Comparative Analysis of Skin Cancer (Benign vs. Malignant) Detection Using Convolutional Neural Networks

We live in a world where people are suffering from many diseases. Cancer is the most threatening of them all. Among all the variants of cancer, skin cancer is spreading rapidly. It happens because of the abnormal growth of skin cells. The increase in ultraviolet radiation on the Earth’s surface is also helping skin cancer spread in every corner of the world. Benign and malignant types are the most common skin cancers people suffer from. People go through expensive and time-consuming treatments to cure skin cancer but yet fail to lower the mortality rate. To reduce the mortality rate, early detection of skin cancer in its incipient phase is helpful. In today’s world, deep learning is being used to detect diseases. The convolutional neural network (CNN) helps to find skin cancer through image classification more accurately. This research contains information about many CNN models and a comparison of their working processes for finding the best results. Pretrained models like VGG16, Support Vector Machine (SVM), ResNet50, and self-built models (sequential) are used to analyze the process of CNN models. These models work differently as there are variations in their layer numbers. Depending on their layers and work processes, some models work better than others. An image dataset of benign and malignant data has been taken from Kaggle. In this dataset, there are 6594 images of benign and malignant skin cancer. Using different approaches, we have gained accurate results for VGG16 (93.18%), SVM (83.48%), ResNet50 (84.39%), Sequential_Model_1 (74.24%), Sequential_Model_2 (77.00%), and Sequential_Model_3 (84.09%). This research compares these outcomes based on the model’s work process. Our comparison includes model layer numbers, working process, and precision. The VGG16 model has given us the highest accuracy of 93.18%.

The lymphatic system and sentinel lymph nodes: conduit for cancer metastasis

The lymphatic system is a complicated system consisting of the lymphatic vessels and lymph nodes draining the extracellular fluid containing cellular debris, excess water and toxins to the circulatory system. The lymph nodes serve as a filter, thus, when the lymph fluid returns to the heart, it is completely sterile. In addition, the lymphatic system includes the mucosa-associated lymphoid tissue, such as tonsils, adenoids, Peyers patches in the small bowel and even the appendix. Taking advantage of the drainage system of the lymphatics, cancer cells enter the lymphatic vessels and then the lymph nodes. In general, the lymph nodes may serve as a gateway in the majority of cases in early cancer. Occasionally, the cancer cells may enter the blood vessels. This review article emphasizes the structural integrity of the lymphatic system through which cancer cells may spread. Using melanoma and breast cancer sentinel lymph node model systems, the spread of early cancer through the lymphatic system is progressive in a majority of cases. The lymphatic systems of the internal organs are much more complicated and difficult to study. Knowledge from melanoma and breast cancer spread to the sentinel lymph node may establish the basic principles of cancer metastasis. The goal of this review article is to emphasize the complexity of the lymphatic system. To date, the molecular mechanisms of cancer spread from the cancer microenvironment to the sentinel lymph node and distant sites are still poorly understood and their elucidation should take major priority in cancer metastasis research.

The larynx

The larynx, trachea and bronchi develop embryologically from the foregut in the form of an outpouching during the fourth week of gestation. The larynx bridges the gap from the base of the tongue above, to the trachea below lying within the hypopharynx. It sits in the neck spanning the distance from the third to sixth cervical vertebrae. It is a complex respiratory organ composed of a cartilage framework, ligaments, intrinsic and extrinsic muscles and is lined by an epithelial mucous membrane continuous above with the pharynx and below with the trachea. Its primary function is protection of the lower respiratory tract against aspiration. It allows the generation of a high intrathoracic pressure required for coughing, straining and lifting (Valsalva manoeuvre) and phonation. The anatomy of the larynx can either be considered by its surgical division of the supraglottis, glottis and subglottis (these landmarks are important in the consideration of cancer spread).

Effects of Enhancement on Deep Learning Based Hepatic Vessel Segmentation

Colorectal cancer (CRC) is the third most common type of cancer with the liver being the most common site for cancer spread. A precise understanding of patient liver anatomy and pathology, as well as surgical planning based on that, plays a critical role in the treatment process. In some cases, surgeons request a 3D reconstruction, which requires a thorough analysis of the available images to be converted into 3D models of relevant objects through a segmentation process. Liver vessel segmentation is challenging due to the large variations in size and directions of the vessel structures as well as difficult contrasting conditions. In recent years, deep learning-based methods had been outperforming the conventional image analysis methods in the field of medical imaging. Though Convolutional Neural Networks (CNN) have been proved to be efficient for the task of medical image segmentation, the way of handling the image data and the preprocessing techniques play an important role in segmentation. Our work focuses on the combination of different vesselness enhancement filters and preprocessing methods to enhance the hepatic vessels prior to segmentation. In the first experiment, the effect of enhancement using individual vesselness filters was studied. In the second experiment, the effect of gamma correction on vesselness filters was studied. Lastly, the effect of fused vesselness filters over individual filters was studied. The methods were evaluated on clinical CT data. The quantitative analysis of the results in terms of different evaluation metrics from experiments can be summed up as (i) each of the filtered methods shows an improvement as compared to unenhanced with the best mean DICE score of 0.800 in comparison to 0.740 for unenhanced; (ii) applied gamma correction provides a statistically significant improvement in the performance of each filter with improvement in mean DICE of around 2%; (iii) both the fused filtered images and fused segmentation give the best results (mean DICE score of 0.818 and 0.830, respectively) with the statistically significant improvement compared to the individual filters with and without Gamma correction. The results have further been verified by qualitative analysis and hence show the importance of our proposed fused filter and segmentation approaches.

Molecular response to induction chemotherapy and its correlation with treatment outcome in head and neck cancer patients by means of NMR-based metabolomics

Background The aim of this prospective study is to identify the biomarkers associated with the effects of induction chemotherapy (iCHT) in terms of the favorable/weaker response to the treatment in locally advanced head and neck squamous cells carcinomas (LA-HNSCC). Methods The studied group consisted of 53 LA-HNSCC patients treated with iCHT. The treatment tolerance was measured by the Common Terminology Criteria for Adverse Events (CTCAE). The response to the treatment was evaluated by the clinical, fiberoptic and radiological examinations made before and after iCHT (the TNM Classification of Malignant Tumors was used for classifying the extent of cancer spread). Proton nuclear magnetic resonance (1H NMR) serum spectra of the samples collected before and after iCHT were acquired with a 400 MHz spectrometer and analyzed using the multivariate and univariate statistical methods. Results The molecular response to iCHT involves an increase of the serum lipids which is accompanied by the simultaneous decrease of alanine, glucose and N-acetyl-glycoprotein (NAG). Furthermore, in males, the iCHT induced changes in the lipid signals and NAG significantly correlate with the regression of the primary tumor. The OPLS-DA multivariate model identified two subgroups of the patients with a weaker metabolic and clinical response. The first one consisted of the patients with a significantly lower initial nodal stage, the second one showed no differences in the initial clinical and metabolic statuses. Conclusions The NMR-based metabolomic study of the serum spectra revealed that iCHT induces the marked changes in the LA-HNSCC patients’ metabolic profiles and makes it possible to stratify the patients according to their response to iCHT. These effects are sex dependent. Further studies on a larger scale accounting for sex and the clinical and metabolic factors are warranted.

A level-set approach for a multi-scale cancer invasion model

The quest for a deeper understanding of the cancer growth and spread process focuses on the naturally multiscale nature of cancer invasion, which requires an appropriate multiscale modeling and analysis approach. The cross-talk between the dynamics of the cancer cell population on the tissue scale (macroscale) and the proteolytic molecular processes along the tumor border on the cell scale (microscale) plays a particularly important role within the invasion processes, leading to dramatic changes in tumor morphology and influencing the overall pattern of cancer spread. Building on the multiscale moving boundary framework proposed in Trucu et al. (Multiscale Model. Simul 11(1): 309-335), in this work we propose a new formulation of this process involving a novel derivation of the macro scale boundary movement law based on micro-dynamics, involving a transport equation combined with the level-set method. This is explored numerically in a novel finite element macro-micro framework based on cut-cells.

Evolved Resistance to Placental Invasion Secondarily Confers Increased Survival in Melanoma Patients

Mammals exhibit large differences in rates of cancer malignancy, even though the tumor formation rates may be similar. In placental mammals, rates of malignancy correlate with the extent of placental invasion. Our Evolved Levels of Invasibility (ELI) framework links these two phenomena identifying genes that potentially confer resistance in stromal fibroblasts to limit invasion, from trophoblasts in the endometrium, and from disseminating melanoma in the skin. Herein, using patient data from The Cancer Genome Atlas (TCGA), we report that these anti-invasive genes may be crucial in melanoma progression in human patients, and that their loss is correlated with increased cancer spread and lowered survival. Our results suggest that, surprisingly, these anti-invasive genes, which have lower expression in humans compared to species with non-invasive placentation, may potentially prevent stromal invasion, while a further reduction in their levels increases the malignancy and lethality of melanoma. Our work links evolution, comparative biology, and cancer progression across tissues, indicating new avenues for using evolutionary medicine to prognosticate and treat human cancers.

Ultrasound of the Uterosacral Ligament, Parametrium, and Paracervix: Disagreement in Terminology between Imaging Anatomy and Modern Gynecologic Surgery

Ultrasound is an effective tool to detect and characterize lesions of the uterosacral ligament, parametrium, and paracervix. They may be the site of diseases such as endometriosis and the later stages of cervical cancer. Endometriosis and advanced stages of cervical cancer may infiltrate the parametrium and may also involve the ureter, resulting in a more complex surgery. New functional, surgical anatomy requires the complete diagnostic description of retroperitoneal spaces and tissues that contain vessels and nerves. Most endometriosis lesions and cervical cancer spread involve the cervical section of the uterosacral ligament, which is close to tissues, namely the parametrium and paracervix, which contain vessels and important nerves and nerve anastomoses of the inferior hypogastric plexus. Efferent fibers of the plexus travel to the rectum, uterus, rectovaginal ligament, deep vesicouterine ligament, and bladder. These efferent fibers are essential for bladder and rectal functionality so tailored nerve-sparing surgery became a standard approach for treating deep infiltrating endometriosis and cervical cancer. An accurate diagnosis by ultrasound has significant clinical impact and is important for appropriate treatment. In this article, we try to establish a common terminology between imaging diagnostic and modern surgical anatomy.