New Google AI can detect lung cancer in CT scans

Henrietta Brewer
May 22, 2019

"Radiologists typically look through hundreds of 2D images within a single CT scan and cancer can be miniscule and hard to spot".

Google LLC has built an artificial intelligence model that can analyze CT scans of people's chests to determine if they might have lung cancer.

Prior LDCT scans are useful because they can reveal an abnormal growth rate of lung nodules, thus indicating malignancy.

The computer was trained using fully de-identified, biopsy-confirmed low-dose chest CT scans.

When an earlier scan was available, the AI and the radiologists performed equally well in detecting cancers, but in the second study, the AI outperformed the human doctors with fewer false positives and fewer false negatives.

The CNN cancer risk prediction model utilizes outputs from the previous two models and can also incorporate regions from a patient's prior LDCT studies into its analysis, according to the researchers. The model and the radiologists achieved almost identical results when they were given access to multiple scans of a patient's chest.

Rebecca Campbell, from Cancer Research UK, said: "It's encouraging to see new technological innovations that could one day help us to detect lung cancer early".

In the former scenario, the deep learning algorithm - which was trained on computed tomography scans of people with lung cancer, without it, and with nodules turned cancerous, the New York Times reported - had a higher identification rate than six radiologists, and in the latter, the humans and machine were even.

Etemadi leads a research team while also working in anesthesiology residency training at Northwestern as part of a unique residency research track. "The concept is novel but the actual engineering of it is also novel because of the scale", he said. Based on this, the model provides an overall malignancy prediction, which can help in increasing the survival rate because medical treatment can be more successful when the cancer is caught early.

The artificial intelligence (AI) researchers at Google have created an AI model that is capable of identifying lung cancer with screening tests.

Etemadi pointed out that the system can categorize a lesion with more specificity.

The AI was able to retroactively diagnose the presence or absence of lung cancer with 94 percent accuracy in 6,716 National Lung Cancer Screening Trial cases with known diagnoses, and with similar accuracy in 1,139 more cases from a clinical validation set. These cases were pulled from the Northwestern Electronic Data Warehouse along with other Northwestern Medicine data sources.

The authors caution that these findings need to be clinically validated in large patient populations, but they say this model may assist in improving the management and outcome of patients with lung cancer.

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