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Title: MO-FG-CAMPUS-JeP2-02: Audiovisual Biofeedback Guided Respiratory-Gated MRI: An Investigation of Tumor Definition and Scan Time for Lung Cancer

Abstract

Purpose: Breathing consistency variations can cause respiratory-related motion blurring and artifacts and increase in MRI scan time due to inadequate respiratory-gating and discarding of breathing cycles. In a previous study the concept of audiovisual biofeedback (AV) guided respiratory-gated MRI was tested with healthy volunteers and it demonstrated image quality improvement on anatomical structures and scan time reduction. This study tests the applicability of AV-guided respiratorygated MRI for lung cancer in a prospective patient study. Methods: Image quality and scan time were investigated in thirteen lung cancer patients who underwent two 3T MRI sessions. In the first MRI session (pre-treatment), respiratory-gated MR images with free breathing (FB) and AV were acquired at inhalation and exhalation. An RF navigator placed on the liver dome was employed for the respiratory-gated MRI. This was repeated in the second MRI session (mid-treatment). Lung tumors were delineated on each dataset. FB and AV were compared in terms of (1) tumor definition assessed by lung tumor contours and (2) intra-patient scan time variation using the total image acquisition time of inhalation and exhalation datasets from the first and second MRI sessions across 13 lung cancer patients. Results: Compared to FB AV-guided respiratory-gated MRI improved image quality formore » contouring tumors with sharper boundaries and less blurring resulted in the improvement of tumor definition. Compared to FB the variation of intra-patient scan time with AV was reduced by 48% (p<0.001) from 54 s to 28 s. Conclusion: This study demonstrated that AV-guided respiratorygated MRI improved the quality of tumor images and fixed tumor definition for lung cancer. These results suggest that audiovisual biofeedback breathing guidance has the potential to control breathing for adequate respiratory-gating for lung cancer imaging and radiotherapy.« less

Authors:
; ;  [1]; ; ;  [2];  [3]
  1. University of Sydney, Sydney, NSW (Australia)
  2. Calvary Mater Newcastle, Newcastle, NSW (Australia)
  3. Virginia Commonwealth University, Glen Allen, VA (United States)
Publication Date:
OSTI Identifier:
22653903
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; BIOMEDICAL RADIOGRAPHY; IMAGES; LUNGS; NEOPLASMS; NMR IMAGING; PATIENTS; RESPIRATION; VARIATIONS

Citation Formats

Lee, D, Pollock, S, Keall, P, Greer, P, Lapuz, C, Ludbrook, J, and Kim, T. MO-FG-CAMPUS-JeP2-02: Audiovisual Biofeedback Guided Respiratory-Gated MRI: An Investigation of Tumor Definition and Scan Time for Lung Cancer. United States: N. p., 2016. Web. doi:10.1118/1.4957355.
Lee, D, Pollock, S, Keall, P, Greer, P, Lapuz, C, Ludbrook, J, & Kim, T. MO-FG-CAMPUS-JeP2-02: Audiovisual Biofeedback Guided Respiratory-Gated MRI: An Investigation of Tumor Definition and Scan Time for Lung Cancer. United States. doi:10.1118/1.4957355.
Lee, D, Pollock, S, Keall, P, Greer, P, Lapuz, C, Ludbrook, J, and Kim, T. 2016. "MO-FG-CAMPUS-JeP2-02: Audiovisual Biofeedback Guided Respiratory-Gated MRI: An Investigation of Tumor Definition and Scan Time for Lung Cancer". United States. doi:10.1118/1.4957355.
@article{osti_22653903,
title = {MO-FG-CAMPUS-JeP2-02: Audiovisual Biofeedback Guided Respiratory-Gated MRI: An Investigation of Tumor Definition and Scan Time for Lung Cancer},
author = {Lee, D and Pollock, S and Keall, P and Greer, P and Lapuz, C and Ludbrook, J and Kim, T},
abstractNote = {Purpose: Breathing consistency variations can cause respiratory-related motion blurring and artifacts and increase in MRI scan time due to inadequate respiratory-gating and discarding of breathing cycles. In a previous study the concept of audiovisual biofeedback (AV) guided respiratory-gated MRI was tested with healthy volunteers and it demonstrated image quality improvement on anatomical structures and scan time reduction. This study tests the applicability of AV-guided respiratorygated MRI for lung cancer in a prospective patient study. Methods: Image quality and scan time were investigated in thirteen lung cancer patients who underwent two 3T MRI sessions. In the first MRI session (pre-treatment), respiratory-gated MR images with free breathing (FB) and AV were acquired at inhalation and exhalation. An RF navigator placed on the liver dome was employed for the respiratory-gated MRI. This was repeated in the second MRI session (mid-treatment). Lung tumors were delineated on each dataset. FB and AV were compared in terms of (1) tumor definition assessed by lung tumor contours and (2) intra-patient scan time variation using the total image acquisition time of inhalation and exhalation datasets from the first and second MRI sessions across 13 lung cancer patients. Results: Compared to FB AV-guided respiratory-gated MRI improved image quality for contouring tumors with sharper boundaries and less blurring resulted in the improvement of tumor definition. Compared to FB the variation of intra-patient scan time with AV was reduced by 48% (p<0.001) from 54 s to 28 s. Conclusion: This study demonstrated that AV-guided respiratorygated MRI improved the quality of tumor images and fixed tumor definition for lung cancer. These results suggest that audiovisual biofeedback breathing guidance has the potential to control breathing for adequate respiratory-gating for lung cancer imaging and radiotherapy.},
doi = {10.1118/1.4957355},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To investigate whether the breathing-guidance system: audiovisual (AV) biofeedback improves tumor motion consistency for lung cancer patients. This will minimize respiratory-induced tumor motion variations across cancer imaging and radiotherapy procedues. This is the first study to investigate the impact of respiratory guidance on tumor motion. Methods: Tumor motion consistency was investigated with five lung cancer patients (age: 55 to 64), who underwent a training session to get familiarized with AV biofeedback, followed by two MRI sessions across different dates (pre and mid treatment). During the training session in a CT room, two patient specific breathing patterns were obtained beforemore » (Breathing-Pattern-1) and after (Breathing-Pattern-2) training with AV biofeedback. In each MRI session, four MRI scans were performed to obtain 2D coronal and sagittal image datasets in free breathing (FB), and with AV biofeedback utilizing Breathing-Pattern-2. Image pixel values of 2D images after the normalization of 2D images per dataset and Gaussian filter per image were used to extract tumor motion using image pixel values. The tumor motion consistency of the superior-inferior (SI) direction was evaluated in terms of an average tumor motion range and period. Results: Audiovisual biofeedback improved tumor motion consistency by 60% (p value = 0.019) from 1.0±0.6 mm (FB) to 0.4±0.4 mm (AV) in SI motion range, and by 86% (p value < 0.001) from 0.7±0.6 s (FB) to 0.1±0.2 s (AV) in period. Conclusion: This study demonstrated that audiovisual biofeedback improves both breathing pattern and tumor motion consistency for lung cancer patients. These results suggest that AV biofeedback has the potential for facilitating reproducible tumor motion towards achieving more accurate medical imaging and radiation therapy procedures.« less
  • Purpose: Target delineation in lung cancer radiotherapy has, in general, large variability. MRI has so far not been investigated in detail for lung cancer delineation variability. The purpose of this study is to investigate delineation variability for lung tumors using MRI and compare it to CT alone and PET-CT based delineations. Methods: Seven physicians delineated the primary tumor volumes of nine patients for the following scenarios: (1) CT only; (2) post-contrast T1-weighted MRI registered with diffusion-weighted MRI; and (3) PET-CT fusion images. To compute interobserver variability, the median surface was generated from all observers’ contours and used as the referencemore » surface. A single physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest-wall) on the median surface. Volume variation (normalized to PET-CT volume), minimum distance (MD), and bidirectional local distance (BLD) between individual observers’ contours and the reference contour were measured. Results: CT- and MRI-based normalized volumes were 1.61±0.76 (mean±SD) and 1.38±0.44, respectively, both significantly larger than PET-CT (p<0.05, paired t-test). The overall uncertainty (root mean square of SD values over all points) of both BLD and MD measures of the observers for the interfaces were not significantly different (p>0.05, two-samples t-test) for all imaging modalities except between tumor-mediastinum and tumor-atelectasis in PET-CT. The largest mean overall uncertainty was observed for tumor-atelectasis interface, the smallest for tumor-mediastinum and tumor-lung interfaces for all modalities. The whole tumor uncertainties for both BLD and MD were not significantly different between any two modalities (p>0.05, paired t-test). Overall uncertainties for the interfaces using BLD were similar to using MD. Conclusion: Large volume variations were observed between the three imaging modalities. Contouring variability appeared to depend on the interface type. This study will be useful for understanding the delineation uncertainty for radiotherapy planning of lung cancer using different imaging modalities. Disclosures: Research agreement with Phillips Healthcare (GH and EW), National Institutes of Health Licensing agreement with Varian Medical Systems (GH and EW), research grants from the National Institute of Health (GH and EW), UpToDate royalties (EW), and none (others). Authors have no potential conflicts of interest to disclose.« less
  • Purpose: Audiovisual biofeedback breath-hold (AVBH) was employed to reproduce tumor position on inhale and exhale breath-holds for 4D tumor information. We hypothesize that lung tumor position will be more consistent using AVBH compared with conventional breath-hold (CBH). Methods: Lung tumor positions were determined for seven lung cancer patients (age: 25 – 74) during to two separate 3T MRI sessions. A breathhold training session was performed prior to the MRI sessions to allow patients to become comfortable with AVBH and their exhale and inhale target positions. CBH and AVBH 4D image datasets were obtained in the first MRI session (pre-treatment) andmore » the second MRI session (midtreatment) within six weeks of the first session. Audio-instruction (MRI: Siemens Skyra) in CBH and verbal-instruction (radiographer) in AVBH were used. A radiation oncologist contoured the lung tumor using Eclipse (Varian Medical Systems); tumor position was quantified as the centroid of the contoured tumor after rigid registration based on vertebral anatomy across two MRI sessions. CBH and AVBH were compared in terms of the reproducibility assessed via (1) the difference between the two exhale positions for the two sessions and the two inhale positions for the sessions. (2) The difference in amplitude (exhale to inhale) between the two sessions. Results: Compared to CBH, AVBH improved the reproducibility of two exhale (or inhale) lung tumor positions relative to each other by 33%, from 6.4±5.3 mm to 4.3±3.0 mm (p=0.005). Compared to CBH, AVBH improved the reproducibility of exhale and inhale amplitude by 66%, from 5.6±5.9 mm to 1.9±1.4 mm (p=0.005). Conclusions: This study demonstrated that audiovisual biofeedback can be utilized for improving the reproducibility of breath-hold lung tumor position. These results are advantageous towards achieving more accurate emerging radiation treatment planning methods, in addition to imaging and treatment modalities utilizing breath-hold procedures.« less
  • Purpose: To assess the impact of an audiovisual (AV) biofeedback on intra- and interfraction tumor motion for lung cancer patients. Methods and Materials: Lung tumor motion was investigated in 9 lung cancer patients who underwent a breathing training session with AV biofeedback before 2 3T magnetic resonance imaging (MRI) sessions. The breathing training session was performed to allow patients to become familiar with AV biofeedback, which uses a guiding wave customized for each patient according to a reference breathing pattern. In the first MRI session (pretreatment), 2-dimensional cine-MR images with (1) free breathing (FB) and (2) AV biofeedback were obtained, andmore » the second MRI session was repeated within 3-6 weeks (mid-treatment). Lung tumors were directly measured from cine-MR images using an auto-segmentation technique; the centroid and outlier motions of the lung tumors were measured from the segmented tumors. Free breathing and AV biofeedback were compared using several metrics: intra- and interfraction tumor motion consistency in displacement and period, and the outlier motion ratio. Results: Compared with FB, AV biofeedback improved intrafraction tumor motion consistency by 34% in displacement (P=.019) and by 73% in period (P<.001). Compared with FB, AV biofeedback improved interfraction tumor motion consistency by 42% in displacement (P<.046) and by 74% in period (P=.005). Compared with FB, AV biofeedback reduced the outlier motion ratio by 21% (P<.001). Conclusions: These results demonstrated that AV biofeedback significantly improved intra- and interfraction lung tumor motion consistency for lung cancer patients. These results demonstrate that AV biofeedback can facilitate consistent tumor motion, which is advantageous toward achieving more accurate medical imaging and radiation therapy procedures.« less
  • Purpose: To evaluate implanted markers as a surrogate for tumor-based setup during image-guided lung cancer radiotherapy with audiovisual biofeedback. Methods and Materials: Seven patients with locally advanced non-small-cell lung cancer were implanted bronchoscopically with gold coils. Markers, tumor, and a reference bony structure (vertebra) were contoured for all 10 phases of the four-dimensional respiration-correlated fan-beam computed tomography and weekly four-dimensional cone-beam computed tomography. Results: The systematic/random interfractional marker-to-tumor centroid displacements were 2/3, 2/2, and 3/3 mm in the x (lateral), y (anterior-posterior), and z (superior-inferior) directions, respectively. The systematic/random interfractional marker-to-bone displacements were 2/3, 2/3, and 2/3 mm in themore » x, y, and z directions, respectively. The systematic/random tumor-to-bone displacements were 2/3, 2/4, and 4/4 mm in the x, y, and z directions, respectively. All displacements changed significantly over time (p < 0.0001). Conclusions: Although marker-based image guidance may decrease the risk for geometric miss compared with bony anatomy-based positioning, the observed displacements between markers and tumor centroids indicate the need for repeated soft tissue imaging, particularly in situations with large tumor volume change and large initial marker-to-tumor centroid distance.« less