Detecting lung cancer early, while surgery is still an option.

Surgical interventions, like VATS (video-assisted thoracoscopic surgery), significantly improve lung cancer survival rates, but depend on its early detection and diagnosis. 

The earlier a malignant nodule is discovered, the better the options for curative treatment. Finding cancer earlier broadens the range of possible surgical procedures, reducing reliance on thoracotomy and enabling minimally invasive approaches like VATS.  When open procedures are still required, smaller, early-stage nodules may be managed by less invasive procedures like wedge resections or segmentectomy rather than lobectomy or pneumonectomy. The increased surgical options increase the chance of a successful surgery, with reduced post-surgery mortality rates, lower complications rates and improved survival rates for patients. (1) 

What are the challenges of early detection and diagnosis? 

Lung cancer is often asymptomatic. Therefore, it is often reliant on incidental findings or lung screening programs to get an early diagnosis. Of these, 90% of lung nodules are found incidentally [2], so appropriate management of these patients is paramount. Unfortunately, despite incidental findings being widely identified and reported, the workup rates are low, with around 60% of patients being lost to timely follow-ups [3], representing a significant missed opportunity for early diagnosis. 

Lung screening programs also face significant challenges and can’t be relied upon either. In the US, according to recent data, only 16% of those at high risk for lung cancer and eligible are screened, with some states having uptake figures as low as 8.6% [4]. The combination of poor incidental follow-ups and low lung screening uptake means that too many lung cancers are found in the late stages. 

One way to overcome these challenges is to give providers access to technology that both reduces the number of incidentally identified patients lost to follow-up and also enables optimized clinical decisions to support earlier diagnosis and appropriate intervention in patients with suspicious nodules. 

How can AI-enabled technology help? 

“Lung cancer has been the number one cause of cancer deaths in the US for both men and women since 1986, but now we have the tools to discover the cancer earlier, an early diagnosis saves lives. Incidental lung nodules are often the first sign of cancer, and if we don’t act quickly, we miss our window of opportunity for a cure” says Daniel L Miller MD , Chief, Thoracic Surgery, at the Medical College of Georgia at Augusta University , Georgia. “AI tools, like Virtual Nodule Clinic, are improving how we identify and track at-risk patients for lung cancer, making sure our patients get into the correct care pathways for diagnosis and treatment without delay. The sooner we identify a malignancy, the better our chances of offering minimally invasive procedures that reduce risks and improve patient outcomes.” 

We are addressing the challenges of incidental lung nodule management by leveraging technology to enhance detection, streamline follow-up workflows, and support physicians in making optimal clinical decisions. 

Our AI-enabled platform, Virtual Nodule Clinic (VNC), ensures that incidental lung nodules identified in radiology reports are flagged to the appropriate team to be followed up in a timely manner, driving earlier diagnosis and intervention. VNC integrates into clinical workflows, helping providers enroll patients in lung nodule clinics as soon as possible, significantly reducing delays in care and increasing the chances of curative treatment. 

Additionally, VNC supports clinicians' decision-making, with the integration of a clinically validated computer vision AI Lung cancer prediction score (LCP) within our platform. The impact of these features combined is clear: 

• More accurate clinical decisions: Studies show that AI-assisted decision-making improved 22% of cases, leading to more timely interventions [5]. 

• Faster action on cancers: Recent research found that AI use accelerated intervention in approximately 10 out of every 100 cancers (71.9% vs. 81.4%) [6]. 

For thoracic surgeons, the goal is clear: find lung cancer earlier to improve surgical outcomes. By integrating AI-driven technology into lung nodule management, we are not just identifying cancers sooner—we are giving patients the best possible chance for curative treatment. 

References: 

1. Morgan H, Baldwin D, Hubbard R, et al. Ninety-day mortality following lung cancer surgery: outcomes from the English national clinical outcomes audit. Thorax. 2022;77:724-726.
2. Gould MK, Tang T, Liu IL, et al. Recent trends in the identification of incidental pulmonary nodules. Am J Respir Crit Care Med. 2015;192(10):1208-1214. Optellum projections based on this data.
3. Pyenson BS, Bazell CM, Bellanich MJ, Caplen MA, Zulueta JJ. No apparent workup for most new indeterminate pulmonary nodules in US commercially insured patients. J Health Econ Outcomes Res. 2019;6(3):118-129. 
4. American Lung Association. State of Lung Cancer: Key Findings. https://www.lung.org/research/state-of-lung-cancer/key-findings
5. Kim RY, Oke JL, Pickup LC, et al. Artificial intelligence tool for assessment of indeterminate pulmonary nodules detected with CT. Radiology. 2022;304(3):683-691. 
6. Kim RY, Oke JL, Dotson TL, et al. Effect of an artificial intelligence tool on management decisions for indeterminate pulmonary nodules. Respirology. 2023;28(6):582-584.