A Simple and Safe Method for Checking the Position of Central Venous Catheters-A New and Reliable Threshold for Right Atrial Swirl Sign in Microbubbles Tests.

Background: Central venous catheters (CVCs) are indispensable tools in intensive care and emergency medicine. CVC malpositions still occur frequently and can cause various complications leading to increased patient mortality. A microbubbles test (MBT) can be used to confirm correct CVC positioning. However, there is serious doubt regarding whether the currently applied threshold of a 2 s push-to-bubbles time (PTB time) for rapid atrial swirl sign (RASS) in an MBT is reliable and accurate. The aim of the present study was to prove the quality of a new threshold: 1 s. Methods: Consecutive patients who were admitted to the intensive care unit (ICU) in a German neurological specialist hospital from 1 March 2021 to 20 July 2022 were enrolled. After ultrasound-guided CVC insertion, an MBT was performed, PTB time was measured, and RASS was interpreted. Additionally, a chest X-ray (CXR) was requested to check CVC position. Results: A total of 102 CVCs (98% jugular and 2% subclavian) were inserted in 102 patients (38% female and 62% male; median age: 66 years). Negative RASS (PTB time > 1 s) was observed in 2 out of 102 patients, resulting in an echocardiographic malposition rate of 2.0%. CXR confirmed the echocardiographic results. After correcting CVC position in the initially malpositioned CVCs, the PTB time was <1 s (positive RASS). The MBT protocol took about 0.5 min on average, while the CXR results were all available within 30 min. Sensitivity, specificity, and positive and negative predictive value were each 100% for the detection of CVC malpositions via an MBT using a threshold of 1 s compared to CXR. Conclusions: A new threshold of a 1 s PTB time for RASS in an MBT could detect CVC malpositions with excellent quality compared to CXR. Since the MBT was fast and safe and could be performed at the bedside, we propose that an MBT with the new and reliable threshold of 1 s should be routinely used in patient care.

The Transabdominal Lumbar Approach (TALA) for Robotic Renal Surgery-A Retrospective Single-Center Comparative Study and Step-by-Step Description of a Novel Approach.

The transperitoneal approach (TP) and the retroperitoneal approach (RP) are two common methods for performing nephrectomy or partial nephrectomy. However, both approaches face difficulties, such as trocar placement and limited working space (RP). TP is impaired in the case of dorsal tumors and dissection of the renal artery can be challenging due to the anatomic localization dorsally to the renal vein. A hybrid approach that combines both methods has been previously reported in a case series, but not evaluated systematically. This study proposes a modified hybrid approach, which we call the transabdominal lumbar approach (TALA), involving late robotic docking after elaborating the retroperitoneum using conventional laparoscopy. The study compares the last 20 consecutive patients who underwent RP and the last 20 patients who underwent TALA at our institution. The investigated variables include operative time and amount of blood loss, hospitalization duration, postoperative analgesia requirement, and postoperative complications. The study found no significant difference in operative time, blood loss, ischemia time, or hospital stay between the two groups. The TALA group had fewer complications regarding Clavien-Dindo category 3, but one complication of category 4. In Conclusion, TALA is a safe and promising approach that combines the advantages of RP and TP.

Evaluation of Image Quality of Overweight and Obese Patients in CT Using High Data Rate Detectors.

BACKGROUND/AIM: To evaluate the impact of high data rate and sampling frequency detector technology compared to standard scan equipment on the image quality in abdominal computed tomography (CT) of overweight and obese patients. PATIENTS AND METHODS: A total of 173 patients were retrospectively included in this study. Objective image quality in abdominal CT was evaluated using comparative analysis with new detector technology prior to market launch and standard CT equipment. Contrast noise ratio (CNR), image noise, volumetric computed tomography dose index (CTDIVol), and figures of merit (Q and Q1) were assessed for all patients. RESULTS: Image quality was superior in the new detector technology for all parameters evaluated. The dose dependent parameters Q and Q1 showed a significant difference (p<0.001). CONCLUSION: A significant increase in objective image quality could be demonstrated using a new generation detector setup with increased frequency transfer in abdominal CT of overweight patients.

Assessment of Image Quality in Chest CT With Precision Matrix and Increased Framing Rate Using Single Source CT: A Phantom Study.

BACKGROUND/AIM: The aim was to evaluate the effect of a combined precision matrix and high sampling rate on the delineation of anatomical structures and objective image quality in single source CT in a qualitative approach. MATERIALS AND METHODS: An anthropomorphic thoracic phantom was used to evaluate the objective image quality parameters, including image noise, noise power spectrum, image stepness and Q for different CT scanners including high/standard matrix and framing frequency setups. Scan parameters were standardized over all scanners. Additional subjective quality assessment was also performed. RESULTS: A linear mixed effects model was used to determine the effect of sampling rate and image matrix on objective image quality parameters. Noise power spectrum and image noise were significantly influenced by both framing frequency and image matrix. There were significant differences between high and standard frequency/matrix acquisitions. CONCLUSION: Higher framing frequency and image matrix allows for improved image noise texture and objective image quality in CT.

Towards universal comparability of pericoronary adipose tissue attenuation: a coronary computed tomography angiography phantom study.

OBJECTIVES: Different computed tomography (CT) scanners, variations in acquisition protocols, and technical parameters employed for image reconstruction may introduce bias in the analysis of pericoronary adipose tissue (PCAT) attenuation derived from coronary computed tomography angiography (CCTA). Therefore, the aim of this study was to establish the effect of tube voltage, measured as kilovoltage peak (kVp), and iterative reconstruction on PCAT mean attenuation (PCATMA). METHODS: Twelve healthy ex vivo porcine hearts were injected with iodine-enriched agar-agar to allow for ex vivo CCTA imaging on a 256-slice CT and a dual-source CT system. Images were acquired at tube voltages of 80, 100, 120, and 140 kVp and reconstructed by using both filtered back projection and iterative reconstruction algorithms. PCATMA was measured semi-automatically on CCTA images in the proximal segment of coronary arteries. RESULTS: The tube voltage showed a significant effect on PCATMA measurements on both the 256-slice CT scanner (p < 0.001) and the dual-source CT system (p = 0.013), resulting in higher attenuation values with increasing tube voltage. Similarly, the use of iterative reconstructions was associated with a significant increase of PCATMA (256-slice CT: p < 0.001 and dual-source CT: p = 0.014). Averaged conversion factors to correct PCATMA measurements for tube voltage other than 120 kVp were 1.267, 1.080 and 0.947 for 80, 100, and 140 kVp, respectively. CONCLUSION: PCATMA values are significantly affected by acquisition and reconstruction parameters. The same tube voltage and reconstruction type are recommended when PCAT attenuation is used in multicenter and longitudinal studies. KEY POINTS: • The tube voltage used for CCTA acquisition affects pericoronary adipose tissue attenuation, resulting in higher attenuation values of fat with increasing tube voltage. • Conversion factors for pericoronary adipose tissue attenuation values could be used to adjust for differences in attenuation between scans performed at different tube voltages. • In longitudinal CCTA studies employing pericoronary adipose tissue attenuation as imaging endpoint, it is recommended to maintain tube voltage and image reconstruction type constant across serial scans.

Development and In Vitro Assessment of a Novel Vacuum-Based Tissue-Holding Device for Laparoscopic and Robotic Kidney Cancer Operations.

In this paper, we describe the development and evaluation of a novel tissue-holding device (THD) for use during robotic-assisted laparoscopic partial nephrectomy. The THD is a vacuum-based apparatus made of either 3D-printed polyethylene or stainless steel. The proximal end connects to suction tubing routed outside the body, while the distal end is conically shaped and designed to firmly interface with the tumor. Device feasibility studies were performed on six porcine kidneys, two porcine livers, and two embalmed human cadavers. A Likert-scale rating was used to assess device setup, suction, and tissue handling. Additional tests were performed using the daVinci Xi® robotic system. Finally, the holding force of the THD was assessed using different standard vacuum systems and pressure settings. In porcine tissue, the device setup, tissue suction, and handling were rated as "good". THD insertion and removal was uncomplicated. In a simulated transabdominal approach on fixed human cadavers, the device setup, suction, and tissue handling were also rated as "good". No macroscopic tissue compromise or device deterioration was noted. The handling and holding abilities using the daVinci Xi® robotic system were also rated "good". The device was able to successfully hold over 300 g of tissue at a suction pressure of -600 mmHg. The preliminary evaluation of the THD demonstrated satisfactory results.

The Swiss Approach - feasibility of a national low-dose CT lung cancer screening program.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths in Switzerland. Despite this, there is no lung cancer screening program in the country. In the United States, low-dose computed tomography (LDCT) lung cancer screening is partially established and endorsed by guidelines. Moreover, evidence is growing that screening reduces lung cancer-related mortality and this was recently shown in a large European randomized controlled trial. Implementation of a lung cancer screening program, however, is challenging and depends on many country-specific factors. The goal of this article is to outline a potential Swiss lung cancer screening program. FRAMEWORK: An exhaustive literature review on international screening models as well as interviews and site visits with international experts were initiated. Furthermore, workshops and interviews with national experts and stakeholders were conducted to share experiences and to establish the basis for a national Swiss lung cancer screening program. SCREENING APPROACH: General practitioners, pulmonologists and the media should be part of the recruitment process. Decentralisation of the screening might lead to a higher adherence rate. To reduce stigmatisation, the screening should be integrated in a "lung health check". Standardisation and a common quality level are mandatory. The PLCOm2012 risk calculation model with a threshold of 1.5% risk for developing cancer in the next six years should be used in addition to established inclusion criteria. Biennial screening is preferred. LUNG RADS and NELSON+ are applied as classification models for lung nodules. CONCLUSION: Based on data from recent studies, literature research, a health technology assessment, the information gained from this project and a pilot study the Swiss Interest Group for lung cancer screening (CH-LSIG) recommends the timely introduction of a systematic lung cancer screening program in Switzerland. The final decision is for the Swiss Cancer Screening Committee to make.

Quantifying and Statistically Modeling Residual Pneumoperitoneum after Robotic-Assisted Laparoscopic Prostatectomy: A Prospective, Single-Center, Observational Study.

BACKGROUND: Laparoscopic surgery (LS) requires CO2 insufflation to establish the operative field. Patients with worsening pain post-operatively often undergo computed tomography (CT). CT is highly sensitive in detecting free air-the hallmark sign of a bowel injury. Yet, the clinical significance of free air is often confounded by residual CO2 and is not usually due to a visceral injury. The aim of this study was to attempt to quantify the residual pneumoperitoneum (RPP) after a robotic-assisted laparoscopic prostatectomy (RALP). METHODS: We prospectively enrolled patients who underwent RALP between August 2018 and January 2020. CT scans were performed on postoperative days (POD) 3, 5, and 7. To investigate potential factors influencing the quantity of RPP, correlation plots were made against common variables. RESULTS: In total, 31 patients with a mean age of 66 years (median 67, IQR 62-70.5) and mean BMI 26.59 (median 25.99, IQR: 24.06-29.24) underwent RALP during the study period. All patients had a relatively unremarkable post-operative course (30/31 with Clavien-Dindo class 0; 1/31 with class 2). After 3, 5, and 7 days, 3.2%, 6.4%, and 32.3% were completely without RPP, respectively. The mean RPP at 3 days was 37.6 mL (median 9.58 mL, max 247 mL, IQR 3.92-31.82 mL), whereas the mean RPP at 5 days was 19.85 mL (median 1.36 mL, max 220.77 mL, IQR 0.19-5.61 mL), and 7 days was 10.08 mL (median 0.09 mL, max 112.42 mL, IQR 0-1.5 mL). There was a significant correlation between RPP and obesity (p = 0.04665), in which higher BMIs resulted in lower initial insufflation volumes and lower RPP. CONCLUSIONS: This is the first study to systematically assess RPP after a standardized laparoscopic procedure using CT. Larger patients tend to have smaller residuals. Our data may help surgeons interpreting post-operative CTs in similar patient populations.

Analysis of Diagnostic Modalities in Hospital-admitted Patients Evaluated for COVID-19.

BACKGROUND/AIM: To assess the diagnostic performance of reverse transcriptase polymerase chain reaction (RT-PCR), low-dose chest computed tomography (CT), and serological testing, alone and in combinations, as well as routine inflammatory markers in patients evaluated for COVID-19 during the first wave in early 2020. PATIENTS AND METHODS: We retrospectively analyzed data of all patients who were admitted to the emergency department due to fever and/or respiratory symptoms. CT scans were rated using the COVID-19 Reporting and Data System (CO-RADS) suspicion score. True disease status (COVID-19 - positive vs. negative) was adjudicated by two independent clinicians. Receiver-operating characteristic curves and areas under the curves were calculated for inflammatory markers. Sensitivities and specificities were calculated for RT-PCR, CT, and serology alone, as well as the combinations of RT-PCR+CT, RT-PCR+serology, CT+serology, and all three modalities. RESULTS: Of 221 patients with a median age of 72 years, 113 were classified as COVID-19 positive. Among 180 patients from which data on CT and RT-PCR were available, RT-PCR had the highest sensitivity to detect COVID-19 (0.87; 95%CI=0.78-0.93). Notably, the addition of CT in the analysis increased sensitivity to 0.89 (95%CI=0.8-0.94), but lowered specificity from 1 (95%CI=0.96-1) to 0.9 (95%CI=0.83-0.95). The combination of RT-PCR, CT and serology (n=60 patients with complete dataset) yielded a sensitivity of 0.83 (95%CI=0.61-0.94) and specificity of 0.86 (95%CI=0.72-0.93). CONCLUSION: RT-PCR was the best single test in patients evaluated for COVID-19. Conversely, the routine performance of chest CT adds little sensitivity and decreases specificity.

Influence of Radiation Dose, Photon Energy, and Reconstruction Kernel on rho/z Analysis in Spectral Computer Tomography: A Phantom Study.

BACKGROUND/AIM: The effective atomic number (Zeff) and electron density relative to water (ρe or Rho) of elements can be derived in dual-energy computed tomography (DECT). The aim of this phantom study was to investigate the effect of different photon energies, radiation doses, and reconstruction kernels on Zeff and Rho measured in DECT. MATERIALS AND METHODS: An anthropomorphic head phantom including five probes of known composition was scanned under three tube-voltage combinations in DECT: Sn140/100 kV, 140/80 kV and Sn140/80 kV with incremented radiation doses. Raw data were reconstructed with four reconstruction kernels (I30, I40, I50, and I70). Rho and Zeff were measured for each probe for all possible combinations of scan and reconstruction parameters. RESULTS: DECT-based Rho and Zeff closely approached the reference values with a mean and maximum error of 1.7% and 6.8%, respectively. Rho was lower for 140/80 kV compared with Sn140/100 kV and Sn140/80 kV with differences being 0.009. Zeff differed among all tube voltages with the most prominent difference being 0.28 between 140/80 kV and Sn140/100 kV. Zeff was lower in I70 compared with those of I30 and I40 with a difference of 0.07. Varying radiation dose yielded a variation of 0.0002 in Rho and 0.03 in Z, both considered negligible in practice. CONCLUSION: DECT comprises a feasible method for the extraction of material-specific information. Slight variations should be taken into account when different radiation doses, photon energies, and kernels are applied; however, they are considered small and in practice not crucial for an effective tissue differentiation.

The Role of New Technologies in the Diagnosis and Surveillance of Non-Muscle Invasive Bladder Carcinoma: A Prospective, Double-Blinded, Monocentric Study of the XPERT© Bladder Cancer Monitor and Narrow Band Imaging© Cystoscopy.

Follow-up is essential for the early detection of recurrent non-muscle invasive bladder cancers (NMIBC). This study investigates the clinical relevance of new diagnostic tools such as an mRNA-based urine test (XPERT© Bladder Cancer Monitor, XBCM) and Narrow Band Imaging© (NBI) and compares them with the established follow-up diagnostics (white-light cystoscopy (WLC) and urine cytology). This was a prospective, double-blind, single-center study that involved patients undergoing NMIBC screening at a tertiary care center. Enrollment occurred between January 2018 and March 2020. In addition to standard care (WLC, cytology, and ultrasound), patients underwent XBCM urine testing and NBI cystoscopy. In total, 301 WLCs were performed; through this, 49 patients demonstrated NMIBC recurrence. NBI cystoscopy was congruent with WLC in all patients. Cytology showed a sensitivity (SE) and specificity (SP) of 27% and 97% (PPV: 65%; NPV 87%), respectively, whereas XBCM showed SE and SP of 58% and 89%, respectively (PPV: 51%; NPV: 92%; AUC: 0.79 (0.716-0.871)). Subgroup analysis showed improved SE and similar SP (PPV, NPV) for high grade (HG) recurrence, with a SE of 74% and SP of 89% (39%, 97%). NBI cystoscopy does not necessarily provide additional benefit over standard WLC. However, the XBCM may provide better SE and a diagnostic advantage in instances of HG disease recurrence.

Quantifying image quality in chest computed tomography angiography: Evaluation of different contrast-to-noise ratio measurement methods.

BACKGROUND: Contrast-to-noise ratio is used to objectively evaluate image quality in chest computed tomography angiography (CTA). Different authors define and measure contrast-to-noise ratio using different methods. PURPOSE: To summarize and evaluate the different contrast-to-noise ratio calculation formulas in the current literature. MATERIAL AND METHODS: A systematic review of the recent literature for studies using contrast-to-noise ratio was performed. Contrast-to-noise ratio measurement methods reported by the different authors were recorded and reproduced in three patients who underwent chest CTA in our department for exploring variations among the different measurement methods. RESULTS: The search resulted in 109 articles, of which 26 were included. The studies involved 69 different measurements and overall, three different formula patterns. In all three, aorta and pulmonary arteries comprised the objects of interest in the numerator. In the denominator, standard deviation of the attenuation of the object of interest itself or of another background were used to reflect image noise. Some authors averaged the ratio values at different levels to obtain global ratio values. Using the object of interest itself for image noise calculation in the denominator compared to the usage of another background caused the most prominent variances of contrast-to-noise ratio between the two different protocols used for the reproduction of the measurements. CONCLUSION: We recommend using the standard deviation of the attenuation of a background indicator as image noise rather than the object of interest itself for more reliable and comparative values. Global contrast-to-noise ratios based on averaging the values of different measurement levels should be avoided.

Detection and characterization of COVID-19 findings in chest CT: Feasibility and applicability of an AI-based software tool.

ABSTRACT: The COVID-19 pandemic has challenged institutions' diagnostic processes worldwide. The aim of this study was to assess the feasibility of an artificial intelligence (AI)-based software tool that automatically evaluates chest computed tomography for findings of suspected COVID-19.Two groups were retrospectively evaluated for COVID-19-associated ground glass opacities of the lungs (group A: real-time polymerase chain reaction positive COVID patients, n = 108; group B: asymptomatic pre-operative group, n = 88). The performance of an AI-based software assessment tool for detection of COVID-associated abnormalities was compared with human evaluation based on COVID-19 reporting and data system (CO-RADS) scores performed by 3 readers.All evaluated variables of the AI-based assessment showed significant differences between the 2 groups (P < .01). The inter-reader reliability of CO-RADS scoring was 0.87. The CO-RADS scores were substantially higher in group A (mean 4.28) than group B (mean 1.50). The difference between CO-RADS scoring and AI assessment was statistically significant for all variables but showed good correlation with the clinical context of the CO-RADS score. AI allowed to predict COVID positive cases with an accuracy of 0.94.The evaluated AI-based algorithm detects COVID-19-associated findings with high sensitivity and may support radiologic workflows during the pandemic.

The classification of renal stones by gratings-based dark-field radiography.

INTRODUCTION: Occurrence of urinary calculi is a common medical condition. Since treatment and prevention measures depend on the type of stone found, reliable diagnostic tools are required. Dual energy computed tomography (CT) allows for rough classification of the stones found. After extraction, stone composition can be confirmed by laboratory analysis.We investigated to which degree gratings-based X-ray interferometry, which can measure attenuation, refraction and scattering (dark-field) properties of samples, allows for the discrimination of urinary stone type by calculating the ratio (R) of attenuation and scattering signals. MATERIAL AND METHODS: In an experimental setup we investigated 322 renal stone fragments from 96 patients which were extracted during routine clinical practice. Laboratory analysis showed the chemical composition of the urinary stones.These were correlated with dark field analysis of the stone samples. Measurements were performed on a X-rays gratings interferometer prototype. The attenuation, refraction and scattering signals were measured and the R-value calculated. RESULTS: The spread of R-values of a given type of calculi is large, reducing the specificity of the method. Only uric acid stones can reliably be distinguished (sensitivity of 0.86 at a specificity of 0.9) from the other stones. CONCLUSIONS: Gratings-based dark-field imaging is a non-destructive and potentially non-invasive technique that allows to discriminate between uric acid and non-uric acid stones, which from a clinical point of view represents by far the most important question for stone treatment.

Right ventricular thrombus, a challenge in imaging diagnostics: a case series.

BACKGROUND: Presence of right ventricular thrombus (RVT) is a rare but life-threatening condition, thus immediate diagnosis and therapy are mandatory. Unfortunately, detection and distinction from intraventricular tumour masses or vegetations represent a complex task. Furthermore, consecutive therapy is principally led by clinical presentation without considering morphological features of the thrombus. Current literature suggests a multimodal non-invasive imaging approach. In this article, we discuss the role of cardiac magnetic resonance imaging (CMR) for the detection of RVT in patients with pulmonary embolism (PE). We consider the relatively expensive and not broadly available imaging procedure and weigh it up to its assumed high sensitivity, specificity, and importance for differential diagnosis and therapeutic decision-making. CASE SUMMARY: In this case series, we report three cases of RVT with concomitant PE, whereof two were missed during routine cardiac workup by transthoracic echocardiography and computer tomography. Cardiac magnetic resonance imaging led to detection and further characterization of the thrombi in both cases. CONCLUSIONS: Cardiac magnetic resonance imaging reliably detects and characterizes RVT, even under unfavourable conditions for echocardiography such as arrhythmia, adiposity, or in posterior position of RVT. Obtained information could facilitate the choice of therapeutic approach (anticoagulation vs. systemic lysis vs. surgical thrombectomy). Future risk stratification scores will promote cost-effective use of CMR.

Influence of Radiation Dose and Reconstruction Kernel on Fat Fraction Analysis in Dual-energy CT: A Phantom Study.

BACKGROUND/AIM: The quantitative evaluation of fat tissue, mainly for the determination of liver steatosis, is possible by using dual-energy computed tomography. Different photon energy acquisitions allow for estimation of attenuation coefficients. The effect of variation in radiation doses and reconstruction kernels on fat fraction estimation was investigated. MATERIALS AND METHODS: A six-probe-phantom with fat concentrations of 0%, 20%, 40%, 60%, 80%, and 100% were scanned in Sn140/100 kV with radiation doses ranging between 20 and 200 mAs before and after calibration. Images were reconstructed using iterative kernels (I26,Q30,I70). RESULTS: Fat fractions measured in dual-energy computed tomography (DECT) were consistent with the 20%-stepwise varying actual concentrations. Variation in radiation dose resulted in 3.1% variation of fat fraction. Softer reconstruction kernel (I26) underestimated the fat fraction (-9.1%), while quantitative (Q30) and sharper kernel (I70) overestimated fat fraction (10,8% and 13,1, respectively). CONCLUSION: The fat fraction in DECT approaches the actual fat concentration when calibrated to the reconstruction kerneö. Variation of radiation dose caused an acceptable 3% variation.

Spectral Properties of Abdominal Tissues on Dual-energy Computed Tomography and the Effects of Contrast Agent.

BACKGROUND/AIM: Multiparametric dual energy comptuted tomography (CT) imaging allows for multidimensional tissue characterization beyond the measurement of Hounsfield units. The purpose of this study was to evaluate multiple imaging parameters for different abdominal organs in dual energy CT (DECT) and analyze the effects of the contrast agent on these different parameters and provide normal values for characterization of parenchymatous organs. PATIENTS AND METHODS: This retrospective analysis included a total of 484 standardized DECT scans of the abdomen. Hounsfield Units (HU), rho (electron density relative to water), Zeff (effective atomic number) and FF (fat fraction) were evaluated for liver, spleen, kidney, muscle, fat-tissue. Independent generalized estimation equation models were fitted. RESULTS: In DECT imaging there is only little difference in mean HUmixed for parenchymatous abdominal organs. Analysis including Zeff, rho and FF allows for better discrimination while a large overlap remains for liver, spleen and muscle. Including multidimensional analysis and the effects of contrast medium further enhances tissue characterization. Small differences remain for liver and spleen. CONCLUSION: Organ characterization using multiparametric dual energy CT analysis is possible. An increased number of parameters obtained from DECT improves organ characterization. To our knowledge this is the first attempt to provide normal values for characterization of parenchymatous organs.

Preoperative chest computed tomography in emergency surgery during COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic challenges the recommendations for patients' preoperative assessment for preventing severe acute respiratory syndrome coronavirus type 2 transmission and COVID-19-associated postoperative complications and morbidities. PURPOSE: To evaluate the contribution of chest computed tomography for preoperatively assessing patients who are not suspected of being infected with COVID-19 at the time of referral. METHODS: Candidates for emergency surgery screened via chest computed tomography from 8 to 27 April 2020 were retrospectively evaluated. Computed tomography images were analysed for the presence of COVID-19-associated intrapulmonary changes. When applicable, laboratory and recorded clinical symptoms were extracted. RESULTS: Eighty-eight patients underwent preoperative chest computed tomography; 24% were rated as moderately suspicious and 11% as highly suspicious on computed tomography. Subsequent reverse transcription polymerase chain reaction (RT-PCR) was performed for seven patients, all of whom tested negative for COVID-19. Seven patients showed COVID-19-associated clinical symptoms, and most were classified as being mildly to moderately severe as per the clinical classification grading system. Only one case was severe. Four cases underwent RT-PCR with negative results. CONCLUSION: In a cohort without clinical suspicion of COVID-19 infection upon referral, preoperative computed tomography during the COVID-19 pandemic can yield a high suspicion of infection, even if the patient lacks clinical symptoms and is RT-PCR-negative. No recommendations can be made based on our results but contribute to the debate.

Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings.

OBJECTIVE: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. MATERIALS AND METHODS: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]). Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. Additionally, six laboratory findings indicating inflammation and cellular damage were considered. Differences in CT metrics, laboratory findings, and demographics between the patient management groups were assessed. The potential of these parameters to predict patients' needs for intensive care (yes/no) was analyzed using logistic regression and receiver operating characteristic curves. Internal and external validity were assessed using 109 independent chest CT scans. RESULTS: While demographic parameters alone (sex and age) were not sufficient to predict ICU management status, both CT metrics alone (including both pulmonary and cardiovascular metrics; area under the curve [AUC] = 0.88; 95% confidence interval [CI] = 0.79-0.97) and laboratory findings alone (C-reactive protein, lactate dehydrogenase, white blood cell count, and albumin; AUC = 0.86; 95% CI = 0.77-0.94) were good classifiers. Excellent performance was achieved by a combination of demographic parameters, CT metrics, and laboratory findings (AUC = 0.91; 95% CI = 0.85-0.98). Application of a model that combined both pulmonary CT metrics and demographic parameters on a dataset from another hospital indicated its external validity (AUC = 0.77; 95% CI = 0.66-0.88). CONCLUSION: Chest CT of patients with COVID-19 contains valuable information that can be accessed using automated image analysis. These metrics are useful for the prediction of patient management.