Role of Chest Radiographs in Early Lung Cancer Detection

Junghyun Kim; Kwan Hyoung Kim

Disclosures

Transl Lung Cancer Res. 2020;9(3):522-531. 

In This Article

Abstract and Introduction

Abstract

Background: Lung cancer is the second most common and the most fatal form of cancer. Although annual low-dose computed tomography is used as the primary method of cancer screening, it presents challenges regarding resources as well as potential health risks from radiation exposure. Chest radiography (CXR), though less effective, is used frequently and commonly. Moreover, often in clinical settings, CXR is the first imaging modality used; computed tomography is subsequently performed if abnormalities are detected on CXRs. This study examined whether controlling for distractors and time constraints, as well as side-by-side comparison of multiple CXRs in clinical settings can aid earlier detection of radiological abnormalities indicative of lung cancer lesions.

Methods: Thirty-two attending physicians in the Republic of Korea examined 1,750 radiographs of 50 lung cancer cases. Using "hot spot" technology, participants indicated the possible locations of cancer lesions on each radiograph. Subsequently, the same radiographs, cropped to focus the anatomical regions where lung cancers were diagnosed, were shown side-by-side to the participants. The participants were asked to identify the radiograph which first enabled the diagnosis of lung cancer and which first showed a possible lesion.

Results: Removal of systemic constraints alone significantly improved lesion identification by 221.72±9.69 days. Presenting radiographs side-by-side, cropped to relevant areas, had an additional significant and positive impact on cancer detection in both hidden and open areas on CXRs. Also, lesions were detected at smaller sizes and earlier than when actually diagnosed.

Conclusions: CXR with improved methods and settings provides an easily accessible and low-risk imaging method for earlier detection of lung cancer compared to current clinical imaging settings. Further, this study demonstrates the potential effectiveness of programs that allow side-by-side comparisons of cropped areas of multiple radiographs to detect radiological abnormalities.

Introduction

In 2018, Siegel et al. predicted that the number of newly diagnosed lung cancers that year would be approximately 234,030, making it the second most common cancer. Moreover, they estimated the number of deaths from this condition in 2018 would be approximately 154,050 (25.3% of total cancer deaths), making it the most fatal form of cancer.[1]

Despite the risk of overdiagnosis, false positives, radiation exposure, and unnecessary studies, low-dose computer tomography (LDCT) screening of at-risk patients has offered positive outcomes for lung cancer mortality. The United States preventive services task force recommends annual LDCT screening for people aged 55 to 80 years with a 30 pack-year smoking history and a history of smoking within the last 15 years.[2,3]

However, this does not mean all lung cancers can be detected with LDCT.[4] Additionally, although the amount of radiation exposure in LDCT is 1/6 of that in regular CT,[5] the potential health risk from this exposure is still significant.[6] Furthermore, abundant resources and manpower are also needed to operate this screening system.

Conversely, chest radiographs (CXRs) are one of the most commonly utilized diagnostic tools for chest diseases in clinical practice. The technology is easy to operate and the procedure has a relatively low level of radiation exposure; thus, it is the standard diagnostic tool for respiratory illnesses. Also, it imposes less of a burden on radiologists than other, more sophisticated diagnostic imaging tools.

However, CXRs are not without their shortcomings. CXRs are often performed by personnel that do not specialize in radiology. Therefore, they are more prone to misinterpretation. Of all misdiagnosed lung cancer cases, 90% utilized CXRs and 10% used CTs and other diagnostic tools.[7] Misinterpreting images can result in delayed diagnosis and more negative clinical outcomes. Identifying lesions early while maintaining accuracy is the key to improving lung cancer survival.[8,9]

Multiple studies have suggested that using CXRs in lung cancer screening may improve survival. For instance, Strauss et al. reported findings from randomized controlled trials that show CXR screening can improve lung cancer survival as cancers are diagnosed at earlier stages.[8,9] Another large population-based cohort study showed an 18% reduction in lung cancer mortality with CXR screening in at-risk populations.[10] Furthermore, a case-control study found that lung cancer mortality was reduced by more than 20% with CXR screening.[11] These studies suggest that CXRs can be significantly beneficial for the screening of lung cancer.

In this study, we examine whether retrospective observation of lung cancer patients confirmed by pathology can elucidate significant radiological abnormalities earlier than when diagnoses were made. We also introduce a new comparison method for CXR interpretation in lung cancer patients. We hypothesize that side-by-side comparisons of cropped CXRs will improve abnormal lesion detection.

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