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Computer-based radiological longitudinal evaluation of meningiomas following stereotactic radiosurgery.
Shimol, Eli Ben; Joskowicz, Leo; Eliahou, Ruth; Shoshan, Yigal.
Afiliación
  • Shimol EB; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
  • Joskowicz L; School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel. josko@cs.huji.ac.il.
  • Eliahou R; CASMIP Lab - Computer Aided Surgery and Medical Image Processing Laboratory, The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Givat Ram Campus, 91904, Jerusalem, Israel. josko@cs.huji.ac.il.
  • Shoshan Y; Department of Radiology, Hadassah University Medical Center, Ein-Karem, Jerusalem, Israel.
Int J Comput Assist Radiol Surg ; 13(2): 215-228, 2018 Feb.
Article en En | MEDLINE | ID: mdl-29032421
ABSTRACT

PURPOSE:

Stereotactic radiosurgery (SRS) is a common treatment for intracranial meningiomas. SRS is planned on a pre-therapy gadolinium-enhanced T1-weighted MRI scan (Gd-T1w MRI) in which the meningioma contours have been delineated. Post-SRS therapy serial Gd-T1w MRI scans are then acquired for longitudinal treatment evaluation. Accurate tumor volume change quantification is required for treatment efficacy evaluation and for treatment continuation.

METHOD:

We present a new algorithm for the automatic segmentation and volumetric assessment of meningioma in post-therapy Gd-T1w MRI scans. The inputs are the pre- and post-therapy Gd-T1w MRI scans and the meningioma delineation in the pre-therapy scan. The output is the meningioma delineations and volumes in the post-therapy scan. The algorithm uses the pre-therapy scan and its meningioma delineation to initialize an extended Chan-Vese active contour method and as a strong patient-specific intensity and shape prior for the post-therapy scan meningioma segmentation. The algorithm is automatic, obviates the need for independent tumor localization and segmentation initialization, and incorporates the same tumor delineation criteria in both the pre- and post-therapy scans.

RESULTS:

Our experimental results on retrospective pre- and post-therapy scans with a total of 32 meningiomas with volume ranges 0.4-26.5 cm[Formula see text] yield a Dice coefficient of [Formula see text]% with respect to ground-truth delineations in post-therapy scans created by two clinicians. These results indicate a high correspondence to the ground-truth delineations.

CONCLUSION:

Our algorithm yields more reliable and accurate tumor volume change measurements than other stand-alone segmentation methods. It may be a useful tool for quantitative meningioma prognosis evaluation after SRS.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Neoplasias Encefálicas / Imagen por Resonancia Magnética / Radiocirugia / Meningioma Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Int J Comput Assist Radiol Surg Asunto de la revista: RADIOLOGIA Año: 2018 Tipo del documento: Article País de afiliación: Israel

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Neoplasias Encefálicas / Imagen por Resonancia Magnética / Radiocirugia / Meningioma Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Int J Comput Assist Radiol Surg Asunto de la revista: RADIOLOGIA Año: 2018 Tipo del documento: Article País de afiliación: Israel