Chengjun Yao

Transsphenoidal pituitary macroadenomas resection guided by PoleStar N20 low-field intraoperative magnetic resonance imaging: comparison with early postoperative high-field magnetic resonance imaging.

OBJECTIVETo evaluate the applicability of low-field intraoperative magnetic resonance imaging (iMRI) during transsphenoidal surgery of pituitary macroadenomas. METHODSFifty-five transsphenoidal surgeries were performed for macroadenomas (modified Hardys Grade II–IV) resections. All of the surgical processes were guided by real-time updated contrast T1-weighted coronal and sagittal images, which were acquired with 0.15 Tesla PoleStar N20 iMRI (Medtronic Navigation, Louisville, CO). The definitive benefits as well as major drawbacks of low-field iMRI in transsphenoidal surgery were assessed with respect to intraoperative imaging, tumor resection control, comparison with early postoperative high-field magnetic resonance imaging, and follow-up outcomes. RESULTSIntraoperative imaging revealed residual tumor and guided extended tumor resection in 17 of 55 cases. As a result, the percentage of gross total removal of macroadenomas increased from 58.2% to 83.6%. The accuracy of imaging evaluation of low-field iMRI was 81.8%, compared with early postoperative high-field MRI (Correlation coefficient, 0.677; P < 0.001). A significantly lower accuracy was identified with low-field iMRI in 6 cases with cavernous sinus invasion (33.3%) in contrast to the 87.8% found with other sites (Fishers exact test, P < 0.001). CONCLUSIONThe PoleStar N20 low-field iMRI navigation system is a promising tool for safe, minimally invasive, endonasal, transsphenoidal pituitary macroadenomas resection. It enables neurosurgeons to control the extent of tumor resection, particularly for suprasellar tumors, ensuring surgical accuracy and safety, and leading to a decreased likelihood of repeat surgeries. However, this technology is still not satisfying in estimating the amount of the parasellar residual tumor invading into cavernous sinus, given the false or uncertain images generated by low-field iMRI in this region, which are difficult to discriminate between tumor remnant and blood within the venous sinus.

Clinical application of motor pathway mapping using diffusion tensor imaging tractography and intraoperative direct subcortical stimulation in cerebral glioma surgery: a prospective cohort study.

BACKGROUND Glioma surgery in eloquent areas remains a challenge because of the risk of postoperative motor deficits. OBJECTIVE To prospectively evaluate the efficiency of using a combination of diffusion tensor imaging (DTI) tractography functional neuronavigation and direct subcortical stimulation (DsCS) to yield a maximally safe resection of cerebral glioma in eloquent areas. METHODS A prospective cohort study was conducted in 58 subjects with an initial diagnosis of primary cerebral glioma within or adjacent to the pyramidal tract (PT). The white matter beneath the resection cavity was stimulated along the PT, which was visualized with DTI tractography. The intercept between the PT border and DsCS site was measured. The sensitivity and specificity of DTI tractography for PT mapping were evaluated. The efficiency of the combined use of both techniques on motor function preservation was assessed. RESULTS Postoperative analysis showed gross total resection in 40 patients (69.0%). Seventeen patients (29.3%) experienced postoperative worsening; 1-month motor deficit was observed in 6 subjects (10.3%). DsCS verified a high concordance rate with DTI tractography for PT mapping. The sensitivity and specificity of DTI were 92.6% and 93.2%, respectively. The intercepts between positive DsCS sites and imaged PTs were 2.0 to 14.7 mm (5.2 ± 2.2 mm). The 6-month Karnofsky performance scale scores in 50 postoperative subjects were significantly increased compared with their preoperative scores. CONCLUSION DTI tractography is effective but not completely reliable in delineating the descending motor pathways. Integration of DTI and DsCS favors patient-specific surgery for cerebral glioma in eloquent areas.

The relationship between Cho/NAA and glioma metabolism: implementation for margin delineation of cerebral gliomas

BackgroundThe marginal delineation of gliomas cannot be defined by conventional imaging due to their infiltrative growth pattern. Here we investigate the relationship between changes in glioma metabolism by proton magnetic resonance spectroscopic imaging (1H-MRSI) and histopathological findings in order to determine an optimal threshold value of choline/N-acetyl-aspartate (Cho/NAA) that can be used to define the extent of glioma spread.MethodEighteen patients with different grades of glioma were examined using 1H-MRSI. Needle biopsies were performed under the guidance of neuronavigation prior to craniotomy. Intraoperative magnetic resonance imaging (MRI) was performed to evaluate the accuracy of sampling. Haematoxylin and eosin, and immunohistochemical staining with IDH1, MIB-1, p53, CD34 and glial fibrillary acidic protein (GFAP) antibodies were performed on all samples. Logistic regression analysis was used to determine the relationship between Cho/NAA and MIB-1, p53, CD34, and the degree of tumour infiltration. The clinical threshold ratio distinguishing tumour tissue in high-grade (grades III and IV) glioma (HGG) and low-grade (grade II) glioma (LGG) was calculated.ResultsIn HGG, higher Cho/NAA ratios were associated with a greater probability of higher MIB-1 counts, stronger CD34 expression, and tumour infiltration. Ratio threshold values of 0.5, 1.0, 1.5 and 2.0 appeared to predict the specimens containing the tumour with respective probabilities of 0.38, 0.60, 0.79, 0.90 in HGG and 0.16, 0.39, 0.67, 0.87 in LGG.ConclusionsHGG and LGG exhibit different spectroscopic patterns. Using 1H-MRSI to guide the extent of resection has the potential to improve the clinical outcome of glioma surgery.

Awake language mapping and 3-Tesla intraoperative MRI-guided volumetric resection for gliomas in language areas.

The use of both awake surgery and intraoperative MRI (iMRI) has been reported to optimize the maximal safe resection of gliomas. However, there has been little research into combining these two demanding procedures. We report our unique experience with, and methodology of, awake surgery in a movable iMRI system, and we quantitatively evaluate the contribution of the combination on the extent of resection (EOR) and functional outcome of patients with gliomas involving language areas. From March 2011 to November 2011, 30 consecutive patients who underwent awake surgery with iMRI guidance were prospectively investigated. The EOR was assessed by volumetric analysis. Language assessment was conducted before surgery and 1 week, 1 month, 3 months and 6 months after surgery using the Aphasia Battery of Chinese. Awake language mapping integrated with 3.0 Tesla iMRI was safely performed for all patients. An additional resection was conducted in 11 of 30 patients (36.7%) after iMRI. The median EOR significantly increased from 92.5% (range, 75.1-97.0%) to 100% (range, 92.6-100%) as a result of iMRI (p<0.01). Gross total resection was achieved in 18 patients (60.0%), and in seven of those patients (23.3%), the gross total resection could be attributed to iMRI. A total of 12 patients (40.0%) suffered from transient language deficits; however, only one (3.3%) patient developed a permanent deficit. This study demonstrates the potential utility of combining awake craniotomy with iMRI; it is safe and reliable to perform awake surgery using a movable iMRI.

A Sparse Intraoperative Data-Driven Biomechanical Model to Compensate for Brain Shift during Neuronavigation

BACKGROUND AND PURPOSE: Intraoperative brain deformation is an important factor compromising the accuracy of image-guided neurosurgery. The purpose of this study was to elucidate the role of a model-updated image in the compensation of intraoperative brain shift. MATERIALS AND METHODS: An FE linear elastic model was built and evaluated in 11 patients with craniotomies. To build this model, we provided a novel model-guided segmentation algorithm. After craniotomy, the sparse intraoperative data (the deformed cortical surface) were tracked by a 3D LRS. The surface deformation, calculated by an extended RPM algorithm, was applied on the FE model as a boundary condition to estimate the entire brain shift. The compensation accuracy of this model was validated by the real-time image data of brain deformation acquired by intraoperative MR imaging. RESULTS: The prediction error of this model ranged from 1.29 to 1.91 mm (mean, 1.62 ± 0.22 mm), and the compensation accuracy ranged from 62.8% to 81.4% (mean, 69.2 ± 5.3%). The compensation accuracy on the displacement of subcortical structures was higher than that of deep structures (71.3 ± 6.1%:66.8 ± 5.0%, P < .01). In addition, the compensation accuracy in the group with a horizontal bone window was higher than that in the group with a nonhorizontal bone window (72.0 ± 5.3%:65.7 ± 2.9%, P < .05). CONCLUSIONS: Combined with our novel model-guided segmentation and extended RPM algorithms, this sparse data-driven biomechanical model is expected to be a reliable, efficient, and convenient approach for compensation of intraoperative brain shift in image-guided surgery.

Awake intraoperative functional MRI (ai-fMRI) for mapping the eloquent cortex: Is it possible in awake craniotomy?

As a promising noninvasive imaging technique, functional MRI (fMRI) has been extensively adopted as a functional localization procedure for surgical planning. However, the information provided by preoperative fMRI (pre-fMRI) is hampered by the brain deformation that is secondary to surgical procedures. Therefore, intraoperative fMRI (i-fMRI) becomes a potential alternative that can compensate for brain shifts by updating the functional localization information during craniotomy. However, previous i-fMRI studies required that patients be under general anesthesia, preventing the wider application of such a technique as the patients cannot perform tasks unless they are awake. In this study, we propose a new technique that combines awake surgery and i-fMRI, named “awake” i-fMRI (ai-fMRI). We introduced ai-fMRI to the real-time localization of sensorimotor areas during awake craniotomy in seven patients. The results showed that ai-fMRI could successfully detect activations in the bilateral primary sensorimotor areas and supplementary motor areas for all patients, indicating the feasibility of this technique in eloquent area localization. The reliability of ai-fMRI was further validated using intraoperative stimulation mapping (ISM) in two of the seven patients. Comparisons between the pre-fMRI-derived localization result and the ai-fMRI derived result showed that the former was subject to a heavy brain shift and led to incorrect localization, while the latter solved that problem. Additionally, the approaches for the acquisition and processing of the ai-fMRI data were fully illustrated and described. Some practical issues on employing ai-fMRI in awake craniotomy were systemically discussed, and guidelines were provided.

Metabolic approach for tumor delineation in glioma surgery: 3D MR spectroscopy image–guided resection

OBJECT The extent of resection is one of the most essential factors that influence the outcomes of glioma resection. However, conventional structural imaging has failed to accurately delineate glioma margins because of tumor cell infiltration. Three-dimensional proton MR spectroscopy ((1)H-MRS) can provide metabolic information and has been used in preoperative tumor differentiation, grading, and radiotherapy planning. Resection based on glioma metabolism information may provide for a more extensive resection and yield better outcomes for glioma patients. In this study, the authors attempt to integrate 3D (1)H-MRS into neuronavigation and assess the feasibility and validity of metabolically based glioma resection. METHODS Choline (Cho)-N-acetylaspartate (NAA) index (CNI) maps were calculated and integrated into neuronavigation. The CNI thresholds were quantitatively analyzed and compared with structural MRI studies. Glioma resections were performed under 3D (1)H-MRS guidance. Volumetric analyses were performed for metabolic and structural images from a low-grade glioma (LGG) group and high-grade glioma (HGG) group. Magnetic resonance imaging and neurological assessments were performed immediately after surgery and 1 year after tumor resection. RESULTS Fifteen eligible patients with primary cerebral gliomas were included in this study. Three-dimensional (1)H-MRS maps were successfully coregistered with structural images and integrated into navigational system. Volumetric analyses showed that the differences between the metabolic volumes with different CNI thresholds were statistically significant (p < 0.05). For the LGG group, the differences between the structural and the metabolic volumes with CNI thresholds of 0.5 and 1.5 were statistically significant (p = 0.0005 and 0.0129, respectively). For the HGG group, the differences between the structural and metabolic volumes with CNI thresholds of 0.5 and 1.0 were statistically significant (p = 0.0027 and 0.0497, respectively). All patients showed no tumor progression at the 1-year follow-up. CONCLUSIONS This study integrated 3D MRS maps and intraoperative navigation for glioma margin delineation. Optimum CNI thresholds were applied for both LGGs and HGGs to achieve resection. The results indicated that 3D (1)H-MRS can be integrated with structural imaging to provide better outcomes for glioma resection.

A point based non-rigid registration for tumor resection using iMRI

This paper presents a novel feature point based non-rigid registration of preoperative MRI with resected intra-operative MRI (iMRI) to compensate for brain shift during tumor resection.

An ITK implementation of a physics-based non-rigid registration method for brain deformation in image-guided neurosurgery

As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, for the non-rigid registration of brain MRIs, the performance of the block matching filter on average is about 10 times faster when 12 hyperthreaded multi-cores are used and about 83 times faster when the NVIDIA Tesla GPU is used in Dell Workstation.

Alteration of the Intra- and Cross- Hemisphere Posterior Default Mode Network in Frontal Lobe Glioma Patients.

Patients with frontal lobe gliomas often experience neurocognitive dysfunctions before surgery, which affects the default mode network (DMN) to different degrees. This study quantitatively analyzed this effect from the perspective of cerebral hemispheric functional connectivity (FC). We collected resting-state fMRI data from 20 frontal lobe glioma patients before treatment and 20 healthy controls. All of the patients and controls were right-handed. After pre-processing the images, FC maps were built from the seed defined in the left or right posterior cingulate cortex (PCC) to the target regions determined in the left or right temporal-parietal junction (TPJ), respectively. The intra- and cross-group statistical calculations of FC strength were compared. The conclusions were as follows: (1) the intra-hemisphere FC strength values between the PCC and TPJ on the left and right were decreased in patients compared with controls; and (2) the correlation coefficients between the FC pairs in the patients were increased compared with the corresponding controls. When all of the patients were grouped by their tumor’s hemispheric location, (3) the FC of the subgroups showed that the dominant hemisphere was vulnerable to glioma, and (4) the FC in the dominant hemisphere showed a significant correlation with WHO grade.