Literature DB >> 21285888

Treatment monitoring in gliomas: comparison of dynamic susceptibility-weighted contrast-enhanced and spectroscopic MRI techniques for identifying treatment failure.

Jonathan Vöglein1, Jochen Tüttenberg, Marc Weimer, Lars Gerigk, Hans-Ulrich Kauczor, Marco Essig, Marc-André Weber.   

Abstract

OBJECTIVE: To evaluate whether dynamic susceptibility-weighted contrast-enhanced (DSC), dynamic contrast-enhanced (DCE), and proton spectroscopic imaging ((1)H-MRSI) can identify progression and predict treatment failure during follow-up before tumor size changes, contrast agent uptake, or when new lesions become obvious. The aim was also to find out which of the aforementioned techniques had the best diagnostic performance compared with each other and standard magnetic resonance imaging (MRI).
MATERIALS AND METHODS: Thirty-seven patients with gliomas (21 women, 16 men; mean age at inclusion, 48 ± 14 years [standard deviation]) were assessed prospectively by (1)H-MRSI (point-resolved spectroscopy), DCE, and DSC perfusion MRI, each after a single dose of gadobenate dimeglumine during follow-up. Histology was available in all cases (resection, N = 18; biopsy, N = 19). All patients with low-grade gliomas (n = 20) did not receive any radio- or chemotherapy after partial resection (n = 7) or biopsy (n = 13), whereas 17 patients with high-grade gliomas had received adjuvant radiotherapy immediately after surgery. Tumor progression (progressive disease, PD) was defined as increase in longest glioma diameter by at least 20% (Response Evaluation Criteria in Solid Tumors), appearance of new lesions, or new contrast-enhancement. DSC, DCE, and MRSI image analyses comprised a detailed semiquantitative region of interest (ROI) analysis of the different parameters. Wilcoxon signed-rank test, Wilcoxon rank sum test, and Cox regression were used for statistical analysis.
RESULTS: The median follow-up time was 607 days. Twenty patients showed PD (54%), 8 of 20 with low-grade (40%) and 12 of 17 with high-grade gliomas (71%). In PD, significant positive differences between log2-transformed ROI ratios at the last measurement in comparison to the first measurement (baseline) could be detected for tumor blood flow (P < 0.006) and volume (P < 0.001) derived from DSC and for maximum choline within tumor tissue (P = 0.0029) and Cho/Cr (P = 0.032) but not choline/N-acetyl-aspartate (P = 0.37) derived from MRSI. In contrast, these parameters were not significantly higher at last measurement in stable disease. Also, the differences between last value and baseline were significantly different between PD and stable disease for tumor blood flow (P < 0.004) and volume (P < 0.002) as well as for maximum choline within tumor tissue (P = 0.0011). The best prognostic parameter for PD at Cox analysis was time-dependent difference to baseline of log2 of relative regional cerebral blood flow normalized on gray matter (hazard ratio, 2.67; 95% confidence interval, 1.25-6.08; P = 0.01), while a prognostic value of MRS parameters could not be demonstrated.
CONCLUSION: DSC perfusion imaging can identify progression and can predict treatment failure during follow-up of gliomas with the best diagnostic performance.

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Year:  2011        PMID: 21285888     DOI: 10.1097/RLI.0b013e31820e1511

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  19 in total

Review 1.  Applications of imaging technology in radiation research.

Authors:  MingDe Lin; Edward F Jackson
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2.  Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen.

Authors:  Sarah J Nelson; Achuta K Kadambi; Ilwoo Park; Yan Li; Jason Crane; Marram Olson; Annette Molinaro; Ritu Roy; Nicholas Butowski; Soonmee Cha; Susan Chang
Journal:  Neuro Oncol       Date:  2017-03-01       Impact factor: 12.300

3.  Diagnostic accuracy of proton magnetic resonance spectroscopy and perfusion-weighted imaging in brain gliomas follow-up: a single institutional experience.

Authors:  Monica Anselmi; Alessia Catalucci; Valentina Felli; Valentina Vellucci; Alessandra Di Sibio; Giovanni Luca Gravina; Mario Di Staso; Ernesto Di Cesare; Carlo Masciocchi
Journal:  Neuroradiol J       Date:  2017-01-01

Review 4.  Benefits of dynamic susceptibility-weighted contrast-enhanced perfusion MRI for glioma diagnosis and therapy.

Authors:  Ramon Francisco Barajas; Soonmee Cha
Journal:  CNS Oncol       Date:  2014-11

5.  Effect of Region of Interest Size on the Repeatability of Quantitative Brain Imaging Biomarkers.

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Journal:  IEEE Trans Biomed Eng       Date:  2018-07-27       Impact factor: 4.538

6.  Survival prediction in high-grade gliomas using CT perfusion imaging.

Authors:  Timothy Pok Chi Yeung; Yong Wang; Wenqing He; Benedetta Urbini; Roberta Gafà; Linda Ulazzi; Slav Yartsev; Glenn Bauman; Ting-Yim Lee; Enrico Fainardi
Journal:  J Neurooncol       Date:  2015-04-11       Impact factor: 4.130

7.  Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma.

Authors:  M A Prah; S M Stufflebeam; E S Paulson; J Kalpathy-Cramer; E R Gerstner; T T Batchelor; D P Barboriak; B R Rosen; K M Schmainda
Journal:  AJNR Am J Neuroradiol       Date:  2015-06-11       Impact factor: 3.825

8.  Posttreatment DSC-MRI is Predictive of Early Treatment Failure in Children with Supratentorial High-Grade Glioma Treated with Erlotinib.

Authors:  John T Lucas; Brendan J Knapp; Jinsoo Uh; Chia-Ho Hua; Thomas E Merchant; Scott N Hwang; Zoltan Patay; Alberto Broniscer
Journal:  Clin Neuroradiol       Date:  2017-04-05       Impact factor: 3.649

9.  ¹⁸F-Fluorocholine PET/CT as a complementary tool in the follow-up of low-grade glioma: diagnostic accuracy and clinical utility.

Authors:  Manuel Gómez-Río; Nathalie Testart Dardel; Alicia Santiago Chinchilla; Antonio Rodríguez-Fernández; Gonzalo Olivares Granados; Raquel Luque Caro; Mercedes Zurita Herrera; Clara E Chamorro Santos; Pablo Lardelli-Claret; José M Llamas-Elvira
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-02-12       Impact factor: 9.236

Review 10.  Musculoskeletal tumors: how to use anatomic, functional, and metabolic MR techniques.

Authors:  Laura M Fayad; Michael A Jacobs; Xin Wang; John A Carrino; David A Bluemke
Journal:  Radiology       Date:  2012-11       Impact factor: 11.105

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