Content sponsored by Siemens Healthineers
Lung cancer is the deadliest type of cancer worldwide. It has the highest mortality rate and one of the worst five-year survival rates of all cancers at 17 percent for men and 22 percent for women.1 Because the lungs have no pain receptors, lung cancer usually remains symptom-free for a long time. Patients often only come to the clinic when cancer cells have attacked the lymph nodes or have metastasized. By the time they complain of symptoms like difficulty breathing, the disease is usually far advanced. In stages III or IV, curative therapy is nearly impossible, and the five-year survival rate drops to just five percent.2One way to reduce lung cancer mortality is to diagnose the disease when it’s clinically silent. There’s strong evidence that with low-dose computed tomography (LDCT) scans, lung cancer can be detected at stage I, where curative surgical treatment is feasible.
Survival improves when lung cancer is detected early
To put it concisely: The earlier the disease can be diagnosed, the better the prognosis for the patient. But screening programs are far from standard in the EU. Sebastian Schmidt knows the reasons: “One of the big concerns is healthcare costs. But there have been many analyses showing that screening costs are significantly lower than what we pay today for late-stage treatments. Another reason is that there have been issues in the past with false positives, which is a commonly mentioned reason for not implementing national screening programs. But there are now guidelines and strategies for solving the problem of false positives. For example, in the UK pilots there are only two percent false positives. You’ll achieve a very, very low rate of false positives if you do it properly.”
DID YOU KNOW?
IN THE COUNTRIES OF THE EU, LUNG CANCER RESULTS IN 240,000 DEATHS ANNUALLY.3
➡︎ Have you seen the discussion “What can the radiology community do to drive lung screening in Europe?” at ECR 2023 in Vienna?
Photon-counting: Drastic improvements in lung screening
Computed tomography is the imaging method of choice to assist physicians in diagnosing lung cancer.4 However, the diagnostic benefits of lung cancer screening need to be balanced with the inherent risks of ionizing radiation. Screening basically consists of performing a LDCT, which takes five seconds and is painless. But NAEOTOM Alpha, the world’s first photon-counting CT (PCCT) provides up to a 45 percent lower radiation dose compared with conventional CT detectors.5 With higher spatial and contrast resolution of soft tissue and reduced artifacts, PCCT improved the ability to depict pulmonary emphysema and lung nodule borders.6
“A question of political decision-making”
Multiple studies conducted worldwide have consistently demonstrated the benefits of LDCT lung screening.7 To give just one example: England has had screening on a regional level since 2018 and is seeing success with almost three-quarters of the patients in the screening programs diagnosed in stage I or II. Croatia and Poland are also beginning implementation, and pilot projects are underway in countries like Slovakia, Hungary, and Germany. But there are still no nationwide lung cancer screening programs in EU countries.
It was a very important signal for many countries that the European Council updated its cancer screening recommendation. Whereas the previous cancer screening recommendation from 2003 was limited to breast, cervical and colorectal cancer, member states agreed to broaden the focus. Countries should now explore the feasibility and effectiveness of lung screening with use of low-dose CT.8 “Everything is ready to start,” says Sebastian Schmidt. “The infrastructure is there, the technology is there, and there are training programs for doctors. Now it’s all a question of political decision-making.”
How artificial intelligence supports radiology professionals
But what if the number of examinations increases, but there continues to be a shortage of radiology professionals? AI could then play a critical role by providing a second opinion in diagnostic assessment, because it can help produce faster and more precise results. The AI-Rad Companion Chest CT9 highlights abnormalities and helps radiologists interpret CT images of the thorax. And AI in conjunction with medical imaging can do much more: A special sequence from Siemens Healthineers calculates patient movements and triggers the acquisition of CT images at the exact moment when conditions are right for the optimal image quality. That helps reduce image artifacts that occur when the patient breathes during an examination. France is preparing to start a pilot study funded by the Ministry of Health and the National Cancer Institute to evaluate the role of AI in screening. The study will assess the potential of using AI as a second reader of the results. If it shows that the negative predictive value of AI is very high, it would be a good way to simplify screening.10
Content sponsored by Siemens Healthineers
https://www.siemens-healthineers.com/
REFERENCES
1 https://www.krebsdaten.de/Krebs/EN/Content/Cancer_ sites/Lung_cancer/lung_cancer_node.html (June 2023)
2 https://www.lung.org/lung-health-diseases/lung-disease-lookup/lung-cancer/resource-library/lung-cancer-fact-sheet
3 https://ecis.jrc.ec.europa.eu/factsheets.php
4 https://www.cdc.gov/cancer/lung/basic_info/screening. htm
5 https://www.siemens-healthineers.com/press/releases/ naeotomalpha NAEOTOM Alpha is not commercially available in all countries. Due to regulatory reasons, its future availability cannot be guaranteed. Please contact your local Siemens Healthineers organization for further details.
6 https://journals.lww.com/jcat/Abstract/2023/03000/ Lung_Cancer_Screening_Using_Clinical.8.aspx
7 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6037972/
8 https://data.consilium.europa.eu/doc/document/ ST-14770-2022-INIT/en/pdf
9 AI-Rad Companion Chest CT consists of several products that are medical devices in their own right. AI-Rad Companion Chest CT is not commercially available in all countries. Its future availability cannot be ensured.
10 The statements by Siemens Healthineers’ customers described herein are based on results that were achieved in the customer’s unique setting. Because there is no “typical” hospital and many variables exist (e.g., hospital size, case mix, level of IT and/or automation adoption) there can be no guarantee that other customers will achieve the same results.
