Computer-assisted 3D planning, navigation and the possibilities offered by intra-operative imaging updates have made a large impact on neurological surgery. Three-dimensional rendering of complex medical image information, as well as co-registration of multimodal sources has reached a highly sophisticated level. When introduced into surgical navigation however, this pre-operative data is unable to account for intra-operative changes, ('brain-shift'). To update structural information during surgery, an open-configured, intra-operative MRI (Signa SP, 0.5 T) was realised at our institution in 1995. The design, advantages, limitations and current applications of this system are discussed, with emphasis on the integration of imaging into procedures. We also introduce our integrated platform for intra-operative visualisation and navigation, the 3D Slicer.
OBJECTIVE: Recent evidence suggests that the cerebellum may play a role in higher cognitive functions and, therefore, may play an important role in schizophrenia. METHOD: The authors used magnetic resonance imaging to measure cerebellum and vermis volume in 15 patients with schizophrenia and 15 normal comparison subjects. RESULTS: They found that 1) vermis volume was greater in patients with schizophrenia than in normal subjects, 2) greater vermis white matter volume in the patients with schizophrenia significantly correlated with severity of positive symptoms and thought disorder and with impairment in verbal logical memory, and 3) patients with schizophrenia showed a trend for more cerebellar hemispheric volume asymmetry (left greater than right). CONCLUSIONS: These data suggest that an abnormality in the vermis may contribute to the pathophysiology of schizophrenia.
OBJECTIVE: Gray matter volume and glucose utilization have been reported to be reduced in the left subgenual cingulate of subjects with familial bipolar or unipolar depression. It is unclear whether these findings are secondary to recurrent illness or are part of a familial/genetic syndrome. The authors' goal was to clarify these findings. METHOD: Volumetric analyses were performed by using magnetic resonance imaging in 41 patients experiencing their first episode of affective disorder or schizophrenia and in 20 normal comparison subjects. RESULTS: The left subgenual cingulate volume of the patients with affective disorder who had a family history of affective disorder was smaller than that of patients with affective disorder with no family history of the illness and the normal comparison subjects. Patients with schizophrenia did not differ from comparison subjects in left subgenual cingulate volume. CONCLUSIONS: Left subgenual cingulate abnormalities are present at first hospitalization for psychotic affective disorder in patients who have a family history of affective disorder.
BACKGROUND: Structural MRI data indicate schizophrenics have reduced left-sided temporal lobe gray matter volumes, especially in the superior temporal gyrus (STG) and medial temporal lobe. Our data further suggest a specificity to schizophrenia spectrum disorders of STG volume reduction. Interpretation of research studies involving schizophrenics may be complicated by the effects of exposure to neuroleptics and chronic illness. Sharing the same genetic diathesis of schizophrenics, subjects with schizotypal personality disorder (SPD) offer a unique opportunity to evaluate commonalities between schizophrenia and SPD, particularly as SPD subjects are characterized by cognitive and perceptual distortions, an inability to tolerate close friendships, and odd behavior, but they are not psychotic and so have generally not been prescribed neuroleptics nor hospitalized. Evaluation of brain structure in SPD may thus offer insight into the "endophenotype" common to both disorders. In addition, differences between groups may suggest which are the brain structures of schizophrenics that contribute to the development of psychosis. METHODS: To test the hypothesis of whether SPD subjects might show similar STG abnormalities, STG and medial temporal lobe regions of interest (ROI) were manually drawn on high resolution coronal MRI 1.5 mm thick slices. Images were derived from 16 right-handed male SPD subjects, without regard to family history, and 14 healthy, right-handed, comparison males who did not differ from the SPD group on parental socio-economic status, age, or verbal IQ. RESULTS: As predicted, SPD subjects showed a reduction in left STG gray matter volume compared with age and gender matched comparison subjects. SPD subjects also showed reduced parahippocampal left/right asymmetry and a high degree of disordered thinking. Comparisons with chronic schizophrenics previously studied by us showed the SPD group had a similarity of left STG gray matter volume reduction, but fewer medial temporal lobe abnormalities. CONCLUSIONS: These abnormalities strengthen the hypothesis of a temporal lobe abnormality in SPD, and the similarity of STG findings in schizophrenia and SPD suggest that STG abnormalities may be part of the spectrum "endophenotype." It is also possible that presence of medial temporal lobe abnormalities may help to differentiate who will develop schizophrenia and who will develop the less severe schizophrenia spectrum disorder, SPD.
PURPOSE: To review preliminary experience with an open-bore magnetic resonance (MR) imaging system for guidance in intracranial surgical procedures. MATERIALS AND METHODS: A vertically oriented, open-configuration 0.5-T MR imager was housed in a sterile procedure room. Receive and transmit surface coils were wrapped around the patient's head, and images were displayed on monitors mounted in the gap of the magnet and visible to surgeons. During 2 years, 200 intracranial procedures were performed. RESULTS: There were 111 craniotomies, 68 biopsies, 12 intracranial cyst evaluations, four subdural drainages, and five transsphenoidal pituitary resections performed with the intraoperative MR unit. In each case, the intraoperative MR system yielded satisfactory results by allowing the radiologist to guide surgeons toward lesions and to assist in treatment. In two patients, hyperacute hemorrhage was noted and removed. The duration of the procedure and the complication rate were similar to those of conventional surgery. CONCLUSION: Intraoperative MR imaging was successfully implemented for a variety of intracranial procedures and provided continuous visual feedback, which can be helpful in all stages of neurosurgical intervention without affecting the duration of the procedure or the incidence of complications. This system has potential advantages over conventional frame-based and frameless stereotactic procedures with respect to the safety and effectiveness of neurosurgical interventions.
OBJECTIVE: Studies of schizophrenia have not clearly defined handedness as a differentiating variable. Moreover, the relationship between thought disorder and anatomical anomalies has not been studied extensively in left-handed schizophrenic men. The twofold purpose of this study was to investigate gray matter volumes in the superior temporal gyrus of the temporal lobe (left and right hemispheres) in left-handed schizophrenic men and left-handed comparison men, in order to determine whether thought disorder in the left-handed schizophrenic men correlated with tissue volume abnormalities. METHOD: Left-handed male patients (N = 8) with DSM-III-R diagnoses of schizophrenia were compared with left-handed comparison men (N = 10) matched for age, socioeconomic status, and IQ. Magnetic resonance imaging (MRI) with a 1.5-T magnet was used to obtain scans, which consisted of contiguous 1.5-mm slices of the whole brain. MRI analyses (as previously defined by the authors) included the anterior, posterior, and total superior temporal gyrus in both the left and right hemispheres. RESULTS: There were three significant findings regarding the left-handed schizophrenic men: 1) bilaterally smaller gray matter volumes in the posterior superior temporal gyrus (16% smaller on the right, 15% smaller on the left); 2) a smaller volume on the right side of the total superior temporal gyrus; and 3) a positive correlation between thought disorder and tissue volume in the right anterior superior temporal gyrus. CONCLUSIONS: These results suggest that expression of brain pathology differs between left-handed and right-handed schizophrenic men and that the pathology is related to cognitive disturbance.
PURPOSE: Diffusion encoding with asymmetric gradient waveforms is appealing because the asymmetry provides superior efficiency. However, concomitant gradients may cause a residual gradient moment at the end of the waveform, which can cause significant signal error and image artifacts. The purpose of this study was to develop an asymmetric waveform designs for tensor-valued diffusion encoding that is not sensitive to concomitant gradients. METHODS: The "Maxwell index" was proposed as a scalar invariant to capture the effect of concomitant gradients. Optimization of "Maxwell-compensated" waveforms was performed in which this index was constrained. Resulting waveforms were compared to waveforms from literature, in terms of the measured and predicted impact of concomitant gradients, by numerical analysis as well as experiments in a phantom and in a healthy human brain. RESULTS: Maxwell-compensated waveforms with Maxwell indices below 100 (mT/m) ms showed negligible signal bias in both numerical analysis and experiments. By contrast, several waveforms from literature showed gross signal bias under the same conditions, leading to a signal bias that was large enough to markedly affect parameter maps. Experimental results were accurately predicted by theory. CONCLUSION: Constraining the Maxwell index in the optimization of asymmetric gradient waveforms yields efficient diffusion encoding that negates the effects of concomitant fields while enabling arbitrary shapes of the b-tensor. This waveform design is especially useful in combination with strong gradients, long encoding times, thick slices, simultaneous multi-slice acquisition, and large FOVs.
Computational biomechanics of the brain for neurosurgery is an emerging area of research recently gaining in importance and practical applications. This review paper presents the contributions of the Intelligent Systems for Medicine Laboratory and its collaborators to this field, discussing the modeling approaches adopted and the methods developed for obtaining the numerical solutions. We adopt a physics-based modeling approach and describe the brain deformation in mechanical terms (such as displacements, strains, and stresses), which can be computed using a biomechanical model, by solving a continuum mechanics problem. We present our modeling approaches related to geometry creation, boundary conditions, loading, and material properties. From the point of view of solution methods, we advocate the use of fully nonlinear modeling approaches, capable of capturing very large deformations and nonlinear material behavior. We discuss finite element and meshless domain discretization, the use of the total Lagrangian formulation of continuum mechanics, and explicit time integration for solving both time-accurate and steady-state problems. We present the methods developed for handling contacts and for warping 3D medical images using the results of our simulations. We present two examples to showcase these methods: brain shift estimation for image registration and brain deformation computation for neuronavigation in epilepsy treatment.
Jean-Jacques Lemaire, Antonio De Salles, Guillaume Coll, Youssef El Ouadih, Rémi Chaix, Jérôme Coste, Franck Durif, Nikos Makris, and Ron Kikinis. 8/2019. “MRI Atlas of the Human Deep Brain.” Front Neurol, 10, Pp. 851.Abstract
Mastering detailed anatomy of the human deep brain in clinical neurosciences is challenging. Although numerous pioneering works have gathered a large dataset of structural and topographic information, it is still difficult to transfer this knowledge into practice, even with advanced magnetic resonance imaging techniques. Thus, classical histological atlases continue to be used to identify structures for stereotactic targeting in functional neurosurgery. Physicians mainly use these atlases as a template co-registered with the patient's brain. However, it is possible to directly identify stereotactic targets on MRI scans, enabling personalized targeting. In order to help clinicians directly identify deep brain structures relevant to present and future medical applications, we built a volumetric MRI atlas of the deep brain (MDBA) on a large scale (infra millimetric). Twelve hypothalamic, 39 subthalamic, 36 telencephalic, and 32 thalamic structures were identified, contoured, and labeled. Nineteen coronal, 18 axial, and 15 sagittal MRI plates were created. Although primarily designed for direct labeling, the anatomic space was also subdivided in twelfths of AC-PC distance, leading to proportional scaling in the coronal, axial, and sagittal planes. This extensive work is now available to clinicians and neuroscientists, offering another representation of the human deep brain ([https://hal.archives-ouvertes.fr/] [hal-02116633]). The atlas may also be used by computer scientists who are interested in deciphering the topography of this complex region.
Intraoperative tissue deformation, known as brain shift, decreases the benefit of using preoperative images to guide neurosurgery. Non-rigid registration of preoperative magnetic resonance (MR) to intraoperative ultrasound (US) has been proposed as a means to compensate for brain shift. We focus on the initial registration from MR to predurotomy US. We present a method that builds on previous work to address the need for accuracy and generality of MR-iUS registration algorithms in multi-site clinical data. To improve accuracy of registration, we use high-dimensional texture attributes instead of image intensities and propose to replace the standard difference-based attribute matching with correlation-based attribute matching. We also present a strategy that deals explicitly with the large field-of-view mismatch between MR and iUS images. We optimize key parameters across independent MR-iUS brain tumor datasets acquired at three different institutions, with a total of 43 tumor patients and 758 corresponding landmarks to validate the registration algorithm. Despite differences in imaging protocols, patient demographics and landmark distributions, our algorithm was able to reduce landmark errors prior to registration in three data sets (5.37 ± 4.27, 4.18 ± 1.97 and 6.18 ± 3.38 mm, respectively) to a consistently low level (2.28 ± 0.71, 2.08 ± 0.37 and 2.24 ± 0.78 mm, respectively). Our algorithm is compared to 15 other algorithms that have been previously tested on MR-iUS registration and it is competitive with the state-of-the-art on multiple datasets. We show that our algorithm has one of the lowest errors in all datasets (accuracy), and this is achieved while sticking to a fixed set of parameters for multi-site data (generality). In contrast, other algorithms/tools of similar performance need per-dataset parameter tuning (high accuracy but lower generality), and those that stick to fixed parameters have larger errors or inconsistent performance (generality but not the top accuracy). We further characterized landmark errors according to brain regions and tumor types, a topic so far missing in the literature. We found that landmark errors were higher in high-grade than low-grade glioma patients, and higher in tumor regions than in other brain regions.
PURPOSE: In image-guided surgery for glioma removal, neurosurgeons usually plan the resection on images acquired before surgery and use them for guidance during the subsequent intervention. However, after the surgical procedure has begun, the preplanning images become unreliable due to the brain shift phenomenon, caused by modifications of anatomical structures and imprecisions in the neuronavigation system. To obtain an updated view of the resection cavity, a solution is to collect intraoperative data, which can be additionally acquired at different stages of the procedure in order to provide a better understanding of the resection. A spatial mapping between structures identified in subsequent acquisitions would be beneficial. We propose here a fully automated segmentation-based registration method to register ultrasound (US) volumes acquired at multiple stages of neurosurgery. METHODS: We chose to segment sulci and falx cerebri in US volumes, which remain visible during resection. To automatically segment these elements, first we trained a convolutional neural network on manually annotated structures in volumes acquired before the opening of the dura mater and then we applied it to segment corresponding structures in different surgical phases. Finally, the obtained masks are used to register US volumes acquired at multiple resection stages. RESULTS: Our method reduces the mean target registration error (mTRE) between volumes acquired before the opening of the dura mater and during resection from 3.49 mm (± 1.55 mm) to 1.36 mm (± 0.61 mm). Moreover, the mTRE between volumes acquired before opening the dura mater and at the end of the resection is reduced from 3.54 mm (± 1.75 mm) to 2.05 mm (± 1.12 mm). CONCLUSION: The segmented structures demonstrated to be good candidates to register US volumes acquired at different neurosurgical phases. Therefore, our solution can compensate brain shift in neurosurgical procedures involving intraoperative US data.