Optical spectroscopic methods for intraoperative diagnosis

A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition

PURPOSE

Infrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore, we propose the exploitation of these common spectral changes for brain tumor recognition.

METHODS

Attenuated total reflection IR spectroscopy was performed on fresh specimens of 790 patients within minutes after resection. Using principal component analysis and linear discriminant analysis, a classification model was developed on a subset of glioblastoma (n = 135) and non-neoplastic brain (n = 27) specimens, and then applied to classify the IR spectra of several types of brain tumors.

RESULTS

The model correctly classified 82% (517/628) of specimens as "tumor" or "non-tumor", respectively. While the sensitivity was limited for infiltrative glioma, this approach recognized GBM (86%), other types of primary brain tumors (92%) and brain metastases (92%) with high accuracy and all non-tumor samples were correctly identified.

CONCLUSION

The concept of differentiation of brain tumors from non-tumor brain based on a common spectroscopic tumor signature will accelerate clinical translation of infrared spectroscopy and related technologies. The surgeon could use a single instrument to detect a variety of brain tumor types intraoperatively in future clinical settings. Our data suggests that this would be associated with some risk of missing infiltrative regions or tumors, but not with the risk of removing non-tumor brain.

Perspectives on infrared spectroscopic imaging from cancer diagnostics to process analysis

This perspective paper discusses the recent and potential developments in the application of infrared spectroscopic imaging, with a focus on Fourier transform infrared (FTIR) spectroscopic imaging. The current state-of-the-art has been briefly reported, that includes recent trends and advances in applications of FTIR spectroscopic imaging to biomedical systems. Here, some new opportunities for research in the biomedical field, particularly for cancer diagnostics, and also in the engineering field of process analysis; as well as challenges in FTIR spectroscopic imaging are discussed. Current and future prospects that will bring spectroscopic imaging technologies to the frontier of advanced medical diagnostics and to process analytics in engineering applications will be outlined in this opinion paper.

Dual-Modality Surface-Enhanced Resonance Raman Scattering and Multispectral Optoacoustic Tomography Nanoparticle Approach for Brain Tumor Delineation

Difficulty in visualizing glioma margins intraoperatively remains a major issue in the achievement of gross total tumor resection and, thus, better clinical outcome of glioblastoma (GBM) patients. Here, the potential of a new combined optical + optoacoustic imaging method for intraoperative brain tumor delineation is investigated. A strategy using a newly developed gold nanostar synthesis method, Raman reporter chemistry, and silication method to produce dual-modality contrast agents for combined surface-enhanced resonance Raman scattering (SERRS) and multispectral optoacoustic tomography (MSOT) imaging is devised. Following intravenous injection of the SERRS-MSOT-nanostars in brain tumor bearing mice, sequential MSOT imaging is performed in vivo and followed by Raman imaging. MSOT is able to accurately depict GBMs three-dimensionally with high specificity. The MSOT signal is found to correlate well with the SERRS images. Because SERRS enables uniquely sensitive high-resolution surface detection, it could represent an ideal complementary imaging modality to MSOT, which enables real-time, deep tissue imaging in 3D. This dual-modality SERRS-MSOT-nanostar contrast agent reported here is shown to enable high precision depiction of the extent of infiltrating GBMs by Raman- and MSOT imaging in a clinically relevant murine GBM model and could pave new ways for improved image-guided resection of brain tumors.

Dual-Modality Surface-Enhanced Resonance Raman Scattering and Multispectral Optoacoustic Tomography Nanoparticle Approach for Brain Tumor Delineation

Difficulty in visualizing glioma margins intraoperatively remains a major issue in the achievement of gross total tumor resection and, thus, better clinical outcome of glioblastoma (GBM) patients. Here, the potential of a new combined optical + optoacoustic imaging method for intraoperative brain tumor delineation is investigated. A strategy using a newly developed gold nanostar synthesis method, Raman reporter chemistry, and silication method to produce dual-modality contrast agents for combined surface-enhanced resonance Raman scattering (SERRS) and multispectral optoacoustic tomography (MSOT) imaging is devised. Following intravenous injection of the SERRS-MSOT-nanostars in brain tumor bearing mice, sequential MSOT imaging is performed in vivo and followed by Raman imaging. MSOT is able to accurately depict GBMs three-dimensionally with high specificity. The MSOT signal is found to correlate well with the SERRS images. Because SERRS enables uniquely sensitive high-resolution surface detection, it could represent an ideal complementary imaging modality to MSOT, which enables real-time, deep tissue imaging in 3D. This dual-modality SERRS-MSOT-nanostar contrast agent reported here is shown to enable high precision depiction of the extent of infiltrating GBMs by Raman- and MSOT imaging in a clinically relevant murine GBM model and could pave new ways for improved image-guided resection of brain tumors.

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area.

[Importance of preoperative and intraoperative imaging for operative strategies]

Recent advances in preoperative and postoperative imaging have an increasing influence on surgical decision-making and make more complex surgical interventions possible. This improves the possibilities for frequently occurring challenges and promoting improved functional and oncological outcome. This manuscript reviews the role of preoperative and intraoperative imaging in surgery. Various techniques are explained based on examples from hepatobiliary surgery and neurosurgery, in particular real-time procedures, such as the online use of augmented reality and in vivo fluorescence, as well as new and promising optical techniques including imaging of intrinsic signals and vibrational spectroscopy.