Basal cell carcinoma has provided science with an important example of how effective the application of molecular biology can be in the treatment of cancers. Basal cell carcinoma has been treated primarily through surgical intervention, such as excision and Mohs micrographic surgery, or radiation therapy. As discussed, the discovery of its linkage to the abnormal activity has led to the development of targeted drugs known as Hedgehog inhibitors. These Hedgehog inhibitors have been used not only to treat BCC, but to treat other types of cancers that are known to be associated with the Hedgehog pathway, such as medulloblastoma, and to support the treatment of other cancers, such as pancreatic cancer (Ngueyn & Cho, 2022). These treatments can be used to help patients who may not be ideal canidates for surgical procedures. The main limitations of these inhibitors, including tumor resistance, and side effects, such as muscle cramps, hair loss, and fatigue still apply (Stratigos et al., 2021).
There are concerns to be had over the access and equity of Basal cell carcinoma treatments. Specialized procedures such as Mohs surgery and advanced drug therapies are often only available at at larger medical facilities, and can also be highly expensive. Because of this, patients who live in more rural areas or are socioeconomically disadvatanged may have difficulty accessing these treatments (Bossi et al., 2023).
An exciting development of Basal cell carcinoma research is the use of artificial intelligence to detect skin cancer. Artificial intelligence has shown great potential in the detection of BCC as a support system for its diagnosis (Widaatalla et al., 2023). Challenges of this development being used in daily practice include privacy concerns from sharing potentially identifying patient images, and potentially biased AI models due to the lack of skin-tone diversities suffering from the illness. Further research is required to bring this tool to optimal widespread usage.
Open challenges involving usage of AI in Skin Cancer Diagnosis
Artificial Intelligence (AI) may help support basal cell carcinoma diagnosis, but challenges like dataset bias, patient privacy, image quality, lesion variation, and ethical concerns should be addressed before clinical use.
Source: Melarkode, N., Srinivasan, K., Qaisar, S. M., & Plawiak, P. (2023). AI-Powered Diagnosis of Skin Cancer: A Contemporary Review, Open Challenges and Future Research Directions. Cancers, 15(4), 1183. https://doi.org/10.3390/cancers15041183.