Literature DB >> 21527563

Prospective analysis of parametric response map-derived MRI biomarkers: identification of early and distinct glioma response patterns not predicted by standard radiographic assessment.

Craig J Galbán1, Thomas L Chenevert, Charles R Meyer, Christina Tsien, Theodore S Lawrence, Daniel A Hamstra, Larry Junck, Pia C Sundgren, Timothy D Johnson, Stefanie Galbán, Judith S Sebolt-Leopold, Alnawaz Rehemtulla, Brian D Ross.   

Abstract

PURPOSE: Currently, radiologic response of brain tumors is assessed according to the Macdonald criteria 10 weeks from the start of therapy. There exists a critical need to identify nonresponding patients early in the course of their therapy for consideration of alternative treatment strategies. Our study assessed the effectiveness of the parametric response map (PRM) imaging biomarker to provide for an earlier measure of patient survival prediction. EXPERIMENTAL
DESIGN: Forty-five high-grade glioma patients received concurrent chemoradiation. Quantitative MRI including apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired pretreatment and 3 weeks midtreatment on a prospective institutional-approved study. PRM, a voxel-by-voxel image analysis method, was evaluated as an early prognostic biomarker of overall survival. Clinical and conventional MR parameters were also evaluated.
RESULTS: Multivariate analysis showed that PRM(ADC+) in combination with PRM(rCBV-) obtained at week 3 had a stronger correlation to 1-year and overall survival rates than any baseline clinical or treatment response imaging metric. The composite biomarker identified three distinct patient groups, nonresponders [median survival (MS) of 5.5 months, 95% CI: 4.4-6.6 months], partial responders (MS of 16 months, 95% CI: 8.6-23.4 months), and responders (MS has not yet been reached).
CONCLUSIONS: Inclusion of PRM(ADC+) and PRM(rCBV-) into a single imaging biomarker metric provided early identification of patients resistant to standard chemoradiation. In comparison to the current standard of assessment of response at 10 weeks (Macdonald criteria), the composite PRM biomarker potentially provides a useful opportunity for clinicians to identify patients who may benefit from alternative treatment strategies.

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Year:  2011        PMID: 21527563      PMCID: PMC3139775          DOI: 10.1158/1078-0432.CCR-10-2098

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  40 in total

1.  Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.

Authors:  C R Meyer; J L Boes; B Kim; P H Bland; K R Zasadny; P V Kison; K Koral; K A Frey; R L Wahl
Journal:  Med Image Anal       Date:  1997-04       Impact factor: 8.545

Review 2.  Modeling tracer kinetics in dynamic Gd-DTPA MR imaging.

Authors:  P S Tofts
Journal:  J Magn Reson Imaging       Date:  1997 Jan-Feb       Impact factor: 4.813

3.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis.

Authors:  L Ostergaard; R M Weisskoff; D A Chesler; C Gyldensted; B R Rosen
Journal:  Magn Reson Med       Date:  1996-11       Impact factor: 4.668

Review 4.  Personalized medicine in oncology: the future is now.

Authors:  Richard L Schilsky
Journal:  Nat Rev Drug Discov       Date:  2010-05       Impact factor: 84.694

5.  Survival and failure patterns of high-grade gliomas after three-dimensional conformal radiotherapy.

Authors:  June L Chan; Susan W Lee; Benedick A Fraass; Daniel P Normolle; Harry S Greenberg; Larry R Junck; Stephen S Gebarski; Howard M Sandler
Journal:  J Clin Oncol       Date:  2002-03-15       Impact factor: 44.544

6.  Refocusing the war on cancer: the critical role of personalized treatment.

Authors:  Anil Potti; Richard L Schilsky; Joseph R Nevins
Journal:  Sci Transl Med       Date:  2010-04-21       Impact factor: 17.956

7.  Magnetic resonance perfusion and permeability imaging in brain tumors.

Authors:  Saulo Lacerda; Meng Law
Journal:  Neuroimaging Clin N Am       Date:  2009-11       Impact factor: 2.264

8.  Diffusion magnetic resonance imaging: an imaging treatment response biomarker to chemoradiotherapy in a mouse model of squamous cell cancer of the head and neck.

Authors:  Daniel A Hamstra; Kuei C Lee; Bradford A Moffat; Thomas L Chenevert; Alnawaz Rehemtulla; Brian D Ross
Journal:  Transl Oncol       Date:  2008-12       Impact factor: 4.243

9.  Recursive partitioning analysis of prognostic factors in three Radiation Therapy Oncology Group malignant glioma trials.

Authors:  W J Curran; C B Scott; J Horton; J S Nelson; A S Weinstein; A J Fischbach; C H Chang; M Rotman; S O Asbell; R E Krisch
Journal:  J Natl Cancer Inst       Date:  1993-05-05       Impact factor: 13.506

10.  Monitoring of gliomas in vivo by diffusion MRI and (1)H MRS during gene therapy-induced apoptosis: interrelationships between water diffusion and mobile lipids.

Authors:  Timo Liimatainen; Juhana M Hakumäki; Risto A Kauppinen; Mika Ala-Korpela
Journal:  NMR Biomed       Date:  2009-04       Impact factor: 4.044

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  46 in total

Review 1.  Multimodality Brain Tumor Imaging: MR Imaging, PET, and PET/MR Imaging.

Authors:  James R Fink; Mark Muzi; Melinda Peck; Kenneth A Krohn
Journal:  J Nucl Med       Date:  2015-08-20       Impact factor: 10.057

Review 2.  Mechanism-Based Modeling of Tumor Growth and Treatment Response Constrained by Multiparametric Imaging Data.

Authors:  David A Hormuth; Angela M Jarrett; Ernesto A B F Lima; Matthew T McKenna; David T Fuentes; Thomas E Yankeelov
Journal:  JCO Clin Cancer Inform       Date:  2019-02

3.  Parametric response mapping of dynamic CT for predicting intrahepatic recurrence of hepatocellular carcinoma after conventional transcatheter arterial chemoembolization.

Authors:  Seung Joon Choi; Jonghoon Kim; Jongbum Seo; Hyung Sik Kim; Jong-min Lee; Hyunjin Park
Journal:  Eur Radiol       Date:  2015-05-20       Impact factor: 5.315

4.  Feasibility evaluation of diffusion-weighted imaging using an integrated MRI-radiotherapy system for response assessment to neoadjuvant therapy in rectal cancer.

Authors:  Narek Shaverdian; Yingli Yang; Peng Hu; Steven Hart; Ke Sheng; James Lamb; Minsong Cao; Nzhde Agazaryan; David Thomas; Michael Steinberg; Daniel A Low; Percy Lee
Journal:  Br J Radiol       Date:  2017-01-12       Impact factor: 3.039

5.  Radiomic signature of infiltration in peritumoral edema predicts subsequent recurrence in glioblastoma: implications for personalized radiotherapy planning.

Authors:  Saima Rathore; Hamed Akbari; Jimit Doshi; Gaurav Shukla; Martin Rozycki; Michel Bilello; Robert Lustig; Christos Davatzikos
Journal:  J Med Imaging (Bellingham)       Date:  2018-03-01

6.  Analyzing Spatial Heterogeneity in DCE- and DW-MRI Parametric Maps to Optimize Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer.

Authors:  Xia Li; Hakmook Kang; Lori R Arlinghaus; Richard G Abramson; A Bapsi Chakravarthy; Vandana G Abramson; Jaime Farley; Melinda Sanders; Thomas E Yankeelov
Journal:  Transl Oncol       Date:  2014-02-01       Impact factor: 4.243

7.  Assessing reproducibility of diffusion-weighted magnetic resonance imaging studies in a murine model of HER2+ breast cancer.

Authors:  Jennifer G Whisenant; Gregory D Ayers; Mary E Loveless; Stephanie L Barnes; Daniel C Colvin; Thomas E Yankeelov
Journal:  Magn Reson Imaging       Date:  2013-12-14       Impact factor: 2.546

Review 8.  Clinical applications for diffusion magnetic resonance imaging in radiotherapy.

Authors:  Christina Tsien; Yue Cao; Thomas Chenevert
Journal:  Semin Radiat Oncol       Date:  2014-07       Impact factor: 5.934

9.  Impact of perfusion map analysis on early survival prediction accuracy in glioma patients.

Authors:  Benjamin Lemasson; Thomas L Chenevert; Theodore S Lawrence; Christina Tsien; Pia C Sundgren; Charles R Meyer; Larry Junck; Jennifer Boes; Stefanie Galbán; Timothy D Johnson; Alnawaz Rehemtulla; Brian D Ross; Craig J Galbán
Journal:  Transl Oncol       Date:  2013-12-01       Impact factor: 4.243

10.  MRI perfusion in determining pseudoprogression in patients with glioblastoma.

Authors:  Robert J Young; Ajay Gupta; Akash D Shah; Jerome J Graber; Timothy A Chan; Zhigang Zhang; Weiji Shi; Kathryn Beal; Antonio M Omuro
Journal:  Clin Imaging       Date:  2012-06-08       Impact factor: 1.605

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