Int J Comput Assist Radiol Surg - Deformable registration of preoperative MR, pre-resection ultrasound, and post-resection ultrasound images of neurosurgery.

Tópicos

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Resumo

RPOSE: Sites that use ultrasound (US) in image-guided neurosurgery (IGNS) of brain tumors generally have three sets of imaging data: preoperative magnetic resonance (MR) image, pre-resection US, and post-resection US. The MR image is usually acquired days before the surgery, the pre-resection US is obtained after the craniotomy but before the resection, and finally, the post-resection US scan is performed after the resection of the tumor. The craniotomy and tumor resection both cause brain deformation, which significantly reduces the accuracy of the MR-US alignment.METHOD: Three unknown transformations exist between the three sets of imaging data: MR to pre-resection US, pre- to post-resection US, and MR to post-resection US. We use two algorithms that we have recently developed to perform the first two registrations (i.e., MR to pre-resection US and pre- to post-resection US). Regarding the third registration (MR to post-resection US), we evaluate three strategies. The first method performs a registration between the MR and pre-resection US, and another registration between the pre- and post-resection US. It then composes the two transformations to register MR and post-resection US; we call this method compositional registration. The second method ignores the pre-resection US and directly registers the MR and post-resection US; we refer to this method as direct registration. The third method is a combination of the first and second: it uses the solution of the compositional registration as an initial solution for the direct registration method. We call this method group-wise registration.RESULTS: We use data from 13 patients provided in the MNI BITE database for all of our analysis. Registration of MR and pre-resection US reduces the average of the mean target registration error (mTRE) from 4.1 to 2.4 mm. Registration of pre- and post-resection US reduces the average mTRE from 3.7 to 1.5 mm. Regarding the registration of MR and post-resection US, all three strategies reduce the mTRE. The initial average mTRE is 5.9 mm, which reduces to 3.3 mm with the compositional method, 2.9 mm with the direct technique, and 2.8 mm with the group-wise method.CONCLUSION: Deformable registration of MR and pre- and post-resection US images significantly improves their alignment. Among the three methods proposed for registering the MR to post-resection US, the group-wise method gives the lowest TRE values. Since the running time of all registration algorithms is less than 2 min on one core of a CPU, they can be integrated into IGNS systems for interactive use during surgery.

Resumo Limpo

rpose site use ultrasound us imageguid neurosurgeri ign brain tumor general three set imag data preoper magnet reson mr imag preresect us postresect us mr imag usual acquir day surgeri preresect us obtain craniotomi resect final postresect us scan perform resect tumor craniotomi tumor resect caus brain deform signific reduc accuraci mrus alignmentmethod three unknown transform exist three set imag data mr preresect us pre postresect us mr postresect us use two algorithm recent develop perform first two registr ie mr preresect us pre postresect us regard third registr mr postresect us evalu three strategi first method perform registr mr preresect us anoth registr pre postresect us compos two transform regist mr postresect us call method composit registr second method ignor preresect us direct regist mr postresect us refer method direct registr third method combin first second use solut composit registr initi solut direct registr method call method groupwis registrationresult use data patient provid mni bite databas analysi registr mr preresect us reduc averag mean target registr error mtre mm registr pre postresect us reduc averag mtre mm regard registr mr postresect us three strategi reduc mtre initi averag mtre mm reduc mm composit method mm direct techniqu mm groupwis methodconclus deform registr mr pre postresect us imag signific improv align among three method propos regist mr postresect us groupwis method give lowest tre valu sinc run time registr algorithm less min one core cpu can integr ign system interact use surgeri

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