OBJECTIVE: 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. MATERIALS AND METHODS: 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). RESULTS: 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. CONCLUSION: 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.
OBJECTIVE: 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. MATERIALS AND METHODS: 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). RESULTS: 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. CONCLUSION: 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.
Authors: Jan L M A Gielen; Arthur M De Schepper; Filip Vanhoenacker; Paul M Parizel; Xiaoling L Wang; Raf Sciot; Joost Weyler Journal: Eur Radiol Date: 2004-07-29 Impact factor: 5.315
Authors: Carlo Masciocchi; Giuseppe Lanni; Laura Conti; Armando Conchiglia; Eva Fascetti; Stefano Flamini; Gino Coletti; Antonio Barile Journal: Skeletal Radiol Date: 2011-09-24 Impact factor: 2.199
Authors: Youssef Erfanian; Johannes Grueneisen; Julian Kirchner; Axel Wetter; Lars Erik Podleska; Sebastian Bauer; Thorsten Poeppel; Michael Forsting; Ken Herrmann; Lale Umutlu Journal: Eur J Nucl Med Mol Imaging Date: 2017-05-31 Impact factor: 9.236