Literature DB >> 16267128

Evaluation of the functional diffusion map as an early biomarker of time-to-progression and overall survival in high-grade glioma.

Daniel A Hamstra1, Thomas L Chenevert, Bradford A Moffat, Timothy D Johnson, Charles R Meyer, Suresh K Mukherji, Douglas J Quint, Stephen S Gebarski, Xiaoying Fan, Christina I Tsien, Theodore S Lawrence, Larry Junck, Alnawaz Rehemtulla, Brian D Ross.   

Abstract

Diffuse malignant gliomas, the most common type of brain tumor, carry a dire prognosis and are poorly responsive to initial treatment. The response to treatment is typically evaluated by measurements obtained from radiographic images several months after the start of treatment; therefore, an early biomarker of tumor response would be useful for making early treatment decisions and for prognostic information. Thirty-four patients with malignant glioma were examined by diffusion MRI before treatment and 3 weeks later. These images were coregistered, and differences in tumor-water diffusion values were calculated as functional diffusion maps (fDM), which were correlated with the radiographic response, time-to-progression (TTP), and overall survival (OS). Changes in fDM at 3 weeks were closely associated with the radiographic response at 10 weeks. The percentage of the tumor undergoing a significant change in the diffusion of water (V(T)) was different between patients with progressive disease (PD) vs. stable disease (SD) (P < 0.001). Patients classified as PD by fDM analysis at 3 weeks were found to have a shorter TTP compared with SD (median TTP, 4.3 vs. 7.3 months; P < 0.04). By using fDM, early patient stratification also was correlated with shorter OS in the PD group compared with SD patients (median survival, 8.0 vs. 18.2 months; P < 0.01). On the basis of fDM, tumor assessment provided an early biomarker for response, TTP, and OS in patients with malignant glioma. Further evaluation of this technique is warranted to determine whether it may be useful in the individualization of treatment or evaluation of the response in clinical protocols.

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Year:  2005        PMID: 16267128      PMCID: PMC1276616          DOI: 10.1073/pnas.0508347102

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  34 in total

1.  In vivo diffusion-weighted MRI of the breast: potential for lesion characterization.

Authors:  Shantanu Sinha; Flora Anne Lucas-Quesada; Usha Sinha; Nanette DeBruhl; Lawrence W Bassett
Journal:  J Magn Reson Imaging       Date:  2002-06       Impact factor: 4.813

2.  Diffusion tensor MR imaging of the human brain.

Authors:  C Pierpaoli; P Jezzard; P J Basser; A Barnett; G Di Chiro
Journal:  Radiology       Date:  1996-12       Impact factor: 11.105

3.  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

4.  Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging.

Authors:  D Le Bihan; E Breton; D Lallemand; M L Aubin; J Vignaud; M Laval-Jeantet
Journal:  Radiology       Date:  1988-08       Impact factor: 11.105

5.  Response and progression in recurrent malignant glioma.

Authors:  K R Hess; E T Wong; K A Jaeckle; A P Kyritsis; V A Levin; M D Prados; W K Yung
Journal:  Neuro Oncol       Date:  1999-10       Impact factor: 12.300

6.  Radiation response and survival time in patients with glioblastoma multiforme.

Authors:  F G Barker; M D Prados; S M Chang; P H Gutin; K R Lamborn; D A Larson; M K Malec; M W McDermott; P K Sneed; W M Wara; C B Wilson
Journal:  J Neurosurg       Date:  1996-03       Impact factor: 5.115

7.  Head and neck lesions: characterization with diffusion-weighted echo-planar MR imaging.

Authors:  J Wang; S Takashima; F Takayama; S Kawakami; A Saito; T Matsushita; M Momose; T Ishiyama
Journal:  Radiology       Date:  2001-09       Impact factor: 11.105

8.  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

Review 9.  Primary brain tumours in adults.

Authors:  Anthony Behin; Khe Hoang-Xuan; Antoine F Carpentier; Jean-Yves Delattre
Journal:  Lancet       Date:  2003-01-25       Impact factor: 79.321

10.  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

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  125 in total

1.  Independent prognostic value of pre-treatment 18-FDG-PET in high-grade gliomas.

Authors:  Cécile Colavolpe; Philippe Metellus; Julien Mancini; Maryline Barrie; Céline Béquet-Boucard; Dominique Figarella-Branger; Olivier Mundler; Olivier Chinot; Eric Guedj
Journal:  J Neurooncol       Date:  2011-12-15       Impact factor: 4.130

2.  Functional diffusion maps (fDMs) evaluated before and after radiochemotherapy predict progression-free and overall survival in newly diagnosed glioblastoma.

Authors:  Benjamin M Ellingson; Timothy F Cloughesy; Taryar Zaw; Albert Lai; Phioanh L Nghiemphu; Robert Harris; Shadi Lalezari; Naveed Wagle; Kourosh M Naeini; Jose Carrillo; Linda M Liau; Whitney B Pope
Journal:  Neuro Oncol       Date:  2012-01-22       Impact factor: 12.300

3.  Monitoring peri-therapeutic cerebral circulation time: a feasibility study using color-coded quantitative DSA in patients with steno-occlusive arterial disease.

Authors:  C J Lin; S C Hung; W Y Guo; F C Chang; C B Luo; J Beilner; M Kowarschik; W F Chu; C Y Chang
Journal:  AJNR Am J Neuroradiol       Date:  2012-04-12       Impact factor: 3.825

Review 4.  Applications of molecular imaging.

Authors:  Craig J Galbán; Stefanie Galbán; Marcian E Van Dort; Gary D Luker; Mahaveer S Bhojani; Alnawaz Rehemtulla; Brian D Ross
Journal:  Prog Mol Biol Transl Sci       Date:  2010       Impact factor: 3.622

5.  Longitudinal Image Analysis of Tumor/Healthy Brain Change in Contrast Uptake Induced by Radiation.

Authors:  Xiaoxi Zhang; Timothy D Johnson; Roderick J A Little; Yue Cao
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2010-11-01       Impact factor: 1.864

6.  Evaluation of diffusion parameters as early biomarkers of disease progression in glioblastoma multiforme.

Authors:  Inas S Khayal; Mei-Yin C Polley; Llewellyn Jalbert; Adam Elkhaled; Susan M Chang; Soonmee Cha; Nicholas A Butowski; Sarah J Nelson
Journal:  Neuro Oncol       Date:  2010-05-25       Impact factor: 12.300

Review 7.  Diffusion-weighted MRI for assessment of early cancer treatment response.

Authors:  Stefanie Galbán; Jean-Christophe Brisset; Alnawaz Rehemtulla; Thomas L Chenevert; Brian D Ross; Craig J Galbán
Journal:  Curr Pharm Biotechnol       Date:  2010-09-01       Impact factor: 2.837

8.  Effects of perfusion on diffusion changes in human brain tumors.

Authors:  Alexander D Cohen; Peter S LaViolette; Melissa Prah; Jennifer Connelly; Mark G Malkin; Scott D Rand; Wade M Mueller; Kathleen M Schmainda
Journal:  J Magn Reson Imaging       Date:  2013-02-06       Impact factor: 4.813

Review 9.  Whole-body diffusion-weighted and proton imaging: a review of this emerging technology for monitoring metastatic cancer.

Authors:  Michael A Jacobs; Li Pan; Katarzyna J Macura
Journal:  Semin Roentgenol       Date:  2009-04       Impact factor: 0.800

Review 10.  Invited review--neuroimaging response assessment criteria for brain tumors in veterinary patients.

Authors:  John H Rossmeisl; Paulo A Garcia; Gregory B Daniel; John Daniel Bourland; Waldemar Debinski; Nikolaos Dervisis; Shawna Klahn
Journal:  Vet Radiol Ultrasound       Date:  2013-11-13       Impact factor: 1.363

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