According to the Mayo Clinic, more than half of all people with cancer receive radiation therapy as part of their cancer treatment. Although radiotherapy has become a more increasingly common aspect of the cancer treatment process, there are still potential challenges that oncology professionals face in the radiotherapy treatment process. Two primary areas of concern are healthcare worker’s overall time availability and accuracy of contours in the radiotherapy process.
What are common challenges in the radiotherapy process?
Taipei Veterans General Hospital defines clinical target volume delineation (TVD) as, “all potential areas at risk for microscopic tumor involvement either by direct extension or nodal spread.” A literature review published in 2017 by the Frontiers in Oncology journal focused on reviewing literature related to TVD variability and its impact on dosimetry and clinical outcomes. The review found that, “TVD variability is a significant problem in radiotherapy both within and outside clinical trials.” The accuracy of contouring directly affects the TVD variability, and therefore is of concern to oncology departments.
Additionally, the radiotherapy process can be time consuming for both the patient and the oncology department as a whole. Not only can the contouring process be rather cumbersome: the patient waiting time can be slow-moving as well. According to Cancer Research UK, patients may have to wait up to 2 months (62 days) to receive proper cancer treatment.
MVision AI always seeks to further understand and address radiotherapy-related needs and concerns of healthcare professionals. In order to do so, MVision AI conducted a poll, via various social media platforms, asking the question: if you could change one thing about your clinic’s radiotherapy process, what would it be? Respondents were given the opportunity to provide their own, original response, or to select an answer from the following options: the time spent on contouring; the accuracy of the contouring; the waiting time for patients; or more time to help patients.
The MVision AI team really appreciated all of the responses from medical professionals around the globe. We received a total of 116, well thought, responses. The results of the poll indicated that:
- 41% of respondents wanted to change: the accuracy of contouring
- 28% wanted to change the waiting time for patients
- 18% wanted to change the time spent on contouring
- 10% wanted more time to help patients
- 3% provided their own responses
The minority of respondents provided their own, original responses (3%), including: more time to focus on the follow-up and side effects, and to reduce the spent on the quality assurance of the Linear Accelerator, or LINAC (the device commonly used for external beam radiation treatments for patients with cancer).
MVision AI assists medical professionals with overcoming challenges in the radiotherapy treatment process.
MVision AI’s GDPR and guideline compliant, automatic segmentation and contouring software uses breakthrough deep learning technology to power its artificial intelligence (AI) algorithms. MVision assists oncology departments worldwide in improving contour accuracy. The MVision team is aware of current challenges surrounding inter-observer variation in manual contouring. We replace variation with high consistency. This helps to limit adverse effects related to errors in delineation of structures.
MVision also helps save healthcare professionals time and helps to reduce patient waiting times. Mvision’s fully automated 3D organ models that are delivered within minutes, as opposed to hours of manual work. This helps medical professionals focus on more complex delineation tasks; stop wasting limited resources; reduce patient waiting times; have more time to focus on the follow-up and side effects; and gives oncologists more time to spend with their patients.
MVision is happy to be at your service
You are more than welcome to contact us:
c/o Terkko Health Hub, Haartmaninkatu 4, 00290 Helsinki, Finland.
Tel: +358 (0) 40 5489 229
For media inquiries
Tel: +358 40 500 7915
“Cancer Waiting Times.” Cancer Waiting Times | Cancer Information | Cancer Research UK, 6 Jan. 2020, www.cancerresearchuk.org/about-cancer/cancer-in-general/treatment/access-to-treatment/waiting-times-after-diagnosis.
Chang, Amy Tien Yee, et al. “Challenges for Quality Assurance of Target Volume Delineation in Clinical Trials.” Frontiers in Oncology, Frontiers Media S.A., 25 Sept. 2017, www.ncbi.nlm.nih.gov/pmc/articles/PMC5622143/.