Audio-visual biofeedback does not improve the reliability of target delineation using maximum intensity projection in 4-dimensional computed tomography radiation therapy planning.

ABSTRACT

PURPOSE: To investigate whether coaching patients' breathing would improve the match between ITVMIP (internal target volume generated by contouring in the maximum intensity projection scan) and ITV10 (generated by combining the gross tumor volumes contoured in 10 phases of a 4-dimensional CT [4DCT] scan). METHODS AND MATERIALS Eight patients with a thoracic tumor and 5 patients with an abdominal tumor were included in an institutional review board-approved prospective study. Patients underwent 3 4DCT scans with (1) free breathing (FB); (2) coaching using audio-visual (AV) biofeedback via the Real-Time Position Management system; and (3) coaching via a spirometer system (Active Breathing Coordinator or ABC). One physician contoured all scans to generate the ITV10 and ITVMIP. The match between ITVMIP and ITV10 was quantitatively assessed with volume ratio, centroid distance, root mean squared distance, and overlap/Dice coefficient. We investigated whether coaching (AV or ABC) or uniform expansions (1, 2, 3, or 5 mm) of ITVMIP improved the match. RESULTS: Although both AV and ABC coaching techniques improved frequency reproducibility and ABC improved displacement regularity, neither improved the match between ITVMIP and ITV10 over FB. On average, ITVMIP underestimated ITV10 by 19%, 19%, and 21%, with centroid distance of 1.9, 2.3, and 1.7 mm and Dice coefficient of 0.87, 0.86, and 0.88 for FB, AV, and ABC, respectively. Separate analyses indicated a better match for lung cancers or tumors not adjacent to high-intensity tissues. Uniform expansions of ITVMIP did not correct for the mismatch between ITVMIP and ITV10. CONCLUSIONS: In this pilot study, audio-visual biofeedback did not improve the match between ITVMIP and ITV10. In general, ITVMIP should be limited to lung cancers, and modification of ITVMIP in each phase of the 4DCT data set is recommended.