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Case study: automating the quantification of PD-L1 in lung cancer

Liesbeth Hondelink, MSc student at Leiden University Medical Centre, describes using AI to automate the quantification of PD-L1 in lung cancer studies.
Written by Aiforia
“When I first started, I did not know anything about AI,” describes Liesbeth Hondelink, MSc student at Leiden University Medical Centre in the Netherlands, when she applied to the aiForward program.

Her research focuses on PD-L1, a protein that has gained much popularity in a field that has been under the spotlight for some time now: cancer immunotherapy. Liesbeth and her lab are specifically assessing the programmed death-ligand 1, which is what PD-L1 stands for, in non-small cell lung cancer (NSCLC).

Prescribing the correct immunotherapy

“Immunotherapy has very beneficial effects, particularly in lung cancer,” explains Liesbeth. The percentage of tumor cells positive for PD-L1 in NSCLC has significant consequences on the choice of this expensive treatment since it predicts its effectiveness. Therefore, the proportion of the protein must be calculated to aid clinicians in prescribing the correct course of treatment.

This is calculated by specialized pathologists, an arduous task prone to inter- and intra-observer variability, as Liesbeth describes: “Pulmonary pathologists are finding it difficult to score PD-L1 on lung biopsies and disagree in 15-20% of all cases. This has been extensively assessed in the literature.”


AI helps provide guidance

“Aiforia seemed like the most approachable, easy-to-use solution,” Liesbeth explains why she applied to aiForward. Using Aiforia® Create, Liesbeth has already trained her own deep learning AI model to calculate PD-L1 in a speedy and consistent manner. “We annotated everything, about 60 slides, in just a few weeks, and it was actually quite easy. Easier than I expected it to be, and I expected it to take much longer,” she describes the training process.

PD-L1 detecting AI model
Annotation Assistant really saves you a lot of time. It also brings up the more difficult areas that I myself would not have realized to annotate. It really made the algorithm better,” she adds, having used Aiforia’s new active learning tool to speed up her AI model creation.

Analysis underway

Training is done, and now, with the PD-L1 detecting AI model in her hands, Liesbeth has already started the analysis with the support of the pulmonary pathologists in validating the results. 

“Aiforia's AI really does something that we could not do otherwise, and the results are looking good.”

Expecting to finish her aiForward project soon, this researcher transformed from not knowing anything about AI to creating her own deep learning AI model in just a few weeks.

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