ChimeraNet: U-Net for Hair Detection in Dermoscopic Skin Lesion Images.

Hair and ruler mark structures in dermoscopic images are an obstacle preventing accurate image segmentation and detection of critical network features. Recognition and removal of hairs from images can be challenging, especially for hairs that are thin, overlapping, faded, or of similar color as skin or overlaid on a textured lesion. This paper proposes a novel deep learning (DL) technique to detect hair and ruler marks in skin lesion images. Our proposed ChimeraNet is an encoder-decoder architecture that employs pretrained EfficientNet in the encoder and squeeze-and-excitation residual (SERes) structures in the decoder. We applied this approach at multiple image sizes and evaluated it using the publicly available HAM10000 (ISIC2018 Task 3) skin lesion dataset. Our test results show that the largest image size (448 × 448) gave the highest accuracy of 98.23 and Jaccard index of 0.65 on the HAM10000 (ISIC 2018 Task 3) skin lesion dataset, exhibiting better performance than for two well-known deep learning approaches, U-Net and ResUNet-a. We found the Dice loss function to give the best results for all measures. Further evaluated on 25 additional test images, the technique yields state-of-the-art accuracy compared to 8 previously reported classical techniques. We conclude that the proposed ChimeraNet architecture may enable improved detection of fine image structures. Further application of DL techniques to detect dermoscopy structures is warranted.

Part II: Missouri's Fentanyl Poisonings Rise to Record Levels.

Missouri's dramatic rise in fentanyl-related overdoses was reported in Part I of this two-part series. In Part II, we report that previous efforts to combat the surge in illicit fentanyl supply from China failed, as Chinese factories shifted production to basic fentanyl precursor chemicals, known as dual-use pre-precursors. Mexican drug cartels now synthesize fentanyl from these basic chemicals and have overpowered the Mexican government. All efforts to reduce the fentanyl supply appear to be failing. Missouri has implemented harm reduction methods: training first responders and educating people who use drugs in safer practices. Harm reduction agencies are distributing naloxone at unprecedented levels. The "One Pill Can Kill" campaign begun by the Drug Enforcement Agency (DEA) in 2021 and foundations created by bereaved parents aim to educate young people on the extraordinary danger of counterfeit pills. In 2022, Missouri is at a crossroads, with record numbers of fatalities from illicit fentanyl and new levels of effort by harm reduction agencies to combat the soaring rate of deaths from this powerful narcotic.

Part I: Missouri's Fentanyl Poisonings Rise to Record Levels.

Missourians are dying of fentanyl poisoning at an unprecedented rate. We identified growth areas in Missouri for fatal fentanyl encounters in rural and western counties. Though the deaths occur for a multitude of reasons, a growing trend adds to the surge in fentanyl fatalities: poisonings from counterfeit pills. The tablets are often labeled with brand names for alprazolam or oxycodone, but may contain only fentanyl at a dangerous level. Teenagers find counterfeit pills all too easily via social media. Believing they have found an easy way to obtain a quick high or relief of minor pain and anxiety, they take the pill alone in their bedroom, with no possibility of reversing a fatal fentanyl dose. There is a wide range of respiratory depression from illicit drugs containing fentanyl. We reviewed the physiologic respiratory response to drugs containing fentanyl that varies with genetics and the unpredictable amount of fentanyl contained in illicit drugs.

Missouri's Fentanyl Problem: The China Connection.

Recently, Missouri has followed an overall upward trend in opioid overdose deaths. In 2018, Missouri was the state with the largest absolute and percentage increase in opioid-related overdose fatality rates per capita over the previous year (18.3% and 3.1/100,000). This increase occurred despite an overall decrease in U.S. opioid-related death rates in the same period. This report identifies illicitly manufactured fentanyl (IMF) (and analogues) as the drug most responsible for this rise in opioid deaths in Missouri, with stimulant overdoses (primarily from methamphetamine) in second place. Within Missouri, we find the areas where opioid deaths are highest: St. Louis and the city's fringe areas, following the national trend for high rates in fringe areas. Based on reports from CDC Wonder data, county medical examiners, law enforcement agencies, and drug addiction prevention agencies, we conclude that IMF and related synthetic opioids arriving from China are primarily responsible for fatal narcotic overdoses in Missouri. Despite the COVID-19 disruption of fentanyl manufacturing and distribution centers in and around Wuhan, China early in the pandemic, preliminary 2020 data from medical examiners' offices show an upswing in opioid deaths, an indicator that Chinese fentanyl producers have restored the supply chain.

Automatic lesion border selection in dermoscopy images using morphology and color features.

PURPOSE: We present a classifier for automatically selecting a lesion border for dermoscopy skin lesion images, to aid in computer-aided diagnosis of melanoma. Variation in photographic technique of dermoscopy images makes segmentation of skin lesions a difficult problem. No single algorithm provides an acceptable lesion border to allow further processing of skin lesions. METHODS: We present a random forests border classifier model to select a lesion border from 12 segmentation algorithm borders, graded on a "good-enough" border basis. Morphology and color features inside and outside the automatic border are used to build the model. RESULTS: For a random forests classifier applied to an 802-lesion test set, the model predicts a satisfactory border in 96.38% of cases, in comparison to the best single border algorithm, which detects a satisfactory border in 85.91% of cases. CONCLUSION: The performance of the classifier-based automatic skin lesion finder is found to be better than any single algorithm used in this research.

The 5 P's of Pyoderma Gangrenosum

The diagnosis of pyoderma gangrenosum (PG) is often difficult to establish based on a clinical presentation, which can mimic other dermatologic conditions. The formation of a mnemonic that incorporates the most prevalent clinical features of PG could aid in accuracy and speed of diagnosis. The 5 P's of PG: Painful, Progressive, Purple, Pretibial, Pathergy, and systemic associations, incorporate parameters recognizable on the first encounter with a patient with PG without reliance on histopathology and laboratory findings or treatment response. We postulate that this simple mnemonic will have the most utility with non-dermatology clinicians encountering a lesion suspicious for PG. By assisting in differential diagnosis formation, this mnemonic may lead to timelier biopsies and treatment initiation. The limitations of this approach mirror those of other studies and include lower sensitivities in patients with an atypical PG presentation. In conclusion, the 5 P's of PG offer a useful mnemonic for the diagnosis of PG, particularly in the initial clinical diagnosis prior to skin biopsy and treatment. J Drugs Dermatol. 2019;18(12):1282-1283.

CELLULITIS: A mnemonic to increase accuracy of cellulitis diagnosis.

Cellulitis, a bacterial infection of the skin and subcutaneous tissue, is often misdiagnosed. Cellulitis accounts for a large number of all infectious disease-related hospitalizations in the U.S. Cellulitis can be challenging to diagnose since it lacks pathognomonic findings. We reviewed all articles on cellulitis within the last 20 years that included a statistical analysis, with odds ratios (OR), of specific clinical features of cellulitis. We then constructed a mnemonic encompassing the features with the highest odds ratios. Our mnemonic is CELLULITIS for cellulitis history, edema, local warmth, lymphangitis, unilateral, leukocytosis, injury, tender, instant onset, and systemic signs. The first characteristic has the highest OR and may be the easiest to recall: past episode(s) of cellulitis.

Marijuana Use in the Era of Changing Cannabis Laws: What Are the Risks? Who is Most at Risk?

We review recent findings on medical aspects of marijuana use in order to identify those who are at greatest risk of marijuana-related medical problems. We analyze the impact of medical marijuana laws on health, in particular the disproportionate effects on adolescents and children. Chronic marijuana use predominantly affects certain areas of the brain that overlap the default mode network, linked hubs in the brain that play a supervisory role in critical thought processes such as attention, memory, and social interactions. Disruption of the default mode network areas has been documented in schizophrenia and Alzheimer's disease, illnesses with symptoms and brain changes that parallel findings in marijuana abusers. These findings counter the claim that marijuana is a harmless drug and are a cause for alarm in persons with cannabis dependence.

Unna boot central gauze technique for chronic venous leg ulcers.

BACKGROUND: Venous leg ulcers generally take manyweeks to heal. Novel therapies that shorten healingtime and require less complex care are needed. PURPOSE: The purpose of this report is to presenta pilot study for a new method that can result ina faster healing time for venous leg ulcers usinginexpensive materials. METHODS: A central-gauzeprotocol was developed as described here. A three-ply gauze sponge was placed in the center of theulcer, allowing a peripheral 3-5 mm rim of ulcer toremain exposed. Saline solution was applied to thegauze sponge. A 3-layer Unna boot was applied overthe ulcer with short-stretch compression. This noveltechnique exposed only a peripheral rim of the ulcerto the zinc oxide paste, allowing the central portionof the ulcer to drain through the saline-soaked gauze.The ulcer was photographed at each clinic visit andthe wound area was estimated by finding the bestfitellipse for the ulcer area and computing the areaof the ellipse by a standard formula. RESULTS: Threepatients with small venous leg ulcers treated with thezinc rim technique showed an average healing rate of46.1% per week (range 27.8% - 50.7%). All ulcers werenearly healed by three weeks. After the ulcer size wasreduced sufficiently, patients were discharged withinstructions to apply pieces of Unna dressing to theulcer, under a conventional self-adhesive bandage,maintaining compression, without any saline-gauzein the center. CONCLUSIONS: The three patients in thispilot study showed rapid healing for venous leg ulcerswith the central gauze modification of Unna boottherapy.

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.

Boys at Risk: Fatal Accidental Fentanyl Ingestions in Children: Analysis of Cases Reported to the FDA 2004-2013.

We analyze 25 accidental childhood fentanyl exposures reported to FDA, 2004-2013. These exposures had a case-fatality rate = 48%; male:female ratio = 7.3; 76% were within the 2-4 age range. The ability of fentanyl to kill children so quickly is explained by fentanyl's ability to suppress respiration-as quantified by the antinociceptive potency per milligram, fentanyl far and away leads all narcotics. FDA recommends for fentanyl disposal: flush all forms of fentanyl down the toilet.

Clues from hands/Part 2. Personal details about patients revealed by hand examination.

This is the second part of a two-part article on personal details revealed by hand examination. Examining hands to determine daily activities was the focus of Part 1 in the July/August 2014 Missouri Medicine. Personal traits and preferences, including pets, nutrition and psychology are presented here. These articles serve as a guide for visual clues on the hands to discern a patient's daily activities and personal preference, thereby providing social information that may help establish rapport between patient and physician and may have medical significance.

Clues from hands Part 1: personal details about patients revealed by hand examination.

This is the first part of a two-part article on personal details revealed by the hand examination. Daily activities revealed by hand examination are the focus of Part 1, while personal details including nutrition and psychological assessment are presented in Part 2. These clues enable the examiner to discern hobbies, vocation, sporting activities, dietary information, and psychosocial information of the patient. We describe signs that may aid the clinician in determining these activities, enabling us to provide better patient care by establishing good patient rapport. Part 1, presented here, focuses on detection of visible traces on the hands of sporting activities, hobbies, and vocation. The patient through long familiarity may be oblivious to these features or may find them too insignificant to mention, yet they can provide meaningful social details for the

Obtundation and Myocardial Infarction in a Case of Systemic Loxoscelism.

We report an atypical course of a likely brown recluse spider bite in a 79-year-old male. The Rader scale and Loxosceles reclusa venom detection by ELISA provide supporting evidence for a loxoscelism diagnosis. Obtundation and myocardial infarction occurred following a drop in hemoglobin to 6.5g/dL. The rapid loss of blood volume was considered a significant etiologic factor for both the obtundation and myocardial infarction. The neurological symptoms reversed rapidly after packed red blood cell transfusion.

Basal Cell Carcinoma Diagnosis with Fusion of Deep Learning and Telangiectasia Features.

In recent years, deep learning (DL) has been used extensively and successfully to diagnose different cancers in dermoscopic images. However, most approaches lack clinical inputs supported by dermatologists that could aid in higher accuracy and explainability. To dermatologists, the presence of telangiectasia, or narrow blood vessels that typically appear serpiginous or arborizing, is a critical indicator of basal cell carcinoma (BCC). Exploiting the feature information present in telangiectasia through a combination of DL-based techniques could create a pathway for both, improving DL results as well as aiding dermatologists in BCC diagnosis. This study demonstrates a novel "fusion" technique for BCC vs non-BCC classification using ensemble learning on a combination of (a) handcrafted features from semantically segmented telangiectasia (U-Net-based) and (b) deep learning features generated from whole lesion images (EfficientNet-B5-based). This fusion method achieves a binary classification accuracy of 97.2%, with a 1.3% improvement over the corresponding DL-only model, on a holdout test set of 395 images. An increase of 3.7% in sensitivity, 1.5% in specificity, and 1.5% in precision along with an AUC of 0.99 was also achieved. Metric improvements were demonstrated in three stages: (1) the addition of handcrafted telangiectasia features to deep learning features, (2) including areas near telangiectasia (surround areas), (3) discarding the noisy lower-importance features through feature importance. Another novel approach to feature finding with weak annotations through the examination of the surrounding areas of telangiectasia is offered in this study. The experimental results show state-of-the-art accuracy and precision in the diagnosis of BCC, compared to three benchmark techniques. Further exploration of deep learning techniques for individual dermoscopy feature detection is warranted.

Hybrid Topological Data Analysis and Deep Learning for Basal Cell Carcinoma Diagnosis.

A critical clinical indicator for basal cell carcinoma (BCC) is the presence of telangiectasia (narrow, arborizing blood vessels) within the skin lesions. Many skin cancer imaging processes today exploit deep learning (DL) models for diagnosis, segmentation of features, and feature analysis. To extend automated diagnosis, recent computational intelligence research has also explored the field of Topological Data Analysis (TDA), a branch of mathematics that uses topology to extract meaningful information from highly complex data. This study combines TDA and DL with ensemble learning to create a hybrid TDA-DL BCC diagnostic model. Persistence homology (a TDA technique) is implemented to extract topological features from automatically segmented telangiectasia as well as skin lesions, and DL features are generated by fine-tuning a pre-trained EfficientNet-B5 model. The final hybrid TDA-DL model achieves state-of-the-art accuracy of 97.4% and an AUC of 0.995 on a holdout test of 395 skin lesions for BCC diagnosis. This study demonstrates that telangiectasia features improve BCC diagnosis, and TDA techniques hold the potential to improve DL performance.

Region growing by sector analysis for detection of blue-gray ovoids in basal cell carcinoma.

Blue-gray ovoids (B-GOs) are critical dermoscopic structures in basal cell carcinomas (BCCs) that pose a challenge for automatic detection. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could help further accomplish the goal of automatic BCC detection. This study introduces an efficient sector-based method for segmenting B-GOs. Four modifications of conventional region-growing techniques are presented: (i) employing a seed area rather than a seed point, (ii) utilizing fixed control limits determined from the seed area to eliminate re-calculations of previously-added regions, (iii) determining region growing criteria using logistic regression, and (iv) area analysis and expansion by sectors. Contact dermoscopy images of 68 confirmed BCCs having B-GOs were obtained. A total of 24 color features were analyzed for all B-GO seed areas. Logistic regression analysis determined blue chromaticity, followed by red variance, were the best features for discriminating B-GO edges from surrounding areas. Segmentation of malignant structures obtained an average Pratt's figure of merit of 0.397. The techniques presented here provide a non-recursive, sector-based, region-growing method applicable to any colored structure appearing in digital images. Further research using these techniques could lead to automatic detection of B-GOs in BCCs.