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WE‐G‐141‐09: Prospective Image Planning in Radiation Therapy for Optimization of Image Quality and Reduction of Patient Dose
Author(s) -
Thapa B,
Molloy J
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4815660
Subject(s) - image guided radiation therapy , image quality , imaging phantom , medicine , nuclear medicine , medical imaging , dosimetry , radiation treatment planning , cone beam computed tomography , radiation therapy , medical physics , radiology , artificial intelligence , computer science , computed tomography , image (mathematics)
Purpose: X‐ray image‐guided radiotherapy (IGRT) relies on generalized, vendor‐provided acquisition parameters. These parameters are chosen via broad categorizations in patient anatomy and often do not yield optimal image contrast and patient dose. In the IGRT setting, precise prior knowledge of patient anatomy and imaging goal are available via the simulation CT scan. We developed and tested a patient‐specific image planning system (IPS) for radiotherapy and assessed its predictive capabilities and ability to reduce patient imaging dose. Methods: The IPS calculates patient‐specific attenuation of the imaging beam and integrates the detector response into the simulated image. Experimental validation was conducted using an anthropomorphic phantom over a range of mAs values for 80 and 120 kVp beam qualities. Data for the head and neck (H/N), thorax and pelvis were acquired. Clinical data was collected from patients undergoing IGRT for H/N and abdominal diseases. Retention of image contrast following imaging dose reduction was verified using mutual information as a metric. Results: The IPS was found to be capable of predicting under exposure, saturation and a contrast plateau over a wide exposure range. The IPS was successful at predicting a lack of appreciable change in contrast between the images acquired at high and low kVp settings. It was found to be capable of reducing patient imaging dose without loss of appreciable contrast. With the IPS, imaging dose reduction of at least 37 to 74 percent was achieved for the patients studied. Conclusion: Image contrast resulting from under exposure, over exposure as well as a contrast plateau can be predicted by use of a prospective image planning algorithm. Image acquisition parameters can be predicted that reduce patient dose without loss of contrast.