A real-time prostate cancer detection technique using needle insertion force and patient-specific criteria during percutaneous intervention

Assessment of needle-tissue force models based on ex vivo measurements

Needle insertion is one of the most common procedures in clinical practice. Existing statistics reveal that success rates of needle insertions can be low, leading to potential complications and patient discomfort. Real-time imaging techniques like ultrasound and X-ray can assist in improving precision, but even experienced practitioners may face challenges in visualizing the needle tip. Researchers have proposed models of force interactions during needle insertions into biological tissue to enhance accuracy. This article presents an evaluation of the forces acting on intravenous needles during insertion into skin. The aim was to explore mathematical models, compare them with data from tests on animal specimens, and select the most suitable model for future research. The experimental setup involved conducting needle insertion tests on animal-originated cadavers, using the Brucker Universal Mechanical Tester device, which measured the force response during vertical movement of the needle. The research was divided into 2 stages. In Stage I, force measurements were recorded for both the insertion and extraction phases of the hypodermic needles. The measurements were conducted for several different needle sizes, speed and insertion angles. In Stage II, five different models were examined to determine how well they matched the experimental data. Based on the analysis of fit quality coefficients, the Gordon's exponential model was identified as the best fit to the measured data. The influence of needle size, insertion angle, and insertion speed on the measured force values was confirmed. Different insertion speeds revealed the viscoelastic properties of the tested samples. The presence of the skin layer affected the puncture force and force values for subsequent layers.

Developing a novel force forecasting technique for early prediction of critical events in robotics

Safety critical events in robotic applications can often be characterized by forces between the robot end-effector and the environment. One application in which safe interaction between the robot and environment is critical is in the area of medical robots. In this paper, we propose a novel Compact Form Dynamic Linearization Model-Free Prediction (CFDL-MFP) technique to predict future values of any time-series sensor data, such as interaction forces. Existing time series forecasting methods have high computational times which motivates the development of a novel technique. Using Autoregressive Integrated Moving Average (ARIMA) forecasting as benchmark, the performance of the proposed model was evaluated in terms of accuracy, computation efficiency, and stability on various force profiles. The proposed algorithm was 11% more accurate than ARIMA and maximum computation time of CFDL-MFP was 4ms, compared to ARIMA (7390ms). Furthermore, we evaluate the model in the special case of predicting needle buckling events, before they occur, by using only axial force and needle-tip position data. The model was evaluated experimentally for robustness with steerable needle insertions into different tissues including gelatin and biological tissue. For a needle insertion velocity of 2.5mm/s, the proposed algorithm was able to predict needle buckling 2.03s sooner than human detections. In biological tissue, no false positive or false negative buckling detections occurred and the rates were low in artificial tissue. The proposed forecasting model can be used to ensure safe robot interactions with delicate environments by predicting adverse force-based events before they occur.

Fiber Optic Force Sensors for MRI-Guided Interventions and Rehabilitation: A Review

Magnetic Resonance Imaging (MRI) provides both anatomical imaging with excellent soft tissue contrast and functional MRI imaging (fMRI) of physiological parameters. The last two decades have witnessed the manifestation of increased interest in MRI-guided minimally invasive intervention procedures and fMRI for rehabilitation and neuroscience research. Accompanying the aspiration to utilize MRI to provide imaging feedback during interventions and brain activity for neuroscience study, there is an accumulated effort to utilize force sensors compatible with the MRI environment to meet the growing demand of these procedures, with the goal of enhanced interventional safety and accuracy, improved efficacy and rehabilitation outcome. This paper summarizes the fundamental principles, the state of the art development and challenges of fiber optic force sensors for MRI-guided interventions and rehabilitation. It provides an overview of MRI-compatible fiber optic force sensors based on different sensing principles, including light intensity modulation, wavelength modulation, and phase modulation. Extensive design prototypes are reviewed to illustrate the detailed implementation of these principles. Advantages and disadvantages of the sensor designs are compared and analyzed. A perspective on the future development of fiber optic sensors is also presented which may have additional broad clinical applications. Future surgical interventions or rehabilitation will rely on intelligent force sensors to provide situational awareness to augment or complement human perception in these procedures.

Clinical study of a noninvasive multimodal sono-contrast induced spectroscopy system for breast cancer diagnosis

PURPOSE

To present a noninvasive multimodal sono-contrast induced spectroscopy (SCIS) system for breast cancer detection.

METHODS

An IRB approved clinical study was carried out to evaluate its diagnostic power. A total of 66 subjects were enrolled with informed consent. The study data were grouped into healthy breast tissue (26), histologically proven cancer (14), and benign mass (26). The diffuse reflectance optical intensity and low intensity focused ultrasound (LIFU) signals, as well as ultrasound images, were collected during each study. The ratio of optical intensities at wavelengths 685 and 830 nm was analyzed using wavelet technique to compare the LIFU effects in cancer and noncancerous tissues. The ultrasound images were also processed to obtain tissue texture parameters, such as correlation, energy, contrast, homogeneity, etc. Backward stepwise regression method was performed to identify the statistically significant factors correlating to tissue types (cancer vs benign mass).

RESULTS

Comparison of the optical signals showed that LIFU induced transitory fluctuation in noncancerous tissue, but not in malignant tissue, as quantified by the ratio of mean absolute deviation (RMAD) of the high frequency component. Statistical analysis revealed that the RMAD ratios were significantly different in tumor vs noncancerous masses (p ≪ 0.01). For tissue texture parameters, energy and correlation were found to statistically correlate with the tissue types. A cancer characterization model was developed using the weighted factors to differentiate the tumor from the benign mass. Trade-off between sensitivity and specificity was obtained by varying the threshold value that estimated the upper-bound of the cancer output factor, from which the receiver-operating characteristic (ROC) curve was generated. The characterization model was optimized using ten modeling datasets and verified using another ten validation datasets randomly generated from the database. The optimization results show that an AUC of 0.93 can be achieved. With threshold 0.3, sensitivity of 96.0%, specificity of 84.1%, and negative predictive value (NPV) of 97.3% can be achieved.

CONCLUSIONS

The feasibility of the multimodal system in characterizing breast cancer vs benign mass is established.

Needle-tissue interaction forces--a survey of experimental data

The development of needles, needle-insertion simulators, and needle-wielding robots for use in a clinical environment depends on a thorough understanding of the mechanics of needle-tissue interaction. It stands to reason that the forces arising from this interaction are influenced by numerous factors, such as needle type, insertion speed, and tissue characteristics. However, exactly how these factors influence the force is not clear. For this reason, the influence of various factors on needle insertion-force was investigated by searching literature for experimental data. This resulted in a comprehensive overview of experimental insertion-force data available in the literature, grouped by factor for quick reference. In total, 99 papers presenting such force data were found, with typical peak forces in the order of 1-10N. The data suggest, for example, that higher velocity tends to decrease puncture force and increase friction. Furthermore, increased needle diameter was found to increase peak forces, and conical needles were found to create higher peak forces than beveled needles. However, many questions remain open for investigation, especially those concerning the influence of tissue characteristics.

Feasibility Study of an Optically Actuated MR-compatible Active Needle

An active needle is proposed for the development of MRI guided percutaneous procedures. The needle uses internal laser heating, conducted via optical fibers, of a shape memory alloy (SMA) actuator to produce bending in the distal section of the needle. Active bending of the needle as it is inserted allows it to reach small targets while overcoming the effects of interactions with surrounding tissue, which can otherwise deflect the needle away from its ideal path. The active section is designed to bend preferentially in one direction under actuation, and is also made from SMA for its combination of MR and bio-compatibility and its superelastic bending properties. A prototype, with a size equivalent to standard 16G biopsy needle, exhibits significant bending with a tip rotation of more than 10°. A numerical analysis and experiments provide information concerning the required amount of heating and guidance for design of efficient optical heating systems.