article · Journal of computational science and data analytics.
Breast cancer is the second most common cancer and cause of cancer deaths among women in Tanzania, where approximately half of diagnosed patients die from the disease. Around 80 percent of cases are identified at advanced stages due to high diagnosis costs and shortages of screening facilities, pathologists, and oncologists. An investigation into breast imaging in the country revealed an absence of routine screening programmes, a high rate of malignancies appearing below the standard screening age of 50, and substantial variability among radiologists interpreting scans. Furthermore, 66 percent of suspected cases in the study sample did not receive pathology confirmation, likely owing to expenses and travel distances. To counter these diagnostic bottlenecks, the findings support adjusting the screening age guidelines, having multiple radiologists review scans, and deploying artificial intelligence computer-aided diagnosis tools to assist local specialists.
In many developing nations, the lack of medical infrastructure and specialists causes breast cancer to be detected too late for effective treatment. Identifying specific barriers, such as diagnostic interpretation inconsistencies and high drop-off rates before pathology confirmation, highlights where health systems need intervention. Pointing to alternative screening thresholds and computational decision support provides clear targets for improving early detection and patient survival.
The research highlights an urgent need for artificial intelligence and computer-aided diagnosis tools to support radiologists in low-resource clinical settings. Healthcare providers and diagnostic centres would be the primary users. Because the study only profiles current systemic challenges and recommends the adoption of these computational tools without evaluating a specific system, commercial application remains at an early concept stage.
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Breast cancer is not only the most commonly occurring cancer among women, but also the most frequent cause of cancer-related deaths in women in developing countries. The mortality rate is marginally higher in developing countries than in developed countries with about 60% of the deaths occurring in developing countries. In Tanzania for exam ple, breast cancer is the second leading cancer in terms of incidence and mortality among women after cervical cancer. Approximately half of all women diagnosed with breast can cer in Tanzania die of the disease. This is due to the limited number of medical facilities for cancer screening and diagnosis, the limited number of oncologists and pathologists, and the diagnosis costs in the country. Due to the mentioned factors, it is approximated that, 80% of breast cancer cases in Tanzania are diagnosed at advanced stages (III or IV), when treatment is less effective and outcomes are poor. By 2030, new breast can cer cases are approximated to increase by 82% in Tanzania. The diagnosis/screening of breast cancer starts with breast imaging with ultrasound and mammograms. Suspected cases are then subjected to pathology for confirmatory tests. Although breast imaging plays a major role in both breast cancer screening and diagnosis, the service is largely not available in many developing countries. Our study found the absence of routine breast cancer screening in Tanzania, resulting in late-stage detection of many cases. This is mainly due to a lack of enough well-trained radiologists to read the images and the costs of the process. This study is aimed at exploring the role, importance and challenges of breast imaging in the screening and diagnosis of breast cancer in Tanzania, a developing country. It is worth noting that, breast imaging is an important step in screening for breast cancer. Our results found that, there is a significant number of malignancies under the recommended age of breast cancer screening of fifty years of age. Our study also found a very high Inter variability among radiologists. This study also discovered in our sample size that 66% of patients did not have their samples taken for confirmation by the pathologists. This might be due to the costs of the process or loss of follow-ups as many patients came far from the diagnosis Centre. Due to the higher intervariability among radiologists, this suggests the necessity of at least two radiologists reading the same case before the conclusion of the diagnosis. Also, due to the significant number of malignancies under the recommended age of 50 years, this study recommends the age to be reconsidered based on different settings. Due to the challenges observed in breast imaging, this study recommends the use of computer-aided diagnosis (CAD) with Artificial Intelligence to assist the limited number of radiologists available.
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DOI: 10.69660/jcsda.02012501
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