Clinical and histopathological features of lentigo maligna and lentigo maligna melanoma: a retrospective analysis in Korea

Introduction

Lentigo maligna (LM) and lentigo maligna melanoma (LMM) are rare in Asian countries. The histopathological diagnosis of LM is often challenging, and misdiagnosis is common. Although histopathologic features of LM/LMM are known, statistical analysis of them were scarcely reported. In this study, we aimed to investigate the histopathological characteristics of LM/LMM in Korean patients and identify key histopathological clues distinguishing LM from benign lentigo.

Methods

We performed a retrospective study of the clinical and histopathological features of patients diagnosed with LM/LMM at our center between 2011 and 2022. We assessed the histopathological features in each case based on 16 pathological criteria according to previous literature. Pathologically confirmed cases of benign lentigo were analyzed for comparison.

Results

Twenty-one patients (10 with LM and 11 with LMM) were analyzed. Several statistically significant difference existed between the features of LM and benign lentigo (N = 10), including asymmetry of overall structure (p < 0.001), cytologic atypia (p < 0.001), predominant single-cell proliferation (p < 0.001), melanocytic nests (p = 0.033), melanocytes forming rows (p = 0.003), pagetoid spread of melanocytes (p < 0.001), and hair follicle invasion by atypical melanocytes (p < 0.001). Degree of solar elastosis was more severe in group "Age ≥ 60" (p = 0.015), and group "Diameter ≥ 20 mm" (p = 0.043). Presence of elongated rete ridges were less common in the older than 60 age group (p = 0.015) and group "Diameter ≥ 20 mm." Invasion was associated with mitosis (p = 0.001, OR 49.285), multinucleated cells (p = 0.035, OR 17.769), and degree of lymphocyte infiltration (p = 0.004).

Conclusion

This study investigated the clinical and histopathologic characteristics of LM and LMM in Koreans. Although histopathological diagnosis is challenging, especially in the early stages of LM, our data showed essential histopathological changes in architectural, cytological, and dermal patterns. Considering the potential aggressiveness of LM/LMM, it is essential to recognize its histopathological features and provide timely management.

Assist-Dermo: A Lightweight Separable Vision Transformer Model for Multiclass Skin Lesion Classification

A dermatologist-like automatic classification system is developed in this paper to recognize nine different classes of pigmented skin lesions (PSLs), using a separable vision transformer (SVT) technique to assist clinical experts in early skin cancer detection. In the past, researchers have developed a few systems to recognize nine classes of PSLs. However, they often require enormous computations to achieve high performance, which is burdensome to deploy on resource-constrained devices. In this paper, a new approach to designing SVT architecture is developed based on SqueezeNet and depthwise separable CNN models. The primary goal is to find a deep learning architecture with few parameters that has comparable accuracy to state-of-the-art (SOTA) architectures. This paper modifies the SqueezeNet design for improved runtime performance by utilizing depthwise separable convolutions rather than simple conventional units. To develop this Assist-Dermo system, a data augmentation technique is applied to control the PSL imbalance problem. Next, a pre-processing step is integrated to select the most dominant region and then enhance the lesion patterns in a perceptual-oriented color space. Afterwards, the Assist-Dermo system is designed to improve efficacy and performance with several layers and multiple filter sizes but fewer filters and parameters. For the training and evaluation of Assist-Dermo models, a set of PSL images is collected from different online data sources such as Ph2, ISBI-2017, HAM10000, and ISIC to recognize nine classes of PSLs. On the chosen dataset, it achieves an accuracy (ACC) of 95.6%, a sensitivity (SE) of 96.7%, a specificity (SP) of 95%, and an area under the curve (AUC) of 0.95. The experimental results show that the suggested Assist-Dermo technique outperformed SOTA algorithms when recognizing nine classes of PSLs. The Assist-Dermo system performed better than other competitive systems and can support dermatologists in the diagnosis of a wide variety of PSLs through dermoscopy. The Assist-Dermo model code is freely available on GitHub for the scientific community.

Light-Dermo: A Lightweight Pretrained Convolution Neural Network for the Diagnosis of Multiclass Skin Lesions

Skin cancer develops due to the unusual growth of skin cells. Early detection is critical for the recognition of multiclass pigmented skin lesions (PSLs). At an early stage, the manual work by ophthalmologists takes time to recognize the PSLs. Therefore, several "computer-aided diagnosis (CAD)" systems are developed by using image processing, machine learning (ML), and deep learning (DL) techniques. Deep-CNN models outperformed traditional ML approaches in extracting complex features from PSLs. In this study, a special transfer learning (TL)-based CNN model is suggested for the diagnosis of seven classes of PSLs. A novel approach (Light-Dermo) is developed that is based on a lightweight CNN model and applies the channelwise attention (CA) mechanism with a focus on computational efficiency. The ShuffleNet architecture is chosen as the backbone, and squeeze-and-excitation (SE) blocks are incorporated as the technique to enhance the original ShuffleNet architecture. Initially, an accessible dataset with 14,000 images of PSLs from seven classes is used to validate the Light-Dermo model. To increase the size of the dataset and control its imbalance, we have applied data augmentation techniques to seven classes of PSLs. By applying this technique, we collected 28,000 images from the HAM10000, ISIS-2019, and ISIC-2020 datasets. The outcomes of the experiments show that the suggested approach outperforms compared techniques in many cases. The most accurately trained model has an accuracy of 99.14%, a specificity of 98.20%, a sensitivity of 97.45%, and an F1-score of 98.1%, with fewer parameters compared to state-of-the-art DL models. The experimental results show that Light-Dermo assists the dermatologist in the better diagnosis of PSLs. The Light-Dermo code is available to the public on GitHub so that researchers can use it and improve it.

VISIA Skin Analysis System as a Tool to Evaluate the Reduction of Pigmented Skin and Vascular Lesions Using the 532 Nm Laser

Purpose

Esthetic medicine is a rapidly developing field of medicine that is not only beneficial in terms of external appearance, but also significantly improves overall quality of life. Currently, pigmented and vascular skin lesions are more prevalent due to multiple environmental factors and are a characteristic manifestation of skin aging. The development of modern laser therapy has contributed to the successful management of multiple skin conditions. The aim of our study was to show the effect of concomitant reduction of both vascular and hyperpigmented skin lesions located on the facial area after repetitive 532 nm laser therapy and to emphasize that the detection of such observation was possible due to the implementation of System of Skin Analysis and Assessment.

Patients and Methods

We retrospectively analyzed 100 patients' records with "VISIA" Skin Analysis System after 532nm laser therapy.

Results

Laser therapy significantly decreased VISIA scores for all tested lesions, ie, macules, pigmented and vascular lesions (p<0.0001 for all). The efficacy of laser treatment was not significantly different regarding skin phototype (p>0.05) and did not correlate with age of participants (p>0.05). The more laser sessions were performed, the higher improvement in vascular lesion VISIA scores was observed (r=0.26, p=0.0097).

Conclusion

532 nm laser therapy is effective regarding vascular and hyperpigmented skin lesions located on the facial area. The System of Skin Analysis and Assessment is a good tool to test the treatment efficacy during regular follow-up procedure.

System for the Recognizing of Pigmented Skin Lesions with Fusion and Analysis of Heterogeneous Data Based on a Multimodal Neural Network

Simple Summary

Skin cancer is one of the most common cancers in humans. This study aims to create a system for recognizing pigmented skin lesions by analyzing heterogeneous data based on a multimodal neural network. Fusing patient statistics and multidimensional visual data allows for finding additional links between dermoscopic images and medical diagnostic results, significantly improving neural network classification accuracy. The use by specialists of the proposed system of neural network recognition of pigmented skin lesions will enhance the efficiency of diagnosis compared to visual diagnostic methods.

Abstract

Today, skin cancer is one of the most common malignant neoplasms in the human body. Diagnosis of pigmented lesions is challenging even for experienced dermatologists due to the wide range of morphological manifestations. Artificial intelligence technologies are capable of equaling and even surpassing the capabilities of a dermatologist in terms of efficiency. The main problem of implementing intellectual analysis systems is low accuracy. One of the possible ways to increase this indicator is using stages of preliminary processing of visual data and the use of heterogeneous data. The article proposes a multimodal neural network system for identifying pigmented skin lesions with a preliminary identification, and removing hair from dermatoscopic images. The novelty of the proposed system lies in the joint use of the stage of preliminary cleaning of hair structures and a multimodal neural network system for the analysis of heterogeneous data. The accuracy of pigmented skin lesions recognition in 10 diagnostically significant categories in the proposed system was 83.6%. The use of the proposed system by dermatologists as an auxiliary diagnostic method will minimize the impact of the human factor, assist in making medical decisions, and expand the possibilities of early detection of skin cancer.

The Study of Usefulness of a Set of Fractal Parameters to Build Classes of Disease Units Based on Images of Pigmented Skin Lesions

Dermatoscopic images are also increasingly used to train artificial neural networks for the future to provide fully automatic diagnostic systems capable of determining the type of pigmented skin lesion. Therefore, fractal analysis was used in this study to measure the irregularity of pigmented skin lesion surfaces. This paper presents selected results from individual stages of preliminary processing of the dermatoscopic image on pigmented skin lesion, in which fractal analysis was used and referred to the effectiveness of classification by fuzzy or statistical methods. Classification of the first unsupervised stage was performed using the method of analysis of scatter graphs and the fuzzy method using the Kohonen network. The results of the Kohonen network learning process with an input vector consisting of eight elements prove that neuronal activation requires a larger learning set with greater differentiation. For the same training conditions, the final results are at a higher level and can be classified as weaker. Statistics of factor analysis were proposed, allowing for the reduction in variables, and the directions of further studies were indicated.

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.

Performance of a computer-aided digital dermoscopic image analyzer for melanoma detection in 1,076 pigmented skin lesion biopsies

BACKGROUND

Digital dermoscopic image analysis of pigmented skin lesions (PSLs) has become increasingly popular, despite its unclear clinical utility. Unbiased, high-powered studies investigating the efficacy of commercially available systems are limited.

OBJECTIVE

To investigate the diagnostic performance of the FotoFinder Mole-Analyzer in assessing PSLs for cutaneous melanoma.

METHODS

In this 15-year retrospective study, the histopathologies of 1076 biopsied PSLs among a total of 2500 imaged PSLs were collected. The biopsied PSLs were categorized as benign or malignant (cutaneous melanoma) based on histopathology. Analyzer scores (0-1.00) for these PSLs were obtained and grouped according to histopathology.

RESULTS

At an optimized cutoff score of 0.50, a sensitivity of 56% and a specificity of 74% were achieved. The area under the receiver operating characteristics curve was 0.698, indicating poor accuracy as a diagnostic tool.

LIMITATIONS

This study had a retrospective design and involved only a single institution.

CONCLUSION

Our study reveals a low sensitivity of the scoring function of this digital dermoscopic image analyzer for detecting cutaneous melanomas. Physicians must apply keen clinical judgment when using such devices in the screening of suspicious PSLs.

Estimating melanin location in the pigmented skin lesions by hue-saturation-lightness color space values of dermoscopic images

The depth of melanin in the skin can be estimated roughly by observation of the color exhibited on dermoscopy. Currently, there are no objective methods to estimate it. The aim of the present study was to clarify the relationship between the depth of melanin in the skin and the color variation exhibited, and to objectively estimate the 3-D location of melanin in the pigmented skin lesions from dermoscopic images. Representative colors in dermoscopic images of acral compound nevus, Spitz nevus and blue nevus were evaluated by the subjectively perceived color on dermoscopy and objective values in hue-saturation-lightness color space values. Brown colors due to small quantities of superficial melanin in the skin had high saturation and low lightness values, whereas black colors due to large quantities of superficial melanin had low saturation and low lightness values. On the other hand, colors due to melanin in the dermis were perceived as blue-gray on dermoscopy, but extracted colors showed gray-brown hue and intermediate saturation and high lightness values. In all cases, extracted representative colors of pigmented skin lesions had similar hue values within the red-orange range. Objective estimation of the 3-D location of melanin in the pigmented skin lesions is possible by the saturation and lightness values of the colors extracted from dermoscopic images. Subjectively perceived colors of melanin, especially in the dermis, can be modified by the surrounding environment effect and blue color perception.

The diagnostic value and histologic correlate of distinct patterns of shiny white streaks for the diagnosis of melanoma: A retrospective, case-control study

BACKGROUND

Shiny white streaks (SWSs) are best visualized with polarized dermoscopy and correlate with dermal fibroplasia histopathologically. SWSs have been described at higher frequencies in melanomas than in benign nevi.

OBJECTIVE

We assessed the diagnostic value of different patterns of SWSs and their histologic correlate in melanocytic lesions.

METHODS

Polarized dermoscopic images of 1507 histopathologically diagnosed melanocytic neoplasms were analyzed for presence and pattern of SWSs. Histology was also reviewed for correlation.

RESULTS

Among 1507 melanocytic neoplasms, SWSs were observed in 31 of 144 melanomas (22%) and 22 of 1363 benign neoplasms (1.6%) (P < .001). The sensitivity and specificity of SWSs for melanoma were 22% and 98%, respectively. Diffuse SWSs exhibited the greatest diagnostic value for melanoma, with sensitivity of 11.8% and specificity of 99.5%. Focal central and peripheral SWSs were comparable in diagnostic significance. The presence of SWSs was highly uncommon in dysplastic nevi, whereas in certain benign subgroups of nevi such as Spitz nevi and atypical genital special site nevi, SWSs were not uncommon. Diffuse SWSs correlated with greater breadth of deep fibroplasia than focal SWSs (P = .009), and SWSs correlated with greater Breslow depth among melanomas (P = .007).

LIMITATIONS

This study was retrospective.

CONCLUSION

Polarized dermoscopy is a valuable diagnostic tool in the identification of SWSs, a feature that is highly specific for melanoma.

Standardization of terminology in dermoscopy/dermatoscopy: Results of the third consensus conference of the International Society of Dermoscopy

BACKGROUND

Evolving dermoscopic terminology motivated us to initiate a new consensus.

OBJECTIVE

We sought to establish a dictionary of standardized terms.

METHODS

We reviewed the medical literature, conducted a survey, and convened a discussion among experts.

RESULTS

Two competitive terminologies exist, a more metaphoric terminology that includes numerous terms and a descriptive terminology based on 5 basic terms. In a survey among members of the International Society of Dermoscopy (IDS) 23.5% (n = 201) participants preferentially use descriptive terminology, 20.1% (n = 172) use metaphoric terminology, and 484 (56.5%) use both. More participants who had been initially trained by metaphoric terminology prefer using descriptive terminology than vice versa (9.7% vs 2.6%, P < .001). Most new terms that were published since the last consensus conference in 2003 were unknown to the majority of the participants. There was uniform consensus that both terminologies are suitable, that metaphoric terms need definitions, that synonyms should be avoided, and that the creation of new metaphoric terms should be discouraged. The expert panel proposed a dictionary of standardized terms taking account of metaphoric and descriptive terms.

LIMITATIONS

A consensus seeks a workable compromise but does not guarantee its implementation.

CONCLUSION

The new consensus provides a revised framework of standardized terms to enhance the consistent use of dermoscopic terminology.

Using the 7-point checklist as a diagnostic aid for pigmented skin lesions in general practice: a diagnostic validation study

BACKGROUND

GPs need to recognise significant pigmented skin lesions, given rising UK incidence rates for malignant melanoma. The 7-point checklist (7PCL) has been recommended by NICE (2005) for routine use in UK general practice to identify clinically significant lesions which require urgent referral.

AIM

To validate the Original and Weighted versions of the 7PCL in the primary care setting.

DESIGN AND SETTING

Diagnostic validation study, using data from a SIAscopic diagnostic aid randomised controlled trial in eastern England.

METHOD

Adults presenting in general practice with a pigmented skin lesion that could not be immediately diagnosed as benign were recruited into the trial. Reference standard diagnoses were histology or dermatology expert opinion; 7PCL scores were calculated blinded to the reference diagnosis. A case was defined as a clinically significant lesion for primary care referral to secondary care (total 1436 lesions: 225 cases, 1211 controls); or melanoma (36).

RESULTS

For diagnosing clinically significant lesions there was a difference between the performance of the Original and Weighted 7PCLs (respectively, area under curve: 0.66, 0.69, difference = 0.03, P<0.001). For the identification of melanoma, similar differences were found. Increasing the Weighted 7PCL's cut-off score from recommended 3 to 4 improved detection of clinically significant lesions in primary care: sensitivity 73.3%, specificity 57.1%, positive predictive value 24.1%, negative predictive value 92.0%, while maintaining high sensitivity of 91.7% and moderate specificity of 53.4% for melanoma.

CONCLUSION

The Original and Weighted 7PCLs both performed well in a primary care setting to identify clinically significant lesions as well as melanoma. The Weighted 7PCL, with a revised cut-off score of 4 from 3, performs slightly better and could be applied in general practice to support the recognition of clinically significant lesions and therefore the early identification of melanoma.

Computerized evaluation of pigmented skin lesion images recorded by a videomicroscope: comparison between polarizing mode observation and oil/slide mode observation

BACKGROUND/AIMS

It has now been established that ELM significantly improves the clinical diagnosis of pigmented skin lesions, particularly when associated with image analysis on digital pictures. Besides surface microscopes, so called "videomicroscopes" are nowadays commercially available. Thanks to their practicality and to their reasonable price and small volume, they could be usefully employed by general practitioners or peripheral dermatologists in their practice. The aim of our study was to evaluate the usefulness and the handiness of a videomicroscope provided with polarized light, and to compare images recorded in the polarizing mode to those of the same lesions recorded after application of oil and a glass slide.

METHODS

114 images of benign pigmented skin lesions were recorded both in polarizing mode and in oil/slide mode observation. Digital images were then analyzed by means of a dedicated software, evaluating 34 different parameters.

RESULTS

The instrument is easy to handle and the acquisition of images is simple and quick. Polarizing mode observation enables the recognition of subsurface structures, like pigment network and capillaries. Red and blue components in the images tend to be more pronounced, when images are acquired by the polarizing system, whereas green components are prominent in oil images. Values referring to dark areas are also higher for oil images. However, the 2 observation modes provide digital images, whose values, in most cases, do not differ statistically.

CONCLUSION

Videomicroscopes are cheap, space saving, and enable a quick examination of skin areas to be imaged. The possibility of a rapid switch from surface to subsurface polarizing mode observation, makes the examination procedure even faster. Our data demonstrate that polarizing mode observation and recording can be employed as a basis for clinical and computerized epiluminescence, particularly in situations, where a rapid screening of numerous patients and lesions is necessary.