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RESEARCH PRODUCT
Computer-Assisted Approaches for Uterine Fibroid Segmentation in MRgFUS Treatments: Quantitative Evaluation and Clinical Feasibility Analysis
Giorgio Ivan RussoMaria Carla GilardiLeonardo RundoAndrea TangherloniCarmelo MilitelloGiancarlo MauriSalvatore VitabileRoberto Lagallasubject
ING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICAmedicine.medical_specialtyTreatment responseUterine fibroidsComputer scienceMagnetic Resonance guided Focused Ultrasound Surgery0206 medical engineeringThermal ablation02 engineering and technologyClinical feasibility; Computer-assisted medical image segmentation; Magnetic resonance guided focused ultrasound surgery; Non-Perfused volume assessment; Pattern recognition; Uterine fibroidsPattern RecognitionClinical feasibilityING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imagingMagnetic resonance guided focused ultrasound surgeryMagnetic Resonance guided Focused Ultrasound Surgery Uterine fibroids03 medical and health sciences0302 clinical medicineNon-Perfused Volume assessmentmedicineUterine fibroidSegmentationUterine fibroids Indexed keywordsSettore INF/01 - InformaticaComputer Science (all)INF/01 - INFORMATICAmedicine.disease020601 biomedical engineeringComputer-assisted medical image segmentation; Pattern Recognition; Magnetic Resonance guided Focused Ultrasound Surgery Uterine fibroids; Non-Perfused Volume assessment; Clinical feasibility;Decision Sciences (all)Pattern recognition (psychology)RadiologyUterine fibroidsComputer-assisted medical image segmentationdescription
Nowadays, uterine fibroids can be treated using Magnetic Resonance guided Focused Ultrasound Surgery (MRgFUS), which is a non-invasive therapy exploiting thermal ablation. In order to measure the Non-Perfused Volume (NPV) for treatment response assessment, the ablated fibroid areas (i.e., Region of Treatment, ROT) are manually contoured by a radiologist. The current operator-dependent methodology could affect the subsequent follow-up phases, due to the lack of result repeatability. In addition, this fully manual procedure is time-consuming, considerably increasing execution times. These critical issues can be addressed only by means of accurate and efficient automated Pattern Recognition approaches. In this contribution, we evaluate two computer-assisted segmentation methods, which we have already developed and validated, for uterine fibroid segmentation in MRgFUS treatments. A quantitative comparison on segmentation accuracy, in terms of area-based and distance-based metrics, was performed. The clinical feasibility of these approaches was assessed from physicians' perspective, by proposing an integrated solution.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 |