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1.
Res Diagn Interv Imaging ; 4: 100018, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2132214

ABSTRACT

Objectives: We evaluated the contribution of lung lesion quantification on chest CT using a clinical Artificial Intelligence (AI) software in predicting death and intensive care units (ICU) admission for COVID-19 patients. Methods: For 349 patients with positive COVID-19-PCR test that underwent a chest CT scan at admittance or during hospitalization, we applied the AI for lung and lung lesion segmentation to obtain lesion volume (LV), and LV/Total Lung Volume (TLV) ratio. ROC analysis was used to extract the best CT criterion in predicting death and ICU admission. Two prognostic models using multivariate logistic regressions were constructed to predict each outcome and were compared using AUC values. The first model ("Clinical") was based on patients' characteristics and clinical symptoms only. The second model ("Clinical+LV/TLV") included also the best CT criterion. Results: LV/TLV ratio demonstrated best performance for both outcomes; AUC of 67.8% (95% CI: 59.5 - 76.1) and 81.1% (95% CI: 75.7 - 86.5) respectively. Regarding death prediction, AUC values were 76.2% (95% CI: 69.9 - 82.6) and 79.9% (95%IC: 74.4 - 85.5) for the "Clinical" and the "Clinical+LV/TLV" models respectively, showing significant performance increase (+ 3.7%; p-value<0.001) when adding LV/TLV ratio. Similarly, for ICU admission prediction, AUC values were 74.9% (IC 95%: 69.2 - 80.6) and 84.8% (IC 95%: 80.4 - 89.2) respectively corresponding to significant performance increase (+ 10%: p-value<0.001). Conclusions: Using a clinical AI software to quantify the COVID-19 lung involvement on chest CT, combined with clinical variables, allows better prediction of death and ICU admission.

2.
Diagn Interv Imaging ; 102(5): 305-312, 2021 May.
Article in English | MEDLINE | ID: covidwho-1237673

ABSTRACT

PURPOSE: The purpose of this study was to characterize the technical capabilities and feasibility of a large field-of-view clinical spectral photon-counting computed tomography (SPCCT) prototype for high-resolution (HR) lung imaging. MATERIALS AND METHODS: Measurement of modulation transfer function (MTF) and acquisition of a line pairs phantom were performed. An anthropomorphic lung nodule phantom was scanned with standard (120kVp, 62mAs), low (120kVp, 11mAs), and ultra-low (80kVp, 3mAs) radiation doses. A human volunteer underwent standard (120kVp, 63mAs) and low (120kVp, 11mAs) dose scans after approval by the ethics committee. HR images were reconstructed with 1024 matrix, 300mm field of view and 0.25mm slice thickness using a filtered-back projection (FBP) and two levels of iterative reconstruction (iDose 5 and 9). The conspicuity and sharpness of various lung structures (distal airways, vessels, fissures and proximal bronchial wall), image noise, and overall image quality were independently analyzed by three radiologists and compared to a previous HR lung CT examination of the same volunteer performed with a conventional CT equipped with energy integrating detectors (120kVp, 10mAs, FBP). RESULTS: Ten percent MTF was measured at 22.3lp/cm with a cut-off at 31lp/cm. Up to 28lp/cm were depicted. While mixed and solid nodules were easily depicted on standard and low-dose phantom images, higher iDose levels and slice thicknesses (1mm) were needed to visualize ground-glass components on ultra-low-dose images. Standard dose SPCCT images of in vivo lung structures were of greater conspicuity and sharpness, with greater overall image quality, and similar image noise (despite a flux reduction of 23%) to conventional CT images. Low-dose SPCCT images were of greater or similar conspicuity and sharpness, similar overall image quality, and lower but acceptable image noise (despite a flux reduction of 89%). CONCLUSIONS: A large field-of-view SPCCT prototype demonstrates HR technical capabilities and high image quality for high resolution lung CT in human.


Subject(s)
Lung , Tomography, X-Ray Computed , Algorithms , Feasibility Studies , Humans , Image Processing, Computer-Assisted , Lung/diagnostic imaging , Phantoms, Imaging , Radiation Dosage , Radiographic Image Interpretation, Computer-Assisted
4.
Eur Radiol ; 31(2): 795-803, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-722374

ABSTRACT

OBJECTIVES: To assess the diagnostic performances of chest CT for triage of patients in multiple emergency departments during COVID-19 epidemic, in comparison with reverse transcription polymerase chain reaction (RT-PCR) test. METHOD: From March 3 to April 4, 2020, 694 consecutive patients from three emergency departments of a large university hospital, for which a hospitalization was planned whatever the reasons, i.e., COVID- or non-COVID-related, underwent a chest CT and one or several RT-PCR tests. Chest CTs were rated as "Surely COVID+," "Possible COVID+," or "COVID-" by experienced radiologists. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using the final RT-PCR test as standard of reference. The delays for CT reports and RT-PCR results were recorded and compared. RESULTS: Among the 694 patients, 287 were positive on the final RT-PCR exam. Concerning the 694 chest CT, 308 were rated as "Surely COVID+", 34 as "Possible COVID+," and 352 as "COVID-." When considering only the "Surely COVID+" CT as positive, accuracy, sensitivity, specificity, PPV, and NPV reached 88.9%, 90.2%, 88%, 84.1%, and 92.7%, respectively, with respect to final RT-PCR test. The mean delay for CT reports was three times shorter than for RT-PCR results (187 ± 148 min versus 573 ± 327 min, p < 0.0001). CONCLUSION: During COVID-19 epidemic phase, chest CT is a rapid and most probably an adequately reliable tool to refer patients requiring hospitalization to the COVID+ or COVID- hospital units, when response times for virological tests are too long. KEY POINTS: • In a large university hospital in Lyon, France, the accuracy, sensitivity, specificity, PPV, and NPV of chest CT for COVID-19 reached 88.9%, 90.2%, 88%, 84.1%, and 92.7%, respectively, using RT-PCR as standard of reference. • The mean delay for CT reports was three times shorter than for RT-PCR results (187 ± 148 min versus 573 ± 327 min, p < 0.0001). • Due to high accuracy of chest CT for COVID-19 and shorter time for CT reports than RT-PCR results, chest CT can be used to orient patients suspected to be positive towards the COVID+ unit to decrease congestion in the emergency departments.


Subject(s)
COVID-19/diagnostic imaging , Triage , Aged , Aged, 80 and over , COVID-19/epidemiology , Emergency Service, Hospital , Epidemics , Female , France , Hospitals, University , Humans , Male , Predictive Value of Tests , SARS-CoV-2 , Time Factors , Tomography, X-Ray Computed
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