In comparison to primary lung cancer, pulmonary metastases had a 33 percent higher frequency of ring-like peripheral high iodine concentration on dual-energy computed tomography (DECT), according to a new retrospective study.
Emerging research suggests a key finding on dual-energy computed tomography (DECT) may help resolve the diagnostic challenge of differentiating between pulmonary metastases and primary lung cancer.
In a recent retrospective study, published in the American Journal of Roentgenology, researchers reviewed preoperative DECT findings in 68 patients who had resection for primary lung cancer and 25 patients who had resection for pulmonary metastases.
While the study authors saw no significant differences between pulmonary metastases and primary lung cancer for spiculated margins, air bronchograms and rim enhancement, they found a 52 percent frequency of ring-like peripheral high iodine concentration in patients with pulmonary metastases versus 19 percent in patients with primary lung cancer.
In a subsequent analysis, which considered factors such as lesion diameter, multiple lesion resections and smoking history, the researchers also found that ring-like peripheral high iodine concentration was the only significant independent predictor of pulmonary metastasis.
“(Ring-like) peripheral high iodine concentration was significantly more frequent in pulmonary metastases than in primary lung cancers … and was the only significant independent predictor of pulmonary metastases in multivariable regression analysis,” wrote lead study author Yoshinao Sato, M.D., Ph.D., who is affiliated with the Cancer Institute Hospital in Tokyo, Japan, and colleagues. “This finding may help guide further management in patients in whom a lung lesion presents a diagnostic challenge (e.g., a solitary nodule in a patient with a history of malignancy).”
(Editor’s note: For related content, see “Nine Takeaways from Recent Meta-Analysis on Lung Cancer Screening with Low-Dose CT” and “New Computed Tomography Study Shows High 20-Year Survival Rates for Early-Stage Lung Cancer.”)
Sato and colleagues also found that ring-like peripheral high iodine concentration demonstrated a high specificity rate of 81 percent (albeit with a low sensitivity rate of 52 percent) for pulmonary metastases. Univariable analysis showed the presence of smaller lesions and multiple resected lesions were also predictive of pulmonary metastases and have implications in lung cancer management, according to the study authors.
“Metastases’ smaller size may reflect prompt detection of such lesions resulting from oncologic surveillance in these patients,” noted Sato and colleagues. “In addition, such lesions may have been more likely to undergo prompt intervention after detection; in comparison, suspected primary lung cancers may undergo an initial observation perior to demonstrate potential growth.”
The researchers acknowledged the inherent limitations of a retrospective, single-center study as well as the small sample size. The study did not include lung metastases assessed by percutaneous lung or transbronchoscopic biopsy, and the researchers concede that the focus on resected nodules may have led to potential patient selection biases. Dr. Sato and colleagues added that only the largest lung lesion was evaluated in patients with multiple pulmonary metastases that may have had a variety of diagnostic characteristics.
Photon-Counting Computed Tomography: Eleven Takeaways from a New Literature Review
May 27th 2025In a review of 155 studies, researchers examined the capabilities of photon-counting computed tomography (PCCT) for enhanced accuracy, tissue characterization, artifact reduction and reduced radiation dosing across thoracic, abdominal, and cardiothoracic imaging applications.
Can AI Predict Future Lung Cancer Risk from a Single CT Scan?
May 19th 2025In never-smokers, deep learning assessment of single baseline low-dose computed tomography (CT) scans demonstrated a 79 percent AUC for predicting lung cancer up to six years later, according to new research presented today at the American Thoracic Society (ATS) 2025 International Conference.
Can Emerging AI Software Offer Detection of CAD on CCTA on Par with Radiologists?
May 14th 2025In a study involving over 1,000 patients who had coronary computed tomography angiography (CCTA) exams, AI software demonstrated a 90 percent AUC for assessments of cases > CAD-RADS 3 and 4A and had a 98 percent NPV for obstructive coronary artery disease.