OBJECTIVE: Differentiation between recurrent neoplasm and postradiation change in patients previously treated for primary brain tumors is often difficult based on imaging features alone. The purpose of this study was to develop a method using alterations in the ratios of standard brain metabolites-choline (Cho), creatine (Cr), and N-acetylaspartate (NAA)-to predict the probability of tumor recurrence in patients previously treated for brain tumors with new contrast-enhancing lesions. MATERIALS AND METHODS: Thirty-three patients who had undergone treatment for primary brain tumors in whom routine MRI showed new contrast-enhancing lesions were retrospectively studied. The final diagnosis was assigned using histopathology (n = 13) or imaging follow-up (n = 20; range, 2-27 months). Ratios of three metabolites (Cho, Cr, and NAA) were calculated, and the results were correlated with the final diagnosis using a Wilcoxon's rank sum analysis. A logistic regression model was then used to create a prediction model based on the most statistically significant ratio. RESULTS: Elevations of the metabolic ratios Cho/Cr (p < 0.001) and Cho/NAA (p < 0.001) and a decrease in the ratio NAA/Cr (p = 0.018) were found in patients with recurrent tumor (n = 20) versus those with postradiation change (n = 13). A prediction model using the Cho/NAA ratio yielded a sensitivity of 85%, a specificity of 69.2%, and an area under the receiver operating characteristic curve of 0.92. CONCLUSION: An elevated Cho/NAA ratio correlated with evidence of tumor recurrence and allowed creation of a prediction rule to aid in lesion classification. The results suggest that MR spectroscopy is a useful tool in assigning patients with nonspecific enhancing lesions to either invasive biopsy or conservative management.
OBJECTIVE: Differentiation between recurrent neoplasm and postradiation change in patients previously treated for primary brain tumors is often difficult based on imaging features alone. The purpose of this study was to develop a method using alterations in the ratios of standard brain metabolites-choline (Cho), creatine (Cr), and N-acetylaspartate (NAA)-to predict the probability of tumor recurrence in patients previously treated for brain tumors with new contrast-enhancing lesions. MATERIALS AND METHODS: Thirty-three patients who had undergone treatment for primary brain tumors in whom routine MRI showed new contrast-enhancing lesions were retrospectively studied. The final diagnosis was assigned using histopathology (n = 13) or imaging follow-up (n = 20; range, 2-27 months). Ratios of three metabolites (Cho, Cr, and NAA) were calculated, and the results were correlated with the final diagnosis using a Wilcoxon's rank sum analysis. A logistic regression model was then used to create a prediction model based on the most statistically significant ratio. RESULTS: Elevations of the metabolic ratios Cho/Cr (p < 0.001) and Cho/NAA (p < 0.001) and a decrease in the ratio NAA/Cr (p = 0.018) were found in patients with recurrent tumor (n = 20) versus those with postradiation change (n = 13). A prediction model using the Cho/NAA ratio yielded a sensitivity of 85%, a specificity of 69.2%, and an area under the receiver operating characteristic curve of 0.92. CONCLUSION: An elevated Cho/NAA ratio correlated with evidence of tumor recurrence and allowed creation of a prediction rule to aid in lesion classification. The results suggest that MR spectroscopy is a useful tool in assigning patients with nonspecific enhancing lesions to either invasive biopsy or conservative management.
Authors: Rajan Jain; Jayant Narang; Pia M Sundgren; David Hearshen; Sona Saksena; Jack P Rock; Jorge Gutierrez; Tom Mikkelsen Journal: J Neurooncol Date: 2010-02-24 Impact factor: 4.130
Authors: William R Masch; Page I Wang; Thomas L Chenevert; Larry Junck; Christina Tsien; Jason A Heth; Pia C Sundgren Journal: Acad Radiol Date: 2016-02-23 Impact factor: 3.173
Authors: Manickam Muruganandham; Patrick P Clerkin; Brian J Smith; Carryn M Anderson; Ann Morris; Aristides A Capizzano; Vincent Magnotta; Sarah M McGuire; Mark C Smith; John E Bayouth; John M Buatti Journal: Int J Radiat Oncol Biol Phys Date: 2014-06-28 Impact factor: 7.038