April 21, 2024
Lung Cancer Diagnostic and Screening Market

Lung Cancer Diagnostic and Screening Market is driven by Technological Advancements in Imaging Techniques

Lung cancer is one of the deadliest forms of cancer that develops in tissues of the lungs. Computed tomography (CT) scans, X-rays, MRI scans, chest X-rays, and positron emission tomography (PET) scans are some of the most widely used imaging techniques for lung cancer screening and diagnosis. Advancements in imaging technologies such as low-dose computed tomography (LDCT) scans have significantly improved detection of lung cancer as well as guided procedures such as biopsies and surgeries. LDCT scans use much lower radiation doses than conventional CT scans to produce clear images of the lungs. This allows radiologists to detect even small lung nodules indicative of early-stage lung cancer.

The global Lung Cancer Diagnostic and Screening Market is estimated to be valued at US$ 2243.98 Mn in 2023 and is expected to exhibit a CAGR of 42.% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.

Market key trends: Advancements in AI and ML technologies have enabled more precise and early lung cancer diagnosis. Machine learning algorithms are being used to analyze imaging scans and other diagnostic data to detect anomalies indicative of lung cancer. Deep learning algorithms can identify suspicious regions in CT scans at a resolution several times higher than human radiologists. They can also integrate information from multiple scans over time to detect tiny changes indicative of cancer development or progression. This helps in more accurate diagnoses and better screening outcomes. With continuous improvements in computing power and availability of large diagnostic datasets, adoption of AI and machine learning is expected to grow significantly in lung cancer screening and diagnostics over the coming years.

Porter’s Analysis

Threat of new entrants: The lung cancer diagnostic and screening market requires huge investment in research and development as well as regulatory approvals, which acts as a barrier for new entrants.

Bargaining power of buyers: The bargaining power of buyers is moderate as there are several existing players offering diverse diagnostic and screening solutions for lung cancer.

Bargaining power of suppliers: Suppliers have moderate bargaining power due to the availability of substitutes and differentiation in products.

Threat of new substitutes: Threat of new substitutes is high as there exists alternatives for diagnosing lung cancer such as CT scan, biopsy, chest X-ray, and sonography.

Competitive rivalry: The competitive rivalry in the market is high owing to the presence of key global and regional players offering differentiated products.

Key Takeaways

Global Lung Cancer Diagnostic And Screening Market Insights is expected to witness high growth over the forecast period. The global Lung Cancer Diagnostic and Screening Market is estimated to be valued at US$ 2243.98 Mn in 2023 and is expected to exhibit a CAGR of 42.% over the forecast period 2023 to 2030.

Regional analysis: North America holds the largest share in the lung cancer diagnostic and screening market owing to increasing government support for research and development activities along with rising prevalence of lung cancer and adoption of advanced diagnostic techniques. The Asia Pacific region is anticipated to witness the highest CAGR during the forecast period with increasing healthcare expenditure and growing lung cancer incidence in the region.

Key players: Key players operating in the lung cancer diagnostic and screening market include ABB, ANSYS, Inc., Autodesk Inc., AVEVA Group plc, Amazon Web Services, Inc., Dassault Systèmes, GE DIGITAL, General Electric, Hexagon AB, IBM Corporation, Microsoft Corporation, PTC Inc., Rockwell Automation, SAP SE and Siemens AG. ABB specializes in development of precision diagnostics systems for lung cancer screening.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it