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BACKGROUND AND PURPOSE Diffusion magnetic resonance imaging (dMRI) provides preoperative maps of neurosurgical patients’ white matter tracts, but these maps suffer from echo-planar imaging (EPI) distortions caused by magnetic field inhomogeneities. In clinical neurosurgical planning, these distortions are generally not corrected and thus contribute to the uncertainty of fiber tracking. Multiple image processing pipelines have been proposed for image-registration-based EPI distortion correction in healthy subjects. In this article, we perform the first comparison of such pipelines in neurosurgical patient data. METHODS Five pipelines were tested in a retrospective clinical dMRI dataset of 9 patients with brain tumors. Pipelines differed in the choice of fixed and moving images and the similarity metric for image registration. Distortions were measured in two important tracts for neurosurgery, the arcuate fasciculus and corticospinal tracts. RESULTS Significant differences in distortion estimates were found across processing pipelines. The most successful pipeline used dMRI baseline and T2-weighted images as inputs for distortion correction. This pipeline gave the most consistent distortion estimates across image resolutions and brain hemispheres. CONCLUSIONS Quantitative results of mean tract distortions on the order of 1–2 mm are in line with other recent studies, supporting the potential need for distortion correction in neurosurgical planning. Novel results include significantly higher distortion estimates in the tumor hemisphere and greater effect of image resolution choice on results in the tumor hemisphere. Overall, this study demonstrates possible pitfalls and indicates that care should be taken when implementing EPI distortion correction in clinical settings.

Contrast-enhanced MR images are widely used to confirm the adequacy of ablation margin after liver ablation for early prediction of local recurrence. However, quantitative assessment of the ablation margin by comparing pre- and post-procedural images remains challenging. We developed and tested a novel method for three-dimensional quantitative assessment of ablation margin based on non-rigid image registration and 3D distance map.Our method was tested with pre- and post-procedural MR images acquired in 21 patients who underwent image-guided percutaneous liver ablation. The two images were co-registered using non-rigid intensity-based registration. After the tumor and ablation volumes were segmented, target volume coverage, percent of tumor coverage, and Dice similarity coefficient were calculated as metrics representing overall adequacy of ablation. In addition, 3D distance map around the tumor was computed and superimposed on the ablation volume to identify the area with insufficient margins. For patients with local recurrences, the follow-up images were registered to the post-procedural image. Three-dimensional minimum distance between the recurrence and the areas with insufficient margins was quantified.The percent tumor coverage for all nonrecurrent cases was 100 %. Five cases had tumor recurrences, and the 3D distance map revealed insufficient tumor coverage or a 0-mm margin. It also showed that two recurrences were remote to the insufficient margin.Non-rigid registration and 3D distance map allow us to quantitatively evaluate the adequacy of the ablation margin after percutaneous liver ablation. The method may be useful to predict local recurrences immediately following ablation procedure.

Purpose: Image-guided cryotherapy of renal cancer is an emerging alternative to surgical nephrectomy, particularly for those who cannot sustain the physical burden of surgery. It is well known that the outcome of this therapy depends on the accurate placement of the cryotherapy probe. Therefore, a robotic instrument guide may help physicians aim the cryotherapy probe precisely to maximize the efficacy of the treatment and avoid damage to critical surrounding structures. The objective of this paper was to propose a robotic instrument guide for orienting cryotherapy probes in image-guided cryotherapy of renal cancers. The authors propose a body-mounted robotic guide that is expected to be less susceptible to guidance errors caused by the patient’s whole body motion. Methods: Keeping the device’s minimal footprint in mind, the authors developed and validated a body-mounted, robotic instrument guide that can maintain the geometrical relationship between the device and the patient’s body, even in the presence of the patient’s frequent body motions. The guide can orient the cryotherapy probe with the skin incision point as the remote-center-of-motion. The authors’ validation studies included an evaluation of the mechanical accuracy and position repeatability of the robotic instrument guide. The authors also performed a mock MRI-guided cryotherapy procedure with a phantom to compare the advantage of robotically assisted probe replacements over a free-hand approach, by introducing organmotions to investigate their effects on the accurate placement of the cryotherapy probe. Measurements collected for performance analysis included accuracy and time taken for probe placements. Multivariate analysis was performed to assess if either or both organmotion and the robotic guide impacted these measurements. Results: The mechanical accuracy and position repeatability of the probe placement using the robotic instrument guide were 0.3 and 0.1 mm, respectively, at a depth of 80 mm. The phantom test indicated that the accuracy of probe placement was significantly better with the robotic instrument guide (4.1 mm) than without the guide (6.3 mm, p

The aim of this study was to present a tractography algorithm using a two-tensor unscented Kalman filter (UKF) to improve the modeling of the corticospinal tract (CST) by tracking through regions of peritumoral edema and crossing fibers. Ten patients with brain tumors in the vicinity of motor cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-T magnetic resonance imaging (MRI) including functional MRI (fMRI) and a diffusion-weighted data set with 31 directions. Fiber tracking was performed using both single-tensor streamline and two-tensor UKF tractography methods. A two-region-of-interest approach was used to delineate the CST. Results from the two tractography methods were compared visually and quantitatively. fMRI was applied to identify the functional fiber tracts. Single-tensor streamline tractography underestimated the extent of tracts running through the edematous areas and could only track the medial projections of the CST. In contrast, two-tensor UKF tractography tracked fanning projections of the CST despite peritumoral edema and crossing fibers. Based on visual inspection, the two-tensor UKF tractography delineated tracts that were closer to motor fMRI activations, and it was apparently more sensitive than single-tensor streamline tractography to define the tracts directed to the motor sites. The volume of the CST was significantly larger on two-tensor UKF than on single-tensor streamline tractography ( $$p < 0.001$$ ). Two-tensor UKF tractography tracks a larger volume CST than single-tensor streamline tractography in the setting of peritumoral edema and crossing fibers in brain tumor patients.

Intraoperative magnetic resonance imaging (IoMRI) was devised to overcome brain shifts during craniotomies. Yet, the acceptance of IoMRI is limited.To evaluate impact of IoMRI on intracranial glioma resection outcome including overall patient survival.A retrospective review of records was performed on a cohort of 164 consecutive patients who underwent resection surgery for newly diagnosed intracranial gliomas either with or without IoMRI technology performed by 2 neurosurgeons in our center. Patient follow-up was at least 5 years. Extent of resection (EOR) was calculated using pre- and postoperative contrast-enhanced and T2-weighted MR-images. Adjusted analysis was performed to compare gross total resection (GTR), EOR, permanent surgery-associated neurologic deficit, and overall survival between the 2 groups.Overall median EOR was 92.1%, and 97.45% with IoMRI use and 89.9% without IoMRI, with crude (unadjusted) P0.005. GTR was achieved in 49.3% of IoMRI cases, versus in only 21.4% of no-IoMRI cases, P0.001. GTR achieved was more with the use of IoMRI among gliomas located in both eloquent and noneloquent brain areas, P = 0.017 and0.001, respectively. Permanent surgery-associated neurologic deficit was not (statistically) more significant with no-IoMRI, P = 0.284 (13.8% vs. 6.7%). In addition, the IoMRI group had better 5-year overall survival, P0.001.This study shows that the use of IoMRI was associated with greater rates of EOR and GTR, and better overall 5-year survival in both eloquent brain areas located and non-eloquent brain areas located gliomas, with no increased risk of neurologic complication.

Background To achieve maximal resection with minimal risk of postoperative neurologic morbidity, different neurosurgical adjuncts are being used during low-grade glioma (LGG) surgery. Objectives To investigate the effect of pre- and intraoperative adjuncts on the extent of resection (EOR) of hemispheric LGGs. Methods Medical records were reviewed to identify patients of any sex, ≥ 18 years of age, who underwent LGG surgery at X Hospital between January 2005 and July 2013. Patients were divided into eight subgroups based on the use of various combinations of a neuronavigation system alone (NN), functional MRI-diffusion tensor imaging (fMRI-DTI) guided neuronavigation (FD), intraoperative MRI (MR), and direct electrical stimulation (DES). Initial and residual tumors were measured, and mean EOR was compared between groups. Results Of all 128 patients, gross total resection was achieved in 23.4%. Overall mean EOR was 81.3% ± 20.5%. Using DES in combination with fMRI-DTI (mean EOR: 86.7% ± 12.4%) on eloquent tumors improved mean EOR significantly after adjustment for potential confounders when compared with NN alone (mean EOR: 76.4% ± 25.5%; p = 0.001). Conclusions Using DES in combination with fMRI and DTI significantly improves EOR when LGGs are located in eloquent areas compared with craniotomies in which only NN was used.

Rationale and Objectives Accuracy and speed are essential for the intraprocedural nonrigid magnetic resonance (MR) to computed tomography (CT) image registration in the assessment of tumor margins during CT-guided liver tumor ablations. Although both accuracy and speed can be improved by limiting the registration to a region of interest (ROI), manual contouring of the ROI prolongs the registration process substantially. To achieve accurate and fast registration without the use of an ROI, we combined a nonrigid registration technique on the basis of volume subdivision with hardware acceleration using a graphics processing unit (GPU). We compared the registration accuracy and processing time of GPU-accelerated volume subdivision–based nonrigid registration technique to the conventional nonrigid B-spline registration technique. Materials and Methods Fourteen image data sets of preprocedural MR and intraprocedural CT images for percutaneous CT-guided liver tumor ablations were obtained. Each set of images was registered using the GPU-accelerated volume subdivision technique and the B-spline technique. Manual contouring of ROI was used only for the B-spline technique. Registration accuracies (Dice similarity coefficient [DSC] and 95% Hausdorff distance [HD]) and total processing time including contouring of ROIs and computation were compared using a paired Student t test. Results Accuracies of the GPU-accelerated registrations and B-spline registrations, respectively, were 88.3 ± 3.7% versus 89.3 ± 4.9% (P = .41) for DSC and 13.1 ± 5.2 versus 11.4 ± 6.3 mm (P = .15) for HD. Total processing time of the GPU-accelerated registration and B-spline registration techniques was 88 ± 14 versus 557 ± 116 seconds (P

BACKGROUND Functional MRI (fMRI) based on language tasks has been used in presurgical language mapping in patients with lesions in or near putative language areas. However, if patients have difficulty performing the tasks due to neurological deficits, it leads to unreliable or noninterpretable results. In this study, we investigate the feasibility of using a movie-watching fMRI for language mapping. METHODS A 7-minute movie clip with contrasting speech and nonspeech segments was shown to 22 right-handed healthy subjects. Based on all subjects’ language functional regions-of-interest, 6 language response areas were defined, within which a language response model (LRM) was derived by extracting the main temporal activation profile. Using a leave-one-out procedure, individuals’ language areas were identified as the areas that expressed highly correlated temporal responses with the LRM derived from an independent group of subjects. RESULTS Compared with an antonym generation task-based fMRI, the movie-watching fMRI generated language maps with more localized activations in the left frontal language area, larger activations in the left temporoparietal language area, and significant activations in their right-hemisphere homologues. Results of 2 brain tumor patients’ movie-watching fMRI using the LRM derived from the healthy subjects indicated its ability to map putative language areas; while their task-based fMRI maps were less robust and noisier. CONCLUSIONS These results suggest that it is feasible to use this novel “task-free” paradigm as a complementary tool for fMRI language mapping when patients cannot perform the tasks. Its deployment in more neurosurgical patients and validation against gold-standard techniques need further investigation.

To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2. We retrospectively identified treatment-naive pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean ADCT, mean ADCN, ADCratio (ADCT/ADCN) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC). Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) ADCT (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) ADCT (0.86) was higher than ADCratio (0.68, p

To determine the accuracy of in-bore transperineal 3-Tesla (T) magnetic resonance (MR) imaging-guided prostate biopsies for predicting final Gleason grades in patients who subsequently underwent radical prostatectomy (RP). A retrospective review of men who underwent transperineal MR imaging-guided prostate biopsy (tpMRGB) with subsequent radical prostatectomy within 1 year was conducted from 2010 to 2015. All patients underwent a baseline 3-T multiparametric MRI (mpMRI) with endorectal coil and were selected for biopsy based on MR findings of a suspicious prostate lesion and high degree of clinical suspicion for cancer. Spearman correlation was performed to assess concordance between tpMRGB and final RP pathology among patients with and without previous transrectal ultrasound (TRUS)-guided biopsies. A total of 24 men met all eligibility requirements, with a median age of 65 years (interquartile range [IQR] 11.7). The median time from biopsy to RP was 85 days (IQR 50.5). Final pathology revealed Gleason 3 + 4 = 7 in 12 patients, 4 + 3 = 7 in 10 patients, and 4 + 4 = 8 in 2 patients. A strong correlation (ρ: +0.75, p

BACKGROUND AND PURPOSE: Diffusion magnetic resonance imaging (dMRI) provides preoperative maps of neurosurgical patients’ white matter tracts, but these maps suffer from echo-planar imaging (EPI) distortions caused by magnetic field inhomogeneities. In clinical neurosurgical planning, these distortions are generally not corrected and thus contribute to the uncertainty of fiber tracking. Multiple image processing pipelines have been proposed for image-registration-based EPI distortion correction in healthy subjects. In this article, we perform the first comparison of such pipelines in neurosurgical patient data. METHODS: Five pipelines were tested in a retrospective clinical dMRI dataset of 9 patients with brain tumors. Pipelines differed in the choice of fixed and moving images and the similarity metric for image registration. Distortions were measured in two important tracts for neurosurgery, the arcuate fasciculus and corticospinal tracts. RESULTS: Significant differences in distortion estimates were found across processing pipelines. The most successful pipeline used dMRI baseline and T2-weighted images as inputs for distortion correction. This pipeline gave the most consistent distortion estimates across image resolutions and brain hemispheres. CONCLUSIONS: Quantitative results of mean tract distortions on the order of 1–2 mm are in line with other recent studies, supporting the potential need for distortion correction in neurosurgical planning. Novel results include significantly higher distortion estimates in the tumor hemisphere and greater effect of image resolution choice on results in the tumor hemisphere. Overall, this study demonstrates possible pitfalls and indicates that care should be taken when implementing EPI distortion correction in clinical settings.

To determine if tumor cell density and percentage of Gleason pattern within an outlined volumetric tumor region of interest (TROI) on whole-mount pathology (WMP) correlate with apparent diffusion coefficient (ADC) values on corresponding TROIs outlined on pre-operative MRI. Men with biopsy-proven prostate adenocarcinoma undergoing multiparametric MRI (mpMRI) prior to prostatectomy were consented to this prospective study. WMP and mpMRI images were viewed using 3D Slicer and each TROI from WMP was contoured on the high b-value ADC maps (b0, 1400). For each TROI outlined on WMP, TCD (tumor cell density) and the percentage of Gleason pattern 3, 4, and 5 were recorded. The ADCmean, ADC10th percentile, ADC90th percentile, and ADCratio were also calculated in each case from the ADC maps using 3D Slicer. Nineteen patients with 21 tumors were included in this study. ADCmean values for TROIs were 944.8 ± 327.4 vs. 1329.9 ± 201.6 mm2/s for adjacent non-neoplastic prostate tissue (p

Purpose To demonstrate the utility of a robotic needle-guidance template device as compared to a manual template for in-bore 3T transperineal magnetic resonance imaging (MRI)-guided prostate biopsy. Materials and Methods This two-arm mixed retrospective-prospective study included 99 cases of targeted transperineal prostate biopsies. The biopsy needles were aimed at suspicious foci noted on multiparametric 3T MRI using manual template (historical control) as compared with a robotic template. The following data were obtained: the accuracy of average and closest needle placement to the focus, histologic yield, percentage of cancer volume in positive core samples, complication rate, and time to complete the procedure. Results In all, 56 cases were performed using the manual template and 43 cases were performed using the robotic template. The mean accuracy of the best needle placement attempt was higher in the robotic group (2.39 mm) than the manual group (3.71 mm, P

We propose a method for the automated identification of key white matter fiber tracts for neurosurgical planning, and we apply the method in a retrospective study of 18 consecutive neurosurgical patients with brain tumors. Our method is designed to be relatively robust to challenges in neurosurgical tractography, which include peritumoral edema, displacement, and mass effect caused by mass lesions. The proposed method has two parts. First, we learn a data-driven white matter parcellation or fiber cluster atlas using groupwise registration and spectral clustering of multi-fiber tractography from healthy controls. Key fiber tract clusters are identified in the atlas. Next, patient-specific fiber tracts are automatically identified using tractography-based registration to the atlas and spectral embedding of patient tractography. Results indicate good generalization of the data-driven atlas to patients: 80% of the 800 fiber clusters were identified in all 18 patients, and 94% of the 800 fiber clusters were found in 16 or more of the 18 patients. Automated subject-specific tract identification was evaluated by quantitative comparison to subject-specific motor and language functional MRI, focusing on the arcuate fasciculus (language) and corticospinal tracts (motor), which were identified in all patients. Results indicate good colocalization: 89 of 95, or 94%, of patient-specific language and motor activations were intersected by the corresponding identified tract. All patient-specific activations were within 3mm of the corresponding language or motor tract. Overall, our results indicate the potential of an automated method for identifying fiber tracts of interest for neurosurgical planning, even in patients with mass lesions., Highlights • Spectral clustering machine learning approach for white matter tract identification • Data-driven white matter parcellation learned from healthy subjects tractography • White matter parcellation applied to 18 consecutive patients with brain tumors • Arcuate fasciculus and corticospinal tracts identified in all patients • All tracts within 3 mm of corresponding patient-specific functional activations

We present a proof of concept study designed to support the clinical development of mass spectrometry imaging (MSI) for the detection of pituitary tumors during surgery. We analyzed by matrix-assisted laser desorption/ionization (MALDI) MSI six nonpathological (NP) human pituitary glands and 45 hormone secreting and nonsecreting (NS) human pituitary adenomas. We show that the distribution of pituitary hormones such as prolactin (PRL), growth hormone (GH), adrenocorticotropic hormone (ACTH), and thyroid stimulating hormone (TSH) in both normal and tumor tissues can be assessed by using this approach. The presence of most of the pituitary hormones was confirmed by using MS/MS and pseudo-MS/MS methods, and subtyping of pituitary adenomas was performed by using principal component analysis (PCA) and support vector machine (SVM). Our proof of concept study demonstrates that MALDI MSI could be used to directly detect excessive hormonal production from functional pituitary adenomas and generally classify pituitary adenomas by using statistical and machine learning analyses. The tissue characterization can be completed in fewer than 30 min and could therefore be applied for the near-real-time detection and delineation of pituitary tumors for intraoperative surgical decision-making.

Functional MRI (fMRI) based on language tasks has been used in presurgical language mapping in patients with lesions in or near putative language areas. However, if patients have difficulty performing the tasks due to neurological deficits, it leads to unreliable or noninterpretable results. In this study, we investigate the feasibility of using a movie-watching fMRI for language mapping.A 7-minute movie clip with contrasting speech and nonspeech segments was shown to 22 right-handed healthy subjects. Based on all subjects' language functional regions-of-interest, 6 language response areas were defined, within which a language response model (LRM) was derived by extracting the main temporal activation profile. Using a leave-one-out procedure, individuals' language areas were identified as the areas that expressed highly correlated temporal responses with the LRM derived from an independent group of subjects.Compared with an antonym generation task-based fMRI, the movie-watching fMRI generated language maps with more localized activations in the left frontal language area, larger activations in the left temporoparietal language area, and significant activations in their right-hemisphere homologues. Results of 2 brain tumor patients' movie-watching fMRI using the LRM derived from the healthy subjects indicated its ability to map putative language areas; while their task-based fMRI maps were less robust and noisier.These results suggest that it is feasible to use this novel "task-free" paradigm as a complementary tool for fMRI language mapping when patients cannot perform the tasks. Its deployment in more neurosurgical patients and validation against gold-standard techniques need further investigation.

INTRODUCTION: Majority of patients with glioblastoma are 65 years and older at the time of diagnosis. There is no standard treatment regimen for this group of elderly patients. The treatment options will include radiation alone, radiation with concomitant and adjuvant temozolomide or temozolomide alone. METHODS: We reviewed the records of 161 GBM patients with age of 70 and above at the time of diagnosis from 2007 until 2014. The demographic information, KPS, type of surgery, MGMT methylation, IDH1 mutation, treatment and overall survival were collected and analyzed. RESULTS: 55% of the patients were males with median age of 76 years (range: 70 - 90) and KPS of 80 (range: 30 - 100). 119 (74%) of patients had surgical resection and 38 (24%) had biopsy only. MGMT methylation status was available in 68% of patients (109/61). MGMT was methylated in 56 (35%) patients and unmethylated in 53 (33%) patients. Majority of patients had no IDH1 mutation. Further treatments included 60 patients (37%) who received radiation 60 Gy with concomitant and adjuvant temozolomide, 29 (18%) were treated with radiation followed by adjuvant temozolomide, 24 (15%) had radiation alone, while 44 (27%) received no further treatment after the surgery. No patient received temozolomide alone. Median overall survival for all patients was 5.45 months. Kaplan-Meier -based analysis showed further treatment after surgery with standard radiation course of 60 Gy with concomitant and adjuvant temozolomide is associated with significantly higher survival (p< 0.001). CONCLUSION: Elderly patients with newly diagnosed glioblastoma may benefit from radiation for 60 Gy with concomitant and adjuvant temozolomide.

BACKGROUND: Diffusion tensor imaging (DTI) tractography enables the graphical reconstruction of the white matter pathways in vivo. The use of this technique to display the key fiber tracts in brain tumor patients for reducing the risk of post-operative neurologic deficit has increased in recent years. However, the effects of peritumoral edema pose a major challenge to the conventional single-tensor streamline fiber tracking method. OBJECTIVE: To present a novel technique using the two-tensor unscented Kalman filter (UKF) algorithm for the tracking of arcuate fasciculus (AF) in brain tumor patients by resolving the effects of peritumoral edema. METHODS: Ten patients with malignant brain tumors in the vicinity of language-related areas underwent 3-T magnetic resonance imaging including a diffusion-weighted data set with 31 gradient directions. DTI data was preprocessed using an automatic quality control pipeline method. Fiber tracking was performed using both single-tensor streamline and two-tensor UKF tractography. A two-regions-of-interest approach was applied to perform delineation of the AF. Results from two different algorithms were compared side-by-side. RESULTS: Single-tensor streamline and two-tensor UKF tractography showed fundamental differences in mapping the fiber tracts in the edema area surrounding the malignant brain tumor. Using single-tensor streamline tractography, 4 of 10 patients showed disrupted and incomplete AF and the remaining six patients demonstrated only a slender fiber bundle. In contrast, the two-tensor UKF tractography could fully delineate the AF within such edematous brain areas in all ten patients. CONCLUSION: The findings suggest that two-tensor UKF tractography provides the ability to trace the AF more accurately than single-tensor streamline tractography particularly in the setting of peritumoral edema in brain tumor patients. UKF tractography may be helpful in the quest to preserve the language function in brain surgery.