Children born very prematurely (≤32 weeks) often exhibit visual-perceptual difficulties at school-age, even in the absence of major neurological impairment. The alterations in functional brain activity that give rise to such problems, as well as the relationship between adverse neonatal experience and neurodevelopment, remain poorly understood. Repeated procedural pain-related stress during neonatal intensive care has been proposed to contribute to altered neurocognitive development in these children. Due to critical periods in the development of thalamocortical systems, the immature brain of infants born at extremely low gestational age (ELGA; ≤28 weeks) may have heightened vulnerability to neonatal pain. In a cohort of school-age children followed since birth we assessed relations between functional brain activity measured using magnetoencephalogragy (MEG), visual-perceptual abilities and cumulative neonatal pain. We demonstrated alterations in the spectral structure of spontaneous cortical oscillatory activity in ELGA children at school-age. Cumulative neonatal pain-related stress was associated with changes in background cortical rhythmicity in these children, and these alterations in spontaneous brain oscillations were negatively correlated with visual-perceptual abilities at school-age, and were not driven by potentially confounding neonatal variables. These findings provide the first evidence linking neonatal painrelated stress, the development of functional brain activity, and school-age cognitive outcome in these vulnerable children.

A noise-tolerant approach to strain estimation in phase-sensitive optical coherence elastography, robust to decorrelation distortions, is discussed. The method is based on evaluation of interframe phase-variation gradient, but its main feature is that the phase is singled out at the very last step of the gradient estimation. All intermediate steps operate with complex-valued optical coherence tomography (OCT) signals represented as vectors in the complex plane (hence, we call this approach the 'vector' method). In comparison with such a popular method as least-square fitting of the phase-difference slope over a selected region (even in the improved variant with amplitude weighting for suppressing small-amplitude noisy pixels), the vector approach demonstrates superior tolerance to both additive noise in the receiving system and speckle-decorrelation caused by tissue straining. Another advantage of the vector approach is that it obviates the usual necessity of error-prone phase unwrapping. Here, special attention is paid to modifications of the vector method that make it especially suitable for processing deformations with significant lateral inhomogeneity, which often occur in real situations. The method's advantages are demonstrated using both simulated and real OCT scans obtained during reshaping of a collagenous tissue sample irradiated by an IR laser beam producing complex spatially inhomogeneous deformations.

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Optical coherence tomography (OCT) is a promising method for detecting cancer margins during tumor resection. This study focused on differentiating tumorous from nontumorous tissues in human brain tissues using cross-polarization OCT (CP OCT). The study was performed on fresh ex vivo human brain tissues from 30 patients with high- and low-grade gliomas. Different tissue types that neurosurgeons should clearly distinguish during surgery, such as the cortex, white matter, necrosis and tumorous tissue, were separately analyzed. Based on volumetric CP OCT data, tumorous and normal brain tissue were differentiated using two optical coefficients — attenuation and forward cross-scattering. Compared with white matter, tumorous tissue without necrotic areas had significantly lower optical attenuation and forward cross-scattering values. The presence of particular morphological patterns, such as necrosis and injured myelinated fibers, can lead to dramatic changes in coefficient values and create some difficulties in differentiating between tissues. Color-coded CP OCT maps based on optical coefficients provided a visual assessment of the tissue. This study demonstrated the high translational potential of CP OCT in differentiating tumorous tissue from white matter. The clinical use of CP OCT during surgery in patients with gliomas could increase the extent of tumor resection and improve overall and progression-free survival.

This paper considers valuable visual assessment criteria for distinguishing between tumorous and non-tumorous tissues, intraoperatively, using cross-polarization OCT (CP OCT)—OCT with a functional extension, that enables detection of the polarization properties of the tissues in addition to their conventional light scattering. Materials and Methods: The study was performed on 176 ex vivo human specimens obtained from 30 glioma patients. To measure the degree to which the typical parameters of CP OCT images can be matched to the actual histology, 100 images of tumors and white matter were selected for visual analysis to be undertaken by three “single-blinded” investigators. An evaluation of the inter-rater reliability between the investigators was performed. Application of the identified visual CP OCT criteria for intraoperative use was performed during brain tumor resection in 17 patients. Results: The CP OCT image parameters that can typically be used for visual assessment were separated: (1) signal intensity; (2) homogeneity of intensity; (3) attenuation rate; (4) uniformity of attenuation. The degree of match between the CP OCT images and the histology of the specimens was significant for the parameters “signal intensity” in both polarizations, and “homogeneity of intensity” as well as the “uniformity of attenuation” in co-polarization. A test based on the identified criteria showed a diagnostic accuracy of 87–88%. Intraoperative in vivo CP OCT images of white matter and tumors have similar signals to ex vivo ones, whereas the cortex in vivo is characterized by indicative vertical striations arising from the “shadows” of the blood vessels; these are not seen in ex vivo images or in the case of tumor invasion. Conclusion: Visual assessment of CP OCT images enables tumorous and non-tumorous tissues to be distinguished. The most powerful aspect of CP OCT images that can be used as a criterion for differentiation between tumorous tissue and white matter is the signal intensity. In distinguishing white matter from tumors the diagnostic accuracy using the identified visual CP OCT criteria was 87–88%. As the CP OCT data is easily associated with intraoperative neurophysiological and neuronavigation findings this can provide valuable complementary information for the neurosurgeon tumor resection.