Three-dimensional high-frequency characterization of cancerous lymph nodes

Electrical lymph node scanning (ELS) system for real-time intra-operative detection of involved axillary lymph nodes in adjuvant breast cancer patients

Lymph node (LN) status is an essential prognostic factor in breast cancer (BC) patients, with an important role in the surgical and therapeutic plan. Recently, we have been developed a novel system for real-time intra-operative electrical LN scanning in BC patients. The ELS scores were calibrated by pathological evaluation of the LNs. Herein, we evaluated the efficacy of ELS in a prospective study for non-chemo-treated breast cancer patients. This is a prospective study in which ELS scores are blind for pathologists who declare the clearance or involvement of LNs based on permanent pathology as the gold standard. ELS and frozen-section (FS) pathology results were achieved intra-operatively, and samples were sent for the permanent pathology. The score of ELS did not affect the surgeons' decision, and the treatment approach was carried out based on FS pathology and pre-surgical data, such as imaging and probable biopsies. Patients were recruited from October 2021 through November 2022, and 381 lymph nodes of 97 patients were included in the study. In this study we recruited 38 patients (39.2%) with sentinel lymph node biopsy (SLNB) and 59 patients (60.8%) with ALND. Of the 381 LNs scored by ELS, 329 sentinel LNs underwent routine pathology, while others (n = 52) underwent both FS and permanent pathology. ELS showed a sensitivity of 91.4% for node-positive patients, decreasing to 84.8% when considering all LNs. Using ROC analysis, ELS diagnosis showed a significant AUC of 0.878 in relation to the permanent pathology gold standard. Comparison of ELS diagnosis for different tumor types and LN sizes demonstrated no significant differences, while increasing LN size correlated with enhanced ELS sensitivity. This study confirmed ELS's efficacy in real-time lymph node detection among non-chemo-treated breast cancer patients. The use of ELS's pathological scoring for intra-operative LN diagnosis, especially in the absence of FS pathology or for non-sentinel LN involvement, could improve prognosis and reduce complications by minimizing unnecessary dissection.

Relationship between transmission/reception conditions of high-frequency plane wave compounding and evaluation accuracy of extended amplitude envelope statistics

The double-Nakagami (DN) model provides a method for analyzing the amplitude envelope statistics of quantitative ultrasound (QUS). In this study, the relationship between the sound field characteristics and the robustness of QUS evaluation was evaluated using five HF linear array probes and tissue-mimicking phantoms. Compound plane-wave imaging (CPWI) was used to acquire echo data. Five phantoms containing two types of scatterers were used to mimic fatty liver tissue. After clarifying the relationship between the sound field characteristics of the probes and QUS parameters, DN QUS parameters in 10 rat livers with different lipidification were evaluated using one HF linear array probe. For both phantom and in situ liver analyses, correlations between fat content and multiple QUS parameters were confirmed, suggesting that the combination of CPWI using a HF linear array probe with the DN model is a robust method for quantifying fatty liver and has potential clinical diagnostic applications.

Cancer characterization using light backscattering spectroscopy and quantitative ultrasound: an ex vivo study on sarcoma subtypes

Histological analysis is the gold standard method for cancer diagnosis. However, it is prone to subjectivity and sampling bias. In response to these limitations, we introduce a quantitative bimodal approach that aims to provide non-invasive guidance towards suspicious regions. Light backscattering spectroscopy and quantitative ultrasound techniques were combined to characterize two different bone tumor types from animal models: chondrosarcomas and osteosarcomas. Two different cell lines were used to induce osteosarcoma growth. Histological analyses were conducted to serve as references. Three ultrasound parameters and intensities of the light reflectance profiles showed significant differences between chondrosarcomas and osteosarcomas at the 5% level. Likewise, variations in the same biomarkers were reported for the two types of osteosarcoma, despite their similar morphology observed in the histological examinations. These observations show the sensitivity of our techniques in probing fine tissue properties. Secondly, the ultrasound spectral-based technique identified the mean size of chondrosarcoma cells and nuclei with relative errors of about 22% and 9% respectively. The optical equivalent technique correctly extracted scatterer size distributions that encompass nuclei and cells for chondrosarcomas and osteosarcomas ([Formula: see text] and [Formula: see text] respectively). The optical scattering contributions of nuclei were estimated at 52% for the chondrosarcomas and 69% for the osteosarcomas, probably indicating the abundant and the absent extracellular matrix respectively. Thus, the ultrasound and the optical methods brought complementary parameters. They successfully estimated morphological parameters at the cellular and the nuclear scales, making our bimodal technique promising for tumor characterization.

High-frequency ultrasound point-of-care device to quantify myopia-induced microstructural changes in the anterior sclera

PURPOSE

To develop a point-of-care (POC) device using high-frequency ultrasound (US) for evaluating microstructural changes in the anterior sclera associated with myopia.

METHODS

The proposed POC device must satisfy four primary requirements for effective clinical use: the measurement component is handheld; the software must be simple and provide real-time feedback; patient safety and health data security requirements set forth by relevant governing bodies must be satisfied and the measurement data must have sufficient signal-to-noise ratio (SNR) and repeatability. Radiofrequency (RF) echo data acquired by the POC device will be processed using our quantitative US methods to characterise tissue microstructure and biomechanical properties.

RESULTS

All stated requirements have been met in the developed POC device. The high-frequency transducer is housed in a custom, 3D-printed, pen-like holder that allows for easy measurements of the anterior sclera. Custom software provides a simple interface for data acquisition, real-time data display and secure data storage. Exposimetry measurements of the US pressure field indicate device compliance with United States Food and Drug Administration limits for ophthalmic US. In vivo measurements on a volunteer suggest the RF data SNR and acquisition consistency are suitable for quantitative analysis.

CONCLUSIONS

A fully functioning POC device using high-frequency US has been created for evaluating the microstructure of the anterior sclera. Planned studies using the POC device to scan the eyes of myopia patients will help clarify how the anterior sclera microstructure may be affected by myopia. If effective, this portable, inexpensive and user-friendly system could be an important part of routine eye examinations.

Classification of Metastatic Lymph Nodes In Vivo Using Quantitative Ultrasound at Clinical Frequencies

Quantitative ultrasound (QUS) methods characterizing the backscattered echo signal have been of use in assessing tissue microstructure. High-frequency (30 MHz) QUS methods have been successful in detecting metastases in surgically excised lymph nodes (LNs), but limited evidence exists regarding the efficacy of QUS for evaluating LNs in vivo at clinical frequencies (2-10 MHz). In this study, a clinical scanner and 10-MHz linear probe were used to collect radiofrequency (RF) echo data of LNs in vivo from 19 cancer patients. QUS methods were applied to estimate parameters derived from the backscatter coefficient (BSC) and statistics of the envelope-detected RF signal. QUS parameters were used to train classifiers based on linear discriminant analysis (LDA) and support vector machines (SVMs). Two BSC-based parameters, scatterer diameter and acoustic concentration, were the most effective for accurately detecting metastatic LNs, with both LDA and SVMs achieving areas under the receiver operating characteristic (AUROC) curve ≥0.94. A strategy of classifying LNs based on the echo frame with the highest cancer probability improved performance to 88% specificity at 100% sensitivity (AUROC = 0.99). These results provide encouraging evidence that QUS applied at clinical frequencies may be effective at accurately identifying metastatic LNs in vivo, helping in diagnosis while reducing unnecessary biopsies and surgical treatments.

Implementation of Non-Invasive Quantitative Ultrasound in Clinical Cancer Imaging

Quantitative ultrasound (QUS) is a non-invasive novel technique that allows treatment response monitoring. Studies have shown that QUS backscatter variables strongly correlate with changes observed microscopically. Increases in cell death result in significant alterations in ultrasound backscatter parameters. In particular, the parameters related to scatterer size and scatterer concentration tend to increase in relation to cell death. The use of QUS in monitoring tumor response has been discussed in several preclinical and clinical studies. Most of the preclinical studies have utilized QUS for evaluating cell death response by differentiating between viable cells and dead cells. In addition, clinical studies have incorporated QUS mostly for tissue characterization, including classifying benign versus malignant breast lesions, as well as responder versus non-responder patients. In this review, we highlight some of the important findings of previous preclinical and clinical studies and expand the applicability and therapeutic benefits of QUS in clinical settings. We summarized some recent clinical research advances in ultrasound-based radiomics analysis for monitoring and predicting treatment response and characterizing benign and malignant breast lesions. We also discuss current challenges, limitations, and future prospects of QUS-radiomics.

Machine learning-enabled quantitative ultrasound techniques for tissue differentiation

PURPOSE

Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for tissue differentiation.

METHODS

This study first validated chicken liver and gizzard muscle as suitable acoustic phantoms for human brain and brain tumour tissues via measurement of the speed of sound and acoustic attenuation. A total of thirteen QUS parameters were estimated from twelve samples, each using data obtained with a transducer with a frequency of 5-11 MHz. Spectral parameters, i.e., effective scatterer diameter and acoustic concentration, were calculated from the backscattered power spectrum of the tissue, and echo envelope statistics were estimated by modelling the scattering inside the tissue as a homodyned K-distribution, yielding the scatterer clustering parameter α and the structure parameter κ. Standard deviation and higher-order moments were calculated from the echogenicity value assigned in conventional B-mode images.

RESULTS

The k-nearest neighbours algorithm was used to combine those parameters, which achieved 94.5% accuracy and 0.933 F1-score.

CONCLUSION

We were able to generate classification parametric images in near-real-time speed as a potential diagnostic tool in the operating room for the possible use for human brain tissue characterisation.

Intraoperative pathologically-calibrated diagnosis of lymph nodes involved by breast cancer cells based on electrical impedance spectroscopy; a prospective diagnostic human model study

BACKGROUND

Nodal status evaluation is a crucial step in determining prognostic factors and managing treatment strategies for breast cancer patients. Preoperative (CNB), intraoperative (SLNB), and even postoperative techniques (Formalin-Fixed Paraffin-Embedded sectioning, FFPE) have definite limitations of precision or sometimes are time-consuming for the result declaration. The primary purpose of this prospective study is to provide a precise complementary system for distinguishing lymph nodes (LNs) involved by cancerous cells in breast cancer patients intraoperatively.

METHODS

The proposed system, Electrical Lymph Scoring(ELS), is designed based on the dielectric properties of the under-test LNs. The system has a needle-shaped 2-electrode probe entered into SLNs or ALNs dissected from patients through standard surgical guidelines. Impedance magnitude in f = 1 kH (Z_1kHz) and Impedance Phase Slope in frequency ranges of 100 kHz-500 kHz (IPS) were then extracted from the impedance spectroscopy data in a cohort study of 77 breast cancer patients(totally 282 dissected LNs) who had been undergone surgery before (n = 55) or after (n = 22) chemical therapies (non-neoadjuvant or neoadjuvant chemotherapy). A new admittance parameter(Y_n^') also proposed for LN detection in neoadjuvant chemotherapy patients.

RESULTS

Considering the permanent pathology result as the gold standard checked by two independent expert pathologists, a significant correlation was observed between the presence of cancerous cells in LNs and individual ranges of the ELS electrical responses. Compared with normal LNs containing fatty ambient and immune cells, LNs involved by cancerous clusters would reduce the Z_1kHz and increase the IPS. These changes correlate with fat metabolism by cancer cells due to their Fatty Acid Oxidation (FAO) in LN, which results in different dielectric properties between high and low-fat content of normal and cancerous LNs, respectively.

CONCLUSIONS

By finding the best correlation between our defined impedimetric parameters and pathological states of tested LNs, a real-time intraoperative detection approach was developed for highly-sensitive (92%, P<0.001) diagnosis of involved sentinel or axillary LNs. The impact of real-time intraoperative scoring of SLNs would make a pre-estimation about the necessity of excising further LNs to help the surgeon for less invasive surgery, especially in the absence of frozen-section equipment.

Quantitative characterization of the colorectal cancer in a rabbit model using high-frequency endoscopic ultrasound

PURPOSE

Colonoscopy accompanied with biopsy works as the routine endoscopic strategy for the diagnosis of colorectal cancer (CRC) in clinic; however, the colonoscopy is limited to the tissue surface. During the last decades, enabling technologies are emerging to complement with the colonoscopy for better administration of CRC. The conventional low-frequency (<12 MHz) endoscopic ultrasound (EUS) guided fine-needle aspiration (FNA) has been widely used to assess the lesion penetration. With the high-frequency ultrasound transducer (>20 MHz), EUS allows more precise visualization of the colorectal abnormalities. In order to achieve the accurate detection or in situ characterization of the colorectal lesions, the EUS diagnosis needs more patho-physiological related information in the micro-structural or molecular level. Quantitative ultrasound (QUS) technique, which could extract the micro-structural information from the ultrasound radio-frequency (RF) signal, is promising for the non-invasive tissue characterization. To date, the knowledge of the high-frequency endoscopic QUS for the CRC characterization has not been fully determined.

METHODS

In this work, to our best knowledge, it is the first application of the QUS technique based on a customized high-frequency EUS system (30.5 MHz center frequency) to characterize the colorectal malignancies in a VX2 rabbit CRC model. To eliminate the response from the ultrasound electronic system and transducer, the ultrasound signals from colon tissue were calibrated. And, the resulting quasi-liner ultrasound spectra were fit by the linear regression test. As a result, three spectral parameters, including the slope (k), intercept (I) and Midband Fit (M), were obtained from the best-fit line. The three spectral parameters were compared between the malignant tissue regions and adjacent normal tissue regions of the colon tissue specimen ex vivo. The independent t-test was conducted between the three parameters from the normal and malignant group. The statistical method of Fisher Linear Discriminant (FLD) was used to explore the linear combinations of the three parameters, so as to provide more tissue micro-structural features than the single parameter alone. The three FLD values were derived from three different combinations among k, I and M. The threshold was selected from the statistical analysis to optimize the differentiation criteria between the malignant and the normal tissues. The color-coded images were used to display the local FLD values and combined with the EUS B-mode image.

RESULTS AND CONCLUSIONS

The mean Midband Fit (M) and intercept (I) showed significant differences between the malignant and normal tissue regions. The statistical analysis showed that there were significant differences in all the mean FLD values of the spectral parameter combinations (kI, kM and IM) (t test, P < 0.05). And, the combined image result from the B-mode image and color-coded image could visually correlate with the histology result. In conclusion, the high-frequency endoscopic QUS technique was potential to be used as a complementary method to distinguish the colorectal malignancies by leveraging its morphological and micro-structural ultrasound information.

Improved evaluation of backscatter characteristics of soft tissue using high-frequency annular array

Clinical ultrasound is widely used for quantitative diagnosis. To clarify the relationship between anatomical and acoustic properties, high resolution imaging using high-frequency ultrasound (HFU) is required. However, when tissue properties are evaluated using HFU, the depth of field (DOF) is limited. To overcome this problem, an annular array transducer, which has a simple structure and produces high-quality images, is applied to HFU measurement. In previous phantom experiments, we demonstrated that the HFU annular array extends the DOF compared to that of a single-element transducer for quantitative ultrasound (QUS) analysis. Here, we extend that work by applying QUS methods to an ex vivo rat liver. The present study demonstrates that an annular array extends the region and improves the resolution for tissue characterization for an excised healthy rat liver. Amplitude envelope statistics and spectral-based analysis are used as QUS methods.

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.

Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments

Solid tumors are typically supplied nutrients by a network of irregular blood vessels. By targeting these vascular networks, it might be possible to hinder cancer growth and metastasis. Vascular disrupting agents induce intertumoral hemorrhaging, making photoacoustic (PA) imaging well positioned to detect bleeding due to its sensitivity to hemoglobin and its various states. We introduce a fractal-based numerical model of intertumoral hemorrhaging to simulate the PA signals from disrupted tumor blood vessels. The fractal model uses bifurcated cylinders to represent vascular trees. To mimic bleeding from blood vessels, hemoglobin diffusion from microvessels was simulated. In the simulations, the PA signals were detected by a linear array transducer (30 MHz center frequency) of four different vascular trees. The power spectrum of each beamformed PA signal was computed and fitted to a straight line within the −6-dB bandwidth of the receiving transducer. The spectral slope and midband fit (MBF) based on the fit decreased by 0.11  dB  /  MHz and 2.12 dB, respectively, 1 h post bleeding, while the y-intercept increased by 1.21 dB. The results suggest that spectral PA analysis can be used to measure changes in the concentration and spatial distribution of hemoglobin in tissue without the need to resolve individual vessels. The simulations support the feasibility of using PA imaging and spectral analysis in cancer treatment monitoring by detecting microvessel disruption.

Probing the Cellular Size Distribution in Cell Samples Undergoing Cell Death

A polydisperse scattering model adapted for concentrated medium, namely the polydisperse structure factor model, was examined to explain the backscatter coefficients (BSCs) measured from packed cell samples undergoing cell death. Cell samples were scanned using high-frequency ultrasound in the 10-42 MHz bandwidth. A parameter estimation procedure was proposed to estimate the volume fraction and the relative impedance contrast that could explain the changes in BSC pattern by considering the actual change in cellular size distribution. Quantitative ultrasound parameters were estimated and related to the percentage of dead cells determined by flow cytometry. The standard deviation of scatterer size distribution extracted from the polydisperse structure factor model and the spectral intercept were found to be strongly correlated to the percentage of dead cells (r² = 0.79 and r² = 0.72, respectively). This study contributes to the understanding of ultrasonic scattering from cells undergoing cell death toward the monitoring of cancer therapy.

Autoregressive Signal Processing Applied to High-Frequency Acoustic Microscopy of Soft Tissues

Quantitative acoustic microscopy (QAM) at frequencies exceeding 100 MHz has become an established imaging tool to depict acoustical and mechanical properties of soft biological tissues at microscopic resolutions. In this study, we investigate a novel autoregressive (AR) model to improve signal processing and parameter estimation and to test its applicability to QAM. The performance of the AR model for estimating acoustical parameters of soft tissues (i.e., acoustic impedance, speed of sound, and attenuation) was compared to the performance of the Hozumi model using simulated ultrasonic QAM signals and using experimentally measured signals from thin (i.e., 12 and ) sections of human lymph-node and pig-cornea tissue specimens. Results showed that the AR and Hozumi methods performed equally well (i.e., produced an estimation error of 0) in signals with low, linear attenuation in the tissue and high impedance contrast between the tissue and the coupling medium. However, the AR model outperformed the Hozumi model in estimation accuracy and stability (i.e., parameter error variation and number of outliers) in cases of 1) thin tissue-sample thickness and high tissue-sample speed of sound, 2) small impedance contrast between the tissue sample and the coupling medium, 3) high attenuation in the tissue sample, and 4) nonlinear attenuation in the tissue sample. Furthermore, the AR model allows estimating the exponent of nonlinear attenuation. The results of this study suggest that the AR model approach can improve current QAM by providing more reliable, quantitative, tissue-property estimates and also provides additional values of parameters related to nonlinear attenuation.

High-Frequency Quantitative Ultrasound for Imaging Prostate Cancer Using a Novel Micro-Ultrasound Scanner

Currently, biopsies guided by transrectal ultrasound (TRUS) are the only method for definitive diagnosis of prostate cancer. Studies by our group suggest that quantitative ultrasound (QUS) could provide a more sensitive means of targeting biopsies and directing focal treatments to cancer-suspicious regions in the prostate. Previous studies have utilized ultrasound signals at typical clinical frequencies, i.e., in the 6-MHz range. In the present study, a 29-MHz, TRUS, micro-ultrasound system and transducer (ExactVu micro-ultrasound, Exact Imaging, Markham, Canada) was used to acquire radio frequency data from 163 patients immediately before 12-core biopsy procedures, comprising 1956 cores. These retrospective data are a subset of data acquired in an ongoing, multisite, 2000-patient, randomized, clinical trial (clinicaltrials.gov NCT02079025). Spectrum-based QUS estimates of effective scatter diameter (ESD), effective acoustic concentration (EAC), midband (M), intercept (I) and slope (S) as well as envelope statistics employing a Nakagami distribution were used to train linear discriminant classifiers (LDCs) and support vector machines (SVMs). Classifier performance was assessed using area-under-the-curve (AUC) values obtained from receiver operating characteristic (ROC) analyses with 10-fold cross validation. A combination of ESD and EAC parameters resulted in an AUC value of 0.77 using a LDC. When Nakagami-µ or prostate-specific antigen (PSA) values were added as features, the AUC value increased to 0.79. SVM produced an AUC value of 0.77, using a combination of envelope and spectral QUS estimates. The best classification produced an AUC value of 0.81 using an LDC when combining envelope statistics, PSA, ESD and EAC. In a previous study, B-mode-based scoring and evaluation using the PRI-MUS protocol produced a maximal AUC value of 0.74 for higher Gleason-score values (GS >7) when read by an expert. Our initial results with AUC values of 0.81 are very encouraging for developing a new, predominantly user-independent, prostate-cancer, risk-assessing tool.

Segmentation of 3-D High-Frequency Ultrasound Images of Human Lymph Nodes Using Graph Cut With Energy Functional Adapted to Local Intensity Distribution

Previous studies by our group have shown that 3-D high-frequency quantitative ultrasound (QUS) methods have the potential to differentiate metastatic lymph nodes (LNs) from cancer-free LNs dissected from human cancer patients. To successfully perform these methods inside the LN parenchyma (LNP), an automatic segmentation method is highly desired to exclude the surrounding thin layer of fat from QUS processing and accurately correct for ultrasound attenuation. In high-frequency ultrasound images of LNs, the intensity distribution of LNP and fat varies spatially because of acoustic attenuation and focusing effects. Thus, the intensity contrast between two object regions (e.g., LNP and fat) is also spatially varying. In our previous work, nested graph cut (GC) demonstrated its ability to simultaneously segment LNP, fat, and the outer phosphate-buffered saline bath even when some boundaries are lost because of acoustic attenuation and focusing effects. This paper describes a novel approach called GC with locally adaptive energy to further deal with spatially varying distributions of LNP and fat caused by inhomogeneous acoustic attenuation. The proposed method achieved Dice similarity coefficients of 0.937±0.035 when compared with expert manual segmentation on a representative data set consisting of 115 3-D LN images obtained from colorectal cancer patients.

Effects of Signal Saturation on QUS Parameter Estimates Based on High-Frequency-Ultrasound Signals Acquired From Isolated Cancerous Lymph Nodes

Choosing an appropriate dynamic range (DR) for acquiring radio frequency (RF) data from a high-frequency-ultrasound (HFU) system is challenging because signals can vary greatly in amplitude as a result of focusing and attenuation effects. In addition, quantitative ultrasound (QUS) results are altered by saturated data. In this paper, the effects of saturation on QUS estimates of effective scatterer diameter (ESD) and effective acoustic concentration (EAC) were quantified using simulated and experimental RF data. Experimental data were acquired from 69 dissected human lymph nodes using a single-element transducer with a 26-MHz center frequency. Artificially saturated signals ( x_c) were produced by thresholding the original unsaturated RF echo signals. Saturation severity was expressed using a quantity called saturate-signal-to-noise ratio (SSNR). Results indicated that saturation has little effect on ESD estimates. However, EAC estimates decreased significantly with decreasing SSNR. An EAC correction algorithm exploiting a linear relationship between EAC values over a range of SSNR values and l¹ -norm of x_c (i.e., the sum of absolute values of the true RF echo signal) is developed. The maximal errors in EAC estimates resulting from saturation were -8.05, -3.59, and -0.93 dB/mm³ with the RF echo signals thresholded to keep 5, 6, and 7-bit from the original 8-bit DR, respectively. The EAC correction algorithm reduced maximal errors to -3.71, -0.89, and -0.26 dB/mm³ when signals were thresholded at 5, 6, and 7-bit, respectively.

Local Transverse-Slice-Based Level-Set Method for Segmentation of 3-D High-Frequency Ultrasonic Backscatter From Dissected Human Lymph Nodes

OBJECTIVE

To detect metastases in freshly excised human lymph nodes (LNs) using three-dimensional (3-D), high-frequency, quantitative ultrasound (QUS) methods, the LN parenchyma (LNP) must be segmented to preclude QUS analysis of data in regions outside the LNP and to compensate ultrasound attenuation effects due to overlying layers of LNP and residual perinodal fat (PNF).

METHODS

After restoring the saturated radio-frequency signals from PNF using an approach based on smoothing cubic splines, the three regions, i.e., LNP, PNF, and normal saline (NS), in the LN envelope data are segmented using a new, automatic, 3-D, three-phase, statistical transverseslice-based level-set (STS-LS) method that amends Lankton's method. Due to ultrasound attenuation and focusing effects, the speckle statistics of the envelope data vary with imaged depth. Thus, to mitigate depth-related inhomogeneity effects, the STS-LS method employs gamma probabilitydensity functions to locally model the speckle statistics within consecutive transverse slices.

RESULTS

Accurate results were obtained on simulated data. On a representative dataset of 54 LNs acquired from colorectal-cancer patients, the Dice similarity coefficient for LNP, PNF, and NS were 0.938 ± 0.025, 0.832 ± 0.086, and 0.968 ± 0.008, respectively, when compared to expert manual segmentation.

CONCLUSION

The STS-LS outperforms the established methods based on global and local statistics in our datasets and is capable of accurately handling the depth-dependent effects due to attenuation and focusing.

SIGNIFICANCE

This advance permits the automatic QUS-based cancer detection in the LNs. Furthermore, the STS-LS method could potentially be used in a wide range of ultrasound-imaging applications suffering from depth-dependent effects.

Quantitative Characterization of Tissue Microstructure in Concentrated Cell Pellet Biophantoms Based on the Structure Factor Model

Quantitative ultrasound (QUS) methods based on the backscatter coefficient (BSC) are typically model-based. The BSC is estimated from experiments and is fit to a model. The fit parameters are often termed QUS estimates and are used to characterize the scattering properties of the tissue under investigation. Nevertheless, for physical interpretation of QUS estimates to be accurate, the scattering model chosen must also be accurate. The goal of this work was to investigate the use of the structure factor model (SFM) to take into account coherent scattering from high volume fractions of scatterers. The study focuses on comparing the performance of two sparse models (fluid-filled sphere and Gaussian) and one concentrated model (SFM) to estimate QUS parameters from simulations and cell pellet biophantoms with a range of scatterer volume fractions. Results demonstrated the superiority of the SFM for all investigated volume fractions (i.e., from 0.006 to 0.30). In particular, the sparse models underestimated scatterer size and overestimated acoustic concentration when the volume fraction was greater than 0.12. In addition, the SFM has the ability to provide the volume fraction and the relative impedance contrast (instead of only the acoustic concentration provided by the sparse models), which could have a great benefit for tissue characterization. This study demonstrates that the SFM could prove to be an invaluable tool for QUS and could help to more accurately characterize tissue from ultrasound measurements.

Can early hepatic fibrosis stages be discriminated by combining ultrasonic parameters?

In this study, we put forward a new approach to classify early stages of fibrosis based on a multiparametric characterization using backscatter ultrasonic signals. Ultrasonic parameters, such as backscatter coefficient (Bc), speed of sound (SoS), attenuation coefficient (Ac), mean scatterer spacing (MSS), and spectral slope (SS), have shown their potential to differentiate between healthy and pathologic samples in different organs (eye, breast, prostate, liver). Recently, our group looked into the characterization of stages of hepatic fibrosis using the parameters cited above. The results showed that none of them could individually distinguish between the different stages. Therefore, we explored a multiparametric approach by combining these parameters in two and three, to test their potential to discriminate between the stages of liver fibrosis: F0 (normal), F1, F3, and/without F4 (cirrhosis), according to METAVIR Score. Discriminant analysis showed that the most relevant individual parameter was Bc, followed by SoS, SS, MSS, and Ac. The combination of (Bc, SoS) along with the four stages was the best in differentiating between the stages of fibrosis and correctly classified 85% of the liver samples with a high level of significance (p<0.0001). Nevertheless, when taking into account only stages F0, F1, and F3, the discriminant analysis showed that the parameters (Bc, SoS) and (Bc, Ac) had a better classification (93%) with a high level of significance (p<0.0001). The combination of the three parameters (Bc, SoS, and Ac) led to a 100% correct classification. In conclusion, the current findings show that the multiparametric approach has great potential in differentiating between the stages of fibrosis, and thus could play an important role in the diagnosis and follow-up of hepatic fibrosis.

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and preclinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

Unifying Concepts of Statistical and Spectral Quantitative Ultrasound Techniques

Quantitative ultrasound (QUS) techniques using radiofrequency (RF) backscattered signals have been used for tissue characterization of numerous organ systems. One approach is to use the magnitude and frequency dependence of backscatter echoes to quantify tissue structures. Another approach is to use first-order statistical properties of the echo envelope as a signature of the tissue microstructure. We propose a unification of these QUS concepts. For this purpose, a mixture of homodyned K-distributions is introduced to model the echo envelope, together with an estimation method and a physical interpretation of its parameters based on the echo signal spectrum. In particular, the total, coherent and diffuse signal powers related to the proposed mixture model are expressed explicitly in terms of the structure factor previously studied to describe the backscatter coefficient (BSC). Then, this approach is illustrated in the context of red blood cell (RBC) aggregation. It is experimentally shown that the total, coherent and diffuse signal powers are determined by a structural parameter of the spectral Structure Factor Size and Attenuation Estimator. A two-way repeated measures ANOVA test showed that attenuation (p-value of 0.077) and attenuation compensation (p-value of 0.527) had no significant effect on the diffuse to total power ratio. These results constitute a further step in understanding the physical meaning of first-order statistics of ultrasound images and their relations to QUS techniques. The proposed unifying concepts should be applicable to other biological tissues than blood considering that the structure factor can theoretically model any spatial distribution of scatterers.

Quantitative assessment of damage during MCET: a parametric study in a rodent model

Background

Myocardial cavitation-enabled therapy (MCET) has been proposed as a means to achieve minimally invasive myocardial reduction using ultrasound to produce scattered microlesions by cavitating contrast agent microbubbles.

Methods

Rats were treated using burst mode focused ultrasound at 1.5 MHz center frequency and varying envelope and pressure amplitudes. Evans blue staining indicated lethal cardiomyocytic injury. A previously developed quantitative scheme, evaluating the histologic treatment results, provides an insightful analysis for MCET treatment parameters. Such include ultrasound exposure amplitude and pulse modulation, contrast agent dose, and infusion rate.

Results

The quantitative method overcomes the limitation of visual scoring and works for a large dynamic range of treatment impact. Macrolesions are generated as an accumulation of probability driven microlesion formations. Macrolesions grow radially with radii from 0.1 to 1.6 mm as the ultrasound exposure amplitude (peak negative) increases from 2 to 4 MPa. To shorten treatment time, a swept beam was investigated and found to generate an acceptable macrolesion volume of about 40 μL for a single beam position.

Conclusions

Ultrasound parameters and administration of microbubbles directly influence lesion characteristics such as microlesion density and macrolesion dimension. For lesion generation planning, control of MCET is crucial, especially when targeting larger pre-clinical models.

Quantitative Ultrasound Comparison of MAT and 4T1 Mammary Tumors in Mice and Rats Across Multiple Imaging Systems

OBJECTIVES

Quantitative ultrasound estimates such as the frequency-dependent backscatter coefficient (BSC) have the potential to enhance noninvasive tissue characterization and to identify tumors better than traditional B-mode imaging. Thus, investigating system independence of BSC estimates from multiple imaging platforms is important for assessing their capabilities to detect tissue differences.

METHODS

Mouse and rat mammary tumor models, 4T1 and MAT, respectively, were used in a comparative experiment using 3 imaging systems (Siemens, Ultrasonix, and VisualSonics) with 5 different transducers covering a range of ultrasonic frequencies.

RESULTS

Functional analysis of variance of the MAT and 4T1 BSC-versus-frequency curves revealed statistically significant differences between the two tumor types. Variations also were found among results from different transducers, attributable to frequency range effects. At 3 to 8 MHz, tumor BSC functions using different systems showed no differences between tumor type, but at 10 to 20 MHz, there were differences between 4T1 and MAT tumors. Fitting an average spline model to the combined BSC estimates (3-22 MHz) demonstrated that the BSC differences between tumors increased with increasing frequency, with the greatest separation above 15 MHz. Confining the analysis to larger tumors resulted in better discrimination over a wider bandwidth.

CONCLUSIONS

Confining the comparison to higher ultrasonic frequencies or larger tumor sizes allowed for separation of BSC-versus-frequency curves from 4T1 and MAT tumors. These constraints ensure that a greater fraction of the backscattered signals originated from within the tumor, thus demonstrating that statistically significant tumor differences were detected.

Ultrasound-based quantification of vitreous floaters correlates with contrast sensitivity and quality of life

PURPOSE

Clinical evaluation of floaters lacks quantitative assessment of vitreous structure. This study used quantitative ultrasound (QUS) to measure vitreous opacities. Since floaters reduce contrast sensitivity (CS) and quality of life (Visual Function Questionnaire [VFQ]), it is hypothesized that QUS will correlate with CS and VFQ in patients with floaters.

METHODS

Twenty-two eyes (22 subjects; age = 57 ± 19 years) with floaters were evaluated with Freiburg acuity contrast testing (FrACT; %Weber) and VFQ. Ultrasonography used a customized probe (15-MHz center frequency, 20-mm focal length, 7-mm aperture) with longitudinal and transverse scans taken in primary gaze and a horizontal longitudinal scan through premacular vitreous in temporal gaze. Each scan set had 100 frames of log-compressed envelope data. Within each frame, two regions of interest (ROIs) were analyzed (whole-central and posterior vitreous) to yield three parameters (energy, E; mean amplitude, M; and percentage of vitreous filled by echodensities, P50) averaged over the entire 100-frame dataset. Statistical analyses evaluated E, M, and P50 correlations with CS and VFQ.

RESULTS

Contrast sensitivity ranged from 1.19%W (normal) to 5.59%W. All QUS parameters in two scan positions within the whole-central ROI correlated with CS (R > 0.67, P < 0.001). P50 in the nasal longitudinal position had R = 0.867 (P < 0.001). Correlations with VFQ ranged from R = 0.52 (P < 0.013) to R = 0.65 (P < 0.001).

CONCLUSIONS

Quantitative ultrasound provides quantitative measures of vitreous echodensity that correlate with CS and VFQ, providing objective assessment of vitreous structure underlying the functional disturbances induced by floaters, useful to quantify vitreous disease severity and the response to therapy.

Noninvasive characterization of locally advanced breast cancer using textural analysis of quantitative ultrasound parametric images

PURPOSE: The identification of tumor pathologic characteristics is an important part of breast cancer diagnosis, prognosis, and treatment planning but currently requires biopsy as its standard. Here, we investigated a noninvasive quantitative ultrasound method for the characterization of breast tumors in terms of their histologic grade, which can be used with clinical diagnostic ultrasound data. METHODS: Tumors of 57 locally advanced breast cancer patients were analyzed as part of this study. Seven quantitative ultrasound parameters were determined from each tumor region from the radiofrequency data, including mid-band fit, spectral slope, 0-MHz intercept, scatterer spacing, attenuation coefficient estimate, average scatterer diameter, and average acoustic concentration. Parametric maps were generated corresponding to the region of interest, from which four textural features, including contrast, energy, homogeneity, and correlation, were determined as further tumor characterization parameters. Data were examined on the basis of tumor subtypes based on histologic grade (grade I versus grade II to III). RESULTS: Linear discriminant analysis of the means of the parametric maps resulted in classification accuracy of 79%. On the other hand, the linear combination of the texture features of the parametric maps resulted in classification accuracy of 82%. Finally, when both the means and textures of the parametric maps were combined, the best classification accuracy was obtained (86%). CONCLUSIONS: Textural characteristics of quantitative ultrasound spectral parametric maps provided discriminant information about different types of breast tumors. The use of texture features significantly improved the results of ultrasonic tumor characterization compared to conventional mean values. Thus, this study suggests that texture-based quantitative ultrasound analysis of in vivo breast tumors can provide complementary diagnostic information about tumor histologic characteristics.

Experimental evaluation of spectral-based quantitative ultrasound imaging using plane wave compounding

Quantitative ultrasound (QUS) based on backscatter coefficient (BSC) estimation has shown potential for tissue characterization. Beamforming using plane wave compounding has advantages for echographic, Doppler, and elastographic imaging; however, to date, plane wave compounding has not been experimentally evaluated for the purpose of BSC estimation. In this study, two BSC-derived parameters (i.e., the BSC midband fit and intercept) were estimated from experimental data obtained using compound plane wave beamforming. For comparison, QUS parameters were also estimated from data obtained using both fixed focus and dynamic receive beamforming. An ultrasound imaging system equipped with a 9-MHz center frequency, 64-element array was used to collect data up to a depth of 45 mm. Two gelatin phantoms with randomly distributed 20-μm inclusions with a homogeneous scatterer concentration and a two-region scatterer concentration were used for assessing the precision and lateral resolution of QUS imaging, respectively. The use of plane wave compounding resulted in accurate QUS estimation (i.e., bias in the BSC parameters of less than 2 dB) and relatively constant lateral resolution (i.e., BSC midband fit 10% to 90% rise distance ranging between 1.0 and 1.5 mm) throughout a 45 mm field of view. Although both fixed focus and dynamic receive beamforming provided the same performance around the focal depth, the reduction in SNR away from the focus resulted in a reduced field of view in the homogeneous phantom (i.e., only 28 mm). The lateral resolution also degraded away from the focus, with up to a 2-fold and 10-fold increase in the rise distance at 20 mm beyond the focal depth for dynamic receive and fixed focus beamforming, respectively. These results suggest that plane wave compounding has the potential to improve the performance of spectral-based quantitative ultrasound over other conventional beamforming strategies.

Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties

PURPOSE

Tumor grading is an important part of breast cancer diagnosis and currently requires biopsy as its standard. Here, the authors investigate quantitative ultrasound parameters in locally advanced breast cancers that can potentially separate tumors from normal breast tissue and differentiate tumor grades.

METHODS

Ultrasound images and radiofrequency data from 42 locally advanced breast cancer patients were acquired and analyzed. Parameters related to the linear regression of the power spectrum--midband fit, slope, and 0-MHz-intercept--were determined from breast tumors and normal breast tissues. Mean scatterer spacing was estimated from the spectral autocorrelation, and the effective scatterer diameter and effective acoustic concentration were estimated from the Gaussian form factor. Parametric maps of each quantitative ultrasound parameter were constructed from the gated radiofrequency segments in tumor and normal tissue regions of interest. In addition to the mean values of the parametric maps, higher order statistical features, computed from gray-level co-occurrence matrices were also determined and used for characterization. Finally, linear and quadratic discriminant analyses were performed using combinations of quantitative ultrasound parameters to classify breast tissues.

RESULTS

Quantitative ultrasound parameters were found to be statistically different between tumor and normal tissue (p < 0.05). The combination of effective acoustic concentration and mean scatterer spacing could separate tumor from normal tissue with 82% accuracy, while the addition of effective scatterer diameter to the combination did not provide significant improvement (83% accuracy). Furthermore, the two advanced parameters, including effective scatterer diameter and mean scatterer spacing, were found to be statistically differentiating among grade I, II, and III tumors (p = 0.014 for scatterer spacing, p = 0.035 for effective scatterer diameter). The separation of the tumor grades further improved when the textural features of the effective scatterer diameter parametric map were combined with the mean value of the map (p = 0.004).

CONCLUSIONS

Overall, the binary classification results (tumor versus normal tissue) were more promising than tumor grade assessment. Combinations of advanced parameters can further improve the separation of tumors from normal tissue compared to the use of linear regression parameters. While the linear regression parameters were sufficient for characterizing breast tumors and normal breast tissues, advanced parameters and their textural features were required to better characterize tumor subtypes.

Structure factor model for understanding the measured backscatter coefficients from concentrated cell pellet biophantoms

Ultrasonic backscatter coefficient (BSC) measurements were performed on K562 cell pellet biophantoms with cell concentrations ranging from 0.006 to 0.30 in the 10-42 MHz frequency bandwidth. Three scattering models, namely, the fluid-filled sphere model (FFSM), the particle model (PM), and the structure factor model (SFM), were compared for modeling the scattering from an ensemble of concentrated cells. A parameter estimation procedure was developed in order to estimate the scatterer size and relative impedance contrast that could explain the measured BSCs from all the studied cell concentrations. This procedure was applied to the BSC data from K562 cell pellet biophantoms in the 10-42 MHz frequency bandwidth and to the BSC data from Chinese hamster ovary cell pellet biophantoms in the 26-105 MHz frequency bandwidth given in Han, Abuhabsah, Blue, Sarwate, and O'Brien [J. Acoust. Soc. Am. 130, 4139-4147 (2011)]. The data fitting quality and the scatterer size estimates show that the SFM was more suitable than the PM and the FFSM for modeling the responses from concentrated cell pellet biophantoms.

Three-dimensional quantitative ultrasound to guide pathologists towards metastatic foci in lymph nodes

The detection of metastases in freshly-excised lymph nodes from cancer patients during lymphadenectomy is critically important for cancer staging, treatment, and optimal patient management. Currently, conventional histologic methods suffer a high rate of false-negative determinations because pathologists cannot evaluate each excised lymph nodes in its entirety. Therefore, lymph nodes are undersampled and and small but clinically relevant metastatic regions can be missed. In this study, quantitative ultrasound (QUS) methods using high-frequency transducers (i.e., > 20 MHz) were developed and evaluated for their ability to detect and guide pathologists towards suspicious regions in lymph nodes. A custom laboratory scanning system was used to acquire radio-frequency (RF) data in 3D from excised lymph nodes using a 26-MHz center-frequency transducer. Overlapping 1-mm cylindrical regions-of-interest (ROIs) of the RF data were processed to yield 13 QUS estimates quantifying tissue microstructure and organization. These QUS methods were applied to more than 260 nodes from more than 160 colorectal-, gastric-, and breast-cancer patients. Cancer-detection performance was assessed for individual estimates and linear combinations of estimates. ROC results demonstrated excellent classification. For colorectal- and gastric-cancer nodes, the areas under the ROC curves (AUCs) were greater than 0.95. Slightly poorer results (AUC=0.85) were obtained for breast-cancer nodes. Images based on QUS parameters also permitted localization of cancer foci in some micrometastatic cases.

Assessment of high-intensity focused ultrasound treatment of rodent mammary tumors using ultrasound backscatter coefficients

Fischer 344 rats with subcutaneous mammary adenocarcinoma tumors were exposed to therapeutic ultrasound at one of three exposure levels (335, 360, and 502 W/cm(2) spatial-peak temporal-average intensity). Quantitative ultrasound estimates were generated from ultrasound radio frequency (RF) data from tumors before and after high-intensity focused ultrasound treatment. Treatment outcome was independently assessed by triphenyl tetrazolium chloride (TTC) staining, histological analysis by a pathologist, and thermocouple data. The average backscatter coefficient (BSC) and integrated backscatter coefficient (IBSC) were estimated before and after therapeutic ultrasound exposure for each tumor from RF data collected using clinical (Ultrasonix Sonix RP) and small-animal (Visualsonics Vevo 2100) array systems. Changes in the BSC with treatment were comparable to inter-sample variation of untreated tumors, but statistically significant differences in the change in the IBSCs were observed when comparing the exposures collectively (p < 0.10 for Sonix RP, p < 0.05 for Vevo 2100). Several exposure levels produced statistically significant differences in the change in IBSC when examined pair-wise, including two exposures having similar intensities (p < 0.05, Vevo 2100). A comparison of the IBSC results with temperature data, histology, and TTC staining revealed that the BSC was not always sensitive to thermal insult and that peak exposure pressure appeared to correlate with observed BSC increases.

Quantitative assessment of in vivo breast masses using ultrasound attenuation and backscatter

Clinical analysis of breast ultrasound imaging is done qualitatively, facilitated with the ultrasound breast imaging-reporting and data system (US BI-RADS) lexicon, which helps to standardize imaging assessments. Two descriptors in that lexicon, "posterior acoustic features" and the "echo pattern" within a mass, are directly related to quantitative ultrasound (QUS) parameters, namely, ultrasound attenuation and the average backscatter coefficient (BSC). The purpose of this study was to quantify ultrasound attenuation and backscatter in breast masses and to investigate these QUS properties as potential differential diagnostic markers. Radio frequency (RF) echo signals were from patients with breast masses during a special ultrasound imaging session prior to core biopsy. Data were also obtained from a well characterized phantom using identical system settings. Masses include 14 fibroadenomas and 10 carcinomas. Attenuation for the acoustic path lying proximal to the tumor was estimated offline using a least squares method with constraints. BSCs were estimated using a reference phantom method (RPM). The attenuation coefficient within each mass was assessed using both the RPM and a hybrid method, and effective scatterer diameters (ESDs) were estimated using a Gaussian form factor model. Attenuation estimates obtained with the RPM were consistent with estimates done using the hybrid method in all cases except for two masses. The mean slope of the attenuation coefficient versus frequency for carcinomas was 20% greater than the mean slope value for the fibroadenomas. The product of the attenuation coefficient and anteroposterior dimension of the mass was computed to estimate the total attenuation for each mass. That value correlated well with the BI-RADS assessment of "posterior acoustic features" judged qualitatively from gray scale images. Nearly all masses were described as "hypoechoic," so no strong statements could be made about the correlation of echo pattern findings in BI-RADS with the averaged BSC values. However, most carcinomas exhibited lower values for the frequency-average BSC than fibroadenomas. The mean ESD alone did not differentiate the mass type, but fibroadenomas had greater variability in ESDs within the ROI than that found for invasive ductal carcinomas. This study demonstrates the potential to use attenuation and QUS parameters associated with the BSC as quantitative descriptors.

Three-dimensional quantitative ultrasound for detecting lymph node metastases

PURPOSE

Detection of metastases in lymph nodes (LNs) is critical for cancer management. Conventional histological methods may miss metastatic foci. To date, no practical means of evaluating the entire LN volume exists. The aim of this study was to develop fast, reliable, operator-independent, high-frequency, quantitative ultrasound (QUS) methods for evaluating LNs over their entire volume to effectively detect LN metastases.

METHODS

We scanned freshly excised LNs at 26 MHz and digitally acquired echo-signal data over the entire three-dimensional (3D) volume. A total of 146 LNs of colorectal, 26 LNs of gastric, and 118 LNs of breast cancer patients were enrolled. We step-sectioned LNs at 50-μm intervals and later compared them with 13 QUS estimates associated with tissue microstructure. Linear-discriminant analysis classified LNs as metastatic or nonmetastatic, and we computed areas (Az) under receiver-operator characteristic curves to assess classification performance. The QUS estimates and cancer probability values derived from discriminant analysis were depicted in 3D images for comparison with 3D histology.

RESULTS

Of 146 LNs of colorectal cancer patients, 23 were metastatic; Az = 0.952 ± 0.021 (95% confidence interval [CI]: 0.911-0.993); sensitivity = 91.3% (specificity = 87.0%); and sensitivity = 100% (specificity = 67.5%). Of 26 LNs of gastric cancer patients, five were metastatic; Az = 0.962 ± 0.039 (95% CI: 0.807-1.000); sensitivity = 100% (specificity = 95.3%). A total of 17 of 118 LNs of breast cancer patients were metastatic; Az = 0.833 ± 0.047 (95% CI: 0.741-0.926); sensitivity = 88.2% (specificity = 62.5%); sensitivity = 100% (specificity = 50.5%). 3D cancer probability images showed good correlation with 3D histology.

CONCLUSIONS

These results suggest that operator- and system-independent QUS methods allow reliable entire-volume LN evaluation for detecting metastases. 3D cancer probability images can help pathologists identify metastatic foci that could be missed using conventional methods.

Ultrasonic assessment of thermal therapy in rat liver

One way to assess the efficacy of thermal therapy is to quantify changes in tissue properties through ultrasonic interrogation, which requires knowledge of the acoustic properties of thermally treated tissues. In this study, estimates of ultrasonic attenuation, speed of sound, backscatter coefficient (BSC), and scattering property estimates were generated from rat liver samples submersed for 10 minutes in a saline bath that was heated to one of seven temperature values over a range of 37-70°C. The attenuation coefficient increased monotonically with exposure temperature, with a maximum increase of 90%. Speed of sound changed by <1% for the different treatment conditions. The BSC had close agreement for all thermal doses over the frequency range of 8-15 MHz. Above this frequency range, samples heated ≥55°C demonstrated an increased BSC slope, and the effective scatterer diameter and effective acoustic concentration were able to distinguish treated from nontreated cases. The findings suggest that attenuation and either BSCs or scatterer property estimates above 15 MHz were sensitive to tissue changes in excised liver caused by thermal therapy.

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%.

Comparison of ultrasound attenuation and backscatter estimates in layered tissue-mimicking phantoms among three clinical scanners

Backscatter and attenuation coefficient estimates are needed in many quantitative ultrasound strategies. In clinical applications, these parameters may not be easily obtained because of variations in scattering by tissues overlying a region of interest (ROI). The goal of this study is to assess the accuracy of backscatter and attenuation estimates for regions distal to nonuniform layers of tissue-mimicking materials. In addition, this work compares results of these estimates for "layered" phantoms scanned using different clinical ultrasound machines. Two tissue-mimicking phantoms were constructed, each exhibiting depth-dependent variations in attenuation or backscatter. The phantoms were scanned with three ultrasound imaging systems, acquiring radio frequency echo data for offline analysis. The attenuation coefficient and the backscatter coefficient (BSC) for sections of the phantoms were estimated using the reference phantom method. Properties of each layer were also measured with laboratory techniques on test samples manufactured during the construction of the phantom. Estimates of the attenuation coefficient versus frequency slope, α(0), using backscatter data from the different systems agreed to within 0.24 dB/cm-MHz. Bias in the α(0) estimates varied with the location of the ROI. BSC estimates for phantom sections whose locations ranged from 0 to 7 cm from the transducer agreed among the different systems and with theoretical predictions, with a mean bias error of 1.01 dB over the used bandwidths. This study demonstrates that attenuation and BSCs can be accurately estimated in layered inhomogeneous media using pulse-echo data from clinical imaging systems.

Lymph node characterization in vivo using endoscopic ultrasound spectrum analysis with electronic array echo endoscopes

Our purpose was to demonstrate the use of radiofrequency spectral analysis to distinguish between benign and malignant lymph nodes with data obtained using electronic array echo endoscopes, as we have done previously using mechanical echo endoscopes. In a prospective study, images were obtained from eight patients with benign-appearing lymph nodes and 11 with malignant lymph nodes, as verified by fine-needle aspiration. Midband fit, slope, intercept, correlation coefficient, and root-mean-square (RMS) deviation from a linear regression of the calibrated power spectra were determined and compared between the groups. Significant differences were observable for mean midband fit, intercept, and RMS deviation (t test P < 0.05). For benign (n = 16) vs. malignant (n = 12) lymph nodes, midband fit and RMS deviation provided classification with 89 % accuracy and area under receiver operating characteristic (ROC) curve of 0.95 based on linear discriminant analysis. We concluded that the mean spectral parameters of the backscattered signals from electronic array echo endoscopy can provide a noninvasive method to quantitatively discriminate between benign and malignant lymph nodes.

Characterization of the pancreas in vivo using EUS spectrum analysis with electronic array echoendoscopes

BACKGROUND

Spectral analysis of the radiofrequency (RF) signals that underlie grayscale EUS images has been used to provide quantitative, objective information about tissue histology.

OBJECTIVE

Our purpose was to validate RF spectral analysis as a method to distinguish between chronic pancreatitis (CP) and pancreatic cancer (PC).

DESIGN AND SETTING

A prospective study of eligible patients was conducted to analyze the RF data obtained by using electronic array echoendoscopes.

PATIENTS

Pancreatic images were obtained by using electronic array echoendoscopes from 41 patients in a prospective study, including 15 patients with PC, 15 with CP, and 11 with a normal pancreas.

MAIN OUTCOME MEASUREMENTS

Midband fit, slope, intercept, correlation coefficient, and root mean square deviation from a linear regression of the calibrated power spectra were determined and compared among the groups.

RESULTS

Statistical analysis showed that significant differences were observable between groups for mean midband fit, intercept, and root mean square deviation (t test, P < .05). Discriminant analysis of these parameters was then performed to classify the data. For CP (n = 15) versus PC (n = 15), the same parameters provided 83% accuracy and an area under the curve of 0.83.

LIMITATIONS

Moderate sample size and spatial averaging inherent in the technique.

CONCLUSIONS

This study shows that mean spectral parameters of the backscattered signals obtained by using electronic array echoendoscopes can provide a noninvasive method to quantitatively discriminate between CP and PC.

Algorithms and results of eye tissues differentiation based on RF ultrasound

Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation.

Theoretical and phantom based investigation of the impact of sound speed and backscatter variations on attenuation slope estimation

Quantitative ultrasound features such as the attenuation slope, sound speed and scatterer size, have been utilized to evaluate pathological variations in soft tissues such as the liver and breast. However, the impact of variations in the sound speed and backscatter due to underlying fat content or fibrotic changes, on the attenuation slope has not been addressed. Both numerical and acoustically uniform tissue-mimicking experimental phantoms are used to demonstrate the impact of sound speed variations on attenuation slope using clinical real-time ultrasound scanners equipped with linear array transducers. Radiofrequency data at center frequencies of 4 and 5 MHz are acquired for the experimental and numerical phantoms respectively. Numerical phantom sound speeds between 1480 and 1600 m/s in increments of 20 m/s for attenuation coefficients of 0.3, 0.4, 0.5, 0.6, and 0.7 dB/cm/MHz are simulated. Variations in the attenuation slope when the backscatter intensity of the sample is equal, 3 dB higher, and 3 dB lower than the reference is also evaluated. The sound speed for the experimental tissue-mimicking phantoms were 1500, 1540, 1560 and 1580 m/s respectively, with an attenuation coefficient of 0.5 dB/cm/MHz. Radiofrequency data is processed using three different attenuation estimation algorithms, i.e. the reference phantom, centroid downshift, and a hybrid method. In both numerical and experimental phantoms our results indicate a bias in attenuation slope estimates when the reference phantom sound speed is higher (overestimation) or lower (underestimation) than that of the sample. This bias is introduced via a small spectral shift in the normalized power spectra of the reference and sample with different sound speeds. The hybrid method provides the best estimation performance, especially for sample attenuation coefficient values lower than that of the reference phantom. The performance of all the methods deteriorates when the attenuation coefficient of the reference phantom is lower than that of the sample. In addition, the hybrid method is the least sensitive to sample backscatter intensity variations.

Entire-volume serial histological examination for detection of micrometastases in lymph nodes of colorectal cancers

The purpose of this study was to accurately detect lymph-node micrometastases, i.e., metastatic cancer foci that have a size between 2.0 and 0.2 mm, in nodes excised from colorectal cancer (CRC) patients, and to determine how frequently micrometastases might be missed when standard histological examination procedures are used. A total of 311 lymph nodes were removed and examined from 90 patients with Stage I to IV CRC. The number of slices of histology sections ranged from 6 to 75 per node (average = 25.5; SD = 11.1), which provided a total of 7,943 slices. Lymph nodes were examined in their entire volume at every 50-μm and 100-μm intervals for nodes smaller and larger than 5 mm respectively. The total number of thin sections examined in each node and the number of thin sections where metastatic foci were present were counted. The number of thin sections with metastatic foci and the total number of slices was determined for each node. In addition, the presence or absence of metastatic foci in the "central" slice was determined. Micrometastases were found in 12/311 (3.9%) of all lymph nodes. In the 12 lymph nodes with micrometastases, the rate of metastatic slices over all slices was 39.4% (range = 6.3 to 81.3%; SD = 25.8%) In the central slice of each node, micrometastases were present only in 6 of 12 lymph nodes (50%); accordingly, they were not present in the central slice for half the micrometastatic nodes. These 6 nodes represented 1.9% of the 311 nodes and 11.1% of the 54 metastatic nodes. This study suggests that a significant fraction of micrometastases can be missed by traditional singleslice sectioning; half of the micrometastases would have been overlooked in our data set of 311 nodes.

Three-dimensional high-frequency backscatter and envelope quantification of cancerous human lymph nodes

Quantitative imaging methods using high-frequency ultrasound (HFU) offer a means of characterizing biological tissue at the microscopic level. Previously, high-frequency, 3-D quantitative ultrasound (QUS) methods were developed to characterize 46 freshly-dissected lymph nodes of colorectal-cancer patients. 3-D ultrasound radiofrequency data were acquired using a 25.6 MHz center-frequency transducer and each node was inked before tissue fixation to recover orientation after sectioning for 3-D histological evaluation. Backscattered echo signals were processed using 3-D cylindrical regions-of-interest (ROIs) to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept and slope). These QUS estimates, obtained by parameterizing the backscatter spectrum, showed great potential for cancer detection. In the present study, these QUS methods were applied to 112 lymph nodes from 77 colorectal and gastric cancer patients. Novel QUS methods parameterizing the envelope statistics of the ROIs using Nakagami and homodyned-K distributions were also developed; they yielded four additional QUS estimates. The ability of these eight QUS estimates to classify lymph nodes and detect cancer was evaluated using receiver operating characteristics (ROC) curves. An area under the ROC curve of 0.996 with specificity and sensitivity of 95% were obtained by combining effective scatterer size and one envelope parameter based on the homodyned-K distribution. Therefore, these advanced 3-D QUS methods potentially can be valuable for detecting small metastatic foci in dissected lymph nodes.

Quantitative ultrasound in cancer imaging

Ultrasound is a relatively inexpensive, portable, and versatile imaging modality that has a broad range of clinical uses. It incorporates many imaging modes, such as conventional gray-scale "B-mode" imaging to display echo amplitude in a scanned plane; M-mode imaging to track motion at a given fixed location over time; duplex, color, and power Doppler imaging to display motion in a scanned plane; harmonic imaging to display nonlinear responses to incident ultrasound; elastographic imaging to display relative tissue stiffness; and contrast-agent imaging with simple contrast agents to display blood-filled spaces or with targeted agents to display specific agent-binding tissue types. These imaging modes have been well described in the scientific, engineering, and clinical literature. A less well-known ultrasonic imaging technology is based on quantitative ultrasound (QUS), which analyzes the distribution of power as a function of frequency in the original received echo signals from tissue and exploits the resulting spectral parameters to characterize and distinguish among tissues. This article discusses the attributes of QUS-based methods for imaging cancers and providing improved means of detecting and assessing tumors. The discussion will include applications to imaging primary prostate cancer and metastatic cancer in lymph nodes to illustrate the methods.

Tissue typing using ultrasound RF time series: experiments with animal tissue samples

PURPOSE

This article provides experimental evidence to show that the time series of radiofrequency (RF) ultrasound data can be used for tissue typing. It also explores the tissue typing information in RF time series. Clinical and high-frequency ultrasound are studied.

METHODS

Bovine liver, pig liver, bovine muscle, and chicken breast were used in the experiments as the animal tissue types. In the proposed approach, the authors record RF echo signals backscattered from tissue, while the imaging probe and the tissue are stationary. This sequence of recorded RF data generates a time series of RF echoes for each spatial sample of the RF signal. The authors use spectral and fractal features of ultrasound RF time series averaged over a region of interest, along with feedforward neural networks for tissue typing. The experiments are repeated at ultrasound frequency of 6.6 and also 55 MHz. The effects of increasing power and frame rate are studied.

RESULTS

The methodology yielded an average two-class classification accuracy of 95.1% when ultrasound data were acquired at 6.6 MHz and 98.1% when data were collected with a high-frequency probe operating at 55 MHz. In four-class classification experiments, the recorded accuracies were 78.6% and 86.5% for low and high-frequency ultrasound data, respectively. A set of 12 texture features extracted from the B-mode image equivalents of the RF data yields an accuracy of only 77.5% in typing the analyzed tissues. An increase in acoustic power and the frame rate of ultrasound results in an improvement in classification results.

CONCLUSIONS

The results of this study demonstrate that RF time series can be used for ultrasound-based tissue typing. Further investigation of the underlying physical mechanisms is necessary.