Daniel Gareau

Rapid Screening of Cancer Margins in Tissue with Multimodal Confocal Microscopy

BACKGROUNDnComplete and accurate excision of cancer is guided by the examination of histopathology. However, preparation of histopathology is labor intensive and slow, leading to insufficient sampling of tissue and incomplete and/or inaccurate excision of margins. We demonstrate the potential utility of multimodal confocal mosaicing microscopy for rapid screening of cancer margins, directly in fresh surgical excisions, without the need for conventional embedding, sectioning, or processing.nnnMATERIALS AND METHODSnA multimodal confocal mosaicing microscope was developed to image basal cell carcinoma margins in surgical skin excisions, with the resolution that shows nuclear detail. Multimodal contrast is with fluorescence for imaging nuclei and reflectance for cellular cytoplasm and dermal collagen. Thirty-five excisions of basal cell carcinomas from Mohs surgery were imaged, and the mosaics analyzed by comparison with the corresponding frozen pathology.nnnRESULTSnConfocal mosaics are produced in about 9 min, displaying tissue in fields of view of 12 mm with ×2 magnification. A digital staining algorithm transforms black and white contrast to purple and pink, which simulates the appearance of standard histopathology. Mosaicing enables rapid digital screening, which mimics the examination of histopathology.nnnCONCLUSIONSnMultimodal confocal mosaicing microscopy offers a technology platform to potentially enable real-time pathology at the bedside. The imaging may serve as an adjunct to conventional histopathology to expedite screening of margins and guide surgery toward more complete and accurate excision of cancer.

The tryptophan metabolism enzyme L-kynureninase is a novel inflammatory factor in psoriasis and other inflammatory diseases

BACKGROUNDnMany human diseases arise from or have pathogenic contributions from a dysregulated immune response. One pathway with immunomodulatory ability is the tryptophan metabolism pathway, which promotes immune suppression through the enzyme indoleamine 2,3-dioxygenase (IDO) and subsequent production of kynurenine. However, in patients with chronic inflammatory skin disease, such as psoriasis and atopic dermatitis (AD), another tryptophan metabolism enzyme downstream of IDO, L-kynureninase (KYNU), is heavily upregulated. The role of KYNU has not been explored in patients with these skin diseases or in general human immunology.nnnOBJECTIVEnWe sought to explore the expression and potential immunologic function of the tryptophan metabolism enzyme KYNU in inflammatory skin disease and its potential contribution to general human immunology.nnnMETHODSnPsoriatic skin biopsy specimens, as well as normal human skin, blood, and primary cells, were used to investigate the immunologic role of KYNU and tryptophan metabolites.nnnRESULTSnHere we show that KYNU(+) cells, predominantly of myeloid origin, infiltrate psoriatic lesional skin. KYNU expression positively correlates with disease severity and inflammation and is reduced on successful treatment of psoriasis or AD. Tryptophan metabolites downstream of KYNU upregulate several cytokines, chemokines, and cell adhesions. By mining data on several human diseases, we found that in patients with cancer, IDO is preferentially upregulated compared with KYNU, whereas in patients with inflammatory diseases, such as AD, KYNU is preferentially upregulated compared with IDO.nnnCONCLUSIONnOur results suggest that tryptophan metabolism might dichotomously modulate immune responses, with KYNU as a switch between immunosuppressive versus inflammatory outcomes. Although tryptophan metabolism is increased in many human diseases, how tryptophan metabolism is proceeding might qualitatively affect the immune response in patients with that disease.

Methods of Melanoma Detection.

Detection and removal of melanoma, before it has metastasized, dramatically improves prognosis and survival. The purpose of this chapter is to (1) summarize current methods of melanoma detection and (2) review state-of-the-art detection methods and technologies that have the potential to reduce melanoma mortality. Current strategies for the detection of melanoma range from population-based educational campaigns and screening to the use of algorithm-driven imaging technologies and performance of assays that identify markers of transformation. This chapter will begin by describing state-of-the-art methods for educating and increasing awareness of at-risk individuals and for performing comprehensive screening examinations. Standard and advanced photographic methods designed to improve reliability and reproducibility of the clinical examination will also be reviewed. Devices that magnify and/or enhance malignant features of individual melanocytic lesions (and algorithms that are available to interpret the results obtained from these devices) will be compared and contrasted. In vivo confocal microscopy and other cellular-level in vivo technologies will be compared to traditional tissue biopsy, and the role of a noninvasive optical biopsy in the clinical setting will be discussed. Finally, cellular and molecular methods that have been applied to the diagnosis of melanoma, such as comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH), and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), will be discussed.

Use of Digitally Stained Multimodal Confocal Mosaic Images to Screen for Nonmelanoma Skin Cancer.

ImportancenConfocal microscopy has the potential to provide rapid bedside pathologic analysis, but clinical adoption has been limited in part by the need for physician retraining to interpret grayscale images. Digitally stained confocal mosaics (DSCMs) mimic the colors of routine histologic specimens and may increase adaptability of this technology.nnnObjectivenTo evaluate the accuracy and precision of 3 physicians using DSCMs before and after training to detect basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) in Mohs micrographic surgery fresh-tissue specimens.nnnDesignnThis retrospective study used 133 DSCMs from 64 Mohs tissue excisions, which included clear margins, residual BCC, or residual SCC. Discarded tissue from Mohs surgical excisions from the dermatologic surgery units at Memorial Sloan Kettering Cancer Center and Oregon Health & Science University were collected for confocal imaging from 2006 to 2011. Final data analysis and interpretation took place between 2014 and 2016. Two Mohs surgeons and a Mohs fellow, who were blinded to the correlating gold standard frozen section diagnoses, independently reviewed the DSCMs for residual nonmelanoma skin cancer (NMSC) before and after a brief training session (about 5 minutes). The 2 assessments were separated by a 6-month washout period.nnnMain Outcomes and MeasuresnDiagnostic accuracy was characterized by sensitivity and specificity of detecting NMSC using DSCMs vs standard frozen histopathologic specimens. The diagnostic precision was calculated based on interobserver agreement and κ scores. Paired 2-sample t tests were used for comparative means analyses before and after training.nnnResultsnThe average respective sensitivities and specificities of detecting NMSC were 90% (95% CI, 89%-91%) and 79% (95% CI, 52%-100%) before training and 99% (95% CI, 99%-99%) (Pu2009=u2009.001) and 93% (95% CI, 90%-96%) (Pu2009=u2009.18) after training; for BCC, they were 83% (95% CI, 59%-100%) and 92% (95% CI, 81%-100%) before training and 98% (95% CI, 98%-98%) (Pu2009=u2009.18) and 97% (95% CI, 95%-100%) (Pu2009=u2009.15) after training; for SCC, they were 73% (95% CI, 65%-81%) and 89% (95% CI, 72%-100%) before training and 100% (Pu2009=u2009.004) and 98% (95% CI, 95%-100%) (Pu2009=u2009.21) after training. The pretraining interobserver agreement was 72% (κu2009=u20090.58), and the posttraining interobserver agreement was 98% (κu2009=u20090.97) (Pu2009=u2009.04).nnnConclusions and RelevancenDiagnostic use of DSCMs shows promising correlation to frozen histologic analysis, but image quality was affected by variations in image contrast and mosaic-stitching artifact. With training, physicians were able to read DSCMs with significantly improved accuracy and precision to detect NMSC.

Noninvasive Detection of Inflammatory Changes in White Adipose Tissue by Label-Free Raman Spectroscopy

White adipose tissue inflammation (WATi) has been linked to the pathogenesis of obesity-related diseases, including type 2 diabetes, cardiovascular disease, and cancer. In addition to the obese, a substantial number of normal and overweight individuals harbor WATi, putting them at increased risk for disease. We report the first technique that has the potential to detect WATi noninvasively. Here, we used Raman spectroscopy to detect WATi with excellent accuracy in both murine and human tissues. This is a potentially significant advance over current histopathological techniques for the detection of WATi, which rely on tissue excision and, therefore, are not practical for assessing disease risk in the absence of other identifying factors. Importantly, we show that noninvasive Raman spectroscopy can diagnose WATi in mice. Taken together, these results demonstrate the potential of Raman spectroscopy to provide objective risk assessment for future cardiometabolic complications in both normal weight and overweight/obese individuals.

Hyperspectral imaging for melanoma screening

The 5-year survival rate for patients diagnosed with Melanoma, a deadly form of skin cancer, in its latest stages is about 15%, compared to over 90% for early detection and treatment. We present an imaging system and algorithm that can be used to automatically generate a melanoma risk score to aid clinicians in the early identification of this form of skin cancer. Our system images the patients skin at a series of different wavelengths and then analyzes several key dermoscopic features to generate this risk score. We have found that shorter wavelengths of light are sensitive to information in the superficial areas of the skin while longer wavelengths can be used to gather information at greater depths. This accompanying diagnostic computer algorithm has demonstrated much higher sensitivity and specificity than the currently commercialized system in preliminary trials and has the potential to improve the early detection of melanoma.

Digital imaging biomarkers feed machine learning for melanoma screening

We developed an automated approach for generating quantitative image analysis metrics (imaging biomarkers) that are then analysed with a set of 13 machine learning algorithms to generate an overall risk score that is called a Q‐score. These methods were applied to a set of 120 “difficult” dermoscopy images of dysplastic nevi and melanomas that were subsequently excised/classified. This approach yielded 98% sensitivity and 36% specificity for melanoma detection, approaching sensitivity/specificity of expert lesion evaluation. Importantly, we found strong spectral dependence of many imaging biomarkers in blue or red colour channels, suggesting the need to optimize spectral evaluation of pigmented lesions.

Monte Carlo modeling of pigmented lesions

Colors observed in clinical dermoscopy are critical to diagnosis but the mechanisms that lead to the spectral components of diffuse reflectance are more than meets the eye: combinations of the absorption and scattering spectra of the biomolecules as well as the “structural color” effect of skin anatomy. We modeled diffuse remittance from skin based on histopathology. The optical properties of the tissue types were based on the relevant chromophores and scatterers. The resulting spectral images mimic the appearance of pigmented lesions quite well when the morphology is mathematically derived but limited when based on histopathology, raising interesting questions about the interaction between various wavelengths with various pathological anatomical features.

Line scanning, stage scanning confocal microscope (LSSSCM)

For rapid pathological assessment of large surgical tissue excisions with cellular resolution, we present a line scanning, stage scanning confocal microscope (LSSSCM). LSSSCM uses no scanning mirrors. Laser light is focused with a single cylindrical lens to a line of diffraction-limited width directly into the (Z) sample focal plane, which is parallel to and near the flattened specimen surface. Semi-confocal optical sections are derived from the linear array distribution (Y) and a single mechanical drive that moves the sample parallel to the focal plane and perpendicular to the focused line (X). LSSSCM demonstrates cellular resolution in the conditions of high nuclear density within micronodular basal cell carcinoma.

Line-scanning, stage scanning confocal microscope

We created a line-scanning, stage scanning confocal microscope as part of a new procedure: video assisted micrographic surgery (VAMS). The need for rapid pathological assessment of the tissue on the surface of skin excisions very large since there are 3.5 million new skin cancers diagnosed annually in the United States. The new design presented here is a confocal microscope without any scanning optics. Instead, a line is focused in space and the sample, which is flattened, is physically translated such that the line scans across its face in a direction perpendicular to the line its self. The line is 6mm long and the stage is capable of scanning 50 mm, hence the field of view is quite large. The theoretical diffraction-limited resolution is 0.7um lateral and 3.7um axial. However, in this preliminary report, we present initial results that are a factor of 5-7 poorer in resolution. The results are encouraging because they demonstrate that the linear array detector measures sufficient signal from fluorescently labeled tissue and also demonstrate the large field of view achievable with VAMS.