Histology-based simulations for the ultrasonic detection of microscopic cancer in vivo

High-Frequency Ultrasonic Forceps for the In Vivo Detection of Cancer During Breast-Conserving Surgery

A major aim in the surgical management of soft tissue cancers is to detect and remove all cancerous tissues while ensuring noncancerous tissue remains intact. Breast-conserving surgery provides a prime illustration of this aim, since remaining cancer in breast margins results in multiple surgeries, while removal of too much unaffected tissue often has undesirable cosmetic effects. Similarly, resection of benign lymph nodes during sentinel lymph node biopsy can cause deleterious health outcomes. The objective of this study was to create an intraoperative, in vivo device to address these challenges. Instant diagnostic information generated by this device could allow surgeons to precisely and completely remove all malignant tissue during the first surgery. Surgical forceps based on Martin forceps were instrumented at the tips with high-frequency ultrasonic transducers composed of polyvinylidene difluoride, a thickness-sensing rotary potentiometer at the base, and a spring to provide the appropriate restoring force. Transducer wires within the forceps were connected to an external high-frequency pulser-receiver, activating the forceps' transmitting transducer at 50 MHz and amplifying through-transmission signals from the receiving transducer. The forceps were tested with tissue-mimicking agarose phantoms embedded with 58–550 μm polyethylene microspheres to simulate various stages of cancer progression and to provide a range of measurement values. Results were compared with measurements from standard 50 MHz immersion transducers. The results showed that the forceps displayed similar sensitivity for attenuation and increased accuracy for wave speed. The forceps could also be extended to endoscopes and laparoscopes.

B-mode ultrasound for the assessment of hepatic fibrosis: a quantitative multiparametric analysis for a radiomics approach

Hepatic fibrosis and cirrhosis are a growing global health problem with increasing mortality rates. Early diagnosis and staging of hepatic fibrosis represent a major challenge. Currently liver biopsy is the gold standard for fibrosis assessment; however, biopsy requires an invasive procedure and is prone to sampling error and reader variability. In the current study we investigate using quantitative analysis of computer-extracted features of B-mode ultrasound as a non-invasive tool to characterize hepatic fibrosis. Twenty-two rats were administered diethylnitrosamine (DEN) orally for 12 weeks to induce hepatic fibrosis. Four control rats did not receive DEN. B-mode ultrasound scans sampling throughout the liver were acquired at baseline, 10, and 13 weeks. Computer extracted quantitative parameters representing brightness (echointensity, hepatorenal index) and variance (heterogeneity, anisotropy) of the liver were studied. DEN rats showed an increase in echointensity from 37.1 ± SD 7.8 to 53.5 ± 5.7 (10 w) to 57.5 ± 6.1 (13 w), while the control group remained unchanged at an average of 34.5 ± 4.5. The three other features studied increased similarly over time in the DEN group. Histologic analysis showed METAVIR fibrosis grades of F2-F4 in DEN rats and F0-F1 in controls. Increasing imaging parameters correlated with increasing METAVIR grades, and anisotropy showed the strongest correlation (ρ = 0.58). Sonographic parameters combined using multiparametric logistic regression were able to differentiate between clinically significant and insignificant fibrosis. Quantitative B-mode ultrasound imaging can be implemented in clinical settings as an accurate non-invasive tool for fibrosis assessment.

Investigation of Physical Phenomena Underlying Temporal-Enhanced Ultrasound as a New Diagnostic Imaging Technique: Theory and Simulations

Temporal-enhanced ultrasound (TeUS) is a novel noninvasive imaging paradigm that captures information from a temporal sequence of backscattered US radio frequency data obtained from a fixed tissue location. This technology has been shown to be effective for classification of various in vivo and ex vivo tissue types including prostate cancer from benign tissue. Our previous studies have indicated two primary phenomena that influence TeUS: 1) changes in tissue temperature due to acoustic absorption and 2) micro vibrations of tissue due to physiological vibration. In this paper, first, a theoretical formulation for TeUS is presented. Next, a series of simulations are carried out to investigate micro vibration as a source of tissue characterizing information in TeUS. The simulations include finite element modeling of micro vibration in synthetic phantoms, followed by US image generation during TeUS imaging. The simulations are performed on two media, a sparse array of scatterers and a medium with pathology mimicking scatterers that match nuclei distribution extracted from a prostate digital pathology data set. Statistical analysis of the simulated TeUS data shows its ability to accurately classify tissue types. Our experiments suggest that TeUS can capture the microstructural differences, including scatterer density, in tissues as they react to micro vibrations.

Experimental assessment of four ultrasound scattering models for characterizing concentrated tissue-mimicking phantoms

Tissue-mimicking phantoms with high scatterer concentrations were examined using quantitative ultrasound techniques based on four scattering models: The Gaussian model (GM), the Faran model (FM), the structure factor model (SFM), and the particle model (PM). Experiments were conducted using 10- and 17.5-MHz focused transducers on tissue-mimicking phantoms with scatterer concentrations ranging from 1% to 25%. Theoretical backscatter coefficients (BSCs) were first compared with the experimentally measured BSCs in the forward problem framework. The measured BSC versus scatterer concentration relationship was predicted satisfactorily by the SFM and the PM. The FM and the PM overestimated the BSC magnitude at actual concentrations greater than 2.5% and 10%, respectively. The SFM was the model that better matched the BSC magnitude at all the scatterer concentrations tested. Second, the four scattering models were compared in the inverse problem framework to estimate the scatterer size and concentration from the experimentally measured BSCs. The FM did not predict the concentration accurately at actual concentrations greater than 12.5%. The SFM and PM need to be associated with another quantitative parameter to differentiate between low and high concentrations. In that case, the SFM predicted the concentration satisfactorily with relative errors below 38% at actual concentrations ranging from 10% to 25%.

High-frequency ultrasound for intraoperative margin assessments in breast conservation surgery: a feasibility study

Background

In addition to breast imaging, ultrasound offers the potential for characterizing and distinguishing between benign and malignant breast tissues due to their different microstructures and material properties. The aim of this study was to determine if high-frequency ultrasound (20-80 MHz) can provide pathology sensitive measurements for the ex vivo detection of cancer in margins during breast conservation surgery.

Methods

Ultrasonic tests were performed on resected margins and other tissues obtained from 17 patients, resulting in 34 specimens that were classified into 15 pathology categories. Pulse-echo and through-transmission measurements were acquired from a total of 57 sites on the specimens using two single-element 50-MHz transducers. Ultrasonic attenuation and sound speed were obtained from time-domain waveforms. The waveforms were further processed with fast Fourier transforms to provide ultrasonic spectra and cepstra. The ultrasonic measurements and pathology types were analyzed for correlations. The specimens were additionally re-classified into five pathology types to determine specificity and sensitivity values.

Results

The density of peaks in the ultrasonic spectra, a measure of spectral structure, showed significantly higher values for carcinomas and precancerous pathologies such as atypical ductal hyperplasia than for normal tissue. The slopes of the cepstra for non-malignant pathologies displayed significantly greater values that differentiated them from the normal and malignant tissues. The attenuation coefficients were sensitive to fat necrosis, fibroadenoma, and invasive lobular carcinoma. Specificities and sensitivities for differentiating pathologies from normal tissue were 100% and 86% for lobular carcinomas, 100% and 74% for ductal carcinomas, 80% and 82% for benign pathologies, and 80% and 100% for fat necrosis and adenomas. Specificities and sensitivities were also determined for differentiating each pathology type from the other four using a multivariate analysis. The results yielded specificities and sensitivities of 85% and 86% for lobular carcinomas, 85% and 74% for ductal carcinomas, 100% and 61% for benign pathologies, 84% and 100% for fat necrosis and adenomas, and 98% and 80% for normal tissue.

Conclusions

Results from high-frequency ultrasonic measurements of human breast tissue specimens indicate that characteristics in the ultrasonic attenuation, spectra, and cepstra can be used to differentiate between normal, benign, and malignant breast pathologies.

Ultrasonic differentiation of normal versus malignant breast epithelial cells in monolayer cultures

Normal and malignant mammary epithelial cells were studied using laboratory measurements, wavelet analysis, and numerical simulations of monolayer cell cultures to determine whether microscopic breast cancer can be detected in vitro with high-frequency ultrasound. Pulse-echo waveforms were acquired by immersing a broadband, unfocused 50-MHz transducer in the growth media of cell culture well plates and collecting the first reflection from the well bottoms. The simulations included a multilayer pulse-reflection model and a model of two-dimensional arrays of spherical cells and nuclei. The results show that normal and malignant cells produce time-domain signals and spectral features that are significantly different.

Stochastic modeling of normal and tumor tissue microstructure for high-frequency ultrasound imaging simulations

High-frequency (20-60 MHz) ultrasound images of preclinical tumor models are sensitive to changes in tissue microstructure that accompany tumor progression and treatment responses, but the relationships between tumor microanatomy and high-frequency ultrasound backscattering are incompletely understood. This paper introduces a 3-D microanatomical model in which tissue is treated as a population of stochastically positioned spherical cells consisting of a spherical nucleus surrounded by homogeneous cytoplasm. The model is used to represent the microstructure of both healthy mouse liver and an experimental liver metastasis that are analyzed using 4 ',6-diamidino-2-phenylindole- and hematoxylin and eosin-stained histology specimens digitized at 20 x magnification. The spatial organization of cells is controlled in the model by a Gibbs-Markov point process whose parameters are tuned to maximize the similarity of experimental and simulated tissue microstructure, which is characterized using three descriptors of nuclear spatial arrangement adopted from materials science. The model can accurately reproduce the microstructure of the relatively homogeneous healthy liver and the average cell clustering observed in the experimental metastasis, but is less effective at reproducing the spatial heterogeneity of the experimental metastasis. The model provides a framework for computational investigations of the effects of individual microstructural and acoustic properties on high-frequency backscattering.

Simulation of elastic wave scattering in cells and tissues at the microscopic level

The scattering of longitudinal and shear waves from spherical, nucleated cells and three-dimensional tissues with simple and hierarchical microstructures was numerically modeled at the microscopic level using an iterative multipole approach. The cells were modeled with a concentric core-shell (nucleus-cytoplasm) structure embedded in an extracellular matrix. Using vector multipole expansions and boundary conditions, scattering solutions were derived for single cells with either solid or fluid properties for each of the cell components. Tissues were modeled as structured packings of cells. Multiple scattering between cells was simulated using addition theorems to translate the multipole fields from cell to cell in an iterative process. Backscattering simulations of single cells indicated that changes in the shear properties and nuclear diameter had the greatest effect on the frequency spectra. Simulated wave field images and high-frequency spectra (15-75 MHz) from tissues containing 1211-2137 cells exhibited up to 20% enhancement of the field amplitudes at the plasma membrane, significant changes in spectral features due to neoplastic and other microstructural alterations, and a detection threshold of approximately 8.5% infiltration of tumor cells into normal tissue. These findings suggest that histology-based simulations may provide insight into fundamental ultrasound-tissue interactions and help in the development of new medical technologies.