This federal Project Grant award from the National Cancer Institute (NCI), under the Cancer Detection and Diagnosis Research program (CFDA 93.394), aims to develop an x-ray dual-energy cone-beam microCT (DECB microCT) system for intraoperative imaging of lumpectomy specimens during breast-conserving surgery (BCS). The $2,020,098 award to the University of Chicago will support the following key objectives over the 5-year project period: Develop the DECB microCT technology to provide enhanced...
This $255,991 National Science Foundation project grant supports the development of an automated system for rapid analysis of biopsy samples by Amcyt, Inc. The system aims to increase the efficiency and accessibility of fine needle aspiration biopsy procedures through three automated processes: sample smearing, staining, and image capture. This addresses a critical need to improve biopsy analytics and potentially eliminate up to 20% of failed procedures due to sampling errors. By automating...
This $400,000 Project Grant award from the National Cancer Institute (NCI), under the Cancer Detection and Diagnosis Research program (CFDA 93.394), aims to develop a new Mini-Reflectance Confocal Microscope (Mini-RCM) device to aid in skin cancer diagnosis and treatment. The project, led by Argosmd, Inc., seeks to create a low-cost, portable, and fast Mini-RCM system that can non-invasively examine cellular details of skin lesions. This builds on prior work by the University of Arizona to...
This $272,835 Project Grant award from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), under the Discovery and Applied Research for Technological Innovations to Improve Human Health (CFDA 93.286) program, aims to develop a new Probe-Based Light Sheet Microscopy (PLSM) device and evaluate its clinical utility for in vivo imaging of the anal mucosa during cancer screening. The University of Arizona, as the prime awardee, will collaborate with researchers from Memorial...
The National Institute of Biomedical Imaging and Bioengineering (NIBIB) awarded a $249,000 Project Grant under the "Discovery and Applied Research for Technological Innovations to Improve Human Health" (CFDA 93.286) program to Case Western Reserve University. The grant will fund the development of a high-throughput photoacoustic histology platform to enable real-time intraoperative pathological diagnosis. Key objectives include creating an ultrafast reflection-mode ultraviolet...
This $593,383 Project Grant awarded by the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394) aims to develop an AI-augmented, multimodal, label-free nonlinear optical microscopy system for rapid and precise diagnosis of thyroid cancer and lymph node metastasis. The award supports the creation of a compact, portable, AI-integrated label-free microendoscope designed to fit within a core biopsy needle. This device is intended to enable...
Visikol Inc. received a $4,103,265 Project Grant award from the National Cancer Institute, a division of the Department of Health and Human Services, under the Cancer Detection and Diagnosis Research program (CFDA 93.394). The award will support the development of a 3D imaging diagnostic tool to improve characterization of metastatic melanoma in sentinel lymph node biopsies. Visikol will conduct a retrospective clinical study using archived negative sentinel lymph node biopsy tissue blocks to...
This Project Grant award from the National Cancer Institute (NCI), under the Cancer Detection and Diagnosis Research program (CFDA 93.394), provides $598,046 to Case Western Reserve University (CWRU) to develop a rapid and reproducible magnetic resonance fingerprinting (MRF) method. The goal is to quantitatively and accurately characterize prostatic peripheral zone tissue to limit overdiagnosis and overtreatment of prostate cancer. The key products and services to be delivered include:...
This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) provides $658,336 to Rarecyte, Inc. to develop the ORION2 instrument, a novel system for highly multiplexed spatial profiling of tumor and tissue samples. The ORION2 will combine advanced methods for quantifying 10-60 protein markers in tissue sections at subcellular resolution with machine learning algorithms to prioritize and acquire optimized high-resolution images. This...
This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) provides $710,656 to Loma Linda University to develop and validate the PROSPECT (Premalignant Oral Lesions Pathology and Epigenetic Risk Prediction Tool), a multi-stage, multi-modal biomarker to risk-stratify oral premalignant lesions (OPL) and predict progression to oral cavity squamous cell carcinoma. The project aims to: 1) Train deep learning models to predict OPL progression...
DEVELOPMENT AND EVALUATION OF A COMBINED X-RAY TRANSMISSION AND DIFFRACTION IMAGING SYSTEM FOR PATHOLOGY - ABSTRACT PATHOLOGY, WHICH PLAYS A VITAL ROLE IN CLINICAL DIAGNOSIS, FACES NUMEROUS CHALLENGES THAT IMPACT ITS EFFICACY. FOR EXAMPLE, RESECTED SPECIMENS OFTEN REQUIRE PREPARING AND ANALYSIS OF AS MANY AS 30-40 SLIDE BLOCKS UNDER A MICROSCOPE UNTIL THE DISEASE IS CONFIRMED; SELECTION OF SLICES FOR SLIDE PREPARATION USES SUBJECTIVE METHODS SUCH AS PALPATION, WHICH DEPEND GREATLY ON THE SKILL OF THE INDIVIDUAL PERFORMING THE ASSESSMENT AND INTRODUCES INCONSISTENCY IN THE CLINICAL PROCESS; AND FOR EACH SLIDE BLOCK EXAMINED, ANALYSIS AND ANNOTATION REQUIRES MANUAL OBSERVATION OF EVERY MICROSCOPIC REGION OF THE TISSUE. AS A RESULT, MOST PATHOLOGY EVALUATIONS OFTEN TAKE 1-3 WEEKS TO ANALYZE SAMPLES AND REACH A CONCLUSION REGARDING POTENTIAL CANCERS. AN ADDED CHALLENGE IS THAT INSURANCE REIMBURSEMENTS ARE CAPPED PER CASE REGARDLESS OF THE NUMBER OF SLIDE BLOCKS PROCESSED, WITH ANY ADDITIONAL COSTS BEING ABSORBED BY THE HOSPITAL. CONSEQUENTLY, HOSPITALS MUST BALANCE THE TRADE-OFF BETWEEN MINIMIZING THE NUMBER OF SLICES (FOR ECONOMIC VIABILITY) AND NOT COMPROMISING DIAGNOSTIC CARE. THESE CHALLENGES AFFECT NOT ONLY CLINICAL PATHOLOGY BUT ALSO RESEARCH INVOLVING PATHOLOGY SPECIMENS AND TISSUE SELECTION FOR BIOBANKING. THERE IS A CRITICAL NEED TO ELIMINATE SUBJECTIVITY, REDUCE PATHOLOGISTS' WORKLOAD, AND INCREASE THROUGHPUT IN HISTOLOGICAL ANALYSIS. WE PROPOSE TO MEET THIS NEED BY DEVELOPING A NEW TECHNOLOGY CALLED X-RAY DIFFRACTION IMAGING (XRDI), WHICH CAN SCAN ANY NUMBER OF SURGICALLY RESECTED, SLICED PATHOLOGY SPECIMENS AND AUTOMATICALLY INDICATE THE LIKELIHOOD AND LOCATION OF DISEASE IN EACH SLICE WITHIN MINUTES. IN COLLABORATION WITH DUKE UNIVERSITY, WE PREVIOUSLY BUILT A RESEARCH PROTOTYPE XRDI SYSTEM AND DEMONSTRATED ITS UTILITY BY SCANNING AND EVALUATING 300 BREAST CANCER SLICES WITH HIGH ACCURACY AND RESOLUTION. IN THIS DIRECT-TO-PHASE-II SBIR APPLICATION, WE WILL NOW CONSTRUCT A NEW CLINICAL VERSION OF THE XRDI SCANNER THAT IS AFFORDABLE, RELIABLE, AND ACCURATE, AND CAN BE DIRECTLY INTEGRATED INTO THE CLINICAL PATHOLOGY WORKFLOW. WE WILL BUILD THE SCANNER, TEST AND EVALUATE ITS PERFORMANCE, AND DEMONSTRATE ITS UTILITY THROUGH FIELD-TESTING IN COLLABORATION WITH CLINICAL PATHOLOGY LABORATORIES IN THE US. THIS PROJECT WILL PROVIDE A FIRST-OF-ITS-KIND, COMMERCIALLY FEASIBLE XRDI SCANNER FOR RAPID, NON-DESTRUCTIVE IMAGING OF PATHOLOGY SPECIMENS WITH THE ABILITY TO INFORM PATHOLOGISTS ABOUT THE PRESENCE AND LOCATION OF CANCER WITHIN THE DIFFERENT TISSUE SLICES. THE PROPOSED CLINICAL SCANNER WILL ENABLE: 1) ANALYSIS OF THE WHOLE SLICE VOLUME OF THE SPECIMEN RATHER THAN A FEW MICRONS AT THE SURFACE OF A SUBSET OF THE SLICES, WHICH IS THE CURRENT STANDARD OF CARE PROCESS USING MICROSCOPY, 2) QUANTITATIVE IDENTIFICATION OF DISEASE BASED ON XRD INFORMATION OBTAINED DIRECTLY FROM THE TISSUE, AND 3) SLICE SELECTION BASED ON QUANTITATIVE, REPRODUCIBLE MEASUREMENTS, THEREBY ELIMINATING USER-RELATED SUBJECTIVITY. IMPORTANTLY, IT WOULD SIGNIFICANTLY SPEED UP PATHOLOGY WORKFLOW, PROVIDING DECISIONS WITHIN HOURS INSTEAD OF DAYS, AND IMPROVE THE PRODUCTIVITY AND PROFITABILITY OF PATHOLOGY LABS BY REDUCING THE NUMBER OF SLIDE BLOCKS ANALYZED PER CASE.