唐楚怡,陆杰,高叶祺,仲艳,沈杰.小视野弥散加权成像鉴别低危型与高危型胸腺瘤[J].中国医学影像技术,2024,40(12):1926~1930 |
小视野弥散加权成像鉴别低危型与高危型胸腺瘤 |
Reduced field-of-view diffusion weighted imaging for differentiating low-risk and high-risk thymoma |
投稿时间:2024-07-30 修订日期:2024-11-03 |
DOI:10.13929/j.issn.1003-3289.2024.12.025 |
中文关键词: 胸腺肿瘤 弥散磁共振成像 病理学 |
英文关键词:thymus neoplasms diffusion magnetic resonance imaging pathology |
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中文摘要: |
目的 观察小视野(rFOV)弥散加权成像(DWI)鉴别低危型与高危型胸腺瘤的价值。方法 回顾性收集145例经病理确诊的胸腺瘤患者,包括96例低危型(低危型组,含33例A型、29例AB型及34例B1型胸腺瘤)及49例高危型(高危型组,含26例B2型及23例B3型胸腺瘤)。比较治疗前MR常规单次激发平面回波成像(SSEPI)和ZOOMit序列DWI,针对2种图像所示解剖结构、胸腺瘤病灶、图像伪影和整体诊断信心进行主观评分,利用图像信噪比(SNR)和对比度噪声比(CNR)进行客观评价。对比低危型与高危型胸腺瘤的表观弥散系数(ADC);绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),评估ADC的鉴别效能。结果 ZOOMit序列DWI显示解剖结构、胸腺瘤病灶、图像伪影及整体诊断信心均优于SSEPI(P均<0.001),且其SNR及CNR均高于SSEPI(P<0.001)。组间ADCSSEPI及ADCZOOMit差异均有统计学意义(P均<0.001);ADCSSEPI及ADCZOOMit鉴别低危型与高危型胸腺瘤的AUC分别为0.865及0.922,后者高于前者(Z=2.091,P=0.037)。结论 rFOV DWI可用于评估胸腺瘤类型。 |
英文摘要: |
Objective To observe the value of reduced field-of-view (rFOV) diffusion weighted imaging (DWI) for differentiating low-risk and high-risk thymoma. Methods A total of 145 patients with pathologically confirmed thymoma were retrospectively collected, among them there were 96 cases of low-risk thymoma (low-risk group, including 33 cases of type A, 29 cases of type AB and 34 cases of type B1 thymoma) and 49 cases of high-risk thymoma (high-risk group, including 26 cases of type B2 and 23 cases of type B3 thymoma). Conventional single-shot echo planar imaging (SSEPI) and ZOOMit sequence DWI before treatment were compared, and subjective scoring based on displaying of anatomical structures, thymoma lesions, image artifacts and overall diagnosis confidence were performed, so did objective evaluation according to image signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of 2 kinds of images. The apparent diffusion coefficient (ADC) obtained with DWI were compared between groups. Receiver operating characteristic (ROC) curve was drawn, and area under the curve (AUC) was calculated to analyze the efficacy of ADC for differentiating low-risk and high-risk thymoma. Results Subjective scores of displaying anatomical structures, thymoma lesions, image artifacts and overall diagnosis confidence of ZOOMit were all superior to those of SSEPI (all P<0.001), while SNR and CNR of ZOOMit were both higher than those of SSEPI (all P<0.001). There were statistical differences of ADCSSEPI and ADCZOOMit between groups (both P<0.001). The AUC of ADCSSEPI and ADCZOOMit for distinguishing low-risk and high-risk thymoma was 0.865 and 0.922, respectively, of the former was higher than of the latter (Z=2.091, P=0.037). Conclusion rFOV DWI could be used to differentiate low-risk and high-risk thymoma. |
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