Vessel-based brain-shift compensation using elastic registration driven by a patient-specific finite element model

International audienceDuring brain tumor surgery, planning and guidance are based on pre-operative images which do not account for brain-shift.However, this shift is a major source of error in neuro-navigation systems and affects the accuracy of the procedure. The vascular tree is extracted from pre-operative Magnetic Resonance Angiography and from intra-operative Doppler ultrasound images, which provides sparse information on brain deformations.The pre-operative images are then updated based on an elastic registration of the blood vessels, driven by a patient-specific biomechanical model.This biomechanical model is used to extrapolate the deformation to the surrounding soft tissues.Quantitative results on a single surgical case are provided, with an evaluation of the execution time for each processing step.Our method is proved to be efficient to compensate for brain deformation while being compatible with a surgical process

Spatial distribution of malignant transformation in patients with low-grade glioma

Background Malignant transformation represents the natural evolution of diffuse low-grade gliomas (LGG). This is a catastrophic event, causing neurocognitive symptoms, intensified treatment and premature death. However, little is known concerning the spatial distribution of malignant transformation in patients with LGG. Materials and methods Patients histopathological diagnosed with LGG and subsequent radiological malignant transformation were identified from two different institutions. We evaluated the spatial distribution of malignant transformation with (1) visual inspection and (2) segmentations of longitudinal tumor volumes. In (1) a radiological transformation site < 2 cm from the tumor on preceding MRI was defined local transformation. In (2) overlap with pretreatment volume after importation into a common space was defined as local transformation. With a centroid model we explored if there were particular patterns of transformations within relevant subgroups. Results We included 43 patients in the clinical evaluation, and 36 patients had MRIs scans available for longitudinal segmentations. Prior to malignant transformation, residual radiological tumor volumes were > 10 ml in 93% of patients. The transformation site was considered local in 91% of patients by clinical assessment. Patients treated with radiotherapy prior to transformation had somewhat lower rate of local transformations (83%). Based upon the segmentations, the transformation was local in 92%. We did not observe any particular pattern of transformations in examined molecular subgroups. Conclusion Malignant transformation occurs locally and within the T2w hyperintensities in most patients. Although LGG is an infiltrating disease, this data conceptually strengthens the role of loco-regional treatments in patients with LGG.publishedVersio

Employment challenges i Norwegian radiology - whining or real problem?

Masteroppgave i helseledelse (EMBA) - Nord universitet 202

Vessel-based brain-shift compensation using elastic registration driven by a patient-specific finite element model

International audienceDuring brain tumor surgery, planning and guidance are based on pre-operative images which do not account for brain-shift.However, this shift is a major source of error in neuro-navigation systems and affects the accuracy of the procedure. The vascular tree is extracted from pre-operative Magnetic Resonance Angiography and from intra-operative Doppler ultrasound images, which provides sparse information on brain deformations.The pre-operative images are then updated based on an elastic registration of the blood vessels, driven by a patient-specific biomechanical model.This biomechanical model is used to extrapolate the deformation to the surrounding soft tissues.Quantitative results on a single surgical case are provided, with an evaluation of the execution time for each processing step.Our method is proved to be efficient to compensate for brain deformation while being compatible with a surgical process

Vessel-based brain-shift compensation using elastic registration driven by a patient-specific finite element model

International audienceDuring brain tumor surgery, planning and guidance are based on pre-operative images which do not account for brain-shift.However, this shift is a major source of error in neuro-navigation systems and affects the accuracy of the procedure. The vascular tree is extracted from pre-operative Magnetic Resonance Angiography and from intra-operative Doppler ultrasound images, which provides sparse information on brain deformations.The pre-operative images are then updated based on an elastic registration of the blood vessels, driven by a patient-specific biomechanical model.This biomechanical model is used to extrapolate the deformation to the surrounding soft tissues.Quantitative results on a single surgical case are provided, with an evaluation of the execution time for each processing step.Our method is proved to be efficient to compensate for brain deformation while being compatible with a surgical process

Is the anatomical distribution of low-grade gliomas linked to regions of gliogenesis?

Introduction According to the stem cell theory, two neurogenic niches in the adult human brain may harbor cells that initiate the formation of gliomas: The larger subventricular zone (SVZ) and the subgranular zone (SGZ) in the hippocampus. We wanted to explore whether defining molecular markers in low-grade gliomas (LGG; WHO grade II) are related to distance to the neurogenic niches. Methods Patients treated at two Norwegian university hospitals with population-based referral were included. Eligible patients had histopathological verified supratentorial low-grade glioma. IDH mutational status and 1p19q co-deletion status was retrospectively assessed. 159 patients were included, and semi-automatic tumor segmentation was done from pre-treatment T2-weighted (T2W) or Fluid-Attenuated Inversion Recovery (FLAIR) images. 3D maps showing the anatomical distribution of the tumors were then created for each of the three molecular subtypes (IDH mutated/1p19q co-deleted, IDH mutated and IDH wild-type). Both distance from tumor center and tumor border to the neurogenic niches were recorded. Results In this population-based cohort of previously untreated low-grade gliomas, we found that low-grade gliomas are more often found closer to the SVZ than the SGZ, but IDH wild-type tumors are more often found near SGZ. Conclusion Our study suggests that the stem cell origin of IDH wild-type and IDH mutated low-grade gliomas may be different

Spatial distribution of malignant transformation in patients with low-grade glioma

Background Malignant transformation represents the natural evolution of diffuse low-grade gliomas (LGG). This is a catastrophic event, causing neurocognitive symptoms, intensified treatment and premature death. However, little is known concerning the spatial distribution of malignant transformation in patients with LGG. Materials and methods Patients histopathological diagnosed with LGG and subsequent radiological malignant transformation were identified from two different institutions. We evaluated the spatial distribution of malignant transformation with (1) visual inspection and (2) segmentations of longitudinal tumor volumes. In (1) a radiological transformation site < 2 cm from the tumor on preceding MRI was defined local transformation. In (2) overlap with pretreatment volume after importation into a common space was defined as local transformation. With a centroid model we explored if there were particular patterns of transformations within relevant subgroups. Results We included 43 patients in the clinical evaluation, and 36 patients had MRIs scans available for longitudinal segmentations. Prior to malignant transformation, residual radiological tumor volumes were > 10 ml in 93% of patients. The transformation site was considered local in 91% of patients by clinical assessment. Patients treated with radiotherapy prior to transformation had somewhat lower rate of local transformations (83%). Based upon the segmentations, the transformation was local in 92%. We did not observe any particular pattern of transformations in examined molecular subgroups. Conclusion Malignant transformation occurs locally and within the T2w hyperintensities in most patients. Although LGG is an infiltrating disease, this data conceptually strengthens the role of loco-regional treatments in patients with LGG

Quantitative texture analysis in the prediction of IDH status in low-grade gliomas.

publishedVersio