OBJECTIVE: The aim of this study was to determine whether elastography, a sonographically based real-time strain imaging method for registering the elastic properties of tissue, can be used in brain tumor surgery. METHODS: A modification of classic elastography called vibrography was applied in these measurements with static compression replaced by low-frequency axial vibration. Twenty patients were examined with this technique during brain tumor surgery. A conventional sonographic system with a custom-designed radio frequency (RF) interface was used. The RF data were digitized with a 50-MHz, 12-bit peripheral component interconnect analog/digital converter for real-time or offline processing. Sonographic RF data were acquired with a 6.5-MHz endocavity curved array. A special applicator equipped with a stepping motor moved the ultrasonic probe and produced a low-frequency mechanical vibration of approximately 5 to 10 Hz with a vibration amplitude of 0.3 mm. RESULTS: Detection of tumors was possible in 18 of 20 cases. Brain tissue was normally color coded orange or red. Three major groups of tumors with different elastic properties relative to brain tissue could be differentiated. In 3 cases, the stiffness of the tumor was identical to that of brain tissue, but the tumors were surrounded by a thin yellow border. Six tumors displayed higher strain than brain, whereas 7 tumors exhibited lower strain than the surrounding cerebrum. Two patients could not be assigned clearly to either of these groups. CONCLUSIONS: These findings indicate that vibrography is a feasible imaging method for brain tumor surgery and may have numerous potential applications in neurosurgery if further improvements are made.
OBJECTIVE: The aim of this study was to determine whether elastography, a sonographically based real-time strain imaging method for registering the elastic properties of tissue, can be used in brain tumor surgery. METHODS: A modification of classic elastography called vibrography was applied in these measurements with static compression replaced by low-frequency axial vibration. Twenty patients were examined with this technique during brain tumor surgery. A conventional sonographic system with a custom-designed radio frequency (RF) interface was used. The RF data were digitized with a 50-MHz, 12-bit peripheral component interconnect analog/digital converter for real-time or offline processing. Sonographic RF data were acquired with a 6.5-MHz endocavity curved array. A special applicator equipped with a stepping motor moved the ultrasonic probe and produced a low-frequency mechanical vibration of approximately 5 to 10 Hz with a vibration amplitude of 0.3 mm. RESULTS: Detection of tumors was possible in 18 of 20 cases. Brain tissue was normally color coded orange or red. Three major groups of tumors with different elastic properties relative to brain tissue could be differentiated. In 3 cases, the stiffness of the tumor was identical to that of brain tissue, but the tumors were surrounded by a thin yellow border. Six tumors displayed higher strain than brain, whereas 7 tumors exhibited lower strain than the surrounding cerebrum. Two patients could not be assigned clearly to either of these groups. CONCLUSIONS: These findings indicate that vibrography is a feasible imaging method for brain tumor surgery and may have numerous potential applications in neurosurgery if further improvements are made.
Authors: R F Barajas; C P Hess; J J Phillips; C J Von Morze; J P Yu; S M Chang; S J Nelson; M W McDermott; M S Berger; S Cha Journal: AJNR Am J Neuroradiol Date: 2013-02-14 Impact factor: 3.825
Authors: Shreyas S Rao; John J Lannutti; Mariano S Viapiano; Atom Sarkar; Jessica O Winter Journal: Tissue Eng Part B Rev Date: 2013-10-30 Impact factor: 6.389
Authors: Rahul Sastry; Wenya Linda Bi; Steve Pieper; Sarah Frisken; Tina Kapur; William Wells; Alexandra J Golby Journal: J Neuroimaging Date: 2016-08-19 Impact factor: 2.486
Authors: Francesco Prada; Massimiliano Del Bene; Alessandro Moiraghi; Cecilia Casali; Federico Giuseppe Legnani; Andrea Saladino; Alessandro Perin; Ignazio Gaspare Vetrano; Luca Mattei; Carla Richetta; Marco Saini; Francesco DiMeco Journal: Biomed Res Int Date: 2015-05-25 Impact factor: 3.411