There is an unacceptably high complication rate after reimplantation of the autologous bone following DC in pediatric TBI patients, especially in young children up to seven years of age. Artificial or synthetic cranioplasties may be considered as alternatives to initial bone flap reimplantation in the growing child. Despite the fact that DC is an effective treatment in TBI with persistent intracranial hypertension, it is important to realize that DC is not only combined with replacement of the autologous bone flap but also with a high rate of additional complications especially in pediatric patients.

This study assessed the diagnostic potential of Raman spectroscopic mapping by evaluating its ability to distinguish between normal brain tissue and the human intracranial tumors gliomas and meningeomas. Seven Raman maps of native specimens were collected ex vivo by a Raman spectrometer with 785 nm excitation coupled to a microscope with a motorized stage. Variations within each Raman map were analyzed by cluster analysis. The dependence of tissue composition on the tissue type in cluster averaged Raman spectra was shown by linear combinations of reference spectra. Normal brain tissue was found to contain higher levels of lipids, intracranial tumors have more hemoglobin and lower lipid to protein ratios, meningeomas contain more collagen with maximum collagen content in normal meninges. One sample was studied without freezing. Whereas tumor regions did not change significantly, spectral changes were observed in the hemoglobin component after snap freezing and thawing to room temperature. The results constitute a basis for subsequent Raman studies to develop classification models for diagnosis of brain tissue.

The focus of this paper is to identify and quantify risk factors for early hemorrhagic progression of brain contusions (HPC) in patients with traumatic brain injury (TBI) and to evaluate their impact on patients' outcome. Further, based on abnormal values in routine blood tests, the role of trauma-induced coagulopathy is analyzed in detail. Therefore, a prospective study of 153 TBI patients was completed at one institution between January 2008 and June 2012. The collected data included demographics, initial Glasgow Coma Scale pupillary response, initial and 6 h follow-up computed tomography scan findings, coagulation parameters (international normalized ratio, partial thromboplastin time, platelet count, fibrinogen, D-dimer and factor XIII), as well as outcome data using the modified Rankin score at discharge and after one year. The overall rate of early HPC within the first 6 h was 43.5%. The frequency of coagulopathy was 47.1%. When analyzing for risk factors that independently influenced outcome in the form of mRS ≥4 at both points, the following variables appeared: elevated D-dimer level (≥10,000 μg/L), HPC, and initial brain contusions ≥3 cm. Patients sustaining early HPC had a hazard ratio of 5.4 for unfavorable outcome at discharge (p=0.002) and of 3.9 after one year (p=0.006). Overall, patients who developed early HPC were significantly more likely to be gravely disabled or to die. Unfavorable neurological outcome after an isolated TBI is determined largely by early HPC and coagulopathy, which seem to occur very frequently in TBI patients, irrespective of the severity of the trauma.

Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm2 tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis.

Intracranial tumors are neoplasias of brain tissue or other tissue inside the skull. Cryosections of the three most frequent primary intracranial tumors -gliomas, meningeomas and schwannomas -were prepared on calcium fluoride windows and studied by both Raman spectroscopy and infrared (IR) spectroscopy. Spectroscopic maps were recorded by sequential acquisition of spectra in a raster pattern. Cluster analyses on selected wavenumber regions were applied for evaluation of these data sets. Raman spectroscopic contributions of proteins including collagen and hemoglobin were identified in cluster centroids, as were nucleic acids and lipids including cholesterol, cholesterol ester (CE) and phosphatidylcholine (PC). Moreover, hydroxyapatite and tricalciumphosphate could be identified as markers for calcification. The spatial distributions of these spectral properties were visualized in pseudocolor Raman and IR maps representing the cluster memberships. The prospects of both methods are discussed.