DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology.

Histopathology plays a critical role in the diagnosis and surgical management of cancer. However, access to histopathology services, especially frozen section pathology during surgery, is limited in resource-constrained settings because preparing slides from resected tissue is time-consuming, labor-intensive, and requires expensive infrastructure. Here, we report a deep-learning-enabled microscope, named DeepDOF-SE, to rapidly scan intact tissue at cellular resolution without the need for physical sectioning. Three key features jointly make DeepDOF-SE practical. First, tissue specimens are stained directly with inexpensive vital fluorescent dyes and optically sectioned with ultra-violet excitation that localizes fluorescent emission to a thin surface layer. Second, a deep-learning algorithm extends the depth-of-field, allowing rapid acquisition of in-focus images from large areas of tissue even when the tissue surface is highly irregular. Finally, a semi-supervised generative adversarial network virtually stains DeepDOF-SE fluorescence images with hematoxylin-and-eosin appearance, facilitating image interpretation by pathologists without significant additional training. We developed the DeepDOF-SE platform using a data-driven approach and validated its performance by imaging surgical resections of suspected oral tumors. Our results show that DeepDOF-SE provides histological information of diagnostic importance, offering a rapid and affordable slide-free histology platform for intraoperative tumor margin assessment and in low-resource settings.

Mildly dysplastic oral lesions with optically-detectable abnormalities share genetic similarities with severely dysplastic lesions.

OBJECTIVE: Optical imaging studies of oral premalignant lesions have shown that optical markers, including loss of autofluorescence and altered morphology of epithelial cell nuclei, are predictive of high-grade pathology. While these optical markers are consistently positive in lesions with moderate/severe dysplasia or cancer, they are positive only in a subset of lesions with mild dysplasia. This study compared the gene expression profiles of lesions with mild dysplasia (stratified by optical marker status) to lesions with severe dysplasia and without dysplasia. MATERIALS AND METHODS: Forty oral lesions imaged in patients undergoing oral surgery were analyzed: nine without dysplasia, nine with severe dysplasia, and 22 with mild dysplasia. Samples were submitted for high throughput gene expression analysis. RESULTS: The analysis revealed 116 genes differentially expressed among sites without dysplasia and sites with severe dysplasia; 50 were correlated with an optical marker quantifying altered nuclear morphology. Ten of 11 sites with mild dysplasia and positive optical markers (91%) had gene expression similar to sites with severe dysplasia. Nine of 11 sites with mild dysplasia and negative optical markers (82%) had similar gene expression as sites without dysplasia. CONCLUSION: This study suggests that optical imaging may help identify patients with mild dysplasia who require more intensive clinical follow-up. If validated, this would represent a significant advance in patient care for patients with oral premalignant lesions.

Deep learning extended depth-of-field microscope for fast and slide-free histology.

Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained, and imaged to determine whether surgical margins are free of tumor cells-a costly and time- and labor-intensive procedure. Here, we introduce a deep-learning extended DOF (DeepDOF) microscope to quickly image large areas of freshly resected tissue to provide histologic-quality images of surgical margins without physical sectioning. The DeepDOF microscope consists of a conventional fluorescence microscope with the simple addition of an inexpensive (less than $10) phase mask inserted in the pupil plane to encode the light field and enhance the depth-invariance of the point-spread function. When used with a jointly optimized image-reconstruction algorithm, diffraction-limited optical performance to resolve subcellular features can be maintained while significantly extending the DOF (200 µm). Data from resected oral surgical specimens show that the DeepDOF microscope can consistently visualize nuclear morphology and other important diagnostic features across highly irregular resected tissue surfaces without serial refocusing. With the capability to quickly scan intact samples with subcellular detail, the DeepDOF microscope can improve tissue sampling during intraoperative tumor-margin assessment, while offering an affordable tool to provide histological information from resected tissue specimens in resource-limited settings.

A PIK3CA transgenic mouse model with chemical carcinogen exposure mimics human oral tongue tumorigenesis.

Oral cancer causes significant global mortality and has a five-year survival rate of around 64%. Poor prognosis results from late-stage diagnosis, highlighting an important need to develop better approaches to detect oral premalignant lesions (OPLs) and identify which OPLs are at highest risk of progression to oral squamous cell carcinoma (OSCC). An appropriate animal model that reflects the genetic, histologic, immunologic, molecular and gross visual features of human OSCC would aid in the development and evaluation of early detection and risk assessment strategies. Here, we present an experimental PIK3CA + 4NQO transgenic mouse model of oral carcinogenesis that combines the PIK3CA oncogene mutation with oral exposure to the chemical carcinogen 4NQO, an alternate experimental transgenic mouse model with PIK3CA as well as E6 and E7 mutations, and an existing wild-type mouse model based on oral exposure to 4NQO alone. We compare changes in dorsal and ventral tongue gross visual appearance, histologic features and molecular biomarker expression over a time course of carcinogenesis. Both transgenic models exhibit cytological and architectural features of dysplasia that mimic human disease and exhibit slightly increased staining for Ki-67, a cell proliferation marker. The PIK3CA + 4NQO model additionally exhibits consistent lymphocytic infiltration, presents with prominent dorsal and ventral tongue tumours, and develops cancer quickly relative to the other models. Thus, the PIK3CA + 4NQO model recapitulates the multistep genetic model of human oral carcinogenesis and host immune response in carcinogen-induced tongue cancer, making it a useful resource for future OSCC studies.

Noninvasive diagnostic adjuncts for the evaluation of potentially premalignant oral epithelial lesions: current limitations and future directions.

Potentially premalignant oral epithelial lesions (PPOELs) are a group of clinically suspicious conditions, of which a small percentage will undergo malignant transformation. PPOELs are suboptimally diagnosed and managed under the current standard of care. Dysplasia is the most well-established marker to distinguish high-risk PPOELs from low-risk PPOELs, and performing a biopsy to establish dysplasia is the diagnostic gold standard. However, a biopsy is limited by morbidity, resource requirements, and the potential for underdiagnosis. Diagnostic adjuncts may help clinicians better evaluate PPOELs before definitive biopsy, but existing adjuncts, such as toluidine blue, acetowhitening, and autofluorescence imaging, have poor accuracy and are not generally recommended. Recently, in vivo microscopy technologies, such as high-resolution microendoscopy, optical coherence tomography, reflectance confocal microscopy, and multiphoton imaging, have shown promise for improving PPOEL patient care. These technologies allow clinicians to visualize many of the same microscopic features used for histopathologic assessment at the point of care.

Time course study of the antigen-specific immune response to a PLGA microparticle vaccine formulation.

Microparticle-based vaccine delivery systems are known to promote enhanced immune responses to protein antigens and can elicit TH1-biased responses when used in combination with Toll-like receptor (TLR) agonists. It is important to understand the kinetics of the immune responses to microparticle-based protein vaccines in order to predict the duration of protective immunity and to optimize prime-boost vaccination regimens. We carried out a 10-week time course study to investigate the magnitude and kinetics of the antibody and cellular immune responses to poly(lactic-co-glycolic acid) (PLGA) microparticles containing 40 µg ovalbumin (OVA) protein and 16 µg CpG-ODN adjuvant (MP/OVA/CpG) in comparison to OVA-containing microparticles, soluble OVA plus CpG, or OVA formulated with Alhydrogel(®) aluminum adjuvant. Mice vaccinated with MP/OVA/CpG developed the highest TH1-associated IgG2b and IgG2c antibody titers, while also eliciting TH2-associated IgG1 antibody titers on par with Alhydrogel(®)-formulated OVA, with all IgG subtype titers peaking at day 56. The MP/OVA/CpG vaccine also induced the highest antigen-specific splenocyte IFN-γ responses, with high levels of IFN-γ responses persisting until day 42. Thus the MP/OVA/CpG formulation produced a sustained and heightened humoral and cellular immune response, with an overall TH1 bias, while maintaining high levels of IgG1 antibody equivalent to that seen with Alhydrogel(®) adjuvant. The time course kinetics study provides a useful baseline for designing vaccination regimens for microparticle-based protein vaccines.