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Title: SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability

Abstract

Purpose: To determine the variation in tumor contrast between different MRI sequences and between patients for the purpose of MRI-based treatment planning. Methods: Multiple MRI scans of 11 patients with cancer(s) in the liver were included in this IRB-approved study. Imaging sequences consisted of T1W MRI, Contrast-Enhanced T1W MRI, T2W MRI, and T2*/T1W MRI. MRI images were acquired on a 1.5T GE Signa scanner with a four-channel torso coil. We calculated the tumor-to-tissue contrast to noise ratio (CNR) for each MR sequence by contouring the tumor and a region of interest (ROI) in a homogeneous region of the liver using the Eclipse treatment planning software. CNR was calculated (I-Tum-I-ROI)/SD-ROI, where I-Tum and I-ROI are the mean values of the tumor and the ROI respectively, and SD-ROI is the standard deviation of the ROI. The same tumor and ROI structures were used in all measurements for different MR sequences. Inter-patient Coefficient of variation (CV), and inter-sequence CV was determined. In addition, mean and standard deviation of CNR were calculated and compared between different MR sequences. Results: Our preliminary results showed large inter-patient CV (range: 37.7% to 88%) and inter-sequence CV (range 5.3% to 104.9%) of liver tumor CNR, indicating great variationsmore » in tumor CNR between MR sequences and between patients. Tumor CNR was found to be largest in CE-T1W (8.5±7.5), followed by T2W (4.2±2.4), T1W (3.4±2.2), and T2*/T1W (1.7±0.6) MR scans. The inter-patient CV of tumor CNR was also the largest in CE-T1W (88%), followed by T1W (64.3%), T1W (56.2%), and T2*/T1W (37.7) MR scans. Conclusion: Large inter-sequence and inter-patient variations were observed in liver tumor CNR. CE-T1W MR images on average provided the best tumor CNR. Efforts are needed to optimize tumor contrast and its consistency for MRI-based treatment planning of cancer in the liver. This project is supported by NIH grant: 1R21CA165384.« less

Authors:
 [1]; ;  [1];  [2]; ;  [3]
  1. Duke University Medical Physics Graduate Program, Durham, NC (United States)
  2. (United States)
  3. Duke University Medical Center, Radiation Oncology, Durham, NC (United States)
Publication Date:
OSTI Identifier:
22634712
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ANIMAL TISSUES; BIOMEDICAL RADIOGRAPHY; COMPUTER CODES; IMAGES; LIVER; NEOPLASMS; NMR IMAGING; PATIENTS; PLANNING; RADIOTHERAPY

Citation Formats

Moore, B, Yin, F, Cai, J, Duke University Medical Center, Radiation Oncology, Durham, NC, Czito, B, and Palta, M. SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability. United States: N. p., 2016. Web. doi:10.1118/1.4956011.
Moore, B, Yin, F, Cai, J, Duke University Medical Center, Radiation Oncology, Durham, NC, Czito, B, & Palta, M. SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability. United States. doi:10.1118/1.4956011.
Moore, B, Yin, F, Cai, J, Duke University Medical Center, Radiation Oncology, Durham, NC, Czito, B, and Palta, M. Wed . "SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability". United States. doi:10.1118/1.4956011.
@article{osti_22634712,
title = {SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability},
author = {Moore, B and Yin, F and Cai, J and Duke University Medical Center, Radiation Oncology, Durham, NC and Czito, B and Palta, M},
abstractNote = {Purpose: To determine the variation in tumor contrast between different MRI sequences and between patients for the purpose of MRI-based treatment planning. Methods: Multiple MRI scans of 11 patients with cancer(s) in the liver were included in this IRB-approved study. Imaging sequences consisted of T1W MRI, Contrast-Enhanced T1W MRI, T2W MRI, and T2*/T1W MRI. MRI images were acquired on a 1.5T GE Signa scanner with a four-channel torso coil. We calculated the tumor-to-tissue contrast to noise ratio (CNR) for each MR sequence by contouring the tumor and a region of interest (ROI) in a homogeneous region of the liver using the Eclipse treatment planning software. CNR was calculated (I-Tum-I-ROI)/SD-ROI, where I-Tum and I-ROI are the mean values of the tumor and the ROI respectively, and SD-ROI is the standard deviation of the ROI. The same tumor and ROI structures were used in all measurements for different MR sequences. Inter-patient Coefficient of variation (CV), and inter-sequence CV was determined. In addition, mean and standard deviation of CNR were calculated and compared between different MR sequences. Results: Our preliminary results showed large inter-patient CV (range: 37.7% to 88%) and inter-sequence CV (range 5.3% to 104.9%) of liver tumor CNR, indicating great variations in tumor CNR between MR sequences and between patients. Tumor CNR was found to be largest in CE-T1W (8.5±7.5), followed by T2W (4.2±2.4), T1W (3.4±2.2), and T2*/T1W (1.7±0.6) MR scans. The inter-patient CV of tumor CNR was also the largest in CE-T1W (88%), followed by T1W (64.3%), T1W (56.2%), and T2*/T1W (37.7) MR scans. Conclusion: Large inter-sequence and inter-patient variations were observed in liver tumor CNR. CE-T1W MR images on average provided the best tumor CNR. Efforts are needed to optimize tumor contrast and its consistency for MRI-based treatment planning of cancer in the liver. This project is supported by NIH grant: 1R21CA165384.},
doi = {10.1118/1.4956011},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: Quantification of volume changes on CBCT during SBRT for NSCLC may provide a useful radiological marker for radiation response and adaptive treatment planning, but the reproducibility of CBCT volume delineation is a concern. This study is to quantify inter-scan/inter-observer variability in tumor volume delineation on CBCT. Methods: Twenty earlystage (stage I and II) NSCLC patients were included in this analysis. All patients were treated with SBRT with a median dose of 54 Gy in 3 to 5 fractions. Two physicians independently manually contoured the primary gross tumor volume on CBCTs taken immediately before SBRT treatment (Pre) and after themore » same SBRT treatment (Post). Absolute volume differences (AVD) were calculated between the Pre and Post CBCTs for a given treatment to quantify inter-scan variability, and then between the two observers for a given CBCT to quantify inter-observer variability. AVD was also normalized with respect to average volume to obtain relative volume differences (RVD). Bland-Altman approach was used to evaluate variability. All statistics were calculated with SAS version 9.4. Results: The 95% limit of agreement (mean ± 2SD) on AVD and RVD measurements between Pre and Post scans were −0.32cc to 0.32cc and −0.5% to 0.5% versus −1.9 cc to 1.8 cc and −15.9% to 15.3% for the two observers respectively. The 95% limit of agreement of AVD and RVD between the two observers were −3.3 cc to 2.3 cc and −42.4% to 28.2% respectively. The greatest variability in inter-scan RVD was observed with very small tumors (< 5 cc). Conclusion: Inter-scan variability in RVD is greatest with small tumors. Inter-observer variability was larger than inter-scan variability. The 95% limit of agreement for inter-observer and inter-scan variability (∼15–30%) helps define a threshold for clinically meaningful change in tumor volume to assess SBRT response, with larger thresholds needed for very small tumors. Part of the work was funded by a Kaye award; Disclosure/Conflict of interest: Raymond H. Mak: Stock ownership: Celgene, Inc. Consulting: Boehringer-Ingelheim, Inc.« less
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