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Cone-Beam CT image contrast and attenuation-map linearity improvement (CALI) for brain stereotactic radiosurgery procedures.
Hashemi, SayedMasoud; Huynh, Christopher; Sahgal, Arjun; Song, William Y; Nordström, Håkan; Eriksson, Markus; Mainprize, James G; Lee, Young; Ruschin, Mark.
Afiliación
  • Hashemi S; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Huynh C; Department of Physics, Ryerson University, Toronto, ON, Canada.
  • Sahgal A; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Song WY; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Nordström H; Elekta Instrument AB, Stockholm, Sweden.
  • Eriksson M; Elekta Instrument AB, Stockholm, Sweden.
  • Mainprize JG; Sunnybrook Research Institute, Toronto, ON, Canada.
  • Lee Y; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Ruschin M; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
J Appl Clin Med Phys ; 19(6): 200-208, 2018 Nov.
Article en En | MEDLINE | ID: mdl-30338919
A Contrast and Attenuation-map Linearity Improvement (CALI) framework is proposed for cone-beam CT (CBCT) images used for brain stereotactic radiosurgery (SRS). The proposed framework is tailored to improve soft tissue contrast of a new point-of-care image-guided SRS system that employs a challenging half cone beam geometry, but can be readily reproduced on any CBCT platform. CALI includes a pre- and post-processing step. In pre-processing we apply a shading and beam hardening artifact correction to the projections, and in post-processing step we correct the dome/capping artifact on reconstructed images caused by the spatial variations in X-ray energy generated by the bowtie-filter. The shading reduction together with the beam hardening and dome artifact correction algorithms aim to improve the linearity and accuracy of the CT-numbers (CT#). The CALI framework was evaluated using CatPhan to quantify linearity, contrast-to-noise (CNR), and CT# accuracy, as well as subjectively on patient images acquired on a clinical system. Linearity of the reconstructed attenuation-map was improved from 0.80 to 0.95. The CT# mean absolute measurement error was reduced from 76.1 to 26.9 HU. The CNR of the acrylic insert in the sensitometry module was improved from 1.8 to 7.8. The resulting clinical brain images showed substantial improvements in soft tissue contrast visibility, revealing structures such as ventricles which were otherwise undetectable in the original clinical images obtained from the system. The proposed reconstruction framework also improved CT# accuracy compared to the original images acquired on the system. For frameless image-guided SRS, improving soft tissue visibility can facilitate evaluation of MR to CBCT co-registration. Moreover, more accurate CT# may enable the use of CBCT for daily dose delivery measurements.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Neoplasias Encefálicas / Radiocirugia / Fantasmas de Imagen / Tomografía Computarizada de Haz Cónico Tipo de estudio: Etiology_studies Límite: Humans Idioma: En Revista: J Appl Clin Med Phys Asunto de la revista: BIOFISICA Año: 2018 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Planificación de la Radioterapia Asistida por Computador / Neoplasias Encefálicas / Radiocirugia / Fantasmas de Imagen / Tomografía Computarizada de Haz Cónico Tipo de estudio: Etiology_studies Límite: Humans Idioma: En Revista: J Appl Clin Med Phys Asunto de la revista: BIOFISICA Año: 2018 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos