The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

A g-factor metric for k-t-GRAPPA- and PEAK-GRAPPA-based parallel imaging.

PURPOSE The aim of this work is to derive a theoretical framework for quantitative noise and temporal fidelity analysis of time-resolved k-space-based parallel imaging methods. THEORY An analytical formalism of noise distribution is derived extending the existing g-factor formulation for nontime-resolved generalized autocalibrating partially parallel acquisition (GRAPPA) to time-resolved k-space-based methods. The noise analysis considers temporal noise correlations and is further accompanied by a temporal filtering analysis. METHODS All methods are derived and presented for k-t-GRAPPA and PEAK-GRAPPA. A sliding window reconstruction and nontime-resolved GRAPPA are taken as a reference. Statistical validation is based on series of pseudoreplica images. The analysis is demonstrated on a short-axis cardiac CINE dataset. RESULTS The superior signal-to-noise performance of time-resolved over nontime-resolved parallel imaging methods at the expense of temporal frequency filtering is analytically confirmed. Further, different temporal frequency filter characteristics of k-t-GRAPPA, PEAK-GRAPPA, and sliding window are revealed. CONCLUSION The proposed analysis of noise behavior and temporal fidelity establishes a theoretical basis for a quantitative evaluation of time-resolved reconstruction methods. Therefore, the presented theory allows for comparison between time-resolved parallel imaging methods and also nontime-resolved methods. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Endovascular Treatment of Acute Stroke: Evolution and Selection of Techniques and Instruments Based on Thrombus Imaging.

Mechanical thrombectomy provides higher recanalization rates than intravenous or intra-arterial thrombolysis. Finally this has been shown to translate into improved clinical outcome in six multicentric randomized controlled trials. However, within cohorts the clinical outcomes may vary, depending on the endovascular techniques applied. Systems aiming mainly for thrombus fragmentation and lacking a protection against distal embolization have shown disappointing results when compared to recent stent-retriever studies or even to historical data on local arterial fibrinolysis. Procedure-related embolic events are usually graded as adverse events in interventional neuroradiology. In stroke, however, the clinical consequences of secondary emboli have so far mostly been neglected and attributed to progression of the stroke itself. We summarize the evolution of instruments and techniques for endovascular, image-guided, microneurosurgical recanalization in acute stroke, and discuss how to avoid procedure-related embolic complications.

Indocyanine Green Fluorescence Imaging in the Surgical Management of an Iatrogenic Lymphatic Fistula: Description of a Surgical Technique

We present a case of laparoscopic surgical management of an iatrogenic lymphorrhea using indocyanine green (ICG). A case of a patient who developed recurrent symptomatic lymphorrhea after laparoscopic radical hysterectomy and bilateral pelvic lymphadenectomy for an early stage cervical cancer is presented. Intraoperative bipedal interdigital subcutaneous injection of ICG exactly localized the disrupted lymphatic duct on fluorescence imaging performed with a near-infrared laparoscopic fluorescent optic device, thus allowing a successful surgical repair.

A Comparison of Radiocolloid and Indocyanine Green Fluorescence Imaging, Sentinel Lymph Node Mapping in Patients with Cervical Cancer Undergoing Laparoscopic Surgery.

BACKGROUND AND PURPOSE (99)TC combined with blue-dye mapping is considered the best sentinel lymph node (SLN) mapping technique in cervical cancer. Indocyanine green (ICG) with near infrared fluorescence imaging has been introduced as a new methodology for SLN mapping. The aim of this study was to compare these two techniques in the laparoscopic treatment of cervical cancer. METHODS Medical records of patients undergoing laparoscopic SLN mapping for cervical cancer with either (99)Tc and patent blue dye (Group 1) or ICG (Group 2) from April 2008 until August 2012 were reviewed. Sensitivity, specificity, and overall and bilateral detection rates were calculated and compared. RESULTS Fifty-eight patients were included in the study-36 patients in Group 1 and 22 patients in Group 2. Median tumor diameter was 25 and 29 mm, and mean SLN count was 2.1 and 3.7, for Groups 1 and 2, respectively. Mean non-SLN (NSLN) count was 39 for both groups. SLNs were ninefold more likely to be affected by metastatic disease compared with NSLNs (p < 0.005). Sensitivity and specificity were both 100 %. Overall detection rates were 83 and 95.5 % (p = nonsignificant), and bilateral detection rates were 61 and 95.5 % (p < 0.005), for Groups 1 and 2, respectively. In 75 % of cases, SLNs were located along the external or internal iliac nodal basins. CONCLUSIONS ICG SLN mapping in cervical cancer provides high overall and bilateral detection rates that compare favorably with the current standard of care.

Sentinel node mapping using hysteroscopic injection of indocyanine green and laparoscopic near-infrared fluorescence imaging in endometrial cancer staging.

Herein is presented a technique for minimally invasive sentinel node mapping. The patient had apparently early stage endometrial cancer. Sentinel node mapping was performed using a hysteroscopic injection of indocyanine green followed by laparoscopic sentinel node detection via near-infrared fluorescence. This technique ensures delineation of lymphatic drainage from the tumor area, thus achieving accurate detection of sentinel nodes.