open-source-miniature-fluorimeter-to-monitor-real-time-isothermal

Open-Source Miniature Fluorimeter to Monitor Real-Time Isothermal Nucleic Acid Amplification Reactions in Resource-Limited Settings

Traditional methods to detect and quantify nucleic acids rely on polymerase chain reaction (PCR) and require the use of expensive thermocyclers with ...

Rice University

Early detection of oral cancer and oral premalignant lesions (OPL) containing dysplasia could improve oral cancer outcomes. However, general dental practitioners have difficulty distinguishing dysplastic OPLs from confounder oral mucosal lesions in low-risk populations. We evaluated the ability of two optical imaging technologies, autofluorescence imaging (AFI) and high-resolution microendoscopy (HRME), to diagnose moderate dysplasia or worse (ModDys) in 56 oral mucosal lesions in a low-risk patient population, using histopathology as the gold standard, and in 46 clinically normal sites. AFI correctly diagnosed 91% of ModDys lesions, 89% of clinically normal sites, and 33% of benign lesions. Benign lesions with severe inflammation were less likely to be correctly diagnosed by AFI (13%) than those without (42%). Multimodal imaging (AFI+HRME) had higher accuracy than either modality alone; 91% of ModDys lesions, 93% of clinically normal sites, and 64% of benign lesions were correctly diagnosed. Photos of the 56 lesions were evaluated by 28 dentists of varied training levels, including 26 dental residents. We compared the area under the receiver operator curve (AUC) of clinical impression alone to clinical impression plus AFI and clinical impression plus multimodal imaging using -Nearest Neighbors models. The mean AUC of the dental residents was 0.71 (range: 0.45-0.86). The addition of AFI alone to clinical impression slightly lowered the mean AUC (0.68; range: 0.40-0.82), whereas the addition of multimodal imaging to clinical impression increased the mean AUC (0.79; range: 0.61-0.90). On the basis of these findings, multimodal imaging could improve the evaluation of oral mucosal lesions in community dental settings. .

 Multimodal Optical Imaging: Improved Detection of Oral Dysplasia in Low-Risk Oral Mucosal Lesions.

Fiber-optic endomicroscopy is a minimally invasive tool to probe disease progression with subcellular resolution. In this Letter, we demonstrate a low-cost and compact fluorescence microendoscope capable of line-scanning confocal imaging by synchronizing a digital light projector with a CMOS camera. We present the digital aperture design to enable real-time confocal imaging, and we implement parallel illumination to improve the optical sectioning performance. Furthermore, we show that the confocal microendoscope can enhance visualization of disease-associated features when imaging highly scattering esophageal specimens.

Improving nuclear morphometry imaging with real-time and low-cost line-scanning confocal microendoscope.

Oral premalignant lesions (OPLs), such as leukoplakia, are at risk of malignant transformation to oral cancer. Clinicians can elect to biopsy OPLs and assess them for dysplasia, a marker of increased risk. However, it is challenging to decide which OPLs need a biopsy and to select a biopsy site. We developed a multimodal optical imaging system (MMIS) that fully integrates the acquisition, display, and analysis of macroscopic white-light (WL), autofluorescence (AF), and high-resolution microendoscopy (HRME) images to noninvasively evaluate OPLs. WL and AF images identify suspicious regions with high sensitivity, which are explored at higher resolution with the HRME to improve specificity. Key features include a heat map that delineates suspicious regions according to AF images, and real-time image analysis algorithms that predict pathologic diagnosis at imaged sites. Representative examples from ongoing studies of the MMIS demonstrate its ability to identify high-grade dysplasia in OPLs that are not clinically suspicious, and to avoid unnecessary biopsies of benign OPLs that are clinically suspicious. The MMIS successfully integrates optical imaging approaches (WL, AF, and HRME) at multiple scales for the noninvasive evaluation of OPLs.

Development of an integrated multimodal optical imaging system with real-time image analysis for the evaluation of oral premalignant lesions.

Patients with oral potentially malignant disorders (OPMD) must undergo regular clinical surveillance to ensure that any progression to malignancy is detected promptly. Autofluorescence imaging (AFI) is an optical modality that can assist clinicians in detecting early cancers and high-grade dysplasia. Patients with OPMD undergoing surveillance for the development of oral cancer were examined using AFI at successive clinic visits. Autofluorescence images acquired at 133 clinical visits from sites in 15 patients who met inclusion criteria were analyzed quantitatively using an algorithm to calculate the red-to-green pixel intensity (RG ratio). A quantitative AFI threshold for high risk of progression was defined based on the RG ratio and was compared with expert clinical impression and with histopathology when available. Patients were divided into two groups based on their endpoint: surveillance ( = 6) or surgery ( = 9). In the surveillance group, 0 of 6 (0%) of patients were clinically identified as high risk for progression prior to the study endpoint, whereas 1 of 6 (17%) of patients were deemed at high risk for progression based on AFI during the same time period. In the surgery group, 9 of 9 (100%) of patients were clinically identified as high risk prior to the study endpoint, whereas 8 of 9 (89%) of patients were at high risk for progression based on AFI during the same time period. AFI results tracked over time were comparable with expert clinical impression in these patient groups. AFI has the potential to aid clinicians in noninvasively monitoring oral precancer and evaluating OPMDs that require increased surveillance.

Autofluorescence Imaging to Monitor the Progression of Oral Potentially Malignant Disorders.

Line-scanning confocal microendoscopy offers video-rate cellular imaging of scattering tissue with relatively simple hardware, but its axial response is inferior to that of point-scanning systems. Based on Fourier optics theory, we designed differential confocal apertures with a simple subtraction technique to improve the line-scanning sectioning performance. Taking advantage of digital slit apertures on a digital light projector and a CMOS rolling shutter, we demonstrate real-time optical sectioning performance comparable to point scanning in a dual-camera microendoscope (<$6,000). We validate the background rejection capability when imaging porcine columnar epithelium stained with fluorescent contrast agents with different uptake mechanisms and staining properties.

Simple differential digital confocal aperture to improve axial response of line-scanning confocal microendoscopes.

Multimodal optical imaging, incorporating reflectance and fluorescence modalities, is a promising tool to detect oral premalignant lesions in real-time.

Prospective evaluation of oral premalignant lesions using a multimodal imaging system: a pilot study.

Cervical cancer incidence and mortality rates remain high in medically underserved areas. In this study, we present a low-cost (<$5,000), portable and user-friendly confocal microendoscope, and we report on its clinical use to image precancerous lesions in the cervix. The confocal microendoscope employs digital apertures on a digital light projector and a CMOS sensor to implement line-scanning confocal imaging. Leveraging its versatile programmability, we describe an automated aperture alignment algorithm to ensure clinical ease-of-use and to facilitate technology dissemination in low-resource settings. Imaging performance is then evaluated in  and  pilot studies; results demonstrate that the confocal microendoscope can enhance visualization of nuclear morphology, contributing to significantly improved recognition of clinically important features for detection of cervical precancer.

In vivo imaging of cervical precancer using a low-cost and easy-to-use confocal microendoscope.

 optical imaging technologies like high-resolution microendoscopy (HRME) can image nuclei of the oral epithelium. In principle, automated algorithms can then calculate nuclear features to distinguish neoplastic from benign tissue. However, images frequently contain regions without visible nuclei, due to biological and technical factors, decreasing the data available to and accuracy of image analysis algorithms.  We developed the nuclear density-confidence interval (ND-CI) algorithm to determine if an HRME image contains sufficient nuclei for classification, or if a better image is required. The algorithm uses a convolutional neural network to exclude image regions without visible nuclei. Then the remaining regions are used to estimate a confidence interval (CI) for the number of abnormal nuclei  , a feature used by a previously developed algorithm (called the ND algorithm), to classify images as benign or neoplastic. The range of the CI determines whether the ND-CI algorithm can classify an image with confidence, and if so, the predicted category. The ND and ND-CI algorithm were compared by calculating their positive predictive value (PPV) and negative predictive value (NPV) on 82 oral biopsies with histopathologically confirmed diagnoses.  After excluding the images that could not be classified with confidence, the ND-CI algorithm had higher PPV (65% versus 59%) and NPV (78% versus 75%) than the ND algorithm.  The ND-CI algorithm could improve the real-time classification of HRME images of the oral epithelium by informing the user if an improved image is required for diagnosis.

Algorithm to quantify nuclear features and confidence intervals for classification of oral neoplasia from high-resolution optical images.

 Conventional cystoscopy plays an important role in detection of bladder cancer; however, it is difficult to differentiate benign and neoplastic lesions based on cystoscopic appearance alone. Advanced microscopic modalities, such as confocal laser endomicroscopy and optical coherence tomography, have been shown to provide critical histopathologic information to help identify neoplastic bladder lesions in real time, but their availability and clinical adoption are limited due to a high cost. In this study, we present the first use of a novel and low-cost ($ <5000) confocal high-resolution microendoscope (confocal HRME) for  imaging of bladder lesions.  In a cohort of 15 patients undergoing white light cystoscopy as part of their standard of care, high-resolution images of proflavine-stained bladder lesions were acquired  using the confocal HRME. Based on these images, we evaluated the ability of the confocal HRME to visualize uroepithelium with subcellular resolution and high contrast. Furthermore, we analyzed the cellular architecture and staining patterns of benign and neoplastic bladder lesions in confocal HRME images and compared results to that of standard cystoscopy and histopathology.  imaging in the pilot study demonstrates that the confocal HRME resolved subcellular structures of bladder uroepithelium with high contrast. In a wide range of clinical conditions from normal bladder wall to benign and neoplastic lesions, confocal HRME images revealed important diagnostic features that correlated to histopathology.  The confocal HRME provides an affordable, portable, and easy-to-use tool to allow real-time and high-contrast subcellular characterization of bladder lesions, well suited for bladder cancer detection in community and resource-constrained settings. The ClinicalTrials.gov Identifier: NCT02340650.

Imran Vohra

Department of Bioengineering

Rice University

Open-Source Miniature Fluorimeter to Monitor Real-Time Isothermal Nucleic Acid Amplification Reactions in Resource-Limited Settings

Imran Vohra

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Bioengineering

Rice University

Open-Source Miniature Fluorimeter to Monitor Real-Time Isothermal Nucleic Acid Amplification Reactions in Resource-Limited Settings

Department of Bioengineering