Quantitative ultrasonic analysis of liver metastases.
Huisman HJ. Thijssen JM. Wagener DJ. Rosenbusch GJ.
Department of Pediatrics, University Hospital, Nijmegen, The Netherlands.
The performance of five features of ultrasonic tissue characterization (UTC) of metastases in vivo in liver was investigated. We acquired serial radiofrequency data sets of 12 patients with metastases in the liver from adenocarcinoma of the colon. Parenchyma and metastases UTC features were estimated in semiautomatically segmented regions. Over 200 metastases were measured in patients and 43 dummy metastases in healthy volunteers. Two attenuation features could be estimated in only 15% of the metastases, and these were not different from those in parenchyma. The texture features signal-to-noise ratio (SNR) could not discriminate real from dummy metastases. Average backscatter intensity, b0, is an established discriminative echographic image feature. However, the metastases that were hypoechoic relative to surrounding parenchyma appeared to be isoechoic relative to normal liver parenchyma. They were visible because of an increased b0 in the surrounding liver parenchyma. Finally, we found an increased backscatter coefficient slope vs. frequency in hypoechoic metastases that may predict a deterioration of lesion contrast at higher transducer frequencies. We conclude that the backscatter coefficient slope can improve detection of metastases, and that b0 measured relative to normal liver parenchyma should be used to correctly correlate metastasis echography with histology.
Comparisons of the Rayleigh and K-distribution models using in vivo breast and liver tissue.
Molthen RC. Shankar PM. Reid JM. Forsberg F. Halpern EJ. Piccoli CW. Goldberg BB.
School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA.
There is a strong interest in finding out which statistical model is the most appropriate for describing the envelope of the backscattered ultrasonic echoes from different types of tissues. The Rayleigh model is commonly employed, but this requires conditions, such as the presence of large number of randomly located scatterers with fairly uniform cross-sections, that are not always met. However, our research indicates that a model based on the K-distribution may provide a better fit to empirical data over a range of scattering conditions than the standard Rayleigh model. In this study, we looked at the K-distribution as a descriptor of the backscattered envelope of the breast and liver tissues (in vivo). By examining data from various tissue regions, a goodness-of-fit test (a least squares error method) was used to determine whether a Rayleigh or K-distribution model is more appropriate. From a large group of patients and volunteer scans (a total of 72 subjects), the fit between the K-distribution and the data is shown to have a much smaller error than the Rayleigh model.
In vitro investigation of lymph node metastasis of colorectal cancer using ultrasonic spectral parameters.
Noritomi T. Machi J. Feleppa EJ. Yanagihara E. Shirouzu K.
Department of Surgery, Kurume University School of Medicine, Japan.
Lymph node involvement is one of the major factors affecting the prognosis of colorectal cancer. Various imaging methods, including ultrasound and computed tomography, are not sufficiently sensitive or specific for reliably determining lymph node involvement. We investigated the feasibility of using ultrasonic tissue characterization (UTC) based on spectrum analysis of backscattered echo signals for diagnosing lymph node metastasis of colorectal cancer in vitro. Forty lymph nodes, including 17 metastatic and 23 nonmetastatic nodes, from 11 colorectal cancer operations were investigated. Lymph nodes were scanned using a clinical instrument; B-mode imaging was performed for each lymph node, and radiofrequency (RF) data were acquired. The UTC parameters, slope and intercept, were calculated from the normalized power spectrum of the backscattered echo signals from each lymph node. The mean values of UTC parameters of metastatic and nonmetastatic lymph nodes were compared. The accuracy of UTC in distinguishing metastatic from nonmetastatic lymph nodes was calculated using discriminant analysis. Receiver operating characteristic (ROC) analysis was performed to compare the classification efficacy of UTC and B-mode ultrasound. UTC parameters demonstrated a significant difference in parameter values between metastatic and nonmetastatic lymph nodes. The overall accuracy in diagnosing the lymph node metastasis was 87.5% for UTC and 77.5% for B-mode ultrasound. ROC analysis produced an ROC curve area of 0.92 or 0.89 for UTC (depending on the performance-assessment algorithm) and 0.84 for B-mode ultrasound, which indicated that UTC performed markedly better than B-mode ultrasound in diagnosing metastatic lymph nodes. The advantages of UTC over conventional B-mode ultrasound in discriminating metastatic lymph nodes from nonmetastatic lymph nodes are extremely encouraging, and warrant an in vivo UTC study.