alexa Characterizing at-Risk Voxels by Using Perfusion Magnetic Resonance Imaging for Cervical Cancer during Radiotherapy | OMICS International | Abstract
ISSN: 1948-5956

Journal of Cancer Science & Therapy
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Research Article

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

Zhibin Huang1*, Nina A Mayr2, Simon S Lo3, John C Grecula4, Jian Z Wang2, Guang Jia4 and William TC Yuh4

1Department of Radiation Oncology, East Carolina University, Greenville, NC 27834, USA

2Department of Radiation Oncology, The Ohio State University, Columbus, OH 43210, USA

3Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH 44106, USA

4Department of Radiology, The Ohio State University, Columbus, OH 43210, USA

*Corresponding Author:
Zhibin Huang, Ph.D
Assistant Professor
Department of Radiation Oncology
Brody School of Medicine
East Carolina University
600 Moye Boulevard, Greenville
NC 27834, USA
Tel: 252-744-3768
Fax: 252-744-3775
E-mail: [email protected]

Received date: January 13, 2012; Accepted date: August 11, 2012; Published date: August 13, 2012

Citation:Huang Z, Mayr NA, Lo SS, Grecula JC, Wang JZ, et al. (2012) Characterizing at-Risk Voxels by Using Perfusion Magnetic Resonance Imaging for Cervical Cancer during Radiotherapy. J Cancer Sci Ther 4: 254-259. doi: 10.4172/1948-5956.1000151

Copyright: © 2012 Huang Z, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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.

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