SU‐E‐J‐130: Impact of Audiovisual Biofeedback Respiratory Training On 4D‐CT Image Quality

Tokihiro Yamamoto, S. Gopalan, J. Berger, E. Johnston, M. Chung, N. Eclov, M. Diehn, B. Loo, P. Keall

Research output: Contribution to journalArticle

Abstract

Purpose: Current 4D‐CT methods show artifacts of >4 mm in 90% of cases. The purpose of this study was to quantify the impact of audiovisual (AV) biofeedback respiratory training on 4D‐CT image quality. Methods: In an IRB‐approved clinical trial, two 4D‐CT scans, with free breathing and AV biofeedback, were acquired with a cine method for ten thoracic cancer patients. AV biofeedback was based on: (1) a patient‐specific representative waveform and a dot moving according to the abdominal displacement, displayed on the video screen of the goggles; and (2) musical guides provided with a beat period corresponding to the waveform period. The phase‐sorted 4D‐CT images with free breathing and AV biofeedback at the 0% (peak‐inhale), 30%, 50% (peak‐exhale) and 80% phases were analyzed for artifacts by: (1) comparing normalized cross correlation (NCC)‐based scores (artifacts give high scores) of the two images; and (2) quantifying a score for each pair based on visual assessment of the two image sets (positive scores mean that AV biofeedback 4D‐CT is of higher quality). We tested the hypothesis that AV biofeedback significantly reduces 4D‐CT artifacts using the two‐tailed paired t‐test. Results: The impact of AV biofeedback varied widely with patients and phases, suggesting inconsistent patient compliance. For example, patient 5 demonstrated a visual assessment score of 4 at the 0% phase indicating that AV biofeedback 4D‐CT was of higher quality than free breathing, while a score of −3 at the 50% phase indicating the opposite. Overall, no statistically significant differences were found in both the NCC‐based score (free 0.60±0.32 vs. AV 0.65±0.27, p=0.32) and visual assessment score (0.0±2.7, p=0.95). Conclusion: A 10‐patient study demonstrated no statistically significant impact of AV biofeedback respiratory training on 4D‐CT image quality. Future studies will investigate strategies to improve patient compliance by optimizing the biofeedback interface or increasing patient comfort. NIH/NCI 2 R01 CA 093626; Stanford BioX Interdisciplinary Initiatives Program.

Original languageEnglish (US)
Number of pages1
JournalMedical Physics
Volume40
Issue number6
DOIs
StatePublished - Jan 1 2013

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Artifacts
Respiration
Patient Compliance
Biofeedback (Psychology)
Eye Protective Devices
Thorax
Clinical Trials
Neoplasms

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

SU‐E‐J‐130 : Impact of Audiovisual Biofeedback Respiratory Training On 4D‐CT Image Quality. / Yamamoto, Tokihiro; Gopalan, S.; Berger, J.; Johnston, E.; Chung, M.; Eclov, N.; Diehn, M.; Loo, B.; Keall, P.

In: Medical Physics, Vol. 40, No. 6, 01.01.2013.

Research output: Contribution to journalArticle

Yamamoto, T, Gopalan, S, Berger, J, Johnston, E, Chung, M, Eclov, N, Diehn, M, Loo, B & Keall, P 2013, 'SU‐E‐J‐130: Impact of Audiovisual Biofeedback Respiratory Training On 4D‐CT Image Quality', Medical Physics, vol. 40, no. 6. https://doi.org/10.1118/1.4814342
Yamamoto, Tokihiro ; Gopalan, S. ; Berger, J. ; Johnston, E. ; Chung, M. ; Eclov, N. ; Diehn, M. ; Loo, B. ; Keall, P. / SU‐E‐J‐130 : Impact of Audiovisual Biofeedback Respiratory Training On 4D‐CT Image Quality. In: Medical Physics. 2013 ; Vol. 40, No. 6.
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abstract = "Purpose: Current 4D‐CT methods show artifacts of >4 mm in 90{\%} of cases. The purpose of this study was to quantify the impact of audiovisual (AV) biofeedback respiratory training on 4D‐CT image quality. Methods: In an IRB‐approved clinical trial, two 4D‐CT scans, with free breathing and AV biofeedback, were acquired with a cine method for ten thoracic cancer patients. AV biofeedback was based on: (1) a patient‐specific representative waveform and a dot moving according to the abdominal displacement, displayed on the video screen of the goggles; and (2) musical guides provided with a beat period corresponding to the waveform period. The phase‐sorted 4D‐CT images with free breathing and AV biofeedback at the 0{\%} (peak‐inhale), 30{\%}, 50{\%} (peak‐exhale) and 80{\%} phases were analyzed for artifacts by: (1) comparing normalized cross correlation (NCC)‐based scores (artifacts give high scores) of the two images; and (2) quantifying a score for each pair based on visual assessment of the two image sets (positive scores mean that AV biofeedback 4D‐CT is of higher quality). We tested the hypothesis that AV biofeedback significantly reduces 4D‐CT artifacts using the two‐tailed paired t‐test. Results: The impact of AV biofeedback varied widely with patients and phases, suggesting inconsistent patient compliance. For example, patient 5 demonstrated a visual assessment score of 4 at the 0{\%} phase indicating that AV biofeedback 4D‐CT was of higher quality than free breathing, while a score of −3 at the 50{\%} phase indicating the opposite. Overall, no statistically significant differences were found in both the NCC‐based score (free 0.60±0.32 vs. AV 0.65±0.27, p=0.32) and visual assessment score (0.0±2.7, p=0.95). Conclusion: A 10‐patient study demonstrated no statistically significant impact of AV biofeedback respiratory training on 4D‐CT image quality. Future studies will investigate strategies to improve patient compliance by optimizing the biofeedback interface or increasing patient comfort. NIH/NCI 2 R01 CA 093626; Stanford BioX Interdisciplinary Initiatives Program.",
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