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- Edition 3 - AI in Healthcare: Adaptive Therapy, Reimbursement, and Predictive Tools
Edition 3 - AI in Healthcare: Adaptive Therapy, Reimbursement, and Predictive Tools
Discover Elekta's new adaptive therapy technology, the push for AI reimbursement, and predictive tools for breast cancer.
Evo launched by Elekta
Patients call for AI reimbursement in Radiology
AI autoplanning
AI tool predicts which DCIS cases become invasive
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Specialty: Radiotherapy // Sub-Specialty: Equipment // Body Site: All
1. Evo launched by Elekta:
Elekta launches the Evo, which, while it has similar characteristics to its current top-of-range Linac VersaHD, has the capability to perform online adaptive therapy based on the CBCT.
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Paul’s Thoughts:
This is a big step forward for Elekta, which had been seen to be falling behind Varian given the fast uptake of Halcyon and Ethos systems in the western world. Elekta's approach is somewhat different, allowing the end user to decide whether a patient needs to undergo adaptive treatment on any given day. With specifications identical to the VersaHD, it offers flexibility to clinical teams to move patients between an adaptive and non-adaptive routine when required.
Timescale: Acute | 0 Years
Specialty: Radiology // Sub-Specialty: AI // Body Site: All
2. Patients call for AI reimbursement in Radiology:
Patient groups call for reimbursement to cover AI in radiology. In a letter to representatives and senators, 15 patient advocacy organisation have noted that in radiology, AI is being used to help read and interpret images and help make more informed diagnoses, but reimbursement in the US is limited to less than 10 AI applications currently compared to the 600+ AI-enabled medical dveices cleared by the FDA.
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Paul’s Thoughts:
Such patient advocacy could be critical for the future of AI-enabled technologies, as often it is stated that patients are concerned about AI and its autonomy. What this letter demonstrates is that patients, as well as the clinicians and researchers, are recognising the benefits of AI for their diagnosis and treatment.
Timescale: Early | 2 Years
Specialty: Radiotherapy // Sub-Specialty: AI // Body Site: All
3. AI autoplanning:
Lead researcher Dr Mathieu Gaudreault reports on the use of autoplanning in radiotherapy, that allows plans to be created in a matter of hours instead of days. Based on hundreds of real treatment plans that have been delivered in the past, the AI model "trains and learns from these treatment plans and comes up with the best possible plan for the patient.
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Paul’s Thoughts:
As AI autocontouring becomes almost ubiquitous with radiotherapy clinics worldwide, the next wave will see automated treatment planning, as shown here. It has been implemented in only a few clinics to date, but the expectation is that with increased awareness of the power of AI will come an increased willingness to accept other processes to be conducted by AI. Treatment planning is the next logical step after autocontouring. As well as faster plans, the standard of plans should increase because of the standardisation.
Timescale: Early | 2 Years
Specialty: Radiology // Sub-Specialty: Prognosis // Body Site: Breast
4. AI tool predicts which DCIS cases become invasive:
Using randomised data from the UK/ANZ DCIS trial, researchers showed that a high density of TILs is associated with a 3-fold higher risk of progression to invasive breast cancer. Tumours with a high density of TILs were also found to be more susceptible to radiotherapy.
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Paul’s Thoughts:
This work provides a new way to help distinguish and identify those women with DCIS who would benefit from radiation therapy over and above surgery from women who could be spared overtreatment in the form of radiation therapy. It could also be provided at lower cost to women with DCIS all over the world, thanks to its non-tissue destructive approach, which would allow more informed treatment decision making.
Timescale: Early | 3 Years
A round-up of some of the best posts we found online this week.
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