Lung Magnetic Resonance Imaging

Ohno, Yoshiharu; Ozawa, Yoshiyuki; Nagata, Hiroyuki; Ueda, Takahiro; Yoshikawa, Takeshi; Takenaka, Daisuke; Koyama, Hisanobu

doi:10.1097/rli.0000000000001017

Invest Radiol

2023

DOI: 10.1097/rli.0000000000001017

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Lung Magnetic Resonance Imaging

Yoshiharu Ohno,

Yoshiyuki Ozawa,

Hiroyuki Nagata

et al.

Abstract: Since lung magnetic resonance imaging (MRI) became clinically available, limited clinical utility has been suggested for applying MRI to lung diseases. Moreover, clinical applications of MRI for patients with lung diseases or thoracic oncology may vary from country to country due to clinical indications, type of health insurance, or number of MR units available. Because of this situation, members of the Fleischner Society and of the Japanese Society for Magnetic Resonance in Medicine have published new reports… Show more

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2024

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Cited by 4 publications

References 231 publications

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Chiral ultrasmall nickel hydroxide nanoparticles enable enantioselective magnetic resonance imaging of hepatocellular carcinoma and lung metastases

Li,

Zhang,

Gao

et al. 2024

New J. Chem.

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Chiral ultrasmall nickel hydroxide nanoparticles enable enantioselective magnetic resonance imaging of hepatocellular carcinoma and lung metastases

Li,

Zhang,

Gao

et al. 2024

New J. Chem.

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Advancing Medical Imaging Research Through Standardization

Jeon,

Park,

Kahn

et al. 2024

Invest Radiol

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Artificial intelligence (AI) has made significant advances in radiology. Nonetheless, challenges in AI development, validation, and reproducibility persist, primarily due to the lack of high-quality, large-scale, standardized data across the world. Addressing these challenges requires comprehensive standardization of medical imaging data and seamless integration with structured medical data. Developed by the Observational Health Data Sciences and Informatics community, the OMOP Common Data Model enables large-scale international collaborations with structured medical data. It ensures syntactic and semantic interoperability, while supporting the privacy-protected distribution of research across borders. The recently proposed Medical Imaging Common Data Model is designed to encompass all DICOM-formatted medical imaging data and integrate imaging-derived features with clinical data, ensuring their provenance. The harmonization of medical imaging data and its seamless integration with structured clinical data at a global scale will pave the way for advanced AI research in radiology. This standardization will enable federated learning, ensuring privacy-preserving collaboration across institutions and promoting equitable AI through the inclusion of diverse patient populations. Moreover, it will facilitate the development of foundation models trained on large-scale, multimodal datasets, serving as powerful starting points for specialized AI applications. Objective and transparent algorithm validation on a standardized data infrastructure will enhance reproducibility and interoperability of AI systems, driving innovation and reliability in clinical applications.

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Leveraging Phase Information of 3D Isotropic Ultrashort Echo Time Pulmonary MRI for the Detection of Thoracic Lymphadenopathy

Ziegelmayer,

Van,

Weiss

et al. 2024

Invest Radiol

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Background Ultrashort echo time (UTE) allows imaging of tissues with short relaxation times, but it comes with the expense of long scan times. Magnitude images of UTE magnetic resonance imaging (MRI) are widely used in pulmonary imaging due to excellent parenchymal signal, but have insufficient contrast for other anatomical regions of the thorax. Our work investigates the value of UTE phase images (UTE-Ps)—generated simultaneously from the acquired UTE signal used for the magnitude images—for the detection of thoracic lymph nodes based on water-fat contrast. It employs an advanced imaging sequence and reconstruction allowing isotropic 3D UTE MRI in clinically acceptable scan times. Methods In our prospective study, 42 patients with 136 lymph nodes had undergone venous computed tomography and pulmonary MRI scans with UTE within a 14-day interval. 3D isotropic UTE images were acquired using FLORET (fermat looped, orthogonally encoded trajectories). Background-corrected phase images (UTE-P) and magnitude images were reconstructed simultaneously from the UTE-Signal. Three radiologists performed a blinded reading in which all lymph nodes with a short-axis diameter (SAD) of at least 0.5 cm were detected. Detection rates and performance metrics of UTE-P for all lymph node regions and for pathologic (SAD ≥10 mm) and nonpathologic lymph nodes (SAD <10 mm) were calculated using computed tomography as a reference. The interreader agreement defined as the presence or absence of lymph nodes based on patient and region was calculated using Fleiss kappa (κ). Findings In the phase images, pathologic lymph nodes in the mediastinal and hilar region were detected with a high diagnostic confidence due to the achieved water-fat contrast (average sensitivity, specificity, positive predictive value, and negative predictive value of 95.83% [confidence interval (CI), 92.76%–98.91%], 100%, 100%, and 99.32% [CI, 98.08%–100%]). Stepwise inclusion of all lymph node regions and nonpathologic lymph nodes was associated with a moderate decrease resulting in an average sensitivity, specificity, positive predictive value, and negative predictive value of 77.9% (CI, 70.9%–84.7%), 99.4% (CI, 98.7%–99.9%), 97.0% (CI, 93.4%–99.7%), and 94.7% (CI, 92.8%–96.4%) for the inclusion of all lymph nodes sizes and regions. Interreader agreement was almost perfect (κ = 0.92). Conclusions Pathological lymph nodes in the mediastinal and hilar region can be detected in phase-images with high diagnostic confidence, thanks to the ability of the phase images to depict water-fat contrast in combination with high spatial 3D resolution, extending the clinical applicability of UTE into the simultaneous assessment of lung parenchyma and lymph nodes.

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Lung Magnetic Resonance Imaging

Cited by 4 publications

References 231 publications

Chiral ultrasmall nickel hydroxide nanoparticles enable enantioselective magnetic resonance imaging of hepatocellular carcinoma and lung metastases

Chiral ultrasmall nickel hydroxide nanoparticles enable enantioselective magnetic resonance imaging of hepatocellular carcinoma and lung metastases

Advancing Medical Imaging Research Through Standardization

Leveraging Phase Information of 3D Isotropic Ultrashort Echo Time Pulmonary MRI for the Detection of Thoracic Lymphadenopathy

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