Melanoma clinicopathological groups characterized and compared with dermoscopy and reflectance confocal microscopy.

BACKGROUND: Dermoscopic and reflectance confocal microscopy (RCM) correlations between morphologic groups of melanoma have not yet been described. OBJECTIVE: Describe and compare dermoscopic and RCM features of cutaneous melanomas with histopathological confirmation. METHODS: Single center, retrospective analysis of consecutive melanomas evaluated with RCM (2015-2019). Lesions were clinically classified as typical, nevus-like, amelanotic/nonmelanoma skin cancer (NMSC)-like, seborrheic keratosis (SK)-like and lentigo/lentigo maligna (LM)-like. Presence or absence of common facial and nonfacial melanoma dermoscopic and RCM patterns were recorded. Clusters were compared with typical lesions by multivariate logistic regression. RESULTS: Among 583 melanoma lesions, significant differences between clusters were evident (compared to typical lesions). Observation of dermoscopic features (>50% of lesions) in amelanotic/NMSC-like lesions consistently displayed 3 patterns (atypical network, atypical vascular pattern + regression structures), and nevus-like and SK-like lesions and lentigo/LM-like lesions consistently displayed 2 patterns (atypical network + regression structures, and nonevident follicles + heavy pigmentation intensity). Differences were less evident with RCM, as almost all lesions were consistent with melanoma diagnosis. LIMITATIONS: Small SK-like lesions sample, single RCM analyses (no reproduction of outcome). CONCLUSION: RCM has the potential to augment our ability to consistently and accurately diagnose melanoma independently of clinical and dermoscopic features.

Optical coherence tomography confirms non-malignant pigmented lesions in phacomatosis pigmentokeratotica using a support vector machine learning algorithm.

INTRODUCTION: Phacomatosis pigmentokeratotica (PPK), an epidermal nevus syndrome, is characterized by the coexistence of nevus spilus and nevus sebaceus. Within the nevus spilus, an extensive range of atypical nevi of different morphologies may manifest. Pigmented lesions may fulfill the ABCDE criteria for melanoma, which may prompt a physician to perform a full-thickness biopsy. MOTIVATION: Excisions result in pain, mental distress, and physical disfigurement. For patients with a significant number of nevi with morphologic atypia, it may not be physically feasible to biopsy a large number of lesions. Optical coherence tomography (OCT) is a non-invasive imaging modality that may be used to visualize non-melanoma and melanoma skin cancers. MATERIALS AND METHOD: In this study, we used OCT to image pigmented lesions with morphologic atypia in a patient with PPK and assessed their quantitative optical properties compared to OCT cases of melanoma. We implement a support vector machine learning algorithm with Gabor wavelet transformation algorithm during post-image processing to extract optical properties and calculate attenuation coefficients. RESULTS: The algorithm was trained and tested to extract and classify textural data. CONCLUSION: We conclude that implementing this post-imaging machine learning algorithm to OCT images of pigmented lesions in PPK has been able to successfully confirm benign optical properties. Additionally, we identified remarkable differences in attenuation coefficient values and tissue optical characteristics, further defining separating benign features of pigmented lesions in PPK from malignant features.

Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks.

BACKGROUND: The number of naevi on a person is the strongest risk factor for melanoma; however, naevus counting is highly variable due to lack of consistent methodology and lack of inter-rater agreement. Machine learning has been shown to be a valuable tool for image classification in dermatology. OBJECTIVES: To test whether automated, reproducible naevus counts are possible through the combination of convolutional neural networks (CNN) and three-dimensional (3D) total body imaging. METHODS: Total body images from a study of naevi in the general population were used for the training (82 subjects, 57,742 lesions) and testing (10 subjects; 4,868 lesions) datasets for the development of a CNN. Lesions were labelled as naevi, or not ("non-naevi"), by a senior dermatologist as the gold standard. Performance of the CNN was assessed using sensitivity, specificity, and Cohen's kappa, and evaluated at the lesion level and person level. RESULTS: Lesion-level analysis comparing the automated counts to the gold standard showed a sensitivity and specificity of 79% (76-83%) and 91% (90-92%), respectively, for lesions ≥2 mm, and 84% (75-91%) and 91% (88-94%) for lesions ≥5 mm. Cohen's kappa was 0.56 (0.53-0.59) indicating moderate agreement for naevi ≥2 mm, and substantial agreement (0.72, 0.63-0.80) for naevi ≥5 mm. For the 10 individuals in the test set, person-level agreement was assessed as categories with 70% agreement between the automated and gold standard counts. Agreement was lower in subjects with numerous seborrhoeic keratoses. CONCLUSION: Automated naevus counts with reasonable agreement to those of an expert clinician are possible through the combination of 3D total body photography and CNNs. Such an algorithm may provide a faster, reproducible method over the traditional in person total body naevus counts.

Suggested methodology for longitudinal evaluation of nevi based on clinical images.

BACKGROUND: Melanoma screening includes the assessment of changes in melanocytic lesions using images. However, previous studies of normal nevus temporal changes showed variable results and the optimal method for evaluating these changes remains unclear. Our aim was to evaluate the reproducibility of (a) nevus count done at a single time point (method I) versus two time points (method II); and (b) manual and automated nevus diameter measurements. MATERIALS AND METHODS: In a first experiment, participants used either a single time point or a two time point annotation method to evaluate the total number and size of nevi on the back of an atypical mole syndrome patient. A Monte Carlo simulation was used to calculate the variance observed. In a second experiment, manual measurements of nevi on 2D images were compared to an automated measurement on 3D images. Percent difference in the paired manual and automated measurements was calculated. RESULTS: Mean nevus count was 137 in method I and 115.5 in method II. The standard deviation was greater in method I (38.80) than in method II (4.65) (p = 0.0025). Manual diameter measurements had intraclass correlation coefficient of 0.88. The observed mean percent difference between manual and automated diameter measurements was 1.5%. Lightly pigmented and laterally located nevi had a higher percent difference. CONCLUSIONS: Comparison of nevi from two different time points is more consistent than nevus count performed separately at each time point. In addition, except for selected cases, automated measurements of nevus diameter on 3D images can be used as a time-saving reproducible substitute for manual measurement on 2D images.

Digital dermoscopy monitoring of melanocytic lesions: Two novel calculators combining static and dynamic features to identify melanoma.

BACKGROUND: Early diagnosis is the most effective intervention to improve the prognosis of cutaneous melanoma. Even though the introduction of dermoscopy has improved the diagnostic accuracy, it can still be difficult to distinguish some melanomas from benign melanocytic lesions. Digital dermoscopy monitoring can identify dynamic changes of melanocytic lesions: To date, some algorithms were proposed, but a universally accepted one is still lacking. OBJECTIVES: To identify independent predictive variables associated with the diagnosis of cutaneous melanoma and develop a multivariable dermoscopic prediction model able to discriminate benign from malignant melanocytic lesions undergoing digital dermoscopy monitoring. METHODS: We collected dermoscopic images of melanocytic lesions excised after dermoscopy monitoring and carried out static and dynamic evaluations of dermoscopic features. We built two multivariable predictive models based on logistic regression and random forest. RESULTS: We evaluated 173 lesions (65 cutaneous melanomas and 108 nevi). Forty-two melanomas were in situ, and the median thickness of invasive melanomas was 0.35 mm. The median follow-up time was 9.8 months for melanomas and 9.1 for nevi. The logistic regression and random forest models performed with AUC values of 0.87 and 0.89, respectively, were substantially higher than those of the static evaluation models (ABCD TDS score, 0.57; 7-point checklist, 0.59). Finally, we built two risk calculators, which translate the proposed models into user-friendly applications, to assist clinicians in the decision-making process. CONCLUSIONS: The present study demonstrates that the integration of dynamic and static evaluations of melanocytic lesions is a safe approach that can significantly boost the diagnostic accuracy for cutaneous melanoma. We propose two diagnostic tools that significantly increase the accuracy in discriminating melanoma from nevi during digital dermoscopy monitoring.

Computer Aided Diagnosis of Melanoma Using Deep Neural Networks and Game Theory: Application on Dermoscopic Images of Skin Lesions.

Early detection of melanoma remains a daily challenge due to the increasing number of cases and the lack of dermatologists. Thus, AI-assisted diagnosis is considered as a possible solution for this issue. Despite the great advances brought by deep learning and especially convolutional neural networks (CNNs), computer-aided diagnosis (CAD) systems are still not used in clinical practice. This may be explained by the dermatologist's fear of being misled by a false negative and the assimilation of CNNs to a "black box", making their decision process difficult to understand by a non-expert. Decision theory, especially game theory, is a potential solution as it focuses on identifying the best decision option that maximizes the decision-maker's expected utility. This study presents a new framework for automated melanoma diagnosis. Pursuing the goal of improving the performance of existing systems, our approach also attempts to bring more transparency in the decision process. The proposed framework includes a multi-class CNN and six binary CNNs assimilated to players. The players' strategies is to first cluster the pigmented lesions (melanoma, nevus, and benign keratosis), using the introduced method of evaluating the confidence of the predictions, into confidence level (confident, medium, uncertain). Then, a subset of players has the strategy to refine the diagnosis for difficult lesions with medium and uncertain prediction. We used EfficientNetB5 as the backbone of our networks and evaluated our approach on the public ISIC dataset consisting of 8917 lesions: melanoma (1113), nevi (6705) and benign keratosis (1099). The proposed framework achieved an area under the receiver operating curve (AUROC) of 0.93 for melanoma, 0.96 for nevus and 0.97 for benign keratosis. Furthermore, our approach outperformed existing methods in this task, improving the balanced accuracy (BACC) of the best compared method from 77% to 86%. These results suggest that our framework provides an effective and explainable decision-making strategy. This approach could help dermatologists in their clinical practice for patients with atypical and difficult-to-diagnose pigmented lesions. We also believe that our system could serve as a didactic tool for less experienced dermatologists.

Case 289: PIK3CA-related Overgrowth Spectrum (PROS): CLOVES Syndrome and Coexisting Fibroadipose Vascular Anomaly.

HISTORY: Part one of this case appeared 4 months previously and may contain larger images. An 8-year-old girl presented to our hospital with painful swelling of the left thigh and soft-tissue swelling in the right chest wall. The patient's history revealed that the swelling had been present since birth but had grown slowly. She had no history of relevant trauma. Her blood pressure was 145/95 mmHg (normal value, <115/76 mmHg), and her heart rate was 105 beats per minute (normal value, 75-118 beats per minute). The patient's electrocardiogram displayed sinus tachycardia. Physical examination revealed soft-tissue hypertrophy in the left thigh and right lower chest wall. A painful soft and flexible mass measuring approximately 5 × 6 × 15 cm (in the anteroposterior, transverse, and craniocaudal directions, respectively) was detected at the left thigh. Moreover, a painless soft mass measuring approximately 3 × 8 × 10 cm (in the anteroposterior, transverse, and craniocaudal directions, respectively) was detected in the right lower chest wall, and the overlying skin was intact. Pink macules with a 3-cm diameter on the anterior left superior thigh and a 2.5-cm diameter in the left inguinal region were detected. Examination of other systems, including the cardiovascular system, revealed normal findings. Laboratory test results were within normal limits. Abdominal US showed perirenal vascular collaterals, and musculoskeletal US of the left thigh revealed vascular collaterals (images not shown). Therefore, thoracoabdominal CT angiography and contrast material-enhanced MRI of the bilateral thigh were performed.

Evaluation of 20-MHz high-frequency ultrasonography for the diagnosis of choroidal nevi.

PURPOSE: Evaluate short-term intraoperator reproducibility of ultrasonographic measurements of choroidal nevi using 10- and 20-MHz probes, and the efficacy of the high-frequency probes for the diagnosis of choroidal nevi. METHODS: Diameters and thicknesses of choroidal nevi were measured using a 10-MHz probe and a high-frequency long focal length 20-MHz probe (Quantel Medical™). The first part of the study evaluated intraoperator reproducibility of measurements of choroidal nevi with 10- and 20-MHz probes and the second part of the study allowed the comparisons of the measurements of largest tumor diameter (LDT) of choroidal nevi of 40 patients between the 10- and 20-MHz probes. The two-way random average agreement intraclass correlation coefficients (ICC), Bland-Altman plot, and a paired t test were used. RESULTS: The intraoperator reproducibility of choroidal nevi measurements with 10- and 20-MHz probes was excellent (ICC > 0.9, n = 20). Four flat nevi, not detectable at 10 MHz, could be located with the high-frequency probe (p = 0.12). There was no significant difference in thickness or LTD measurements between the 10- and 20-MHz probes (n = 31). Both techniques showed an excellent agreement (ICC > 0.8) for thickness and LTD measurements. All the choroidal nevi that were not measurable with the 10-MHz probe (n = 7) were measured with the 20-MHz probe. CONCLUSION: The high-frequency 20-MHz probe allows additional detection and measurements of flat choroidal nevi. When detectable, the ultrasonographic measurements of thickness and diameter of choroidal nevi are similar with both the 10- and the 20-MHz probes.

Naevus vascularis mixtus and mixed vascular naevus syndrome.

Naevus vascularis mixtus (NVM), or mixed vascular naevus (MVN), is a binary phenotype resulting from allelic twin spotting, consisting of a naevus anaemicus paired with a telangiectatic naevus reminiscent of naevus roseus, and caused by a mosaic GNA11 mutation. MVN syndrome is characterized by an NVM associated with soft tissue hypotrophy or central nervous system abnormalities, mainly involving the cerebral vasculature. The differential diagnoses of NVM and its syndrome include vascular twin naevi, syndromes featuring naevus flammeus and other port-wine naevi, and the various types of phacomatosis pigmentovascularis. NVM and MVN syndrome are rare but probably underdiagnosed and under-reported.

Ultrasound Imaging of Nevus Sebaceous of Jadassohn.

Nevus sebaceous of Jadassohn (NSJ) is a cutaneous hamartoma commonly found in the scalp and face and more frequent in children. Clinically, it presents as a yellowish and hairless plaque. In later stages, the NSJ can develop secondary tumors, including skin cancer. We reviewed the ultrasound characteristics of 9 patients (67% female; mean age, 3 years) with NSJ at 18 and 70 MHz. The ultrasound analysis covers the data on the location, thickness, echo structure, and vascularity. The provision of the ultrasound patterns of NSJ can support early diagnosis, avoid unnecessary biopsies, and support monitoring.

In vivo confocal microscopy: The role of comparative approach in patients with multiple atypical nevi.

BACKGROUND: In vivo reflectance confocal microscopy (RCM) increases diagnostic accuracy for melanoma diagnosis when combined with dermoscopy. In patients with multiple atypical nevi, a comparative dermoscopic approach improves melanoma recognition and saves unnecessary excision. The performance of a comparative approach combining dermoscopy and RCM has not been yet investigated. OBJECTIVE: To validate a comparative dermoscopic + RCM approach according to melanoma diagnostic accuracy in patients with multiple atypical nevi. METHODS: Consecutive patients undergoing RCM examination for ≥3 atypical melanocytic lesions, assessed with a dermoscopic + RCM comparative approach in a real-life setting, from July 2012 to April 2018 at a single centre, were enrolled. Dermoscopic and dermoscopic + RCM morphologic approaches were retrospectively applied by evaluating revisited 7-point checklist, RCM and Delphi scores for each enrolled lesion. Comparative dermoscopic and dermoscopic + RCM approaches were subsequently used. For each approach, lesions were classified as non-suspicious (long-term follow-up) or suspicious (short-term follow-up or excision) and diagnostic accuracy for melanoma diagnosis was assessed. RESULTS: Diagnostic accuracy progressively increased comparing morphologic to comparative approaches, and comparing dermoscopic to dermoscopic + RCM approaches. The retrospective comparative dermoscopic + RCM approach revealed the largest area under the curve (0.84; 95%CI:0.79-0.89; P < .001) and the lowest number needed to excise (5.7). Furthermore, this approach had the highest specificity (67.6%) and sensitivity (100%) levels, which were similar to those verified in the real-life setting. The main study limitations are the retrospective design and high-risk patient inclusion only. CONCLUSIONS: Comparative dermoscopic + RCM approach increases melanoma diagnostic accuracy, reducing unnecessary excision without missing melanomas.

Dermatofluoroscopy Is Also for Redheads a Sensitive Method of Early Melanoma Detection.

BACKGROUND: Caucasians with red hair and fair skin have a remarkably increased risk of malignant melanoma compared to non-redhead Caucasians. OBJECTIVES: With the aim of a reliable melanoma diagnosis in redheads, the application of dermatofluoroscopy was analyzed in 16 patients with red hair. Most of them had been included in a clinical dermatofluoroscopy study for patients with the suspicion of melanoma. We examined whether the 25 lesions of the redheads showed the same characteristic melanin fluorescence spectra for dysplastic nevi and melanomas as those of non-redhead Caucasians or whether there was a different fluorescence pattern. This is important in view of the known significantly altered ratio of eumelanin to pheomelanin in the skin of redheads. METHODS: More than 8,000 spatially resolved fluorescence spectra of 25 pigmented lesions were measured and analysed. The spectra were excited by the stepwise absorption of two 800-nm photons (principle of dermatofluoroscopy). Furthermore, the fluorescence spectra of eumelanin and pheomelanin in hair samples were determined in the same way. RESULTS: The evaluation revealed that the melanin fluorescence spectra of dysplastic nevi and melanomas of redheads have the same spectral characteristics as those of non-redhead Caucasians. An accompanying result is that dermatofluoroscopy shows identical fluorescence spectra for eumelanin and pheomelanin. CONCLUSIONS: Dermatofluoroscopy proves to be a reliable diagnostic method also for redheads. Our results also explain our recent finding that there is a uniform fluorescence spectroscopic fingerprint for melanomas of all subtypes, which is of particular interest for hypomelanotic and apparently amelanotic melanomas containing pheomelanin.

Microblotches on Dermoscopy of Melanocytic Lesions are Associated with Melanoma: A Cross-sectional Study.

Numerous dermoscopic structures for the early detection of melanoma have been described. The aim of this study was to illustrate the characteristics of dermoscopic structures that are similar to blotches, but smaller (termed microblotches), and to evaluate their association with other well-known dermoscopic structures. A cross-sectional study design, including 165 dermoscopic images of melanoma was used to define microblotches, and 241 consecutive images of naevi from the HAM10000 database, were studied to evaluate the prevalence of this criterion in both groups. Microblotches were defined as sharply demarcated structures ≤1 mm, with geographical borders visible only with dermoscopy. Microblotches were present in 38.7% of the melanomas and 6.7% of the naevi. Moreover, microblotches were associated with an odds ratio (OR) of malignancy of 5.79, and were more frequent in invasive melanoma than in the in-situ subtype (OR 2.92). Histologically, they correspond to hyperpigmented parakeratosis or epidermal consumption. In conclusion, microblotches are related to melanomas. This finding could help dermatologists to differentiate between naevi and melanomas.

Nevus-associated melanoma: An observational retrospective study of 22 patients evaluated with dermoscopy and reflectance confocal microscopy.

BACKGROUND: The frequency of nevus-associated melanoma (NAM) has been estimated to be 29% of diagnosed melanomas. MATERIALS AND METHODS: This is an observational retrospective study of 22 cases of NAM diagnosed in the Universitary Hospital Alcorcón between September 2011 and 2018. The main objective was to analyze dermoscopic and RCM features of NAM. We also studied if there was an association between any dermoscopic or RCM parameter and Breslow depth. RESULTS: The most frequent dermoscopic characteristics were multicomponent pattern (50%), multifocal pigmentation (45.5%), atypical network (59.1%), and blue-gray regression structures (77.3%). RCM evidenced pagetoid cells in 95.5% melanomas (abundant in 59.1%), non-edged dermal papillae in 86.4%, atypical cells at the dermal-epidermal junction in 90.9%, and atypical junctional nesting in 81.8%. Deeper Breslow index was associated with red color (mean Breslow 0.65 vs 0.37 in melanomas without red, P = 0.035), shiny white streaks (0.85 vs 0.38, P = 0.041), abundant pagetoid cells (0.68 vs 0.26, P = 0.017), and non-edged papillae (0.59 vs 0.00, P = 0.014). CONCLUSION: RCM is a valuable tool for diagnosing NAM. Even it is very difficult to differentiate NAM from DNM both with dermoscopy and RCM, RCM can help us to detect remnants of a preexisting nevus and estimate Breslow depth.

CT and MR imaging findings of solitary nevus lipomatosus cutaneous superficialis: radiological-pathological correlation.

OBJECTIVE: This study assessed the CT and MRI findings of solitary nevus lipomatosus cutaneous superficialis (NLCS). MATERIALS AND METHODS: Eleven patients with histopathologically and clinically confirmed solitary NLCS who underwent CT and/or MRI were enrolled. Radiological and histopathological findings of elevated lesions located above the level of the surrounding normal skin surface and coexisting subcutaneous lipoma-like lesions were assessed retrospectively. RESULTS: Elevated skin lesions were observed in all 11 patients; these lesions were pedunculated in 4 patients (36%) and broad-based in 7 (64%). The CT attenuation of elevated lesions was fat attenuation in 2 out of 7 patients (29%), slightly increased fat attenuation in 4 out of 7 (57%), and combined fat and soft-tissue attenuation in 1 out of 7 (14%). The MR signal intensity of elevated lesions on T1-weighted images was fat signal intensity in 2 out of 6 patients (33%), slightly decreased fat signal intensity in 3 out of 6 (50%), and combined fat signal intensity and hypointensity in 1 out of 6 (17%). Subcutaneous lipoma-like lesions with fat attenuation and/or fat signal intensity were observed in 6 out of 11 patients (55%). Histopathologically, various amounts of fatty tissue and collagenous fiber were observed within the elevated lesions in all 11 patients. CONCLUSION: The CT and MRI features of solitary NLCS were the broad-based or pedunculated elevated lesions, including fatty components. Additionally, subcutaneous lipoma-like lesions were frequently observed.

Automated Lesion Segmentation and Quantitative Analysis of Nevus in Whole-Face Images.

BACKGROUND: Nevus is very common; however, melanoma is slightly related to the deterioration of nevus because of its vulnerability to solarization, friction, aging, heredity, and other factors. Early diagnosis is essential for melanoma treatment, since patients have a high survival rate with early detection and treatment. Computer-aided diagnosis has been applied in the differential diagnosis of melanoma and benign nevi and achieved high accuracy, but it does not suit the screening of nevi because most studies are based on dermoscopy with a narrow field of vision and performed by professional doctors. Therefore, this study aimed to present the accuracy and effectiveness of our algorithm. METHODS: Based on whole-face images of patients, the authors used logistic regression and the Newton method to detect the nevus region. Then, Python and OpenCV were employed to detect the lesion edge and compute the area of the regions. A multicenter clinical trial with a sample size of 600 was then conducted to evaluate the effectiveness of the algorithm. RESULTS: The algorithm detected 2672 nevi from 600 patients, in which there were 195 patients of missed diagnosis and 310 patients of misdiagnosis. The Kappa value between 2 groups was 0.860 (>0.8). Paired t-test showed no significant difference between 2 groups' area results (P = 0.265, P > 0.05). CONCLUSION: Within the limitations of this study, the authors demonstrated a high agreement between algorithm's detection and doctor's diagnosis. Our new algorithm has great effectiveness in nevus detection, edge segmentation, and area measurement.

Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders.

In this research, we present a semi-supervised segmentation solution using convolutional autoencoders to solve the problem of segmentation tasks having a small number of ground-truth images. We evaluate the proposed deep network architecture for the detection of nests of nevus cells in histopathological images of skin specimens is an important step in dermatopathology. The diagnostic criteria based on the degree of uniformity and symmetry of border irregularities are particularly vital in dermatopathology, in order to distinguish between benign and malignant skin lesions. However, to the best of our knowledge, it is the first described method to segment the nests region. The novelty of our approach is not only the area of research, but, furthermore, we address a problem with a small ground-truth dataset. We propose an effective computer-vision based deep learning tool that can perform the nests segmentation based on an autoencoder architecture with two learning steps. Experimental results verified the effectiveness of the proposed approach and its ability to segment nests areas with Dice similarity coefficient 0.81, sensitivity 0.76, and specificity 0.94, which is a state-of-the-art result.

Smartphone based multispectral imager and its potential for point-of-care testing.

We report a smartphone based multispectral imager (MSI), a promising tool for point-of-care (POC) testing, which utilizes a bio-inspired MSI chip to capture both the spectral and spatial information of a target simultaneously. As the key component for compact MSI, the proposed MSI chip mimics the structure of an insect compound-eye, wherein each sub-eye responds to a specific spectral band. This could allow a smartphone to be transformed into an MSI device that could acquire a snap-shot spectral image in a single exposure. An orthogonal polarization imaging method is adopted, to boost the capability of the smartphone MSI for chemical analysis. The feasibility and application potential of the proposed device are demonstrated non-invasively for skin lesion and dental plaque analysis. The experimental results are consistent with the physiological expectations, validating the ability of the smartphone MSI for multispectral image acquisition and further analytical determination. The chemical analysis capability, portability and cost-effectiveness of the smartphone MSI make it a promising analytical tool for POC testing, from chemical analysis to in vivo pathological diagnosis.

Reflectance confocal microscopy made easy: The 4 must-know key features for the diagnosis of melanoma and nonmelanoma skin cancers.

BACKGROUND: Reflectance confocal microscopy (RCM)-based skin cancer diagnosis requires proficiency. OBJECTIVE: To identify a short list of key RCM features of skin cancers and test their diagnostic utility. METHODS: We identified key RCM features through consensus among 6 experts using a modified Delphi method. To test the diagnostic utility of these RCM key features, 10 novice RCM readers evaluated a subset of 100 RCM cases from a retrospective data set of benign and malignant skin neoplasms. RESULTS: From 56 features reported in the literature, the experts identified 18 RCM features as highly valuable for skin cancer diagnosis. On the basis of consensus definitions, these RCM features were further clustered into 2 melanoma-specific key features (atypical cells and dermoepidermal junction disarray), 1 basal cell carcinoma-specific key feature (basaloid cords/islands), and 1 squamous cell carcinoma-specific key feature (keratinocyte disarray). The novice reading study showed that the presence of at least 1 of the 4 key features was associated with an overall sensitivity for skin cancer diagnosis of 91%, with a sensitivity for melanoma of 93%, a sensitivity for basal cell carcinoma of 92%, and a sensitivity for squamous cell carcinoma of 67%, and an overall specificity of 57%. LIMITATIONS: The consensus was based on only six RCM experts and the validation study was retrospective. CONCLUSIONS: A consensus terminology short list identifying the 4 RCM key features for skin cancer diagnosis may facilitate dissemination of RCM to novice users.

Congenital Limb Overgrowth Syndromes Associated with Vascular Anomalies.

Congenital limb length discrepancy disorders are frequently associated with a variety of vascular anomalies and have unique genetic and phenotypic features. Many of these syndromes have been linked to sporadic somatic mosaicism involving mutations of the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, which has an important role in tissue growth and angiogenesis. Radiologists who are aware of congenital limb length discrepancies can make specific diagnoses based on imaging findings. Although genetic confirmation is necessary for a definitive diagnosis, the radiologist serves as a central figure in the identification and treatment of these disorders. The clinical presentations, diagnostic and imaging workups, and treatment options available for patients with Klippel-Trenaunay syndrome, CLOVES (congenital lipomatous overgrowth, vascular anomalies, epidermal nevi, and scoliosis/spinal deformities) syndrome, fibroadipose vascular anomaly, phosphatase and tensin homolog mutation spectrum, Parkes-Weber syndrome, and Proteus syndrome are reviewed. ©RSNA, 2019.