A low-cost, paper-based hybrid capture assay to detect high-risk HPV DNA for cervical cancer screening in low-resource settings.

Cervical cancer is a leading cause of cancer death for women in low-resource settings. The World Health Organization recommends that cervical cancer screening programs incorporate HPV DNA testing, but available tests are expensive, require laboratory infrastructure, and cannot be performed at the point-of-care. We developed a two-dimensional paper network (2DPN), hybrid-capture, signal amplification assay and a point-of-care sample preparation protocol to detect high-risk HPV DNA from exfoliated cervical cells within an hour. The test does not require expensive equipment and has an estimated cost of <$3 per test without the need for batching. We evaluated performance of the paper HPV DNA assay with short synthetic and genomic HPV DNA targets, HPV positive and negative cellular samples, and two sets of clinical samples. The first set of clinical samples consisted of 16 biobanked, provider-collected cervical samples from a study in El Salvador previously tested with careHPV and subsequently tested in a controlled laboratory environment. The paper HPV DNA test correctly identified eight of eight HPV-negative clinical samples and seven of eight HPV-positive clinical samples. We then performed a field evaluation of the paper HPV DNA test in a hospital laboratory in Mozambique. Cellular controls generated expected results throughout field testing with fully lyophilized sample preparation and 2DPN reagents. When evaluated with 16 residual self-collected cervicovaginal samples previously tested by the GeneXpert HPV assay ("Xpert"), the accuracy of the HPV DNA paper test in the field was reduced compared to testing in the controlled laboratory environment, with positive results obtained for all eight HPV-positive samples as well as seven of eight HPV-negative samples. Further evaluation showed reduction in performance was likely due in part to increased concentration of exfoliated cells in the self-collected clinical samples from Mozambique compared with provider-collected samples from El Salvador. Finally, a formal usability assessment was conducted with users in El Salvador and Mozambique; the assay was rated as acceptable to perform after minimal training. With additional optimization for higher cell concentrations and inclusion of an internal cellular control, the paper HPV DNA assay offers promise as a low-cost, point-of-care cervical cancer screening test in low-resource settings.

Multi-task network for automated analysis of high-resolution endomicroscopy images to detect cervical precancer and cancer.

Cervical cancer is a public health emergency in low- and middle-income countries where resource limitations hamper standard-of-care prevention strategies. The high-resolution endomicroscope (HRME) is a low-cost, point-of-care device with which care providers can image the nuclear morphology of cervical lesions. Here, we propose a deep learning framework to diagnose cervical intraepithelial neoplasia grade 2 or more severe from HRME images. The proposed multi-task convolutional neural network uses nuclear segmentation to learn a diagnostically relevant representation. Nuclear segmentation was trained via proxy labels to circumvent the need for expensive, manually annotated nuclear masks. A dataset of images from over 1600 patients was used to train, validate, and test our algorithm; data from 20% of patients were reserved for testing. An external evaluation set with images from 508 patients was used to further validate our findings. The proposed method consistently outperformed other state-of-the art architectures achieving a test per patient area under the receiver operating characteristic curve (AUC-ROC) of 0.87. Performance was comparable to expert colposcopy with a test sensitivity and specificity of 0.94 (p = 0.3) and 0.58 (p = 1.0), respectively. Patients with recurrent human papillomavirus (HPV) infections are at a higher risk of developing cervical cancer. Thus, we sought to incorporate HPV DNA test results as a feature to inform prediction. We found that incorporating patient HPV status improved test specificity to 0.71 at a sensitivity of 0.94.

Cervical cancer prevention in El Salvador: A prospective evaluation of screening and triage strategies incorporating high-resolution microendoscopy to detect cervical precancer.

Cervical cancer remains a leading cause of cancer death for women in low- and middle-income countries. The goal of our study was to evaluate screening and triage strategies, including high-resolution microendoscopy (HRME), to detect cervical abnormalities concerning for precancer at the point of care. Women (n = 1824) were enrolled at the Instituto de Cáncer de El Salvador. All underwent screening by both human papillomavirus (HPV) testing using careHPV and visual inspection with acetic acid (VIA). Screen-positives, along with 10% of screen-negatives, were invited to return for a follow-up examination that included triage with VIA, colposcopy and HRME imaging. Biopsies were taken of any abnormalities identified. If no abnormalities were identified, then the worst scoring site by HRME was biopsied. The sensitivities of HPV testing and VIA to screen for cervical intraepithelial neoplasia Grade 2 or more severe diagnoses (CIN2+) were 82.1% and 75% (P = .77), while the specificities were 90.4% and 80.9% (P < .001), respectively. The sensitivities of VIA, colposcopy and HRME as triage tests for CIN2+ were 82.1%, 82.1% and 71.4%, respectively (P ≥ .38). HRME had a significantly higher specificity (66.7%) than VIA (51.9%) (P < .001) and colposcopy (53.3%) (P < .001). When evaluating different theoretical screening and triage strategies, screening with HPV testing followed by triage with HRME would result in more women receiving appropriate care (97%) compared to screening with VIA (75%) or HPV alone (90%). Our findings demonstrate that screening with HPV is superior to VIA, and that triage with HRME imaging increases the specificity of detecting CIN2+ at the point of care in a low-resource setting.

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

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 ex vivo and in vivo 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.

Low-cost, high-resolution imaging for detecting cervical precancer in medically-underserved areas of Texas.

OBJECTIVE: Cervical cancer rates in the United States have declined since the 1940's, however, cervical cancer incidence remains elevated in medically-underserved areas, especially in the Rio Grande Valley (RGV) along the Texas-Mexico border. High-resolution microendoscopy (HRME) is a low-cost, in vivo imaging technique that can identify high-grade precancerous cervical lesions (CIN2+) at the point-of-care. The goal of this study was to evaluate the performance of HRME in medically-underserved areas in Texas, comparing results to a tertiary academic medical center. METHODS: HRME was evaluated in five different outpatient clinical settings, two in Houston and three in the RGV, with medical providers of varying skill and training. Colposcopy, followed by HRME imaging, was performed on eligible women. The sensitivity and specificity of traditional colposcopy and colposcopy followed by HRME to detect CIN2+ were compared and HRME image quality was evaluated. RESULTS: 174 women (227 cervical sites) were included in the final analysis, with 12% (11% of cervical sites) diagnosed with CIN2+ on histopathology. On a per-site basis, a colposcopic impression of low-grade precancer or greater had a sensitivity of 84% and a specificity of 45% to detect CIN2+. While there was no significant difference in sensitivity (76%, p = 0.62), the specificity when using HRME was significantly higher than that of traditional colposcopy (56%, p = 0.01). There was no significant difference in HRME image quality between clinical sites (p = 0.77) or medical providers (p = 0.33). CONCLUSIONS: HRME imaging increased the specificity for detecting CIN2+ when compared to traditional colposcopy. HRME image quality remained consistent across different clinical settings.

Caregiver perceptions of child nutritional status in Magallanes, Chile.

BACKGROUND: We aimed to identify risk factors for childhood overweight and obesity and the accuracy of caregivers'€™ perceptions of their child's nutritional status in the Magallanes region, Patagonia, Chile. METHODS: Heights and weights of children attending day care centers and elementary schools were collected and caregivers completed questionnaires regarding their child's health and behavior. The child's nutritional status was diagnosed using the 2006 WHO Child Growth Standards (for children under age 6) and the CDC 2000 Growth Charts (for children age 6 and older). Logistic regression was used to evaluate factors related to childhood overweight/obesity and weight underestimation by caregivers of overweight or obese children. RESULTS: Of the 795 children included in the study, 247 (31.1%) were overweight and 223 (28.1%) were obese. Risk factors for overweight/obesity included younger age and being perceived to eat more than normal by the caregiver. Caregivers were less likely to underestimate their child's weight if the child was older or if the caregiver believed the child ate more than a normal amount. CONCLUSIONS: There is a high prevalence of overweight and obesity among children in Magallanes and the majority of caregivers underestimate the extent of the problem in their children.

Multiphoton microscopy of cleared mouse brain expressing YFP.

Multiphoton microscopy of intrinsic fluorescence and second harmonic generation (SHG) of whole mouse organs is made possible by optically clearing the organ before imaging.(1,2) However, for organs that contain fluorescent proteins such as GFP and YFP, optical clearing protocols that use methanol dehydration and clear using benzyl alcohol:benzyl benzoate (BABB) while unprotected from light(3) do not preserve the fluorescent signal. The protocol presented here is a novel way in which to perform whole organ optical clearing on mouse brain while preserving the fluorescence signal of YFP expressed in neurons. Altering the optical clearing protocol such that the organ is dehydrated using an ethanol graded series has been found to reduce the damage to the fluorescent proteins and preserve their fluorescent signal for multiphoton imaging.(4) Using an optimized method of optical clearing with ethanol-based dehydration and clearing by BABB while shielded from light, we show high-resolution multiphoton images of yellow fluorescent protein (YFP) expression in the neurons of a mouse brain more than 2 mm beneath the tissue surface.

Multiphoton microscopy of cleared mouse organs.

Typical imaging depths with multiphoton microscopy (MPM) are limited to less than 300 mum in many tissues due to light scattering. Optical clearing significantly reduces light scattering by replacing water in the organ tissue with a fluid having a similar index of refraction to that of proteins. We demonstrate MPM of intact, fixed, cleared mouse organs with penetration depths and fields of view in excess of 2 mm. MPM enables the creation of large 3-D data sets with flexibility in pixel format and ready access to intrinsic fluorescence and second-harmonic generation. We present high-resolution images and 3-D image stacks of the brain, small intestine, large intestine, kidney, lung, and testicle with image sizes as large as 4,096 x 4,096 pixels.