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Investigation of tumor and vessel motion correlation in the liver
by
Hill, Patrick M.
, Jupitz, Sydney A.
, Shepard, Andrew J.
, Bednarz, Bryan P.
in
Abdomen
/ Algorithms
/ Annotations
/ breathing motion
/ Datasets
/ Diaphragm (Anatomy)
/ IGRT
/ Liver
/ Liver cancer
/ motion management
/ Patients
/ Radiation Oncology Physics
/ Radiation therapy
/ Respiration
/ Tumors
/ vessel tracking
2020
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Investigation of tumor and vessel motion correlation in the liver
by
Hill, Patrick M.
, Jupitz, Sydney A.
, Shepard, Andrew J.
, Bednarz, Bryan P.
in
Abdomen
/ Algorithms
/ Annotations
/ breathing motion
/ Datasets
/ Diaphragm (Anatomy)
/ IGRT
/ Liver
/ Liver cancer
/ motion management
/ Patients
/ Radiation Oncology Physics
/ Radiation therapy
/ Respiration
/ Tumors
/ vessel tracking
2020
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Investigation of tumor and vessel motion correlation in the liver
by
Hill, Patrick M.
, Jupitz, Sydney A.
, Shepard, Andrew J.
, Bednarz, Bryan P.
in
Abdomen
/ Algorithms
/ Annotations
/ breathing motion
/ Datasets
/ Diaphragm (Anatomy)
/ IGRT
/ Liver
/ Liver cancer
/ motion management
/ Patients
/ Radiation Oncology Physics
/ Radiation therapy
/ Respiration
/ Tumors
/ vessel tracking
2020
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Investigation of tumor and vessel motion correlation in the liver
Journal Article
Investigation of tumor and vessel motion correlation in the liver
2020
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Overview
Intrafraction imaging‐based motion management systems for external beam radiotherapy can rely on internal surrogate structures when the target is not easily visualized. This work evaluated the validity of using liver vessels as internal surrogates for the estimation of liver tumor motion. Vessel and tumor motion were assessed using ten two‐dimensional sagittal MR cine datasets collected on the ViewRay MRIdian. For each case, a liver tumor and at least one vessel were tracked for 175 s. A tracking approach utilizing block matching and multiple simultaneous templates was applied. Accuracy of the tracked motion was calculated from the error between the tracked centroid position and manually defined ground truth annotations. The patient’s abdomen surface and diaphragm were manually annotated in all frames. The Pearson correlation coefficient (CC) was used to compare the motion of the features and tumor in the anterior–posterior (AP) and superior–inferior (SI) directions. The distance between the centroids of the features and the tumors was calculated to assess if feature proximity affects relative correlation, and the tumor range of motion was determined. Intra‐ and interfraction motion amplitude variabilities were evaluated to further assess the relationship between tumor and feature motion. The mean CC between the motion of the vessel and the tumor were 0.85 ± 0.11 (AP) and 0.92 ± 0.04 (SI), 0.83 ± 0.11 (AP) and −0.89 ± 0.06 (SI) for the surface and tumor, and 0.80 ± 0.17 (AP) and 0.94 ± 0.03 (SI) for the diaphragm and tumor. For intrafraction analysis, the average amplitude variability was 2.47 ± 0.77 mm (AP) and 3.14 ± 1.49 mm (SI) for the vessels, 2.70 ± 1.08 mm (AP) and 3.43 ± 1.73 mm (SI) for the surface, and 2.76 ± 1.41 mm (AP) and 2.91 ± 1.38 mm (SI) for the diaphragm. No relationship between distance and motion correlation was observed. The motion of liver tumors and liver vessels was well correlated, making vessels a suitable surrogate for tumor motion in the liver.
Publisher
John Wiley & Sons, Inc,John Wiley and Sons Inc
Subject
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