Magnetic Resonance Imaging (MRI) for High-Dose-Rate (HDR) Brachytherapy

High-dose-rate (HDR) brachytherapy is a radiation therapy technique which places radioactive sources within or adjacent to the tumor tissue. It is commonly employed to treat gynecological and skin cancers, using applicators featuring catheters into which the sources are inserted for short dwell times. Precise catheter localization within 1 mm is crucial for accurate dose delivery. Catheter detection is performed manually on computed tomography (CT) images of the applicators in situ. Magnetic resonance imaging (MRI) offers superior soft tissue contrast to CT, but brachytherapy applicators are not visualized on standard sequences. Pointwise encoding time reduction with radial acquisition (PETRA) sequences have recently demonstrated the potential to identify brachytherapy applicators and catheters. In this study, PETRA was compared to a Volumetric Interpolated Breath-hold Examination (VIBE) sequence on an endometrial adenocarcinoma patient treated with HDR brachytherapy. Interstitial catheters and a Syed-Neblett interstitial template were better discerned on PETRA than on VIBE. A newly developed algorithm for automated catheter detection identified successfully all catheters inside tissue by their minimum intensity on the PETRA images. A PETRA and a Dixon VIBE sequence were also compared for a healthy volunteer with a Freiburg Flap (FF) surface applicator around her leg. Dixon opposed-phase (OP) images offered the highest contrast between applicator spheres and empty catheters and allowed for skin identification and cutaneous thickness quantification. Chemical shift induced geometric distortions of the FF applicator spheres on Dixon OP images were assessed on a flat FF applicator phantom and amounted to 1 mm on average. Building the geometric mean of the Dixon IP and OP images reduced the shifts from the corresponding sphere positions on CT images to below 0.5 mm. Automated detection of all catheters tunneling a flat FF applicator was achieved with submillimeter accuracy using signal intensity characteristics on PETRA images.