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Evaluation Of Automated Tools To Plan Radiotherapy Treatment Of Breast Cancer Patients Literature Review Examples
Abstract
Radiotherapy is a treatment method that involves the use of a high energy radiation, and mostly used in the treatment of cancer. The method can also be used in the treatment of non-cancerous begin, tumour, thyroid diseases, as well as other blood disorders. In the process of the treatment of breast cancer, there are several automated tools or equipment required for the success of treatment. For instance, computers are used in performing automated medical tasks such as radiology systems, bibliography retrieval, and patient-monitoring in the process of treatment.
Introduction
Radiotherapy is a treatment method that involves the use of a high energy radiation, and mostly used in the treatment of different types of cancers like breast cancer. The method can also be used in the treatment of non-cancerous begin, tumour, thyroid diseases, as well as other blood disorders. The method can be used alone or in a combination with chemotherapy. Yet the treatment of a tumour, it is used before surgery to shrink the tumour for easy removal or after the surgery for adjuvant treatment that removes any trace of the tumour that might have been left in the process of the surgery (Short et al., 124). It can be carried out internally or externally using an accelerator which focuses a high-energy radiation beam to the area to be treated. On the other hand, internal radiotherapy, involves a temporal use of small pieces of radioactive materials near the cancerous cells in the body or a radioactive liquid that can be injected or swallowed. Even though the procedure can cause a mild discomfort, the radiation emitted is normally painless. The size and type and length of radiotherapy adopted are dependent on the size and type of cancer to be treated as well as the location in the body (Short et al., 124). This paper will evaluate the automated tools that are used in the planning or a radiotherapy treatment of breast cancer.
Radiation in the process of breast cancer treatment has been found to one of the major causes of heart risks, in their research found out that the risk of a woman’s heart rises by 7.4 % for every guy of radiation. However, there is still an open complication in the correlation between the heart tissue damages and the radiation dose. Another model of heart damage with better accuracy is required as it can result in a significant improvement in the heart safety of radiotherapy patients. However, the most common radiotherapy effect is temporary damage to the body tissues, but most of them are short-lived. The common side effects include tiredness, hair loss, and sore skin. However, these conditions tend to be better a few weeks or days of the end of the treatment. In rare cases, the payment method can result in long term effects, for instance, the treatment of pelvic region or in the genitals can be a cause of permanent infertility to the individual or victim (Chao et al., 180).
Automated tools involved in the radiotherapy treatment
In the process of the treatment of breast cancer, there are several automated tools or equipment required for the success of treatment. For instance, computers are used in performing automated medical tasks such as radiology systems, bibliography retrieval, and patient-monitoring in the process of treatment. The machines are used for computing or calculating intensive doses of the rays used as well as the image processing for external beam radiation. With the advancement in technology, computers have proven in the 3D radiation plan to make decisions on therapy selection, evaluation, and diagnosis depending on the severity of the breast cancer. After a patient has been diagnosed with breast cancer, the 3D, and Artificial Intelligence-based systems are used for the treatment modality selection, the level of radiation, dosage, reaction cell monitoring, and data generation (Koppel et al., 1200). The automated processes ensure success and precise outcomes.
Planning Target Volume Tool (PTVT) is a rule-based expert system developed by the National Cancer Institute that is used in generating the planning target volumes. It generates a region of tissues to gross breast cancer and tumour volume. In the process, the automated system helps in examining the area of the tissues that are adjacent to the breast tissues affected by cancer and any possible error in positioning of the patient. The tool also monitors the reaction or movement of other organs and tissues during treatment, as well as physiological processes like breathing (Short et al., 124). Through the process clients and professionals can have assured and preise outcomes.
ROENTGEN is also an automated tool used in deciding the treatment plan after the diagnosis. It hence helps in describing target dosage as it retrieves a similar prior case from the case library depending on the level of cancer. It hence helps in identifying a plan that satisfies the condition of the patient in deciding the number of beams as well as the beam energy chosen. However, the tool applies the use of several other tools in the process of correct functionality. For instance, it uses the Retriever tool in finding prior similar cases to the current breast cancer patient that best matches the condition of the patient. It then applies the Adaptor module in modifying the retrieved plan to account for any difference that may occur between the current and provisos patient. The adapter automatically plan-specific features from the Retriever to ensure they are correct for the patient (Short et al., 124).
In their study, Chao et al., 180, further reports that with the potential current plan in place for the patient, a Detector model is used in determining whether the plan and the required dose distribution may result in any fault that may cause harm to the patient. The fault will be indicated by a field that will show either a cold or hot spot. In case any fault occurs, an automated Corrector tool module asks the expert for the relevant medical step to use in correcting and elimination of the error. It passes through the detector once more to ensure any possible error is eliminated. The new plan developed in the current patient is also kept using a Storer model along with the plan-specific features. All these automated tools are designed in a simplified system as a unit working tool for the diagnosis and treatment plan for breast cancer and also tumour patients.
After the treatment plan above, RADEK automated expert tool is used to evaluate the plan if it is clinically compatible with the condition of the patient. It hence determines whether the plan can be adopted or rejected. The system calculates the dose distribution, the volume of cold or/and hot spots, and compare the integral and peak dosage in the various breast tissues. Based on the evaluation plan, it prunes the plan to ensure it is the most relevant to the patient (Chen et al. , 5).
CARTES automated tool is then used to adopt a treatment decision, designing of treatment protocols, and the analysis of the results. It works in stages where the first stage uses relevant information and data about the medical and social history of the patient, clinical symptoms and signs, various test results, and intention of the therapy. CARTES also determine when the patient has some symptoms of other related complications that may require immediate attention. At the third stage, it examines the treatment results. At this stage, RADONCOL model is used to recommending the appropriate treatment, while CAVCAV performs the treatment planning on the breast cancer patient (Koppel et al., 1197).
Theories involved
In the process of treatment of breast cancer patients, several theories have evolved into the use of radiotherapy. For instance, Social Cognitive and Planned Behaviour Theory have been identified as the most commonly applied models breast cancer patients. The theories are vital in the examination and understanding of the behaviour of the patient in the process of surgery and recovery. The two models are proving to be vital in the meta-analyses on improving tailored-print health and behavioural changes, intervention, and psychological response to the process of recovery (Short et al., 124).
Decision theory is known to be a branch of operation research that provides an explicit methodology of handling preferences and uncertainty in optional decision making as per the objectives of the decision maker. Making the right choice has significance in ensuring efficiency and success of the outcomes. Clinical decision analysis has been used in the medical field for three decades in decision making during radiotherapy surgery. Here, a simple decision tree is used in choosing between radiotherapy and surgery using squares it represents choices, rectangles representing the outcome of the patient, and circles that represent uncertainty events. For cancer patients, representative applications are like choosing between testing and treatment, no treatment and treatment, and the therapy sequence (Chao et al., 180). Professional knowledge and appropriate skills are handy in ensuring sustained outcomes.
The theory works together with Markov theory in handling large decision-making trees for patients who have worse cases that need immediate attention. In this case, the two theories are used in handling large decision trees that have time-dependent events and scales of uniform outcome measurements. The medical professionals will then be able to determine survival quality-adjusted life after the treatment, cost-effectiveness, as well as cost-benefit analysis to trade off costs versus trade-off expected benefits for the cancer patient (Short et al., 124).
Conclusion
Generally, the tools used include computers, Planning Target Volume Tool (PTVT) that helps in examining the area of the tissues that are adjacent to the breast tissues affected by cancer and any possible error in positioning of the patient. ROENTGEN is used in deciding the treatment plan after the diagnosis, thus evaluates the plan if it is clinically compatible with the condition of the patient. CARTES are then used to adopt a treatment decision, designing of treatment protocols, and the analysis of the results. At this stage, RADONCOL model is used to recommending the appropriate treatment, while CAVCAV performs the treatment planning on the breast cancer patient. Several manual and automated tools and models have been effective in improving the treatment or health outcomes for patients suffering from breast cancer. However, with the development in technology, automated tools and models have proven to be more effective and sufficient in the process of cancer treatment. By the help of the above automated tools, it has been easier to manage and treat breast cancer and other related diseases like tumour.
Works cited
Short, Camille E., Erica L. James, and Ronald C. Plotnikoff. “Theory-and evidence-based development and process evaluation of the Move More for Life program: a tailored-print intervention designed to promote physical activity among post-treatment breast cancer survivors.” Int J Behav Nutr Phys Act 10.1 (2013): 124 Print.
Chao, KS Clifford, et al. “Intensity-modulated radiation therapy reduces late salivary toxicity without compromising tumor control in patients with oropharyngeal carcinoma: a comparison with conventional techniques.”Radiotherapy and oncology 61.3 (2001): 275-280 Print.
Chen, Ting, et al. “Tagged MRI based cardiac motion modeling and toxicity evaluation in breast cancer radiotherapy.” Frontiers in oncology 5 (2015) Print.
Koppel, Ross, et al. “Role of computerized physician order entry systems in facilitating medication errors.” Jama 293.10 (2005): 1197-1203 Print.
