Comparison of standard mammography with digital mammography and digital infrared thermal imaging for breast cancer screening

Detection of canine obstructive nasal disease using infrared thermography: A pilot study

Infrared thermography detects variations in heat signature and is utilized in other species to non-invasively identify respiratory disease. This study aimed to determine if infrared thermography could be used to detect nasal disease in dogs. Eight dogs presenting for nasal disease (ND group) and ten healthy control dogs (C group) were enrolled. Dorsal and rostral images of the nose were acquired using a Fluke TiX580 60Hz thermal imaging camera. Images were analyzed using the accompanying software. Regions of interest were defined over the right and left nasal passages to determine the maximum (max), average (avg), and minimum (min) temperatures. Temperatures were compared between ND and C groups, and correlation to disease state (ND or C) was evaluated. Temperature differences and imaging patterns were subjectively compared with diagnosis based on computed tomography (CT) and histopathology. The ND group consisted of 5 spayed females and 3 neutered males. Clinical sings included unilateral epistaxis (n = 4); bilateral serous discharge and sneezing (n = 1); bilateral mucopurulent discharge, epistaxis, and sneezing (n = 1); unilateral mucoid discharge, epistaxis and sneezing (n = 1); and sneezing and unilateral epistaxis (n = 1). Temperatures were significantly different between ND and C groups on dorsal (max p = <0.001, avg p = 0.001, min p = <0.001) and rostral (max p = <0.001, avg p = <0.001, min p = 0.005) images. Temperature positively correlated to disease status (ND vs C group) in both dorsal and rostral images. Subjective analysis of images allowed correct identification of abnormal or normal 27/36 times. Obstructive nasal disease results in a local temperature increase in the affected nasal passage that can be non-invasively detected by infrared thermography.

A Survey of Convolutional Neural Network in Breast Cancer

Problems

For people all over the world, cancer is one of the most feared diseases. Cancer is one of the major obstacles to improving life expectancy in countries around the world and one of the biggest causes of death before the age of 70 in 112 countries. Among all kinds of cancers, breast cancer is the most common cancer for women. The data showed that female breast cancer had become one of the most common cancers.

Aims

A large number of clinical trials have proved that if breast cancer is diagnosed at an early stage, it could give patients more treatment options and improve the treatment effect and survival ability. Based on this situation, there are many diagnostic methods for breast cancer, such as computer-aided diagnosis (CAD).

Methods

We complete a comprehensive review of the diagnosis of breast cancer based on the convolutional neural network (CNN) after reviewing a sea of recent papers. Firstly, we introduce several different imaging modalities. The structure of CNN is given in the second part. After that, we introduce some public breast cancer data sets. Then, we divide the diagnosis of breast cancer into three different tasks: 1. classification; 2. detection; 3. segmentation.

Conclusion

Although this diagnosis with CNN has achieved great success, there are still some limitations. (i) There are too few good data sets. A good public breast cancer dataset needs to involve many aspects, such as professional medical knowledge, privacy issues, financial issues, dataset size, and so on. (ii) When the data set is too large, the CNN-based model needs a sea of computation and time to complete the diagnosis. (iii) It is easy to cause overfitting when using small data sets.

Folic Acid Preconditioning Alleviated Radiation-Induced Ovarian Dysfunction in Female Mice

Radiological therapy/examination is the primary source of artificial radiation exposure in humans. While its application has contributed to major advances in disease diagnosis and treatment, ionizing radiation exposure is associated with ovarian damage. The use of natural products, either alone or as an adjunct, has become increasingly common for reducing the side effects of radiological therapy during disease treatment. Herein, we explored the protective effect of folic acid (FA), a widely used B vitamin, against radiation-induced ovarian injury and its mechanism of action. Female mice with normal ovarian function were randomly divided into control, FA, radiation, and radiation + FA groups. The intervention strategy included daily intragastric administration of FA (5 mg/kg) for 3 weeks prior to radiation exposure. Mice in the radiation and radiation + FA groups received a single dose of 5 Gy X-ray irradiation. Changes in the estrous cycle were then recorded, and ovarian tissues were collected. Pathophysiological changes as well as reproductive and endocrine-related indexes were determined via H&E staining, immunohistochemistry, Western blot, and ELISA. The reproductive performance and emotional symptoms of animals were also monitored. Our results indicated that FA intervention effectively alleviated ovarian damage, leading to more regular estrous cycles, lesser impairment of follicular morphology and endocrine status, as well as greater germ cell preservation. Reduced levels of oxidative stress, inflammation, and enhanced DNA repair were associated these changes. FA pre-administration improved the reproductive performance, leading to higher pregnancy rates and greater litter sizes. Further, the anxiety levels of animals were significantly reduced. Our results indicate that FA pre-administration significantly alleviates radiation-induced ovarian damage in rodents, highlighting its potential as a protective strategy against radiation exposure in the female population.

The Current State of Optical Sensors in Medical Wearables

Optical sensors play an increasingly important role in the development of medical diagnostic devices. They can be very widely used to measure the physiology of the human body. Optical methods include PPG, radiation, biochemical, and optical fiber sensors. Optical sensors offer excellent metrological properties, immunity to electromagnetic interference, electrical safety, simple miniaturization, the ability to capture volumes of nanometers, and non-invasive examination. In addition, they are cheap and resistant to water and corrosion. The use of optical sensors can bring better methods of continuous diagnostics in the comfort of the home and the development of telemedicine in the 21st century. This article offers a large overview of optical wearable methods and their modern use with an insight into the future years of technology in this field.

Techniques for Temperature Monitoring of Myocardial Tissue Undergoing Radiofrequency Ablation Treatments: An Overview

Cardiac radiofrequency ablation (RFA) has received substantial attention for the treatment of multiple arrhythmias. In this scenario, there is an ever-growing demand for monitoring the temperature trend inside the tissue as it may allow an accurate control of the treatment effects, with a consequent improvement of the clinical outcomes. There are many methods for monitoring temperature in tissues undergoing RFA, which can be divided into invasive and non-invasive. This paper aims to provide an overview of the currently available techniques for temperature detection in this clinical scenario. Firstly, we describe the heat generation during RFA, then we report the principle of work of the most popular thermometric techniques and their features. Finally, we introduce their main applications in the field of cardiac RFA to explore the applicability in clinical settings of each method.

Monitoring tissue temperature during photothermal therapy for cancer

Phototherapies offer promising alternatives to traditional cancer therapies. Phototherapies mainly rely on manipulation of target tissue through photothermal, photochemical, or photomechanical interactions. Combining phototherapy with immunotherapy has the benefit of eliciting a systemic immune response. Specifically, photothermal therapy (PTT) has been shown to induce apoptosis and necrosis in cancer cells, releasing tumor associated antigenic peptides while sparing healthy host cells, through temperature increase in targeted tissue. However, the tissue temperature must be monitored and controlled to minimize adverse thermal effects on normal tissue and to avoid the destruction of tumor-specific antigens, in order to achieve the desired therapeutic effects of PTT. Techniques for monitoring PTT have evolved from post-treatment quantification methods like enzyme linked immunosorbent assay, western blot analysis, and flow cytometry to modern methods capable of real-time monitoring, such as magnetic resonance thermometry, computed tomography, and photoacoustic imaging. Monitoring methods are largely chosen based on the type of light delivery to the target tissue. Interstitial methods of thermometry, such as thermocouples and fiber-optic sensors, are able to monitor temperature of the local tumor environment. However, these methods can be challenging if the phototherapy itself is interstitially administered. Increasingly, non-invasive therapies call for non-invasive monitoring, which can be achieved through magnetic resonance thermometry, computed tomography, and photoacoustic imaging techniques. The purpose of this review is to introduce the feasible methods used to monitor tissue temperature during PTT. The descriptions of different techniques and the measurement examples can help the researchers and practitioners when using therapeutic PTT.

Photoacoustic Imaging for Management of Breast Cancer: A Literature Review and Future Perspectives

In this review article, a detailed chronological account of the research related to photoacoustic imaging for the management of breast cancer is presented. Performing a detailed analysis of the breast cancer detection related photoacoustic imaging studies undertaken by different research groups, this review attempts to present the clinical evidence in support of using photoacoustic imaging for breast cancer detection. Based on the experimental evidence obtained from the clinical studies conducted so far, the performance of photoacoustic imaging is compared with that of conventional breast imaging modalities. While we find that there is enough experimental evidence to support the use of photoacoustic imaging for breast cancer detection, additional clinical studies are required to be performed to evaluate the diagnostic potential of photoacoustic imaging for identifying different types of breast cancer. To establish the utility of photoacoustic imaging for breast cancer screening, clinical studies with high-risk asymptomatic patients need to be done.

Application and Analysis of Biomedical Imaging Technology in Early Diagnosis of Breast Cancer

Breast cancer is the primary malignant tumor that endangers women's health. The incidence of breast cancer is increasing rapidly in recent years. Accurate disease evaluation before treatment is the key to the selection of treatment options. Biomedical imaging technology plays an irreplaceable role in the diagnosis and staging of tumors. Various imaging methods can provide excellent temporal and spatial resolution from multiple levels and perspectives and have become one of the most commonly used means of breast cancer early detection. With the development of radiomics, it has been found that early imaging diagnosis of breast cancer plays an important guiding role in clinical decision-making. The purpose of this study is to explore the characteristics of various breast cancer imaging technologies, promote the development of individualized accurate diagnosis and treatment of imaging, and improve the clinical application value of radiomics in the early diagnosis of breast cancer.

The influence of size, depth and histologic characteristics of invasive ductal breast carcinoma on thermographic properties of the breast

Invasive breast carcinoma is the most common oncologic disease worldwide. The existing diagnostic methods use morphologic changes in the breast to diagnose a carcinoma when it has reached a certain size. Therefore, it is important to augment the morphologic diagnostic examinations with a new method that focuses on characteristics other than morphology such as electromagnetic changes produced by cancer. 50 adult female patients with confirmed ductal carcinoma following a core biopsy due to a suspicious breast mass were included in the study. They underwent breast thermography using a specially designed infrared camera. The data collected was statistically analyzed to determine how the presence of a tumor and its histologic characteristics influence breast thermographic properties. Twenty eight [56 %] patients in the study had an abnormal thermogram. Following statistical analysis, it was found that temperature of the diseased breast was directly correlated to tumor volume [p=0.009] and negatively correlated to depth of tumor [p=0.042]. Tumors that were ER+ and PR+ tumors produced warmer temperatures [p=0.017 and p=0.038 respectively] than tumors without these receptors. HER2 status and Ki-67 index had no statistical correlation with breast temperature. Tumor size, distance from the skin surface and receptor status cause changes in breast thermographic properties. Despite technical advances in the field of thermography, there are still contradictory results associated with thermography. Its diagnostic abilities are generally poorer than conventional methods and its use in breast cancer screening or as an adjunctive tool for diagnostic purposes is not recommended.

Multi-physics modeling to study the influence of tissue compression and cold stress on enhancing breast tumor detection using microwave radiometry

The influence of tissue compression and external thermal modulation on passive detection of breast tumors using medical microwave radiometry was investigated using multi-physics numerical modeling. A three-dimensional numerical model of the pendant breast with 10 and 6 mm diameter tumors at varying depths (15 mm, 30 mm) was analyzed at thermodynamic equilibrium using a circular waveguide as the receive antenna. The contrast in the brightness temperature, ΔT_B , between the unhealthy and healthy breasts was found to be significantly more for breast compression alone, compared to thermal modulation of the tissue surface, irrespective of tissue composition, tumor size, and depth. The study also concludes that small deep-seated tumor with very low metabolic activity that is not detectable by a radiometer with 0.1 °C sensitivity could be detected under breast compression and short duration cold stress. Thus, detection of deep-seated breast tumors can be significantly improved under controlled tissue compression with an optional cold stress. Bioelectromagnetics. © 2019 Bioelectromagnetics Society.

Breast Cancer Detection in Thermal Infrared Images Using Representation Learning and Texture Analysis Methods

Nowadays, breast cancer is one of the most common cancers diagnosed in women. Mammography is the standard screening imaging technique for the early detection of breast cancer. However, thermal infrared images (thermographies) can be used to reveal lesions in dense breasts. In these images, the temperature of the regions that contain tumors is warmer than the normal tissue. To detect that difference in temperature between normal and cancerous regions, a dynamic thermography procedure uses thermal infrared cameras to generate infrared images at fixed time steps, obtaining a sequence of infrared images. In this paper, we propose a novel method to model the changes on temperatures in normal and abnormal breasts using a representation learning technique called learning-to-rank and texture analysis methods. The proposed method generates a compact representation for the infrared images of each sequence, which is then exploited to differentiate between normal and cancerous cases. Our method produced competitive (AUC = 0.989) results when compared to other studies in the literature.

Best practices for standardized performance testing of infrared thermographs intended for fever screening

Infrared (IR) modalities represent the only currently viable mass fever screening approaches for outbreaks of infectious disease pandemics such as Ebola virus disease and severe acute respiratory syndrome. Non-contact IR thermometers (NCITs) and IR thermographs (IRTs) have been used for fever screening in public areas such as airports. While NCITs remain a more popular choice than IRTs, there has been increasing evidences in the literature that IRTs can provide great accuracy in estimating body temperature if qualified systems are used and appropriate procedures are consistently applied. In this study, we addressed the issue of IRT qualification by implementing and evaluating a battery of test methods for objective, quantitative assessment of IRT performance based on a recent international standard (IEC 80601-2-59). We tested two commercial IRTs to evaluate their stability and drift, image uniformity, minimum resolvable temperature difference, and radiometric temperature laboratory accuracy. Based on these tests, we illustrated how experimental and data processing procedures could affect results, and suggested methods for clarifying and optimizing test methods. Overall, the insights into thermograph standardization and acquisition methods provided by this study may improve the utility of IR thermography and aid in comparing IRT performance, thus improving the potential for producing high quality disease pandemic countermeasures.

Breast Cancer Detection Using Infrared Thermal Imaging and a Deep Learning Model

Women’s breasts are susceptible to developing cancer; this is supported by a recent study from 2016 showing that 2.8 million women worldwide had already been diagnosed with breast cancer that year. The medical care of a patient with breast cancer is costly and, given the cost and value of the preservation of the health of the citizen, the prevention of breast cancer has become a priority in public health. Over the past 20 years several techniques have been proposed for this purpose, such as mammography, which is frequently used for breast cancer diagnosis. However, false positives of mammography can occur in which the patient is diagnosed positive by another technique. Additionally, the potential side effects of using mammography may encourage patients and physicians to look for other diagnostic techniques. Our review of the literature first explored infrared digital imaging, which assumes that a basic thermal comparison between a healthy breast and a breast with cancer always shows an increase in thermal activity in the precancerous tissues and the areas surrounding developing breast cancer. Furthermore, through our research, we realized that a Computer-Aided Diagnostic (CAD) undertaken through infrared image processing could not be achieved without a model such as the well-known hemispheric model. The novel contribution of this paper is the production of a comparative study of several breast cancer detection techniques using powerful computer vision techniques and deep learning models.

Reliability of Infrared Thermography Images in the Analysis of the Plantar Surface Temperature in Diabetes Mellitus

Objective

The purpose of this study was to evaluate the intraexaminer and interexaminer reliability of image assessment of infrared thermography of the plantar surface of people with diabetes mellitus.

Methods

Fifty-one participants with diabetes were included. The interexaminer reliability (test) consisted of measuring the temperature of the plantar surface by 2 evaluators who separately performed the analysis of thermographic images. The intraexaminer reliability (retest) consisted of the revaluation of the images by a single evaluator 10 days after the first analysis.

Results

The analysis of intrareliability and interreliability indicated excellent levels of correlation (intraclass correlation coefficient >0.75, 95% confidence interval >0.70) in the plantar surface points analyzed.

Conclusion

Infrared thermography image evaluation identified intrareliability and interreliability for temperature analysis of the plantar surface of people with diabetes mellitus. However, further studies need to be conducted to assess validity and its application in health care.

Medical applications of infrared thermography: A review

Abnormal body temperature is a natural indicator of illness. Infrared thermography (IRT) is a fast, passive, non-contact and non-invasive alternative to conventional clinical thermometers for monitoring body temperature. Besides, IRT can also map body surface temperature remotely. Last five decades witnessed a steady increase in the utility of thermal imaging cameras to obtain correlations between the thermal physiology and skin temperature. IRT has been successfully used in diagnosis of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has also been used to detect problems associated with gynecology, kidney transplantation, dermatology, heart, neonatal physiology, fever screening and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The present efforts are focused on automatic analysis of temperature distribution of regions of interest and their statistical analysis for detection of abnormalities. This critical review focuses on advances in the area of medical IRT. The basics of IRT, essential theoretical background, the procedures adopted for various measurements and applications of IRT in various medical fields are discussed in this review. Besides background information is provided for beginners for better understanding of the subject.