Background: Pulmonary vein sign (PVS) indicates abnormal pulmonary venous flow on computed tomography pulmonary angiography (CTPA) is a frequent finding in proximal chronic thromboembolic pulmonary hypertension (CTEPH). PVS’s occurrence in distal CTEPH and correlation to disease severity is unknown. Using right heart catheterization data, we evaluated the relationship between PVS and CTEPH disease distribution and severity. Materials and Method: A total of 93 consecutive CTEPH cases with both CTPA and right heart catheterization were identified in this retrospective multi-institutional study. After excluding 17 cases with suboptimal CTPA, there were 52 proximal and 24 distal CTEPH cases. Blood flow in the major pulmonary veins was graded qualitatively. Subgroup analysis of PVS was performed in 38 proximal CTEPH cases before and after pulmonary endarterectomy. Results: PVS was more frequent in proximal (79%) than distal CTEPH (29%) (P<0.001). No significant difference was noted in invasive mean pulmonary artery pressure (46±11 and 41±12 mm Hg) or pulmonary vascular resistance (9.4±4.5 and 8.4±4.8 WU) between the 2 groups. In the subgroup analysis, PVS was present in 29/38 patients (76%) before surgery. Postoperatively, 33/38 cases (87%, P<0.001) had normal venous flow (mean pulmonary artery pressure 46±11 and 25; pulmonary vascular resistance 9.2±4.3 and 2.6 WU preop and postop, respectively). Conclusion: PVS is a common feature in proximal but infrequent findings in distal CTEPH. PVS does not correlate with hemodynamic severity. PVS resolution was seen in the majority of patients following successful endarterectomy.

Purpose: Quantitative biomarkers from chest computed tomography (CT) can facilitate the incidental detection of important diseases. Atrial fibrillation (AFib) substantially increases the risk for comorbid conditions including stroke. This study investigated the relationship between AFib status and left atrial enlargement (LAE) on CT. Materials and Methods: A total of 500 consecutive patients who had undergone nongated chest CTs were included, and left atrium maximal axial cross-sectional area (LA-MACSA), left atrium anterior-posterior dimension (LA-AP), and vertebral body cross-sectional area (VB-Area) were measured. Height, weight, age, sex, and diagnosis of AFib were obtained from the medical record. Parametric statistical analyses and receiver operating characteristic curves were performed. Machine learning classifiers were run with clinical risk factors and LA measurements to predict patients with AFib. Results: Eighty-five patients with a diagnosis of AFib were identified. Mean LA-MACSA and LA-AP were significantly larger in patients with AFib than in patients without AFib (28.63 vs. 20.53 cm², P<0.000001; 4.34 vs. 3.5 cm, P<0.000001, respectively), both with area under the curves (AUCs) of 0.73. Multivariable logistic regression analysis including age, sex, and VB-Area with LA-MACSA improved the AUC for predicting AFib (AUC=0.77). An LA-MACSA threshold of 30 cm² demonstrated high specificity for AFib diagnosis at 92% and sensitivity of 48%, and LA-AP threshold at 4.5 cm demonstrated 90% specificity and 42% sensitivity. A Bayesian machine learning model using age, sex, height, body surface area, and LA-MACSA predicted AFib with an AUC of 0.743. Conclusions: LA-MACSA or LA-AP can be rapidly measured from routine chest CT, and when >30 cm² and >4.5 cm, respectively, are specific indicators to predict patients at increased risk for AFib.

Purpose: Patients with systemic lupus erythematosus (SLE) are at risk of cardiac disease including antimalarial-induced cardiomyopathy (AMIC). The purpose of this study is to evaluate cardiac magnetic resonance imaging parametric mapping findings in SLE patients with AMIC and investigate the relationship of T1/T2 mapping to antimalarial (AM) treatment duration. Materials and Methods: All patients with SLE who had undergone cardiac magnetic resonance imaging with T1/T2 mapping for evaluation of suspected cardiac disease between 2018 and 2021 were evaluated and compared with healthy controls. To facilitate comparison between scanners, T1/T2 values were converted to a z-score using scanner-specific local reference values. Patients were classified into 3 groups: AMIC, myocarditis, and other (no AMIC or myocarditis). Results: Forty-five SLE patients (47±17 y, 80% female; 8 [18%] with AMIC and 7 [16%] with myocarditis) and 30 healthy controls (39±15 y, 60% female) were included. Patients with AMIC had higher T1 and T2 compared with controls (z-score 1.1±1.3 vs. 0±0.6, P=0.01 and 1.7±1.1 vs. 0±1.0, P<0.01, respectively) and lower values compared with those with myocarditis (3.7±1.6, P<0.01 and 4.0±2.0, P<0.01, respectively). T1 correlated negatively with AM treatment duration in patients without AMIC or myocarditis (r=−0.36, P=0.048) and positively in patients with AMIC (r=0.92, P=0.001). AM treatment duration did not correlate significantly with T1 in patients with myocarditis or with T2 in any group. Conclusions: The relationship between T1 and AM treatment duration differed between groups. Native T1 decreases with longer treatment in patients without AMIC or myocarditis, possibility due to glycosphingolipid accumulation. In patients with AMIC, increasing T1 with longer treatment could reflect fibrosis.

Purpose: To assess the association between interstitial lung abnormalities (ILAs) and worse outcome in patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19)-related pneumonia. Materials and Methods: The study included patients older than 18 years, who were admitted at the emergency department between February 29 and April 30, 2020 with findings of COVID-19 pneumonia at chest computed tomography (CT), with positive reverse-transcription polymerase chain reaction nasal-pharyngeal swab for SARS-CoV-2, and with the availability of prepandemic chest CT. Prepandemic CTs were reviewed for the presence of ILAs, categorized as fibrotic in cases with associated architectural distortion, bronchiectasis, or honeycombing. Worse outcome was defined as intensive care unit (ICU) admission or death. Cox proportional hazards regression analysis was used to test the association between ICU admission/death and preexisting ILAs. Results: The study included 147 patients (median age 73 y old; 95% CIs: 71-76-y old; 29% females). On prepandemic CTs, ILA were identified in 33/147 (22%) of the patients, 63% of which were fibrotic ILAs. Fibrotic ILAs were associated with higher risk of ICU admission or death in patients with COVID-19 pneumonia (hazard ratios: 2.73, 95% CIs: 1.50-4.97, P=0.001). Conclusions: In patients affected by COVID-19 pneumonia, preexisting fibrotic ILAs were an independent predictor of worse prognosis, with a 2.7 times increased risk of ICU admission or death. Chest CT scans obtained before the diagnosis of COVID-19 pneumonia should be carefully reviewed for the presence and characterization of ILAs.

Ischemic heart disease continues to be the leading cause of death and disability worldwide. For the diagnosis of ischemic heart disease, some form of cardiac stress test involving exercise or pharmacological stimulation continues to play an important role, despite advances within modalities like computer tomography for the noninvasive detection and characterization of epicardial coronary lesions. Among noninvasive stress imaging tests, cardiac magnetic resonance (CMR) combines several capabilities that are highly relevant for the diagnosis of ischemic heart disease: assessment of wall motion abnormalities, myocardial perfusion imaging, and depiction of replacement and interstitial fibrosis markers by late gadolinium enhancement techniques and T1 mapping. On top of these qualities, CMR is also well tolerated and safe in most clinical scenarios, including in the presence of cardiovascular implantable devices, while in the presence of renal disease, gadolinium-based contrast should only be used according to guidelines. CMR also offers outstanding viability assessment and prognostication of cardiovascular events. The last 2019 European Society of Cardiology guidelines for chronic coronary syndromes has positioned stress CMR as a class I noninvasive imaging technique for the diagnosis of coronary artery disease in symptomatic patients. In the present review, we present the current state-of-the-art assessment of myocardial ischemia by stress perfusion CMR, highlighting its advantages and current shortcomings. We discuss the safety, clinical, and cost-effectiveness aspects of gadolinium-based CMR-perfusion imaging for ischemic heart disease assessment.

Purpose: To evaluate the accuracy of a deep learning-based computer-aided detection (CAD) system in identifying active pulmonary tuberculosis on chest radiographs (CRs) of patients with positive interferon-gamma release assay (IGRA) results in different scenarios of clinical implementation. Materials and Methods: We collected the CRs of consecutive patients with positive IGRA results. Findings of active pulmonary tuberculosis on CRs were independently evaluated by the CAD and a thoracic radiologist, followed by interpretation using the CAD. Sensitivity and specificity were evaluated in different scenarios: (a) radiologists’ interpretation, (b) radiologists’ CAD-assisted interpretation, and (c) CAD-based prescreening (radiologists’ interpretation for positive CAD results only). We conducted a reader test to compare the accuracy of the CAD with those of 5 radiologists. Results: Among 1780 patients (men, 53.8%; median age, 56 y), 44 (2.5%) were diagnosed with active pulmonary tuberculosis. The CAD-assisted interpretation exhibited a higher sensitivity (81.8% vs. 72.7%; P=0.046) but lower specificity than the radiologists’ interpretation (84.1% vs. 85.7%; P<0.001). The CAD-based prescreening exhibited a higher specificity than the radiologists’ interpretation (88.8% vs. 85.7%; P<0.001) at the same sensitivity, with a workload reduction of 85.2% (1780 to 263). In the reader test, the CAD exhibited a higher sensitivity than radiologists (72.7% vs. 59.5%; P=0.005) at the same specificity (88.0%), and CAD-assisted interpretation significantly improved the sensitivity of radiologists’ interpretation (72.3%; P<0.001). Conclusions: For identifying active pulmonary tuberculosis among patients with positive IGRA results, deep learning-based CAD can enhance the sensitivity of interpretation. CAD-based prescreening may reduce the radiologists’ workload at an improved specificity.

Purpose: Shortened injection durations are not recommended in step-and-shoot coronary computed tomography angiography (CCTA). We aimed to evaluate the image quality of CCTA performed using bodyweight-adjusted iodinated contrast media (ICM) with different injection durations to generate an optimized ICM administration protocol to acquire convincible image quality in step-and-shoot CCTA. Materials and Methods: A total of 200 consecutive patients with suspected coronary artery disease (CAD) were enrolled in group A (N=50, 350 mgI/mL, bodyweight×0.8 mL/kg with a 13-s injection duration), group B (N=50, 350 mgI/mL, bodyweight×0.9 mL/kg with a 13-s injection duration), group C (N=50, 350 mgI/mL, bodyweight×0.8 mL/kg with a 12-s injection duration), and group D (N=50, 320 mgI/mL, bodyweight×0.8 mL/kg with a 13-s injection duration). Patient characteristics, ICM administration protocols, quantitative computed tomography (CT) value measurements, and qualitative image scores were analyzed and compared among the groups. Results: Groups A and D achieved the lowest ICM volume, saline volume, injection flow rate, and total iodine and iodine injection rates among the groups. All the CT values of the coronary arteries in all groups were >300 HU. All the observers’ average scores exceeded three points. In group A, the CT values showed significant positive correlation with the iodine injection rate (r=0.226, P<0.001), whereas the signal-to-noise ratio (r=−0.004, P=0.927) and contrast-to-noise ratio (r=−0.006, P=0.893) values were not. Conclusions: Bodyweight×0.8 mL/kg with a 13-second injection duration is a comprehensive option for step-and-shoot CCTA with improved image quality, and a 350 mgI/mL iodine concentration is preferred.

Purpose: To assess automated coronary artery calcium (CAC) and quantitative emphysema (percentage of low attenuation areas [%LAA]) for predicting mortality and lung cancer (LC) incidence in LC screening. To explore correlations between %LAA, CAC, and forced expiratory value in 1 second (FEV₁) and the discriminative ability of %LAA for airflow obstruction. Materials and Methods: Baseline low-dose computed tomography scans of the BioMILD trial were analyzed using an artificial intelligence software. Univariate and multivariate analyses were performed to estimate the predictive value of %LAA and CAC. Harrell C-statistic and time-dependent area under the curve (AUC) were reported for 3 nested models (Model_survey: age, sex, pack-years; Model_survey-LDCT: Model_survey plus %LAA plus CAC; Model_final: Model_survey-LDCT plus selected confounders). The correlations between %LAA, CAC, and FEV₁ and the discriminative ability of %LAA for airflow obstruction were tested using the Pearson correlation coefficient and AUC-receiver operating characteristic curve, respectively. Results: A total of 4098 volunteers were enrolled. %LAA and CAC independently predicted 6-year all-cause (Model_final hazard ratio [HR], 1.14 per %LAA interquartile range [IQR] increase [95% CI, 1.05-1.23], 2.13 for CAC ≥400 [95% CI, 1.36-3.28]), noncancer (Model_final HR, 1.25 per %LAA IQR increase [95% CI, 1.11-1.37], 3.22 for CAC ≥400 [95%CI, 1.62-6.39]), and cardiovascular (Model_final HR, 1.25 per %LAA IQR increase [95% CI, 1.00-1.46], 4.66 for CAC ≥400, [95% CI, 1.80-12.58]) mortality, with an increase in concordance probability in Model_survey-LDCT compared with Model_survey (P<0.05). No significant association with LC incidence was found after adjustments. Both biomarkers negatively correlated with FEV₁ (P<0.01). %LAA identified airflow obstruction with a moderate discriminative ability (AUC, 0.738). Conclusions: Automated CAC and %LAA added prognostic information to age, sex, and pack-years for predicting mortality but not LC incidence in an LC screening setting. Both biomarkers negatively correlated with FEV₁, with %LAA enabling the identification of airflow obstruction with moderate discriminative ability.

Purpose: To explore the role of quantitative plaque analysis and fractional flow reserve (CT-FFR) derived from coronary computed angiography (CCTA) in evaluating plaque progression (PP). Methods: A total of 248 consecutive patients who underwent serial CCTA examinations were enrolled. All patients’ images were analyzed quantitatively by plaque analysis software. The quantitative analysis indexes included diameter stenosis (%DS), plaque length, plaque volume (PV), calcified PV, noncalcified PV, minimum lumen area (MLA), and remodeling index (RI). PP is defined as PAV (percentage atheroma volume) change rate >1%. CT-FFR analysis was performed using the cFFR software. Results: A total of 76 patients (30.6%) and 172 patients (69.4%) were included in the PP group and non-PP group, respectively. Compared with the non-PP group, the PP group showed greater %DS, smaller MLA, larger PV and non-calcified PV, larger RI, and lower CT-FFR on baseline CCTA (all P<0.05). Logistic regression analysis showed that RI≥1.10 (odds ratio [OR]: 2.709, 95% CI: 1.447-5.072), and CT-FFR≤0.85 (OR: 5.079, 95% CI: 2.626-9.283) were independent predictors of PP. The model based on %DS, quantitative plaque features, and CT-FFR (area under the receiver-operating characteristics curve [AUC]=0.80, P<0.001) was significantly better than that based rarely on %DS (AUC=0.61, P=0.007) and that based on %DS and quantitative plaque characteristics (AUC=0.72, P<0.001). Conclusions: Quantitative plaque analysis and CT-FFR are helpful to identify PP. RI and CT-FFR are important predictors of PP. Compared with the prediction model only depending on %DS, plaque quantitative markers and CT-FFR can further improve the predictive performance of PP.