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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/mm3 with the RF echo signals thresholded to keep 5, 6, and 7-bit from the original 8-bit DR, respectively. The EAC correction algorithm reduced maximal errors to −3.71, −0.89, and −0.26 dB/mm3 when signals were thresholded at 5, 6, and 7-bit, respectively.

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 transverse-slice-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 probability-density 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 $\pm$ 0.025, 0.832 $\pm$ 0.086, and 0.968 $\pm$ 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.

INTRODUCTION: Thyroid cancer is the most common endocrine malignancy. While thyroid nodules (TN) can been seen in up to 50% of the adult population, only about 5 percent of the nodules are malignant. Currently, management of TN involves risk stratification prior to biopsy using B-mode grey-scale ultrasound (US) characteristics including echogenicity, micro- and macrocalcifications, and margins. A less-subjective method of TN evaluation, shear wave elastography, has been evaluated but both the grey-scale classification and elastography are subject to operator and machine variability. This study assesses the use of quantitative ultrasound (QUS) to differentiate between malignant and benign thyroid nodules. B-mode appearance based on the radiofrequency (RF) signal envelope and discards much of the information in the RF signal. QUS uses the normalized power spectrum and extracts discarded RF signal information to obtain parameters that reflect scatterer size, concentration and relative acoustic impedance. The advantage of using QUS is that the parameter values reflect the microarchitecture (

Thyroid cancer is the most-common endocrine malignancy in the world. The objective of this study was to investigate the suitability of quantitative ultrasound (QUS)for detecting thyroid cancer. Radio-frequency (RF)data were acquired from 53 patients using a GE Logiq E9 research ultrasound system equipped with a lO-MHz, ML6-l5 linear probe. QVS-estimate values, such as effective acoustic concentration (EAC), effective scatter diameter (ESD), and spectral parameters (i.e., midband fit (Mf), slope (SS), and intercept (I0))were derived using a reference-phantom method. Additional QUS estimates (i.e., μ and Ω)were derived from the envelope statistics of a Nakagami distribution. Estimate values were used to train a linear classifier, and performance was assessed using area-under-the-curve (AUC)values obtained from receiver operating characteristic (ROC)analyses based on lO-fold cross validation. Eight patients had pathology-confirmed thyroid cancer. A combination of EAC, I0, and μ produced an AUC value of 0.96. TI-RADS used alone by clinical thyroid sonographic experts produced an AUC of 0.94. A combination of TI-RADS, EAC, andμ produced an AUC value of 0.97. By achieving AUC values of 0.97, our initial results are very encouraging for developing a new objective and non-invasive tool for thyroid-cancer detection. These results suggest that QUS has promising potential to improve non-surgical evaluation of thyroid nodules.

Thyroid nodules suspicious for malignancy during clinical-ultrasound (US) evaluation undergo fine-needle-aspiration biopsy (FNAB) followed by cytological evaluation and, in indeterminate cases, an additional surgical intervention or molecular testing is recommended. Quantitative ultrasound (QUS) was investigated as a non-invasive approach to detect thyroid cancer and potentially reduce the currently large number of unnecessary FNABs. RF data were acquired from 225 nodules of 208 patients using a GE Logiq E9 US equipped with a 10-MHz linear-array probe. Five QUS estimates were computed throughout each nodule. Specifically, effective scatter diameter, effective scatter concentration, midband fit, and intercept were obtained using a reference-phantom method. The Nakagami shape parameter was computed using a maximum-likelihood estimator. Mean and standard deviations (SD) of QUS estimates within nodules were used for classification. QUS-based classification performance was quantified using area-under-the-curve (AUC) values obtained from receiver-operating- characteristic analyses. An AUC value of 0.77 was obtained using the SD of intercept alone; the value increased to 0.86 when five QUS estimates were linearly combined. Our in vivo results demonstrate the potential of QUS methods to detect cancerous nodules. Ultimately, the clinical protocol could be altered to prevent FNABs of nodules highly unlikely to be malignant based on QUS analysis.

Purpose: Transrectal ultrasound (TRUS)-guided needle biopsy is the current gold standard for prostate cancer diagnosis. However, up to 40% of prostate cancer lesions appears isoechoic on TRUS. Hence, TRUS-guided biopsy has a high false negative rate for prostate cancer diagnosis. Magnetic resonance imaging (MRI) is better able to distinguish prostate cancer from benign tissue. However, MRI-guided biopsy requires special equipment and training and a longer procedure time. MRI-TRUS fusion, where MRI is acquired preoperatively and then aligned to TRUS, allows for advantages of both modalities to be leveraged during biopsy. MRI-TRUS-guided biopsy increases the yield of cancer positive biopsies. In this work, the authors present multiattribute probabilistic postate elastic registration (MAPPER) to align prostate MRI and TRUS imagery. Methods: MAPPER involves (1) segmenting the prostate on MRI, (2) calculating a multiattribute probabilistic map of prostate location on TRUS, and (3) maximizing overlap between the prostate segmentation on MRI and the multiattribute probabilistic map on TRUS, thereby driving registration of MRI onto TRUS. MAPPER represents a significant advancement over the current state-of-the-art as it requires no user interaction during the biopsy procedure by leveraging texture and spatial information to determine the prostate location on TRUS. Although MAPPER requires manual interaction tomore » segment the prostate on MRI, this step is performed prior to biopsy and will not substantially increase biopsy procedure time. Results: MAPPER was evaluated on 13 patient studies from two independent datasets—Dataset 1 has 6 studies acquired with a side-firing TRUS probe and a 1.5 T pelvic phased-array coil MRI; Dataset 2 has 7 studies acquired with a volumetric end-firing TRUS probe and a 3.0 T endorectal coil MRI. MAPPER has a root-mean-square error (RMSE) for expert selected fiducials of 3.36 ± 1.10 mm for Dataset 1 and 3.14 ± 0.75 mm for Dataset 2. State-of-the-art MRI-TRUS fusion methods report RMSE of 3.06–2.07 mm. Conclusions: MAPPER aligns MRI and TRUS imagery without manual intervention ensuring efficient, reproducible registration. MAPPER has a similar RMSE to state-of-the-art methods that require manual intervention.« less

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

Previous studies by our group have shown that three-dimensional high-frequency quantitative ultrasound methods have the potential to differentiate metastatic lymph nodes from cancer-free lymph nodes dissected from human cancer patients. To successfully perform these methods inside the lymph node parenchyma, an automatic segmentation method is highly desired to exclude the surrounding thin layer of fat from quantitative ultrasound processing and accurately correct for ultrasound attenuation. In high-frequency ultrasound images of lymph nodes, the intensity distribution of lymph node parenchyma and fat varies spatially because of acoustic attenuation and focusing effects. Thus, the intensity contrast between two object regions (e.g., lymph node parenchyma and fat) is also spatially varying. In our previous work, nested graph cut demonstrated its ability to simultaneously segment lymph node parenchyma, 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 graph cut with locally adaptive energy to further deal with spatially varying distributions of lymph node parenchyma and fat caused by inhomogeneous acoustic attenuation. The proposed method achieved Dice similarity coefficients of 0.937+-0.035 when compared to expert manual segmentation on a representative dataset consisting of 115 three-dimensional lymph node images obtained from colorectal cancer patients.

We have developed a family of quantitative descriptors in order to provide noninvasive, reliable means of distinguishing benign from malignant breast lesions. These include acoustic descriptors (“echogenicity,” “heterogeneity,” “shadowing”) and morphometric descriptors (“area,” “aspect ratio,” “border irregularity,” “margin definition”). These quantitative descriptors are designed to be independent of instrument properties and physician expertise. Our analysis included manual tracing of lesion boundaries and adjacent areas on grayscale images generated from RF data. To derive quantitative acoustic features, we computed spectral-parameter maps of radio-frequency (RF) echo signals (using a sliding-window Fourier analysis) of the lesion and adjacent areas. We quantified morphometric features by geometric and fractal analysis of traced lesion boundaries. Although no single parameter can reliably discriminate cancerous from non-cancerous breast lesions, multi-feature analysis provides excellent discrimination of cancerous and non-cancerous lesions. Our analysis of data acquired during routine ultrasonic examination of 130 biopsy-scheduled patients produced a receiver-operating characteristic (ROC) area under the curve (AUC) of 0.947±0.045. Lesion-margin definition, spiculation, and border irregularity were the most useful among the quantitative descriptors; some morphometric features (such as border irregularity) also were particularly effective in lesion classification. Our results are consistent with many of the Breast Imaging Reporting and Data System (BI-RADS) breast-lesion-classification criteria in use today. DOI: http://dx.doi.org/10.3329/bjmp.v4i1.14672 Bangladesh Journal of Medical Physics Vol.4 No.1 2011 1-10

Choosing an appropriate dynamic range for acquiring radio-frequency (RF) data from a high-frequency ultrasound (HFU) system is challenging because the RF data amplitude typically covers several orders of magnitude between the sample surface and the deepest imaged regions. In addition, the saturated signal may decrease the accuracy of QUS methods because quantitative ultrasound (QUS) methods are sensitive to saturated data. In this study, the effects of saturation on QUS estimates of Nakagami shape parameter (Nakagami parameter) were quantified by analyzing data acquired from 20 dissected human lymph nodes with a single-element transducer operating at a center frequency of 26 MHz. Artificially saturated signals (x sat ) were produced by applying artificial saturation methods to the original unsaturated signals (x ori ). Saturation degree was quantified using an index termed Saturate-SNR (SSNR). Nakagami parameters were estimated from x sat over a wide range of SSNR values. Nakagami parameters of saturated signals were increased (0.18 when the signal decremented 2 bit) significantly with decreasing SSNR. Nakagami parameters were corrected by pretreatment that applied a smoothing spline to the saturated signal. The smoothing spline restoration method is tuned P parameter. The best correction occurred when P was 1 (i.e., cubic spline interpolation). The maximum Nakagami parameter error in the corrected with 6-bit signal was 0.10, which is less than the average difference of 0.12 that existed between non-metastatic and metastatic lymph nodes.

Quantitative acoustic microscopy (QAM) at 500 MHz permits measuring acoustic properties, such as speed of sound (SOS), attenuation (A) and acoustic impedance (Z), of tissue microstructure with a spatial resolution of 4 µm. Although high-frequency QAM has been shown to be a suitable tool for measuring the acoustic properties of several soft tissues, very few studies have been performed at 500 MHz, and none in cancerous lymph nodes (LNs). However, data at such fine resolutions are essential to improve our understanding of ultrasound scattering at lower frequencies (25 MHz) from LNs to detect clinically significant micrometastases. In this study, quantitative acoustic microscopy (QAM) at 500 MHz was performed to obtain 2D maps of speed of sound (c), attenuation (A), acoustic impedance (Z), and other derived acoustical parameters of nodal tissue microstructure with a spatial resolution of 4 µm. Thin section (i.e., 6-µm) of lymph nodes were scanned using a custom-built QAM system based on a novel F-1.08, 500-MHz transducer. The system digitized radio-frequency (RF) signals at 2.5 GHz with 12-bit accuracy.2D QAM maps of the acoustic parameters were obtained using custom a signal-processing algorithm. Following QAM scanning, the samples were stained using hematoxylin and eosin and imaged by light microscopy. The study illustrates that fine-resolution maps of acoustic properties of lymph nodes can be obtained and can provide previously unavailable information. Future studies will investigate the use of 2DZMs to improve the model of ultrasound scattering at 26 MHz. The new lymphnode-specific, ultrasound-scattering models could improve sensitivity and specificity of current QUS approaches for detecting metastatic regions in freshly excised lymph nodes from cancer patients.

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.

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 (p0.05) 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.

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.

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.

Because of time and cost constraints, current histological methods are unable to detect all clinically significant lymph-node metastases efficiently. Therefore, in previous studies, quantitative ultrasound (QUS) methods were developed to detect metastatic regions in freshly excised sentinel lymph nodes from breast-cancer patients using a 26-MHz transducer. A Gaussian form factor was used to obtain QUS estimates for cancer detection. In this study, quantitative acoustic microscopy (QAM) at 250 MHz was performed to obtain 2D maps of speed of sound (c), attenuation (A) and acoustic impedance (Z) of nodal tissue microstructure with a spatial resolution of 7 µm. These maps were used to develop new ultrasound-scattering models to improve understanding of ultrasound scattering in lymph nodes. In total, 17 12-µm thick sections from 12 lymph nodes were scanned using a custom-built QAM system based on an F-1.16, 250-MHz transducer (160-MHz bandwidth). Radio-frequency (RF) signals were digitized at 2.5 GHz with 12-bit accuracy, and 2D QAM maps of Z, A, and c were generated using custom-developed, signal-processing algorithms. Scanned samples were stained using hematoxylin and eosin and imaged by light microscopy. 2D Z maps (2DZMs) were then processed to yield a novel lymph-node-specific scattering model (i.e., form factor), which then was compared to the currently used Gaussian model. The new model was obtained by optimizing an exponential model fit to the Fourier transform of the autocorrelation of the 2DZMs that assumed isotropic scattering. The study illustrates that fine-resolution maps of acoustic properties of lymph nodes can improve the model of ultrasound scattering at 26 MHz. The new lymph-node-specific, ultrasound-scattering model is expected to improve current QUS approaches for detecting metastatic regions in freshly excised sentinel lymph nodes from breast-cancer patients.

To detect metastatic foci in excised human lymph nodes (LNs) using three-dimensional (3D), high-frequency quantitative ultrasound (QUS), the 3D envelope data must be accurately segmented into LN parenchyma (LNP), fat and normal saline (NS). However, automatic segmentation of the 3D data is challenging because of speckle as well as low contrast and intensity inhomogeneities caused by focusing and attenuation effects. We describe a novel method to automatically segment these media using initialization and refinement steps. In the first step, random forest classification (RFC) is employed for initial segmentation of the 3 media. To train the forest classifier and classify each voxel, features including backscattered energy, statistical parameters and contextual information are extracted from LN envelope data. In the second step, the initialization is refined by a 3-phase, local region-based, level-set segmentation method that uses the gamma probability density function as a statistical model of the envelope data. To handle depth-dependent data inhomogeneity efficiently, the gamma distribution parameters are estimated locally in transverse slices. From a database of 54 representative LNs acquired from colorectal-cancer patients, 12 LNs were used to train the random forest classifier, and the 42 remaining LNs were used for evaluation. The Dice similarity coefficient (DSC) was used to compare automatic and manual segmentation. For RFC alone, DSCs were 0.922 ± 0.022, 0.801 ± 0.075 and 0.959 ± 0.013 for LNP, fat and NS, respectively. For initialization and refinement, significantly better DSCs were obtained: 0.937 ± 0.021, 0.824 ± 0.074 and 0.961 ± 0.009 (Wilcoxon signed rank test). Results also demonstrate that accurate QUS estimates can be obtained with automatic segmentation in excised colorectal LNs, thus eliminating the need for operator-dependent, manual segmentation.

Choosing an appropriate dynamic range for acquiring radio-frequency (RF) data from a high-frequency ultrasound (HFU) system is challenging because signals can vary greatly in amplitude because of focusing and attenuation effects. In addition, quantitative ultrasound (QUS) methods are sensitive to saturated data. In this study, the effects of saturation on QUS estimates of effective scatterer diameter (ESD) and effective acoustic concentration (EAC) were quantified using data acquired from 69 dissected human lymph nodes with a single-element transducer operating at a center frequency of 26 MHz. Artificially saturated signals (x c ) were produced by thresholding the original, unsaturated RF echo signals (x). Saturation degree was quantified using Saturate-SNR. ESD and EAC were estimated from x c over a wide range of Saturate-SNR values. The value of the ESD estimate was minimally affected when Saturate-SNR ranged from infinity to 3.99 dB. However, the value of the EAC estimate decreased significantly with decreasing Saturate-SNR. EAC estimates were corrected using a linear relationship between EAC values over a range of Saturate-SNR values and l1 - norm of x (i.e., the sum of absolute values of the true RF echo signal). To correct the estimates for ESD and EAC of saturated signals, the estimated original RF signal was derived from x c by a cubic spline. A linear-regression line was computed for the EAC values of a set of Saturate-SNR values vs. l1 - norm. The intersection of the regression line and l1- norm of the estimated original signal gave a corrected value for EAC. The maximum error in the corrected EAC estimate was 0.48 dB/mm3. The average differences in corrected ESD and EAC estimates of non-metastatic and metastatic lymph nodes were 7.80 µm and 4.18 dB/mm3, respectively. The error in the corrected EAC value was much smaller than the difference in the corrected values of non-metastatic and metastatic lymph nodes.

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.

Ultrasound (US) data suffer from speckle noise as well as intensity inhomogeneities due to underlying changes in acoustic properties of tissue structure and/or the effects of acoustic focusing and attenuation. This paper describes a 2D and 3D variational level-set method for segmenting such data. To deal with the local statistics of speckle noise, the data term of the level-set energy function is based on local gamma distributions which have shown an ability to model envelope data and gray-level pixel intensities of B-mode clinical images. Local statistics are estimated at a controllable scale using a smooth function with a compact support, a mollifyer, and the method of moments. Compared to manual segmentation, the investigated method provides a high Dice similarity coefficient (DSC) on 3D simulated data, an average DSC of 0.915 on 12 B-mode images of murine tumors acquired with a clinical US system, and average DSCs of 0.920, 0.806 and 0.975 for three media of 54 3D envelope data sets acquired with a high-frequency, focused transducer from dissected human lymph nodes. It also outperforms methods that employ local Gaussian statistics instead of local gamma statistics.

Three-dimensional (3D) quantitative-ultrasound (QUS) methods were recently developed and successfully applied to detect cancerous regions in freshly-dissected lymph nodes (LNs). The 3D high frequency ultrasound (HFU) images obtained from these LNs contain three different parts: LN-parenchyma (LNP), fat, and phosphate-buffered saline (PBS). To apply QUS estimates inside the LNP region, an automatic and accurate algorithm for LNP segmentation is needed. In this paper, we describe a novel, nested-graph-cut (NGC) method that effectively exploits the nested structure of the LN images. To overcome the large variability of the intensity distribution of LNP pixels due to acoustic attenuation and focusing, we further describe an iterative self-updating framework combining NGC and spline-based robust intensity fitting. Dice similarity coefficients of 89.56±8.44% were achieved when the proposed automatic segmentation algorithm was compared to expert manual segmentation on a dataset consisting of 115 LNs.

Staging of cancers and selection of appropriate treatment requires histological examination of multiple dissected lymph nodes (LNs) per patient, so that a staggering number of nodes require histopathological examination, and the finite resources of pathology facilities create a severe processing bottleneck. Histologically examining the entire 3D volume of every dissected node is not feasible, and therefore, only the central region of each node is examined histologically, which results in severe sampling limitations. In this work, we assess the feasibility of using quantitative photoacoustics (QPA) to overcome the limitations imposed by current procedures and eliminate the resulting under sampling in node assessments. QPA is emerging as a new hybrid modality that assesses tissue properties and classifies tissue type based on multiple estimates derived from spectrum analysis of photoacoustic (PA) radiofrequency (RF) data and from statistical analysis of envelope-signal data derived from the RF signals. Our study seeks to use QPA to distinguish cancerous from non-cancerous regions of dissected LNs and hence serve as a reliable means of imaging and detecting small but clinically significant cancerous foci that would be missed by current methods. Dissected lymph nodes were placed in a water bath and PA signals were generated using a wavelength-tunable (680-950 nm) laser. A 26-MHz, f-2 transducer was used to sense the PA signals. We present an overview of our experimental setup; provide a statistical analysis of multi-wavelength classification parameters (mid-band fit, slope, intercept) obtained from the PA signal spectrum generated in the LNs; and compare QPA performance with our established quantitative ultrasound (QUS) techniques in distinguishing metastatic from non-cancerous tissue in dissected LNs. QPA-QUS methods offer a novel general means of tissue typing and evaluation in a broad range of disease-assessment applications, e.g., cardiac, intravascular, musculoskeletal, endocrine-gland, etc.

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/cm 2 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.

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 ( 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. (E-mail: rsilverman@rrinyc.org © 2006 World Federation for Ultrasound in Medicine & Biology.

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.

Spectrum analysis procedures have been developed to improve upon the diagnostic capabilities afforded by conventional ultrasonic images. These procedures analyze the frequency content of broadband, coherent echo signals returned from the body. They include calibration procedures to remove system artifacts and thereby provide quantitative measurements of tissue backscatter. Several independent spectral parameters have been used to establish databases for various organs; several investigations have shown that these parameters can be used with statistical classifiers to identify tissue type. Locally computed spectra have been used to generate sets of images displaying independent spectral parameters. Stained images have been derived by analyzing these parameter images with statistical classifiers and using color to denote tissue type (e.g., cancer). This report describes spectrum analysis procedures, discusses how measured parameters are related to physical tissue properties, and summarizes results describing estimator precision. It also presents illustrative clinical results showing how such procedures are being adapted to address specific clinical problems for a number of organs. This report indicates where further developments are needed and suggests how these techniques may improve image segmentation for three-dimensional displays and volumetric assays.

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-trai...

Currently, transrectal ultrasound (TRUS) guided biopsy is the only method for definitive diagnosis of prostate cancer. Our current study used a high-frequency (i.e., 29-MHz), transrectal, micro-ultrasound system (ExactVu™ micro-ultrasound, Exact Imaging) to acquire RF data from 163 patients immediately before needle firing during 12-core biopsy examinations. Quantitative ultrasound (QUS) estimates of effective scatter diameter (ESD), effective acoustic concentration (EAC), midband (M), intercept (I), and slope (S) were calculated. Additional QUS estimates were derived including envelope statistics employing a Nakagami distribution and the envelope signal-to-noise ratio (ESNR). Estimate values were used to train linear-discriminant classifiers and performance was assessed using area-under-the-curve (AUC) values obtained from receiver operating characteristic (ROC) analyses based on 10-fold cross validation. A combination of ESS- and EAC-related parameters produced an AUC value of 0.75. When ESNR or PSA value was added as a feature, the AUC increased significantly to 0.77 or 0.78, respectively. The best classifier performance was obtained by combining envelope statistics, PSA, ESD, and EAC, which produced an AUC of 0.80. Our initial results with AUC values of 0.80 are very encouraging for developing a new tool for prostate-cancer biopsy guidance and treatment.

Improved means of imaging prostate cancer would enable more-effective biopsy and treatment guidance and would provide a noninvasive means of monitoring patients on active surveillance and nonsurgical therapies. Current, commonly used, conventional means of imaging the prostate do not reliably depict cancerous lesions, and as a result, image-guided biopsies sample prostatic tissue in a systematic manner with respect to visible anatomic features of the gland, but blindly with respect to cancerous foci. Treatment tends to involve the entire gland and posttreatment monitoring of therapy is based predominantly on serum PSA levels, supplemented in some cases by periodic biopsies. Similarly, patients on active surveillance for low-volume, low-risk disease are required to undergo repeat prostate biopsies annually or biannually.

The development of small, easy-to-operate ultrasonic imaging systems has led to the widespread use of ultrasound to visualize anatomic structures during clinical examinations and surgical procedures. These systems provide clinicians with high-definition, real-time images that facilitate transcutaneous, endoscopic, and intraoperative visualization and evaluation. To interpret ultrasonic images effectively and to apply the information they provide properly in the emergency room, endoscopic suite, or operating room, the clinician can benefit from an understanding of some of the basic physics of ultrasonography. This chapter briefly presents key principles of ultrasound that have a direct bearing on medical applications of ultrasound. More-comprehensive discussions of ultrasonic imaging are available in various other technical, scientific, and engineering publications.

Scanning acoustic microscopy (SAM) at 250 MHz permits measuring the acoustic properties of tissue microstructure with a spatial resolution of 7 µm. However, only limited data exist for sentinel lymph nodes at these scales. 250-MHz SAM was performed on four fixed and one fresh lymphnode samples. 12-µm sections of deparaffinized, fixed tissue and fresh half nodes were scanned using a custom-built acoustic microscope. 2D SAM maps of speed of sound (c), attenuation (a), and acoustic impedance (Z) were generated using custom signal processing algorithms. Scanned samples then were stained using hematoxylin and eosin and imaged by light microscopy. The spatial resolution and contrast of SAM maps were sufficient to distinguish among tissue regions consisting of lymphocytes, fat cells, and fibrous tissue. Average properties for lymphocyte-rich tissue were c = 1575 ± 57 m/s, a = 8.27 ± 2.45 dB/MHz/cm, and Z = 1.59 ± 0.14 Mrayl. We found a significant increase (p

Quantitative photoacoustics is emerging as a new hybrid modality to investigate diseases and cells in human pathology and cytology studies. Optical absorption of light is the predominant mechanism behind the photoacoustic effect. Therefore, a need exits to characterize the optical properties of specimens and to identify the relevant operating wavelengths for photoacoustic imaging. We have developed a custom low-cost spectrophotometer to measure the optical properties of human axillary lymph nodes dissected for breast-cancer staging. Optical extinction curves of positive and negative nodes were determined in the spectral range of 400 to 1000 nm. We have developed a model to estimate tissue optical properties, taking into account the role of fat and saline. Our results enabled us to select the optimal optical wavelengths for maximizing the imaging contrast between metastatic and noncancerous tissue in axillary lymph nodes.

Quantitative ultrasound (QUS) estimates derived from power spectra of pulse-echo signals are sensitive to mi- crostructure and potentially can differentiate among tissues. However, QUS estimates do not provide molecular specificity. We investigated the feasibility of obtaining quantitative photoacoustic (QPA) estimates for sensi- tivity to microstructure and chromophores for tissue classification. QPA methods were tested using gel-based phantoms containing uniformly dispersed, black polyethylene spheres (1E5 particles/ml) with nominal mean diameters of 23.5, 29.5, 42.0, and 58.0 μm. A pulsed, 532-nm laser excited the photoacoustic (PA) response. A single-element, 34-MHz transducer with a 12-mm focal length was raster scanned over the phantom to acquire 3D PA data. Normalized power spectra were generated from the PA signals within 2079, moving (50% overlap), 1-mm-cube regions-of-interest (ROIs) to provide three QPA estimates: spectral slope (SS), spectral intercept (SI), and effective absorber size (EAS). SS and SI were computed using a linear-regression approximation to the normalized spectrum in the -6-dB band. EAS was computed by fitting the normalized spectrum in the -20-dB band to the multi-sphere analytical solution. All estimates were correlated with the size of particles dispersed in the phantoms. SS decreased while SI increased with an increase in particle size. EAS was correlated with nominal particle diameter, but particles aggregation and the finite bandwidth of the PAI system resulted in outliers. SS, SI, and EAS for the 23.5-μm-phantom were -0.14±-0.04 dB/MHz, 4.8±1.3 dB, and 25.4±6.3 μm, respectively; the corresponding values for the 58.0-μm phantom were -0.47±-0.03 dB/MHz, 15.6±0.9 dB, and 82.7±0.9 μm.