Improved cancer risk stratification of isoechoic thyroid nodules to reduce unnecessary biopsies using quantitative ultrasound.

Objective: Gray-scale ultrasound (US) is the standard-of-care for evaluating thyroid nodules (TNs). However, the performance is better for the identification of hypoechoic malignant TNs (such as classic papillary thyroid cancer) than isoechoic malignant TNs. Quantitative ultrasound (QUS) utilizes information from raw ultrasonic radiofrequency (RF) echo signal to assess properties of tissue microarchitecture. The purpose of this study is to determine if QUS can improve the cancer risk stratification of isoechoic TNs. Methods: Patients scheduled for TN fine needle biopsy (FNB) were recruited from the Thyroid Health Clinic at Boston Medical Center. B-mode US and RF data (to generate QUS parameters) were collected in 274 TNs (163 isoechoic, 111 hypoechoic). A linear combination of QUS parameters (CQP) was trained and tested for isoechoic [CQP(i)] and hypoechoic [CQP(h)] TNs separately and compared with the performance of conventional B-mode US risk stratification systems. Results: CQP(i) produced an ROC AUC value of 0.937+/- 0.043 compared to a value of 0.717 +/- 0.145 (p >0.05) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.589 +/- 0.173 (p >0.05) for the American Thyroid Association (ATA) risk stratification system. In this study, CQP(i) avoids unnecessary FNBs in 73% of TNs compared to 55.8% and 11.8% when using ACR TI-RADS and ATA classification system. Conclusion: This data supports that a unique QUS-based classifier may be superior to conventional US stratification systems to evaluate isoechoic TNs for cancer and should be explored further in larger studies.

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

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

Quantitative Ultrasound Assessment of Early Osteoarthritis in Human Articular Cartilage Using a High-Frequency Linear Array Transducer.

Quantitative ultrasound (QUS) assessment of osteoarthritis (OA) using high-frequency, research-grade single-element ultrasound systems has been reported. The objective of this ex vivo study was to assess the performance of QUS in detecting early OA using a high-frequency linear array transducer. Osteochondral plugs (n = 26) of human articular cartilage were scanned with ExactVu Micro-Ultrasound using an EV29L side-fire transducer. For comparison, the samples were also imaged with SAM200Ex, a custom 40-MHz scanning acoustic microscope with a single-element, focused transducer. Thirteen QUS parameters were derived from the ultrasound data. Magnetic resonance imaging (MRI) data, with T1 and T2 extracted as the quantitative parameters, were also acquired for comparison. Cartilage degeneration was graded from histology and correlated to all quantitative parameters. A maximum Spearman rank correlation coefficient (ρ) of 0.75 was achieved using a combination of ExactVu QUS parameters, while a maximum ρ of 0.62 was achieved using a combination of parameters from SAM200Ex. A maximum ρ of 0.75 was achieved using the T1 and T2 MRI parameters. This study illustrates the potential of a high-frequency linear array transducer to provide a convenient method for early OA screening with results comparable to those of research-grade single-element ultrasound and MRI.

A Preliminary Study of Quantitative Ultrasound for Cancer-Risk Assessment of Thyroid Nodules.

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.

Multiparametric Ultrasound for Targeting Prostate Cancer: Combining ARFI, SWEI, QUS and B-Mode.

Diagnosing prostate cancer through standard transrectal ultrasound (TRUS)-guided biopsy is challenging because of the sensitivity and specificity limitations of B-mode imaging. We used a linear support vector machine (SVM) to combine standard TRUS imaging data with acoustic radiation force impulse (ARFI) imaging data, shear wave elasticity imaging (SWEI) data and quantitative ultrasound (QUS) midband fit data to enhance lesion contrast into a synthesized multiparametric ultrasound volume. This SVM was trained and validated using a subset of 20 patients and tested on a second subset of 10 patients. Multiparametric US led to a statistically significant improvements in contrast, contrast-to-noise ratio (CNR) and generalized CNR (gCNR) when compared with standard TRUS B-mode and SWEI; in contrast and CNR when compared with MF; and in CNR when compared with ARFI. ARFI, MF and SWEI also outperformed TRUS B-mode in contrast, with MF outperforming B-mode in CNR and gCNR as well. ARFI, although only yielding statistically significant differences in contrast compared with TRUS B-mode, captured critical qualitative features for lesion identification. Multiparametric US enhanced lesion visibility metrics and is a promising technique for targeted TRUS-guided prostate biopsy in the future.

Assessment of Vitreous Structure and Visual Function after Neodymium:Yttrium-Aluminum-Garnet Laser Vitreolysis.

PURPOSE: Neodymium:yttrium-aluminum-garnet (Nd:YAG) laser treatment is performed on vitreous floaters, but studies of structural and functional effects with objective outcome measures are lacking. This study evaluated Nd:YAG laser effects by comparing participants with vitreous floaters who previously underwent laser treatment with untreated control participants and healthy persons without vitreous floaters using quantitative ultrasonography to evaluate vitreous structure and by measuring visual acuity and contrast sensitivity function to assess vision. DESIGN: Retrospective, comparative study. PARTICIPANTS: One eye was enrolled for each of 132 participants: 35 control participants without vitreous floaters, 59 participants with untreated vitreous floaters, and 38 participants with vitreous floaters previously Nd:YAG-treated. Of these, 25 were dissatisfied and sought vitrectomy; 13 were satisfied with observation. METHODS: The 39-item National Eye Institute Visual Function Questionnaire (NEI-VFQ-39) to assess participant visual well-being, quantitative ultrasonography (QUS) to measure vitreous echodensity, and best-corrected visual acuity (BCVA) and contrast sensitivity function (CSF) to evaluate vision. MAIN OUTCOME MEASURES: Results of NEI-VFQ-39, QUS, BCVA, and CSF. RESULTS: Compared with control participants without vitreous floaters, participants with untreated vitreous floaters showed worse NEI-VFQ-39 results, 57% greater vitreous echodensity, and significant (130%) CSF degradation (P < 0.001 for each). Compared with untreated eyes with vitreous floaters, Nd:YAG-treated eyes had 23% less vitreous echodensity (P < 0.001), but no differences in NEI-VFQ-39 (P = 0.51), BCVA (P = 0.42), and CSF (P = 0.17) results. Of 38 participants with vitreous floaters who previously were treated with Nd:YAG, 25 were dissatisfied and seeking vitrectomy, whereas 13 were satisfied with observation. Participants seeking vitrectomy showed 24% greater vitreous echodensity (P = 0.018) and 52% worse CSF (P = 0.006). Multivariate linear regression models confirmed these findings. CONCLUSIONS: As a group, participants previously treated with Nd:YAG laser for bothersome vitreous floaters showed less dense vitreous, but similar visual function as untreated control participants with vitreous floaters. Because some treated eyes showed less dense vitreous and better visual function than those of untreated control participants, a prospective randomized study of Nd:YAG laser treatment of vitreous is warranted, using uniform laser treatment parameters and objective quantitative outcome measures.

A Convolutional Neural Network for 250-MHz Quantitative Acoustic-microscopy Resolution Enhancement.

Quantitative acoustic microscopy (QAM) permits the formation of quantitative two-dimensional (2D) maps of acoustic and mechanical properties of soft tissues at microscopic resolution. The 2D maps formed using our custom SAM systems employing a 250-MHz and a 500-MHz single-element transducer have a nominal resolution of 7 µm and 4µm, respectively. In a previous study, the potential of single-image super-resolution (SR) image post-processing to enhance the spatial resolution of 2D SAM maps was demonstrated using a forward model accounting for blur, decimation, and noise. However, results obtained when the SR method was applied to soft tissue data were not entirely satisfactory because of the limitation of the convolution model considered and by the difficulty of estimating the system point spread function and designing the appropriate regularization term. Therefore, in this study, a machine learning approach based on convolutional neural networks was implemented. For training, data acquired on the same samples at 250 and 500 MHz were used. The resulting trained network was tested on 2D impedance maps (2DZMs) of human lymph nodes acquired from breast-cancer patients. Visual inspection of the reconstructed enhanced 2DZMs were found similar to the 2DZMs obtained at 500 MHz which were used as ground truth. In addition, the enhanced 250-MHz 2DZMs obtained from the proposed method yielded better peak signal to noise ratio and normalized mean square error than those obtained with the previous SR method. This improvement was also demonstrated by the statistical analyses. This pioneering work could significantly reduce challenges and costs associated with current very high-frequency SAM systems while providing enhanced spatial resolution.

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

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

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

Choosing an appropriate dynamic range (DR) for acquiring radio frequency (RF) data from a high-frequency-ultrasound (HFU) system is challenging because signals can vary greatly in amplitude as a result of focusing and attenuation effects. In addition, quantitative ultrasound (QUS) results are altered by saturated data. In this paper, the effects of saturation on QUS estimates of effective scatterer diameter (ESD) and effective acoustic concentration (EAC) were quantified using simulated and experimental RF data. Experimental data were acquired from 69 dissected human lymph nodes using a single-element transducer with a 26-MHz center frequency. Artificially saturated signals ( xc) were produced by thresholding the original unsaturated RF echo signals. Saturation severity was expressed using a quantity called saturate-signal-to-noise ratio (SSNR). Results indicated that saturation has little effect on ESD estimates. However, EAC estimates decreased significantly with decreasing SSNR. An EAC correction algorithm exploiting a linear relationship between EAC values over a range of SSNR values and l1 -norm of xc (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.

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

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

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

OBJECTIVE: To detect metastases in freshly excised human lymph nodes (LNs) using three-dimensional (3-D), high-frequency, quantitative ultrasound (QUS) methods, the LN parenchyma (LNP) must be segmented to preclude QUS analysis of data in regions outside the LNP and to compensate ultrasound attenuation effects due to overlying layers of LNP and residual perinodal fat (PNF). METHODS: After restoring the saturated radio-frequency signals from PNF using an approach based on smoothing cubic splines, the three regions, i.e., LNP, PNF, and normal saline (NS), in the LN envelope data are segmented using a new, automatic, 3-D, three-phase, statistical transverseslice-based level-set (STS-LS) method that amends Lankton's method. Due to ultrasound attenuation and focusing effects, the speckle statistics of the envelope data vary with imaged depth. Thus, to mitigate depth-related inhomogeneity effects, the STS-LS method employs gamma probabilitydensity functions to locally model the speckle statistics within consecutive transverse slices. RESULTS: Accurate results were obtained on simulated data. On a representative dataset of 54 LNs acquired from colorectal-cancer patients, the Dice similarity coefficient for LNP, PNF, and NS were 0.938 ± 0.025, 0.832 ± 0.086, and 0.968 ± 0.008, respectively, when compared to expert manual segmentation. CONCLUSION: The STS-LS outperforms the established methods based on global and local statistics in our datasets and is capable of accurately handling the depth-dependent effects due to attenuation and focusing. SIGNIFICANCE: This advance permits the automatic QUS-based cancer detection in the LNs. Furthermore, the STS-LS method could potentially be used in a wide range of ultrasound-imaging applications suffering from depth-dependent effects.

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

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

Modeling the envelope statistics of three-dimensional high-frequency ultrasound echo signals from dissected human lymph nodes.

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.

High-frequency (20 to 40 MHz) acoustic response of liquid-filled nanocapsules.

Liquid-core nanoparticles are promising candidates for targeted ultrasound-controlled therapy, but their acoustic detection remains challenging. High-frequency (20 to 40 MHz) tone burst sequences were implemented with a programmable ultrasound biomicroscope to characterize acoustic response from perfluorooctyl bromide-core nanoparticles with thick poly(lactide-coglycolide) (PLGA) shells. Radio-frequency signals were acquired from flowing solutions of nanoparticles with two different shell-thickness-to-particle-radius ratios, solid PLGA nanoparticles, and latex nanobeads (linear controls). Normalized fundamental (20 MHz) and second-harmonic power spectral density (PSD) increased with particle concentration and was highest for the thinnest shelled particles. The second- harmonic PSD was detectable from the nanoparticles for peak rarefactional pressures (PRP) from 0.97 to 2.01 MPa at 23 cycles and for tone bursts from 11 to 23 cycles at 2.01 MPa. Their second-harmonic¿to¿fundamental ratio increased as a function of PRP and number of cycles. Within the same PRP and cycle ranges, the second-harmonic¿to¿fundamental ratios from matched concentration solutions of latex nanobeads and solid PLGA nanoparticles was more weakly detectable but also increased with PRP and number of cycles. Nanoparticles were detectable under flow conditions in vitro using the contrast agent mode of a high-frequency commercial scanner. These results characterize linear acoustic response from the nanoparticles (20 to 40 MHz) and demonstrate potential for their highfrequency detection.

Three-dimensional quantitative ultrasound for detecting lymph node metastases.

PURPOSE: Detection of metastases in lymph nodes (LNs) is critical for cancer management. Conventional histological methods may miss metastatic foci. To date, no practical means of evaluating the entire LN volume exists. The aim of this study was to develop fast, reliable, operator-independent, high-frequency, quantitative ultrasound (QUS) methods for evaluating LNs over their entire volume to effectively detect LN metastases. METHODS: We scanned freshly excised LNs at 26 MHz and digitally acquired echo-signal data over the entire three-dimensional (3D) volume. A total of 146 LNs of colorectal, 26 LNs of gastric, and 118 LNs of breast cancer patients were enrolled. We step-sectioned LNs at 50-µm intervals and later compared them with 13 QUS estimates associated with tissue microstructure. Linear-discriminant analysis classified LNs as metastatic or nonmetastatic, and we computed areas (Az) under receiver-operator characteristic curves to assess classification performance. The QUS estimates and cancer probability values derived from discriminant analysis were depicted in 3D images for comparison with 3D histology. RESULTS: Of 146 LNs of colorectal cancer patients, 23 were metastatic; Az = 0.952 ± 0.021 (95% confidence interval [CI]: 0.911-0.993); sensitivity = 91.3% (specificity = 87.0%); and sensitivity = 100% (specificity = 67.5%). Of 26 LNs of gastric cancer patients, five were metastatic; Az = 0.962 ± 0.039 (95% CI: 0.807-1.000); sensitivity = 100% (specificity = 95.3%). A total of 17 of 118 LNs of breast cancer patients were metastatic; Az = 0.833 ± 0.047 (95% CI: 0.741-0.926); sensitivity = 88.2% (specificity = 62.5%); sensitivity = 100% (specificity = 50.5%). 3D cancer probability images showed good correlation with 3D histology. CONCLUSIONS: These results suggest that operator- and system-independent QUS methods allow reliable entire-volume LN evaluation for detecting metastases. 3D cancer probability images can help pathologists identify metastatic foci that could be missed using conventional methods.

Pulse-encoded ultrasound imaging of the vitreous with an annular array.

The vitreous body is nearly transparent both optically and ultrasonically. Conventional 10- to 12-MHz diagnostic ultrasound can detect vitreous inhomogeneities at high gain settings, but has limited resolution and sensitivity, especially outside the fixed focal zone near the retina. To improve visualization of faint intravitreal fluid/gel interfaces, the authors fabricated a spherically curved 20-MHz five-element annular array ultrasound transducer, implemented a synthetic-focusing algorithm to extend the depth-of-field, and used a pulse-encoding strategy to increase sensitivity. The authors evaluated a human subject with a recent posterior vitreous detachment and compared the annular array with conventional 10-MHz ultrasound and spectral-domain optical coherence tomography. With synthetic focusing and chirp pulse-encoding, the array allowed visualization of the formed and fluid components of the vitreous with improved sensitivity and resolution compared with the conventional B-scan. Although optical coherence tomography allowed assessment of the posterior vitreoretinal interface, the ultrasound array allowed evaluation of the entire vitreous body.

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

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

Comparison of template-matching and singular-spectrum-analysis methods for imaging implanted brachytherapy seeds.

Brachytherapy using small implanted radioactive seeds is becoming an increasingly popular method for treating prostate cancer, in which a radiation oncologist implants seeds in the prostate transperineally under ultrasound guidance. Dosimetry software determines the optimal placement of seeds for achieving the prescribed dose based on ultrasonic determination of the gland boundaries. However, because of prostate movement and distortion during the implantation procedure, some seeds may not be placed in the desired locations; this causes the delivered dose to differ from the prescribed dose. Current ultrasonic imaging methods generally cannot depict the implanted seeds accurately. We are investigating new ultrasonic imaging methods that show promise for enhancing the visibility of seeds and thereby enabling real-time detection and correction of seed-placement errors during the implantation procedure. Real-time correction of seed-placement errors will improve the therapeutic radiation dose delivered to target tissues. In this work, we compare the potential performance of a template-matching method and a previously published method based on singular spectrum analysis for imaging seeds. In particular, we evaluated how changes in seed angle and position relative to the ultrasound beam affect seed detection. The conclusion of the present study is that singular spectrum analysis has better sensitivity but template matching is more resistant to false positives; both perform well enough to make seed detection clinically feasible over a relevant range of angles and positions. Combining the information provided by the two methods may further reduce ambiguities in determining where seeds are located.

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

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

Quantitative ultrasound in cancer imaging.

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