scholarly journals Faculty Opinions recommendation of Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma.

Author(s):  
Andrea Pace ◽  
Cherubino Di Lorenzo
2010 ◽  
Vol 28 (13) ◽  
pp. 2293-2299 ◽  
Author(s):  
Christina Tsien ◽  
Craig J. Galbán ◽  
Thomas L. Chenevert ◽  
Timothy D. Johnson ◽  
Daniel A. Hamstra ◽  
...  

Purpose To assess whether a new method of quantifying therapy-associated hemodynamic alterations may help to distinguish pseudoprogression from true progression in patients with high-grade glioma. Patients and Methods Patients with high-grade glioma received concurrent chemoradiotherapy. Relative cerebral blood volume (rCBV) and blood flow (rCBF) maps were acquired before chemoradiotherapy and at week 3 during treatment on a prospective institutional review board–approved study. Pseudoprogression was defined as imaging changes 1 to 3 months after chemoradiotherapy that mimic tumor progression but stabilized or improved without change in treatment or for which resection revealed radiation effects only. Clinical and conventional magnetic resonance (MR) parameters, including average percent change of rCBV and CBF, were evaluated as potential predictors of pseudoprogression. Parametric response map (PRM), an innovative, voxel-by-voxel method of image analysis, was also performed. Results Median radiation dose was 72 Gy (range, 60 to 78 Gy). Of 27 patients, stable disease/partial response was noted in 13 patients and apparent progression was noted in 14 patients. Adjuvant temozolomide was continued in all patients. Pseudoprogression occurred in six patients. Based on PRM analysis, a significantly reduced blood volume (PRMrCBV) at week 3 was noted in patients with progressive disease as compared with those with pseudoprogression (P < .01). In contrast, change in average percent rCBV or rCBF, MR tumor volume changes, age, extent of resection, and Radiation Therapy Oncology Group recursive partitioning analysis classification did not distinguish progression from pseudoprogression. Conclusion PRMrCBV at week 3 during chemoradiotherapy is a potential early imaging biomarker of response that may be helpful in distinguishing pseudoprogression from true progression in patients with high-grade glioma.


2008 ◽  
Vol 26 (20) ◽  
pp. 3387-3394 ◽  
Author(s):  
Daniel A. Hamstra ◽  
Craig J. Galbán ◽  
Charles R. Meyer ◽  
Timothy D. Johnson ◽  
Pia C. Sundgren ◽  
...  

PurposeAssessment of radiologic response (RR) for brain tumors utilizes the Macdonald criteria 8 to 10 weeks from the start of treatment. Diffusion magnetic resonance imaging (MRI) using a functional diffusion map (fDM) may provide an earlier measure to predict patient survival.Patients and MethodsSixty patients with high-grade glioma were enrolled onto a study of intratreatment MRI at 1, 3, and 10 weeks. Receiver operating characteristic curve analysis was used to evaluate imaging parameters as a function of patient survival at 1 year. Both log-rank and Cox proportional hazards models were utilized to assess overall survival.ResultsGreater increases in diffusion in response to therapy over time were observed in those patients alive at 1 year compared with those who died as a result of disease. The volume of tumor with increased diffusion by fDM at 3 weeks was the strongest predictor of patient survival at 1 year, with larger fDM predicting longer median survival (52.6 v 10.9 months; log-rank, P < .003; hazard ratio [HR] = 2.7; 95% CI, 1.5 to 5.9). Radiologic response at 10 weeks had similar prognostic value (median survival, 31.6 v 10.9 months; log-rank P < .0007; HR = 2.9; 95% CI, 1.7 to 7.2). Radiologic response and fDM differed in 25% of cases. A composite index of response including fDM and RR provided a robust predictor of patient survival and may identify patients in whom RR does not correlate with clinical outcome.ConclusionCompared with conventional neuroimaging, fDM provided an earlier assessment of equal predictive value, and the combination of fDM and RR provided a more accurate prediction of patient survival than either metric alone.


2014 ◽  
Vol 41 (10) ◽  
pp. 101903 ◽  
Author(s):  
Patrik Brynolfsson ◽  
David Nilsson ◽  
Roger Henriksson ◽  
Jón Hauksson ◽  
Mikael Karlsson ◽  
...  

2014 ◽  
Vol 16 (suppl 2) ◽  
pp. ii78-ii78
Author(s):  
T. Asklund ◽  
R. Birgander ◽  
P. Brynolfsson ◽  
A. Garpebring ◽  
J. Hauksson ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document