Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor resection, hundreds to thousands of images may be collected. The high number of images requires significant time and storage load for subsequent reviewing, which motivated several research groups to employ deep convolutional neural networks (DCNNs) to improve its utility during surgery. DCNNs have proven to be useful in natural and medical image analysis tasks such as classification, object detection, and image segmentation.
This thesis proposes using DCNNs for analyzing CLE images of brain tumors. Particularly, it explores the practicality of DCNNs in three main tasks. First, off-the shelf DCNNs were used to classify images into diagnostic and non-diagnostic. Further experiments showed that both ensemble modeling and transfer learning improved the classifier’s accuracy in evaluating the diagnostic quality of new images at test stage. Second, a weakly-supervised learning pipeline was developed for localizing key features of diagnostic CLE images from gliomas. Third, image style transfer was used to improve the diagnostic quality of CLE images from glioma tumors by transforming the histology patterns in CLE images of fluorescein sodium-stained tissue into the ones in conventional hematoxylin and eosin-stained tissue slides.
These studies suggest that DCNNs are opted for analysis of CLE images. They may assist surgeons in sorting out the non-diagnostic images, highlighting the key regions and enhancing their appearance through pattern transformation in real time. With recent advances in deep learning such as generative adversarial networks and semi-supervised learning, new research directions need to be followed to discover more promises of DCNNs in CLE image analysis.
A significant ischemic event that overcomes vascular compensatory capacity causes spinal cord injury (SCI). For example, SCI complicating thoracoabdominal aortic aneurysm repair is associated with ischemic injury. The rate of this devastating complication has been decreased significantly by instituting physiological methods of protection. Traumatic spinal cord injury causes complex changes in spinal cord blood flow (SCBF), which are closely related to a severity of injury. Manipulating physiological parameters such as mean arterial pressure (MAP) and intrathecal pressure (ITP) may be beneficial for patients with a spinal cord injury. It was discovered in a pig model of SCI that the combination of MAP elevation and cerebrospinal fluid drainage (CSFD) significantly and sustainably improved SCBF and spinal cord perfusion pressure.
In animal models of SCI, regeneration is usually evaluated histologically, requiring animal sacrifice. Thus, there is a need for a technique to detect changes in SCI noninvasively over time. The study was performed comparing manganese-enhanced magnetic resonance imaging (MEMRI) in hemisection and transection SCI rat models with diffusion tensor imaging (DTI) and histology. MEMERI ratio differed among transection and hemisection groups, correlating to a severity of SCI measured by fraction anisotropy and myelin load. MEMRI is a useful noninvasive tool to assess a degree of neuronal damage after SCI.
Introduction: Fluorescence-guided surgery is one of the rapidly emerging methods of surgical “theranostics.” In this review, we summarize current fluorescence techniques used in neurosurgical practice for brain tumor patients as well as future applications of recent laboratory and translational studies.
Methods: Review of the literature.
Results: A wide spectrum of fluorophores that have been tested for brain surgery is reviewed. Beginning with a fluorescein sodium application in 1948 by Moore, fluorescence-guided brain tumor surgery is either routinely applied in some centers or is under active study in clinical trials. Besides the trinity of commonly used drugs (fluorescein sodium, 5-aminolevulinic acid, and indocyanine green), less studied fluorescent stains, such as tetracyclines, cancer-selective alkylphosphocholine analogs, cresyl violet, acridine orange, and acriflavine, can be used for rapid tumor detection and pathological tissue examination. Other emerging agents, such as activity-based probes and targeted molecular probes that can provide biomolecular specificity for surgical visualization and treatment, are reviewed. Furthermore, we review available engineering and optical solutions for fluorescent surgical visualization. Instruments for fluorescent-guided surgery are divided into wide-field imaging systems and hand-held probes. Recent advancements in quantitative fluorescence-guided surgery are discussed.
Conclusion: We are standing on the threshold of the era of marker-assisted tumor management. Innovations in the fields of surgical optics, computer image analysis, and molecular bioengineering are advancing fluorescence-guided tumor resection paradigms, leading to cell-level approaches to visualization and resection of brain tumors.