Moulton J S, Blebea J S, Dunco D M, Braley S E, Bisset G S, Emery K H
Department of Radiology, University of Cincinnati Medical Center, OH 45267-0742, USA.
AJR Am J Roentgenol. 1995 May;164(5):1191-9. doi: 10.2214/ajr.164.5.7717231.
The purpose of this study was to evaluate the efficacy of MR imaging in predicting the pathologic diagnosis of soft-tissue masses, both neoplastic and nonneoplastic, and in distinguishing benign from malignant lesions.
The imaging features of 225 soft-tissue tumors (179 benign, 46 malignant) in 222 patients were analyzed. Univariate analysis of multiple individual imaging features was done, along with stepwise logistic regression analysis of combinations of imaging features, to determine how useful these are for predicting malignancy or benignity. A subjective (group consensus) analysis of each case was done prospectively, and each tumor was placed into one of three diagnostic categories: (1) benign, diagnostic of a specific entity; (2) nonspecific, most likely benign; or (3) nonspecific, most likely malignant. Results were compared with the final diagnosis established by pathologic examination (n = 184) or imaging/clinical data (n = 41).
By quantitative analysis, no single imaging feature or combination of features could reliably be used to distinguish benign from malignant lesions. For the subjective analysis, a correct and specific benign diagnosis could be made on the basis of MR imaging findings in 100 (44%) of the 225 tumors. For the entire cohort, the sensitivity was 78%, the specificity was 89%, the positive predictive value was 65%, and the negative predictive value was 94% for a malignant diagnosis. When the diagnostic benign tumors were excluded, the specificity and negative predictive value decreased to 76% and 86%, respectively, whereas the sensitivity and positive predictive value remained the same.
Many benign soft-tissue masses can be correctly and confidently diagnosed with MR imaging. The prevalence of benign lesions among soft-tissue masses accounts for the relatively high specificity and negative predictive value that can be achieved with MR imaging for tissue characterization. However, the accuracy of MR imaging declines when these characteristic benign tumors are excluded from analysis. A significant percentage of malignant lesions may appear deceptively "benign" with the currently used criteria. For lesions whose imaging appearance is nonspecific, MR imaging is not reliable for distinguishing benign from malignant tumors, and these lesions warrant biopsy in most cases.
本研究的目的是评估磁共振成像(MR成像)在预测软组织肿块(包括肿瘤性和非肿瘤性)的病理诊断以及区分良性和恶性病变方面的效能。
分析了222例患者的225个软组织肿瘤(179个良性,46个恶性)的影像特征。对多个个体影像特征进行单因素分析,并对影像特征组合进行逐步逻辑回归分析,以确定这些特征在预测恶性或良性方面的有用性。对每个病例进行前瞻性主观(小组共识)分析,每个肿瘤被归入三个诊断类别之一:(1)良性,诊断为特定实体;(2)非特异性,很可能是良性;或(3)非特异性,很可能是恶性。将结果与通过病理检查确定的最终诊断(n = 184)或影像/临床数据(n = 41)进行比较。
通过定量分析,没有单一的影像特征或特征组合能够可靠地用于区分良性和恶性病变。对于主观分析,在225个肿瘤中的100个(44%)中,可根据MR成像结果做出正确且特异的良性诊断。对于整个队列,恶性诊断的敏感性为78%,特异性为89%,阳性预测值为65%,阴性预测值为94%。当排除诊断为良性的肿瘤时,特异性和阴性预测值分别降至76%和86%,而敏感性和阳性预测值保持不变。
许多良性软组织肿块可以通过MR成像正确且自信地诊断。软组织肿块中良性病变的患病率导致MR成像在组织特征描述方面可实现相对较高的特异性和阴性预测值。然而,当从分析中排除这些特征性良性肿瘤时,MR成像的准确性会下降。相当一部分恶性病变按照目前使用的标准可能看似“良性”。对于影像表现非特异性的病变,MR成像在区分良性和恶性肿瘤方面不可靠,在大多数情况下这些病变需要活检。