Non-invasive tools for the diagnosis of cutaneous melanoma

Review of Non-Invasive Imaging Technologies for Cutaneous Melanoma

Imaging technologies are constantly being developed to improve not only melanoma diagnosis, but also staging, treatment planning, and disease progression. We start with a description of how melanoma is characterized using histology, and then continue by discussing nearly two dozen different technologies, including systems currently used in medical practice and those in development. For each technology, we describe its method of operation, how it is or would be projected to be most commonly used in diagnosing and managing melanoma, and for systems in current use, we identify at least one current manufacturer. We also provide a table including the biomarkers identified by and main limitations associated with each technology and conclude by offering suggestions on specific characteristics that might best enhance a technology's potential for widespread clinical adoption.

Dermoscopy and reflectance confocal microscopy of solitary flat pink lesions: A new combined score to diagnose amelanotic melanoma

BACKGROUND

Differential diagnosis of amelanotic/hypomelanotic melanoma among solitary flat pink lesions is challenging, due to limited clinical and dermoscopic clues. Dermoscopy and reflectance confocal microscopy assessments improve diagnostic accuracy, but their combined capacity among solitary flat pink lesions is yet to be defined.

OBJECTIVES

To determine (i) whether diagnostic accuracy is improved with combined dermoscopy and reflectance confocal microscopy, (ii) a model to estimate probability of flat amelanotic/hypomelanotic melanoma among solitary flat pink lesions.

METHODS

A retrospective single-centre study of solitary flat pink lesions, excised for suspected malignancy between 2011 and 2022 was performed. Images were independently evaluated by two dermatologists, blinded to histopathological diagnosis. Diagnostic performance was evaluated on the receiver operating characteristic curve and the area under the curve. Predictive features were identified by univariate and multivariate logistic regression analyses. A final predictive nomogram of independent risk factors was calculated by backward likelihood ratio. Hypothesis being tested was formulated before data collection.

RESULTS

A total of 184 patients (87 females, 47.3%) were included; mean age was 57.6 years (19-95). Combined dermoscopy and reflectance confocal microscopy was more sensitive (83%, CI 69.2-92.4 and 91.5%, CI 79.6-97.6) than dermoscopy alone (76.6%, CI 62.0-87.7 and 85.1%, CI 71.7-93.8). Predictive features defined the new model, including linear irregular vessels (4.26-folds, CI 1.5-12.1), peripheral pigment network (6.07-folds, CI 1.83-20.15), remnants of pigmentation (4.3-folds, CI 1.27-14.55) at dermoscopy and atypical honeycomb (9.98-folds, CI 1.91-51.96), disarranged epidermal pattern (15.22-folds, CI 2.18-106.23), dendritic pagetoid cells in the epidermis (3.77-folds, CI 1.25-11.26), hypopigmented pagetoid cells (27.05-folds, CI 1.57-465.5), and dense and sparse nests (3.68-folds, CI 1.24-10.96) in reflectance confocal microscopy. Diagnostic accuracy of the model was high (AUC 0.91).

CONCLUSIONS

Adjunctive reflectance confocal microscopy increases diagnostic sensitivity of flat amelanotic/hypomelanotic melanoma differential diagnosis. The proposed model requires validation.

Resource Management Challenges in Rural Dermatological Care: A Mapping Review

Skin cancer prevalence in the United States is rapidly on the rise, particularly in rural communities where individuals are subjected to heavy sunlight exposure through occupations such as agricultural work and construction. These geographic regions are often lacking in dermatologic specialty care, thus increasing the disease burden of skin conditions in primary care settings. Access barriers to specialized dermatology care are exacerbated by prolonged wait times to schedule an appointment, travel demands, and a relative paucity of dermatology providers in rural areas as compared to urban areas. In rural communities, the high burden of skin diseases, the logistical challenges, and the shortage of dermatologists lead to increased reliance on primary care physicians (PCPs) for dermatological care. This review aims to identify barriers to dermatology care in rural communities, understand challenges faced by PCPs related to dermatological management, and explore modalities that are currently being used to streamline clinical workflows for PCPs. Dermatology training for PCPs consists primarily of pre-clinical exposure to the field, and it has been reported that there is a relative lack of opportunity for training to further enhance postgraduate dermatology knowledge. Recent studies demonstrate that novel educational and infrastructural support to primary care clinics has had substantial positive impacts on the ability of primary caregivers to provide accurate, cost-effective dermatologic care in addressing skin conditions, as well as increasing diagnostic confidence. Regular skin examinations, dermoscopy, and digital transformation of images are also shown to improve detection and diagnostic accuracy. Interventions like the use of smartphones, teledermatology, and dermoscopy show potential for improving care but must be thoroughly evaluated for effectiveness before widespread adoption in primary care settings.

Non-invasive infrared thermography for screening, diagnosis and monitoring of skin cancer

The incidence of skin cancer is rising continuously. The time of diagnosis is decisive for the morbidity and mortality risk of patients. An optimal screening procedure has yet to be established. Non-contact imaging methods are of great interest but have not yet been sufficiently developed and investigated for large-scale use. Compared to digital photography, infrared thermography offers the additional information of heat radiation from the skin surface, which correlates strongly with malignant changes. Literature on the current scientific status of screening, diagnosis and monitoring of skin cancer using thermographic procedures was identified in PubMed, Embase, and Google Scholar. From a technical and information technology point of view, infrared thermography is very well suited for use as a non-invasive, cost-effective, time-saving, and easy-to-use screening instrument. However, there is still a lack of reliable evidence and practical implementation in 3D systems suitable for mass use. Research in this area should be intensified in order to develop, test and establish applicable systems on a large scale.

Assessing spatial distribution of bioindicator elements in various cutaneous tumors using correlative imaging with laser-ablation-based analytical methods

Correlative imaging of cutaneous tumors provides additional information to the standard histopathologic examination. However, the joint progress in the establishment of analytical techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) and Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) in clinical practice is still limited. Their combination provides complementary information as it is also shown in our study in terms of major biotic (Ca, Mg, and P) and trace (Cu and Zn) elements. To elucidate changes in the elemental composition in tumors, we have compiled a set of malignant tumors (Squamous Cell Carcinoma, Basal Cell Carcinoma, Malignant Melanoma, and Epithelioid Angiosarcoma), one benign tumor (Pigmented Nevus) and one healthy-skin sample. The data processing was based on a methodological pipeline involving binary image registration and affine transformation. Thus, our paper brings a feasibility study of a practical methodological concept that enables us to compare LIBS and LA-ICP-MS results despite the mutual spatial distortion of original elemental images. Moreover, we also show that LIBS could be a sufficient pre-screening method even for a larger number of samples according to the speed and reproducibility of the analyses. Whereas LA-ICP-MS could serve as a ground truth and reference technique for preselected samples.

Noninvasive Technologies for the Diagnosis of Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis

Early cutaneous squamous cell carcinoma (cSCC) diagnosis is essential to initiate adequate targeted treatment. Noninvasive diagnostic technologies could overcome the need of multiple biopsies and reduce tumor recurrence. To assess performance of noninvasive technologies for cSCC diagnostics, 947 relevant records were identified through a systematic literature search. Among the 15 selected studies within this systematic review, 7 were included in the meta-analysis, comprising of 1144 patients, 224 cSCC lesions, and 1729 clinical diagnoses. Overall, the sensitivity values are 92% (95% confidence interval [CI] = 86.6-96.4%) for high-frequency ultrasound, 75% (95% CI = 65.7-86.2%) for optical coherence tomography, and 63% (95% CI = 51.3-69.1%) for reflectance confocal microscopy. The overall specificity values are 88% (95% CI = 82.7-92.5%), 95% (95% CI = 92.7-97.3%), and 96% (95% CI = 94.8-97.4%), respectively. Physician's expertise is key for high diagnostic performance of investigated devices. This can be justified by the provision of additional tissue information, which requires physician interpretation, despite insufficient standardized diagnostic criteria. Furthermore, few deep learning studies were identified. Thus, integration of deep learning into the investigated devices is a potential investigating field in cSCC diagnosis.

Skin lesion segmentation using deep learning algorithm with ant colony optimization

BACKGROUND

Segmentation of skin lesions remains essential in histological diagnosis and skin cancer surveillance. Recent advances in deep learning have paved the way for greater improvements in medical imaging. The Hybrid Residual Networks (ResUNet) model, supplemented with Ant Colony Optimization (ACO), represents the synergy of these improvements aimed at improving the efficiency and effectiveness of skin lesion diagnosis.

OBJECTIVE

This paper seeks to evaluate the effectiveness of the Hybrid ResUNet model for skin lesion classification and assess its impact on optimizing ACO performance to bridge the gap between computational efficiency and clinical utility.

METHODS

The study used a deep learning design on a complex dataset that included a variety of skin lesions. The method includes training a Hybrid ResUNet model with standard parameters and fine-tuning using ACO for hyperparameter optimization. Performance was evaluated using traditional metrics such as accuracy, dice coefficient, and Jaccard index compared with existing models such as residual network (ResNet) and U-Net.

RESULTS

The proposed hybrid ResUNet model exhibited excellent classification accuracy, reflected in the noticeable improvement in all evaluated metrics. His ability to describe complex lesions was particularly outstanding, improving diagnostic accuracy. Our experimental results demonstrate that the proposed Hybrid ResUNet model outperforms existing state-of-the-art methods, achieving an accuracy of 95.8%, a Dice coefficient of 93.1%, and a Jaccard index of 87.5.

CONCLUSION

The addition of ResUNet to ACO in the proposed Hybrid ResUNet model significantly improves the classification of skin lesions. This integration goes beyond traditional paradigms and demonstrates a viable strategy for deploying AI-powered tools in clinical settings.

FUTURE WORK

Future investigations will focus on increasing the version's abilities by using multi-modal imaging information, experimenting with alternative optimization algorithms, and comparing real-world medical applicability. There is also a promising scope for enhancing computational performance and exploring the model's interpretability for more clinical adoption.

Classification of melanocytic lesions using direct illumination multispectral imaging

With rising melanoma incidence and mortality, early detection and surgical removal of primary lesions is essential. Multispectral imaging is a new, non-invasive technique that can facilitate skin cancer detection by measuring the reflectance spectra of biological tissues. Currently, incident illumination allows little light to be reflected from deeper skin layers due to high surface reflectance. A pilot study was conducted at the University Hospital Basel to evaluate, whether multispectral imaging with direct light coupling could extract more information from deeper skin layers for more accurate dignity classification of melanocytic lesions. 27 suspicious pigmented lesions from 23 patients were included (6 melanomas, 6 dysplastic nevi, 12 melanocytic nevi, 3 other). Lesions were imaged before excision using a prototype snapshot mosaic multispectral camera with incident and direct illumination with subsequent dignity classification by a pre-trained multispectral image analysis model. Using incident light, a sensitivity of 83.3% and a specificity of 58.8% were achieved compared to dignity as determined by histopathological examination. Direct light coupling resulted in a superior sensitivity of 100% and specificity of 82.4%. Convolutional neural network classification of corresponding red, green, and blue lesion images resulted in 16.7% lower sensitivity (83.3%, 5/6 malignant lesions detected) and 20.9% lower specificity (61.5%) compared to direct light coupling with multispectral image classification. Our results show that incorporating direct light multispectral imaging into the melanoma detection process could potentially increase the accuracy of dignity classification. This newly evaluated illumination method could improve multispectral applications in skin cancer detection. Further larger studies are needed to validate the camera prototype.

Reflectance confocal microscopy versus dermoscopy for the diagnosis of cutaneous melanoma: a head-to-head comparative meta-analysis

This meta-analysis aimed to evaluate the comparative diagnostic performance of reflectance confocal microscopy (RCM) and dermoscopy in detecting cutaneous melanoma patients. An extensive search was conducted in the PubMed and Embase databases to identify available publications up to December 2023. Studies were included if they evaluated the diagnostic performance of RCM and dermoscopy in patients with cutaneous melanoma. The quality of the included studies was assessed using the Quality Assessment of Diagnostic Performance Studies (QUADAS-2) tool. A total of 14 articles involving 2013 patients were included in the meta-analysis. The overall sensitivity of RCM was 0.94 [95% confidence interval (CI), 0.87-0.98], while the overall sensitivity of dermoscopy was 0.84 (95% CI, 0.71-0.95). These results suggested that RCM has a similar level of sensitivity compared with dermoscopy ( P  = 0.15). In contrast, the overall specificity of RCM was 0.76 (95% CI, 0.67-0.85), while the overall specificity of dermoscopy was 0.47 (95% CI, 0.31-0.63). The results indicated that RCM appears to have a higher specificity in comparison to dermoscopy ( P  < 0.01). Our meta-analysis indicates that RCM demonstrates superior specificity and similar sensitivity to dermoscopy in detecting cutaneous melanoma patients. The high heterogeneity, however, may impact the evidence of the current study, further larger sample prospective research is required to confirm these findings.

Quantitative melanoma diagnosis using spectral phasor analysis of hyperspectral imaging from label-free slices

Introduction

Melanoma diagnosis traditionally relies on microscopic examination of hematoxylin and eosin (H&E) slides by dermatopathologists to search for specific architectural and cytological features. Unfortunately, no single molecular marker exists to reliably differentiate melanoma from benign lesions such as nevi. This study explored the potential of autofluorescent molecules within tissues to provide molecular fingerprints indicative of degenerated melanocytes in melanoma.

Methods

Using hyperspectral imaging (HSI) and spectral phasor analysis, we investigated autofluorescence patterns in melanoma compared to intradermal nevi. Using UV excitation and a commercial spectral confocal microscope, we acquired label-free HSI data from the whole-slice samples.

Results

Our findings revealed distinct spectral phasor distributions between melanoma and intradermal nevi, with melanoma displaying a broader phasor phase distribution, signifying a more heterogeneous autofluorescence pattern. Notably, longer wavelengths associated with larger phases correlated with regions identified as melanoma by expert dermatopathologists using H&E staining. Quantitative analysis of phase and modulation histograms within the phasor clusters of five melanomas (with Breslow thicknesses ranging from 0.5 mm to 6 mm) and five intradermal nevi consistently highlighted differences between the two groups. We further demonstrated the potential for the discrimination of several melanocytic lesions using center-of-mass comparisons of phase and modulation variables. Remarkably, modulation versus phase center of mass comparisons revealed strong statistical significance among the groups. Additionally, we identified the molecular endogenous markers responsible for tissue autofluorescence, including collagen, elastin, NADH, FAD, and melanin. In melanoma, autofluorescence is characterized by a higher phase contribution, indicating an increase in FAD and melanin in melanocyte nests. In contrast, NADH, elastin, and collagen dominate the autofluorescence of the nevus.

Discussion

This work underscores the potential of autofluorescence and HSI-phasor analysis as valuable tools for quantifying tissue molecular fingerprints, thereby supporting more effective and quantitative melanoma diagnosis.

Nanodelivery systems for cutaneous melanoma treatment

Cutaneous melanoma (CM) is a multifactorial disease whose treatment still presents challenges: the rapid progression to advanced CM, which leads to frequent recurrences even after surgical excision and, notably, the low response rates and resistance to the available therapies, particularly in the case of unresectable metastatic CM. Thereby, alternative innovative therapeutic approaches for CM continue to be searched. In this review we discuss relevant preclinical research studies, and provide a broad-brush analysis of patents and clinical trials which involve the application of nanotechnology-based delivery systems in CM therapy. Nanodelivery systems have been developed for the delivery of anticancer biomolecules to CM, which can be administered by different routes. Overall, nanosystems could promote technological advances in several therapeutic modalities and can be used in combinatorial therapies. Nevertheless, the results of these preclinical studies have not been translated to clinical applications. Thus, concerted and collaborative research studies involving basic, applied, translational, and clinical scientists need to be performed to allow the development of effective and safe nanomedicines to treat CM.

Infrared Macrothermoscopy Patterns-A New Category of Dermoscopy

(1) Background: The authors developed a new non-invasive dermatological infrared macroimaging analysis technique (MacroIR) that evaluates microvascular, inflammatory, and metabolic changes that may be dermoscopy complimentary, by analyzing different skin and mucosal lesions in a combined way-naked eye, polarized light dermatoscopy (PLD), and MacroIR-and comparing results; (2) Methods: ten cases were evaluated using a smartphone coupled with a dermatoscope and a macro lens integrated far-infrared transducer into specific software to capture and organize high-resolution images in different electromagnetic spectra, and then analyzed by a dermatologist; (3) Results: It was possible to identify and compare structures found in two dermoscopic forms. Visual anatomical changes were correlated with MacroIR and aided skin surface dermatological analysis, presenting studied area microvascular, inflammatory, and metabolic data. All MacroIR images correlated with PLD, naked eye examination, and histopathological findings; (4) Conclusion: MacroIR and clinic dermatologist concordance rates were comparable for all dermatological conditions in this study. MacroIR imaging is a promising method that can improve dermatological diseases diagnosis. The observations are preliminary and require further evaluation in larger studies.

Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasive melanoma, 88 melanoma in situ, 115 dysplastic naevi, and 48 non-dysplastic naevi. The study included a training set of 358,800 pixels and a validation set of 7,313 pixels, which was then tested with a training set of 24,375 pixels. The majority vote classification achieved high overall sensitivity of 95% and a specificity of 92% (95% confidence interval (95% CI) 0.024-0.029) in differentiating malignant from benign lesions. In the pixel-wise classification, the overall sensitivity and specificity were both 82% (95% CI 0.005-0.005). When divided into 4 subgroups, the diagnostic accuracy was lower. Hyperspectral imaging provides high sensitivity and specificity in distinguishing between naevi and melanoma. This novel method still needs further validation.

Real-time, in vivo skin cancer triage by laser-induced plasma spectroscopy combined with a deep learning-based diagnostic algorithm

BACKGROUND

Although various skin cancer detection devices have been proposed, most of them are not used owing to their insufficient diagnostic accuracies. Laser-induced plasma spectroscopy (LIPS) can noninvasively extract biochemical information of skin lesions using an ultrashort pulsed laser.

OBJECTIVE

To investigate the diagnostic accuracy and safety of real-time noninvasive in vivo skin cancer diagnostics utilizing nondiscrete molecular LIPS combined with a deep neural network (DNN)-based diagnostic algorithm.

METHODS

In vivo LIPS spectra were acquired from 296 skin cancers (186 basal cell carcinomas, 96 squamous cell carcinomas, and 14 melanomas) and 316 benign lesions in a multisite clinical study. The diagnostic performance was validated using 10-fold cross-validations.

RESULTS

The sensitivity and specificity for differentiating skin cancers from benign lesions using LIPS and the DNN-based algorithm were 94.6% (95% CI: 92.0%-97.2%) and 88.9% (95% CI: 85.5%-92.4%), respectively. No adverse events, including macroscopic or microscopic visible marks or pigmentation due to laser irradiation, were observed.

LIMITATIONS

The diagnostic performance was evaluated using a limited data set. More extensive clinical studies are needed to validate these results.

CONCLUSIONS

This LIPS system with a DNN-based diagnostic algorithm is a promising tool to distinguish skin cancers from benign lesions with high diagnostic accuracy in real clinical settings.

Hyperspectral and multispectral image processing for gross-level tumor detection in skin lesions: a systematic review

SIGNIFICANCE

Skin cancer is one of the most prevalent cancers worldwide. In the advent of medical digitization and telepathology, hyper/multispectral imaging (HMSI) allows for noninvasive, nonionizing tissue evaluation at a macroscopic level.

AIM

We aim to summarize proposed frameworks and recent trends in HMSI-based classification and segmentation of gross-level skin tissue.

APPROACH

A systematic review was performed, targeting HMSI-based systems for the classification and segmentation of skin lesions during gross pathology, including melanoma, pigmented lesions, and bruises. The review adhered to the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. For eligible reports published from 2010 to 2020, trends in HMSI acquisition, preprocessing, and analysis were identified.

RESULTS

HMSI-based frameworks for skin tissue classification and segmentation vary greatly. Most reports implemented simple image processing or machine learning, due to small training datasets. Methodologies were evaluated on heavily curated datasets, with the majority targeting melanoma detection. The choice of preprocessing scheme influenced the performance of the system. Some form of dimension reduction is commonly applied to avoid redundancies that are inherent in HMSI systems.

CONCLUSIONS

To use HMSI for tumor margin detection in practice, the focus of system evaluation should shift toward the explainability and robustness of the decision-making process.

Novel Non-Invasive Quantification and Imaging of Eumelanin and DHICA Subunit in Skin Lesions by Raman Spectroscopy and MCR Algorithm: Improving Dysplastic Nevi Diagnosis

Malignant melanoma (MM) is the most aggressive form of skin cancer, and around 30% of them may develop from pre-existing dysplastic nevi (DN). Diagnosis of DN is a relevant clinical challenge, as these are intermediate lesions between benign and malignant tumors, and, up to date, few studies have focused on their diagnosis. In this study, the accuracy of Raman spectroscopy (RS) is assessed, together with multivariate analysis (MA), to classify 44 biopsies of MM, DN and compound nevus (CN) tumors. For this, we implement a novel methodology to non-invasively quantify and localize the eumelanin pigment, considered as a tumoral biomarker, by means of RS imaging coupled with the Multivariate Curve Resolution-Alternative Least Squares (MCR-ALS) algorithm. This represents a step forward with respect to the currently established technique for melanin analysis, High-Performance Liquid Chromatography (HPLC), which is invasive and cannot provide information about the spatial distribution of molecules. For the first time, we show that the 5, 6-dihydroxyindole (DHI) to 5,6-dihydroxyindole-2-carboxylic acid (DHICA) ratio is higher in DN than in MM and CN lesions. These differences in chemical composition are used by the Partial Least Squares-Discriminant Analysis (PLS-DA) algorithm to identify DN lesions in an efficient, non-invasive, fast, objective and cost-effective method, with sensitivity and specificity of 100% and 94.1%, respectively.

In Vivo Melanoma Cell Morphology Reflects Molecular Signature and Tumor Aggressiveness

Melanoma is the deadliest type of skin cancer, characterized by high cellular heterogeneity which contributes to therapy resistance and unpredictable disease outcome. Recently, by correlating Reflectance-Confocal-Microscopy (RCM) morphology with histopathological type, we identified four distinct melanoma-subtypes: dendritic-cell (DC), round-cell (RC), dermal-nest (DN), and combined-type (CT) melanomas. In the present study, each RCM-melanoma subtype expressed a specific biomolecular profile and biological behavior in vitro. Markers of tumor aggressiveness, including Ki67, MERTK, nestin and stemness markers, were highest in the most invasive CT and DN melanomas, as compared to DC and RC. This was also confirmed in multicellular tumor spheroids. Transcriptomic analysis showed a modulation of cancer progression-associated genes from DC to CT melanomas. The switch from E- to N-cadherin expression proved the epithelial-to-mesenchymal transition from DC to CT subtypes. The DN melanoma was predominantly located in the dermis, as also shown in skin reconstructs. It displayed a unique behavior and a molecular profile associated with a high degree of aggressiveness. Altogether, our results demonstrate that each RCM-melanoma subtype has a distinct biological and gene expression profile, related to tumor aggressiveness, confirming that RCM can be a dependable tool for in vivo detecting different types of melanoma and for early diagnostic screening.

Reverse Iontophoretic Extraction of Skin Cancer-Related Biomarkers

Non-invasive methods for early diagnosis of skin cancer are highly valued. One possible approach is to monitor relevant biomarkers such as tryptophan (Trp) and kynurenine (Kyn), on the skin surface. The primary aim of this in vitro investigation was, therefore, to examine whether reverse iontophoresis (RI) can enhance the extraction of Trp and Kyn, and to demonstrate how the Trp/Kyn ratio acquired from the skin surface reflects that in the epidermal tissue. The study also explored whether the pH of the receiver medium impacted on extraction efficiency, and assessed the suitability of a bicontinuous cubic liquid crystal as an alternative to a simple buffer solution for this purpose. RI substantially enhanced the extraction of Trp and Kyn, in particular towards the cathode. The Trp/Kyn ratio obtained on the surface matched that in the viable skin. Increasing the receiver solution pH from 4 to 9 improved extraction of both analytes, but did not significantly change the Trp/Kyn ratio. RI extraction of Trp and Kyn into the cubic liquid crystal was comparable to that achieved with simple aqueous receiver solutions. We conclude that RI offers a potential for non-invasive sampling of low-molecular weight biomarkers and further investigations in vivo are therefore warranted.

Emerging Minimally Invasive Technologies for the Detection of Skin Cancer

With the increasing incidence of skin cancer, many noninvasive technologies to detect its presence have been developed. This review focuses on reflectance confocal microscopy (RCM), optical coherence tomography (OCT), high-frequency ultrasound (HFUS), electrical impedance spectroscopy (EIS), pigmented lesion assay (PLA), and Raman spectroscopy (RS) and discusses the basic principle, clinical applications, advantages, and disadvantages of each technology. RCM provides high cellular resolution and has high sensitivity and specificity for the diagnosis of skin cancer. OCT provides lower resolution than RCM, although its evaluable depth is deeper than that of RCM. RCM and OCT may be useful in reducing the number of unnecessary biopsies, evaluating the tumor margin, and monitoring treatment response. HFUS can be mainly used to delineate tumor depths or margins and monitor the treatment response. EIS provides high sensitivity but low specificity for the diagnosis of skin malignancies. PLA, which is based on the genetic information of lesions, is applicable for the detection of melanoma with high sensitivity and moderate-to-high specificity. RS showed high accuracy for the diagnosis of skin cancer, although more clinical studies are required. Advances in these technologies for the diagnosis of skin cancer can lead to the realization of optimized and individualized treatments.

In vivo two-photon-excited cellular fluorescence of melanin, NAD(P)H, and keratin enables an accurate differential diagnosis of seborrheic keratosis and pigmented cutaneous melanoma

SIGNIFICANCE

Seborrheic keratoses (SKs) are harmless pigmented skin lesions (PSLs) that may be confused clinically not only with other benign conditions but also with cutaneous melanoma (CM). As SKs are one of the most common neoplasms in adults, the importance of their correct diagnosis is high. Misclassifying SK as malignant is not rare and leads to a high number of unnecessary biopsies. On the other hand, misdiagnosing CM as SK may have a large impact on prognosis or therapy.

AIM

In the non-invasive technique of dermatofluoroscopy, the fluorophores in melanocytes and keratinocytes are excited in vivo with nanosecond laser pulses and the resulting spectrally resolved, melanin-dominated fluorescence signals are used to differentiate between pigmented benign lesions and CM.

APPROACH

In this single-center, non-interventional study, 33 PSLs of 20 patients were scanned with dermatofluoroscopy in vivo. For all included cases, dermatofluoroscopic signals were compared to pathology classification.

RESULTS

The characteristic spectral features of SK were identified, where the signals are dominated by keratin, NAD(P)H, and melanin. The fluorescence spectra of SKs differed substantially from those of CM: a characteristic spectrum of SK has been identified in 27 of 28 SKs.

CONCLUSIONS

The high-accuracy differential diagnosis between CM and SK is possible with dermatofluoroscopy.

Clinical performance of a novel hyperspectral imaging device for cutaneous melanoma and pigmented skin lesions in Caucasian skin

BACKGROUND

The quest for diagnostic tools for the detection of cutaneous malignant melanoma (cMM) is ongoing. A challenge in cMM care is not overlooking cMM at an early stage, while simultaneously avoiding unnecessary biopsies or excisions of benign pigmented skin lesions (PSLs). A novel hyperspectral imaging (HSI) device is shown to have potential for differentiating equivocal PSLs in Asian skin types. Our objective was to assess the accuracy of the HSI device in distinguishing between cMM and benign PSLs in patients with Caucasian skin types.

METHODS

Patients with Caucasian skin types (Fitzpatrick I-II), enrolled for excisional biopsies of PSLs were included and examined using the HSI device. The discrimination index (DI) was used to demonstrate the sensitivity (SE) and specificity (SP) in comparison with the re-evaluated histopathology diagnoses.

RESULTS

In 186 patients, 202 pigmented skin lesions were included. The sensitivity to detect cMM was 96.7% (87/90), and the specificity for benign lesions was 42.1% (45/107). The AUC was 0.800 (95% confidence interval (CI): 0.740-0.861).

CONCLUSIONS

Our novel HSI device showed a high sensitivity in detecting malignant lesions in patients with Caucasian skin types. Compared with analogous technologies, as multispectral imaging or electrical impedance spectroscopy, our device showed similar or better accuracy in differentiating cMM from benign PSLs. Therefore, it might be a useful clinical tool in skin types I-IV and where further triage of pigmented skin lesions is important.

Man against machine reloaded: performance of a market-approved convolutional neural network in classifying a broad spectrum of skin lesions in comparison with 96 dermatologists working under less artificial conditions

BACKGROUND

Convolutional neural networks (CNNs) efficiently differentiate skin lesions by image analysis. Studies comparing a market-approved CNN in a broad range of diagnoses to dermatologists working under less artificial conditions are lacking.

MATERIALS AND METHODS

One hundred cases of pigmented/non-pigmented skin cancers and benign lesions were used for a two-level reader study in 96 dermatologists (level I: dermoscopy only; level II: clinical close-up images, dermoscopy, and textual information). Additionally, dermoscopic images were classified by a CNN approved for the European market as a medical device (Moleanalyzer Pro, FotoFinder Systems, Bad Birnbach, Germany). Primary endpoints were the sensitivity and specificity of the CNN's dichotomous classification in comparison with the dermatologists' management decisions. Secondary endpoints included the dermatologists' diagnostic decisions, their performance according to their level of experience, and the CNN's area under the curve (AUC) of receiver operating characteristics (ROC).

RESULTS

The CNN revealed a sensitivity, specificity, and ROC AUC with corresponding 95% confidence intervals (CI) of 95.0% (95% CI 83.5% to 98.6%), 76.7% (95% CI 64.6% to 85.6%), and 0.918 (95% CI 0.866-0.970), respectively. In level I, the dermatologists' management decisions showed a mean sensitivity and specificity of 89.0% (95% CI 87.4% to 90.6%) and 80.7% (95% CI 78.8% to 82.6%). With level II information, the sensitivity significantly improved to 94.1% (95% CI 93.1% to 95.1%; P < 0.001), while the specificity remained unchanged at 80.4% (95% CI 78.4% to 82.4%; P = 0.97). When fixing the CNN's specificity at the mean specificity of the dermatologists' management decision in level II (80.4%), the CNN's sensitivity was almost equal to that of human raters, at 95% (95% CI 83.5% to 98.6%) versus 94.1% (95% CI 93.1% to 95.1%); P = 0.1. In contrast, dermatologists were outperformed by the CNN in their level I management decisions and level I and II diagnostic decisions. More experienced dermatologists frequently surpassed the CNN's performance.

CONCLUSIONS

Under less artificial conditions and in a broader spectrum of diagnoses, the CNN and most dermatologists performed on the same level. Dermatologists are trained to integrate information from a range of sources rendering comparative studies that are solely based on one single case image inadequate.

Photoacoustic tomography for assessment and quantification of cutaneous and metastatic malignant melanoma - A systematic review

BACKGROUND

Photoacoustic tomography (PAT) is an emerging noninvasive imaging technique combining high sensitivity optical absorption contrast, such as melanin, with high-resolution ultrasound for deep tissue imaging. The ability of PAT to provide real-time images of skin structures at depth has been studied for diagnosis of primary and metastatic malignant melanoma (MM).

OBJECTIVE

To provide an overview of the rapidly expanding clinical use of PAT for determination of melanoma thickness and architecture, visualization of metastases in lymph nodes and detection of circulating melanoma cells.

METHODS

Medline, PubMed, EMBASE, Web of Science, Google Scholar, and Cochrane Library were searched for papers using PAT to assess cutaneous malignant melanoma and melanoma metastases in humans or human specimens.

RESULTS

The research resulted in 14 articles which met the search criteria.

CONCLUSIONS

Results from current studies suggest that PAT is a promising tool for assessing both primary and metastatic malignant melanoma in the clinic. The potential of PAT to noninvasively visualize tumour boundaries, as well as assist in the evaluation of metastatic status, could facilitate more effective treatment, resulting in better clearance and reducing the need for additional biopsies. However, larger and methodologically sound studies are warranted.

Technical Note: Noninvasive mid-IR fiber-optic evanescent wave spectroscopy (FEWS) for early detection of skin cancers

PURPOSE

Melanoma is the most lethal of the three primary skin cancers, including also basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), which are less lethal. The accepted diagnosis process involves manually observing a suspicious lesion through a Dermascope (i.e., a magnifying glass), followed by a biopsy. This process relies on the skill and the experience of a dermatologist. However, to the best of our knowledge, there is no accepted automatic, noninvasive, and rapid method for the early detection of the three types of skin cancer, distinguishing between them and noncancerous lesions, and identifying each of them. It is our aim to develop such a system.

METHODS

We developed a fiber-optic evanescent wave spectroscopy (FEWS) system based on middle infrared (mid-IR) transmitting AgClBr fibers and a Fourier-transform infrared spectrometer (FTIR). We used the system to perform mid-IR spectral measurements on suspicious lesions in 90 patients, before biopsy, in situ, and in real time. The lesions were then biopsied and sent for pathology. The spectra were analyzed and the differences between pathological and healthy tissues were found and correlated.

RESULTS

Five of the lesions measured were identified as melanomas, seven as BCC, and three as SCC. Using mathematical analyses of the spectra of these lesions we were able to tell that all were skin cancers and we found specific and easily identifiable differences between them.

CONCLUSIONS

This FEWS method lends itself to rapid, automatic and noninvasive early detection and characterization of skin cancers. It will be easily implemented in community clinics and has the potential to greatly simplify the diagnosis process.

Photographing Alopecia: How Many Pixels Are Needed for Clinical Evaluation?

Determining the minimum image resolution needed for clinical assessment is crucial for computational efficiency, image standardization, and storage needs alleviation. In this paper, we explore the image resolution requirements for the assessment of alopecia by analyzing how clinicians detect the presence of characteristics needed to quantify the disorder in the clinic. By setting the image resolution as a function of width of the patient's head, we mimicked experiments conducted in the computer vision field to understand human perception in the context of scene recognition and object detection and asked 6 clinicians to identify the regions of interest on a set of retrospectively collected de-identified images at different resolutions. The experts were able to detect the presence of alopecia at very low resolutions, while significantly higher resolution was required to identify the presence of vellus-like hair. Furthermore, the accuracy with which alopecia was detected as a function of resolution followed the same trend as the one obtained when we classified normal versus abnormal hair density using a standard neural network architecture, hinting that the resolution needed by an expert human observer may also provide an upper bound for future image processing algorithms.

The diagnostic accuracy of dermoscopy and reflectance confocal microscopy for amelanotic/hypomelanotic melanoma: a systematic review and meta-analysis

BACKGROUND

Dermoscopy and reflectance confocal microscopy (RCM) are noninvasive techniques for the diagnosis of skin lesions. Their accuracy for amelanotic/hypomelanotic melanoma (AHM) has not been systematically studied.

OBJECTIVES

We aimed to investigate systematically the accuracy of dermoscopy and RCM and to compare the accuracy between them for diagnosing AHM.

METHODS

We searched the PubMed, Web of Science, Embase and Cochrane Library databases for eligible studies about dermoscopy, RCM and AHM from inception to 31 June 2019. The quality of the studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool. The pooled results were calculated using a random effects model in Stata 14, Meta-DiSc, RevMan 5·3 and SAS 9·4. We also explored the sources of heterogeneity by sensitivity analysis.

RESULTS

Seven studies with a total of 1111 lesions were included. The pooled sensitivity and specificity of dermoscopy for the diagnosis of AHM were 61% [95% confidence interval (CI) 0·37-0·81] and 90% (95% CI 0·74-0·97), respectively. The corresponding respective values of RCM for the diagnosis of AHM were 67% (95% CI 0·51-0·81) and 89% (95% CI 0·86-0·92). In three studies including the performance of both RCM and dermoscopy, the relative diagnostic odds ratio of RCM over dermoscopy was 4·69 (95% CI 0·81-27·3) (P = 0·068).

CONCLUSIONS

Our study demonstrates that both dermoscopy and RCM offer good diagnostic accuracy with high specificity and moderate sensitivity in the diagnosis of AHM. RCM is more accurate than dermoscopy in diagnosing AHM but the comparison needs to be confirmed. What's already known about this topic? Amelanotic/hypomelanotic melanoma (AHM) is the most lethal skin cancer. The diagnosis of AHM is a great challenge because of its nonspecific clinical manifestation. Early diagnosis can improve the prognosis. Dermoscopy and reflectance confocal microscopy (RCM) have high diagnostic accuracy for pigmented melanoma. What does this study add? Both dermoscopy and RCM offer good diagnostic accuracy with high specificity and moderate sensitivity for AHM. RCM might be more accurate than dermoscopy for diagnosis of AHM. More research on the diagnostic accuracy of dermoscopy and RCM for AHM is required in support of these findings.

Dermatofluoroscopy diagnostics in different pigmented skin lesions: Strengths and weaknesses

BACKGROUND

The melanin fluorescence of skin lesions is measurable with two-photon excitation, a process termed dermatofluoroscopy, which has shown a shift from the green spectra in benign melanocytic lesions to the red spectra in melanoma. This study addressed the question as to which kind of pigmented lesions can be correctly diagnosed as melanin-bearing malignant tumors.

METHODS

476 pigmented lesions including 101 cutaneous melanomas were analyzed with dermatofluoroscopy, measuring the melanin fluorescence in a grid-like fashion with a separation of measurement points of 0.2 mm. The results of the dermatofluoroscopy are presented as a diagnostic score with a cut-off score of ≥ 28 for the diagnosis of melanin-bearing malignant tumors, and were compared to the gold standard of histopathology.

RESULTS

A highly significant difference (p < 0.0001) between the diagnostic scores of different skin tumors was found. Dermatofluoroscopy scores showed the highest sensitivity for melanomas (92.1 %). Interestingly, most pigmented basal cell carcinomas (BCCs, 88.9 %) were diagnosed as melanin-bearing malignant tumors. A higher sensitivity for the correct diagnosis was observed in older patients (≥ 53 years, p = 0.003), in patients with skin tanning (p = 0.025), and in patients with freckles during childhood (p = 0.046).

CONCLUSIONS

Two-photon fluorescence is an innovative technique for the diagnosis of pigmented skin lesions, and shows a high sensitivity for detection of melanomas and pigmented BCCs.

Use of imaging techniques for melanocytic naevi and basal cell carcinoma in integrative analysis (Review)

Early detection of skin cancer is essential in order to obtain an improved prognosis. Clinicians need more objective and non-invasive examination methods to support their decision whether to biopsy or not tumoral lesions. These may include several imaging techniques such as dermoscopy, videodermoscopy, also known as sequential digital dermoscopy (SDD), computer-aided diagnosis (CAD), total body photography, imaging and high-frequency ultrasonography (HFUS), reflectance confocal microscopy, multiphoton tomography, electrical impedance spectroscopy, Raman spectroscopy, stepwise two-photon-laser spectroscopy and quantitative dynamic infrared. This review summarizes the current developments in the field of melanocytic lesions, such as naevi and basal cell carcinoma (BCC) imaging techniques. The aim was to collect and analyze data concerning types, indications, advantages and disadvantages of modern imaging techniques for in vivo skin tumor diagnosis. Two main methods were focused on, namely videodermoscopy and HFUS, which can be included in daily dermatologists' practice. In skin tumors HFUS allows the assessment of tumoral lesions with depth smaller than 1.5 cm, being described a correlation between ultrasonographic depth and the histologic index.

Raman spectroscopy for rapid intra-operative margin analysis of surgically excised tumour specimens

Raman spectroscopy, a form of vibrational spectroscopy, has the ability to provide sensitive and specific biochemical analysis of tissue. This review article provides an in-depth analysis of the suitability of different Raman spectroscopy techniques in providing intra-operative margin analysis in a range of solid tumour pathologies. Surgical excision remains the primary treatment of a number of solid organ cancers. Incomplete excision of a tumour and positive margins on histopathological analysis is associated with a worse prognosis, the need for adjuvant therapies with significant side effects and a resulting financial burden. The provision of intra-operative margin analysis of surgically excised tumour specimens would be beneficial for a number of pathologies, as there are no widely adopted and accurate methods of margin analysis, beyond histopathology. The limitations of Raman spectroscopic studies to date are discussed and future work necessary to enable translation to clinical use is identified. We conclude that, although there remain a number of challenges in translating current techniques into a clinically effective tool, studies so far demonstrate that Raman Spectroscopy has the attributes to successfully perform highly accurate intra-operative margin analysis in a clinically relevant environment.

Stimulation of collagen and elastin production in-vivo using 1,540 nm Er:Glass laser: assessment of safety and efficacy

Introduction: Induction of collagen and elastin remodeling in the human skin can be achieved by non-ablative fractional laser (NAFXL) and ablative fractional laser (AFXL). Our objective was to compare the safety, efficacy, tolerability, and ability to induce collagen and elastin remodeling of NAFXL versus AFXL in a series of treatments over time.Materials and Methods: In this prospective, proof of principle, single-case study, the safety, tolerability and efficacy of the laser systems were assessed via histopathology and clinical evaluations including photographs. Optical biopsies by means of multiphoton tomography (MPT) were used to evaluate the induction of collagen and elastin remodeling.Results: Treatments by both NAFXL and AFXL were well tolerated. The NAFXL system was found to be less painful and resulted in a shorter down- and healing times. MPT findings showed the superior capability of the AFXL procedure to induce collagen; on the other hand, elastin induction was more pronounced after NAFXL treatments.Conclusions: While NAFXL is as effective and safe as the traditional AFXL, it is better tolerated and has a shorter downtime. Serial optical biopsies over time over time can be a useful tool to assess the induction of collagen and elastin remodeling in the human skin.

Surgical Management of Primary Cutaneous Melanoma

Primary cutaneous melanomas are potentially curative with surgical excision alone. Surgical management is based on several factors determined from the initial biopsy, including primary tumor thickness, histologic features including ulceration, and anatomic location. Cosmesis, although important, should be a secondary consideration as oncologic principles take precedence. Pathology has evolved to synoptic reporting with key variables to assist in staging and risk stratification.

Melanoma in a cohort of organ transplant recipients: Experience from a dedicated transplant dermatology clinic in Victoria, Australia

BACKGROUND

There is limited information on the profile of melanomas diagnosed in a specialist transplant dermatology clinic.

OBJECTIVE

To describe the incidence and characteristics of incident primary melanomas in a cohort of organ transplant recipients (OTRs) attending a specialized transplant dermatology clinic and determine the number of pigmented lesions needed to excise for every melanoma diagnosed.

METHODS

A retrospective study of 327 OTRs monitored by an Australian clinic during a 10-year period.

RESULTS

There were 11 incident melanomas diagnosed during a total follow-up of 1280 patient-years. The mean interval between the first transplant and diagnosis was 5.5 years. Only 2 melanomas were >1 mm in Breslow thickness. Seven melanomas (64%) arose de novo. A contiguous nevus was present in 4 cases. Metastatic disease did not develop in the melanoma patients during the follow-up period, and all remain alive. The needed to excise for every melanoma diagnosed ratio was 16:1.

LIMITATIONS

The crude incidence rates were age standardized, unlike the comparison rates of melanoma in the general population, and the cohort was small.

CONCLUSION

Most melanomas diagnosed in OTR patients attending a specialized transplant dermatology service were detected early. Our data suggest early detection may reduce the proportion of OTRs presenting with thick melanomas, thus improving prognosis and patient outcomes. A needed to excise for every melanoma diagnosed ratio of 16:1 is not unreasonable for this cohort of high-risk patients. To our knowledge, this is the first time this ratio has been calculated for a cohort of OTRs.

Optical Radiomic Signatures Derived from Optical Coherence Tomography Images Improve Identification of Melanoma

The current gold standard for clinical diagnosis of melanoma is excisional biopsy and histopathologic analysis. Approximately 15-30 benign lesions are biopsied to diagnose each melanoma. In addition, biopsies are invasive and result in pain, anxiety, scarring, and disfigurement of patients, which can add additional burden to the health care system. Among several imaging techniques developed to enhance melanoma diagnosis, optical coherence tomography (OCT), with its high-resolution and intermediate penetration depth, can potentially provide required diagnostic information noninvasively. Here, we present an image analysis algorithm, "optical properties extraction (OPE)," which improves the specificity and sensitivity of OCT by identifying unique optical radiomic signatures pertinent to melanoma detection. We evaluated the performance of the algorithm using several tissue-mimicking phantoms and then tested the OPE algorithm on 69 human subjects. Our data show that benign nevi and melanoma can be differentiated with 97% sensitivity and 98% specificity. These findings suggest that the adoption of OPE algorithm in the clinic can lead to improvements in melanoma diagnosis and patient experience. SIGNIFICANCE: This study describes a noninvasive, safe, simple-to-implement, and accurate method for the detection and differentiation of malignant melanoma versus benign nevi.

Patient acceptance and trust in automated computer-assisted diagnosis of melanoma with dermatofluoroscopy

BACKGROUND AND OBJECTIVES

Automated computer-guided diagnostic procedures are increasingly being integrated into patient care. However, in contrast to the increasing application of automation, patient acceptance and trust in such technologies has rarely been studied. Automated diagnosis of melanoma with dermatofluoroscopy was recently approved by regulatory agencies. The objective of this study is to assess patient acceptance and trust in automated melanoma diagnosis with dermatofluoroscopy.

PATIENTS AND METHODS

We examined 140 pigmented skin lesions with dermatofluoroscopy as part of a prospective clinical study. Four weeks after their examination with dermatofluoroscopy, we contacted 100 patients with a 10-item questionnaire addressing their acceptance and trust in this technology on a five-point visual analogue scale.

RESULTS

A "high" to "very high" level of patient acceptance and trust in dermatofluoroscopy was found in 74 % of responders. Most patients agreed that computer-assisted diagnoses are trustworthy and may generally improve the diagnostic performance of physicians. However, all responders insisted on the interpretation of computer-assisted diagnoses by a physician and frequently rejected the idea of computers completely replacing physicians.

CONCLUSION

Patient acceptance and trust in dermatofluoroscopy was high. Patients clearly supported the use of automated, computer-assisted diagnostics as an adjunct to the physicians' examination.

Diagnostic accuracy of dermatofluoroscopy in cutaneous melanoma detection: results of a prospective multicentre clinical study in 476 pigmented lesions

BACKGROUND

Early detection is a key factor in improving survival from melanoma. Today, the clinical diagnosis of cutaneous melanoma is based mostly on visual inspection and dermoscopy. Preclinical studies in freshly excised or paraffin-embedded tissue have shown that the melanin fluorescence spectra after stepwise two-photon excitation, a process termed dermatofluoroscopy, differ between cutaneous melanoma and melanocytic naevi. However, confirmation from a larger prospective clinical study is lacking.

OBJECTIVES

The primary end point of this study was to determine the diagnostic accuracy of dermatofluoroscopy in melanoma detection. Secondary end points included the collection of data for improving the computer algorithm that classifies skin lesions based on melanin fluorescence and the assessment of safety aspects.

METHODS

This was a prospective, blinded, multicentre clinical study in patients with pigmented skin lesions (PSLs) indicated for excision either to rule out or to confirm cutaneous melanoma. All included lesions underwent dermoscopy and dermatofluoroscopy in vivo before lesions were excised and subjected to histopathological examination.

RESULTS

In total, 369 patients and 476 PSLs were included in the final analysis. In 101 of 476 lesions (21·2%) histopathology revealed melanoma. The observed sensitivity of dermatofluoroscopy was 89·1% (90 of 101 melanomas identified), with an observed specificity of 44·8%. The positive and negative predictive values were 30·3% and 93·9%, respectively. No adverse events occurred.

CONCLUSIONS

Dermatofluoroscopy is a safe and accurate diagnostic method to aid physicians in diagnosing cutaneous melanoma. Limitations arise from largely amelanotic or regressing lesions lacking sufficient melanin fluorescence.

In-vivo Raman spectroscopy: from basics to applications

For more than two decades, Raman spectroscopy has found widespread use in biological and medical applications. The instrumentation and the statistical evaluation procedures have matured, enabling the lengthy transition from ex-vivo demonstration to in-vivo examinations. This transition goes hand-in-hand with many technological developments and tightly bound requirements for a successful implementation in a clinical environment, which are often difficult to assess for novice scientists in the field. This review outlines the required instrumentation and instrumentation parameters, designs, and developments of fiber optic probes for the in-vivo applications in a clinical setting. It aims at providing an overview of contemporary technology and clinical trials and attempts to identify future developments necessary to bring the emerging technology to the clinical end users. A comprehensive overview of in-vivo applications of fiber optic Raman probes to characterize different tissue and disease types is also given.

Ultrasound and Infrared-Based Imaging Modalities for Diagnosis and Management of Cutaneous Diseases

Non-invasive bedside imaging tools are becoming more prevalent for assessing cutaneous lesions. Ultrasound used at specific frequencies allows us to assess margins of lesions to minimize the extent of the biopsy that is performed and improve cosmetic outcomes. Vascularity, seen on Doppler ultrasound and contrast-enhanced ultrasound, and stiffness, assessed on tissue elastography, can help differentiate between benign and malignant lesions for clinicians to be more judicious in deciding whether to biopsy. Moreover, research has shown the efficacy in using ultrasound in monitoring flares of hidradenitis suppurativa, a disease affecting apocrine gland-rich areas of the body, for which the current gold standard involves examining and scoring inflammatory lesions with the naked eye. Infrared-based modalities have also been on the uptrend to aid in clinical decision-making regarding suspiciousness of lesions. Reflectance confocal microscopy has lateral resolution that is comparable to histopathology and it has been shown to be an appropriate adjunctive tool to dermoscopy, specifically when evaluating melanomas. Optical coherence tomography has utility in determining lesion thickness because of its depth penetration, and spectrophotometric intracutaneous analysis is becoming more popular as a tool that can be used by general practitioners to know when to refer to dermatology regarding worrisome pigmented lesions. Strides have been made to incorporate electrical impedance spectroscopy alongside dermoscopy in decision-making regarding excision, although the evidence for its use in the clincial setting remains inconclusive. This paper reviews the efficacy and drawbacks of these techniques in the field of dermatology and suggests future directions.

Acral melanoma detection using a convolutional neural network for dermoscopy images

Background/Purpose

Acral melanoma is the most common type of melanoma in Asians, and usually results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the hands and feet and evaluated its usefulness for the early diagnosis of these conditions.

Methods

A total of 724 dermoscopy images comprising acral melanoma (350 images from 81 patients) and benign nevi (374 images from 194 patients), and confirmed by histopathological examination, were analyzed in this study. To perform the 2-fold cross validation, we split them into two mutually exclusive subsets: half of the total image dataset was selected for training and the rest for testing, and we calculated the accuracy of diagnosis comparing it with the dermatologist’s and non-expert’s evaluation.

Results

The accuracy (percentage of true positive and true negative from all images) of the convolutional neural network was 83.51% and 80.23%, which was higher than the non-expert’s evaluation (67.84%, 62.71%) and close to that of the expert (81.08%, 81.64%). Moreover, the convolutional neural network showed area-under-the-curve values like 0.8, 0.84 and Youden’s index like 0.6795, 0.6073, which were similar score with the expert.

Conclusion

Although further data analysis is necessary to improve their accuracy, convolutional neural networks would be helpful to detect acral melanoma from dermoscopy images of the hands and feet.

Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images

Melanoma is the deadliest form of skin cancer, and early detection is crucial for patient survival. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classification of dermoscopic images of skin lesions was announced. A training set of 900 images with corresponding class labels and semi-automatic/manual segmentation masks was released for the challenge. An independent test set of 379 images, of which 75 were of melanomas, was used to rank the participants. This article demonstrates the impact of ranking criteria, segmentation method and classifier, and highlights the clinical perspective. We compare five different measures for diagnostic accuracy by analysing the resulting ranking of the computer systems in the challenge. Choice of performance measure had great impact on the ranking. Systems that were ranked among the top three for one measure, dropped to the bottom half when changing performance measure. Nevus Doctor, a computer system previously developed by the authors, was used to participate in the challenge, and investigate the impact of segmentation and classifier. The diagnostic accuracy when using an automatic versus the semi-automatic/manual segmentation is investigated. The unexpected small impact of segmentation method suggests that improvements of the automatic segmentation method w.r.t. resemblance to semi-automatic/manual segmentation will not improve diagnostic accuracy substantially. A small set of similar classification algorithms are used to investigate the impact of classifier on the diagnostic accuracy. The variability in diagnostic accuracy for different classifier algorithms was larger than the variability for segmentation methods, and suggests a focus for future investigations. From a clinical perspective, the misclassification of a melanoma as benign has far greater cost than the misclassification of a benign lesion. For computer systems to have clinical impact, their performance should be ranked by a high-sensitivity measure.

Impact of UV-irradiation on electrical impedance spectroscopy of benign nevi: study protocol for a prospective, controlled, clinical study

INTRODUCTION

The clinical and histological changes of nevi after ultraviolet (UV) irradiation have been studied in detail. In contrast, the impact of UV irradiation on electrical impedance spectroscopy scores of nevi has not been investigated. However, for physicians, it is essential to know the extent to which changes in electrical impedance spectroscopy scores of nevi may be attributed to seasonal effects of UV irradiation.

METHODS

This is a prospective, controlled, clinical study evaluating the impact of UV irradiation on the electrical impedance spectroscopy scores of benign nevi in 50 patients undergoing phototherapy. To this end, benign nevi of patients with a medical indication for phototherapy will be measured by electrical impedance spectroscopy before, during and after UV irradiation. At the same time, non-irradiated nevi of the same patient will be measured to account for changes over time that are independent of direct UV irradiation.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the ethics committee of the medical faculty of the University of Heidelberg (ethics approval number S-279/2017). The design and the final results of the study will be published and made available to the public.

TRIAL REGISTRATION NUMBER

DRKS00012456; Pre-results.