OBJECTIVE: Most patients with a malignant glioma spend considerable time on a treatment protocol before their response (or nonresponse) to the therapy can be determined. Because survival time in the absence of effective therapy is short, the ability to predict the potential chemosensitivity of individual brain tumors noninvasively would represent a significant advance in chemotherapy planning. METHODS: Using proton magnetic resonance spectroscopic imaging (1H MRSI), we studied 16 patients with a recurrent malignant glioma before and during treatment with high-dose orally administered tamoxifen. We evaluated whether 1H MRSI data could predict eventual therapeutic response to tamoxifen at the pretreatment and early treatment stages. RESULTS: Seven patients responded to tamoxifen therapy (three with glioblastomas multiforme; four with anaplastic astrocytomas), and nine did not (six with glioblastomas multiforme; three with anaplastic astrocytomas). Responders and nonresponders exhibited no differences in their age, sex, tumor type, mean tumor volume, mean Karnofsky scale score, mean number of weeks postradiotherapy, or mean amount of prior radiation exposure. Resonance profiles across the five metabolites measured on 1H MRSI spectra (choline-containing compounds, creatine and phosphocreatine, N-acetyl groups, lactate, and lipids) differed significantly between these two groups before and during treatment. Furthermore, linear discriminant analyses based on patients' in vivo biochemical information accurately predicted individual response to tamoxifen both before and at very early treatment stages (2 and 4 wk). Similar analyses based on patient sex, age, Karnofsky scale score, tumor type, and tumor volume could not reliably predict the response to tamoxifen treatment at the same time periods. CONCLUSION: It is possible to accurately predict the response of a tumor to tamoxifen on the basis of noninvasively acquired in vivo biochemical information. 1H MRSI has potential as a prognostic tool in the pharmacological treatment of recurrent malignant gliomas.
OBJECTIVE: Most patients with a malignant glioma spend considerable time on a treatment protocol before their response (or nonresponse) to the therapy can be determined. Because survival time in the absence of effective therapy is short, the ability to predict the potential chemosensitivity of individual brain tumors noninvasively would represent a significant advance in chemotherapy planning. METHODS: Using proton magnetic resonance spectroscopic imaging (1H MRSI), we studied 16 patients with a recurrent malignant glioma before and during treatment with high-dose orally administered tamoxifen. We evaluated whether 1H MRSI data could predict eventual therapeutic response to tamoxifen at the pretreatment and early treatment stages. RESULTS: Seven patients responded to tamoxifen therapy (three with glioblastomas multiforme; four with anaplastic astrocytomas), and nine did not (six with glioblastomas multiforme; three with anaplastic astrocytomas). Responders and nonresponders exhibited no differences in their age, sex, tumor type, mean tumor volume, mean Karnofsky scale score, mean number of weeks postradiotherapy, or mean amount of prior radiation exposure. Resonance profiles across the five metabolites measured on 1H MRSI spectra (choline-containing compounds, creatine and phosphocreatine, N-acetyl groups, lactate, and lipids) differed significantly between these two groups before and during treatment. Furthermore, linear discriminant analyses based on patients' in vivo biochemical information accurately predicted individual response to tamoxifen both before and at very early treatment stages (2 and 4 wk). Similar analyses based on patient sex, age, Karnofsky scale score, tumor type, and tumor volume could not reliably predict the response to tamoxifen treatment at the same time periods. CONCLUSION: It is possible to accurately predict the response of a tumor to tamoxifen on the basis of noninvasively acquired in vivo biochemical information. 1H MRSI has potential as a prognostic tool in the pharmacological treatment of recurrent malignant gliomas.
Authors: Casilda Balmaceda; Dana Critchell; Xiangling Mao; Kenneth Cheung; Susan Pannullo; Robert L DeLaPaz; Dikoma C Shungu Journal: J Neurooncol Date: 2006-01 Impact factor: 4.130
Authors: Jonathan P Dyke; Pina C Sanelli; Henning U Voss; Jennifer V Serventi; Philip E Stieg; Theodore H Schwartz; Douglas Ballon; Dikoma C Shungu; Susan C Pannullo Journal: J Neurooncol Date: 2006-09-22 Impact factor: 4.130
Authors: Barjor Gimi; Arvind P Pathak; Ellen Ackerstaff; Kristine Glunde; Dmitri Artemov; Zaver M Bhujwalla Journal: Proc IEEE Inst Electr Electron Eng Date: 2005-04-01 Impact factor: 10.961