Balaji Pandian

Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy

Conventional methods for intraoperative histopathologic diagnosis are labour- and time-intensive, and may delay decision-making during brain-tumour surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain-tumour infiltration in fresh, unprocessed human tissues. Here, we demonstrate the first application of SRS microscopy in the operating room by using a portable fibre-laser-based microscope and unprocessed specimens from 101 neurosurgical patients. We also introduce an image-processing method – stimulated Raman histology (SRH) – which leverages SRS images to create virtual haematoxylin-and-eosin-stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, we found a remarkable concordance of SRH and conventional histology for predicting diagnosis (Cohens kappa, κ > 0.89), with accuracy exceeding 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain-tumour subtype with 90% accuracy. Our findings provide insight into how SRH can now be used to improve the surgical care of brain tumour patients.

TACO produces robust multisample transcriptome assemblies from RNA-seq

Accurate transcript structure and abundance inference from RNA sequencing (RNA-seq) data is foundational for molecular discovery. Here we present TACO, a computational method to reconstruct a consensus transcriptome from multiple RNA-seq data sets. TACO employs novel change-point detection to demarcate transcript start and end sites, leading to improved reconstruction accuracy compared with other tools in its class. The tool is available at http://tacorna.github.io and can be readily incorporated into RNA-seq analysis workflows.

Posterior Fossa Craniotomy for Adherent Fourth Ventricle Neurocysticercosis

BACKGROUND AND IMPORTANCE Neurocysticercosis (NCC) is an infectious helminthic disease often presenting in patients who have immigration or travel history from areas where NCC is endemic. Fourth ventricle cysts from NCC pose a unique treatment challenge, as there is little consensus on the best treatment. This case study describes the treatment of a patient with fourth ventricle neurocysticercosis (FVNCC), examines the therapeutic decision-making, and provides a video of a posterior fossa craniotomy (PFC) resection of a degenerative cyst. CLINICAL PRESENTATION The patient presented with headache, dizziness, nausea, and memory difficulties. A fourth ventricle cyst consistent with NCC was found on magnetic resonance imaging, and serum enzyme-linked immunosorbent assay (ELISA) confirmed the diagnosis. The cyst was removed utilizing an open PFC followed by antihelminthic therapy and corticosteroids. There was resolution of symptoms at 9 mo postoperatively. CONCLUSION Several treatment modalities have been proposed for isolated cysts in the fourth ventricle, including medication, ventriculoperitoneal shunt, endoscopic removal, and PFC. The treatment decision is complex, and there is little guidance on the best treatment choices. In this article, we describe treatment via PFC for an adherent FVNCC cyst.

MiPanda: A Resource for Analyzing and Visualizing Next-Generation Sequencing Transcriptomics Data.

The Michigan Portal for the Analysis of NGS data portal (http://mipanda.org) is an open-access online resource that provides the scientific community with access to the results of a large-scale computational analysis of thousands of high-throughput RNA sequencing (RNA-seq) samples. The portal provides access to gene expression profiles, enabling users to interrogate expression of genes across myriad normal and cancer tissues and cell lines. From these data, tissue- and cancer-specific expression patterns can be identified. Gene-gene coexpression profiles can also be interrogated. The current portal contains data for over 20,000 RNA-seq samples and will be continually updated.

Rapid Intraoperative Diagnosis of Pediatric Brain Tumors Using Stimulated Raman Histology

Accurate histopathologic diagnosis is essential for providing optimal surgical management of pediatric brain tumors. Current methods for intraoperative histology are time- and labor-intensive and often introduce artifact that limit interpretation. Stimulated Raman histology (SRH) is a novel label-free imaging technique that provides intraoperative histologic images of fresh, unprocessed surgical specimens. Here we evaluate the capacity of SRH for use in the intraoperative diagnosis of pediatric type brain tumors. SRH revealed key diagnostic features in fresh tissue specimens collected from 33 prospectively enrolled pediatric type brain tumor patients, preserving tumor cytology and histoarchitecture in all specimens. We simulated an intraoperative consultation for 25 patients with specimens imaged using both SRH and standard hematoxylin and eosin histology. SRH-based diagnoses achieved near-perfect diagnostic concordance (Cohens kappa, κ > 0.90) and an accuracy of 92% to 96%. We then developed a quantitative histologic method using SRH images based on rapid image feature extraction. Nuclear density, tumor-associated macrophage infiltration, and nuclear morphology parameters from 3337 SRH fields of view were used to develop and validate a decision-tree machine-learning model. Using SRH image features, our model correctly classified 25 fresh pediatric type surgical specimens into normal versus lesional tissue and low-grade versus high-grade tumors with 100% accuracy. Our results provide insight into how SRH can deliver rapid diagnostic histologic data that could inform the surgical management of pediatric brain tumors.Significance: A new imaging method simplifies diagnosis and informs decision making during pediatric brain tumor surgery. Cancer Res; 78(1); 278-89. ©2017 AACR.