53 Salma Dammak Computer Vision News The second challenge involves assessing the success of stereotactic ablative radiotherapy (SABR). SABR is a highly effective and well-tolerated treatment, but it induces benign inflammation and scarring around the tumour, mirroring tumour growth in post-treatment scans. Distinguishing these benign changes from true cancer recurrence is critical, as the latter requires immediate and potentially risky interventions. With current tools, this takes over a year, but this thesis presents a model that can discern the two at the earliest sign of potential growth. The model can do this by analyzing the appearance of lesions on routine follow-up scans, detecting patterns of recurrence before they become visible to the human eye. These studies highlight the potential of artificial-intelligence-based models to address critical clinical challenges in lung cancer care, particularly in the context of novel treatments like immunotherapy and SABR. Two of Salma’s thesis papers can be found here and here. Two patients who received SABR, one with cancer recurrence and one with benign changes. Note that for both cases, the lesion appears to grow progressively after treatment, and that further intervention would be used after the third follow up CT scan (yellow box) due to this progressive growth. This may be too late for the patient with cancer recurrence, and would be unnecessary for the patient with benign changes.
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