RT Journal Article
SR Electronic
T1 Early Metabolic Changes in 1H-MRSI Predictive for Survival in Patients With Newly Diagnosed High-grade Glioma
JF Anticancer Research
JO Anticancer Res
FD International Institute of Anticancer Research
SP 2665
OP 2673
DO 10.21873/anticanres.15744
VO 42
IS 5
A1 MICHAEL H. WANG
A1 WILSON ROA
A1 KEITH WACHOWICZ
A1 ATIYAH YAHYA
A1 ALBERT MURTHA
A1 JOHN AMANIE
A1 JONATHAN CHAINEY
A1 HARVEY QUON
A1 SUNITA GHOSH
A1 SAMIR PATEL
YR 2022
UL http://ar.iiarjournals.org/content/42/5/2665.abstract
AB Background: The purpose of this study was to evaluate the association of specific threshold values for changes in metabolic metrics measured from 1H magnetic resonance spectroscopic imaging (MRSI) to survival of patients with high-grade glioma treated with multimodality therapy. Patients and Methods: Forty-four patients with newly diagnosed high-grade glioma were prospectively enrolled. Serial MRI and MRSI scans provided measures of tumor choline, creatine, and N-acetylaspartate (NAA). Cox regression analyses adjusted for patient age, KPS, and delivery of concurrent chemotherapy were used to assess the association of changes in metabolic metrics with survival. Results: Median follow-up time for patients at risk was 13.4 years. Overall survival (OS) was longer in patients with ≤20% increase (vs. >20%) in normalized choline (p=0.024) or choline/NAA (p=0.024) from baseline to week 4 of RT. During this period, progression-free survival (PFS) was longer in patients with ≤40% increase (vs. >40%) in normalized choline (p=0.013). Changes in normalized creatine, choline/creatine, and NAA/creatine from baseline to mid-RT were not associated with OS. From baseline to post-RT, changes in metabolic metrics were not associated with OS or PFS. Conclusion: Threshold values for serial changes in choline metrics on mid-RT MRSI associated with OS and PFS were identified. Metabolic metrics at post-RT did not predict for these survival endpoints. These findings suggest a potential clinical role for MRSI to provide an early assessment of treatment response and could enable risk-adapted therapy in clinical trial development and clinical practice.