Quantifying B-mode images of in vivo rat mammary tumors by the frequency dependence of backscatter

Repeatability, Reproducibility and Sources of Variability in the Assessment of Backscatter Coefficient and Texture Parameters from High-Frequency Ultrasound Acquisitions in Human Median Nerve

Ultrasound (US) is an increasingly prevalent and effective diagnostic modality for neuromuscular imaging. Gray-scale B-mode imaging has been the dominant US approach to evaluating nerves qualitatively or making morphometric measurements of nerves, providing important insights into pathological changes for conditions such as carpal tunnel syndrome. Among more recent ultrasound strategies, high-frequency ultrasound (often defined as >15 MHz for clinical applications), quantitative ultrasound and image textural analysis offer promising enhancements for improved and more objective approaches to nerve imaging. In this study, we evaluated the repeatability and reproducibility of backscatter coefficient (BSC) and imaging texture features extracted by gray-level co-occurrence matrices (GLCMs) in homogeneous tissue-mimicking reference phantoms and in median nerves in the wrists of healthy participants. We also investigated several practical sources of variability in the assessment of quantitative parameters, including influences of operators, and participant-to-participant variability. Overall, BSC- and GLCM-based outcomes are highly repeatable and reproducible after operator training, based on measurement of descriptive statistics, repeatability coefficient (RC) and reproducibility coefficient recommended by Quantitative Imaging Biomarker Alliance (QIBA RDC). GLCM parameters appear more reproducible and repeatable than BSC-based parameters in healthy participants in vivo. However, such variability noted here must be compared with the value ranges and variability of the results in pathological nerves, including median nerves afflicted by trauma, overuse syndromes such as carpal tunnel syndrome and after surgical repair.

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.

Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy

In this study, a novel deep learning-based methodology was investigated to predict breast cancer response to neo-adjuvant chemotherapy (NAC) using the quantitative ultrasound (QUS) multi-parametric imaging at pre-treatment. QUS multi-parametric images of breast tumors were generated using the data acquired from 181 patients diagnosed with locally advanced breast cancer and planned for NAC followed by surgery. The ground truth response to NAC was identified for each patient after the surgery using the standard clinical and pathological criteria. Two deep convolutional neural network (DCNN) architectures including the residual network and residual attention network (RAN) were explored for extracting optimal feature maps from the parametric images, with a fully connected network for response prediction. In different experiments, the features maps were derived from the tumor core only, as well as the core and its margin. Evaluation results on an independent test set demonstrate that the developed model with the RAN architecture to extract feature maps from the expanded parametric images of the tumor core and margin had the best performance in response prediction with an accuracy of 88% and an area under the receiver operating characteristic curve of 0.86. Ten-year survival analyses indicate statistically significant differences between the survival of the responders and non-responders identified based on the model prediction at pre-treatment and the standard criteria at post-treatment. The results of this study demonstrate the promising capability of DCNNs with attention mechanisms in predicting breast cancer response to NAC prior to the start of treatment using QUS multi-parametric images.

In vivo assessment of pulmonary fibrosis and edema in rodents using the backscatter coefficient and envelope statistics

Quantitative ultrasound methods based on the backscatter coefficient (BSC) and envelope statistics have been used to quantify disease in a wide variety of tissues, such as prostate, lymph nodes, breast, and thyroid. However, to date, these methods have not been investigated in the lung. In this study, lung properties were quantified by BSC and envelope statistical parameters in normal, fibrotic, and edematous rat lungs in vivo. The average and standard deviation of each parameter were calculated for each lung as well as the evolution of each parameter with acoustic propagation time within the lung. The transport mean free path and backscattered frequency shift, two parameters that have been successfully used to assess pulmonary fibrosis and edema in prior work, were evaluated in combination with the BSC and envelope statistical parameters. Multiple BSC and envelope statistical parameters were found to provide contrast between control and diseased lungs. BSC and envelope statistical parameters were also significantly correlated with fibrosis severity using the modified Ashcroft fibrosis score as the histological gold standard. These results demonstrate the potential for BSC and envelope statistical parameters to improve the diagnosis of pulmonary fibrosis and edema as well as monitor pulmonary fibrosis.

Monitoring breast cancer response to neoadjuvant chemotherapy with ultrasound signal statistics and integrated backscatter

Background

Neoadjuvant chemotherapy (NAC) is used in patients with breast cancer to reduce tumor focus, metastatic risk, and patient mortality. Monitoring NAC effects is necessary to capture resistant patients and stop or change treatment. The existing methods for evaluating NAC results have some limitations. The aim of this study was to assess the tumor response at an early stage, after the first doses of the NAC, based on the variability of the backscattered ultrasound energy, and backscatter statistics. The backscatter statistics has not previously been used to monitor NAC effects.

Methods

The B-mode ultrasound images and raw radio frequency data from breast tumors were obtained using an ultrasound scanner before chemotherapy and 1 week after each NAC cycle. The study included twenty-four malignant breast cancers diagnosed in sixteen patients and qualified for neoadjuvant treatment before surgery. The shape parameter of the homodyned K distribution and integrated backscatter, along with the tumor size in the longest dimension, were determined based on ultrasound data and used as markers for NAC response. Cancer tumors were assigned to responding and non-responding groups, according to histopathological evaluation, which was a reference in assessing the utility of markers. Statistical analysis was performed to rate the ability of markers to predict the final NAC response based on data obtained after subsequent therapeutic doses.

Results

Statistically significant differences (p<0.05) between groups were obtained after 2, 3, 4, and 5 doses of NAC for quantitative ultrasound markers and after 5 doses for the assessment based on maximum tumor dimension. Statistical analysis showed that, after the second and third NAC courses the classification based on integrated backscatter marker was characterized by an AUC of 0.69 and 0.82, respectively. The introduction of the second quantitative marker describing the statistical properties of scattering increased the corresponding AUC values to 0.82 and 0.91.

Conclusions

Quantitative ultrasound information can characterize the tumor's pathological response better and at an earlier stage of therapy than the assessment of the reduction of its dimensions. The introduction of statistical parameters of ultrasonic backscatter to monitor the effects of chemotherapy can increase the effectiveness of monitoring and contribute to a better personalization of NAC therapy.

Quantitative ultrasound assessment of breast tumor response to chemotherapy using a multi-parameter approach

PURPOSE

This study demonstrated the ability of quantitative ultrasound (QUS) parameters in providing an early prediction of tumor response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC).

METHODS

Using a 6-MHz array transducer, ultrasound radiofrequency (RF) data were collected from 58 LABC patients prior to NAC treatment and at weeks 1, 4, and 8 of their treatment, and prior to surgery. QUS parameters including midband fit (MBF), spectral slope (SS), spectral intercept (SI), spacing among scatterers (SAS), attenuation coefficient estimate (ACE), average scatterer diameter (ASD), and average acoustic concentration (AAC) were determined from the tumor region of interest. Ultrasound data were compared with the ultimate clinical and pathological response of the patient's tumor to treatment and patient recurrence-free survival.

RESULTS

Multi-parameter discriminant analysis using the κ-nearest-neighbor classifier demonstrated that the best response classification could be achieved using the combination of MBF, SS, and SAS, with an accuracy of 60 ± 10% at week 1, 77 ± 8% at week 4 and 75 ± 6% at week 8. Furthermore, when the QUS measurements at each time (week) were combined with pre-treatment (week 0) QUS values, the classification accuracies improved (70 ± 9% at week 1, 80 ± 5% at week 4, and 81 ± 6% at week 8). Finally, the multi-parameter QUS model demonstrated a significant difference in survival rates of responding and non-responding patients at weeks 1 and 4 (p=0.035, and 0.027, respectively).

CONCLUSION

This study demonstrated for the first time, using new parameters tested on relatively large patient cohort and leave-one-out classifier evaluation, that a hybrid QUS biomarker including MBF, SS, and SAS could, with relatively high sensitivity and specificity, detect the response of LABC tumors to NAC as early as after 4 weeks of therapy. The findings of this study also suggested that incorporating pre-treatment QUS parameters of a tumor improved the classification results. This work demonstrated the potential of QUS and machine learning methods for the early assessment of breast tumor response to NAC and providing personalized medicine with regards to the treatment planning of refractory patients.

Quantification of Ultrasonic Scattering Properties of In Vivo Tumor Cell Death in Mouse Models of Breast Cancer

INTRODUCTION: Quantitative ultrasound parameters based on form factor models were investigated as potential biomarkers of cell death in breast tumor (MDA-231) xenografts treated with chemotherapy. METHODS: Ultrasound backscatter radiofrequency data were acquired from MDA-231 breast cancer tumor–bearing mice (n = 20) before and after the administration of chemotherapy drugs at two ultrasound frequencies: 7 MHz and 20 MHz. Radiofrequency spectral analysis involved estimating the backscatter coefficient from regions of interest in the center of the tumor, to which form factor models were fitted, resulting in estimates of average scatterer diameter and average acoustic concentration (AAC). RESULTS: The ∆AAC parameter extracted from the spherical Gaussian model was found to be the most effective cell death biomarker (at the lower frequency range, r² = 0.40). At both frequencies, AAC in the treated tumors increased significantly (P = .026 and .035 at low and high frequencies, respectively) 24 hours after treatment compared with control tumors. Furthermore, stepwise multiple linear regression analysis of the low-frequency data revealed that a multiparameter quantitative ultrasound model was strongly correlated to cell death determined histologically posttreatment (r² = 0.74). CONCLUSION: The Gaussian form factor model–based scattering parameters can potentially be used to track the extent of cell death at clinically relevant frequencies (7 MHz). The 20-MHz results agreed with previous findings in which parameters related to the backscatter intensity (i.e., AAC) increased with cell death. The findings suggested that, in addition to the backscatter coefficient parameter ∆AAC, biological features including tumor heterogeneity and initial tumor volume were important factors in the prediction of cell death response.

Quantitative evaluation of cell death response in vitro and in vivo using conventional-frequency ultrasound

Previous studies using high-frequency ultrasound have suggested that radiofrequency (RF) spectral analysis can be used to quantify changes in cell morphology to detect cell death response to therapy non-invasively. The study here investigated this at conventional-frequencies, frequently used in clinical settings.

Spectral analysis was performed using ultrasound RF data collected with a clinical ultrasound platform. Acute myeloid leukemia (AML-5) cells were exposed to cisplatinum for 0–72 hours in vitro and prepared for ultrasound data collection. Preclinical in vivo experiments were also performed on AML-5 tumour-bearing mice receiving chemotherapy.

The mid-band fit (MBF) spectral parameter demonstrated an increase of 4.4 ± 1.5 dBr for in vitro samples assessed 48 hours after treatment, a statistically significant change (p < 0.05) compared to control. Further, in vitro concentration-based analysis of a mixture of apoptotic and untreated cells indicated a mean change of 10.9 ± 2.4 dBr in MBF between 0% and 40% apoptotic cell mixtures. Similar effects were reproduced in vivo with an increase of 4.6 ± 0.3 dBr in MBF compared to control, for tumours with considerable apoptotic areas within histological samples. The alterations in the size of cells and nuclei corresponded well with changes measured in the quantitative ultrasound (QUS) parameters.

A simulation study on the quantitative assessment of tissue microstructure with photoacoustics

A detailed derivation of a quantity, defined as the acoustic power per unit solid angle far from the illuminated volume divided by the intensity of the incident light beam and termed as differential photoacoustic (PA) cross section, is presented. The expression for the differential PA cross section per unit absorbing volume retains two terms, namely, the coherent and the incoherent parts. The second part based on a correlation model can be employed to analyze the PA signal power spectrum for tissue characterization. The performances of the fluid sphere, Gaussian, and exponential correlation models in assessing the mean size and the variance in the optical absorption coefficients of absorbers were investigated by performing in silico experiments. It was possible to evaluate diameters of solid spherical absorbers with radii ≥ 20 μm with an accuracy of 10% for an analysis bandwidth of 5 to 50 MHz using the first two correlation models. The accuracy of estimation was about 22% for fluid spheres mimicking erythrocytes for the third correlation model for an analysis bandwidth of 5 to 100 MHz. The extracted values of average variance in the optical absorption coefficients demonstrated good correlation with the nominal values. This study suggests that the method presented here may be developed as a potential tissue characterization tool.

Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture

Early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, in conjunction with changes in their mean values, are demonstrated here, for the first time, to be capable of predicting ultimate clinical/pathologic responses of breast cancer patients to chemotherapy. Mechanisms of cell death, induced by chemotherapy within tumor, introduce morphological alterations in cancerous cells, resulting in measurable changes in tissue echogenicity. We have demonstrated that the development of such changes is reflected in early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, followed by consequent changes in their mean values. The spectral/textural biomarkers derived on this basis have been demonstrated as non-invasive surrogates of breast cancer chemotherapy response. Particularly, spectral biomarkers sensitive to the size and concentration of acoustic scatterers could predict treatment response of patients with up to 80% of sensitivity and specificity (p=0.050), after one week within 3-4 months of chemotherapy. However, textural biomarkers characterizing heterogeneities in distribution of acoustic scatterers, could differentiate between treatment responding and non-responding patients with up to 100% sensitivity and 93% specificity (p=0.002). Such early prediction permits offering effective alternatives to standard treatment, or switching to a salvage therapy, for refractory patients.

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.

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.

[Preclinical imaging in animal models of radiation therapy]

CLINICAL/METHODICAL ISSUE

Modern radiotherapy benefits from precise and targeted diagnostic and pretherapeutic imaging.

STANDARD RADIOLOGICAL METHODS

Standard imaging modalities, such as computed tomography (CT) offer high morphological detail but only limited functional information on tumors.

METHODICAL INNOVATIONS

Novel functional and molecular imaging modalities provide biological information about tumors in addition to detailed morphological information.

PERFORMANCE

Perfusion magnetic resonance imaging (MRI) CT or ultrasound-based perfusion imaging as well as hybrid modalities, such as positron emission tomography (PET) CT or MRI-PET have the potential to identify and precisely delineate viable and/or perfused tumor areas, enabling optimization of targeted radiotherapy. Functional information on tissue microcirculation and/or glucose metabolism allow a more precise definition and treatment of tumors while reducing the radiation dose and sparing the surrounding healthy tissue.

ACHIEVEMENTS

In the development of new imaging methods for planning individualized radiotherapy, preclinical imaging and research plays a pivotal role, as the value of multimodality imaging can only be assessed, tested and adequately developed in a preclinical setting, i.e. in animal tumor models.

PRACTICAL RECOMMENDATIONS

New functional imaging modalities will play an increasing role for the surveillance of early treatment response during radiation therapy and in the assessment of the potential value of new combination therapies (e.g. combining anti-angiogenic drugs with radiotherapy).

[Contrast-enhanced ultrasound in animal models]

In the past the detection of tumor perfusion was achieved solely via invasive procedures, such as intravital microscopy or with the help of costly modalities, such as multidetector computed tomography (MDCT), magnetic resonance tomography (MRT) or the combined use of positron emission tomography and computed tomography (PET/CT). Ultrasound offers the non-invasive display of organs without usage of ionizing radiation and it is widely available. However, colour-coded ultrasound and power Doppler do not allow the detection of tumor microcirculation. The introduction of contrast-enhanced ultrasound (CEUS) as well as new high-frequency ultrasound probes made it possible to detect and quantify tumor microcirculation with high resolution. CEUS has been used clinically on human beings for more than 10 years. During the last years different tumor models in experimental animals were used for the establishment of this new technique, e.g. in rats, hamsters and mice. CEUS allows the detection of functional parameters, such as the angiogenetic metabolic status of tissue pretreatment and posttreatment. Further research is required to solve the problems of absolute quantification of these perfusion parameters to allow the comparison of CEUS with other modalities (e.g. MRT and CT).

Trade-offs in data acquisition and processing parameters for backscatter and scatterer size estimations

By analyzing backscattered echo signal power spectra and thereby obtaining backscatter coefficient vs. frequency data, the size of subresolution scatterers contributing to echo signals can be estimated. Here we investigate trade-offs in data acquisition and processing parameters for reference phantom-based backscatter and scatterer size estimations. RF echo data from a tissue-mimicking test phantom were acquired using a clinical scanner equipped with linear array transducers. One array has a nominal frequency bandwidth of 5 to 13 MHz and the other 4 to 9 MHz. Comparison of spectral estimation methods showed that the Welch method provided spectra yielding more accurate and precise backscatter coefficient and scatterer size estimations than spectra computed by applying rectangular, Hanning, or Hamming windows and much reduced computational load than if using the multitaper method. For small echo signal data block sizes, moderate improvements in scatterer size estimations were obtained using a multitaper method, but this significantly increases the computational burden. It is critical to average power spectra from lateral A-lines for the improvement of scatterer size estimation. Averaging approximately 10 independent A-lines laterally with an axial window length 10 times the center frequency wavelength optimized trade-offs between spatial resolution and the variance of scatterer size estimates. Applying the concept of a time-bandwidth product, this suggests using analysis blocks that contain at least 30 independent samples of the echo signal. The estimation accuracy and precision depend on the ka range where k is the wave number and a is the effective scatterer size. This introduces a region-of-interest depth dependency to the accuracy and precision because of preferential attenuation of higher frequency sound waves in tissuelike media. With the 5 to 13 MHz, transducer ka ranged from 0.5 to 1.6 for scatterers in the test phantom, which is a favorable range, and the accuracy and precision of scatterer size estimations were both within approximately 5% using optimal analysis block dimensions. When the 4- to 9-MHz transducer was used, the ka value ranged from 0.3 to 0.8 to 1.1 for the experimental conditions, and the accuracy and precision were found to be approximately 10% and 10% to 25%, respectively. Although the experiments were done with 2 specific models of transducers on the test phantom, the results can be generalized to similar clinical arrays available from a variety of manufacturers and/or for different size of scatterers with similar ka range.

A novel coded excitation scheme to improve spatial and contrast resolution of quantitative ultrasound imaging

Quantitative ultrasound (QUS) imaging techniques based on ultrasonic backscatter have been used successfully to diagnose and monitor disease. A method for improving the contrast and axial resolution of QUS parametric images by using the resolution enhancement compression (REC) technique is proposed. Resolution enhancement compression is a coded excitation and pulse compression technique that enhances the -6-dB bandwidth of an ultrasonic imaging system. The objective of this study was to combine REC with QUS (REC-QUS) and evaluate and compare improvements in scatterer diameter estimates obtained using the REC technique to conventional pulsing methods. Simulations and experimental measurements were conducted with a single-element transducer (f/4) having a center frequency of 10 MHz and a -6-dB bandwidth of 80%. Using REC, the -6-dB bandwidth was enhanced to 155%. Images for both simulation and experimental measurements contained a signal-to-noise ratio of 28 dB. In simulations, to monitor the improvements in contrast a software phantom with a cylindrical lesion was evaluated. In experimental measurements, tissue-mimicking phantoms that contained glass spheres with different scatterer diameters were evaluated. Estimates of average scatterer diameter in the simulations and experiments were obtained by comparing the normalized backscattered power spectra to theory over the -6-dB bandwidth for both conventional pulsing and REC. Improvements in REC-QUS over conventional QUS were quantified through estimate bias and standard deviation, contrast-to-noise ratio, and histogram analysis of QUS parametric images. Overall, a 51% increase in contrast and a 60% decrease in the standard deviation of average scatterer diameter estimates were obtained during simulations, while a reduction of 34% to 71% was obtained in the standard deviation of average scatterer diameter for the experimental results.

Identifying ultrasonic scattering sites from three-dimensional impedance maps

Ultrasonic backscattered signals contain frequency-dependent information that is usually discarded to produce conventional B-mode images. It is hypothesized that parametrization of the quantitative ultrasound frequency-dependent information (i.e., estimating scatterer size and acoustic concentration) may be related to discrete scattering anatomic structures in tissues. Thus, an estimation technique is proposed to extract scatterer size and acoustic concentration from the power spectrum derived from a three-dimensional impedance map (3DZM) of a tissue volume. The 3DZM can be viewed as a computational phantom and is produced from a 3D histologic data set. The 3D histologic data set is constructed from tissue sections that have been appropriately stained to highlight specific tissue features. These tissue features are assigned acoustic impedance values to yield a 3DZM. From the power spectrum, scatterer size and acoustic concentration estimates were obtained by optimization. The 3DZM technique was validated by simulations that showed relative errors of less than 3% for all estimated parameters. Estimates using the 3DZM technique were obtained and compared against published ultrasonically derived estimates for two mammary tumors, a rat fibroadenoma and a 4T1 mouse mammary carcinoma. For both tumors, the relative difference between ultrasonic and 3DZM estimates was less than 10% for the average scatterer size.

Improved scatterer property estimates from ultrasound backscatter for small gate lengths using a gate-edge correction factor

Backscattered rf signals used to construct conventional ultrasound B-mode images contain frequency-dependent information that can be examined through the backscattered power spectrum. The backscattered power spectrum is found by taking the magnitude squared of the Fourier transform of a gated time segment corresponding to a region in the scattering volume. When a time segment is gated, the edges of the gated regions change the frequency content of the backscattered power spectrum due to truncating of the waveform. Tapered windows, like the Hanning window, and longer gate lengths reduce the relative contribution of the gate-edge effects. A new gate-edge correction factor was developed that partially accounted for the edge effects. The gate-edge correction factor gave more accurate estimates of scatterer properties at small gate lengths compared to conventional windowing functions. The gate-edge correction factor gave estimates of scatterer properties within 5% of actual values at very small gate lengths (less than 5 spatial pulse lengths) in both simulations and from measurements on glass-bead phantoms. While the gate-edge correction factor gave higher accuracy of estimates at smaller gate lengths, the precision of estimates was not improved at small gate lengths over conventional windowing functions.

Differentiation and characterization of rat mammary fibroadenomas and 4T1 mouse carcinomas using quantitative ultrasound imaging

Scatterer properties like the average effective scatterer diameter and acoustic concentration were determined in vivo using a quantitative ultrasound (QUS) technique from two tumor phenotypes grown in animal models. These tumor models included spontaneously occurring mammary fibroadenomas in rats and transplanted 4T1 mammary carcinomas in mice. The scatterer properties of average scatterer diameter and acoustic concentration were estimated using a Gaussian form factor from the backscattered ultrasound measured from both types of tumors. QUS images of the tumors were constructed utilizing estimated scatterer properties from regions in the tumors. The QUS images showed a clear distinction between the two types of tumors and a statistically significant difference existed between their estimated scatterer properties. The average scatterer diameter and acoustic concentration for the mammary fibroadenomas were estimated to be 105 +/- 25 microm and -15.6 +/- 5 dB(mm(-3)), respectively. The average scatterer diameter and acoustic concentration for the carcinomas was estimated to be 28 +/- 4.6 microm and 10.6 +/- 6.9 dB(mm(-3)), respectively. The distinctions in the scattering properties are clearly seen in the QUS images of the tumors and indicate that QUS imaging can be useful in differentiating between different types of mammary tumors.

Defining optimal axial and lateral resolution for estimating scatterer properties from volumes using ultrasound backscatter

The rf signals used to construct conventional ultrasound B-mode images contain frequency-dependent information that can be examined through the backscattered power spectrum. Typically, the backscattered power spectrum is calculated from a region of interest (ROI) within some larger volume. The dimensions of the ROI are defined axially by the spatial length corresponding to the time gate and laterally by the number of scan lines included in the ROI. Averaging the backscattered power spectra from several independent scan lines can reduce the presence of noise caused by electronics and by the random scatterer spacings, but also decreases the lateral resolution of the interrogation region. Furthermore, larger axial gate lengths can be used to reduce the effects of noise and improve the precision and accuracy of scatterer property estimates but also decreases the axial resolution. A trade-off exists between the size of the ROI (the number of scan lines used, the separation distance between each scan line, the axial gate length) and the accuracy and precision of scatterer property estimates. A series of simulations and measurements from physical phantoms were employed to examine these trade-offs. The simulations and phantom measurements indicated the optimal lateral and axial sizes of the ROI, where estimate accuracy and precision were better than 10% and 5%, respectively, occurred at 4 to 5 beamwidths laterally and 15 to 20 spatial pulse lengths axially.

Method of improved scatterer size estimation and application to parametric imaging using ultrasound

The frequency dependence of RF signals backscattered from random media (tissues) has been used to describe the microstructure of the media. The frequency dependence of the backscattered RF signal is seen in the power spectrum. Estimates of scatterer properties (average scatterer size) from an interrogated medium are made by minimizing the average squared deviation (MASD) between the measured power spectrum and a theoretical power spectrum over an analysis bandwidth. Estimates of the scatterer properties become increasingly inaccurate as the average signal to noise ratio (SNR) over the analysis bandwidth becomes smaller. Some frequency components in the analysis bandwidth of the measured power spectrum will have smaller SNR than other frequency components. The accuracy of estimates can be improved by weighting the frequency components that have the smallest SNR less than the frequencies with the largest SNR in the MASD. A weighting function is devised that minimizes the noise effects on the estimates of the average scatterer sizes. Simulations and phantom experiments are conducted that show the weighting function gives improved estimates in an attenuating medium. The weighting function is applied to parametric images using scatterer size estimates of a rat that had developed a spontaneous mammary tumor.

Parametric imaging of rat mammary tumors in vivo for the purposes of tissue characterization

OBJECTIVE

To estimate the average scatterer properties from ultrasonic backscatter in tissues for evaluating differences between neoplastic and healthy tissues.

METHODS

Parametric images of 8 retired breeder rats in which spontaneous mammary tumors had developed were created by superimposing color-coded pixels related to the estimated average scatterer properties on conventional gray scale B-mode images.

RESULTS

The images showed a distinct difference between the tumors and surrounding healthy tissues. Analysis of the average scatterer diameters and acoustic concentrations showed a statistically significant difference (P < .05) between estimates inside and outside the tumors for most of the cases. Scatterer sizes inside the tumors were on average 30% larger than scatterer sizes in surrounding normal tissues. A feature analysis plot showed that there was a distinct difference between results obtained inside and outside the tumors.

CONCLUSIONS

Parametric imaging that uses estimates of scatterer properties in tissues may lead to detection and characterization (diagnosis) of diseased tissues on conventional sonographic scanning systems.

A test phantom for estimating changes in the effective frequency of an ultrasonic scanner

OBJECTIVE

Ultrasonic frequency is an important performance feature of B-mode scanners. It is particularly relevant when comparing instruments from different manufacturers and reporting clinical results. We investigated a test phantom to independently measure an effective imaging frequency, including effects of depth-dependent attenuation and frequency filtering during echo reception.

METHODS

The approach capitalizes on variations of the frequency dependence of backscatter with scatterer size. A tissue-mimicking phantom containing 48-microm-diameter scatterers was constructed. Embedded at depths of 1, 3, 7, and 9 cm were sets of cylindrical inclusions, each containing tissue-mimicking material with a different scatterer size and number density. Computer simulations helped establish scatterer parameters for the cylinder bodies that resulted in image contrast versus the background that varied with frequency, with each cylinder transitioning from negative to positive contrast at a different frequency. Acoustic properties of the phantom were verified by a laboratory apparatus. Initial tests of the effectiveness of the phantom were done by imaging with several scanners using various frequency and imaging settings on transducers.

RESULTS

Images were obtained with 2 clinical scanners in which modest changes in the image acquisition parameters were adjusted. Image contrast between test cylinders and background corresponded to operating frequency with a multihertz transducer. Changes in observable contrast consistent with a shift in operating frequency were not always accompanied by visual indicators that such changes in the scanning protocol had occurred.

CONCLUSIONS

The test phantom performs as predicted by computer simulations and theoretical calculations of backscatter versus frequency. Contrast on images of the test phantom produced by clinical systems correlates with scanner frequency settings, showing feasibility. Relative shifts in effective frequency and operating bandwidth can be assessed from these contrast differences between settings with this test phantom.

Characterization of tissue microstructure using ultrasonic backscatter: theory and technique for optimization using a Gaussian form factor

Characterization of tissue microstructure through ultrasonic backscatter is hypothesized to aid in detection and classification of diseased tissues. Radio frequency signals backscattered from tissues can be modeled according to the assumed shape, size, and distribution of scatterers in tissues. Power spectra of rf backscattered signals describe the frequency dependence of scatterers. Experimental measurements of ultrasonic backscatter from spontaneous mammary tumors in rats are obtained over the frequency range of 4 to 12 MHz. The power spectra measured from rat tumors are compared to theoretical power spectra derived from a 3D spatial autocorrelation function assuming a Gaussian distribution. Independent values of average scatterer diameter and acoustic concentration are obtained by approximating the measured power spectrum with a best-fit line. Enhanced B-mode images are made of the rat tumors and surrounding tissues with superimposed regions of interest quantified by estimated average scatterer sizes and acoustic concentrations. Scattering properties estimated inside the tumors and in surrounding tissues are shown to be distinct. Overall, estimates showed a 44.8% increase of average scatterer diameter inside the tumor as compared to tissues outside the tumor. With the exception of one rat, all estimates of the scatterers' average acoustic concentration inside the tumor were less than outside the tumors.