Quantitative Ultrasound: An Emerging Technology for Detecting, Diagnosing, Imaging, Evaluating, and Monitoring Disease.

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.

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.

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.

Phase I/II prospective trial of cancer-specific imaging using ultrasound spectrum analysis tissue-type imaging to guide dose-painting prostate brachytherapy.

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.

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.

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.

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.

Ultrasonic multi-feature analysis procedure for computer-aided diagnosis of solid breast lesions.

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.

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.

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

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

Three-dimensional high-frequency characterization of cancerous 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 (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.

Effect of corneal hydration on ultrasound velocity and backscatter.

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.

Ultrasonic tissue-type imaging of the prostate: implications for biopsy and treatment guidance.

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.

Angle-dependent ultrasonic detection and imaging of brachytherapy seeds using singular spectrum analysis.

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 .

Angle-dependent ultrasonic detection and imaging of two types of brachytherapy seeds using singular spectrum analysis.

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.

Singular spectrum analysis applied to ultrasonic detection and imaging of brachytherapy seeds.

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.