Purpose: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is regarded as a multisystemic disease. Patients with preexisting cardiovascular disease have an increased risk for a more severe disease course. This study aimed to investigate if a higher degree of coronary artery calcifications (CAC) on a standard chest computed tomography (CT) scan in mechanically ventilated patients was associated with a more severe multiorgan failure over time. Materials and Methods: All mechanically ventilated intensive care unit patients with SARS-CoV-2 infection who underwent a chest CT were prospectively included. CT was used to establish the extent of CAC using a semiquantitative grading system. We categorized patients into 3 sex-specific tertiles of CAC: lowest, intermediate, and highest CAC score. Daily, the Sequential Organ Failure Assessment (SOFA) scores were collected to evaluate organ failure over time. Linear mixed-effects regression was used to investigate differences in SOFA scores between tertiles. The models were adjusted for age, sex, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, cardiovascular risk factors, and chronic liver, lung, and renal disease. Results: In all, 71 patients were included. Patients in the highest CAC tertile had, on average, over time, 1.8 (0.5-3.1) points higher SOFA score, compared with the lowest CAC tertile (P=0.005). This association remained significant after adjustment for age, sex, and APACHE II score (1.4 [0.1-2.7], P=0.042) and clinically relevant after adjustment for cardiovascular risk factors (1.3 [0.0-2.7], P=0.06) and chronic diseases (1.3 [−0.2 to 2.7], P=0.085). Conclusion: A greater extent of CAC is associated with a more severe multiorgan failure in mechanically ventilated coronavirus disease 2019 patients.

Background: Endoscopic lung volume reduction (ELVR) using one-way endobronchial valves is a technique to reduce hyperinflation in patients with severe emphysema by inducing collapse of a severely destroyed pulmonary lobe. Patient selection is mainly based on evaluation of emphysema severity on high-resolution computed tomography and evaluation of lung perfusion with perfusion scintigraphy. Dual-energy contrast-enhanced CT scans may be useful for perfusion assessment in emphysema but has not been compared against perfusion scintigraphy. Aims: The aim of the study was to compare perfusion distribution assessed with dual-energy contrast-enhanced computed tomography and perfusion scintigraphy. Material and Methods: Forty consecutive patients with severe emphysema, who were screened for ELVR, were included. Perfusion was assessed with 99mTc perfusion scintigraphy and using the iodine map calculated from the dual-energy contrast-enhanced CT scans. Perfusion distribution was calculated as usually for the upper, middle, and lower thirds of both lungs with the planar technique and the iodine overlay. Results: Perfusion distribution between the right and left lung showed good correlation (r = 0.8). The limits of agreement of the mean absolute difference in percentage perfusion per region of interest were 0.75–5.6%. The upper lobes showed more severe perfusion reduction than the lower lobes. Mean difference in measured pulmonary perfusion ranged from −2.8% to 2.3%. Lower limit of agreement ranged from −8.9% to 4.6% and upper limit was 3.3–10.0%. Conclusion: Quantification of perfusion distribution using planar 99mTc perfusion scintigraphy and iodine overlays calculated from dual-energy contrast-enhanced CTs correlates well with acceptable variability.

Hybrid PET-MRI systems are being used more frequently. One of the drawbacks of PET-MRI imaging is its inferiority in detecting lung nodules, so it is often combined with a computed tomography (CT) of the chest. However, chest CT often detects additional, indeterminate lung nodules. The objective of this study was to assess the sensitivity of detecting metastatic versus indeterminate nodules with PET-MRI compared to chest CT. A total of 328 patients were included. All patients had a PET/MRI whole-body scan for (re)staging of cancer combined with an unenhanced chest CT performed at our center between 2014 and 2020. Patients had at least a two-year follow-up. Six percent of the patients had lung metastases at initial staging. The sensitivity and specificity of PET-MRI for detecting lung metastases were 85% and 100%, respectively. The incidence of indeterminate lung nodules on chest CT was 30%. The sensitivity of PET-MRI to detect indeterminate lung nodules was poor (23.0%). The average size of the indeterminate lung nodules detected on PET-MRI was 7 ± 4 mm, and the missed indeterminate nodules on PET-MRI were 4 ± 1 mm (p < 0.001). The detection of metastatic lung nodules is fairly good with PET-MRI, whereas the sensitivity of PET-MRI for detecting indeterminate lung nodules is size-dependent. This may be an advantage, limiting unnecessary follow-up of small, indeterminate lung nodules while adequately detecting metastases.

Background/Objectives: The objective of this study is to evaluate the performance of the traditional age/smoking criteria and existing risk prediction models in selecting high-risk populations for lung cancer screening from a Western European general population. Methods: Baseline data from the Dutch population-based Lifelines cohort, collected between 2006 and 2013, were linked to the Dutch cancer registry to confirm lung cancer diagnoses. Five-year lung cancer risk was estimated based on traditional age/smoking criteria (NLST, NELSON, SPSTF-2021) and risk prediction models (LLPv2, PLCOm2012, Hoggart, Bach and Shanghai-LCM). For every strategy, the number of individuals eligible was determined, and total lung cancer cases in the eligible groups versus the ineligible groups were calculated. Results: Among 139,120 participants (aged ≥18 years), 218 (0.2%) developed lung cancer within five years. Age/smoking criteria identified 2161–6295 (1.6–4.5%) participants as eligible, comprising 62–92 (28.4–42.2%) lung cancer cases. Risk prediction models identified 2372–4315 (1.7–3.1%) participants as eligible, comprising 40–85 (18.4–38.9%) lung cancer cases. Among lung cancers in ineligible groups, 46.2–59.6% occurred in individuals who formerly smoked, and 28.7–39.3% occurred in individuals who currently smoke. Additionally, 41.2–70.0% of lung cancer cases in ineligible groups were in individuals younger than 50, and 44.3–72.3% in individuals who had quit smoking > 15 years prior to diagnosis. Conclusions: In a Western European population, current lung cancer screening selection criteria resulted in identifying only 18–42% of lung cancer cases. Cases in ineligible groups predominantly concern individuals who currently smoke and are below the threshold age and individuals who quit smoking > 15 years ago, highlighting the opportunity for more personalized risk-based screening strategies to increase lung cancer detection.