Dataset Information

Novel clinical device tracking and tissue event characterization using proximally placed audio signal acquisition and processing.

ABSTRACT: We propose a new and complementary approach to image guidance for monitoring medical interventional devices (MID) with human tissue interaction and surgery augmentation by acquiring acoustic emission data from the proximal end of the MID outside the patient to extract dynamical characteristics of the interaction between the distal tip and the tissue touched or penetrated by the MID. We conducted phantom based experiments (n = 955) to show dynamic tool/tissue interaction during tissue needle passage (a) and vessel perforation caused by guide wire artery perforation (b). We use time-varying auto-regressive (TV-AR) modelling to characterize the dynamic changes and time-varying maximal energy pole (TV-MEP) to compute subsequent analysis of MID/tissue interaction characterization patterns. Qualitative and quantitative analysis showed that the TV-AR spectrum and the TV-MEP indicated the time instants of the needle path through different phantom objects (a) and clearly showed a perforation versus other generated artefacts (b). We demonstrated that audio signals acquired from the proximal part of an MID could provide valuable additional information to surgeons during minimally invasive procedures.

SUBMITTER: Illanes A

PROVIDER: S-EPMC6089924 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Novel clinical device tracking and tissue event characterization using proximally placed audio signal acquisition and processing.

Illanes Alfredo A Boese Axel A Maldonado Iván I Pashazadeh Ali A Schaufler Anna A Navab Nassir N Friebe Michael M

Scientific reports 20180813 1

We propose a new and complementary approach to image guidance for monitoring medical interventional devices (MID) with human tissue interaction and surgery augmentation by acquiring acoustic emission data from the proximal end of the MID outside the patient to extract dynamical characteristics of the interaction between the distal tip and the tissue touched or penetrated by the MID. We conducted phantom based experiments (n = 955) to show dynamic tool/tissue interaction during tissue needle pass ...[more]

PMID: 30104613

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Project description:Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated.Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R).For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R -0.58 and -0.19 for both studies, respectively.Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.

Dataset Information

Novel clinical device tracking and tissue event characterization using proximally placed audio signal acquisition and processing.

Publications

Novel clinical device tracking and tissue event characterization using proximally placed audio signal acquisition and processing.

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