Dual-energy CT lung perfusion in systemic sclerosis: preliminary experience in 101 patients.

OBJECTIVES: To investigate lung perfusion in systemic sclerosis (SSc). METHODS: The study population included 101 patients who underwent dual-energy CT (DECT) in the follow-up of SSc with pulmonary function tests obtained within 2 months. Fifteen patients had right heart catheterization-proven PH. RESULTS: Thirty-seven patients had no SSc-related lung involvement (Group A), 56 patients had SSc-related interstitial lung disease (Group B) of variable extent (Group B mild: ≤ 10% of lung parenchyma involved: n = 17; Group B moderate: between 11 and 50%: n = 31; Group B severe: > 50%: n = 8), and 8 patients had PVOD/PCH (Group C). Lung perfusion was abnormal in 8 patients in Group A (21.6%), 14 patients in Group B (25%), and 7 patients in Group C (87.5%). In Group A and Group B mild (n = 54), (a) patients with abnormal lung perfusion (n = 14; 26%) had a higher proportion of NYHA III/IV scores of dyspnea (7 [50%] vs 7 [17.5%]; p = 0.031) and a shorter mean walking distance at the 6MWT (397.0 [291.0; 466.0] vs 495.0 [381.0; 549.0]; p = 0.042) but no evidence of difference in the DLCO% predicted (61.0 [53.0; 67.0] vs 68.0 [61.0; 78.0]; p = 0.055) when compared to patients with normal lung perfusion (n = 40; 74%); (b) a negative correlation was found between the iodine concentration in both lungs and the DLCO% predicted but it did not reach statistical significance (r = -0.27; p = 0.059) and no correlation was found with the PAPs (r = 0.16; p = 0.29) and walking distance during the 6MWT (r = -0.029; p = 0.84). CONCLUSIONS: DECT lung perfusion provides complementary information to standard HRCT scans, depicting perfusion changes in SSc patients with normal or minimally infiltrated lung parenchyma. KEY POINTS: • In a retrospective observational study of 101 consecutive patients with SSc, dual-energy CT pulmonary angiography was obtained to evaluate lung perfusion. • Lung perfusion was abnormal in 14 out of 54 patients (26%) with no or mild SSc-related lung infiltration. • Patients with abnormal perfusion and no or mild SSc-related lung infiltration had more severe scores of dyspnea and shorter walking distance than patients with similar lung findings and normal perfusion, suggesting the presence of small vessel vasculopathy.

Ultra-high resolution CT imaging of interstitial lung disease: impact of photon-counting CT in 112 patients.

OBJECTIVES: To compare lung parenchyma analysis on ultra-high resolution (UHR) images of a photon-counting CT (PCCT) scanner with that of high-resolution (HR) images of an energy-integrating detector CT (EID-CT). METHODS: A total of 112 patients with stable interstitial lung disease (ILD) were investigated (a) at T0 with HRCT on a 3rd-generation dual-source CT scanner; (b) at T1 with UHR on a PCCT scanner; (c) with a comparison of 1-mm-thick lung images. RESULTS: Despite a higher level of objective noise at T1 (74.1 ± 14.1 UH vs 38.1 ± 8.7 UH; p < 0.0001), higher qualitative scores were observed at T1 with (a) visualization of more distal bronchial divisions (median order; Q1-Q3) (T1: 10th division [9-10]; T0: 9th division [8-9]; p < 0.0001); (b) greater scores of sharpness of bronchial walls (p < 0.0001) and right major fissure (p < 0.0001). The scores of visualization of CT features of ILD were significantly superior at T1 (micronodules: p = 0.03; linear opacities, intralobular reticulation, bronchiectasis, bronchiolectasis, and honeycombing: p < 0.0001), leading to the reclassification of 4 patients with non-fibrotic ILD at T0, recognized with fibrotic ILD at T1. At T1, the mean (± SD) radiation dose (CTDI vol: 2.7 ± 0.5 mGy; DLP: 88.5 ± 21 mGy.cm) was significantly lower than that delivered at T0 (CTDI vol: 3.6 ± 0.9 mGy; DLP: 129.8 ± 31.7 mGy.cm) (p < 0.0001), corresponding to a mean reduction of 27% and 32% for the CTDIvol and DLP, respectively. CONCLUSIONS: The UHR scanning mode of PCCT allowed a more precise depiction of CT features of ILDs and reclassification of ILD patterns with significant radiation dose reduction. CLINICAL RELEVANCE STATEMENT: Evaluation of lung parenchymal structures with ultra-high-resolution makes subtle changes at the level of the secondary pulmonary lobules and lung microcirculation becoming visually accessible, opening new options for synergistic collaborations between highly-detailed morphology and artificial intelligence. KEY POINTS: • Photon-counting CT (PCCT) provides a more precise analysis of lung parenchymal structures and CT features of interstitial lung diseases (ILDs). • The UHR mode ensures a more precise delineation of fine fibrotic abnormalities with the potential of modifying the categorization of ILD patterns. • Better image quality at a lower radiation dose with PCCT opens new horizons for further dose reduction in noncontrast UHR examinations.

Ultra-High-Resolution Photon-Counting CT Imaging of the Chest: A New Era for Morphology and Function.

ABSTRACT: After a decade of preclinical testing, photon-counting computed tomography (PCCT) has now entered daily routine, enabling radiologists to start investigating thoracic disorders in unprecedented conditions. The improved spatial resolution of the ultra-high-resolution (UHR) scanning mode is a major step for the analysis of bronchopulmonary disorders, making abnormalities at the level of small anatomical structures such as secondary pulmonary lobules accessible to radiologists. Distal divisions of pulmonary and systemic vessels also benefit from UHR protocols as alterations of lung microcirculation were previously excluded from confident analysis with energy-integrating detector CT. Although noncontrast chest CT examinations were the initial target of UHR protocols, the clinical value of this mode is also applicable to chest CT angiographic examinations with improved morphological evaluation and higher-quality lung perfusion imaging. The clinical benefits of UHR have been evaluated in initial studies, allowing radiologists to foresee the field of future applications, all combining high diagnostic value and radiation dose reduction. The purpose of this article is to highlight the technological information relevant to daily practice and to review the current clinical applications in the field of chest imaging.

Assessment of pulmonary arterial circulation 3 months after hospitalization for SARS-CoV-2 pneumonia: Dual-energy CT (DECT) angiographic study in 55 patients.

BACKGROUND: During COVID-19, the main manifestations of the disease are not only pneumonia but also coagulation disorders. The purpose of this study was to evaluate pulmonary vascular abnormalities 3 months after hospitalization for SARS-CoV-2 pneumonia in patients with persistent respiratory symptoms. METHODS: Among the 320 patients who participated in a systematic follow-up 3 months after hospitalization, 76 patients had residual symptoms justifying a specialized follow-up in the department of pulmonology. Among them, dual-energy CT angiography (DECTA) was obtained in 55 patients. FINDINGS: The 55 patients had partial (n = 40; 72.7%) or complete (n = 15; 27.3%) resolution of COVID-19 lung infiltration. DECTA was normal in 52 patients (52/55; 94.6%) and showed endoluminal filling defects in 3 patients (3/55; 5.4%) at the level of one (n = 1) and two (n = 1) segmental arteries of a single lobe and within central and peripheral arteries (n = 1). DECT lung perfusion was rated as non-interpretable (n = 2;3.6%), normal (n = 17; 30.9%) and abnormal (n = 36; 65.5%), the latter group comprising 32 patients with residual COVID-19 opacities (32/36; 89%) and 4 patients with normal lung parenchyma (4/36; 11%). Perfusion abnormalities consisted of (a) patchy defects (30/36; 83%), (b) PE-type defects (6/36; 16.6%) with (n = 1) or without proximal thrombosis (n = 5); and (c) focal areas of hypoperfusion (2/36; 5.5%). Increased perfusion was seen in 15 patients, always matching GGOs, bands and/or vascular tree-in- bud patterns. INTERPRETATION: DECT depicted proximal arterial thrombosis in 5.4% of patients and perfusion abnormalities suggestive of widespread microangiopathy in 65.5% of patients. Lung microcirculation was abnormal in 4 patients with normal lung parenchyma.

Machine Learning and Deep Neural Network Applications in the Thorax: Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Aorta, and Chronic Obstructive Pulmonary Disease.

The radiologic community is rapidly integrating a revolution that has not fully entered daily practice. It necessitates a close collaboration between computer scientists and radiologists to move from concepts to practical applications. This article reviews the current littérature on machine learning and deep neural network applications in the field of pulmonary embolism, chronic thromboembolic pulmonary hypertension, aorta, and chronic obstructive pulmonary disease.

Regional Distribution of Pulmonary Blood Volume with Dual-Energy Computed Tomography: Results in 42 Subjects.

RATIONALE AND OBJECTIVES: The noninvasive approach of lung perfusion generated from dual-energy computed tomography acquisitions has entered clinical practice. The purpose of this study was to analyze the regional distribution of iodine within distal portions of the pulmonary arterial bed on dual-source, dual-energy computed tomography examinations in a cohort of subjects without cardiopulmonary pathologies. MATERIALS AND METHODS: The study population included 42 patients without cardiorespiratory disease, enabling quantitative and qualitative analysis of pulmonary blood volume after administration of a 40% contrast agent. Qualitative analysis was based on visual assessment. Quantitative analysis was obtained after semiautomatic division of each lung into 18 areas. RESULTS: The iodine concentration did not significantly differ between the right (R) and left (L) lungs (P = .49), with a mean attenuation of 41.35 Hounsfield units (HU) and 41.14 HU, respectively. Three regional gradients of attenuation were observed between: (a) lung bases and apices (P < .001), linked to the conditions of examination (mean Δ: 6.23 in the R lung; 5.96 in the L lung); (b) posterior and anterior parts of the lung (P < .001) due to gravity (mean Δ: 11.92 in the R lung ; 15.93 in the L lung); and (c) medullary and cortical lung zones (P < .001) (mean Δ: 9.35 in the R lung ; 8.37 in the L lung). The intensity of dependent-nondependent (r = 0.42; P < .001) and corticomedullary (r = 0.58; P < .0001) gradients was correlated to the overall iodine concentration. CONCLUSION: Distribution of pulmonary blood volume is influenced by physiological gradients and scanning conditions.