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Showing 3 results for Skin Cancer
Haidar Nadrian, Zohreh Rahaee, Seyed Saeed Mazloomy Mahmoodabad, Valee Bahrevar, Zahra Khajeh, Sarisa Najafi, Azar Tol,
Volume 21, Issue 126 (12-2014)
Volume 21, Issue 126 (12-2014)
Abstract
Background: Skin
cancer is the third prevalent cause of mortality and morbidity and the second
widespread cancer based on organ involvement in Yazd province. This study aimed
to assess the effects of educational intervention on promoting skin cancer
preventive behaviors of female students based on of some PRECEDE Model constructs.
Methods: Semi-
experimental interventional study with 75 sample size in each group performing
random sampling from Yazd universities was implemented. Validity and reliability
of researcher made scales were approved. Questionnaires filled by participants
and data were analyzed. Based on problem and weakness of preventive skin cancer
and its predisposing factors adoption analysis was distinguished and
educational intervention planned and performed. Educational strategy was
compromised face to face and group discussion. After three months follow up,
data using descriptive and inferential statistics were analyzed. Significance
level was set less than 0.05.
Results: Before
intervention, predisposing factors was in the moderate level (%56.6) [Knowledge
in moderate (%51.6), attitude relatively good (%66.1)] and preventive behavior
adoption was poor (%48). Knowledge with attitude and practice, also attitude
with practice had direct significant correlation. Knowledge and attitude as
predisposing factor accounted for 25.1% of the variation of skin cancer
preventive behavior changes with the attitude as the strongest predictor.
Dr Shabnam Kia, Prof. Saeed Setayeshi, Prof. Majid Pouladian, Dr Hossein Ardahali,
Volume 27, Issue 7 (10-2020)
Volume 27, Issue 7 (10-2020)
Abstract
Background: Today early detection of common cancer with modern smart calculation is the most interesting issue due to the increased chances of successful treatment. Skin cancer is a serious and dangerous complication that threatens the lives of many people and if not diagnosed in time, it will have bad consequences. It is the fifth most common cancer in the female population and the sixth most common cancer in the male population in the world.
At present, in the discussion of skin diseases, ultrasound is a low-cost and, of course, low-consumption method; during which dermatologists look for unusual symptoms on ultrasound. But ultrasound scans are seemingly complicated, and the early signs of the disease usually seem insignificant or normal; this is the main reason for many misdiagnosis that can be specific to human factors. Skin ultrasound can help diagnose skin cancer early, but it depends directly on the correct interpretation of the ultrasound by a specialist and in many cases can be misleading. Because the consequences of these errors have become costly to humans, there has been a great deal of interest in developing methods for intelligently identifying such abnormalities as a means of assisting dermatologists in accelerating the diagnosis and preventing unnecessary sampling.
The most aim of this study is offering a new procedure by intelligent analyzing skin frequency to diagnose skin cancers with high true negative rates and low false positive rates. In this study, the main goal is the intelligent diagnosis of malignant skin lesions with the help of ultrasound analysis. What distinguishes this study from previous research in this field is the new perspective that this research has on this imaging method and uses it as a tool for processing and analyzing the abundance of skin tissue.
Methods: The theory of biological resonance said that each cell in the whole of human body has a unique resonance due to their bio frequency and this frequency could changes if the cell's texture and status change. In the method of this article, this matter has been used to analyze the structure of skin texture. What can be concluded from this research is that due to the different reactions of two tissues of healthy and unhealthy skin, in the face of ultrasonic stimuli, the frequency response of these two tissues is different from each other; for this reason, the frequency of return waves from those two tissue samples is different.
The most important approach in this study is to try to achieve the ability to use the concept of tissue frequency behavior in the diagnosis of lesions. As explained in this article, the innovative method of this research tries to use the concept of tissue frequency changes due to injury as the main parameter of lesion identification and in fact offers a new way to extract this change in frequency behavior from ultrasound waves.
This means that, in order to offer a new method of early detection of skin tissues malignancy, ultrasonic echoes wave of skin, has been analyzed by various complex frequency calculations using artificial neural networks.
The artificial neural network used in this research is perceptron multilayer pattern recognition. In the design and architecture of this complex network, many parameters are involved that must be carefully studied and analyzed before training to guide the network in the best possible way. The most important of these parameters are the number of hidden layers, the number of nerve cells in each layer and the number of trainings. The important point in this case is the effect of these parameters on different data properties, number of samples, input vector dimension and so on.
The database of this study included 400 ultrasound images of patients in the age range of 18 to 68 years, of which 220 samples in the category of basal cell carcinoma skin cancer, and 180 samples in the category of benign lesions such as Skin moles, fungi and lipodermatic lesions or kerato ulcers were located. A noteworthy point in these data was the presence of definite pathological reports with them, which in turn significantly increases the accuracy of the results.
To set up the network and achieve the optimal result in this research, 60% of the available data was allocated to the training model, 20% to the test model and 20% of the data as data that the network has never encountered.
Results: This study was validated by 400 patients data; the result of this study led to (AUC = 0.986) in order to detect skin malignancy, and has been demonstrated with comparable biological accuracy. With the help of artificial neural networks, it was possible to judge the malignancy or benignity of image lesions with very high accuracy and error rate in the range of 10-2. On the used threshold in this study, the sensitivity and specificity levels reached to 93.7% and 97.8%.
Conclusion: This study could propose an accurate, non-invasive method to early diagnosing of skin cancers via a real-time procedure. Finally, in comparison with the diagnostic method presented in this article, with the common diagnostic and therapeutic methods in conventional medicine, the benefits and advantages of this method are briefly classified in the following few lines:
i. No need for sporadic referrals and spending less time and money
ii. Non-invasive method and less side effects and more patient safety
iii. Early diagnosis of the disease in the early stages of malignant lesion formation
iv. Ease of procedure and no discomfort and pain for the patient
v. Possibility of expanding the application of this method in other medical departments
vi. The high accuracy and high speed of diagnosis with the help of this method is undeniable and in diseases such as cancer, which play a key role in achieving the first step in achieving treatment, the use of the proposed method can be very effective.
Mohammad Ali Eftekhari, Yahya Eftekhari,
Volume 31, Issue 1 (3-2024)
Volume 31, Issue 1 (3-2024)
Abstract
Background & Aims: High-Resolution Optical Coherence Tomography (HD-OCT) is an advanced, non-invasive, in vivo imaging technique that offers cellular resolution images of skin lesions, particularly those with melanocytic characteristics. This study aimed to evaluate the ability of HD-OCT in identifying architectural patterns and cytological features of melanocytic lesions, with a focus on early detection of skin cancer. HD-OCT presents a unique opportunity for enhancing diagnostic accuracy and may serve as a complementary tool in the early diagnosis of skin cancers such as melanoma, especially in cases where clinical examination and dermoscopy are not conclusive.
Methods: This prospective study involved the examination of 26 melanocytic lesions from 26 patients. Each lesion was assessed clinically, using dermoscopy by a trained observer, followed by imaging with HD-OCT. The HD-OCT images were captured in both cross-sectional and en-face modes to ensure comprehensive imaging coverage. The obtained images were then compared with histopathological findings obtained from biopsy specimens of the lesions. The primary aim was to evaluate the HD-OCT’s capacity to identify and differentiate specific features such as cellular architecture, pigmentation patterns, and dermal involvement, which could assist in distinguishing benign from malignant melanocytic lesions. The comparison between the imaging modalities was made to assess the diagnostic performance of HD-OCT relative to the gold standard of histopathology.
Results: The results indicated that HD-OCT was able to detect distinct architectural patterns in both the cross-sectional and en-face modes of imaging. Notably, the technology could provide clear visualization of the cellular features of pigmented cells within various skin layers, including the epidermis and dermis. The technique demonstrated adequate resolution and suitable depth of penetration, allowing for the acquisition of detailed three-dimensional structural data of the melanocytic lesions. However, the lateral resolution of HD-OCT was found to be slightly inferior when compared to confocal reflectance microscopy (RCM), which remains the gold standard for non-invasive skin imaging with cellular resolution. Despite this, HD-OCT was still able to detect significant cytological features that could potentially differentiate benign from malignant lesions. It was noted, however, that while HD-OCT showed promise in identifying malignant melanoma, it was not definitive enough to exclude melanoma as a diagnosis solely based on imaging. This indicates that while the technology can provide valuable insights, it cannot replace histopathology or serve as a standalone diagnostic tool. HD-OCT represents a significant advancement in non-invasive imaging for the early detection of melanocytic skin lesions. The technique’s ability to provide high-resolution, in vivo images of skin lesions at the cellular level allows for the detection of subtle architectural and cytological features that may not be visible through conventional clinical examination or dermoscopy. The ability to capture cross-sectional and en-face images is an added advantage, as it allows for a more comprehensive evaluation of the lesion's depth, structure, and pigmentation, which is essential for differentiating malignant melanoma from benign melanocytic lesions. However, while HD-OCT shows significant potential, it also has limitations. The lateral resolution, while adequate, is still inferior to that of confocal microscopy, which may affect its diagnostic accuracy in certain cases. Additionally, the technology’s diagnostic potential in terms of melanoma detection remains limited. Although HD-OCT can detect patterns suggestive of malignancy, its sensitivity and specificity for ruling out melanoma are not yet sufficient to rely on it exclusively for diagnosis. As such, further refinement of the technology is needed to enhance its diagnostic accuracy. This study demonstrates that HD-OCT can be used as a complementary tool alongside traditional methods such as dermoscopy for the diagnosis of melanocytic lesions. The ability of HD-OCT to visualize cellular and architectural features of skin lesions could be particularly useful in cases where dermoscopy alone is inconclusive, thus potentially reducing the need for unnecessary biopsies. By providing detailed three-dimensional images, HD-OCT can also aid clinicians in monitoring the progression of lesions over time, especially in high-risk patients with a history of skin cancer. However, it is crucial to note that while HD-OCT holds promise, it should not be used as a replacement for histopathological examination, which remains the gold standard for diagnosing melanoma and other skin cancers. HD-OCT should be viewed as a complementary diagnostic tool, enhancing clinical decision-making but not replacing the need for biopsy and histopathological confirmation.
Conclusion: Overall, High-Resolution Optical Coherence Tomography (HD-OCT) presents a significant advancement in the field of non-invasive imaging of melanocytic skin lesions. It provides clinicians with the ability to visualize cellular architecture and cytological features in a non-invasive manner, offering valuable insights into the nature of skin lesions. While HD-OCT is not yet definitive enough to replace histopathology, it holds substantial promise as a complementary tool in the early diagnosis and management of skin cancers, especially melanoma. Further research and development are required to enhance the sensitivity and specificity of HD-OCT and to establish standardized imaging protocols for its clinical use. With these improvements, HD-OCT could become an invaluable tool in dermatology, assisting clinicians in providing better outcomes for patients with melanocytic lesions.
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