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Ultrasound has been a popular clinical imaging modality for decades. It is a well-established means of displaying the macroscopic anatomy of soft-tissue structures. While conventional ultrasound methods, i.e., B-mode and Doppler methods, are well proven and continue to advance technically in many ways, e.g., by extending into higher frequencies and taking advantage of harmonic phenomena in tissues, fundamentally new so-called quantitative ultrasound (QUS) technologies also are emerging and offer exciting promise for making significant improvements in clinical imaging and characterization of disease. These emerging quantitative methods include spectrum analysis, image statistics, elasticity imaging, contrast-agent methods, and flow-detection and -measurement techniques. Each provides independent information. When used alone, each can provide clinically valuable imaging capabilities; when combined with each other, their capabilities may be more powerful in many applications. Furthermore, all can be used fused with other imaging modalities, such as computed tomography (CT), magnetic-resonance (MR), positron-emission-tomography (PET), or single-photon emission computerized tomography (SPECT) imaging, to offer possibly even greater improvements in detecting, diagnosing, imaging, evaluating, and monitoring disease. This chapter focuses on QUS methods that are based on spectrum analysis and image statistics., (© 2023. The Author(s), under exclusive license to Springer Nature Switzerland AG.)

Background: Gray-scale, B-mode ultrasound (US) imaging is part of the standard clinical procedure for evaluating thyroid nodules (TNs). It is limited by its instrument- and operator-dependence and inter-observer variability. In addition, the accepted high-risk B-mode US TN features are more specific for detecting classic papillary thyroid cancer rather than the follicular variant of papillary thyroid cancer or follicular thyroid cancer. Quantitative ultrasound (QUS) is a technique that can non-invasively assess properties of tissue microarchitecture by exploiting information contained in raw ultrasonic radiofrequency (RF) echo signals that is discarded in conventional B-mode imaging. QUS provides quantitative parameter-value estimates that are a function of the properties of US scatterers and microarchitecture of the tissue. The purpose of this preliminary study was to assess the performance of QUS parameters in evaluating benign and malignant thyroid nodules., Methods: Patients from the Thyroid Health Center at the Boston Medical Center were recruited to participate. B-mode and RF data were acquired and analyzed in 225 TNs (24 malignant and 201 benign) from 208 patients. These data were acquired either before (167 nodules) or after (58 nodules) subjects underwent fine-needle biopsy (FNB). The performance of a combination of QUS parameters (CQP) was assessed and compared with the performance of B-mode risk-stratification systems., Results: CQP produced an ROC AUC value of 0.857 ± 0.033 compared to a value of 0.887 ± 0.033 (p=0.327) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.880 ± 0.041 (p=0.367) for the American Thyroid Association (ATA) risk-stratification system. Furthermore, using a CQP threshold of 0.263 would further reduce the number of unnecessary FNBs in 44% of TNs without missing any malignant TNs. When CQP used in combination with ACR TI-RADS, a potential additional reduction of 49 to 66% in unnecessary FNBs was demonstrated., Conclusion: This preliminary study suggests that QUS may provide a method to classify TNs when used by itself or when combined with a conventional gray-scale US risk-stratification system and can potentially reduce the need to biopsy TNs., Competing Interests: Author DR is an employee of Versonics, Inc. and KW is an employee of the General Electric Research Center. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Goundan, Mamou, Rohrbach, Smith, Patel, Wallace, Feleppa and Lee.)

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 l 1 -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/mm 3 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/mm 3 when signals were thresholded at 5, 6, and 7-bit, respectively.

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.

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.

Purpose: To assess the technical feasibility, toxicity, dosimetry, and preliminary efficacy of dose-painting brachytherapy guided by ultrasound spectrum analysis tissue-type imaging (TTI) in low-risk, localized prostate cancer., Methods and Materials: Fourteen men with prostate cancer who were candidates for brachytherapy as sole treatment were prospectively enrolled. Treatment planning goal was to escalate the tumor dose to 200% with a modest de-escalation of dose to remaining prostate compared with our standard. Primary end points included technical feasibility of TTI-guided brachytherapy and equivalent or better toxicity compared with standard brachytherapy. Secondary end points included dose escalation to tumor regions and de-escalated dose to nontumor regions on the preimplant plan, negative prostate biopsy at 2 years, and freedom from biochemical failure., Results: Thirteen of fourteen men successfully completed the TTI-guided brachytherapy procedure for a feasibility rate of 93%. A software malfunction resulted in switching one patient from TTI-guided to standard brachytherapy. An average of 2.7 foci per patient was demonstrated and treated with an escalated dose. Dosimetric goals on preplan were achieved. One patient expired from unrelated causes 65 days after brachytherapy. Toxicity was at least as low as standard brachytherapy. Two-year prostate biopsies were obtained from six men; five (83%) were definitively negative, one showed evidence of disease with treatment effect, and none were positive. No patients experienced biochemical recurrence after a median followup of 31.5 (24-52) months., Conclusions: We have demonstrated that TTI-guided dose-painting prostate brachytherapy is technically feasible and results in clinical outcomes that are encouraging in terms of low toxicity and successful biochemical disease control., (Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.)

This work investigates the statistics of the envelope of three-dimensional (3D) high-frequency ultrasound (HFU) data acquired from dissected human lymph nodes (LNs). Nine distributions were employed, and their parameters were estimated using the method of moments. The Kolmogorov Smirnov (KS) metric was used to quantitatively compare the fit of each candidate distribution to the experimental envelope distribution. The study indicates that the generalized gamma distribution best models the statistics of the envelope data of the three media encountered: LN parenchyma, fat and phosphate-buffered saline (PBS). Furthermore, the envelope statistics of the LN parenchyma satisfy the pre-Rayleigh condition. In terms of high fitting accuracy and computationally efficient parameter estimation, the gamma distribution is the best choice to model the envelope statistics of LN parenchyma, while, the Weibull distribution is the best choice to model the envelope statistics of fat and PBS. These results will contribute to the development of more-accurate and automatic 3D segmentation of LNs for ultrasonic detection of clinically significant LN 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., (Copyright © 2013 Elsevier Inc. All rights reserved.)

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.

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.

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., (Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2011 Elsevier Inc. All rights reserved.)

We have developed quantitative descriptors to provide an objective means of noninvasive identification of cancerous breast lesions. These descriptors include quantitative acoustic features assessed using spectrum analysis of ultrasonic radiofrequency (rf) echo signals and morphometric properties related to lesion shape. Acoustic features include measures of echogenicity, heterogeneity and shadowing, computed by generating spectral-parameter images of the lesion and surrounding tissue. Spectral-parameter values are derived from rf echo signals at each pixel using a sliding-window Fourier analysis. We derive quantitative acoustic features from spectral-parameter maps of the lesion and adjacent areas. We quantify morphometric features by geometric and fractal analysis of traced lesion boundaries. Initial results on biopsy-proven cases show that although a single parameter cannot reliably discriminate cancerous from noncancerous breast lesions, multi-feature analysis provides excellent discrimination for this data set. We have processed data for 130 biopsy-proven patients, acquired during routine ultrasonic examinations at three clinical sites and produced an area under the receiver-operating-characteristics (ROC) curve of 0.947 +/- 0.045. Among the quantitative descriptors, lesion-margin definition, spiculation and border irregularity are the most useful; some additional morphometric features (such as border irregularity) also are particularly effective in lesion classification. Our findings are consistent with many of the BI-RADS (Breast Imaging Reporting and Data System) breast-lesion-classification criteria in use today.

High-frequency ultrasound (HFU) offers a means of investigating biologic tissue at the microscopic level. High-frequency, three-dimensional (3-D) quantitative-ultrasound (QUS) methods were developed to characterize freshly-dissected lymph nodes of cancer patients. Three-dimensional ultrasound data were acquired from lymph nodes using a 25.6-MHz center-frequency transducer. Each node was inked prior to tissue fixation to recover orientation after sectioning for 3-D histologic evaluation. Backscattered echo signals were processed using 3-D cylindrical regions-of-interest to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept and slope). QUS estimates were computed following established methods using two scattering models. In this study, 46 lymph nodes acquired from 27 patients diagnosed with colon cancer were processed. Results revealed that fully-metastatic nodes could be perfectly differentiated from cancer-free nodes using slope or scatterer-size estimates. Specifically, results indicated that metastatic nodes had an average effective scatterer size (i.e., 37.1 +/- 1.7 microm) significantly larger (p < 0.05) than that in cancer-free nodes (i.e., 26 +/- 3.3 microm). Therefore, the 3-D QUS methods could provide a useful means of identifying small metastatic foci in dissected lymph nodes that might not be detectable using current standard pathology procedures., (Copyright 2010 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

The cornea's acoustic properties (speed-of-sound, backscatter, attenuation) are related to its state of hydration. Our aim was to determine these properties as a function of corneal hydration using high-frequency ultrasound. Bovine corneas were suspended in a Dexsol-equivalent corneal preservation medium at 33 degrees C and then immersed successively in 75%, 50% and 25% medium and distilled water. Using a 38-MHz focused ultrasound transducer, we measured speed-of-sound and corneal thickness (n = 8) and stromal backscatter (n = 6) after 45-min immersion in each medium. Corneal speed-of-sound was modeled as a function of corneal thickness. We found the mean speed-of-sound to be 1605.4 +/- 2.9 m/s in normotensive medium. The maximum observed speed-of-sound was 1616 m/s. As we decreased medium tonicity, the cornea swelled and the speed-of-sound decreased, reaching 1563.0 +/- 2.2 m/s in water. Average corneal thickness increased from 969 +/- 93 microm in 100% medium to 1579 +/- 104 microm in water. Going from 100% medium to water, stromal backscatter (midband-fit) increased from -60.0 +/- 0.8 dBr to -52.5 +/- 3.5 dBr, spectral slope increased from -0.119 +/- 0.021 to -0.005 +/- 0.030 dB/MHz and attenuation coefficient decreased from 0.927 +/- 0.434 to 0.010 +/- 0.581 dB/cm-MHz. The observed correlation between acoustic backscatter and attenuation with the speed-of-sound offers a potential means for more accurate determination of speed-of-sound and, hence, thickness in edematous corneas.

Brachytherapy to treat prostate cancer uses transrectal ultrasound to guide implantation of titanium-shelled radioactive seeds. Transperitoneal implantation allows errors in placement that cause suboptimal dosimetry. Conventional ultrasound cannot reliably image implanted seeds; therefore, seed misplacements cannot be corrected in the operating room. Previously, an algorithm based on singular spectrum analysis was shown to image palladium seeds better than B-mode ultrasound could. The algorithm is now applied to imaging an iodine seed in gel and in beef tissue as a function of seed angle relative to the incident ultrasound. Results indicate that both seed types are imaged reliably by the algorithm.

Transrectal-ultrasound-guided brachytherapy uses small titanium-shelled radioactive seeds to locally treat prostate cancer. During the implantation procedure, needles inserted transperitoneally cause gland movement resulting in seed misplacement and suboptimal dosimetry. In a previous study, an algorithm based on singular spectrum analysis (SSA) applied to envelope-detected ultrasound signals was proposed to determine seed locations [J. Mamou and E. J. Feleppa, J. Acoust. Soc. Am. 121, 1790-1801 (2007)]. Successful implementation of the SSA algorithm could allow correcting dosimetry errors during the implantation procedure. The algorithm demonstrated promise when the seed orientation was parallel to the needle and normal to the ultrasound beam. In this present study, the algorithm was tested when the seed orientation deviated up to 22 degrees from normality. Experimental data from a seed in an ideal environment and in beef were collected with a single-element, spherically focused, 5 MHz transducer. Simulations were designed and evaluated with the algorithm. Finally, objective quantitative scoring metrics were developed to evaluate the algorithm performance and for comparison with B-mode images. The results quantitatively established that the SSA algorithm always outperformed B-mode images and that seeds could be detected accurately up to a deviation of approximately 10 degrees .

Improved means of imaging prostate cancer would enable more-effective biopsy and treatment guidance and potentially would provide a reliable means of monitoring non-surgical therapy. Current, commonly used, conventional means of imaging the prostate do not reliably depict cancerous lesions, and as a result, biopsy needles are placed with respect to visible anatomic features of the gland, treatment tends to involve the entire gland, and monitoring of non-surgical therapy is based predominantly on blood PSA levels, and in many cases, periodic biopsies. Conventional transrectal ultrasound often is the imaging modality of choice for prostate biopsy and treatment procedures, but it offers no advantages in terms of reliably depicting cancerous regions of the gland. However, new methods of tissue-type imaging that are based on spectrum analysis of echo signals and that utilize artificial neural networks for classification offer promise of reliably distinguishing cancerous lesions from non-cancerous tissue in the prostate. The classifier produced an ROC-curve area of 0.84 for 617 biopsied locations compared to areas of 0.64 for conventional assessments of the same locations in biopsy-guidance B-mode images. The potential improvement in imaging sensitivity implied by the ROC curves is more than 50%. If current validation studies confirm these initial results, then an effective, inexpensive, noninvasive means of imaging prostate-cancer foci and therefore of guiding biopsies and treatments will be available to urologists and radiation oncologists.

Ultrasound-guided brachytherapy using titanium-shelled radioactive seeds is a popular, effective means of treating prostate cancer. Unfortunately, implantation using needles inserted transperitoneally causes gland movement and distortion, which often results in seed misplacement and dosimetry errors. If actual seed locations could be determined in the operating room, then corrections to dosimetry errors could be made immediately. However, seed specularity, shadowing, and tissue clutter make imaging seeds difficult using conventional ultrasound. Singular spectrum analysis (SSA) shows promise for reliably imaging radioactive seeds implanted in the prostate and enabling additional corrective implantations to be made in the operating room. SSA utilizes eigenvalues derived from the diagonalized correlation matrix of envelope-detected radio-frequency echo signals to yield a P value indicative of the likelihood of a seed-specific repetitive signal. We demonstrated the potential of SSA for seed detection and imaging and illustrated the trade-off considerations for optimization of SSA in clinical applications using simulations assessing performance as a function of different levels of noise and the presence of repetitive signals with various repetition periods; experiments in an ideal scattering environment; and experiments using seeds implanted in beef.

Several factors affect the accuracy and precision of ultrasonic spectrum analysis, which is used for characterization of normal and diseased tissue in a variety of organs. For example, averaging procedures and the sequence of operations affect the accuracy and precision of spectrum analysis. Averaging procedures and logarithmic conversion (i.e., conversion to dB) introduce a constant bias that affects spectral amplitudes and the values of intercept and midband fit; the bias depends on the sequencing of the log conversion and averaging as well as the number of independent spectra or spectral parameters that are averaged. We derive expressions that permit correction of such biases. Furthermore, we show that standard deviations for slope and midband-fit estimation can be minimized by averaging spectra before dB conversion and before computing spectral parameters by linear regression. Experimental results using phantoms agree remarkably with theoretical predictions for the data window functions studied in this article, Hamming and rectangular.

Spectral parameter imaging in both the fundamental and harmonic of backscattered radio-frequency (RF) data were used for immediate visualization of high-intensity focused ultrasound (HIFU) lesion sites. A focused 5-MHz HIFU transducer with a coaxial 9-MHz focused single-element diagnostic transducer was used to create and scan lesions in chicken breast and freshly excised rabbit liver. B-mode images derived from the backscattered RF signal envelope were compared with midband fit (MBF) spectral parameter images in the fundamental (9-MHz) and harmonic (18-MHz) bands of the diagnostic probe. Images of HIFU-induced lesions derived from the MBF to the calibrated spectrum showed improved contrast (approximately 3 dB) of tumor margins versus surround compared with images produced from the conventional signal envelope. MBF parameter images produced from the harmonic band showed higher contrast in attenuated structures (core, shadow) compared with either the conventional envelope (3.3 dB core; 11.6 dB shadow) or MBF images of the fundamental band (4.4 dB core; 7.4 dB shadow). The gradient between the lesion and surround was 3.4 dB/mm, 6.9 dB/mm and 17.2 dB/mm for B-mode, MBF-fundamental mode and MBF-harmonic mode, respectively. Images of threshold and "popcorn" lesions produced in freshly excised rabbit liver were most easily visualized and boundaries best-defined using MBF-harmonic mode.

Objective: This study evaluated variables relevant to creating myocardial lesions using high-intensity focused ultrasound (HIFU). Without an effective means of tracking heart motion, lesion formation in the moving ventricle can be accomplished by intermittent delivery of HIFU energy synchronized by electrocardiographic triggering. In anticipation of future clinical applications, multiple lesions were created by brief HIFU pulses in calf myocardial tissue ex vivo., Methods: Experiments used f-number 1.1 spherical cap HIFU transducers operating near 5 MHz with in situ spatial average intensities of 13 and 7.4 kW/cm2 at corresponding depths of 10 and 25 mm in the tissue. The distance from the HIFU transducer to the tissue surface was measured with a 7.5-MHz A-mode transducer coaxial and confocal with the HIFU transducer. After exposures, fresh, unstained tissue was dissected to measure visible lesion length and width. Lesion dimensions were plotted as functions of pulse parameters, cardiac structure, tissue temperature, and focal depth., Results: Lesion size in ex vivo tissue depended strongly on the total exposure time but did not depend strongly on pulse duration. Lesion width depended strongly on the pulse-to-pulse interval, and lesion width and length depended strongly on the initial tissue temperature., Conclusions: High-intensity focused ultrasound creates well-demarcated lesions in ex vivo cardiac muscle without damaging intervening or distal tissue. These initial studies suggest that HIFU offers an effective, noninvasive method for ablating myocardial tissues to treat several important cardiac diseases.

Very high frequency ultrasound (35-50 MHz) has had a significant impact upon clinical imaging of the anterior segment of the eye, offering an axial resolution as small as 30 microm. Higher frequencies, while potentially offering even finer resolution, are more affected by absorption in ocular tissues and even in the fluid coupling medium. Our aim was to develop and apply improved transducer technology utilizing frequencies beyond those routinely used for ultrasound biomicroscopy of the eye. A 75-MHz lithium niobate transducer with 2 mm aperture and 6 mm focal length was fabricated. We scanned the ciliary body and cornea of a human eye six years post-LASIK. Spectral parameter images were produced from the midband fit to local calibrated power spectra. Images were compared with those produced using a 35 MHz lithium niobate transducer of similar fractional bandwidth and focal ratio. The 75-MHz transducer was found to have a fractional bandwidth (-6 dB) of 61%. Images of the post-LASIK cornea showed higher stromal backscatter at 75 MHz than at 35 MHz. The improved lateral resolution resulted in better visualization of discontinuities in Bowman's layer, indicative of microfolds or breaks occurring at the time of surgery. The LASIK surface was evident as a discontinuity in stromal backscatter between the stromal component of the flap and the residual stroma. The iris and ciliary body were visualized despite attenuation by the overlying sclera. Very high frequency ultrasound imaging of the anterior segment of the eye has been restricted to the 35-50 MHz band for over a decade. We showed that higher frequencies can be used in vivo to image the cornea and anterior segment. This improvement in resolution and high sensitivity to backscatter from the corneal stroma will provide benefits in clinical diagnostic imaging of the anterior segment.

Objective: As are the attenuation coefficient and sound speed, the backscatter coefficient is a fundamental ultrasonic property that has been used to characterize many tissues. Unfortunately, there is currently far less standardization for the ultrasonic backscatter measurement than for the other two, as evidenced by a previous American Institute of Ultrasound in Medicine (AIUM)-sponsored interlaboratory comparison of ultrasonic backscatter, attenuation, and speed measurements (J Ultrasound Med 1999; 18:615-631). To explore reasons for these disparities, the AIUM Endowment for Education and Research recently supported this second interlaboratory comparison, which extends the upper limit of the frequency range from 7 to 9 MHz., Methods: Eleven laboratories were provided with standard test objects designed and manufactured at the University of Wisconsin (Madison, WI). Each laboratory was asked to perform ultrasonic measurements of sound speed, attenuation coefficients, and backscatter coefficients. Each laboratory was blinded to the values of the ultrasonic properties of the test objects at the time the measurements were performed., Results: Eight of the 11 laboratories submitted results. The range of variation of absolute magnitude of backscatter coefficient measurements was about 2 orders of magnitude. If the results of 1 outlier laboratory are excluded, then the range is reduced to about 1 order of magnitude. Agreement regarding frequency dependence of backscatter was better than reported in the previous interlaboratory comparison. For example, when scatterers were small compared with the ultrasonic wavelength, experimental frequency-dependent backscatter coefficient data obtained by the participating laboratories were usually consistent with the expected Rayleigh scattering behavior (proportional to frequency to the fourth power)., Conclusions: Greater standardization of backscatter measurement methods is needed. Measurements of frequency dependence of backscatter are more consistent than measurements of absolute magnitude.

In conventional elastography, internal tissue deformations, induced by external compression applied to the tissue surface, are estimated by cross-correlation analysis of echo signals obtained before and after compression. Conventionally, strains are estimated by computing the gradient of estimated displacement. However, gradient-based algorithms are highly susceptible to noise and decorrelation, which could limit their utility. We previously developed strain estimators based on a frequency-domain (spectral) formulation that were shown to be more robust but less precise compared to conventional strain estimators, In this paper, we introduce a novel spectral strain estimator that estimates local strain by maximizing the correlation between the spectra of pre- and postcompression echo signals using iterative frequency-scaling of the latter; we also discuss a variation of this algorithm that may be computationally more efficient but less precise. The adaptive spectral strain estimator combines the advantages of time- and frequency-domain methods and has outperformed conventional estimators in experiments and 2-D finite-element simulations.

Because current methods of imaging prostate cancer are inadequate, biopsies cannot be effectively guided and treatment cannot be effectively planned and targeted. Therefore, our research is aimed at ultrasonically characterizing cancerous prostate tissue so that we can image it more effectively and thereby provide improved means of detecting, treating and monitoring prostate cancer. We base our characterization methods on spectrum analysis of radiofrequency (rf) echo signals combined with clinical variables such as prostate-specific antigen (PSA). Tissue typing using these parameters is performed by artificial neural networks. We employed and evaluated different approaches to data partitioning into training, validation, and test sets and different neural network configuration options. In this manner, we sought to determine what neural network configuration is optimal for these data and also to assess possible bias that might exist due to correlations among different data entries among the data for a given patient. The classification efficacy of each neural network configuration and data-partitioning method was measured using relative-operating-characteristic (ROC) methods. Neural network classification based on spectral parameters combined with clinical data generally produced ROC-curve areas of 0.80 compared to curve areas of 0.64 for conventional transrectal ultrasound imaging combined with clinical data. We then used the optimal neural network configuration to generate lookup tables that translate local spectral parameter values and global clinical-variable values into pixel values in tissue-type images (TTIs). TTIs continue to show cancerous regions successfully, and may prove to be particularly useful clinically in combination with other ultrasonic and nonultrasonic methods, e.g., magnetic-resonance spectroscopy.

Purpose: The aim of this in vitro study was to assess the feasibility of using high-frequency sonography to identify colorectal lymph nodes and to diagnose colorectal lymph node metastasis., Methods: In part 1 of this study, resected colorectal tissues from 13 patients with colorectal cancer were scanned in a water bath using B-mode sonography performed at high frequency (10 MHz) to identify lymph nodes. The colorectal tissues were then carefully dissected to remove all lymph nodes. Detectability was calculated as the ratio of the number of sonographically detected nodes to the total number of histopathologically confirmed nodes. Student's t test was performed to compare sizes between these groups; a p value of less than 0.05 was considered significant. In part 2, 4 features of lymph nodes identified on B-mode sonography--size, shape, border, and echogenicity--and their combinations were evaluated for their ability to diagnose lymph node metastasis. Discriminant and receiver operating characteristic curve analyses were performed., Results: In part 1, B-mode sonography performed in vitro detected 79 (48%) of the 165 histopathologically identified lymph nodes and 34 (87%) of the 39 histopathologically identified metastatic nodes. The mean size, or mean longest axis (+/- standard deviation), of the sonographically detected nodes (6.4 +/- 2.9 mm) was significantly larger than that of undetected nodes (3.6 +/- 1.7 mm; p < 0.01). In part 2, the most effective feature distinguishing metastatic from nonmetastatic lymph nodes was echogenicity, followed by size, shape, and border. However, a combination of at least 2 features (eg, echogenicity and size) provided better distinction of nodes than did any 1 feature. In the receiver operating characteristic curve of the 4-feature combination, an increase in sensitivity is accompanied by a decrease in specificity: at a sensitivity of 100%, specificities decreased to 60% or less. However, even with the optimal combination of features, the sensitivity and specificity did not both reach 85% at any operating point., Conclusions: The results of this node-by-node in vitro study show the current limitations and potential of sonography for assessing colorectal lymph nodes. High-frequency sonography may be insufficient for identifying lymph node metastasis in colorectal cancer., (Copyright 2003 Wiley Periodicals, Inc.)

Purpose: We explored the clinical usefulness of spectrum analysis and neural networks for classifying prostate tissue and identifying prostate cancer in patients undergoing transrectal ultrasound for diagnostic or therapeutic reasons., Materials and Methods: Data on a cohort of 215 patients who underwent transrectal ultrasound guided prostate biopsies at Memorial-Sloan Kettering Cancer Center, New York, New York were included in this study. Radio frequency data necessary for 2 and 3-dimensional (D) computer reconstruction of the prostate were digitally recorded at transrectal ultrasound and prostate biopsy. The data were spectrally processed and 2-D tissue typing images were generated based on a pre-trained neural network classification. We used manually masked 2-D tissue images as building blocks for generating 3-D tissue images and the images were tissue type color coded using custom software. Radio frequency data on the study cohort were analyzed for cancer probability using the data set pre-trained by neural network methods and compared with conventional B-mode imaging. ROC curves were generated for the 2 methods using biopsy results as the gold standard., Results: The mean area under the ROC curve plus or minus SEM for detecting prostate cancer for the conventional B-mode and neural network methods was 0.66 +/- 0.03 and 0.80 +/- 0.05, respectively. Sensitivity and specificity for detecting prostate cancer by the neural network method were significantly increased compared with conventional B-mode imaging. In addition, the 2 and 3-D prostate images provided excellent visual identification of areas with a higher likelihood of cancer., Conclusions: Spectrum analysis could significantly improve the detection and evaluation of prostate cancer. Routine real-time application of spectrum analysis may significantly decrease the number of false-negative biopsies and improve the detection of prostate cancer at transrectal ultrasound guided prostate biopsy. It may also provide improved identification of prostate cancer foci during therapeutic intervention, such as brachytherapy, external beam radiotherapy or cryotherapy. In addition, 2 and 3-D images with prostate cancer foci specifically identified can help surgical planning and may in the distant future be an additional reliable noninvasive method of selecting patients for prostate biopsy.

Ultrasound has been a popular clinical imaging modality for decades. It is well established as a means of displaying the macroscopic anatomy of soft-tissue structures. While conventional ultrasound methodologies (i.e., B-mode and Doppler methods) are well proven and continue to advance technically on a daily basis, e.g. by extending into higher frequencies and taking advantage of harmonic phenomena in tissues, fundamentally new ultrasound technologies also are emerging and offer exciting promise for making significant improvements in the clinical imaging of disease. These emerging methods include spectrum analysis, elasticity imaging, contrast-agent methods, and advanced flow detection and measurement techniques. Each provides independent information and, used alone, each can provide powerful new imaging capabilities; combined with each other, their capabilities may be even greater in many applications; and all in principle can be used in concert with other imaging modalities to offer the possibility of further improvements in disease detection, evaluation, and monitoring.

Conventional B-mode ultrasound is the standard means of imaging the prostate for guiding prostate biopsies and planning brachytherapy of prostate cancer. Yet B-mode images do not allow adequate visualization of cancerous lesions of the prostate. Ultrasonic tissue-typing imaging based on spectrum analysis of radiofrequency echo signals has shown promise for overcoming the limitations of B-mode imaging for visualizing prostate tumors. Tissue typing based on radiofrequency spectrum analysis uses nonlinear methods, such as neural networks, to classify tissue by using spectral-parameter and clinical-variable values. Two- and three-dimensional images based on these methods show potential for improving the guidance of prostate biopsies and the targeting of radiotherapy of prostate cancer. Two-dimensional images have been imported into instrumentation for real-time biopsy guidance and into commercial dose-planning software for brachytherapy planning. Three-dimensional renderings seem to be capable of depicting locations and volumes of cancer foci.

Conventional B-mode ultrasound currently is the standard means of imaging the prostate for guiding prostate biopsies and planning brachytherapy to treat prostate cancer. Yet B-mode images do not adequately display cancerous lesions of the prostate. Ultrasonic tissue-type imaging based on spectrum analysis of radiofrequency (rf) echo signals has shown promise for overcoming the limitations of B-mode imaging for visualizing prostate tumors. This method of tissue-type imaging utilizes nonlinear classifiers, such as neural networks, to classify tissue based on values of spectral parameter and clinical variables. Two- and three-dimensional images based on these methods demonstrate potential for guiding prostate biopsies and targeting radiotherapy of prostate cancer. Two-dimensional images are being generated in real time in ultrasound scanners used for real-time biopsy guidance and have been incorporated into commercial dosimetry software used for brachytherapy planning. Three-dimensional renderings show promise for depicting locations and volumes of cancer foci for disease evaluation to assist staging and treatment planning, and potentially for registration or fusion with CT images for targeting external-beam radiotherapy.

Although conventional ultrasonography has proven to be clinically useful for depicting many types of cancerous lesions, it cannot distinguish reliably between cancerous and noncancerous tissue of the prostate. Therefore, conventional transrectal ultrasonography (TRUS) is used primarily for general evaluations of the gland and for guiding biopsies based on clearly imaged anatomic features such as the capsule, seminal vesicles, and urethra. Spectrum analysis extracts ultrasound signal parameters associated with biopsy-proven tissue types, and these parameters are then classified using neural network tools such as learning vector quantization, radial basis, and multilayer perceptron algorithms. Classification of cancerous and noncancerous prostate tissue using neural networks produces receiver operating characteristic (ROC) curves of 0.87 +/- 0.04 compared with 0.64 +/- 0.04 for conventional ultrasonography. To image the prostate using these methods, parameter values are computed at each pixel location, then translated into a score for the likelihood of cancer using a look-up table generated using the best classification algorithm. The score for cancer likelihood is expressed as a gray-scale or color value, and the resulting image may be useful to guide biopsies or therapy. Changes in parameter or score values over time potentially can be used to assess progression of disease or efficacy of therapy.

In a study involving 10 different sites, independent results of measurements of ultrasonic properties on equivalent tissue-mimicking samples are reported and compared. The properties measured were propagation speed, attenuation coefficients, and backscatter coefficients. Reasonably good agreement exists for attenuation coefficients, but less satisfactory results were found for propagation speeds. As anticipated, agreement was not impressive in the case of backscatter coefficients. Results for four sites agreed rather well in both absolute values and frequency dependence, and results from other sites were lower by as much as an order of magnitude. The study is valuable for laboratories doing quantitative studies.

Axillary lymph node status is an important factor for staging and treatment planning in breast cancer. Our study was performed in vitro on a node-by-node basis to evaluate the ability of B-mode ultrasonographic images to distinguish metastatic from nonmetastatic nodes. Immediately prior to histologic examination, individual dissected axillary nodes were scanned in a water bath using a 10 MHz B-mode ultrasonographic transducer. Four B-mode features (size, circularity, border demarcation, and internal echo) were evaluated for their ability to distinguish metastatic from nonmetastatic lymph nodes. Lymph node metastasis was indicated by (1) a large size (i.e., a length of the longest axis of 10 mm or greater); (2) a circular shape (i.e., the ratio of the shortest axis to the longest axis between 0.5 and 1.0); (3) a sharply demarcated border compared with surrounding fatty tissue; and (4) a hypoechoic internal echo, with obliteration of the fatty hilum. The sensitivity and specificity were compared for all combinations of features. We examined 84 histologically characterized axillary nodes from 27 breast cancer patients, including 64 nonmetastatic and 20 metastatic nodes. Of the criteria cited, circular shape was the best single feature for distinguishing metastatic from nonmetastatic nodes (sensitivity, 65%; specificity, 73%). The best combination of sensitivity (85%) and specificity (73%) was obtained using the criterion that a lymph node contained cancer when at least three positive features were present. The present in vitro study demonstrated that the sensitivity and specificity of B-mode ultrasonography for diagnosing lymph node metastasis were lower than 90%. Therefore, B-mode ultrasonography may not be an optimal noninvasive screening method for diagnosing axillary lymph node metastasis in breast cancer patients, particularly under in vivo clinical conditions.

Spectrum analysis of radiofrequency (RF) ultrasonic echo signals often can sense tissue differences that are not visible on conventional ultrasonic images. Spectrum-analysis parameter values combined with other variables, such as serum prostate specific antigen (PSA) concentration, can be classified by neural networks to distinguish effectively between cancerous and noncancerous prostate tissues. Images based on neural network classification of spectral parameters and clinical variables can be advantageous for biopsy guidance, staging, and treatment planning and monitoring. A study based on 644 biopsies from 137 patients showed that these methods are significantly superior to B-mode image interpretation for differentiating cancerous from noncancerous prostate tissues. Using the histologic determination of tissue types as the gold standard, the area under the receiver-operator characteristic (ROC) curve for neural network classification based on spectrum analysis and PSA value for the 644 biopsies was 0.87 +/- 0.04, and the ROC curve are for a level-of-suspicion (LOS) assignment based on B-mode imaging was 0.64 +/- 0.04. Color-encoded and gray-scale images derived from neural network assignment of suspicion for cancer at each pixel location showed remarkable detail and suggested potential clinical value for biopsy guidance using real-time two-dimensional (2D) images and staging, treatment planning, and monitoring using three-dimensional (3D) images.

This in vitro study investigated the ability of ultrasonic tissue characterization (UTC) to discriminate between plaques from asymptomatic and symptomatic patients and to compare UTC findings with quantitative measurements of plaque morphology. A total of 34 plaque specimens removed at carotid endarterectomy were scanned transversely at intervals of 1 mm, and compared to tissue cross-sections examined by optical microscopy employing computer-assisted planimetry. UTC was performed by spectral analysis of backscattered radiofrequency signals. The slope, intercept and total power parameters of the spectrum were evaluated. Discriminant analysis was used to compare the ability of the UTC spectral parameters and morphological constituents to correctly classify plaques according to their symptom group membership. UTC correctly classified 88.2% of the plaques. Thrombus was present in 93.9% of the plaques, and there was little difference in the morphological constituents of plaques from asymptomatic and symptomatic patients. Morphological constituents correctly classified 60.7% of the plaques. We conclude, in this preliminary study, that UTC can discriminate between carotid plaques from asymptomatic and symptomatic patients with moderate accuracy, despite a similarity in their morphological composition. UTC discrimination is not related to differences in the type or amount of morphological constituents in the plaques.

Axillary lymph node status is of particular importance for staging and managing breast cancer. Currently, axillary lymph node dissection is performed routinely in cases of invasive breast cancer because of the lack of accurate noninvasive methods for diagnosing lymph node metastasis. We investigated the diagnostic ability of ultrasonic tissue characterization based on spectrum analysis of backscattered echo signals to detect axillary lymph node metastasis in breast cancer in vitro compared with in vitro B-mode imaging. Immediately after surgery, individual lymph nodes were isolated from axillary tissue. Each lymph node was scanned in a water bath using a 10-MHz instrument, and radio frequency data and B-mode images were acquired. Spectral parameter values were calculated, and discriminant analysis was performed to classify metastatic and nonmetastatic lymph nodes. Forty histologically characterized axillary lymph nodes were enrolled in this study, including 25 nonmetastatic and 15 metastatic lymph nodes. A significant difference existed in the spectral parameter values (slope and intercept) for metastatic and nonmetastatic lymph nodes. Spectral parameter-based discriminant function classification of metastatic vs. nonmetastatic lymph nodes provided a sensitivity of 93.3%, specificity of 92.0%, and overall accuracy of 92.5%. In comparison, B-mode ultrasound images of in vitro lymph nodes provided a sensitivity of 73.3%, specificity of 84.0%, and overall accuracy of 80.0%. Receiver operating characteristic (ROC) analysis comparing the efficacy of both methods gave an ROC curve area of 0.9888 for spectral methods, which was greater than the area of 0.8980 for B-mode ultrasound. Hence, this in vitro study suggests that the diagnostic ability of spectrum analysis may prove to be markedly superior to that of B-mode ultrasound in detecting axillary lymph node metastasis in breast cancer. Because of these encouraging results, we intend to conduct an investigation of the ability of spectral methods to classify metastatic axillary lymph nodes in vivo.

Lymph node involvement is one of the major factors affecting the prognosis of colorectal cancer. Various imaging methods, including ultrasound and computed tomography, are not sufficiently sensitive or specific for reliably determining lymph node involvement. We investigated the feasibility of using ultrasonic tissue characterization (UTC) based on spectrum analysis of backscattered echo signals for diagnosing lymph node metastasis of colorectal cancer in vitro. Forty lymph nodes, including 17 metastatic and 23 nonmetastatic nodes, from 11 colorectal cancer operations were investigated. Lymph nodes were scanned using a clinical instrument; B-mode imaging was performed for each lymph node, and radiofrequency (RF) data were acquired. The UTC parameters, slope and intercept, were calculated from the normalized power spectrum of the backscattered echo signals from each lymph node. The mean values of UTC parameters of metastatic and nonmetastatic lymph nodes were compared. The accuracy of UTC in distinguishing metastatic from nonmetastatic lymph nodes was calculated using discriminant analysis. Receiver operating characteristic (ROC) analysis was performed to compare the classification efficacy of UTC and B-mode ultrasound. UTC parameters demonstrated a significant difference in parameter values between metastatic and nonmetastatic lymph nodes. The overall accuracy in diagnosing the lymph node metastasis was 87.5% for UTC and 77.5% for B-mode ultrasound. ROC analysis produced an ROC curve area of 0.92 or 0.89 for UTC (depending on the performance-assessment algorithm) and 0.84 for B-mode ultrasound, which indicated that UTC performed markedly better than B-mode ultrasound in diagnosing metastatic lymph nodes. The advantages of UTC over conventional B-mode ultrasound in discriminating metastatic lymph nodes from nonmetastatic lymph nodes are extremely encouraging, and warrant an in vivo UTC study.

This study examines the statistics of ultrasonic spectral parameter images that are being used to evaluate tissue microstructure in several organs. The parameters are derived from sliding-window spectrum analysis of radiofrequency echo signals. Calibrated spectra are expressed in dB and analyzed with linear regression procedures to compute spectral slope, intercept and midband fit, which is directly related to integrated backscatter. Local values of each parameter are quantitatively depicted in gray-scale cross-sectional images to determine tissue type, response to therapy and physical scatterer properties. In this report, we treat the statistics of each type of parameter image for statistically homogeneous scatterers. Probability density functions are derived for each parameter, and theoretical results are compared with corresponding histograms clinically measured in homogeneous tissue segments in the liver and prostate. Excellent agreement was found between theoretical density functions and data histograms for homogeneous tissue segments. Departures from theory are observed in heterogeneous tissue segments. The results demonstrate how the statistics of each spectral parameter and integrated backscatter are related to system and analysis parameters. These results are now being used to guide the design of system and analysis parameters, to improve assays of tissue heterogeneity and to evaluate the precision of estimating features associated with effective scatterer sizes and concentrations.

We evaluated the ability of ultrasonic tissue characterization (UTC), based on backscattered echo signals, to distinguish among the components of advanced carotid plaques. We performed spectral analysis of echo signals acquired from human carotid endarterectomy specimens in vitro to calculate three parameters of the calibrated power spectrum: slope, intercept and total power for fibrous, lipid pool and thrombus constituents of plaque. Plaque constituents were identified histologically. We evaluated classification efficacy by discriminant function analysis. Slope and intercept parameters alone provided correct classification in 92.5%, 57.6% and 72.4% of fibrous, lipid pool and thrombus plaque components, respectively. Slope, intercept and total power used in combination improved classification of the three tissue types to 93.0%, 69.7% and 81.0%. The overall proportion of correctly classified tissue regions increased from 84.5% to 88.0% by the combined use of the three parameters. The improvement in classification that occurred when we included total power as a third parameter suggests that ultrasound plaque components may not consist solely of small, randomly distributed isotropic scatterers. Our ability to identify plaque thrombi provides motivation for future studies of parameter-based imaging methods for identifying such plaque that presents an increased risk of embolic neurologic ischemic events.

Purpose: The intent of the study was to determine whether ultrasonic tissue characterization (UTC) could indicate acuteness and stability of deep venous thrombosis (DVT) of the lower extremities., Methods: Thrombi presenting as filling defects on color Doppler imaging in the common or superficial femoral or popliteal veins in 50 extremities in 45 patients with DVT were studied. Acute DVT was less than 4 days duration, and chronic DVT was greater than 21 days duration. UTC analysis of parameters from the normalized power spectrum of backscattered ultrasound signals from venous filling defects was performed. This spectrum approaches a straight line, and its basic parameters, slope, and Y-intercept are related to scatterer size, concentration, and the square of the scatterer-to-medium acoustic impedances. Ten of the DVT extremities were reexamined at 1 week to assess UTC changes that would indicate thrombus instability., Results: Acute DVT (19 of the 50 extremities) could be distinguished from chronic DVT, mainly on the basis of significantly higher intercept values for the acute group, which were 11.6 relative decibels (dBr) higher than those of the chronic DVT group. Discriminant linear analysis of the two parameters indicated a sensitivity of 94.7% and specificity of 90.3% in correctly diagnosing acute DVT. In a small sample of 10 extremities reexamined at 1 week, acute DVT extremities showed a mean 9.4 dBr decrease in intercept values with no significant change in slope., Conclusions: UTC distinguished clinically defined acute from chronic DVT. In a small series of extremities, UTC revealed significant instability of acute thrombi in a selected patient population.

Parameters of the power spectrum of backscattered echoes were applied to quantitatively evaluate red cell aggregation in vitro. Human red cell suspensions were circulated in a closed loop of tubing, and ultrasonic, radiofrequency, echo-signal data were obtained using a 10-MHz transducer. Data acquisition was performed at 30-s to 1-min intervals for 5 min after flow stoppage. Two parameters of the normalized power spectrum of the echo signals, spectral slope and Y-intercept, were computed, and estimates of two scattering properties, the scatterer size and acoustic concentration were calculated from these parameters using equations based on scattering theory. Size and acoustic concentration were observed as they changed over time after the stoppage of flow. The key findings were that hematocrit affected the rate of cell aggregation while fibrinogen controlled aggregate size and acoustic concentration.

In vitro experiments using weak scatterers ranging in size from mean longest diameter of 26.9 to 83.0 microns were performed to test the validity of theoretical predictions for scatterer size and concentration derived from normalized power spectrum parameters of ultrasonic backscatterer echoes. Scatterers consisting of cell clusters were suspended in collagen gel and scanned by a 10 MHz transducer system. Optical measurements validated theoretical predictions that (1) slope value is a function solely of scatterer size; (2) intercept value is a function of scatterer size and concentration; and (3) midband fit value increases as scatterer concentration increases, and, to a lesser extent, as size increases. These results were obtained under relatively ideal conditions of minimal attenuation and scatterer spacing (not closer than two scatterer diameters) and were consistent with the assumptions underlying the scattering theory.

The ability of ultrasonic tissue characterization to differentiate and classify benign and malignant breast tissues in vivo in patients with palpable breast masses and in vitro in excised breast tissue was evaluated. One-hundred and twenty-four in vivo and 89 in vitro studies were performed using a technique of UTC based on parameters from the power spectrum of backscattered echoes. Sensitivities and specificities for diagnosing carcinoma were 86 and 84% for in vivo studies and 94 and 92% for in vitro studies. These UTC parameters provided threshold values for color-coding breast lesion images. The results of this preliminary investigation suggest that UTC provides a basis for assessing more accurately lesions suspected of being malignant prior to biopsy and possibly for evaluating breast lesions noninvasively.

Purpose: The ability of ultrasonic tissue characterization based on radiofrequency signal processing to detect compositional differences in thrombi of varying ages was evaluated in vivo., Methods: Thrombi were produced in 49 jugular veins of 26 anesthetized 18 to 20 kg pigs by partial ligation and application of direct electric current. Thrombi were imaged 30 minutes after formation and 1, 7, and 14 days later with a color Doppler ultrasound scanner that identified the thrombi, and acquired radio frequency data for ultrasonic tissue characterization analysis. Ultrasonic tissue characterization used two parameters from the normalized power spectrum, slope, and intercept, which are related to scatterer size, scatterer concentration, and acoustic-impedance differences between scatterers and surrounding medium. Previous in vitro studies demonstrated that lower slope and higher intercept values correlated with greater cellularity and more-dense fibrin mesh. Histologic examination was performed for each time period. The values of slope and intercept for each timed observation were compared by a multilinear discriminant analysis., Results: There were no statistical differences between day 0 and day 1. Statistically-significant differences in ultrasonic tissue characterization parameters were seen between all other time intervals with p values < 0.01. Older thrombi tended to demonstrate higher slope and lower intercept values. These ultrasonic tissue characterization changes correlated with a red cell and fibrin-mesh density reduction, which was confirmed by histologic findings and was indicative of partial spontaneous thrombolysis. The degree of spontaneous thrombolysis provides an estimate of the age of thrombi., Conclusion: Ultrasonic tissue characterization is capable of distinguishing age differences in thrombi in an animal model and has the potential for noninvasive application in clinical diagnosis.