Prospects for Theranostics in Neurosurgical Imaging: Empowering Confocal Laser Endomicroscopy Diagnostics via Deep Learning

Confocal laser endomicroscopy (CLE) is an advanced optical fluorescence imaging technology that has the potential to increase intraoperative precision, extend resection, and tailor surgery for malignant invasive brain tumors because of its subcellular dimension resolution. Despite its promising diagnostic potential, interpreting the gray tone fluorescence images can be difficult for untrained users. In this review, we provide a detailed description of bioinformatical analysis methodology of CLE images that begins to assist the neurosurgeon and pathologist to rapidly connect on-the-fly intraoperative imaging, pathology, and surgical observation into a conclusionary system within the concept of theranostics. We present an overview and discuss deep learning models for automatic detection of the diagnostic CLE images and discuss various training regimes and ensemble modeling effect on the power of deep learning predictive models. Two major approaches reviewed in this paper include the models that can automatically classify CLE images into diagnostic/nondiagnostic, glioma/nonglioma, tumor/injury/normal categories and models that can localize histological features on the CLE images using weakly supervised methods. We also briefly review advances in the deep learning approaches used for CLE image analysis in other organs. Significant advances in speed and precision of automated diagnostic frame selection would augment the diagnostic potential of CLE, improve operative workflow and integration into brain tumor surgery. Such technology and bioinformatics analytics lend themselves to improved precision, personalization, and theranostics in brain tumor treatment.Comment: See the final version published in Frontiers in Oncology here: https://www.frontiersin.org/articles/10.3389/fonc.2018.00240/ful

Improving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

Confocal laser endomicroscopy (CLE), although capable of obtaining images at cellular resolution during surgery of brain tumors in real time, creates as many non-diagnostic as diagnostic images. Non-useful images are often distorted due to relative motion between probe and brain or blood artifacts. Many images, however, simply lack diagnostic features immediately informative to the physician. Examining all the hundreds or thousands of images from a single case to discriminate diagnostic images from nondiagnostic ones can be tedious. Providing a real-time diagnostic value assessment of images (fast enough to be used during the surgical acquisition process and accurate enough for the pathologist to rely on) to automatically detect diagnostic frames would streamline the analysis of images and filter useful images for the pathologist/surgeon. We sought to automatically classify images as diagnostic or non-diagnostic. AlexNet, a deep-learning architecture, was used in a 4-fold cross validation manner. Our dataset includes 16,795 images (8572 nondiagnostic and 8223 diagnostic) from 74 CLE-aided brain tumor surgery patients. The ground truth for all the images is provided by the pathologist. Average model accuracy on test data was 91% overall (90.79 % accuracy, 90.94 % sensitivity and 90.87 % specificity). To evaluate the model reliability we also performed receiver operating characteristic (ROC) analysis yielding 0.958 average for the area under ROC curve (AUC). These results demonstrate that a deeply trained AlexNet network can achieve a model that reliably and quickly recognizes diagnostic CLE images.Comment: SPIE Medical Imaging: Computer-Aided Diagnosis 201

Microvascular Anastomosis Under 3D Exoscope or Endoscope Magnification: A Proof-Of-Concept Study

Background: Extracranial-intracranial bypass is a challenging procedure that requires special microsurgical skills and an operative microscope. The exoscope is a tool for neurosurgical visualization that provides view on a heads-up display similar to an endoscope, but positioned external to the operating field, like a microscope. The authors carried out a proof-of-concept study evaluating the feasibility and effectiveness of performing microvascular bypass using various new exoscopic tools. Methods: We evaluated microsurgical procedures using a three-dimensional (3D) endoscope, hands-free robotic automated positioning two-dimensional (2D) exoscope, and an ocular-free 3D exoscope, including surgical gauze knot tying, surgical glove cutting, placental vessel anastomoses, and rat vessel anastomoses. Image quality, effectiveness, and feasibility of each technique were compared among different visualization tools and to a standard operative microscope. Results: 3D endoscopy produced relatively unsatisfactory resolution imaging. It was shown to be sufficient for knot tying and anastomosis of a placental artery, but was not suitable for anastomosis in rats. The 2D exoscope provided higher resolution imaging, but was not adequate for all maneuvers because of lack of depth perception. The 3D exoscope was shown to be functional to complete all maneuvers because of its depth perception and higher resolution. Conclusion: Depth perception and high resolution at highest magnification are required for microvascular bypass procedures. Execution of standard microanastomosis techniques was unsuccessful using 2D imaging modalities because of depth-perception-related constraints. Microvascular anastomosis is feasible under 3D exoscopic visualization; however, at highest magnification, the depth perception is inferior to that provided by a standard operative microscope, which impedes the procedure

Laminoplasty versus Laminectomy in the Treatment of Primary Spinal Cord Tumors in Adult Patients: A Systematic Review and Meta-analysis of Observational Studies

The present systematic review and meta-analysis was conducted to compare the safety and efficacy of the two approaches for primary spinal cord tumors (PSCTs) in adult patients (laminoplasty [LP] vs. laminectomy [LE]). LE is one of the most common procedures for PSCTs. Despite advantages of LP, it is not yet widely used in the neurosurgical community worldwide. The efficacy of LP vs. LE remains controversial. Adult patients over 18 years of age with PSCT at the level of the cervical, thoracic, and lumbar spine were included in the study. A literature search was performed in MEDLINE via PubMed, EMBASE, The Cochrane Library, and Google Scholar up to December 2021. Operation time, hospital stay, complications, and incidence of postoperative spinal deformity (kyphosis or scoliosis were extracted. A total of seven retrospective observational studies with 540 patients were included. There were no significant differences between LP and LE group in operation time (p=0.25) and complications (p=0.48). The LE group showed larger postoperative spinal deformity rate than the LP group (odds ratio, 0.47; 95% confidence interval [CI], 0.27−0.84; p=0.01). The LP group had a shorter hospital stay (standardized mean differences, −0.68; 95% CI, −1.03 to −0.34; p=0.0001) than the LE group. Both LP and LE have comparable operative times and total complications in the treatment of PSCT. LP was superior to LE in hospital stay and postoperative spinal deformity rate. However, these findings are limited by the very low quality of the available evidence. Randomized controlled trials are needed for further comparison

A Thoracic Surgeon Among Neurosurgeons: Edward Archibald\u27s Forgotten Influence on the Professionalization of Neurosurgery.

Edward Archibald, Professor of Surgery at McGill University (1904-1945), Montreal, Canada, was the foremost thoracic surgeon of his generation. Although instrumental in establishing the American Board of Surgery and in standardizing surgical training, he was also influential as a neurosurgeon. Archibald, an early member invited by Harvey Cushing to join the Society of Neurological Surgeons, helped establish neurosurgery as a distinct, specialized discipline. We review Archibald\u27s contributions to the development of neurosurgery in light of his encyclopedic 1908 monograph, Surgical Affections and Wounds of the Head, which we compare and contrast to the contemporary treatise by Cushing in the same year. Through his writings and correspondence with Wilder Penfield and Cushing, we also describe his role in the creation of the Montreal Neurological Institute. Primary archival sources addressing the professional relationship between Archibald and Cushing and between Archibald and Penfield were consulted. Archibald\u27s personal acquaintance with the principal neurosurgeons of the day, his insight into their personalities, their prominence in the field, and their career paths played a critical role in influencing Penfield to consider relocating to Montreal from Columbia University, despite tempting offers from Boston and Philadelphia. However, it was Archibald\u27s support and mentorship for the creation of an academic center that finally convinced Penfield to move to McGill University. As one of the most influential surgeons of the early 20th century and a founding figure of modern neurosurgery, Archibald is an important part of neurosurgery\u27s legacy