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Significance: Terahertz wave is a potential tool for biological tissues due to its noninvasiveness and high sensitivity to water. Attenuated total reflection (ATR) with the characteristics of high sensitivity and nondestruction has been applied for THz imaging. Aim: We aim to develop an imaging methodology to facilitate practical application of THz ATR imaging. Approach: We have demonstrated a horizontally scanning THz continuous wave ATR imaging system. The effective imaging area was as large as the prism imaging surface by optimizing the ATR prism, and the influence of secondary reflection can be well avoided. By taking the image resolution and stability of this system into consideration, the incident angle α to the prism bottom was chosen to be 30 deg. Results: The image resolution of this system can be up to 400 and 450 μm in horizontal and vertical directions, respectively. Furthermore, U87-glioma regions of mice brain tissues with different sizes and C6-glioma regions of rat brain tissues with relatively large size can be differentiated clearly from normal brain tissues by this imaging system. The volume and location of the tumor region shown in the THz images are similar to those visualized macroscopically in the corresponding visual and H&E-stained images. Conclusion: We indicate terahertz horizontal-scanning ATR imaging technique with large effective imaging area, and high resolution could be used as an alternative method for label-free and high-sensitivity imaging of biological tissues.

Interstitial photodynamic therapy (iPDT) with 5-aminolevulinic acid (ALA) is a possible alternative treatment for malignant brain tumors. Further evaluation is, however, required before it can be clinically applied. Computational simulation of the photophysical process in ALA-iPDT can offer a quantitative tool for understanding treatment outcomes, which depend on various variables related to clinical treatment conditions. We propose a clinical simulation method of ALA-iPDT for malignant brain tumors using a singlet oxygen (O12) model and O12 threshold to induce cell death. In this method, the amount of O12 generated is calculated using a photosensitizer photobleaching coefficient and O12 quantum yield, which have been measured in several previous studies. Results of the simulation using clinical magnetic resonance imaging data show the need to specify the insertion positions of cylindrical light diffusers and the level of light fluence. Detailed analysis with a numerical brain tumor model demonstrates that ALA-iPDT treatment outcomes depend on combinations of photobleaching and threshold values. These results indicate that individual medical procedures, including pretreatment planning and treatment monitoring, will greatly benefit from simulation of ALA-iPDT outcomes.

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins.