Tactile Resonance Sensor Research Articles

A tactile resonance sensor for prostate cancer detection – evaluation on human prostate tissue

Prostate cancer surgery risks erectile problems and incontinence for the patient. An instrument for guiding surgeons to avoid nerve bundle damage and ensure complete cancer removal is desirable. We present a tactile resonance sensor made of PZT ceramics, mounted in a 3D motorized translation stage for scanning and measuring tissue stiffness for detecting cancer in human prostate. The sensor may be used during surgery for guidance, scanning the prostate surface for the presence of cancer, indicating migration of cancer cells into surrounding tissue. Ten fresh prostates, obtained from patients undergoing prostate cancer surgery, were cut into 0.5 cm thick slices. Each slice was measured for tissue stiffness at about 25 different sites and compared to histology for validation cancer prediction by stiffness. The statistical analysis was based on a total of 148 sites with non-cancer and 40 sites with cancer. Using a generalized linear mixed model (GLMM), the stiffness data predicted cancer with an area under the curve of 0.74, after correcting for overfitting using bootstrap validation. Mean prostate stiffness on the logarithmic scale (p = 0.015) and standardized Z-scores (p = 0.025) were both significant predictors of cancer. This study concludes that stiffness measured by the tactile resonance sensor is a significant predictor of prostate cancer with potential for future development towards a clinical instrument for surgical guidance.

Using a look-up table technique and finite element calculations for quick detection of stiff inclusions in silicone rubber

PurposeThe aim of the study was to show that a new method, using a look-up table technique, can be used to detect the presence and position of an inclusion embedded in a tissue-like material. Due to the time-consuming nature of the finite element (FE) method or FEM, real-time applications involving FEM as part of a control loop, are traditionally limited to slowly varying systems. By using a simplified two-dimensional FE model and a look-up table, we show by simulations and experiments that it is possible to achieve reasonable computational times in a tactile resonance sensor application.Design/methodology/approachA piezoelectric disk was placed in the center of a silicone rubber disk (SRD) with viscoelastic properties, where it acted as both sensor and actuator and dissipated radial acoustic waves into the silicone. The look-up table was constructed by calculating the radial Lamb wave transition frequencies in the impedance frequency response of the sensor while varying the position of an inclusion. A position-matching algorithm was developed that matched measured and calculated Lamb wave transitions and thereby identified the presence and position of an inclusion.FindingsIn an experiment, the position of a hard inclusion was determined by measuring the Lamb transition frequencies of the first radial resonance in two SRDs. The result of the matching algorithm for Disk 1 was that the matched position was less than 3% from the expected value. For Disk 2, the matching algorithm erroneously reported two false positions before reporting a position that was less than 5% from the expected value. An explanation for this discrepancy is presented. In a verifying experiment, the algorithm identified the condition with no inclusion present.Originality/valueThe approach outlined in this work, adds to the prospect of developing time-sensitive diagnostic instruments. This approach has the potential to provide a powerful technique to quickly present spatial information on detected tumors.

Prostate Cancer Detection with a Tactile Resonance Sensor-Measurement Considerations and Clinical Setup.

Tumors in the human prostate are usually stiffer compared to surrounding non-malignant glandular tissue, and tactile resonance sensors measuring stiffness can be used to detect prostate cancer. To explore this further, we used a tactile resonance sensor system combined with a rotatable sample holder where whole surgically removed prostates could be attached to detect tumors on, and beneath, the surface ex vivo. Model studies on tissue phantoms made of silicone and porcine tissue were performed. Finally, two resected human prostate glands were studied. Embedded stiff silicone inclusions placed 4 mm under the surface could be detected in both the silicone and biological tissue models, with a sensor indentation of 0.6 mm. Areas with different amounts of prostate cancer (PCa) could be distinguished from normal tissue (p < 0.05), when the tumor was located in the anterior part, whereas small tumors located in the dorsal aspect were undetected. The study indicates that PCa may be detected in a whole resected prostate with an uneven surface and through its capsule. This is promising for the development of a clinically useful instrument to detect prostate cancer during surgery.

Improved tactile resonance sensor for robotic assisted surgery

This paper presents an improved tactile sensor using a piezoelectric bimorph able to differentiate soft materials with similar mechanical characteristics. The final aim is to develop intelligent surgical tools for brain tumour resection using integrated sensors in order to improve tissue tumour delineation and tissue differentiation. The bimorph sensor is driven using a random phase multisine and the properties of contact between the sensor's tip and a certain load are evaluated by means of the evaluation of the nonparametric FRF. An analysis of the nonlinear contributions is presented to show that the use of a linear model is feasible for the measurement conditions. A series of gelatine phantoms were tested. The tactile sensor is able to identify minimal differences in the consistency of the measured samples considering viscoelastic behaviour. A variance analysis was performed to evaluate the reliability of the sensors and to identify possible error sources due to inconsistencies in the preparation method of the phantoms. The results of the variance analysis are discussed showing that ability of the proposed tactile sensor to perform high quality measurements.

Detection of Stiff Nodules Embedded in Soft Tissue Phantoms, Mimicking Cancer Tumours, Using a Tactile Resonance Sensor

Background: Prostate cancer (PCa) is the most common form of cancer among males in Europe and in the USA and the most common curative treatment is removal of the prostate, i.e. prostatectomy. After the removal, the prostate is histopathologically analysed. One area of interest is to examine the perifery of the prostate, as tumours on and near the surface can indicate that the PCa has spread to other parts of the body. There are no current methods to examine the surface of the prostate at the time of surgery. Tactile resonance sensors can be used for detecting areas of different stiffness in soft tissue. Human prostate tissue affected by cancer is usually stiffer than healthy tissue, and for this purpose, a tactile resonance sensor was developed. The aim of this study was to investigate the depth at which embedded stiffer volumes could be detected, using soft tissue phantoms. Methods: With the tactile resonance sensor used in this study, the shift of the resonance frequency and the force at contact with tissue can be measured, and combined into a tissue stiffness parameter. The detection sensitivity of the sensor at impression depths, 0.4 and 0.8 mm, was measured for detection of inserted nodules of stiff silicone in softer silicone and in chicken muscle tissue, mimicking prostate tissue with cancer tumours. Results: Measurements on the silicone samples detected the hidden stiffer object at a depth of 1 - 4 mm with a difference in the stiffness parameter of 80 - 900 mN/kHz (p < 0.028, n = 48). At the depth 5 - 6 mm the difference was smaller but still significant < 30 mN/kHz (p < 0.05, n = 24). For the measurements on chicken muscle, the detectable depth was 4 mm (p < 0.05, n = 24). Conclusion: This model study suggests that, with only a small impression depth of ≤1 mm, the resonance sensor system described here can detect stiffness variations located at least 4 mm in silicone and chicken muscle, mimicking tumours in prostate tissue.

A review of force and resonance sensors used in the clinical study of tissue properties

Tactile sensing is commonly carried out by humans using their fingers or hands to estimate the physical properties of an object. A large body of literature covers a range of applications of these methods in clinical situations. The objective of this work is to show the breadth of application areas explored and the achievements that have been made in the measurement of physical variables of interest to physicians using tactile force and resonance sensors. Although a broad spectrum of applications has been considered, of particular interest is the application of these methods to determine tissue properties in vivo. Progress in this direction has been made by various groups particularly with respect to piezoelectric and capacitance sensors. Also described are the findings of a preliminary study of a tactile system designed to examine the abdomen of the clinically super-obese patient.

Optical fibre probe NIR Raman measurements in ambient light and in combination with a tactile resonance sensor for possible cancer detection

First measurements on a combined instrument with a thin fibre optic Raman probe mounted inside a hollow tactile resonance sensor have been performed in ambient light on porcine tissue. The ambient fluorescent light was removed successfully from the spectra. The stiffness and the biomolecular composition of the tissue were analysed.

Edema and elasticity of a fronto-temporal decompressive craniectomy

Background:Decompressive craniectomy is undertaken for relief of brain herniation caused by acute brain swelling. Brain stiffness can be estimated by palpating the decompressive cranial defect and can provide some relatively subjective information to the neurosurgeon to help guide care. The goal of the present study was to objectively evaluate transcutaneous stiffness of the cranial defect using a tactile resonance sensor and to describe the values in patients with a decompressive window in order to characterize the clinical association between brain edema and stiffness.Methods:Data were prospectively collected from 13 of 37 patients who underwent a decompressive craniectomy in our hospital during a 5-year period. Transcutaneous stiffness was measured as change in frequency and as elastic modulus.Results:Stiffness variables of the decompressive site were measured without any adverse effect and subsequent calculations revealed change in frequency = 101.71 ± 36.42 Hz, and shear elastic modulus = 1.99 ± 1.11 kPa.Conclusions:The elasticity of stiffness of a decompressive site correlated with brain edema, cisternal cerebrospinal fluid pressure, and brain shift, all of which are related to acute brain edema.

Tactile resonance sensors in medicine

Tactile sensors in general are used for measuring the physical parameters associated with contact between sensor and object. Tactile resonance sensors in particular are based on the principle of measuring the frequency shift, Δf, defined as the difference between a freely vibrating sensor resonance frequency and the resonance frequency measured when the sensor makes contact to an object. Δf is therefore related to the acoustic impedance of the object and can be used to characterize its material properties. In medicine, tactile resonance sensor systems have been developed for the detection of cancer, human ovum fertility, eye pressure and oedema. In 1992 a Japanese research group published a paper presenting a unique phase shift circuit to facilitate resonance measurements. In this review we summarize the current state-of-the-art of tactile resonance sensors in medicine based on the phase shift circuit and discuss the relevance of the measured parameters for clinical diagnosis. Future trends and applications enabled by this technology are also predicted.

Explanatory models for a tactile resonance sensor system—elastic and density-related variations of prostate tissue in vitro

Tactile sensors based on piezoelectric resonance have been adopted for medical applications. The sensor consists of an oscillating piezoelectric sensor–circuit system, and a change in resonance frequency is observed when the sensor tip contacts a measured object such as tissue. The frequency change at a constant applied force or mass load is used as a stiffness-sensitive parameter in many applications. Differential relations between force and frequency have also been used for monitoring intraocular pressure and stiffness variations in prostate tissue in vitro. The aim of this study was to relate the frequency change (Δf), measured force (F) and the material properties, density and elasticity to an explanatory model for the resonance sensor measurement principle and thereby to give explanatory models for the stiffness parameters used previously. Simulations of theoretical equations were performed to investigate the relation between frequency change and contact impedance. Measurements with a resonance sensor system on prostate tissue in vitro were used for experimental validation of the theory. Tissue content was quantified with a microscopic-based morphometrical method. Simulation results showed that the frequency change was dependent upon density (ρ) and contact area (S) according to Δf ∝ ρS3/2. The experiments followed the simulated theory at small impression depths. The measured contact force followed a theoretical model with the dependence of the elastic modulus (E) and contact area, F ∝ ES3/2. Measured density variations related to histological variations were statistically weak or non-significant. Elastic variations were statistically significant with contributions from stroma and cancer relative to normal glandular tissue. The theoretical models of frequency change and force were related through the contact area, and a material-dependent explanatory model was found as Δf ∝ ρE−1F. It explains the measurement principle and the previously established stiffness parameters from the material properties point of view.

Spatial variations in prostate tissue histology as measured by a tactile resonance sensor

In recent years, tactile sensors based on piezoelectric resonance sensor technology have been used for medical diagnosis where the sensor's stiffness-measuring properties can reflect tissue pathology. The change in the frequency of the resonating system and the change in force when contact is made with tissue are used as a stiffness parameter. Earlier stiffness measurements of prostate tissue in vitro demonstrate variations related to tissue composition. In this study, measured stiffness from two human prostate specimens was compared to histological composition of prostate tissue below and around the measurement points. Tissue stiffness was measured with the resonance sensor system. Tissue composition was measured at four different depths in the tissue specimen using a microscopic-image-based morphometrical method. With this method, the proportion of tissue types was determined at the points of intersections in a circular grid on the images representing each measurement point. Numerical values were used for weighting the tissue proportions at different depths in the tissue specimen. For an impression depth of 1.0 mm, the sensing depth in this study was estimated to be 3.5–5.5 mm. Stiffness variations due to horizontal tissue variations were investigated by studying the dependence of the size of the circular grid area relative to the contact area of the sensor tip. The sensing area (grid radius) was estimated to be larger than the contact area (contact radius) between the sensor tip and the tissue. Thus, the sensor tip registers spatial variations in prostate tissue histology, both directly below and lateral to the tip itself. These findings indicate that tumours around the sensor tip could be detected, which in turn supports the idea of a future resonance-sensor-based clinical device for detecting tumours and for guiding biopsies.