State of the art in non-invasive imaging of cutaneous melanoma

Functional and molecular 3D mapping of angiosarcoma tumor using non-invasive laser speckle, hyperspectral, and photoacoustic imaging

PURPOSE

The gold standard for skin cancer diagnosis is surgical excisional biopsy and histopathological examination. Several non-invasive diagnostic techniques exist, although they have not yet translated into clinical use. This is a proof-of-concept study to assess the possibility of imaging an angiosarcoma in the periocular area.

METHODS

We use laser speckle, hyperspectral, and photoacoustic imaging to monitor blood perfusion and oxygen saturation, as well as the molecular composition of the tissue. The information obtained from each imaging modality was combined in order to yield a more comprehensive picture of the function, as well as molecular composition of a rapidly growing cutaneous angiosarcoma in the periocular area.

RESULTS

We found an increase in perfusion coupled with a reduction in oxygen saturation in the angiosarcoma. We could also extract the molecular composition of the angiosarcoma at a depth, depicting both the oxygen saturation and highlighting the presence of connective tissue via collagen.

CONCLUSIONS

We demonstrate the different physiological parameters that can be obtained with the different techniques and how these can be combined to provide detailed 3D maps of the functional and molecular properties of tumors useful in preoperative assessment.

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.

The Role of Artificial Intelligence in Early Diagnosis and Molecular Classification of Head and Neck Skin Cancers: A Multidisciplinary Approach

Cancer remains a significant global health concern, with increasing genetic and metabolic irregularities linked to its onset. Among various forms of cancer, skin cancer, including squamous cell carcinoma, basal cell carcinoma, and melanoma, is on the rise worldwide, often triggered by ultraviolet (UV) radiation. The propensity of skin cancer to metastasize highlights the importance of early detection for successful treatment. This narrative review explores the evolving role of artificial intelligence (AI) in diagnosing head and neck skin cancers from both radiological and pathological perspectives. In the past two decades, AI has made remarkable progress in skin cancer research, driven by advances in computational capabilities, digitalization of medical images, and radiomics data. AI has shown significant promise in image-based diagnosis across various medical domains. In dermatology, AI has played a pivotal role in refining diagnostic and treatment strategies, including genomic risk assessment. This technology offers substantial potential to aid primary clinicians in improving patient outcomes. Studies have demonstrated AI's effectiveness in identifying skin lesions, categorizing them, and assessing their malignancy, contributing to earlier interventions and better prognosis. The rising incidence and mortality rates of skin cancer, coupled with the high cost of treatment, emphasize the need for early diagnosis. Further research and integration of AI into clinical practice are warranted to maximize its benefits in skin cancer diagnosis and treatment.

Machine Learning Analysis of Human Skin by Optoacoustic Mesoscopy for Automated Extraction of Psoriasis and Aging Biomarkers

Ultra-wideband raster-scan optoacoustic mesoscopy (RSOM) is a novel modality that has demonstrated unprecedented ability to visualize epidermal and dermal structures in-vivo. However, an automatic and quantitative analysis of three-dimensional RSOM datasets remains unexplored. In this work we present our framework: Deep Learning RSOM Analysis Pipeline (DeepRAP), to analyze and quantify morphological skin features recorded by RSOM and extract imaging biomarkers for disease characterization. DeepRAP uses a multi-network segmentation strategy based on convolutional neural networks with transfer learning. This strategy enabled the automatic recognition of skin layers and subsequent segmentation of dermal microvasculature with an accuracy equivalent to human assessment. DeepRAP was validated against manual segmentation on 25 psoriasis patients under treatment and our biomarker extraction was shown to characterize disease severity and progression well with a strong correlation to physician evaluation and histology. In a unique validation experiment, we applied DeepRAP in a time series sequence of occlusion-induced hyperemia from 10 healthy volunteers. We observe how the biomarkers decrease and recover during the occlusion and release process, demonstrating accurate performance and reproducibility of DeepRAP. Furthermore, we analyzed a cohort of 75 volunteers and defined a relationship between aging and microvascular features in-vivo. More precisely, this study revealed that fine microvascular features in the dermal layer have the strongest correlation to age. The ability of our newly developed framework to enable the rapid study of human skin morphology and microvasculature in-vivo promises to replace biopsy studies, increasing the translational potential of RSOM.

Melanoma Detection Using Deep Learning-Based Classifications

One of the most prevalent cancers worldwide is skin cancer, and it is becoming more common as the population ages. As a general rule, the earlier skin cancer can be diagnosed, the better. As a result of the success of deep learning (DL) algorithms in other industries, there has been a substantial increase in automated diagnosis systems in healthcare. This work proposes DL as a method for extracting a lesion zone with precision. First, the image is enhanced using Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) to improve the image's quality. Then, segmentation is used to segment Regions of Interest (ROI) from the full image. We employed data augmentation to rectify the data disparity. The image is then analyzed with a convolutional neural network (CNN) and a modified version of Resnet-50 to classify skin lesions. This analysis utilized an unequal sample of seven kinds of skin cancer from the HAM10000 dataset. With an accuracy of 0.86, a precision of 0.84, a recall of 0.86, and an F-score of 0.86, the proposed CNN-based Model outperformed the earlier study's results by a significant margin. The study culminates with an improved automated method for diagnosing skin cancer that benefits medical professionals and patients.

Recent advances in optical imaging through deep tissue: imaging probes and techniques

Optical imaging has been essential for scientific observations to date, however its biomedical applications has been restricted due to its poor penetration through tissues. In living tissue, signal attenuation and limited imaging depth caused by the wave distortion occur because of scattering and absorption of light by various molecules including hemoglobin, pigments, and water. To overcome this, methodologies have been proposed in the various fields, which can be mainly categorized into two stategies: developing new imaging probes and optical techniques. For example, imaging probes with long wavelength like NIR-II region are advantageous in tissue penetration. Bioluminescence and chemiluminescence can generate light without excitation, minimizing background signals. Afterglow imaging also has high a signal-to-background ratio because excitation light is off during imaging. Methodologies of adaptive optics (AO) and studies of complex media have been established and have produced various techniques such as direct wavefront sensing to rapidly measure and correct the wave distortion and indirect wavefront sensing involving modal and zonal methods to correct complex aberrations. Matrix-based approaches have been used to correct the high-order optical modes by numerical post-processing without any hardware feedback. These newly developed imaging probes and optical techniques enable successful optical imaging through deep tissue. In this review, we discuss recent advances for multi-scale optical imaging within deep tissue, which can provide reseachers multi-disciplinary understanding and broad perspectives in diverse fields including biophotonics for the purpose of translational medicine and convergence science.

Management of cutaneous melanoma: radiologists challenging and risk assessment

Melanoma patient remains a challenging for the radiologist, due to the difficulty related to the management of a patient more often in an advanced stage of the disease. It is necessary to determine a stratification of risk, optimizing the means, with diagnostic tools that should be optimized in relation to the type of patient, and improving knowledge. Staging and risk assessment procedures are determined by disease presentation at diagnosis. Melanoma staging is a critical tool to assist clinical decision-making and prognostic assessment. It is used for clinical trial design, eligibility, stratification, and analysis. The current standard for regional lymph nodes staging is represented by the sentinel lymph node excision biopsy procedure. For staging of distant metastases, PET-CT has the highest sensitivity and diagnostic odds ratio. Similar trend is observed during melanoma surveillance. The advent of immunotherapy, which has improved patient outcome, however, has determined new issues for radiologists, partly due to atypical response patterns, partly due to adverse reactions that must be identified as soon as possible for the correct management of the patient. The main objectives of the new ir-criteria are to standardize the assessment between different trials. However, these ir-criteria do not take into account all cases of atypical response patterns, as hyperprogression or dissociated responses. None of these criteria has actually been uniformly adopted in routine. The immune-related adverse events (irAEs) can involve various organs from head to toe. It is crucial for radiologists to know the imaging appearances of this condition, to exclude recurrent or progressive disease and for pneumonitis, since it could be potentially life-threatening toxicity, resulting in pneumonitis-related deaths in early phase trials, to allow a proper patient management.

Fast raster-scan optoacoustic mesoscopy enables assessment of human melanoma microvasculature in vivo

Melanoma is associated with angiogenesis and vascular changes that may extend through the entire skin depth. Three-dimensional imaging of vascular characteristics in skin lesions could therefore allow diagnostic insights not available by conventional visual inspection. Raster-scan optoacoustic mesoscopy (RSOM) images microvasculature through the entire skin depth with resolutions of tens of micrometers; however, current RSOM implementations are too slow to overcome the strong breathing motions on the upper torso where melanoma lesions commonly occur. To enable high-resolution imaging of melanoma vasculature in humans, we accelerate RSOM scanning using an illumination scheme that is coaxial with a high-sensitivity ultrasound detector path, yielding 15 s single-breath-hold scans that minimize motion artifacts. We apply this Fast RSOM to image 10 melanomas and 10 benign nevi in vivo, showing marked differences between malignant and benign lesions, supporting the possibility to use biomarkers extracted from RSOM imaging of vasculature for lesion characterization to improve diagnostics.

Raster-Scanning-Optoacoustic Mesoscopy can be used to image the vasculature in skin cancer lesions but is limited by a long exposure time. Here; the authors increase the speed of the imaging using co-axial illumination and a high-sensitivity ultrasound detector path.

Photoacoustic imaging of periorbital skin cancer ex vivo: unique spectral signatures of malignant melanoma, basal, and squamous cell carcinoma

Radical excision of periorbital skin tumors is difficult without sacrificing excessive healthy tissue. Photoacoustic (PA) imaging is an emerging non-invasive biomedical imagi--ng modality that has potential for intraoperative micrographic control of surgical margins. This is the first study to assess the feasibility of PA imaging for the detection of periocular skin cancer. Eleven patients underwent surgical excision of periocular skin cancer, one of which was a malignant melanoma (MM), eight were basal cell carcinomas (BCCs), and two squamous cell carcinomas (SCCs). Six tumors were located in the eyelid, and five in periocular skin. The excised samples, as well as healthy eyelid samples, were scanned with PA imaging postoperatively, using 59 wavelengths in the range 680-970 nm, to generate 3D multispectral images. Spectral unmixing was performed using endmember spectra for oxygenated and deoxygenated Hb, melanin, and collagen, to iden--tify the chromophore composition of tumors and healthy eyelid tissue. After PA scanning, the tumor samples were examined histopathologically using standard hematoxylin and eosin staining. The PA spectra of healthy eyelid tissue were dominated by melanin in the skin, oxygenated and deoxygenated hemoglobin in the orbicularis oculi muscle, and collagen in the tarsal plate. Multiwavelength 3D scanning provided spectral information on the three tumor types. The spectrum from the MM was primarily reconstructed by the endmember melanin, while the SCCs showed contributions primarily from melanin, but also HbR and collagen. BCCs showed contributions from all four endmembers with a predominance of HbO₂ and HbR. PA imaging may be used to distinguish different kinds of periocular skin tumors, paving the way for future intraoperative micrographic control.

Comparison of photoacoustic imaging and histopathological examination in determining the dimensions of 52 human melanomas and nevi ex vivo

Surgical excision followed by histopathological examination is the gold standard for the diagnosis and staging of melanoma. Reoperations and unnecessary removal of healthy tissue could be reduced if non-invasive imaging techniques were available for presurgical tumor delineation. However, no technique has gained widespread clinical use to date due to shallow imaging depth or the absence of functional imaging capability. Photoacoustic (PA) imaging is a novel technology that combines the strengths of optical and ultrasound imaging to reveal the molecular composition of tissue at high resolution. Encouraging results have been obtained from previous animal and human studies on melanoma, but there is still a lack of clinical data. This is the largest study of its kind to date, including 52 melanomas and nevi. 3D multiwavelength PA scanning was performed ex vivo, using 59 excitation wavelengths from 680 nm to 970 nm. Spectral unmixing over this broad wavelength range, accounting for the absorption of several tissue chromophores, provided excellent contrast between healthy tissue and tumor. Combining the results of spectral analysis with spatially resolved information provided a map of the tumor borders in greater detail than previously reported. The tumor dimensions determined with PA imaging were strongly correlated with those determined by histopathological examination for both melanomas and nevi.

Efficient Unet with depth-aware gated fusion for automatic skin lesion segmentation

Melanoma is a very serious disease. The segmentation of skin lesions is a critical step for diagnosing melanoma. However, skin lesions possess the characteristics of large size variations, irregular shapes, blurring borders, and complex background information, thus making the segmentation of skin lesions remain a challenging problem. Though deep learning models usually achieve good segmentation performance for skin lesion segmentation, they have a large number of parameters and FLOPs, which limits their application scenarios. These models also do not make good use of low-level feature maps, which are essential for predicting detailed information. The Proposed EUnet-DGF uses MBconv to implement its lightweight encoder and maintains a strong encoding ability. Moreover, the depth-aware gated fusion block designed by us can fuse feature maps of different depths and help predict pixels on small patterns. The experiments conducted on the ISIC 2017 dataset and PH2 dataset show the superiority of our model. In particular, EUnet-DGF only accounts for 19% and 6.8% of the original Unet in terms of the number of parameters and FLOPs. It possesses a great application potential in practical computer-aided diagnosis systems.

Empirical assessment of laser safety for photoacoustic-guided liver surgeries

Photoacoustic imaging is a promising technique to provide guidance during multiple surgeries and procedures. One challenge with this technique is that major blood vessels in the liver are difficult to differentiate from surrounding tissue within current safety limits, which only exist for human skin and eyes. In this paper, we investigate the safety of raising this limit for liver tissue excited with a 750 nm laser wavelength and approximately 30 mJ laser energy (corresponding to approximately 150 mJ/cm² fluence). Laparotomies were performed on six swine to empirically investigate potential laser-related liver damage. Laser energy was applied for temporal durations of 1 minute, 10 minutes, and 20 minutes. Lasered liver lobes were excised either immediately after laser application (3 swine) or six weeks after surgery (3 swine). Cell damage was assessed using liver damage blood biomarkers and histopathology analyses of 41 tissue samples total. The biomarkers were generally normal over a 6 week post-surgical in vivo study period. Histopathology revealed no cell death, although additional pathology was present (i.e., hemorrhage, inflammation, fibrosis) due to handling, sample resection, and fibrous adhesions as a result of the laparotomy. These results support a new protocol for studying laser-related liver damage, indicating the potential to raise the safety limit for liver photoacoustic imaging to approximately 150 mJ/cm² with a laser wavelength of 750 nm and for imaging durations up to 10 minutes without causing cell death. This investigation and protocol may be applied to other tissues and extended to additional wavelengths and energies, which is overall promising for introducing new tissue-specific laser safety limits for photoacoustic-guided surgery.

Melanoma Biomarkers and Their Potential Application for In Vivo Diagnostic Imaging Modalities

Melanoma is the deadliest form of skin cancer and remains a diagnostic challenge in the dermatology clinic. Several non-invasive imaging techniques have been developed to identify melanoma. The signal source in each of these modalities is based on the alteration of physical characteristics of the tissue from healthy/benign to melanoma. However, as these characteristics are not always sufficiently specific, the current imaging techniques are not adequate for use in the clinical setting. A more robust way of melanoma diagnosis is to "stain" or selectively target the suspect tissue with a melanoma biomarker attached to a contrast enhancer of one imaging modality. Here, we categorize and review known melanoma diagnostic biomarkers with the goal of guiding skin imaging experts to design an appropriate diagnostic tool for differentiating between melanoma and benign lesions with a high specificity and sensitivity.

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.

DSNet: Automatic dermoscopic skin lesion segmentation

BACKGROUND AND OBJECTIVE

Automatic segmentation of skin lesions is considered a crucial step in Computer-aided Diagnosis (CAD) systems for melanoma detection. Despite its significance, skin lesion segmentation remains an unsolved challenge due to their variability in color, texture, and shapes and indistinguishable boundaries.

METHODS

Through this study, we present a new and automatic semantic segmentation network for robust skin lesion segmentation named Dermoscopic Skin Network (DSNet). In order to reduce the number of parameters to make the network lightweight, we used a depth-wise separable convolution in lieu of standard convolution to project the learned discriminating features onto the pixel space at different stages of the encoder. Additionally, we implemented both a U-Net and a Fully Convolutional Network (FCN8s) to compare against the proposed DSNet.

RESULTS

We evaluate our proposed model on two publicly available datasets, namely ISIC-2017¹ and PH2². The obtained mean Intersection over Union (mIoU) is 77.5% and 87.0% respectively for ISIC-2017 and PH2 datasets which outperformed the ISIC-2017 challenge winner by 1.0% with respect to mIoU. Our proposed network also outperformed U-Net and FCN8s respectively by 3.6% and 6.8% with respect to mIoU on the ISIC-2017 dataset.

CONCLUSION

Our network for skin lesion segmentation outperforms the other methods discussed in the article and is able to provide better-segmented masks on two different test datasets which can lead to better performance in melanoma detection. Our trained model along with the source code and predicted masks are made publicly available³.

Histologic Features Associated With an Invasive Component in Lentigo Maligna Lesions

Importance

Lentigo maligna (LM) presents an invasive component in up to 20% of biopsied cases, but to date the histologic features useful in detecting this invasive component have not been described. Some histologic characteristics are hypothesized to contribute to the progression of LM invasion.

Objective

To identify the histologic characteristics associated with lentigo maligna melanoma (LMM) in patients with LM diagnosed by a partial diagnostic biopsy.

Design, Setting, and Participants

A retrospective cross-sectional study of patients treated between January 1, 2000, and December 31, 2017, was conducted in a referral oncology center in València, Spain. Data and specimens of patients (n = 96) with a diagnosis of primary cutaneous melanoma in the form of either LM or LMM who had undergone surgical treatment, a complete histologic examination of the whole tumor, and an initial diagnostic partial biopsy of LM were included in the study. Histologic assessment was blinded to the presence of an invasive component.

Interventions

All biopsy specimens were evaluated for the presence of certain histologic characteristics.

Main Outcomes and Measures

Comparisons between invasive samples and samples without an invasive component were performed. The differences in the distribution of variables between the groups were assessed using the χ2 and Fisher exact tests, and the degree of association of the relevant variables was quantified by logistic regression models. A classification and regression tree analysis was performed to rank the variables by importance.

Results

In total, 96 patients had sufficient histologic material that could be evaluated. The patients were predominantly male (56 [58.3%]) and had a mean (SD) age at diagnosis of 72 (12) years. Of these patients, 63 (65.6%) had an LM diagnosis and 33 (34.4%) had an LMM diagnosis (an invasive component). The histologic variables associated with the presence of an invasive component were melanocytes forming rows (odds ratio [OR], 11.5; 95% CI, 1.4-94.1; P = .02), subepidermal clefts (OR, 2.8; 95% CI, 1.0-7.9; P = .049), nests (OR, 3.0; 95% CI, 1.1-8.6; P = .04), and a lesser degree of solar elastosis (OR, 0.4; 95% CI, 0.1-1.1; P = .07). A classification and regression tree analysis of the relevant histologic features was able to accurately identify lentigo maligna with an invasive component (LMM) in more than 60% of patients.

Conclusions and Relevance

These findings may be useful in classifying early LM specimens at higher risk of invasion, which may eventually be relevant in identifying the most appropriate management for LM.

Photoacoustic clinical imaging

Photoacoustic is an emerging biomedical imaging modality, which allows imaging optical absorbers in the tissue by acoustic detectors (light in - sound out). Such a technique has an immense potential for clinical translation since it allows high resolution, sufficient imaging depth, with diverse endogenous and exogenous contrast, and is free from ionizing radiation. In recent years, tremendous developments in both the instrumentation and imaging agents have been achieved. These opened avenues for clinical imaging of various sites allowed applications such as brain functional imaging, breast cancer screening, diagnosis of psoriasis and skin lesions, biopsy and surgery guidance, the guidance of tumor therapies at the reproductive and urological systems, as well as imaging tumor metastases at the sentinel lymph nodes. Here we survey the various clinical and pre-clinical literature and discuss the potential applications and hurdles that still need to be overcome.

Edge detector-based automatic segmentation of the skin layers and application to moisturization in high-resolution 3 Tesla magnetic resonance imaging

INTRODUCTION

Previous studies have demonstrated the feasibility to explore moisturization with quantification imaging based on T2 mapping. The aim of this study was to describe and validate the first robust automated method to segment the first layers of the skin.

MATERIALS AND METHODS

Data were picked from a previous study that included 35 healthy subjects who underwent a 3T MRI (multi spin echo calculation T2-weighted sequence) with a microscopic coil on the left heel before and one hour after moisturization. The automatic algorithm was composed of the T2 map generation, a Canny filter, a selection of boundaries, and a local regression to delimitate stratum corneum, epidermis, and dermis. An automated affine registration was applied between the exams before and after moisturization.

RESULTS

The failure rate of the algorithm was below 5%. Mean computation time was 139.12s. There was a significant and strong correlation between the automatic measurements and the manual ones for the T2 values (ρ: 0.905, P < 0.001) and for the thickness measurements (ρ: 0.8663; P < 0.001). For registration, mean of the Dice index was 0.64 [0.47; 0.80] and of the Hausdorff distance was 0.29 mm 95% CI: [0.28; 0.30].

CONCLUSION

The proposed automatic method to study the first skin layers in 3T MRI using micro-coils was robust and described T2 values and thickness measurements with a strong correlation to manual measurements. The use of an automated affine registration could also permit the generation of a mapping for a visual assessment of moisturization.

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.

Computational methods for the image segmentation of pigmented skin lesions: A review

BACKGROUND AND OBJECTIVES

Because skin cancer affects millions of people worldwide, computational methods for the segmentation of pigmented skin lesions in images have been developed in order to assist dermatologists in their diagnosis. This paper aims to present a review of the current methods, and outline a comparative analysis with regards to several of the fundamental steps of image processing, such as image acquisition, pre-processing and segmentation.

METHODS

Techniques that have been proposed to achieve these tasks were identified and reviewed. As to the image segmentation task, the techniques were classified according to their principle.

RESULTS

The techniques employed in each step are explained, and their strengths and weaknesses are identified. In addition, several of the reviewed techniques are applied to macroscopic and dermoscopy images in order to exemplify their results.

CONCLUSIONS

The image segmentation of skin lesions has been addressed successfully in many studies; however, there is a demand for new methodologies in order to improve the efficiency.

Multimodal nonlinear microscopy of head and neck carcinoma - toward surgery assisting frozen section analysis

BACKGROUND

Treatment of early cancer stages is deeply connected to a good prognosis, a moderate reduction of the quality of life, and comparably low treatment costs.

METHODS

Head and neck squamous cell carcinomas were investigated using the multimodal combination of coherent anti-Stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF), and second-harmonic generation (SHG) microscopy.

RESULTS

An increased median TPEF to CARS contrast was found comparing cancerous and healthy squamous epithelium with a p value of 1.8·10(-10) . A following comprehensive image analysis was able to predict the diagnosis of imaged tissue sections with an overall accuracy of 90% for a 4-class model.

CONCLUSION

Nonlinear multimodal imaging is verified objectively as a valuable diagnostic tool that complements conventional staining protocols and can serve as filter in future clinical routine reducing the pathologist's workload. © 2016 Wiley Periodicals, Inc. Head Neck 38: First-1552, 2016.

Methods of Melanoma Detection

Detection and removal of melanoma, before it has metastasized, dramatically improves prognosis and survival. The purpose of this chapter is to (1) summarize current methods of melanoma detection and (2) review state-of-the-art detection methods and technologies that have the potential to reduce melanoma mortality. Current strategies for the detection of melanoma range from population-based educational campaigns and screening to the use of algorithm-driven imaging technologies and performance of assays that identify markers of transformation. This chapter will begin by describing state-of-the-art methods for educating and increasing awareness of at-risk individuals and for performing comprehensive screening examinations. Standard and advanced photographic methods designed to improve reliability and reproducibility of the clinical examination will also be reviewed. Devices that magnify and/or enhance malignant features of individual melanocytic lesions (and algorithms that are available to interpret the results obtained from these devices) will be compared and contrasted. In vivo confocal microscopy and other cellular-level in vivo technologies will be compared to traditional tissue biopsy, and the role of a noninvasive "optical biopsy" in the clinical setting will be discussed. Finally, cellular and molecular methods that have been applied to the diagnosis of melanoma, such as comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH), and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), will be discussed.

A comparative study of the effects of retinol and retinoic acid on histological, molecular, and clinical properties of human skin

BACKGROUND

All-trans retinol, a precursor of retinoic acid, is an effective anti-aging treatment widely used in skin care products. In comparison, topical retinoic acid is believed to provide even greater anti-aging effects; however, there is limited research directly comparing the effects of retinol and retinoic acid on skin.

OBJECTIVES

In this study, we compare the effects of retinol and retinoic acid on skin structure and expression of skin function-related genes and proteins. We also examine the effect of retinol treatment on skin appearance.

METHODS

Skin histology was examined by H&E staining and in vivo confocal microscopy. Expression levels of skin genes and proteins were analyzed using RT-PCR and immunohistochemistry. The efficacy of a retinol formulation in improving skin appearance was assessed using digital image-based wrinkle analysis.

RESULTS

Four weeks of retinoic acid and retinol treatments both increased epidermal thickness, and upregulated genes for collagen type 1 (COL1A1), and collagen type 3 (COL3A1) with corresponding increases in procollagen I and procollagen III protein expression. Facial image analysis showed a significant reduction in facial wrinkles following 12 weeks of retinol application.

CONCLUSIONS

The results of this study demonstrate that topical application of retinol significantly affects both cellular and molecular properties of the epidermis and dermis, as shown by skin biopsy and noninvasive imaging analyses. Although the magnitude tends to be smaller, retinol induces similar changes in skin histology, and gene and protein expression as compared to retinoic acid application. These results were confirmed by the significant facial anti-aging effect observed in the retinol efficacy clinical study.

Handheld photoacoustic probe to detect both melanoma depth and volume at high speed in vivo

We applied a linear-array-based photoacoustic probe to detect melanin-containing melanoma tumor depth and volume in nude mice in vivo. This system can image melanomas at five frames per second (fps), which is much faster than our previous handheld single transducer system (0.1 fps). We first theoretically show that, in addition to the higher frame rate, almost the entire boundary of the melanoma can be detected by the linear-array-based probe, while only the horizontal boundary could be detected by the previous system. Then we demonstrate the ability of this linear-array-based system in measuring both the depth and volume of melanoma through phantom, ex vivo, and in vivo experiments. The volume detection ability also enables us to accurately calculate the rate of growth of the tumor, which is an important parameter in quantifying the tumor activity. Our results show that this system can be used for clinical melanoma diagnosis and treatment in humans at the bedside. Linear-array-based PA images of melanoma acquired in vivo on day 3 (a) and day 6 (b).

A Review of the Quantification and Classification of Pigmented Skin Lesions: From Dedicated to Hand-Held Devices

In recent years, the incidence of skin cancer cases has risen, worldwide, mainly due to the prolonged exposure to harmful ultraviolet radiation. Concurrently, the computer-assisted medical diagnosis of skin cancer has undergone major advances, through an improvement in the instrument and detection technology, and the development of algorithms to process the information. Moreover, because there has been an increased need to store medical data, for monitoring, comparative and assisted-learning purposes, algorithms for data processing and storage have also become more efficient in handling the increase of data. In addition, the potential use of common mobile devices to register high-resolution images of skin lesions has also fueled the need to create real-time processing algorithms that may provide a likelihood for the development of malignancy. This last possibility allows even non-specialists to monitor and follow-up suspected skin cancer cases. In this review, we present the major steps in the pre-processing, processing and post-processing of skin lesion images, with a particular emphasis on the quantification and classification of pigmented skin lesions. We further review and outline the future challenges for the creation of minimum-feature, automated and real-time algorithms for the detection of skin cancer from images acquired via common mobile devices.

[Dermoscopy in cutaneous melanoma]

BACKGROUND

The mortality of cutaneous melanoma has not declined over the past 50 years. The only interventions that can reduce mortality are primary prevention and early diagnosis, and the dermoscopic evaluation is essential to achieve this. Dermoscopy identifies characteristics of melanoma that would go unnoticed to the naked eye. The aim of this paper is to report the most frequent dermoscopic findings in patients diagnosed with in situ and invasive melanoma.

MATERIAL AND METHODS

An observational and retrospective study of contact dermoscopy was performed using LED DermliteTM and camera DermliteTM dermoscope. The findings evaluated were: asymmetry in two axes, association of colours, lack of pigment, irregular points, atypical network, pseudopods, blue veil, ulceration, and peri-lesional pink ring. These dermoscopic findings were compared with the histological diagnosis.

RESULTS

The study included 65 patients with cutaneous melanoma; 10 in situ, and 55 invasive. The mean Breslow in invasive melanoma was 3 mm. Most patients (35) had localization in extremities. In all patients, the most frequent dermoscopic finding was asymmetry in two axes, followed by association of two or more colours; in melanoma in situ, asymmetry was the most frequent, followed by atypical-irregular points. In invasive melanoma asymmetry in two axes, the association of two or more colours, and pseudopods, were the most frequent findings.

CONCLUSION

Asymmetry in two axes is the most common dermoscopic finding in in situ and invasive melanoma. The presence of two or more colours in a pigmented lesion should be suspected in an invasive melanoma.

Multimodal Imaging Spectroscopy of Tissue

Advanced optical imaging technologies have experienced increased visibility in medical research, as they allow for a label-free and nondestructive investigation of tissue in either an excised state or living organisms. In addition to a multitude of ex vivo studies proving the applicability of these optical imaging approaches, a transfer of various modalities toward in vivo diagnosis is currently in progress as well. Furthermore, combining optical imaging techniques, referred to as multimodal imaging, allows for an improved diagnostic reliability due to the complementary nature of retrieved information. In this review, we provide a summary of ongoing multifold efforts in multimodal tissue imaging and focus in particular on in vivo applications for medical diagnosis. We also discuss the advantages and potential limitations of the imaging methods and outline opportunities for future developments.

Handheld photoacoustic microscopy to detect melanoma depth in vivo

We developed handheld photoacoustic microscopy (PAM) to detect melanoma and determine tumor depth in nude mice in vivo. Compared to our previous PAM system for melanoma imaging, a new light delivery mechanism is introduced to improve light penetration. We show that melanomas with 4.1 and 3.7 mm thicknesses can be successfully detected in phantom and in in vivo experiments, respectively. With its deep melanoma imaging ability and handheld design, this system can be tested for clinical melanoma diagnosis, prognosis, and surgical planning for patients at the bedside.

Light in and sound out: emerging translational strategies for photoacoustic imaging

Photoacoustic imaging (PAI) has the potential for real-time molecular imaging at high resolution and deep inside the tissue, using nonionizing radiation and not necessarily depending on exogenous imaging agents, making this technique very promising for a range of clinical applications. The fact that PAI systems can be made portable and compatible with existing imaging technologies favors clinical translation even more. The breadth of clinical applications in which photoacoustics could play a valuable role include: noninvasive imaging of the breast, sentinel lymph nodes, skin, thyroid, eye, prostate (transrectal), and ovaries (transvaginal); minimally invasive endoscopic imaging of gastrointestinal tract, bladder, and circulating tumor cells (in vivo flow cytometry); and intraoperative imaging for assessment of tumor margins and (lymph node) metastases. In this review, we describe the basics of PAI and its recent advances in biomedical research, followed by a discussion of strategies for clinical translation of the technique.

Detection and Discrimination of Non-Melanoma Skin Cancer by Multimodal Imaging

Non-melanoma skin cancer (NMSC) belongs to the most frequent human neoplasms. Its exposed location facilitates a fast ambulant treatment. However, in the clinical practice far more lesions are removed than necessary, due to the lack of an efficient pre-operational examination procedure: Standard imaging methods often do not provide a sufficient spatial resolution. The demand for an efficient in vivo imaging technique might be met in the near future by non-linear microscopy. As a first step towards this goal, the appearance of NMSC in various microspectroscopic modalities has to be defined and approaches have to be derived to distinguish healthy skin from NMSC using non-linear optical microscopy. Therefore, in this contribution the appearance of ex vivo NMSC in a combination of coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG) and two photon excited fluorescence (TPEF) imaging—referred as multimodal imaging—is described. Analogous to H&E staining, an overview of the distinct appearances and features of basal cell and squamous cell carcinoma in the complementary modalities is derived, and is expected to boost in vivo studies of this promising technological approach.

Progress against cancer (1971-2011): how far have we come?

'The big C', a common euphemism for cancer, has loomed large on the collective psyche of the mankind for centuries, not least because of the relative dearth of effective treatment against this disease but its ability to relentlessly evade them and come back to haunt us. However, the struggle against cancer took a decisive turn in 1971 when a relentless campaigning by health activists eventually led to signing of the National Cancer Act in the United States, an unprecedented event in the history of diseases. As we commemorate the 40th anniversary of the signing of that historic legislation, an assessment of the progress against cancer would naturally help us understand how we have fared so far in this struggle and guide us in our efforts to re-strategize and re-deploy our limited resources to their best use against this immortal enemy.

7-tesla MR imaging of non-melanoma skin cancer samples: correlation with histopathology

PURPOSE

The aims of this study were to compare in vitro magnetic resonance imaging (MRI) characteristics of keratinocytic skin cancer assessed by a 7-tesla (T) MRI with histopathology, and to describe MRI features of skin tumors.

METHODS

This prospective study included 30 skin tumors treated by surgery. MR images of skin samples were acquired on a 7-T MR scanner using a fast spin-echo T(2)-weighted and an isotropic 3D gradient-echo T(1)-weighted sequence. Length, width, Breslow index and margins of the lesions were measured. The presence or absence of the following was noted: healthy margins, ulceration of the dermis, in situ lesions, superficial and deep dermis involvement, subcutaneous involvement, superficial and intratumoral keratin. MR results were compared to histopathology.

RESULTS

Interclass correlation coefficient (ICC) was very good for the evaluation of the width (ICC = 0.86) and Breslow index (ICC = 0.87). The ICC was good for the evaluation of the margins (ICC = 0.70) but for length, ICC was lower (ICC = 0.67). Mean bias between MRI and histopathology was inferior to 1 mm for width, Breslow index and margin.

CONCLUSION

In vitro 7-T MRI of keratinocytic skin cancer allows delineation of lesions with good correlation with histopathology. After in vivo confirmation it could have a diagnostic role regarding the delineation of surgical margins but its actual limitations prevent its practical adoption at this time.