Ultrafast Computation of Left Ventricular Ejection Fraction by Using Temporal Intensity Variation in Cine Cardiac Magnetic Resonance.

Cardiac magnetic resonance enables comprehensive cardiac evaluation; however, intense time and labor requirements for data acquisition and processing have discouraged many clinicians from using it. We have developed an alternative image-processing algorithm that requires minimal user interaction: an ultrafast algorithm that computes left ventricular ejection fraction (LVEF) by using temporal intensity variation in cine balanced steady-state free precession (bSSFP) short-axis images, with or without contrast medium. We evaluated the algorithm's performance against an expert observer's analysis for segmenting the LV cavity in 65 study participants (LVEF range, 12%-70%). In 12 instances, contrast medium was administered before cine imaging. Bland-Altman analysis revealed quantitative effects of LV basal, midcavity, and apical morphologic variation on the algorithm's accuracy. Total computation time for the LV stack was <2.5 seconds. The algorithm accurately delineated endocardial boundaries in 1,132 of 1,216 slices (93%). When contours in the extreme basal and apical slices were not adequate, they were replaced with manually drawn contours. The Bland-Altman mean differences were <1.2 mL (0.8%) for end-diastolic volume, <5 mL (6%) for end-systolic volume, and <3% for LVEF. Standard deviation of the difference was ≤4.1% of LV volume for all sections except the midcavity in end-systole (8.3% of end-systolic volume). We conclude that temporal intensity variation-based ultrafast LVEF computation is clinically accurate across a range of LV shapes and wall motions and is suitable for postcontrast cine SSFP imaging. Our algorithm enables real-time processing of cine bSSFP images on a commercial scanner console within 3 seconds in an unobtrusive automated process.

Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?

OBJECTIVE: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. MATERIALS AND METHODS: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. RESULTS: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). CONCLUSION: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.

OBJETIVO: Comparar imagens renais ultrassonográficas obtidas de maneira aleatória e controlada (padronizando fatores físicos do aparelho de ultrassom) por diferentes profissionais e aparelhos. MATERIAIS E MÉTODOS: Foram obtidos quatro tipos de imagens, de acordo com sua aquisição e processamento por cinco profissionais e dois tipos de aparelhos de ultrassonografia, em 24 pacientes, totalizando 919 imagens. Comparamos a mediana de escala de cinza e diferentes intervalos de tons de cinza representantes de tecidos histológicos virtuais. RESULTADOS: As medianas de escala de cinza de imagens renais obtidas por dois tipos de aparelhos foram estatisticamente diferentes (p < 2.2e-16). Analisando os quatro tipos de imagens, partindo de uma totalmente aleatória (sem qualquer padronização), uma padronizada (fixado o ganho, time gain control e dynamic range), e essas duas passando por um processo de normatização, obteve-se que a imagem aleatória é totalmente diversa entre os profissionais (p = 0,006098), mesmo passando pelo processo de normatização. A imagem padronizada, após passar pelo processo de normatização, apresentou resultados equivalentes, não possuindo diferença estatística (p = 0,7319). CONCLUSÃO: Constatou-se que na análise de tons de cinza deve-se usar um mesmo tipo de máquina e uma imagem em que sejam padronizados aspectos físicos, passando por um processo de normatização/padronização.

Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images? / Proposição de um diagnóstico auxiliado por computador de imagem renal ultrassonográfica: é possível comparar tons de cinza das imagens ultrassonográficas renais?

Abstract Objective: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. Materials and Methods: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. Results: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). Conclusion: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.

Resumo Objetivo: Comparar imagens renais ultrassonográficas obtidas de maneira aleatória e controlada (padronizando fatores físicos do aparelho de ultrassom) por diferentes profissionais e aparelhos. Materiais e Métodos: Foram obtidos quatro tipos de imagens, de acordo com sua aquisição e processamento por cinco profissionais e dois tipos de aparelhos de ultrassonografia, em 24 pacientes, totalizando 919 imagens. Comparamos a mediana de escala de cinza e diferentes intervalos de tons de cinza representantes de tecidos histológicos virtuais. Resultados: As medianas de escala de cinza de imagens renais obtidas por dois tipos de aparelhos foram estatisticamente diferentes (p < 2.2e-16). Analisando os quatro tipos de imagens, partindo de uma totalmente aleatória (sem qualquer padronização), uma padronizada (fixado o ganho, time gain control e dynamic range), e essas duas passando por um processo de normatização, obteve-se que a imagem aleatória é totalmente diversa entre os profissionais (p = 0,006098), mesmo passando pelo processo de normatização. A imagem padronizada, após passar pelo processo de normatização, apresentou resultados equivalentes, não possuindo diferença estatística (p = 0,7319). Conclusão: Constatou-se que na análise de tons de cinza deve-se usar um mesmo tipo de máquina e uma imagem em que sejam padronizados aspectos físicos, passando por um processo de normatização/padronização.

Comparison of automated and manual protocols for magnetic resonance imaging assessment of liver iron concentration.

OBJECTIVE: To compare automated and manual magnetic resonance imaging protocols for estimating liver iron concentrations at 1.5 T. MATERIALS AND METHODS: Magnetic resonance imaging examination of the liver was performed in 53 patients with clinically suspected hepatic iron overload and in 21 control subjects. Liver iron concentrations were then estimated by two examiners who were blinded to the groups. The examiners employed automated T2* and T1 mapping, as well as manual T2* and signal-intensity-ratio method. We analyzed accuracy by using ROC curves. Interobserver and intraobserver agreement were analyzed by calculating two-way intraclass correlation coefficients. RESULTS: The area under the ROC curve (to discriminate between patients and controls) was 0.912 for automated T2* mapping, 0.934 for the signal-intensity-ratio method, 0.908 for manual T2*, and 0.80 for T1 mapping, the last method differing significantly from the other three. The level of interobserver and intraobserver agreement was good (intraclass correlation coefficient, 0.938-0.998; p < 0.05). Correlations involving T1 mapping, although still significant, were lower. CONCLUSION: At 1.5 T, T2* mapping is a rapid tool that shows promise for the diagnosis of liver iron overload, whereas T1 mapping shows less accuracy. The performance of T1 mapping is poorer than is that of T2* methods.

OBJETIVO: Comparar protocolos automatizados e manuais de ressonância magnética para estimar a concentração hepática de ferro em 1,5 T. MATERIAIS E MÉTODOS: Foi realizada ressonância magnética hepática em 53 pacientes com suspeita de sobrecarga de ferro hepática e 21 controles, seguida da estimativa cega da concentração hepática de ferro por dois examinadores usando mapas automáticos T2* e T1, assim como o manual T2* e o método signal-intensity-ratio. O desempenho foi medido usando curvas ROC e a correlação interobservador e intraobservador usando o coeficiente de correlação intraclasse bidirecional. RESULTADOS: O desempenho da curva ROC separando pacientes e controles mostrou áreas sob a curva de 0,912 para o mapa automático T2*, 0,934 para o método signal-intensity-ratio, 0,908 para manual T2* e 0,80 para mapa T1 (este difere significativamente dos outros três métodos). Houve boa correlação interobservador e intraobservador (coeficiente de correlação intraclasse entre 0,938 e 0,998; p < 0,05). Correlações envolvendo o mapa T1, embora ainda significativas, foram menores. CONCLUSÃO: Em 1,5 T, o mapa T2* representa uma nova ferramenta rápida e promissora para avaliar o diagnóstico de sobrecarga de ferro hepática, enquanto o mapa T1 mostrou menor precisão. O desempenho do mapa T1 foi menor que o dos métodos T2*.

Comparison of automated and manual protocols for magnetic resonance imaging assessment of liver iron concentration / Comparação de protocolos automatizados e manuais de ressonância magnética para avaliação da concentração hepática de ferro

Abstract Objective: To compare automated and manual magnetic resonance imaging protocols for estimating liver iron concentrations at 1.5 T. Materials and Methods: Magnetic resonance imaging examination of the liver was performed in 53 patients with clinically suspected hepatic iron overload and in 21 control subjects. Liver iron concentrations were then estimated by two examiners who were blinded to the groups. The examiners employed automated T2* and T1 mapping, as well as manual T2* and signal-intensity-ratio method. We analyzed accuracy by using ROC curves. Interobserver and intraobserver agreement were analyzed by calculating two-way intraclass correlation coefficients. Results: The area under the ROC curve (to discriminate between patients and controls) was 0.912 for automated T2* mapping, 0.934 for the signal-intensity-ratio method, 0.908 for manual T2*, and 0.80 for T1 mapping, the last method differing significantly from the other three. The level of interobserver and intraobserver agreement was good (intraclass correlation coefficient, 0.938-0.998; p < 0.05). Correlations involving T1 mapping, although still significant, were lower. Conclusion: At 1.5 T, T2* mapping is a rapid tool that shows promise for the diagnosis of liver iron overload, whereas T1 mapping shows less accuracy. The performance of T1 mapping is poorer than is that of T2* methods.

Resumo Objetivo: Comparar protocolos automatizados e manuais de ressonância magnética para estimar a concentração hepática de ferro em 1,5 T. Materiais e Métodos: Foi realizada ressonância magnética hepática em 53 pacientes com suspeita de sobrecarga de ferro hepática e 21 controles, seguida da estimativa cega da concentração hepática de ferro por dois examinadores usando mapas automáticos T2* e T1, assim como o manual T2* e o método signal-intensity-ratio. O desempenho foi medido usando curvas ROC e a correlação interobservador e intraobservador usando o coeficiente de correlação intraclasse bidirecional. Resultados: O desempenho da curva ROC separando pacientes e controles mostrou áreas sob a curva de 0,912 para o mapa automático T2*, 0,934 para o método signal-intensity-ratio, 0,908 para manual T2* e 0,80 para mapa T1 (este difere significativamente dos outros três métodos). Houve boa correlação interobservador e intraobservador (coeficiente de correlação intraclasse entre 0,938 e 0,998; p < 0,05). Correlações envolvendo o mapa T1, embora ainda significativas, foram menores. Conclusão: Em 1,5 T, o mapa T2* representa uma nova ferramenta rápida e promissora para avaliar o diagnóstico de sobrecarga de ferro hepática, enquanto o mapa T1 mostrou menor precisão. O desempenho do mapa T1 foi menor que o dos métodos T2*.

Dual-Energy Computed Tomography-Enabled Material Separation in Diagnosing Left Atrial Appendage Thrombus.

We explored the potential clinical value of material separation enabled by dual-energy spectral computed tomography in detecting left atrial appendage thrombi. The study enrolled 24 patients who were scheduled to undergo atrial fibrillation ablation (12 with and 12 without left atrial appendage thrombi). Computed tomograms were acquired in gemstone spectral imaging mode; the densities in the regions of the left atrial appendage cavities, pectinate muscles, and left atrial appendage thrombi were analyzed on monochromatic 70-keV images. Iodine and blood were chosen as the material basis pair; the iodine and blood densities were observed and quantitatively determined from the iodine- and blood-specific material decomposition images. On the 70-keV monochromatic and iodine-specific images, the left atrial appendage pectinate muscles and thrombi appeared as areas of hypodense attenuation. On the blood-specific images, similar areas of high attenuation were observed in the thrombi and cavities, whereas lower attenuation was noticed in the pectinate muscles. The quantitative iodine and blood densities in the pectinate muscles were lower than those in the cavities (P <0.001). The iodine densities in the thrombi were lower than those in the cavities (P <0.001); however, blood densities did not differ significantly between the thrombi and cavities (P=0.192). Compared with the pectinate muscles, the thrombi showed lower blood-density differences (P=0.003) and higher iodine-density differences (P=0.006) in relation to the cavities. Spectral computed tomography-enabled material separation is a novel method for differentiating left atrial appendage thrombi from pectinate muscles. The potential applications of this technology warrant further studies.

Quantification of visceral adipose tissue by computed tomography and magnetic resonance imaging: reproducibility and accuracy.

OBJECTIVE: To evaluate the feasibility of quantifying visceral adipose tissue (VAT) on computed tomography (CT) and magnetic resonance imaging (MRI) scans, using freeware, as well as calculating intraobserver and interobserver reproducibility. MATERIALS AND METHODS: We quantified VAT in patients who underwent abdominal CT and MRI at our institution between 2010 and 2015, with a maximum of three months between the two examinations. A slice acquired at the level of the umbilicus was selected. Segmentation was performed with the region growing algorithm of the freeware employed. Intraobserver and interobserver reproducibility were evaluated, as was the accuracy of MRI in relation to that of CT. RESULTS: Thirty-one patients (14 males and 17 females; mean age of 57 ± 15 years) underwent CT and MRI (mean interval between the examinations, 28 ± 12 days). The interobserver reproducibility was 82% for CT (bias = 1.52 cm2; p = 0.488), 86% for T1-weighted MRI (bias = -4.36 cm2; p = 0.006), and 88% for T2-weighted MRI (bias = -0.52 cm2; p = 0.735). The intraobserver reproducibility was 90% for CT (bias = 0.14 cm2; p = 0.912), 92% for T1-weighted MRI (bias = -3,4 cm2; p = 0.035), and 90% for T2-weighted MRI (bias = -0.30 cm2; p = 0.887). The reproducibility between T1-weighted MRI and T2-weighted MRI was 87% (bias = -0.11 cm2; p = 0.957). In comparison with the accuracy of CT, that of T1-weighted and T2-weighted MRI was 89% and 91%, respectively. CONCLUSION: The program employed can be used in order to quantify VAT on CT, T1-weighted MRI, and T2-weighted MRI scans. Overall, the accuracy of MRI (in comparison with that of CT) appears to be high, as do intraobserver and interobserver reproducibility. However, the quantification of VAT seems to be less reproducible in T1-weighted sequences.

OBJETIVO: Avaliar a viabilidade da quantificação do tecido adiposo visceral (TAV) pela tomografia computadorizada (TC) e ressonância magnética (RM) usando um software freeware, e também calcular a reprodutibilidade intraobservador e interobservador. MATERIAIS E MÉTODOS: Foi quantificado o TAV em pacientes submetidos a TC e RM de abdome em nossa instituição, entre 2010 e 2015, com um intervalo máximo de três meses entre os dois exames. Selecionou-se um corte adquirido ao nível da cicatriz umbilical. A segmentação foi realizada com o algoritmo de crescimento de região do freeware utilizado. As reprodutibilidades intraobservador e interobservador foram avaliadas, assim como a acurácia da RM em relação à TC. RESULTADOS: Trinta e um pacientes (14 homens e 17 mulheres; média de idade: 57 ± 15 anos) realizaram TC e RM (intervalo médio entre os exames: 28 ± 12 dias). A reprodutibilidade interobservador foi 82% para TC (viés = 1,52 cm2; p = 0,488), 86% para RM ponderada em T1 (viés = −4,36 cm2; p = 0,006) e 88% para RM ponderada em T2 (viés = −0,52 cm2; p = 0,735). A reprodutibilidade intraobservador foi 90% para TC (viés = 0,14 cm2; p = 0,912), 92% para RM ponderada em T1 (viés = −3,4 cm2; p = 0,035) e 90% para RM ponderada em T2 (viés = −0,30 cm2, p = 0,887). A reprodutibilidade entre a RM ponderada em T1 e a RM ponderada em T2 foi 87% (viés = −0,11 cm2; p = 0,957). Em comparação com a TC, a acurácia da RM ponderada em T1 e T2 foi 89% e 91%, respectivamente. CONCLUSÃO: O programa utilizado pode ser usado para quantificar o TAV na TC, na RM ponderada em T1 e na RM ponderada em T2. No geral, a acurácia da RM (em comparação com a TC) parece ser alta, assim como a reprodutibilidade intraobservador e interobservador. No entanto, a quantificação do TAV parece ser menos reprodutível nas sequências ponderadas em T1.

Quantification of visceral adipose tissue by computed tomography and magnetic resonance imaging: reproducibility and accuracy / Quantificação do tecido adiposo visceral por tomografia computadorizada e ressonância magnética: reprodutibilidade e acurácia

Abstract Objective: To evaluate the feasibility of quantifying visceral adipose tissue (VAT) on computed tomography (CT) and magnetic resonance imaging (MRI) scans, using freeware, as well as calculating intraobserver and interobserver reproducibility. Materials and Methods: We quantified VAT in patients who underwent abdominal CT and MRI at our institution between 2010 and 2015, with a maximum of three months between the two examinations. A slice acquired at the level of the umbilicus was selected. Segmentation was performed with the region growing algorithm of the freeware employed. Intraobserver and interobserver reproducibility were evaluated, as was the accuracy of MRI in relation to that of CT. Results: Thirty-one patients (14 males and 17 females; mean age of 57 ± 15 years) underwent CT and MRI (mean interval between the examinations, 28 ± 12 days). The interobserver reproducibility was 82% for CT (bias = 1.52 cm2; p = 0.488), 86% for T1-weighted MRI (bias = −4.36 cm2; p = 0.006), and 88% for T2-weighted MRI (bias = −0.52 cm2; p = 0.735). The intraobserver reproducibility was 90% for CT (bias = 0.14 cm2; p = 0.912), 92% for T1-weighted MRI (bias = −3,4 cm2; p = 0.035), and 90% for T2-weighted MRI (bias = −0.30 cm2; p = 0.887). The reproducibility between T1-weighted MRI and T2-weighted MRI was 87% (bias = −0.11 cm2; p = 0.957). In comparison with the accuracy of CT, that of T1-weighted and T2-weighted MRI was 89% and 91%, respectively. Conclusion: The program employed can be used in order to quantify VAT on CT, T1-weighted MRI, and T2-weighted MRI scans. Overall, the accuracy of MRI (in comparison with that of CT) appears to be high, as do intraobserver and interobserver reproducibility. However, the quantification of VAT seems to be less reproducible in T1-weighted sequences.

Resumo Objetivo: Avaliar a viabilidade da quantificação do tecido adiposo visceral (TAV) pela tomografia computadorizada (TC) e ressonância magnética (RM) usando um software freeware, e também calcular a reprodutibilidade intraobservador e interobservador. Materiais e Métodos: Foi quantificado o TAV em pacientes submetidos a TC e RM de abdome em nossa instituição, entre 2010 e 2015, com um intervalo máximo de três meses entre os dois exames. Selecionou-se um corte adquirido ao nível da cicatriz umbilical. A segmentação foi realizada com o algoritmo de crescimento de região do freeware utilizado. As reprodutibilidades intraobservador e interobservador foram avaliadas, assim como a acurácia da RM em relação à TC. Resultados: Trinta e um pacientes (14 homens e 17 mulheres; média de idade: 57 ± 15 anos) realizaram TC e RM (intervalo médio entre os exames: 28 ± 12 dias). A reprodutibilidade interobservador foi 82% para TC (viés = 1,52 cm2; p = 0,488), 86% para RM ponderada em T1 (viés = −4,36 cm2; p = 0,006) e 88% para RM ponderada em T2 (viés = −0,52 cm2; p = 0,735). A reprodutibilidade intraobservador foi 90% para TC (viés = 0,14 cm2; p = 0,912), 92% para RM ponderada em T1 (viés = −3,4 cm2; p = 0,035) e 90% para RM ponderada em T2 (viés = −0,30 cm2, p = 0,887). A reprodutibilidade entre a RM ponderada em T1 e a RM ponderada em T2 foi 87% (viés = −0,11 cm2; p = 0,957). Em comparação com a TC, a acurácia da RM ponderada em T1 e T2 foi 89% e 91%, respectivamente. Conclusão: O programa utilizado pode ser usado para quantificar o TAV na TC, na RM ponderada em T1 e na RM ponderada em T2. No geral, a acurácia da RM (em comparação com a TC) parece ser alta, assim como a reprodutibilidade intraobservador e interobservador. No entanto, a quantificação do TAV parece ser menos reprodutível nas sequências ponderadas em T1.

Application of diffusion kurtosis imaging to odontogenic lesions: Analysis of the cystic component.

PURPOSE: To assess the feasibility of applying diffusion kurtosis imaging (DKI) to common odontogenic lesions and to compare its diagnostic ability versus that of the apparent diffusion coefficient (ADC) for differentiating keratocystic odontogenic tumors (KCOTs) from odontogenic cysts. MATERIALS AND METHODS: Altogether, 35 odontogenic lesions were studied: 24 odontogenic cysts, six KCOTs, and five ameloblastomas. The diffusion coefficient (D) and excessive kurtosis (K) were obtained from diffusion-weighted images at b-values of 0, 500, 1000, and 1500 s/mm2 on 3T magnetic resonance imaging (MRI). The combination of D and K values showing the maximum density of the probable density function was estimated. The ADC was obtained (0 and 1000 s/mm2 ). Values for odontogenic cysts, KCOTs, and ameloblastomas were compared. Multivariate logistic regression modeling was performed to assess the combination of D and K model versus ADC for differentiating KCOTs from odontogenic cysts. RESULTS: The mean D and ADC were significantly higher for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean K was significantly lower for ameloblastomas than for odontogenic cysts or KCOTs (P < 0.05). The mean values of all parameters for odontogenic cysts and KCOTs showed no significant differences (P = 0.369 for ADC, 0.133 for D, and 0.874 for K). The accuracy of the combination of D and K model (76.7%) was superior to that of ADC (66.7%). CONCLUSION: Use of DKI may be feasible for common odontogenic lesions. A combination of DKI parameters can be expected to increase the accuracy of its diagnostic ability compared with ADC. J. Magn. Reson. Imaging 2016;44:1565-1571.

Preliminary report on use of 3-dimensional computed tomographic images in a disease-based transesophageal echocardiographic simulation system.

We used 3-dimensional computed tomographic images to create a disease-based transesophageal echocardiographic simulation system for complex congenital heart defects. We enrolled 7 pediatric patients with complex congenital heart defects in this proof-of-concept study. Preoperative computed tomographic images and intraoperative transesophageal echocardiographic images were acquired for all patients. Two- and 3-dimensional computed tomographic cross-sectional images were created to simulate the process of transesophageal echocardiographic image acquisition. Computed tomographic images simulating the midesophageal 4- and 5-chamber views, aortic valve short-axis views, long-axis views, and ascending aortic short-axis views were created to correspond with the actual transesophageal echocardiographic images from each patient. Four reviewers then evaluated the image quality of the computed tomographic images, the agreement between the echocardiographic and tomographic images, and the ability of the 3-dimensional computed tomographic full-volume and cross-sectional images to yield the spatial and temporal congruence of transesophageal echocardiograms. In most of the patients, computed tomography yielded images of good-to-excellent quality. Strong agreement was noted between the computed tomographic and transesophageal echocardiographic images acquired in the same patients. The ability of 3-dimensional computed tomography to yield the spatial and temporal congruence of transesophageal echocardiography in selected planes was also good to excellent. We found that 3-dimensional computed tomographic images can simulate the process of transesophageal echocardiography in acquiring the echocardiographic image clearly. This imaging method has the potential to be applied successfully to a disease-based transesophageal echocardiographic simulation system.