analyses via Stiffness and Ultrasound Measurements. Sensors 2019, 19, 2512.

Journal reference: Sensors 2019, 19, 2512
DOI: 10.3390/s19112512

Abstract

This study presents a platform for ex-vivo detection of cancer nodules, addressing automation of medical diagnoses in surgery and associated histological analyses. The proposed approach takes advantage of the property of cancer to alter the mechanical and acoustical properties of tissues, because of changes in stiffness and density. A force sensor and an ultrasound probe were combined to detect such alterations during force-regulated indentations. To explore the specimens, regardless of their orientation and shape, a scanned area of the test sample was defined using shape recognition applying optical background subtraction to the images captured by a camera. The motorized platform was validated using seven phantom tissues, simulating the mechanical and acoustical properties of ex-vivo diseased tissues, including stiffer nodules that can be encountered in pathological conditions during histological analyses. Results demonstrated the platform’s ability to automatically explore and identify the inclusions in the phantom. Overall, the system was able to correctly identify up to 90.3% of the inclusions by means of stiffness in combination with ultrasound measurements, paving pathway towards robotic palpation during intraoperative examinations.

Subject Areas

cancer nodules detection; phantom; stiffness analysis; ultrasound analysis; visual analysis; automatic robotic platform; remote support for pathologists

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