CT Pulmonary Angiography for Risk Stratification of Patients with Nonmassive Acute Pulmonary Embolism

Optimization of CT pulmonary angiography for pulmonary embolism using task-based image quality assessment and diagnostic reference levels: A multicentric study

PURPOSE

To establish size-specific diagnostic reference levels (DRLs) for pulmonary embolism (PE) based on patient CT examinations performed on 74 CT devices. To assess task-based image quality (IQ) for each device and to investigate the variability of dose and IQ across different CTs. To propose a dose/IQ optimization.

METHODS

1051 CT pulmonary angiography dose data were collected. DRLs were calculated as the 75th percentile of CT dose index (CTDI) for two patient categories based on the thoracic perimeters. IQ was assessed with two thoracic phantom sizes using local acquisition parameters and three other dose levels. The area under the ROC curve (AUC) of a 2 mm low perfused vessel was assessed with a non-prewhitening with eye-filter model observer. The optimal IQ-dose point was mathematically assessed from the relationship between IQ and dose.

RESULTS

The DRLs of CTDIvol were 6.4 mGy and 10 mGy for the two patient categories. 75th percentiles of phantom CTDIvol were 6.3 mGy and 10 mGy for the two phantom sizes with inter-quartile AUC values of 0.047 and 0.066, respectively. After the optimization, 75th percentiles of phantom CTDIvol decreased to 5.9 mGy and 7.55 mGy and the interquartile AUC values were reduced to 0.025 and 0.057 for the two phantom sizes.

CONCLUSION

DRLs for PE were proposed as a function of patient thoracic perimeters. This study highlights the variability in terms of dose and IQ. An optimization process can be started individually and lead to a harmonization of practice throughout multiple CT sites.

Does Adding the Pulmonary Infarction and Right Ventricle to Left Ventricle Diameter Ratio to the Qanadli Index (A Combined Qanadli Index) More Accurately, Predict Short-Term Mortality in Patients with Pulmonary Embolism?

Background  The Qanadli index can be used to assess the severity of pulmonary arterial involvement in patients with acute pulmonary embolism. However, it seems that considering pulmonary infarction and right ventricle/left ventricle (RV/LV) ratio along with this index (called the combined Qanadli index) can provide a more accurate view of changes in cardiovascular parameters in these patients and help predict mortality in a better manner. In this regard, we evaluated the ability of the combined Qanadli index versus the Qanadli index in predicting short-term mortality in patients with pulmonary embolism. Methods  This retrospective study enrolled 234 patients with acute pulmonary embolism. Patients were divided into two groups: those who expired in 30 days and who survived. Then they were evaluated by computed tomography angiography of pulmonary arteries. The RV/LV diameter ratio and also pulmonary artery obstruction index (PAOI) were calculated. The patient's computed tomography scans were reviewed for pulmonary infarction. By adding the RV/LV ratio and pulmonary infarction to PAOI, a new index called the modified Qanadli score was made. Univariable and multivariable logistic regression was done for finding predictors of mortality. Results  Nine cases (40%) of patients in the mortality group and 42 (20%) of survivors had ischemic heart disease and the difference was significantly meaningful. The mean Qanadli index in the mortality group was 16.8 ± 8.45 and in survivors was 8.3 ± 4.2. By adding the pulmonary infarction score and PAOI score to RV/LV ratio score, the odds ratio (OR) for predicting mortality increased significantly to 13 and 16, respectively, which were significantly meaningful. Based on our findings, the highest OR for predicting short-term mortality was obtained through a combined Qanadli index (PAOI score + pulmonary infarction score + RV/LV score) that was 17 in univariable and 18 in multivariable logistic regression analysis ( p -value = 0.015). Conclusion  The new combined Qanadli index has more ability than the Qanadli index and RV/LV ratio for predicting changes in cardiovascular parameters and short-term mortality in patients with pulmonary embolism.

Detection and quantification of pulmonary embolism with artificial intelligence: The SFR 2022 artificial intelligence data challenge

PURPOSE

In 2022, the French Society of Radiology together with the French Society of Thoracic Imaging and CentraleSupelec organized their 13th data challenge. The aim was to aid in the diagnosis of pulmonary embolism, by identifying the presence of pulmonary embolism and by estimating the ratio between right and left ventricular (RV/LV) diameters, and an arterial obstruction index (Qanadli's score) using artificial intelligence.

MATERIALS AND METHODS

The data challenge was composed of three tasks: the detection of pulmonary embolism, the RV/LV diameter ratio, and Qanadli's score. Sixteen centers all over France participated in the inclusion of the cases. A health data hosting certified web platform was established to facilitate the inclusion process of the anonymized CT examinations in compliance with general data protection regulation. CT pulmonary angiography images were collected. Each center provided the CT examinations with their annotations. A randomization process was established to pool the scans from different centers. Each team was required to have at least a radiologist, a data scientist, and an engineer. Data were provided in three batches to the teams, two for training and one for evaluation. The evaluation of the results was determined to rank the participants on the three tasks.

RESULTS

A total of 1268 CT examinations were collected from the 16 centers following the inclusion criteria. The dataset was split into three batches of 310, 580 and 378 C T examinations provided to the participants respectively on September 5, 2022, October 7, 2022 and October 9, 2022. Seventy percent of the data from each center were used for training, and 30% for the evaluation. Seven teams with a total of 48 participants including data scientists, researchers, radiologists and engineering students were registered for participation. The metrics chosen for evaluation included areas under receiver operating characteristic curves, specificity and sensitivity for the classification task, and the coefficient of determination r2 for the regression tasks. The winning team achieved an overall score of 0.784.

CONCLUSION

This multicenter study suggests that the use of artificial intelligence for the diagnosis of pulmonary embolism is possible on real data. Moreover, providing quantitative measures is mandatory for the interpretability of the results, and is of great aid to the radiologists especially in emergency settings.

Lobar pulmonary perfusion quantification with dual-energy CT angiography: Interlobar variability and relationship with regional clot burden in pulmonary embolism

Purpose

Semi-automated lobar segmentation tools enable an anatomical assessment of regional pulmonary perfusion with Dual-Energy CTA (DE-CTA). We aimed to quantify lobar pulmonary perfusion with DE-CTA, analyze the perfusion distribution among the pulmonary lobes in subjects without cardiopulmonary diseases and assess the correlation between lobar perfusion and regional endoluminal clots in patients with acute pulmonary embolism (PE).

Methods

We evaluated 151 consecutive subjects with suspected PE and without cardiopulmonary comorbidities. DE-CTA derived perfused blood volume (PBV) of each pulmonary lobe was measured applying a semi-automated lobar segmentation technique. In patients with PE, blood clot location was assessed, and CT-based vascular obstruction index of each lobe (CTOI_lobe) was calculated and classified into three groups: CTOI_lobe= 0, low CTOI_lobe (1–50%) and high CTOI_lobe (>50%).

Results

Among patients without PE (103/151, 68.2%), median lobar PBV was 13.7% (IQR 10.2–18.0%); the right middle lobe presented lower PBV when compared to all the other lobes (p < .001). In patients with PE (48/151, 31.8%), lobar PBV was 12.6% (IQR 9.6–15.7%), 13.7% (IQR 10.1–16.7%) and 6.5% (IQR 5.1–10.2%) in the lobes with CTOI_lobe= 0, low CTOI_lobe and high CTOI_lobe scores, respectively, with a significantly decreased PBV in the lobes with high CTOI_lobe score (p < .001). ROC analysis of lobar PBV for prediction of high CTOI_lobe score revealed AUC of 0.847 (95%CI 0.785–0.908).

Conclusion

Pulmonary perfusion was heterogeneously distributed along the pulmonary lobes in patients without cardiopulmonary diseases. In patients with PE, the lobes with high vascular obstruction score (CTOI_lobe> 50%) presented a decreased lobar perfusion.

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Semi-automated tools enable assessment of lobar perfusion with Dual-Energy CTA.

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The pulmonary perfusion is heterogeneously distributed along the pulmonary lobes.

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Lobar perfusion was decreased only in the lobes with high vascular obstruction index.

Acute Pulmonary Embolism in COVID-19: A Potential Connection between Venous Congestion and Thrombus Distribution

Background: Vascular abnormalities, including venous congestion (VC) and pulmonary embolism (PE), have been recognized as frequent COVID-19 imaging patterns and proposed as severity markers. However, the underlying pathophysiological mechanisms remain unclear. In this study, we aimed to characterize the relationship between VC, PE distribution, and alveolar opacities (AO). Methods: This multicenter observational registry (clinicaltrials.gov identifier NCT04824313) included 268 patients diagnosed with SARS-CoV-2 infection and subjected to contrast-enhanced CT between March and June 2020. Acute PE was diagnosed in 61 (22.8%) patients, including 17 females (27.9%), at a mean age of 61.7 ± 14.2 years. Demographic, laboratory, and outcome data were retrieved. We analyzed CT images at the segmental level regarding VC (qualitatively and quantitatively [diameter]), AO (semi-quantitatively as absent, <50%, or >50% involvement), clot location, and distribution related to VC and AO. Segments with vs. without PE were compared. Results: Out of 411 emboli, 82 (20%) were lobar or more proximal and 329 (80%) were segmental or subsegmental. Venous diameters were significantly higher in segments with AO (p = 0.031), unlike arteries (p = 0.138). At the segmental level, 77% of emboli were associated with VC. Overall, PE occurred in 28.2% of segments with AO vs. 21.8% without (p = 0.047). In the absence of VC, however, AO did not affect PE rates (p = 0.94). Conclusions: Vascular changes predominantly affected veins, and most PEs were located in segments with VC. In the absence of VC, AOs were not associated with the PE rate. VC might result from increased flow supported by the hypothesis of pulmonary arteriovenous anastomosis dysregulation as a relevant contributing factor.

Role of CT and MRI in Cardiac Emergencies

Current strategies for the evaluation of patients with chest pain have significantly changed thanks to the implemented potentiality of CT and MRI. The possible fatal consequences and high malpractice costs of missed acute coronary syndromes lead to unnecessary hospital admissions every year. CT provides consistent diagnostic support, mainly in suspected coronary disease in patients with a low or intermediate pre-test risk. Moreover, it can gain information in the case of cardiac involvement in pulmonary vascular obstructive disease. MRI, on the other hand, has a leading role in the condition of myocardial damage irrespective of the underlying inflammatory or stress related etiology. This article discusses how radiology techniques (CT and MRI) can impact the diagnostic workflow of the most common cardiac and vascular pathologies that are responsible for non-traumatic chest pain admissions to the Emergency Department.

Acute Pulmonary Embolism: Prognostic Role of Computed Tomography Pulmonary Angiography (CTPA)

Computed Tomography Pulmonary Angiography (CTPA) is considered the gold standard diagnostic technique in patients with suspected acute pulmonary embolism in emergency departments. Several studies have been conducted on the predictive value of CTPA on the outcomes of pulmonary embolism (PE). The purpose of this article is to provide an updated review of the literature reporting imaging parameters and quantitative CT scores to predict the severity of PE.

Vascular Abnormalities Detected with Chest CT in COVID-19: Spectrum, Association with Parenchymal Lesions, Cardiac Changes, and Correlation with Clinical Severity (COVID-CAVA Study)

Although vascular abnormalities are thought to affect coronavirus disease 2019 (COVID-19) patients' outcomes, they have not been thoroughly characterized in large series of unselected patients. The Swiss national registry coronavirus-associated vascular abnormalities (CAVA) is a multicentric cohort of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection who underwent a clinically indicated chest computed tomography (CT) aiming to assess the prevalence, severity, distribution, and prognostic value of vascular and non-vascular-related CT findings. Clinical outcomes, stratified as outpatient treatment, inpatient without mechanical ventilation, inpatient with mechanical ventilation, or death, will be correlated with CT and biological markers. The main objective is to assess the prevalence of cardiovascular abnormalities-including pulmonary embolism (PE), cardiac morphology, and vascular congestion. Secondary objectives include the predictive value of cardiovascular abnormalities in terms of disease severity and fatal outcome and the association of lung inflammation with vascular abnormalities at the segmental level. New quantitative approaches derived from CT imaging are developed and evaluated in this study. Patients with and without vascular abnormalities will be compared, which is supposed to provide insights into the prognostic role and potential impact of such signs on treatment strategy. Results are expected to enable the development of an integrative score combining both clinical data and imaging findings to predict outcomes.