The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study

PurposeIn brain tumor surgery, it is crucial to achieve complete tumor resection while conserving adjacent noncancerous brain tissue. Several groups have demonstrated that optical coherence tomography (OCT) has the potential of identifying tumorous brain tissue. However, there is little evidence on human in vivo application of this technology, especially regarding applicability and accuracy of residual tumor detection (RTD). In this study, we execute a systematic analysis of a microscope integrated OCT-system for this purpose.Experimental designMultiple 3-dimensional in vivo OCT-scans were taken at protocol-defined sites at the resection edge in 21 brain tumor patients. The system was evaluated for its intraoperative applicability. Tissue biopsies were obtained at these locations, labeled by a neuropathologist and used as ground truth for further analysis. OCT-scans were visually assessed with a qualitative classifier, optical OCT-properties were obtained and two artificial intelligence (AI)-assisted methods were used for automated scan classification. All approaches were investigated for accuracy of RTD and compared to common techniques.ResultsVisual OCT-scan classification correlated well with histopathological findings. Classification with measured OCT image-properties achieved a balanced accuracy of 85%. A neuronal network approach for scan feature recognition achieved 82% and an auto-encoder approach 85% balanced accuracy. Overall applicability showed need for improvement.ConclusionContactless in vivo OCT scanning has shown to achieve high values of accuracy for RTD, supporting what has well been described for ex vivo OCT brain tumor scanning, complementing current intraoperative techniques and even exceeding them in accuracy, while not yet in applicability

Pressure-induced Pb-Pb bonding and phase transition in Pb2SnO4

High-pressure single-crystal to 20 GPa and powder diffraction measurements to 50 GPa, show that the structure of Pb2SnO4 strongly distorts on compression with an elongation of one axis. A structural phase transition occurs between 10 GPa and 12 GPa, with a change of space group from Pbam to Pnam. The resistivity decreases by more than six orders of magnitude when pressure is increased from ambient conditions to 50 GPa. This insulator-to-semiconductor transition is accompanied by a reversible appearance change from transparent to opaque. Density functional theory-based calculations show that at ambient conditions the channels in the structure host the stereochemically-active Pb 6s2 lone electron pairs. On compression the lone electron pairs form bonds between Pb2+ ions. Also provided is an assignment of irreducible representations to the experimentally observed Raman bands

Structural, elastic and vibrational properties of celestite, SrSO 4 , from synchrotron x-ray diffraction, thermal diffuse scattering and Raman scattering

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Compressibility, microcalorimetry, elastic properties and EELS of rhenium borides

Based on synchrotron X-ray diffraction on phase-pure samples, we revised the bulk moduli of the rhenium borides Re$_7$B$_3$ (B$_0$(Re$_7$B$_3$) = 391(5) GPa) and orthorhombic Re$_3$B (B$_0$ (orthorhombic Re$_3$B) = 393(4) GPa) and determined the bulk modulus of monoclinic Re$_3$B (B$_0$ (monoclinic Re$_3$B) = 390(3) GPa). These results agree well with the DFT calculations on the elastic properties. Microcalorimetry was employed to obtain thermodynamic data for Re$_7$B$_3$ and orthorhombic Re$_3$B and we determined C $_P$ , $_298$ (Re$_7$B$_3$) = 210(4) J/mol, $\Delta H^0_{298}$ (Re$_7$B$_3$) = 40558(400) J/mol, $S^{0}_{298}$(Re$_7$B$_3$) = 267(2) J/mol K and $\Theta_{D,298}$ (Re$_7$B$_3$) = 320(2) K, as well as $C_{p,298}$(Re$_3$B) = 86(1) J/mol, $\Delta H^0_{298}$(Re$_3$B) = 16950(170) J/mol, $\Theta_{D,298}$(Re$_3$B) = 112(1) J/mol K and (Re$_3$B) = 329(3) K. Hardness measurements were performed for Re$_7$B$_3$, which gave a Vickers hardness $H_V$(5 kgf) = 14.5(4) GPa and $H_V$(10 kgf) = 14.1(3) GPa. Electron energy loss spectroscopy (EELS) was performed on orthorhombic Re$_3$B and ReB$_2$, and the experimental spectra are well reproduced by theory in terms of their absorption edges

Elastic stiffness coefficients of thiourea from thermal diffuse scattering

The complete elastic stiffness tensor of thiourea has been determined from thermal diffuse scattering (TDS) using high‐energy photons (100 keV). Comparison with earlier data confirms a very good agreement of the tensor coefficients. In contrast with established methods to obtain elastic stiffness coefficients (e.g. Brillouin spectroscopy, inelastic X‐ray or neutron scattering, ultrasound spectroscopy), their determination from TDS is faster, does not require large samples or intricate sample preparation, and is applicable to opaque crystals. Using high‐energy photons extends the applicability of the TDS‐based approach to organic compounds which would suffer from radiation damage at lower photon energies.The elastic stiffness coefficients of thiourea are determined from thermal diffuse scattering. imag

Image_5_The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study.jpg

PurposeIn brain tumor surgery, it is crucial to achieve complete tumor resection while conserving adjacent noncancerous brain tissue. Several groups have demonstrated that optical coherence tomography (OCT) has the potential of identifying tumorous brain tissue. However, there is little evidence on human in vivo application of this technology, especially regarding applicability and accuracy of residual tumor detection (RTD). In this study, we execute a systematic analysis of a microscope integrated OCT-system for this purpose.Experimental designMultiple 3-dimensional in vivo OCT-scans were taken at protocol-defined sites at the resection edge in 21 brain tumor patients. The system was evaluated for its intraoperative applicability. Tissue biopsies were obtained at these locations, labeled by a neuropathologist and used as ground truth for further analysis. OCT-scans were visually assessed with a qualitative classifier, optical OCT-properties were obtained and two artificial intelligence (AI)-assisted methods were used for automated scan classification. All approaches were investigated for accuracy of RTD and compared to common techniques.ResultsVisual OCT-scan classification correlated well with histopathological findings. Classification with measured OCT image-properties achieved a balanced accuracy of 85%. A neuronal network approach for scan feature recognition achieved 82% and an auto-encoder approach 85% balanced accuracy. Overall applicability showed need for improvement.ConclusionContactless in vivo OCT scanning has shown to achieve high values of accuracy for RTD, supporting what has well been described for ex vivo OCT brain tumor scanning, complementing current intraoperative techniques and even exceeding them in accuracy, while not yet in applicability.</p

Image_4_The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study.jpg

PurposeIn brain tumor surgery, it is crucial to achieve complete tumor resection while conserving adjacent noncancerous brain tissue. Several groups have demonstrated that optical coherence tomography (OCT) has the potential of identifying tumorous brain tissue. However, there is little evidence on human in vivo application of this technology, especially regarding applicability and accuracy of residual tumor detection (RTD). In this study, we execute a systematic analysis of a microscope integrated OCT-system for this purpose.Experimental designMultiple 3-dimensional in vivo OCT-scans were taken at protocol-defined sites at the resection edge in 21 brain tumor patients. The system was evaluated for its intraoperative applicability. Tissue biopsies were obtained at these locations, labeled by a neuropathologist and used as ground truth for further analysis. OCT-scans were visually assessed with a qualitative classifier, optical OCT-properties were obtained and two artificial intelligence (AI)-assisted methods were used for automated scan classification. All approaches were investigated for accuracy of RTD and compared to common techniques.ResultsVisual OCT-scan classification correlated well with histopathological findings. Classification with measured OCT image-properties achieved a balanced accuracy of 85%. A neuronal network approach for scan feature recognition achieved 82% and an auto-encoder approach 85% balanced accuracy. Overall applicability showed need for improvement.ConclusionContactless in vivo OCT scanning has shown to achieve high values of accuracy for RTD, supporting what has well been described for ex vivo OCT brain tumor scanning, complementing current intraoperative techniques and even exceeding them in accuracy, while not yet in applicability.</p

Image_2_The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study.jpg

PurposeIn brain tumor surgery, it is crucial to achieve complete tumor resection while conserving adjacent noncancerous brain tissue. Several groups have demonstrated that optical coherence tomography (OCT) has the potential of identifying tumorous brain tissue. However, there is little evidence on human in vivo application of this technology, especially regarding applicability and accuracy of residual tumor detection (RTD). In this study, we execute a systematic analysis of a microscope integrated OCT-system for this purpose.Experimental designMultiple 3-dimensional in vivo OCT-scans were taken at protocol-defined sites at the resection edge in 21 brain tumor patients. The system was evaluated for its intraoperative applicability. Tissue biopsies were obtained at these locations, labeled by a neuropathologist and used as ground truth for further analysis. OCT-scans were visually assessed with a qualitative classifier, optical OCT-properties were obtained and two artificial intelligence (AI)-assisted methods were used for automated scan classification. All approaches were investigated for accuracy of RTD and compared to common techniques.ResultsVisual OCT-scan classification correlated well with histopathological findings. Classification with measured OCT image-properties achieved a balanced accuracy of 85%. A neuronal network approach for scan feature recognition achieved 82% and an auto-encoder approach 85% balanced accuracy. Overall applicability showed need for improvement.ConclusionContactless in vivo OCT scanning has shown to achieve high values of accuracy for RTD, supporting what has well been described for ex vivo OCT brain tumor scanning, complementing current intraoperative techniques and even exceeding them in accuracy, while not yet in applicability.</p

Image_1_The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study.jpg

PurposeIn brain tumor surgery, it is crucial to achieve complete tumor resection while conserving adjacent noncancerous brain tissue. Several groups have demonstrated that optical coherence tomography (OCT) has the potential of identifying tumorous brain tissue. However, there is little evidence on human in vivo application of this technology, especially regarding applicability and accuracy of residual tumor detection (RTD). In this study, we execute a systematic analysis of a microscope integrated OCT-system for this purpose.Experimental designMultiple 3-dimensional in vivo OCT-scans were taken at protocol-defined sites at the resection edge in 21 brain tumor patients. The system was evaluated for its intraoperative applicability. Tissue biopsies were obtained at these locations, labeled by a neuropathologist and used as ground truth for further analysis. OCT-scans were visually assessed with a qualitative classifier, optical OCT-properties were obtained and two artificial intelligence (AI)-assisted methods were used for automated scan classification. All approaches were investigated for accuracy of RTD and compared to common techniques.ResultsVisual OCT-scan classification correlated well with histopathological findings. Classification with measured OCT image-properties achieved a balanced accuracy of 85%. A neuronal network approach for scan feature recognition achieved 82% and an auto-encoder approach 85% balanced accuracy. Overall applicability showed need for improvement.ConclusionContactless in vivo OCT scanning has shown to achieve high values of accuracy for RTD, supporting what has well been described for ex vivo OCT brain tumor scanning, complementing current intraoperative techniques and even exceeding them in accuracy, while not yet in applicability.</p