Identification of tumor nodule in soft tissue: An inverse finite-element framework based on mechanical characterization.

Autor: Candito A; Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK., Palacio-Torralba J; Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK., Jiménez-Aguilar E; Servicio de Oncología Médica, Hospital 12 de Octubre, Madrid, Spain., Good DW; Edinburgh Urological Cancer Group, Division of Pathology Laboratories, Institute of Genetics and Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK.; Department of Urology, NHS Lothian, Western General Hospital, Edinburgh, UK., McNeill A; Edinburgh Urological Cancer Group, Division of Pathology Laboratories, Institute of Genetics and Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK.; Department of Urology, NHS Lothian, Western General Hospital, Edinburgh, UK., Reuben RL; Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK., Chen Y; Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK.
Jazyk: angličtina
Zdroj: International journal for numerical methods in biomedical engineering [Int J Numer Method Biomed Eng] 2020 Aug; Vol. 36 (8), pp. e3369. Date of Electronic Publication: 2020 Jun 15.
DOI: 10.1002/cnm.3369
Abstrakt: Identification and characterization of nodules in soft tissue, including their size, shape, and location, provide a basis for tumor identification. This study proposes an inverse finite-element (FE) based computational framework, for characterizing the size of examined tissue sample and detecting the presence of embedded tumor nodules using instrumented palpation, without a priori anatomical knowledge. The inverse analysis was applied to a model system, the human prostate, and was based on the reaction forces which can be obtained by trans-rectal mechanical probing and those from an equivalent FE model, which was optimized iteratively, by minimizing an error function between the two cases, toward the target solution. The tumor nodule can be identified through its influence on the stress state of the prostate. The effectiveness of the proposed method was further verified using a realistic prostate model reconstructed from magnetic resonance (MR) images. The results show the proposed framework to be capable of characterizing the key geometrical indices of the prostate and identifying the presence of cancerous nodules. Therefore, it has potential, when combined with instrumented palpation, for primary diagnosis of prostate cancer, and, potentially, solid tumors in other types of soft tissue.
(© 2020 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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