Visual field deficits (VFDs) are common in patients with temporal and occipital lobe lesions. Diffusion tensor fiber tractography (DTI-FT) is widely used for surgery planning to reduce VFDs. Q-ball high-resolution fiber tractography (QBI-HRFT) improves upon DTI. This study aims to evaluate the effectiveness of DTI-FT and QBI-HRFT for surgery planning near the optic radiation (OR) as well as the correlation between VFDs, the nearest distance from the lesion to the OR fiber bundle (nD-LOR), and the lesion volume (LV). This ongoing prospective clinical trial collects clinical and imaging data of patients with lesions in deterrent areas. The present subanalysis included eight patients with gliomas near the OR. Probabilistic HRFT based on QBI-FT and conventional DTI-FT were performed for OR reconstruction based on a standard diffusion-weighted magnetic resonance imaging sequence in clinical use. Quantitative analysis was used to evaluate the lesion volume (LV) and nD-LOR. VFDs were determined based on standardized automated perimetry. We included eight patients (mean age 51.7 years [standard deviation (SD) 9.5]) with lesions near the OR. Among them, five, two, and one patients had temporodorsal, occipital, and temporal lesions, respectively. Four patients had normal vision preoperatively, while four patients had preexisting VFD. QBI-FT analysis indicated that patients with VFD exhibited a significantly smaller median nD-LOR (mean, −4.5; range −7.0; −2.3) than patients without VFD (mean, 7.4; range −4.3; 27.2) (p = 0.050). There was a trend towards a correlation between tumor volume and nD-LOR when QBI-FT was used (rs = −0.6; p = 0.056). A meticulous classification of the spatial relationship between the lesions and OR according to DTI-FT and QBI-FT was performed. The results indicated that the most prevalent orientations were the FT bundles located laterally and intrinsically in relation to the tumor. Compared with conventional DTI-FT, QBI-FT suggests reliable and more accurate results when correlated to preoperative VFDs and might be preferred for preoperative planning and intraoperative use of nearby lesions, particularly for those with larger volumes. A detailed analysis of localization, surgical approach together with QBI-FT and DTI-FT could reduce postoperative morbidity regarding VFDs. The display of HRFT techniques intraoperatively within the navigation system should be pursued for this issue.

Accurately identifying white matter tracts in medical images is essential for various applications, including surgery planning and tract-specific analysis. Supervised machine learning models have reached state-of-the-art solving this task automatically. However, these models are primarily trained on healthy subjects and struggle with strong anatomical aberrations, e.g. caused by brain tumors. This limitation makes them unsuitable for tasks such as preoperative planning, wherefore time-consuming and challenging manual delineation of the target tract is typically employed. We propose semi-automatic entropy-based active learning for quick and intuitive segmentation of white matter tracts from whole-brain tractography consisting of millions of streamlines. The method is evaluated on 21 openly available healthy subjects from the Human Connectome Project and an internal dataset of ten neurosurgical cases. With only a few annotations, the proposed approach enables segmenting tracts on tumor cases comparable to healthy subjects (dice=0.71), while the performance of automatic methods, like TractSeg dropped substantially (dice=0.34) in comparison to healthy subjects. The method is implemented as a prototype named atTRACTive in the freely available software MITK Diffusion. Manual experiments on tumor data showed higher efficiency due to lower segmentation times compared to traditional ROI-based segmentation.

Introduction: After resection of eloquent gliomas, impacting motor pathways, patients frequently harbour pronounced motor deficits (MD), predominantly attributed to damage to the corticospinal tract (CST). Research question: This study compares the results of conventional DTI-FT and q-ball (QBI)-high resolution FT with patient's postoperative morbidity, relating postoperative MD with the nearest distance from the lesion to the CST (nD-LCST). Materials and methods: In this ongoing prospective trial, we utilized probabilistic High-Resolution Fiber Tracking (HRFT) through q-ball imaging (QBI-FT) and conventional Diffusion Tensor Imaging Fiber Tracking (DTI-FT), based on equal and standard diffusion-weighted MRI. Our analysis focused on the normalized Distance from the lesion to the CST-FT (nD-LCST), compared with MD evaluated via standardized clinical examination. Results: Post-surgery, 4 patients developed new MD or deteriorated respectively. Among these, one patient was diagnosed with glioblastoma, one with diffuse astrocytoma, one with anaplastic astrocytoma, and one with oligodendroglioma. QBI-FT analysis revealed that patients with MD had a significantly lower median nD-LCST (-0.4 IQR = 2.1), in contrast to those without MD (8.4 IQR = 3.9; p = 0.029). Median values of QBI-FT were located within the tumor outlines, when MD deteriorated. Patients with postoperatively impaired MD had larger tumor volumes compared to those without MD. Discussion and conclusion: Our preliminary findings suggest that QBI-FT may offer advantages over DTI-FT in predicting postoperative motor deficits, potentially enhancing neurosurgical planning. However, due to the small sample size of our study, these results are exploratory, and further research with larger patient populations is necessary to confirm the benefits of QBI-FT. QBI-FT shows promise as a complementary tractography technique suitable for clinical purposes alongside standard DTI-FT.

Fiber tracking (FT) is used in neurosurgical planning for the resection of lesions in proximity to fiber pathways, as it contributes to a substantial amelioration of postoperative neurological impairments. Currently, diffusion-tensor imaging (DTI)-based FT is the most frequently used technique; however, sophisticated techniques such as Q-ball (QBI) for high-resolution FT (HRFT) have suggested favorable results. Little is known about the reproducibility of both techniques in the clinical setting. Therefore, this study aimed to examine the intra- and interrater agreement for the depiction of white matter pathways such as the corticospinal tract (CST) and the optic radiation (OR). Nineteen patients with eloquent lesions in the proximity of the OR or CST were prospectively enrolled. Two different raters independently reconstructed the fiber bundles by applying probabilistic DTI- and QBI-FT. Interrater agreement was evaluated from the comparison between results obtained by the two raters on the same data set acquired in two independent iterations at different timepoints using the Dice Similarity Coefficient (DSC) and the Jaccard Coefficient (JC). Likewise, intrarater agreement was determined for each rater comparing individual results. DSC values showed substantial intrarater agreement based on DTI-FT (rater 1: mean 0.77 (0.68–0.85); rater 2: mean 0.75 (0.64–0.81); p = 0.673); while an excellent agreement was observed after the deployment of QBI-based FT (rater 1: mean 0.86 (0.78–0.98); rater 2: mean 0.80 (0.72–0.91); p = 0.693). In contrast, fair agreement was observed between both measures for the repeatability of the OR of each rater based on DTI-FT (rater 1: mean 0.36 (0.26–0.77); rater 2: mean 0.40 (0.27–0.79), p = 0.546). A substantial agreement between the measures was noted by applying QBI-FT (rater 1: mean 0.67 (0.44–0.78); rater 2: mean 0.62 (0.32–0.70), 0.665). The interrater agreement was moderate for the reproducibility of the CST and OR for both DSC and JC based on DTI-FT (DSC and JC ≥ 0.40); while a substantial interrater agreement was noted for DSC after applying QBI-based FT for the delineation of both fiber tracts (DSC > 0.6). Our findings suggest that QBI-based FT might be a more robust tool for the visualization of the OR and CST adjacent to intracerebral lesions compared with the common standard DTI-FT. For neurosurgical planning during the daily workflow, QBI appears to be feasible and less operator-dependent.

This series sought to evaluate the role of intraoperative MRI (iMRI) for resection of functional pituitary adenomas (FPAs). We retrospectively reviewed clinical data of 114 consecutive FPAs with excessive hormone secretion treated with transsphenoidal surgery and iMRI during 01/2010-12/2017. We focused on iMRI findings, extend of resection and postoperative hormonal remission. Variables of incomplete resections and persistent hormone excess were evaluated by binary regression. Patients with FPAs presented with hypercortisolism (n = 23, 20%), acromegaly (n = 56, 49%), and as prolactinomas (n = 35, 31%) resistant to medical treatment. Preoperative MRI showed 81 macroadenomas (71%) and optic system involvement in 41 cases (36%). IMRI was suggestive for residual tumor in 51 cases (45%). Re-inspection of the cavity cleared equivocal findings in 16 cases (14%). Additional tumor was removed in 22 cases (19%). Complete resection was achieved in 95 cases (83%). Postoperative morbidity was low (1.7% revision surgeries, 0.8% permanent diabetes insipidus). Overall hormonal remission-rate was 59% (hypercortisolism 78%, acromegaly 52%, prolactinoma 57%). Supra- and parasellar invasion and preoperative visual impairment were significant predictors for incomplete resections despite use of iMRI. Risk for persistent hormone excess was increased sevenfold after incomplete resections. IMRI enabled reliable identification of tumor remnants during surgery and triggered further resection in a considerable proportion of cases. Nevertheless, tumor size and invasiveness set persistent boundaries to the completeness of resections. The low rate of surgical complications could point at a less invasive iMRI-guided surgical approach while achieving a complete tumor resection was a crucial determinant for hormonal outcome.

OBJECTIVE:Fiber tractography (FT) has become an important noninvasive tool to ensure maximal safe tumor resection in eloquent glioma surgery. Intraoperatively applied FT is still predominantly based on diffusion tensor imaging (DTI). However, reconstruction schemes of high angular resolution diffusion imaging data for high-resolution FT (HRFT) are gaining increasing attention. The aim of this prospective study was to compare the accuracy of sophisticated HRFT models compared with DTI-FT. METHODS:Ten patients with eloquent gliomas underwent surgery under awake craniotomy conditions. The localization of acquisition points, representing deteriorations during intraoperative electrostimulation (IOM) and neuropsychological mapping, were documented. The offsets of acquisition points to the respective fiber bundle were calculated. Probabilistic Q-ball imaging (QBI) and constrained spherical deconvolution (CSD)-FT were compared with DTI-FT for the major language-associated fiber bundles (superior longitudinal fasciculus [SLF] II-IV, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus/medial longitudinal fasciculus). RESULTS:Among 186 offset values, 46% were located closer than 10 mm to the estimated fiber bundle (CSD, 36%; DTI, 40% and QBI, 60%). Moreover, only 10 offsets were further away than 30 mm (5%). Lowest mean minimum offsets (SLF, 7.7 ± 7.9 mm; inferior fronto-occipital fasciculus, 12.7 ± 8.3 mm; inferior longitudinal fasciculus/medial longitudinal fasciculus, 17.7 ± 6.7 mm) were found for QBI, indicating a significant advantage compared with CSD or DTI (P < 0.001), respectively. No significant differences were found between CSD-FT and DTI-FT offsets (P = 0.105), albeit for the compound SLF exclusively (P < 0.001). CONCLUSIONS:Comparing HRFT techniques QBI and CSD with DTI, QBI delivered significantly better results with lowest offsets and good correlation to IOM results. Besides, QBI-FT was feasible for neurosurgical preoperative and intraoperative applications. Our findings suggest that a combined approach of QBI-FT and IOM under awake craniotomy is considerable for best preservation of neurological function in the presented setting. Overall, the implementation of selected HRFT models into neuronavigation systems seems to be a promising tool in glioma surgery.

BACKGROUND To date, fiber tractography (FT) is predominantly based on Diffusion Tensor Imaging (DTI). High angular resolution diffusion imaging (HARDI)-based reconstructions have become a focus of interest, enabling the resolution of intravoxel fiber crossing. However, experience with high resolution tractography (HRFT) for neurosurgical applications is still limited to a few reports. This prospectively designed feasibility study shares our initial experience using an analytical q-ball approach (QBI) for FT of language-associated pathways in comparison with DTI-FT, focussing on a quantitative analysis and evaluation of its applicability in clinical routine. METHODS Probabilistic QBI-, and DTI-FT were performed for the major components of the language-associated fiber bundles (superior longitudinal fasciculus, inferior fronto-occipital fasciculus, medial/inferior longitudinal faciculus) in 11 patients with eloquent gliomas. The data was derived from a routine DWI sequence (b=1000s/mm2, 64 gradient directions). Quantitative analysis evaluated tract volume (TV), tract length (TL) and tract density (TD). Results were correlated to tumor and edema size. RESULTS Quantitative analysis showed larger TV and TL of the overall fiber object using QBI-FT compared with DTI-FT (TV: 16.45 ± 1.85 vs. 10.07 ± 1.15cm3; p<0.0001; TL:81.95 ± 6.14 vs. 72.06 ± 6.92 mm; p=0.0011). Regarding overall TD, DTI delivered significantly higher values (40.57 ± 6.59 vs. 60.98 ± 15.94 points/voxel; p=0.0118). Bland-Altman analysis illustrated a systematic advantage to yield lager TV and TL via QBI compared with DTI for all reconstructed pathways. The results were independent of tumor or edema volume. CONCLUSIONS QBI proved to be suitable for an application in the neurosurgical setting without additional expense for the patient. Quantitative analysis of FT reveals larger overall TV, longer TL with lower TD using QBI compared with DTI, suggesting the better depiction of marginal and terminal fibers according to neuroanatomical knowledge. This emphasizes the known limitation of DTI to underestimate the dimensions of a pathway. Rather than relying on DTI, sophisticated HRFT techniques should be considered for preoperative planning and intraoperative guidance in selected cases of eloquent glioma surgery.

OBJECTIVE:As a result of the resolution of intravoxel fiber crossing, high-resolution fiber tractography (HRFT) provides advantages over conventional diffusion tensor imaging (DTI) for fiber tractography (FT). Nevertheless, neurosurgically applied FT is still predominantly based on DTI. Although the application of HRFT is evolving, there is still a lack of data about which method should be preferred. With this prospectively designed study, we present our initial experience comparing an analytical Q-ball imaging (QBI) approach with constrained spherical deconvolution (CSD) and conventional DTI-FT considering a particularly neurosurgical perspective. METHODS:For 18 patients with eloquent gliomas in the dominant hemisphere, probabilistic FT based on QBI, CSD, and DTI was performed for the major components of the language-associated pathways using a routine diffusion-weighted sequence. Quantitative analysis evaluated tract density, tract volume (TV), tract length (TL), number of fibers, and tract surface (TS) of the fiber object. RESULTS:Both HRFT models showed a significantly larger mean TV, TL, and TS compared with DTI (for QBI vs. DTI: TV (P = 0.0000), TL (P = 0.0048), and TS (P = 0.0129); for CSD vs. DTI: TV (P = 0.0000), TL (P = 0.0008), and TS (P = 0.0010)). However, results of QBI versus CSD did not differ significantly for these variables: TV (P = 0.1415), TL (P = 0.2837), and TS (P = 0.3692). Bland-Altman analysis supports these findings, suggesting systematically higher values for TV, TL, and TS with HRFT but no relevant differences of either QBI or CSD. Neither tumor volume nor peritumoral edema influenced FT results. CONCLUSIONS:Our quantitative analysis showed no significant differences regarding TV, TL, and TS for the HRFT methods; however, it suggested advantages over DTI-FT in terms of the display of marginal and terminal fibers. In our recently established setting, QBI-FT shows greater potential for integration into the clinical workflow.

Motivation: Accurate tractography-based segmentation of white matter tracts is crucial for tasks such as pre-surgical planning. Fully automated methods are limited to predefined tracts and struggle with anatomical deviations, e.g. caused by tumors. Goal(s): Our goal is to enhance the manual segmentation process through a novel and intuitive approach. Approach: We recently developed atTRACTive, a tool for semi-automatic fiber dissection relying on entropy-based active learning. In this work, we have improved atTRACTive and conducted an initial evaluation of its test-retest reliability in comparison to traditional ROI-based tract segmentation methods. Results: atTRACTive has demonstrated superior test-retest reliability compared to traditional ROI-based segmentation approaches. Impact: The method offers guidance to researchers in the intuitive and efficient segmentation of arbitrary white matter tracts. Instead of drawing challenging-to-reproduce ROIs, users can simply annotate meaningful streamlines, which are then used to train a classifier.