Clinical usefulness of high-frequency ultrasonography in the monitoring of basal cell carcinoma treatment effects

Seeing beyond skin deep: High-resolution ultrasound in dermatology-A comprehensive review and future prospects

High-resolution ultrasound (HRUS), operating at frequencies of 20-25 MHz, is a non-invasive imaging tool that offers dermatologists the ability to visualize structures beneath the skin surface. The objective of this review is to present a comprehensive overview of HRUS applications, emphasising its utility in diagnosing, characterising and managing various dermatological conditions. We undertook a comprehensive literature review on the dermatological application of HRUS across Medline, Embase and Cochrane Library databases, while also incorporating our own clinical experience of over 16 years with the tool. In normal skin, the epidermis and dermis are hyperechoic, and the subcutaneous layer is hypoechoic. Basal cell carcinomas appear hypoechoic with irregular margins, while the presence of hyperechoic inclusion bodies suggests aggressive pathology. Squamous cell carcinomas pose challenges due to acoustic shadow artefacts from the thickened stratum corneum. Melanomas are homogenous hypoechoic lesions, with HRUS used to accurately predict Breslow thickness. HRUS provides dermatologists with a valuable adjunct to traditional clinical examination. Future advancement in image resolution and the standardisation of diagnostic parameters may further expand its utility.

Rationale for Using High-Frequency Ultrasound as a Routine Examination in Skin Cancer Surgery: A Practical Approach

Ultrasound and high-frequency ultrasound assessment of melanoma and non-melanoma skin cancer in the pre-therapeutical setting is becoming increasingly popular in the field of dermatosurgery and dermatooncology, as it can provide clinicians with relevant, "in vivo" parameters regarding tumor lateral and depth extension as well as potential locoregional spread, cancelling the need of more extensive imaging methods and avoiding a delay in diagnosis. Furthermore, preoperative sonography and color Doppler can aid in orienting the clinical diagnosis, being able in numerous situations to differentiate between benign and malignant lesions, which require a different therapeutic approach. This preoperative knowledge is of paramount importance for planning an individualized treatment regimen. Using sonography at the time of diagnosis, important surgical complications, such as neurovascular damage, can be avoided by performing a preoperative neurovascular mapping. Furthermore, sonography can help reduce the number of surgical steps by identifying the lesions' extent prior to surgery, but it can also spare unnecessary surgical interventions in cases of locally advanced lesions, which infiltrate the bone or already present with locoregional metastases, which usually require modern radiooncological therapies in accordance to European guidelines. With this review, we intend to summarize the current indications of sonography in the field of skin cancer surgery, which can help us improve the therapeutic attitude toward our patients and enhance patient counseling. In the era of modern systemic radiooncological therapies, sonography can help better select patients who qualify for surgical procedures or require systemic treatments due to tumoral extension.

Polarimetric imaging combining optical parameters for classification of mice non-melanoma skin cancer tissue using machine learning

Polarimetric imaging systems combining machine learning is emerging as a promising tool for the support of diagnosis and intervention decision-making processes in cancer detection/staging. A present study proposes a novel method based on Mueller matrix imaging combining optical parameters and machine learning models for classifying the progression of skin cancer based on the identification of three different types of mice skin tissues: healthy, papilloma, and squamous cell carcinoma. Three different machine learning algorithms (K-Nearest Neighbors, Decision Tree, and Support Vector Machine (SVM)) are used to construct a classification model using a dataset consisting of Mueller matrix images and optical properties extracted from the tissue samples. The experimental results show that the SVM model is robust to discriminate among three classes in the training stage and achieves an accuracy of 94 % on the testing dataset. Overall, it is provided that polarimetric imaging systems and machine learning algorithms can dynamically combine for the reliable diagnosis of skin cancer.

Morphology, Histopathology, and Anatomical Distribution of Sporadic Colorectal Polyps in Chinese Patients

Background and Aims

There are limited data regarding the morphology, histopathology, and anatomical distribution of sporadic colorectal polyps in Chinese patients. We evaluated these characteristics of sporadic polyps to guide the endoscopic detection and excision of colorectal polyps.

Methods

This was a retrospective single-center observational study involving 7381 patients with sporadic colorectal polyps. All polyps were removed endoscopically. The morphology and histopathology of polyps were evaluated according to the Paris classification and the World Health Organization classification, respectively.

Results

A total of 22,174 polyps removed endoscopically from 7322 patients were included. In the sigmoid colon, 24.70% of colorectal polyps occurred, followed by the transverse colon (18.58%) in frequency. 0-Is type polyps accounted for 60.60% of all sporadic colorectal polyps. Polyps with 0-Ip, 0-Isp, and 0-IIa types were frequently found in the sigmoid colon, but laterally spreading lesions usually occurred in the ascending colon (24.61%) and rectum (20.51%). Irrespective of the Paris classification and anatomical location, as the polyps enlarge, the proportion of adenomatous polyps gradually increases while the proportion of serrated lesions decreases. Polyps with size ≥1 cm located in the left-sided colon were more likely to have villous/tubulovillous or high-grade dysplasia histology than those located in the right-sided colon, and about 1% of them were demonstrated with adenocarcinoma.

Conclusion

Sigmoid colon should be detected adequately during colonoscopy, and polyps with size ≥1 cm should be treated carefully, especially in the left-sided colon.

Key Points to Select a Device for Dermatologic Ultrasound

What points to consider when selecting a device for practicing dermatologic ultrasound is an excellent question. After we met the requisites published in the guidelines for practicing dermatologic ultrasound, it is necessary to consider the main objective of the use because it is not the same to be focused mostly on the avoidance of the puncture of important facial vessels such as the case of injectors of cosmetic fillers in comparison to the use of operators that need to deal with the diagnosis and monitoring of a wide range of dermatologic pathologies. Currently, a broad variety of ultrasound devices meets the minimum requirements for practicing these examinations in the market. Thus, small, portable, and high-end devices may present advantages and limitations that must be balanced according to the primary purposes and the budget. Moreover, the shape and footprint of the probes can make difficult or facilitate a dermatologic procedure. Other points to consider are the type of storage and the need for technical service. In summary, there are key points that we need to consider when we select a dermatologic ultrasound device in dermatology or aesthetics.

Performance of Ultrasound for Identifying Morphological Characteristics and Thickness of Cutaneous Basal Cell Carcinoma: A Systematic Review

Advances in ultrasound technology and non-surgical treatments of basal cell carcinomas (BCCs) have raised the need to study the performance of high-frequency ultrasound (HFUS) in BCCs. We aimed to assess the performance of HFUS in the evaluation of BCCs to formulate recommendations for its uses and conducted a systematic review of the literature to do so. A search of Central, Medline, Embase, CINHAL, and Web of Science was performed using key/MESH terms "ultrasonography" and "basal cell carcinoma" (January 2005-December 2020). We included primary studies reporting biopsy-confirmed BCCs for which the target intervention was ultrasound assessment at 15 MHz or higher frequency. Thirty articles were included, studying a total of 1,203 biopsy-confirmed BCCs. HFUS provides accurate depth measurements, especially for BCCs >1 mm. The definition of lateral margins in vivo needs further studies; however, ex vivo margin assessment seems convincing. There is a diagnostic role for HFUS in identifying higher recurrence risk BCC subtypes, which can help in risk stratification. Performance of HFUS is significant in BCC management. Pre-surgical scans may support case selection for Mohs. HFUS can improve safety when used to plan brachytherapy treatments, help with case selection and adjunct treatment choice pre-photodynamic therapy. Finally, HFUS can help follow lesions after intervention, particularly non-surgical management, and support the decision to observe or re-intervene. HFUS can enhance clinical practice by providing useful information that cannot be deducted from the clinical examination. It would be recommended to evaluate the extent, mainly depth, and detect the aggressiveness of the BCCs.

Characterization of Mueller matrix elements for classifying human skin cancer utilizing random forest algorithm

SIGNIFICANCE

The Mueller matrix decomposition method is widely used for the analysis of biological samples. However, its presumed sequential appearance of the basic optical effects (e.g., dichroism, retardance, and depolarization) limits its accuracy and application.

AIM

An approach is proposed for detecting and classifying human melanoma and non-melanoma skin cancer lesions based on the characteristics of the Mueller matrix elements and a random forest (RF) algorithm.

APPROACH

In the proposal technique, 669 data points corresponding to the 16 elements of the Mueller matrices obtained from 32 tissue samples with squamous cell carcinoma (SCC), basal cell carcinoma (BCC), melanoma, and normal features are input into an RF classifier as predictors.

RESULTS

The results show that the proposed model yields an average precision of 93%. Furthermore, the classification results show that for biological tissues, the circular polarization properties (i.e., elements m44, m34, m24, and m14 of the Mueller matrix) dominate the linear polarization properties (i.e., elements m13, m31, m22, and m41 of the Mueller matrix) in determining the classification outcome of the trained classifier.

CONCLUSIONS

Overall, our study provides a simple, accurate, and cost-effective solution for developing a technique for classification and diagnosis of human skin cancer.