The Impact of Melanoma Imaging Biomarker Cues on Detection Sensitivity and Specificity in Melanoma versus Clinically Atypical Nevi.

Incorporation of dermoscopy and artificial intelligence (AI) is improving healthcare professionals' ability to diagnose melanoma earlier, but these algorithms often suffer from a "black box" issue, where decision-making processes are not transparent, limiting their utility for training healthcare providers. To address this, an automated approach for generating melanoma imaging biomarker cues (IBCs), which mimics the screening cues used by expert dermoscopists, was developed. This study created a one-minute learning environment where dermatologists adopted a sensory cue integration algorithm to combine a single IBC with a risk score built on many IBCs, then immediately tested their performance in differentiating melanoma from benign nevi.

Fiberoptic hemodynamic spectroscopy reveals abnormal cerebrovascular reactivity in a freely moving mouse model of Alzheimer's disease.

Many Alzheimer's disease (AD) patients suffer from altered cerebral blood flow and damaged cerebral vasculature. Cerebrovascular dysfunction could play an important role in this disease. However, the mechanism underlying a vascular contribution in AD is still unclear.

Deep learning automated pathology in ex vivo microscopy.

Standard histopathology is currently the gold standard for assessment of margin status in Mohs surgical removal of skin cancer. Ex vivo confocal microscopy (XVM) is potentially faster, less costly and inherently 3D/digital compared to standard histopathology. Despite these advantages, XVM use is not widespread due, in part, to the need for pathologists to retrain to interpret XVM images.

Deep learning-level melanoma detection by interpretable machine learning and imaging biomarker cues.

Significance: Melanoma is a deadly cancer that physicians struggle to diagnose early because they lack the knowledge to differentiate benign from malignant lesions. Deep machine learning approaches to image analysis offer promise but lack the transparency to be widely adopted as stand-alone diagnostics.

Aim: We aimed to create a transparent machine learning technology (i.

The erythema Q-score, an imaging biomarker for redness in skin inflammation.

Physician rating of cutaneous erythema is central to clinical dermatological assessment as well as quantification of outcome measures in clinical trials in a number of dermatologic conditions. However, issues with inter-rater reliability and variability in the setting of higher Fitzpatrick skin types make visual erythema assessment unreliable. We developed and validated a computer-assisted image-processing algorithm (EQscore) to reliably quantify erythema (across a range of skin types) in the dermatology clinical setting.

A 3D biofabricated cutaneous squamous cell carcinoma tissue model with multi-channel confocal microscopy imaging biomarkers to quantify antitumor effects of chemotherapeutics in tissue.

Cutaneous squamous cell carcinoma (cSCC) causes approximately 10,000 deaths annually in the U. S. Current therapies are largely ineffective against metastatic and locally advanced cSCC.

Machine Learning in Melanoma Diagnosis. Limitations About to be Overcome.

Background: Automated image classification is a promising branch of machine learning (ML) useful for skin cancer diagnosis, but little has been determined about its limitations for general usability in current clinical practice.

Objective: To determine limitations in the selection of skin cancer images for ML analysis, particularly in melanoma.

Methods: Retrospective cohort study design, including 2,849 consecutive high-quality dermoscopy images of skin tumors from 2010 to 2014, for evaluation by a ML system.

Rapid Generation of Somatic Mouse Mosaics with Locus-Specific, Stably Integrated Transgenic Elements.

In situ transgenesis methods such as viruses and electroporation can rapidly create somatic transgenic mice but lack control over copy number, zygosity, and locus specificity. Here we establish mosaic analysis by dual recombinase-mediated cassette exchange (MADR), which permits stable labeling of mutant cells expressing transgenic elements from precisely defined chromosomal loci. We provide a toolkit of MADR elements for combination labeling, inducible and reversible transgene manipulation, VCre recombinase expression, and transgenesis of human cells.

Hyperspectral imaging in automated digital dermoscopy screening for melanoma.

Objectives: Early melanoma detection decreases morbidity and mortality. Early detection classically involves dermoscopy to identify suspicious lesions for which biopsy is indicated. Biopsy and histological examination then diagnose benign nevi, atypical nevi, or cancerous growths.

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.

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.

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

Importance: Confocal 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.

Objective: To 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.

Programmable Quantitative DNA Nanothermometers.

Developing molecules, switches, probes or nanomaterials that are able to respond to specific temperature changes should prove of utility for several applications in nanotechnology. Here, we describe bioinspired strategies to design DNA thermoswitches with programmable linear response ranges that can provide either a precise ultrasensitive response over a desired, small temperature interval (±0.05 °C) or an extended linear response over a wide temperature range (e.

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.

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

Background: Many 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.

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.

Bayesian analyses demonstrate tissue blood volume is not decreased during acute sickle cell pain episodes: A preliminary study.

Background: Pain is the most common complication of Sickle Cell Disease (SCD). Tissue oximetry properties in SCD during steady state and acute pain are not well described.

Methods: This was a cross sectional study of tissue oximetry properties in individuals with SCD during steady state, acute pain and healthy controls without SCD.

Tri-modal confocal mosaics detect residual invasive squamous cell carcinoma in Mohs surgical excisions.

For rapid, intra-operative pathological margin assessment to guide staged cancer excisions, multimodal confocal mosaic scan image wide surgical margins (approximately 1 cm) with sub-cellular resolution and mimic the appearance of conventional hematoxylin and eosin histopathology (H&E). The goal of this work is to combine three confocal imaging modes: acridine orange fluorescence (AO) for labeling nuclei, eosin fluorescence (Eo) for labeling cytoplasm, and endogenous reflectance (R) for marking collagen and keratin. Absorption contrast is achieved by alternating the excitation wavelength: 488 nm (AO fluorescence) and 532 nm (Eo fluorescence).

Rapid screening of cancer margins in tissue with multimodal confocal microscopy.

Background: Complete 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.

Automated identification of epidermal keratinocytes in reflectance confocal microscopy.

Keratinocytes in skin epidermis, which have bright cytoplasmic contrast and dark nuclear contrast in reflectance confocal microscopy (RCM), were modeled with a simple error function reflectance profile: erf( ). Forty-two example keratinocytes were identified as a training set which characterized the nuclear size a = 8.6±2.

In vivo volumetric imaging of microcirculation within human skin under psoriatic conditions using optical microangiography.

Background And Objective: There is a growing body of evidence suggesting that vascular abnormalities may play crucial role in several dermatologic diseases, such as psoriasis, port wine stain, and skin cancer. To improve our understanding of vascular involvement in these skin conditions, there is a need for a non-invasive imaging modality capable of assessing 3D microcirculations within skin tissue beds in vivo. This study aims to demonstrate whether ultra-high sensitive optical microangiography (UHS-OMAG) is feasible to visualize skin microcirculations in 3D and to quantify microvascular vessel density under normal and psoriatic conditions in vivo.

Decreased conduit perfusion measured by spectroscopy is associated with anastomotic complications.

Background: Gastric conduit ischemia during esophagectomy likely contributes to high anastomotic complication rates, yet we lack a reliable method to assess gastric conduit perfusion. We hypothesize that optical fiber spectroscopy (OFS) can reliably assess conduit perfusion and that the degree of intraoperative gastric ischemia is associated with subsequent anastomotic complications.

Methods: During esophagectomy, OFS was used to measure oxygen saturation (SaO(2)) and blood volume fraction (BVF) in the distal gastric conduit at baseline and after gastric devascularization, conduit formation, and transposition.

Automated detection of malignant features in confocal microscopy on superficial spreading melanoma versus nevi.

In-vivo reflectance confocal microscopy (RCM) shows promise for the early detection of superficial spreading melanoma (SSM). RCM of SSM shows pagetoid melanocytes (PMs) in the epidermis and disarray at the dermal-epidermal junction (DEJ), which are automatically quantified with a computer algorithm that locates depth of the most superficial pigmented surface [D(SPS)(x,y)] containing PMs in the epidermis and pigmented basal cells near the DEJ. The algorithm uses 200 noninvasive confocal optical sections that image the superficial 200 μm of ten skin sites: five unequivocal SSMs and five nevi.

Optical fiber probe spectroscopy for laparoscopic monitoring of tissue oxygenation during esophagectomies.

Anastomotic complication is a major morbidity associated with esophagectomy. Gastric ischemia after conduit creation contributes to anastomotic complications, but a reliable method to assess oxygenation in the gastric conduit is lacking. We hypothesize that fiber optic spectroscopy can reliably assess conduit oxygenation, and that intraoperative gastric ischemia will correlate with the development of anastomotic complications.

In vivo reflectance confocal microscopy of shave biopsy wounds: feasibility of intraoperative mapping of cancer margins.

Background: Reflectance confocal microscopy (RCM) images skin at cellular resolution and has shown utility for the diagnosis of nonmelanoma skin cancer in vivo. Topical application of aluminium chloride (AlCl(3)) enhances contrast in RCM images by brightening nuclei.

Objectives: To investigate feasibility of RCM imaging of shave biopsy wounds using AlCl(3) as a contrast agent.