title: Validation of catheter segmentation for MR-guided gynecologic cancer brachytherapy.
abstract: Segmentation of interstitial catheters from MRI needs to be addressed in order for MRI-based brachytherapy treatment planning to become part of the clinical practice of gynecologic cancer radiotherapy. This paper presents a validation study of a novel image-processing method for catheter segmentation. The method extends the distal catheter tip, interactively provided by the physician, to its proximal end, using knowledge of catheter geometry and appearance in MRI sequences. The validation study consisted of comparison of the algorithm results to expert manual segmentations, first on images of a phantom, and then on patient MRI images obtained during MRI-guided insertion of brachytherapy catheters for the treatment of gynecologic cancer. In the phantom experiment, the maximum disagreement between automatic and manual segmentation of the same MRI image, as computed using the Hausdorf distance, was 1.5 mm, which is of the same order as the MR image spatial resolution, while the disagreement between automatic segmentation of MR images and "ground truth", manual segmentation of CT images, was 3.5 mm. The segmentation method was applied to an IRB-approved retrospective database of 10 interstitial brachytherapy patients which included a total of 101 catheters. Compared with manual expert segmentations, the automatic method correctly segmented 93 out of 101 catheters, at an average rate of 0.3 seconds per catheter using a 3 GHz Intel Core i7 computer with 16 GB RAM and running Mac OS X 10.7. These results suggest that the proposed catheter segmentation is both technically and clinically feasible.
authors: Technische Universität München.
authors: Guillaume
authors: G
authors: Pernelle
authors: Brigham & Women's Hospital and Harvard Medical School, USA.
authors: Alireza
authors: A
authors: Mehrtash
authors: Brigham & Women's Hospital and Harvard Medical School, USA.
authors: Lauren
authors: L
authors: Barber
authors: Siemens Healthcare.
authors: Antonio
authors: A
authors: Damato
authors: Siemens Healthcare.
authors: Wei
authors: W
authors: Wang
authors: Siemens Healthcare.
authors: Ravi Teja
authors: RT
authors: Seethamraju
authors: Brigham & Women's Hospital and Harvard Medical School, USA.
authors: Ehud
authors: E
authors: Schmidt
authors: Brigham & Women's Hospital and Harvard Medical School, USA.
authors: Robert A
authors: RA
authors: Cormack
authors: Brigham & Women's Hospital and Harvard Medical School, USA.
authors: Williams
authors: W
authors: Wells
authors: Brigham & Women's Hospital and Harvard Medical School, USA.
authors: Akila
authors: A
authors: Viswanathan
authors: Brigham & Women's Hospital and Harvard Medical School, USA.
authors: Tina
authors: T
authors: Kapur
mesh_terms: D016477:Artifacts; D001918:Brachytherapy / Q000295:instrumentation* / Q000379:methods; D002408:Catheters, Indwelling; D005260:Female; D006801:Humans; D053783:Magnetic Resonance Imaging, Interventional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D019736:Prostheses and Implants; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D002583:Uterine Cervical Neoplasms / Q000473:pathology* / Q000532:radiotherapy*