Misha Pivovarov

Hybrid PET-optical imaging using targeted probes.

Fusion imaging of radionuclide-based molecular (PET) and structural data [x-ray computed tomography (CT)] has been firmly established. Here we show that optical measurements [fluorescence-mediated tomography (FMT)] show exquisite congruence to radionuclide measurements and that information can be seamlessly integrated and visualized. Using biocompatible nanoparticles as a generic platform (containing a 18F isotope and a far red fluorochrome), we show good correlations between FMT and PET in probe concentration (r2 > 0.99) and spatial signal distribution (r2 > 0.85). Using a mouse model of cancer and different imaging probes to measure tumoral proteases, macrophage content and integrin expression simultaneously, we demonstrate the distinct tumoral locations of probes in multiple channels in vivo. The findings also suggest that FMT can serve as a surrogate modality for the screening and development of radionuclide-based imaging agents.

PepBank - a database of peptides based on sequence text mining and public peptide data sources

BackgroundPeptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequences or associated biological data. Rather, peptide sequences still have to be mined from abstracts and full-length articles, and/or obtained from the fragmented public sources.DescriptionWe have constructed a new database (PepBank), which at the time of writing contains a total of 19,792 individual peptide entries. The database has a web-based user interface with a simple, Google-like search function, advanced text search, and BLAST and Smith-Waterman search capabilities. The major source of peptide sequence data comes from text mining of MEDLINE abstracts. Another component of the database is the peptide sequence data from public sources (ASPD and UniProt). An additional, smaller part of the database is manually curated from sets of full text articles and text mining results. We show the utility of the database in different examples of affinity ligand discovery.ConclusionWe have created and maintain a database of peptide sequences. The database has biological and medical applications, for example, to predict the binding partners of biologically interesting peptides, to develop peptide based therapeutic or diagnostic agents, or to predict molecular targets or binding specificities of peptides resulting from phage display selection. The database is freely available on http://pepbank.mgh.harvard.edu/, and the text mining source code (Peptide::Pubmed) is freely available above as well as on CPAN (http://www.cpan.org/).

Digital diffraction analysis enables low-cost molecular diagnostics on a smartphone

Significance Smartphones and wearable electronics have advanced tremendously over the last several years but fall short of allowing their use for molecular diagnostics. We herein report a generic approach to enable molecular diagnostics on smartphones. The method utilizes molecular-specific microbeads to generate unique diffraction patterns of “blurry beads” which can be recorded and deconvoluted by digital processing. We applied the system to resolve individual precancerous and cancerous cells as well as to detect cancer-associated DNA targets. Because the system is compact, easy to operate, and readily integrated with the standard, portable smartphone, this approach could enable medical diagnostics in geographically and/or socioeconomically limited settings with pathology bottlenecks. The widespread distribution of smartphones, with their integrated sensors and communication capabilities, makes them an ideal platform for point-of-care (POC) diagnosis, especially in resource-limited settings. Molecular diagnostics, however, have been difficult to implement in smartphones. We herein report a diffraction-based approach that enables molecular and cellular diagnostics. The D3 (digital diffraction diagnosis) system uses microbeads to generate unique diffraction patterns which can be acquired by smartphones and processed by a remote server. We applied the D3 platform to screen for precancerous or cancerous cells in cervical specimens and to detect human papillomavirus (HPV) DNA. The D3 assay generated readouts within 45 min and showed excellent agreement with gold-standard pathology or HPV testing, respectively. This approach could have favorable global health applications where medical access is limited or when pathology bottlenecks challenge prompt diagnostic readouts.

High throughput transmission optical projection tomography using low cost graphics processing unit

We implement the use of a graphics processing unit (GPU) in order to achieve real time data processing for high-throughput transmission optical projection tomography imaging. By implementing the GPU we have obtained a 300 fold performance enhancement in comparison to a CPU workstation implementation. This enables to obtain on-the-fly reconstructions enabling for high throughput imaging.

Born Normalization for Fluorescence Optical Projection Tomography for Whole Heart Imaging

Optical projection tomography is a three-dimensional imaging technique that has been recently introduced as an imaging tool primarily in developmental biology and gene expression studies. The technique renders biological sample optically transparent by first dehydrating them and then placing in a mixture of benzyl alcohol and benzyl benzoate in a 2:1 ratio (BABB or Murray s Clear solution). The technique renders biological samples optically transparent by first dehydrating them in graded ethanol solutions then placing them in a mixture of benzyl alcohol and benzyl benzoate in a 2:1 ratio (BABB or Murray s Clear solution) to clear. After the clearing process the scattering contribution in the sample can be greatly reduced and made almost negligible while the absorption contribution cannot be eliminated completely. When trying to reconstruct the fluorescence distribution within the sample under investigation, this contribution affects the reconstructions and leads, inevitably, to image artifacts and quantification errors.. While absorption could be reduced further with a permanence of weeks or months in the clearing media, this will lead to progressive loss of fluorescence and to an unrealistically long sample processing time. This is true when reconstructing both exogenous contrast agents (molecular contrast agents) as well as endogenous contrast (e.g. reconstructions of genetically expressed fluorescent proteins).

Sparsity-Based Pixel Super Resolution for Lens-Free Digital In-line Holography.

Lens-free digital in-line holography (LDIH) is a promising technology for portable, wide field-of-view imaging. Its resolution, however, is limited by the inherent pixel size of an imaging device. Here we present a new computational approach to achieve sub-pixel resolution for LDIH. The developed method is a sparsity-based reconstruction with the capability to handle the non-linear nature of LDIH. We systematically characterized the algorithm through simulation and LDIH imaging studies. The method achieved the spatial resolution down to one-third of the pixel size, while requiring only single-frame imaging without any hardware modifications. This new approach can be used as a general framework to enhance the resolution in nonlinear holographic systems.

MIPortal: a high capacity server for molecular imaging research.

The introduction of novel molecular tools in research and clinical medicine has created a need for more refined information management systems. This article describes the design and implementation of such a new information platform: the Molecular Imaging Portal (MIPortal). The platform was created to organize, archive, and rapidly retrieve large datasets using Web-based browsers as access points. The system has been implemented in a heterogeneous, academic research environment serving Macintosh, Unix, and Microsoft Windows clients and has been shown to be extraordinarily robust and versatile. In addition, it has served as a useful tool for clinical trials and collaborative multi-institutional small-animal imaging research.

Holographic Assessment of Lymphoma Tissue (HALT) for Global Oncology Field Applications.

Low-cost, rapid and accurate detection technologies are key requisites to cope with the growing global cancer challenges. The need is particularly pronounced in resource-limited settings where treatment opportunities are often missed due to the absence of timely diagnoses. We herein describe a Holographic Assessment of Lymphoma Tissue (HALT) system that adopts a smartphone as the basis for molecular cancer diagnostics. The system detects malignant lymphoma cells labeled with marker-specific microbeads that produce unique holographic signatures. Importantly, we optimized HALT to detect lymphomas in fine-needle aspirates from superficial lymph nodes, procedures that align with the minimally invasive biopsy needs of resource-constrained regions. We equipped the platform to directly address the practical needs of employing novel technologies for “real world” use. The HALT assay generated readouts in <1.5 h and demonstrated good agreement with standard cytology and surgical pathology.

Design and clinical validation of a point-of-care device for the diagnosis of lymphoma via contrast-enhanced microholography and machine learning

The identification of patients with aggressive cancer who require immediate therapy is a health challenge in low- and middle-income countries. Limited pathology resources, high healthcare costs and large caseloads call for the development of advanced stand-alone diagnostics. Here, we report and validate an automated, low-cost point-of-care device for the molecular diagnosis of aggressive lymphomas. The device uses contrast-enhanced microholography and a deep learning algorithm to directly analyse percutaneously obtained fine-needle aspirates. We show the feasibility and high accuracy of the device in cells, as well as the prospective validation of the results in 40 patients clinically referred for image-guided aspiration of nodal mass lesions suspicious of lymphoma. Automated analysis of human samples with the portable device should allow for the accurate classification of patients with benign and malignant adenopathy.A low-cost point-of-care device that uses contrast-enhanced microholography and deep learning accurately detects aggressive lymphomas in patients referred for aspiration and biopsy of enlarged lymph nodes.