Ultrasound Based Viscoelasticity Imaging Tool for Differentiation of Breast Lesions

Abstract

Nearly 90% of women called back after a suspicious mammogram do not have breast cancer, yet false positives lead to unnecessary biopsies, psychological distress, additional healthcare visits, and significant financial costs. The authors present an in-clinic compression device compatible with commercial ultrasound systems, utilizing Sub-Hertz Analysis of Visco-Elasticity (SAVE) to assess tissue viscoelasticity as a biomarker for malignancy. SAVE combines ultrasound imaging with a computer-controlled axial compression device to measure viscoelastic parameters, improving diagnostic accuracy and reducing subjectivity. The device integrates mechanical, electrical, and software components into a user-friendly tool, automating the SAVE method. Initial tests with breast phantoms showed strong agreement with a standard mechanical testing instrument, demonstrating high accuracy in key parameters such as the primary time constant, T₁ (mean absolute error: 5.78%). These results underscore the device's potential for accurate measurement of viscoelastic parameters of tissue with the goal of characterizing breast masses in vivo.

I. Introduction

Breast cancer is the most common malignancy (excluding skin cancers) and the second leading cause of cancer-related deaths among women in the U.S. [1]. Statistically, 13% of women in the U.S. will develop breast cancer over their lifetime [2]. Early diagnosis is critical for favorable clinical outcomes, often beginning with screening mammography to identify abnormalities, followed by follow-on diagnostics if necessary. However, while mammography has proven effective in detecting early-stage cancers and reducing mortality at the population level, its limitations as a screening tool in patients with dense breast are increasingly evident.

One of the primary challenges with mammography is its high false-positive rate. Approximately 90% of women called back for additional testing after a suspicious mammogram do not have cancer, and over a 10-year period, 60% of women undergoing mammography experience at least one false-positive result [3,4]. Follow-on imaging modalities, such as diagnostic mammography, ultrasound, and magnetic resonance imaging (MRI), are often employed to clarify these initial findings [5]. Despite these additional diagnostic steps, women with suspicious findings are frequently referred for biopsies, with over 50% of these procedures yielding negative results according to the National Cancer Institute in the USA. [6]. False positives not only result in unnecessary biopsies but also impose psychological distress, additional healthcare visits, physical discomfort, and significant financial costs. The annual expense of unnecessary breast biopsies alone exceeds $2.18 billion, and when follow-on diagnostics are included, the cost of breast cancer over-diagnosis rises to $4 billion annually [3], [7]. Women who experience a false-positive result often endure heightened anxiety and distress, with studies indicating that they are twice as likely to experience anxiety about breast cancer compared to women with true-negative results [8-10].

The limitations of existing diagnostic imaging technologies contribute to these challenges. Current techniques such as mammography, ultrasound, and MRI exhibit suboptimal sensitivity and specificity, particularly in women with dense fibroglandular breast tissue, where masking of cancers is more likely. While MRI offers high sensitivity, its high false-positive rate and cost make it an impractical routine diagnostic tool [11].

Ultrasound imaging, a widely used diagnostic tool, is relatively inexpensive, safe, and non-invasive, offering the advantage of no radiation exposure [12]. It is frequently employed to assess abnormalities detected on mammography or physical examination, helping to differentiate between solid masses and fluid-filled cysts [13]. However, like other modalities, conventional ultrasound is hindered by a high false-positive rate. New diagnostic methods that leverage advanced techniques such as elastography have shown promise in addressing these limitations [14].

Elastography, which estimates tissue stiffness, builds on the clinical observation that many malignant lesions present as stiff, solid masses [15,16]. Among these techniques, ultrasound shear wave elastography (SWE) has demonstrated potential by providing tissue stiffness information in terms of kilopascals (kPa). However, its ability to predict a wide range of pathologies is limited due to the complex biomechanics of breast tissue. The viscoelastic nature of tissue, characterized by its biphasic properties resulting from its high water content, requires a more comprehensive model to capture these biomechanical interactions [17].

Research at the Mayo Clinic, led by Drs. Fatemi and Alizad, has developed Sub-Hertz Analysis of Visco-Elasticity (SAVE), a novel diagnostic technique for differentiating benign and malignant breast lesions. By measuring tissue viscoelasticity at sub-Hertz frequencies, SAVE provides biomechanical insights beyond current elastography methods [18]. Early studies show viscoelastic time constants as effective biomarkers for malignancy [19]. SAVE integrates ultrasound imaging with a computer-controlled axial compression device to automate tissue measurement, viscoelastic mapping, and contrast calculation, reducing subjectivity and improving accuracy. Studies at the Mayo Clinic demonstrated a 77.8% sensitivity and 96.3% specificity in discerning between benign and malignment breast tumors when BIRADS and lesion size were included alongside viscoelasticity parameter in a multivariable logic regression model [20]. This integration further enhances overall diagnostic accuracy, providing physicians with greater precision in tumor classification [17].

The design and testing presented in this paper highlight the development and validation of a novel compression device for in-clinic breast lesion assessment. The device is engineered for future compatibility with commercial ultrasound systems and designed to accommodate a lockable, multi-axis positioning arm for implementing the SAVE method in the clinical settings. This work demonstrates the feasibility of integrating mechanical, electrical, and software components into a user-friendly tool capable of generating reliable viscoelastic measurements.

II. Compression Device Design

A. Mechanical Design

To accurately measure the viscoelastic properties of soft tissues, a prototype force-controlled axial compression device was developed, (Fig. 1 and 2). Designed with both clinician and patients in mind, the viscoelasticity measurement tool prioritizing user-friendliness, portability, and integration with existing ultrasound equipment, enabling its incorporation into clinical workflows. The design includes a fixed frame supporting an ultrasonic probe, which images tissue phantoms while a controlled force profile is applied.

Figure 1.

Schematic of Prototype Compression Device for Testing

Figure 2.

Illustration of the clinical-use compression device, showcasing prototyped components developed in this work.

Mimicking standard mechanical testing instruments (SMTIs), commonly used in materials science, where high-speed ramp functions are used to approximate theoretical step stress for creep tests, our device employs a similar high-speed ramp function (at least 16N/s ramp and up to 8N programmable hold force), optimized for real-time tissue evaluation. These ramp functions must be fast enough to capture the material's shortest retardation times. A key innovation is the free-floating tissue interface (FFTI), a lightweight, skeletonized frame with an open window. This FFTI decouples the ultrasonic probe from the motion system, ensuring the probe does not directly compress the tissue. This maintains a 1mm gel interface for imaging accuracy while minimizing pre-compression forces from the FFTI’s weight and momentum.

The ultrasonic probe and a load cell printed circuit board (PCB) are mounted on a sliding structure driven by a brushless DC motor (BLDC, ElectroCraft Inc., RP17M-16V24-100-D) and a ball-screw linear motion stage (PBC Linear, CSBSM08AGXR1ZF-1LN-0160-0). These components are securely housed within a custom-machined frame to ensure precise alignment, minimal deflection, and reliable operation. The FFTI itself is a lightweight structure fabricated using 3D printing technology, designed for minimal mass and quick detachment. This modularity simplifies cleaning, allows for easy reapplication of ultrasonic gel, and reduces maintenance time, enhancing the device’s overall clinical practicality.

Force applied to the FFTI is measured through load cells on the load-cell PCB, capturing the combined force exerted by the motion control system. However, the force applied to the tissue also accounts for the FFTI's weight and momentum. To prevent unintended pre-compression of the tissue, it was crucial to minimize the FFTI's mass. This design ensure that the device applies a precise and controlled force ramp without significant interference from the FFTI’s own weight or inertia.

B. Electronic Architecture

The electronic architecture of the compression device is centered on two custom-designed PCBs that manage communication, power conversion, manage the force-controlled loop and measurement, and motion control. The control board, powered by a medical-grade 24V power supply, oversees system functionality through an STM32G431 microcontroller. Key features of the control board include:

• An electrically isolated USB interface to simplify IEC 60601-1 compliance.

• GlobTek, Inc. TR9CI6666CCPCIMR6B 24V medical-grade AC to DC power supply directly supplies the Brushless DC motor as well as various voltage rails for system components and the load cell daughter board.

• A brushless DC motor driver circuit utilizing six MOSFETs resistors with corresponding gate drivers, supporting various motor control algorithms and encoder schemes.

• A Texas Instruments (TI) SN65LVDT41 robust low-voltage differential signaling (LVDS) interface for Serial Peripheral Interface (SPI) communication with the daughter load cell board analog-to-digital converter (ADC).

• Serial Wire Debug (SWD) debugging interface.

The load cell board (Fig 3) is connected to the control board using 3M 1700 series twisted pair ribbon cable with insulation displacement connectors and employs a MAX11254 24-bit, 6-channel, 64 ksps sigma-delta ADC with Programmable Gain Amplifier (PGA) for high-resolution force measurements, supported by:

Figure 3.

Physical Layout of Load Cell Board Configuration

• 4 Honeywell FSS015WNGR load cells for precise force detection.

• 4.096V precision reference voltage supply for energizing load cells.

• TI, SN65LVDT14 LVDS interface to ADC SPI output for communication with the control board.

C. Force Control Loop

The four load cells were read with a 24-bit resolution at a sampling rate of 1000 Hz using the MAX11254 and transmitted to the microcontroller unit (MCU) for processing. The MCU calculated the total force applied to the FFTI by summing the values from all load cells. A proportional-integral-derivative (PID) controller was implemented to maintain the desired force by dynamically adjusting the motor's speed and direction. The PID loop was carefully tuned to minimize force oscillations and enable smooth ramping to the target force at an appropriate rate.

Motor speed control was achieved using a six-step trapezoidal motion control algorithm, which adjusted the pulse-width modulation (PWM) frequency of the motor’s three coils to set the rotor angle. The angular position of the motor, combined with the pitch of the ball-screw linear slide, was used to calculate tissue displacement during force application to the FFTI. While the six-step trapezoidal algorithm provided adequate performance for the force control loop, a higher-performance field-oriented control (FOC) algorithm could be explored in future iterations to enhance responsiveness and optimize power consumption in the motor positioning system.

D. User Interface

A PC application was developed to interface with the control board via an isolated Universal Serial Bus (USB) connection, enabling experiment setup, motor homing, experiment initiation, and real-time visualization of force-displacement curves. The Graphical User Interface (GUI) allows users to configure parameters such as force set point, duration, and PID control constants, while displaying load cell forces and overall force-displacement behavior. The device uses Universal Asynchronous Receiver-Transmitter (UART) communication for control and data acquisition. Through UART commands, users can configure loop parameters, adjust motor values, target forces, and positional gains, as well as initiate measurements, control motor movement, and stream raw sensor data in real time.

Data packets, transmitted in a binary format, encapsulate raw sensor data, including multi-channel force measurements, positional data, and timestamps accurate to the nearest millisecond. This structure ensures efficient storage and transmission of large datasets while enabling precise synchronization of data with specific events during experiments. The binary format also facilitates compatibility with analysis tools, allowing one to derive meaningful insights into material viscoelasticity. The implementation of the UART communication system and structured data format has significantly enhanced the device's usability and data integrity. Remote control capabilities, high-resolution real-time data acquisition, and standardized data formatting have streamlined operations, improved accuracy, and facilitated integration with analysis and visualization tools.

Performance testing confirmed the device's capability to achieve feasibility goals. The system demonstrated a ramp and hold force of up to 8 Newtons (N), with a maximum ramp rate of 16 N per second (N/s) and hold times exceeding 20 seconds. During testing, an average ramp rate of 27.9 N/s from 0 to 0.250 seconds was achieved, with consistent 8 N force holds maintained for 60 seconds.

III. Validate the viscoelastic characterization of the compression device

Accurate tissue viscoelasticity measurement is essential for the compression diagnostic tool's functionality. Validation was conducted by comparing the device's performance against a standard mechanical testing instrument (SMTI) (Bose ElectroForce, Eden Prairie, MN, USA) using a gelatin phantom prepared with an established recipe [19].

Viscoelastic parameters estimated using Equation (1), where $\mathrm{d}(\mathrm{t})$ is the time-dependent displacement, ${\mathrm{d}}_0$ represents purely elastic displacement, ${\mathrm{d}}_1$ and ${\mathrm{d}}_2$ are the displacement amplitudes corresponding to the first and second retardation times ${\mathrm{T}}_1$ and ${\mathrm{T}}_2$. For the purpose of comparison, we only consider the parameters ${\mathrm{T}}_1$ and ${\mathrm{T}}_2$. Note that in the above equation, we are assuming infinitesimal strain so that the relationship between strain and displacement is linear (i.e. the time-dependent strain ε(t) is related to the displacement by the scaling of the length of the sample L as ε(t)=d(t)/L) [18].

$$d(t)=d_0+d_1\left(1-\text{exp}\left(-\frac{t}{T_1}\right)\right)+d_2\left(1-\text{exp}\left(-\frac{t}{T_2}\right)\right)$$ (1)

Ultrasound imaging was integrated using a research-grade system (Vantage 256, Verasonics Inc., Kirkland, WA, USA) and a linear array transducer (L11-5, Phillips Healthcare, Bothell, WA, USA). B-mode images before and after compression showed expected compression of the phantom.

Validation results demonstrated strong agreement between the creep response obtained by the compression device and SMTI, with a mean absolute error of 5.78% for ${\mathrm{T}}_1$ and 13.95% for ${\mathrm{T}}_2$. As ${\mathrm{T}}_1$ is the primary parameter for viscoelasticity estimation, these results confirm the device's ability to accurately characterize the creep response and the viscoelastic properties, supporting its potential for diagnostic applications, (Fig 4). These findings strongly establish the potential for accurate and practical viscoelastic characterization of breast tissues, supporting its potential for clinical use in differentiating benign and malignant lesions.

Figure 4.

Measurements (blue for SMTI and purple for compression device) and fitted curves (red and orange) of the viscoelastic creep measurement collected from the device and the SMTI.

IV. Conclusion

This work presents the development and validation of a novel, force-controlled compression device designed to facilitate the clinical implementation of the Sub-Hertz Analysis of Visco-Elasticity (SAVE) method for breast lesion assessment. By integrating mechanical, electrical, and software components into a compact, user-friendly system, the device enables accurate and reproducible measurement of tissue viscoelasticity. Validation against a standard mechanical testing instrument demonstrated high accuracy, particularly in estimating the primary viscoelastic parameter, T1. These results support the feasibility of the device for in-clinic use and highlight its potential to improve diagnostic specificity, reduce false positives, and enhance the overall breast cancer diagnostic workflow.

Clinical Relevance—

This novel compression device, facilitates the accurate application of SAVE method for in-clinic breast lesion assessment, aiming to improve specificity and reduces false positives. Its integration with standard ultrasound systems provides a cost-effective, non-invasive method to distinguish benign from malignant lesions, reducing unnecessary biopsies and patient anxiety. This advancement has the potential to enhance diagnostic workflows and patient care.