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1.
Chinese Journal of Radiology ; (12): 569-572, 2008.
Artigo em Chinês | WPRIM | ID: wpr-400371

RESUMO

Objective To find the effective quantitative parameters for the differentiation of the breast lesions using the post-processing of time.signal curve of 3D dynamic-enhanced MRI.Methods Thirty patients with 35 lesions underwent 3D dynamic-enhanced MRI and the time-signal cHIve was deduced.The four quantitative parameters including SImax,PH,Slope and SlopeR were analyzed in benign andmalignant lesions of the breast.Independent samples t test and rank sum test were used for the statistics.Results Seyenteen benign lesions and 18 malignant lesions were included in this study.The SImax(M)of benign and malignant lesions were 375.2 and 158.1,the 95% confidence intervals of SImax were 278.2-506.0 and 160.5-374.8.The PH(M)of benign and malignant lesions were 114.4 and 87.8,the 95% confidence intervals of PH were 73.7-196.5 and 71.3-162.9.The Slope(M) of benign and malignant lesions were 22.3×10-3 and 44.0×10-3,the 95% confidence intervals of Slope were 13.7×10-3-41.1×10-3 and 46.1×10-3-81.8×10-3.The Slope"(M) of benign and malignant lesions were 2.6 and11.4,the 95% confidence intervals of SlopeR were 1.9-3.4 and 9.8-14.5.There were no significant differences on SImax and PH between benign and malignant lesions(P>0.05).The significant differences existed on Slope(P<0.01)and SlopeR(P<0.01)between benign and malignant lesions of the breast.Conclusion SlopeR is a very effective parameter in t}le differential diagnosis of breast lesions.

2.
Chinese Journal of Oncology ; (12): 173-177, 2002.
Artigo em Chinês | WPRIM | ID: wpr-354042

RESUMO

<p><b>OBJECTIVE</b>To compare quantitatively the enhanced thin CT section with pathologic findings in pulmonary carcinoma, pulmonary inflammatory pseudotumor (IPT) and pulmonary tuberculoma so as to demonstrate the relation of degree of enhancement and the vascular structure within the lesion with special emphasis on pulmonary carcinoma.</p><p><b>METHODS</b>Enhanced thin CT sections were obtained in 35 cases with nodular or patchy lesions in the peripheral lung field which are difficult to differentiate clinically. There were pulmonary carcinoma 21, inflammatory pseudotumor 7 and tuberculoma 7. The number of small vessels (inner diameter 0.02 approximately 0.1 mm), relatively large vessels (inner diameter > 0.1 mm) and their vascular bed areas were analyzed by computed image analyzing system. The relation between CT average attenuation and the number of vessels or the vascular bed areas were statistically evaluated.</p><p><b>RESULTS</b>1. The differences of average attenuation in carcinoma, inflammatory pseudotumor and tuberculoma were statistically significant (P < 0.05). 2. The differences in number of small vessels, relatively large vessels and vascular bed areas among these three types of lesion were also significant (P < 0.05). 3. A positive correlation was found in the average CT affenuation of lung carcinoma and its number of small vessels and relatively large vessels and 4. A positive correlation was found between the average CT attenuation in these three lesions and the relatively large vessels, total vascular amount and vascular bed areas.</p><p><b>CONCLUSIONS</b>1. The average degree of attenuation, being divided into four degrees, is of practical value in the differentiation of lung carcinoma, inflammatory pseudotumor and tuberculoma. 2. The average CT attenuation of lung carcinoma, inflammatory pseudotumor and tuberculoma is in direct proportion to the number of vessels and vessel bed areas and 3. The characteristic CT enhancement in lung carcinoma reflexes the condition of vessels and blood supply within the tumor.</p>


Assuntos
Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pulmão , Diagnóstico por Imagem , Patologia , Neoplasias Pulmonares , Diagnóstico por Imagem , Patologia , Granuloma de Células Plasmáticas Pulmonar , Diagnóstico por Imagem , Patologia , Tomografia Computadorizada por Raios X , Métodos , Tuberculoma , Diagnóstico por Imagem , Patologia , Tuberculose Pulmonar , Diagnóstico por Imagem , Patologia
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