Journal of Thoracic Imaging最新文献

Interstitial lung diseases (ILDs) associated with autoimmune diseases show characteristic signs of imaging. Radiologic signs are also used in the identification of ILDs with features suggestive of autoimmune disease that do not meet the criteria for a specific autoimmune disease. Radiologists play a key role in identifying these signs and assessing their relevance as part of multidisciplinary team discussions. A radiologist may be the first health care professional to pick up signs of autoimmune disease in a patient referred for assessment of ILD or with suspicion for ILD. Multidisciplinary team discussion of imaging findings observed during follow-up may inform a change in diagnosis or identify progression, with implications for a patient's treatment regimen. This article describes the imaging features of autoimmune disease-related ILDs and the role of radiologists in assessing their relevance.

Interstitial lung disease (ILD) is a heterogeneous group of disorders with complex and varied imaging manifestations and prognosis. High-resolution computed tomography (HRCT) is the current standard-of-care imaging tool for ILD assessment. However, visual evaluation of HRCT is limited by interobserver variation and poor sensitivity for subtle changes. Such challenges have led to tremendous recent research interest in objective and reproducible methods to examine ILDs. Computer-aided CT analysis to include texture analysis and machine learning methods have recently been shown to be viable supplements to traditional visual assessment through improved characterization and quantification of ILDs. These quantitative tools have not only been shown to correlate well with pulmonary function tests and patient outcomes but are also useful in disease diagnosis, surveillance and management. In this review, we provide an overview of recent computer-aided tools in diagnosis, prognosis, and longitudinal evaluation of fibrotic ILDs, while outlining some of the pitfalls and challenges that have precluded further advancement of these tools as well as potential solutions and further endeavors.

High-resolution computed tomography (HRCT) is an essential component of the diagnosis and assessment of patients with interstitial lung diseases (ILDs). In some cases, a diagnosis of ILD can be made solely based on a multidisciplinary discussion of HRCT findings and clinical evaluation. HRCT findings also inform prognosis and may influence treatment decisions. It is essential that high-quality HRCT images are obtained using parameters for optimum spatial resolution. Key terms used to describe HRCT findings should be used consistently among clinicians. Radiologic information should be included as part of the multidisciplinary discussion of patients with ILDs during follow-up.

Purpose: Correlate magnetic resonance imaging (MRI) parameters at baseline with disease progression in nonidiopathic pulmonary fibrosis interstitial lung disease (ILD).

Materials and methods: Prospective observational cohort study, in which patients with non-idiopathic pulmonary fibrosis ILD underwent MRI at baseline (1.5 T). T2-weighted images (T2-WI) were acquired by axial free-breathing respiratory-gated fat-suppressed "periodically rotated overlapping parallel lines with enhanced reconstruction" and T1-weighted images (T1-WI) by coronal end-expiratory breath-hold fat-suppressed "volumetric interpolated breath-hold examination" sequences, before and at time points T1, T3, T5, and T10 minutes after gadolinium administration. After MRI segmentation, signal intensity values were extracted by dedicated software. Percentage of the ILD volume and a ratio between signal intensity of ILD (SIILD) and normal lung (SInormal lung) were calculated for T2-WI; percentage of signal intensity (%SI) at each time point, time to peak enhancement, and percent relative enhancement of ILD in comparison with normal lung (%SIILD/normal lung) were calculated for T1-WI. MRI parameters at baseline were correlated with diagnosis of disease progression and variation in percent predicted forced vital capacity (%FVC) and diffusing capacity of the lung for carbon monoxide after 12 months.

Results: Comprehensive MRI evaluation (T2-WI and T1-WI) was performed in 21 of the 25 patients enrolled (68% females; mean age: 62.6 y). Three of the 24 patients who completed follow-up fulfilled criteria for disease progression. Baseline T2-WI SIILD/SInormal lung was higher for the progression group (P = 0.052). T2-WI SIILD/SInormal lung and T1-WI %SIILD/normal lung at T1 were positively correlated with the 12-month variation in %FVC (r = 0.495, P = 0.014 and r = 0.489, P= 0.034, respectively).

Conclusions: Baseline MRI parameters correlate with %FVC decline after 12 months.

Purpose: Intravenous contrast poses challenges to computed tomography (CT) muscle density analysis. We developed and tested corrections for contrast-enhanced CT muscle density to improve muscle analysis and the utility of CT scans for the assessment of myosteatosis.

Materials and methods: Using retrospective images from 240 adults who received routine abdominal CT imaging from March to November 2020 with weight-based iodine contrast, we obtained paraspinal muscle density measurements from noncontrast (NC), arterial, and venous-phase images. We used a calibration sample to develop 9 different mean and regression-based corrections for the effect of contrast. We applied the corrections in a validation sample and conducted equivalence testing.

Results: We evaluated 140 patients (mean age 52.0 y [SD: 18.3]; 60% female) in the calibration sample and 100 patients (mean age 54.8 y [SD: 18.9]; 60% female) in the validation sample. Contrast-enhanced muscle density was higher than NC by 8.6 HU (SD: 6.2) for the arterial phase (female, 10.4 HU [SD: 5.7]; male, 6.0 HU [SD:6.0]) and by 6.4 HU [SD:8.1] for the venous phase (female, 8.0 HU [SD: 8.6]; male, 4.0 HU [SD: 6.6]). Corrected contrast-enhanced and NC muscle density was equivalent within 3 HU for all correctionns. The -7.5 HU correction, independent of sex and phase, performed well for arterial (95% CI: -0.18, 1.80 HU) and venous-phase data (95% CI: -0.88, 1.41 HU).

Conclusions: Our validated correction factor of -7.5 HU renders contrast-enhanced muscle density statistically similar to NC density and is a feasible rule-of-thumb for clinicians to implement.

Purpose: Military deployment to dusty, austere environments in Southwest Asia and Afghanistan is associated with symptomatic airways diseases including asthma and bronchiolitis. The utility of chest high-resolution computed tomographic (HRCT) imaging in lung disease diagnosis in this population is poorly understood. We investigated visual assessment of HRCT for identifying deployment-related lung disease compared with healthy controls.

Materials and methods: Chest HRCT images from 46 healthy controls and 45 symptomatic deployed military personnel with clinically confirmed asthma and/or biopsy-confirmed distal lung disease were scored by 3 independent thoracic radiologists. We compared demographic and clinical characteristics and frequency of imaging findings between deployers and controls, and between deployers with asthma and those with biopsy-confirmed distal lung disease, using χ2, Fisher exact or t tests, and logistic regression where appropriate. We also analyzed inter-rater agreement for imaging findings.

Results: Expiratory air trapping was the only chest CT imaging finding that was significantly more frequent in deployers compared with controls. None of the 24 deployers with biopsy-confirmed bronchiolitis and/or granulomatous pneumonitis had HRCT findings of inspiratory mosaic attenuation or centrilobular nodularity. Only 2 of 21 with biopsy-proven emphysema had emphysema on HRCT.

Conclusions: Compared with surgical lung biopsy, visual assessment of HRCT showed few abnormalities in this small cohort of previously deployed symptomatic veterans with normal or near-normal spirometry.