Surreal illustration of a lung with data streams, symbolizing early lung cancer detection through technology and information.

Lung Cancer Early Detection: Is a standardized Lexicon the Missing Piece?

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Jordan Keane in Health & Wellness August 2025 • 4 min read.

"How Standardized Reporting Can Improve Lung Nodule Management and Early Cancer Diagnosis"


The challenge in lung cancer diagnosis lies in identifying the small percentage of patients whose disease is detected at an early, treatable stage. High-resolution computed tomography (CT) scans have made it possible to detect early cancers as small, indeterminate lung nodules, yet managing these nodules presents a significant challenge.

Small lung nodules, typically 4 to 8 mm in diameter, pose a diagnostic dilemma. They carry a variable risk of malignancy but are often too small for successful biopsy. Current guidelines recommend serial imaging to monitor growth rates, but the evidence supporting specific management approaches remains limited. Recommendations often stem from lung cancer screening trials involving asymptomatic volunteers adhering to strict scanning schedules.

The National Lung Screening Trial (NLST) demonstrated that CT screening could reduce lung cancer death rates among high-risk individuals. However, the trial also revealed that a significant proportion of those screened had indeterminate lung nodules, most of which would prove benign but would still require follow-up imaging and testing. As imaging technology advances, so must our ability to manage lung nodules effectively.

The Power of Standardized Language: Lessons from Mammography

Surreal illustration of a lung with data streams, symbolizing early lung cancer detection through technology and information.

Danforth et al. highlighted a method to identify lung nodules on chest CT scans within a large health plan using computer searches of radiology reports. Their natural language processing algorithm demonstrated high sensitivity and specificity in identifying patients with newly recognized lung nodules.

The need to search radiology reports for lung nodule findings underscores a critical issue: the lack of standardized language in describing these nodules. Ambiguity in descriptions can lead to confusion in management and potentially delay diagnoses. A parallel can be drawn to mammography screening in the 1980s.

  • Improved Communication: Clear communication between radiologists and clinicians regarding suspicious lung nodules is vital for timely follow-up and management.
  • Decision-Oriented Recommendations: Standardized descriptions enable radiologists to make clear recommendations for follow-up surveillance or diagnostic testing, based on scientific evidence.
  • Systematic Follow-Up: Implementing a systematic method for reminders and call-backs ensures timely follow-up, which is critical given the rapid growth rate of many lung cancers.
The Breast Imaging Reporting and Data System (BI-RADS) was developed to standardize language descriptors for breast lesions in mammography. This standardization enabled studies to predict malignancy from specific types of mammographic lesions, leading to more precise language among radiologists. The BI-RADS system assigned mutually exclusive assessment categories, guiding clinicians to specific actions regarding follow-up management and improving quality assurance and patient care.

Seizing the Opportunity: Standardizing Lung Nodule Reporting for Better Outcomes

The National Lung Screening Trial demonstrated that CT scanning could be a powerful tool for early lung cancer diagnosis. To fully realize this potential, the accompanying information technology and reporting practices must keep pace. The use of natural language by radiologists should evolve towards a standardized language.

In the context of lung cancer, early diagnosis is critical for improving prognosis. A standardized lexicon for lung nodule reporting can enhance communication, guide appropriate follow-up, and ensure timely management.

By adopting standardized reporting practices, the medical community can translate advances in imaging technology into tangible improvements in patient outcomes. This proactive approach to lung nodule management can help shift the focus from late-stage diagnosis to early intervention, ultimately saving lives.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1097/jto.0b013e3182606a69, Alternate LINK

Title: Early Diagnosis Of Lung Cancer: The Convergence Of Imaging And Information Technologies

Subject: Pulmonary and Respiratory Medicine

Journal: Journal of Thoracic Oncology

Publisher: Elsevier BV

Authors: Elizabeth Kern

Published: 2012-08-01

Everything You Need To Know

1

What is the main challenge in lung cancer diagnosis discussed?

The challenge lies in the early identification of lung cancer, often found as small, indeterminate lung nodules during high-resolution CT scans. Managing these nodules is difficult because they can be difficult to diagnose as they can vary in their risk of malignancy, and may be too small for successful biopsy. This complexity highlights the need for effective strategies in the management of lung nodules.

2

Why is a standardized language for lung nodules important?

A standardized language is crucial because current descriptions of lung nodules in radiology reports lack uniformity, which can cause confusion and potentially delay a diagnosis. Similar to the impact of BI-RADS in mammography, standardization will enable clear communication between radiologists and clinicians, enabling recommendations for follow-up surveillance or diagnostic testing based on scientific evidence. A standardized approach ensures systematic follow-up, vital because many lung cancers grow quickly.

3

What is the purpose of the Breast Imaging Reporting and Data System (BI-RADS)?

The Breast Imaging Reporting and Data System (BI-RADS) is a system developed to standardize descriptions of breast lesions in mammography. This standardization allowed researchers to predict malignancy from specific types of mammographic lesions, which lead to a more precise language among radiologists. BI-RADS assigns mutually exclusive assessment categories to guide clinicians toward specific actions regarding follow-up management, improving quality assurance and patient care.

4

What were the key findings of the National Lung Screening Trial (NLST)?

The National Lung Screening Trial (NLST) demonstrated that CT screening could lower lung cancer death rates. However, it revealed that a significant number of screened individuals had indeterminate lung nodules, most of which were benign, but still required follow-up imaging and testing. This underscores the importance of efficient management strategies for lung nodules to take full advantage of early detection.

5

How does standardizing language in radiology reports improve patient outcomes in the context of lung cancer?

Standardizing language in radiology reports is key to maximizing the benefits of CT scanning for early lung cancer diagnosis. Improved communication is critical. Standardization enables clear recommendations for follow-up, and systematic methods for reminders and call-backs are implemented. The goal is to catch lung cancer in its earliest, most treatable stages.

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