Objective To measure the performance of smart phone applications which evaluate photographs of skin lesions and provide the user feedback as to their likelihood of malignancy. Design Case-control diagnostic accuracy study Setting Academic dermatology department Participants Digital clinical images of pigmented cutaneous lesions (60 melanoma cases and 128 benign lesion controls), all with histologic diagnosis rendered by a board-certified dermatopathologist, obtained prior to biopsy in patients undergoing lesion removal as part of routine care. Main Outcome Measures Sensitivity, specificity, and positive and negative predictive values of four smart phone applications designed to aid non-clinician users in determining if their skin lesion is benign or malignant. Results Sensitivity of the four tested applications ranged from 6.8% to 98.1%. Specificity ranged from 30.4% to 93.7%. Positive predictive value ranged from 33.3% to 42.1%, and negative predictive value ranged from 65.4% to 97.0%. The highest sensitivity for melanoma diagnosis was observed for an application that sends the image directly to a board-certified dermatologist for analysis and the lowest sensitivity was observed for applications that use automated algorithms to analyze images. Conclusions The performance of smart phone applications in assessing melanoma risk is highly variable, and 3 out of 4 smart phone applications incorrectly classified 30% or more of melanomas as unconcerning. Reliance on these applications, which are not subject to regulatory oversight, in lieu of medical consultation, has the potential to delay the diagnosis of melanoma and to harm users.
Highlights d Cutaneous TRPV1 + neuron activation is sufficient to initiate type 17 inflammation d Cutaneous TRPV1 + neuron activation augments local host defense d Type 17 innate immunity via nerve reflex provides regional anticipatory immunity
BackgroundClinical and histopathologic assessment of pigmented skin lesions remains challenging even for experts. Differentiated and accurate noninvasive diagnostic modalities are highly desirable.ObjectiveWe sought to provide clinicians with such a tool.MethodsA 2-gene classification method based on LINC00518 and preferentially expressed antigen in melanoma (PRAME) gene expression was evaluated and validated in 555 pigmented lesions (157 training and 398 validation samples) obtained noninvasively via adhesive patch biopsy. Results were compared with standard histopathologic assessment in lesions with a consensus diagnosis among 3 experienced dermatopathologists.ResultsIn 398 validation samples (87 melanomas and 311 nonmelanomas), LINC00518 and/or PRAME detection appropriately differentiated melanoma from nonmelanoma samples with a sensitivity of 91% and a specificity of 69%. We established LINC00518 and PRAME in both adhesive patch melanoma samples and underlying formalin fixed paraffin embedded (FFPE) samples of surgically excised primary melanomas and in melanoma lymph node metastases.LimitationsThis technology cannot be used on mucous membranes, palms of hands, and soles of feet.ConclusionsThis noninvasive 2-gene pigmented lesion assay classifies pigmented lesions into melanoma and nonmelanoma groups and may serve as a tool to help with diagnostic challenges that may be inherently linked to the visual image and pattern recognition approach.
BackgroundOnly prototypes 5 years ago, high-speed, automated whole slide imaging (WSI) systems (also called digital slide systems, virtual microscopes or wide field imagers) are becoming increasingly capable and robust. Modern devices can capture a slide in 5 minutes at spatial sampling periods of less than 0.5 micron/pixel. The capacity to rapidly digitize large numbers of slides should eventually have a profound, positive impact on pathology. It is important, however, that pathologists validate these systems during development, not only to identify their limitations but to guide their evolution.MethodsThree pathologists fully signed out 25 cases representing 31 parts. The laboratory information system was used to simulate real-world sign-out conditions including entering a full diagnostic field and comment (when appropriate) and ordering special stains and recuts. For each case, discrepancies between diagnoses were documented by committee and a "consensus" report was formed and then compared with the microscope-based, sign-out report from the clinical archive.ResultsIn 17 of 25 cases there were no discrepancies between the individual study pathologist reports. In 8 of the remaining cases, there were 12 discrepancies, including 3 in which image quality could be at least partially implicated. When the WSI consensus diagnoses were compared with the original sign-out diagnoses, no significant discrepancies were found. Full text of the pathologist reports, the WSI consensus diagnoses, and the original sign-out diagnoses are available as an attachment to this publication.ConclusionThe results indicated that the image information contained in current whole slide images is sufficient for pathologists to make reliable diagnostic decisions and compose complex diagnostic reports. This is a very positive result; however, this does not mean that WSI is as good as a microscope. Virtually every slide had focal areas in which image quality (focus and dynamic range) was less than perfect. In some cases, there was evidence of over-compression and regions made "soft" by less than perfect focus. We expect systems will continue to get better, image quality and speed will continue to improve, but that further validation studies will be needed to guide development of this promising technology.
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