Literature DB >> 23638244

Characterizing at-Risk Voxels by Using Perfusion Magnetic Resonance Imaging for Cervical Cancer during Radiotherapy.

Zhibin Huang1, Nina A Mayr, Simon S Lo, John C Grecula, Jian Z Wang, Guang Jia, William Tc Yuh.   

Abstract

The number of voxels with low signal intensity (Low DCE voxels) might be potentially related to treatment failure, which might be associated with the tumor oxygenation status. Our goal was to investigate whether at-risk voxels can be used to predict treatment outcome during radiation therapy for cervical cancer. 80 patients with Stage IB2-IVB cervical cancer were included. Four sequential MRI scans were performed at pre-RT, every 2-2.5 weeks during RT, and post-radiotherapy. 3D volumetric data including tumor regression and tumor perfusion from dynamic contrast enhanced MRI (DCE-MRI) were analyzed. Based on the signal intensity (SI) curves of the DCE-MRI, the low-DCE tumor voxels was obtained for individual patients. The predictive power of low DCE voxels in predicting the treatment outcomes was evaluated by Kaplan-Meier survival analysis. Correlation of low DCE voxels with hemoglobin (Hgb) was checked by Pearson Correlation. The actuarial local control rate and survival rate in the patient group with a small number of low DCE voxels were 89.7% and 76.9%, compared with 75.6% and 51.2% in the patient group with a big number of low DCE voxels for the MRI study #1, and 94.1% and 80.4% compared with 62.1% and 34.5% for the MRI study #2, and 95.7% and 78.7% compared with 63.6% and 42.4% for the MRI study #3, respectively. Low DCE voxels were significantly correlated with Hgb. At-risk voxels can be used to predict the outcomes and help understand tumor heterogeneity of response to RT. The Hgb level and tumor perfusion during RT influence the radioresponsiveness and survival in cervical cancer patients.

Entities:  

Keywords:  At-risk voxel; Cervical cancer; DCE-MRI; Radiation therapy; Signal intensity; Threshold

Year:  2012        PMID: 23638244      PMCID: PMC3638150          DOI: 10.4172/1948-5956.1000151

Source DB:  PubMed          Journal:  J Cancer Sci Ther


  34 in total

1.  Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?

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Journal:  Radiology       Date:  1999-04       Impact factor: 11.105

2.  Lumbar bone marrow microcirculation measurements from dynamic contrast-enhanced magnetic resonance imaging is a predictor of event-free survival in progressive multiple myeloma.

Authors:  Jens Hillengass; Klaus Wasser; Stefan Delorme; Fabian Kiessling; Christian Zechmann; Axel Benner; Hans-Ulrich Kauczor; Anthony D Ho; Hartmut Goldschmidt; Thomas M Moehler
Journal:  Clin Cancer Res       Date:  2007-01-15       Impact factor: 12.531

3.  Pathophysiologic basis of contrast enhancement in breast tumors.

Authors:  M V Knopp; E Weiss; H P Sinn; J Mattern; H Junkermann; J Radeleff; A Magener; G Brix; S Delorme; I Zuna; G van Kaick
Journal:  J Magn Reson Imaging       Date:  1999-09       Impact factor: 4.813

Review 4.  Tumor heterogeneity.

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Journal:  Cancer Res       Date:  1984-06       Impact factor: 12.701

5.  Dynamic contrast-enhanced MRI for assessing the disease activity of multiple myeloma: a comparative study with histology and clinical markers.

Authors:  Sílvia Nosàs-Garcia; Thomas Moehler; Klaus Wasser; Fabian Kiessling; Reiner Bartl; Ivan Zuna; Jens Hillengass; Hartmut Goldschmidt; Hans-Ulrich Kauczor; Stefan Delorme
Journal:  J Magn Reson Imaging       Date:  2005-07       Impact factor: 4.813

6.  Tumor perfusion studies using fast magnetic resonance imaging technique in advanced cervical cancer: a new noninvasive predictive assay.

Authors:  N A Mayr; W T Yuh; V A Magnotta; J C Ehrhardt; J A Wheeler; J I Sorosky; C S Davis; B C Wen; D D Martin; R E Pelsang; R E Buller; L W Oberley; D E Mellenberg; D H Hussey
Journal:  Int J Radiat Oncol Biol Phys       Date:  1996-10-01       Impact factor: 7.038

7.  Fluctuations in tumor blood perfusion assessed by dynamic contrast-enhanced MRI.

Authors:  Kjetil G Brurberg; Ilana C Benjaminsen; Liv M R Dørum; Einar K Rofstad
Journal:  Magn Reson Med       Date:  2007-09       Impact factor: 4.668

8.  Tumor microvascular changes in antiangiogenic treatment: assessment by magnetic resonance contrast media of different molecular weights.

Authors:  Karl Turetschek; Anda Preda; Viktor Novikov; Robert C Brasch; Hanns J Weinmann; Patrick Wunderbaldinger; Timothy P L Roberts
Journal:  J Magn Reson Imaging       Date:  2004-07       Impact factor: 4.813

9.  Intratumoral heterogeneity as a confounding factor in clonogenic assays for tumour radioresponsiveness.

Authors:  R A Britten; A J Evans; M J Allalunis-Turner; A J Franko; R G Pearcey
Journal:  Radiother Oncol       Date:  1996-05       Impact factor: 6.280

Review 10.  Imaging tumor vascular heterogeneity and angiogenesis using dynamic contrast-enhanced magnetic resonance imaging.

Authors:  Alan Jackson; James P B O'Connor; Geoff J M Parker; Gordon C Jayson
Journal:  Clin Cancer Res       Date:  2007-06-15       Impact factor: 12.531

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  5 in total

1.  Multi-parametric MRI in cervical cancer: early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors.

Authors:  Wei Yang; Jin Wei Qiang; Hai Ping Tian; Bing Chen; Ai Jun Wang; Jian Guo Zhao
Journal:  Eur Radiol       Date:  2017-08-04       Impact factor: 5.315

2.  Real-time active MR-tracking of metallic stylets in MR-guided radiation therapy.

Authors:  Wei Wang; Charles L Dumoulin; Akila N Viswanathan; Zion T H Tse; Alireza Mehrtash; Wolfgang Loew; Isaiah Norton; Junichi Tokuda; Ravi T Seethamraju; Tina Kapur; Antonio L Damato; Robert A Cormack; Ehud J Schmidt
Journal:  Magn Reson Med       Date:  2014-06-05       Impact factor: 4.668

3.  Tumor radiomic heterogeneity: Multiparametric functional imaging to characterize variability and predict response following cervical cancer radiation therapy.

Authors:  Stephen R Bowen; William T C Yuh; Daniel S Hippe; Wei Wu; Savannah C Partridge; Saba Elias; Guang Jia; Zhibin Huang; George A Sandison; Dennis Nelson; Michael V Knopp; Simon S Lo; Paul E Kinahan; Nina A Mayr
Journal:  J Magn Reson Imaging       Date:  2017-10-16       Impact factor: 4.813

Review 4.  Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review.

Authors:  Lejla Alic; Wiro J Niessen; Jifke F Veenland
Journal:  PLoS One       Date:  2014-10-20       Impact factor: 3.240

Review 5.  The value of advanced MRI techniques in the assessment of cervical cancer: a review.

Authors:  Evelyn Dappa; Tania Elger; Annette Hasenburg; Christoph Düber; Marco J Battista; Andreas M Hötker
Journal:  Insights Imaging       Date:  2017-08-21
  5 in total

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