Negative Chest CT Research Articles

Long COVID in Young Patients: Impact on Lung Volume Evaluated Using Multidetector CT.

To evaluate using quantitative analysis on chest CT images a possible lung volume reduction in Long COVID patients who complain mild respiratory symptoms, with chest CT negative for inflammatory findings. CT images of patients from 18 to 40 years old who underwent chest CT scan at our institution were analyzed retrospectively, using AwServer Thoracic VCAR software for a quantitative study. Exclusion criteria were inflammatory findings at CT, previous lung surgery, lung cancer, and breath artifacts that invalidate the quality of images. Patients were divided into two groups: in the first one ("post-COVID") were patients who had previous SARS-CoV-2 infection, confirmed by an RT-PCR, who underwent chest CT from 3 to 6 months after their negativization for long COVID symptoms; in the control group ("non-COVID"), were enrolled patients who underwent a chest CT scan from January 2018 to December 2019, before the spread of COVID in Italy. Our final population included 154 TC, 77 post-COVID patients (mean age 33 ± 6) and 77 non-COVID patients (mean age 33 ± 4.9). Non statistical significative differences were obtained between groups in terms of age, sex, and other characteristics that affect total lung capacity such as obesity, thoracic malformations, and smoking habit. Mean values of the total lung volume (TV), right-lung volume (RV), and left-lung volume (LV) in the post-COVID group compared with non-COVID group were, respectively: 5.25 ± 0.25 L vs. 5.72 ± 0.26 L (p = 0.01); 2.76 ± 0.14 L vs. 3 ± 0.14 L (p = 0.01); 2.48 ± 0.12 L vs. 2.72 ± 0.12 L (p = 0.01). In patients with symptoms suggesting Long COVID and negative chest CT macroscopic findings, quantitative volume analysis demonstrated a mean value of reduction in lung volume of 10% compared to patients of the same age who never had COVID. A chest CT negative for inflammatory findings may induce clinicians to attribute Long COVID mild respiratory symptoms to anxiety, especially in young patients. Our study brings us beyond appearances and beyond the classic radiological signs, introducing a quantitative evaluation of lung volumes in these patients. It is hard to establish to what extent this finding may contribute to Long COVID symptoms, but this is another step to gain a wider knowledge of the potential long-term effects caused by this new virus.

Value of Thoracic CT in Blunt Trauma Patients With High Glasgow Coma Scale and Low Injury Severity Scale.

To determine the value of ordering a routine chest CT (CCT) in patients with blunt trauma presenting to the emergency department with a high GCS and low ISS, we retrospectively collected patient data including CT scan results, when physical examination and initial chest X-ray were normal in the trauma bay area. A retrospective data collection of 901 consecutive blunt trauma patients seen in the ED between 2017 and 2019 was analyzed. Data included physical examination, age, gender, current use of anticoagulation therapy, comorbid conditions, as well as the result of radiologic images, hospital length of stay, surgical intervention, and mortality. The patients were divided into two groups: group one (patients with negative physical examination; chest x-ray and CT) and group 2 (negative physical examination, positive or negative chest x-ray, and positive CT). Statistical analysis was performed using student's t-test and chi-square test. Of the 901 patients there were 489 (54%) males and 412 (46%) females with a mean age of 56 years. There were 461 patients who had a physical examination, chest x-ray, abdominal and CCT done. Group one included 442 (96%) patients, with negative physical examination, negative chest X-ray and CT scan. In group 2, 19 (4%) patients who had positive CT and or chest x-ray. Both groups were similar in GCS and ISS. Of the 19 patients, sixteen patients had a positive CCT, and thirteen of those had a positive chest x-ray. In the three patients who had negative physical examination and chest x-ray, the CT findings included one with a nondisplaced 10th rib fracture and two patients with osteoporotic compression fractures of dorsal vertebrae. The rate of both chest x-ray and CCT being positive among a group of screened patients was 16% (3/19) and the rate of a negative chest x-ray but positive CT was 16% (3/19). The odds ratio between the two outcomes was one. In blunt trauma patients presenting to the ED with a high GCS and low ISS score, when initial physical examination and chest x-ray are negative, routine CCT is of little value.

The Role of CT Scan in Pediatric Airway Foreign Bodies.

We aim to determine the utility of CT scan as a method to accurately confirm pediatric airway foreign bodies (AFBs), the current gold standard of which is chest X-ray as the primary imaging modality in the investigation screening of AFBs with progression to microlaryngobronchoscopy. A retrospective cohort study ofchildren diagnosed with suspected AFBs between July 2019 and June 2020 was conducted. The primary outcome of missed AFBs from radiologic investigations was recorded. A total of 226 childrenwith an average age of 1.94 years were included in this study. One hundred and two children were eventually admitted to the hospital for microlaryngobronchoscopy.A total of 89 cases were initially examined by chest X-ray with the diagnosis confirmed in 26 cases. The initial examination was chest CT scan in 105 cases, of which the diagnosis was confirmed in 46 cases. The initial examination was chest CT scan with airway reconstruction in 32 cases, and the diagnosis was confirmed in 17 cases. Patients with negative chest CT scan with airway reconstruction were observed to have resolution of symptoms with no further need for bronchoscopy. Chest CT scan with airway reconstruction had the highest rate of confirmed diagnosis of pediatric AFBs on initial scanning, followed by chest CT scan, and finally chest X-ray with fluoroscopy; there was no missed diagnosis in chest CT scan with airway reconstruction. Chest CT scan with airway reconstruction can accurately and quickly detect AFBs and reduce unnecessary bronchoscopy.

Clinical Characteristics and Management of Patients with a Suspected COVID-19 Infection in Emergency Departments: A European Retrospective Multicenter Study.

Background: Our aim is to describe and compare the profile and outcome of patients attending the ED with a confirmed COVID-19 infection with patients with a suspected COVID-19 infection. Methods: We conducted a multicentric retrospective study including adults who were seen in 21 European emergency departments (ED) with suspected COVID-19 between 9 March and 8 April 2020. Patients with either a clinical suspicion of COVID-19 or confirmed COVID-19, detected using either a RT-PCR or a chest CT scan, formed the C+ group. Patients with non-confirmed COVID-19 (C− group) were defined as patients with a clinical presentation in the ED suggestive of COVID-19, but if tests were performed, they showed a negative RT-PCR and/or a negative chest CT scan. Results: A total of 7432 patients were included in the analysis: 1764 (23.7%) in the C+ group and 5668 (76.3%) in the C− group. The population was older (63.8 y.o. ±17.5 vs. 51.8 y.o. +/− 21.1, p < 0.01), with more males (54.6% vs. 46.1%, p < 0.01) in the C+ group. Patients in the C+ group had more chronic diseases. Half of the patients (n = 998, 56.6%) in the C+ group needed oxygen, compared to only 15% in the C− group (n = 877). Two-thirds of patients from the C+ group were hospitalized in ward (n = 1128, 63.9%), whereas two-thirds of patients in the C− group were discharged after their ED visit (n = 3883, 68.5%). Conclusion: Our study was the first in Europe to examine the emergency department’s perspective on the management of patients with a suspected COVID-19 infection. We showed an overall more critical clinical situation group of patients with a confirmed COVID-19 infection.

Predicting lung abnormality and severity in chest imaging after COVID-19: Is there a clue based on the clinical spectrum during illness?

Background: Complaints after COVID-19 have been widely reported, especially those related to the respiratory tract. This situation may be related to the presence of lung lesions even though the patient has been cured as evidenced by negative PCR results. Chest CT scan is a good imaging modality that can be used to follow up post-COVID-19 patients. This study aims to determine the characteristics of a negative post-conversion chest CT scan and the correlation of the clinical spectrum of illness and lesions in a chest CT scan. Method: This study is an analytic observational type with a retrospective approach. Researchers will examine the medical records of confirmed COVID-19 patients who are hospitalized at Dr. Soetomo and had a negative post-conversion chest CT scan at Dr. Soetomo Hospital. The severity system uses a modified severity level, then a statistical correlation analysis test is carried out with the Spearman Test. Result: Total sample was 79 patients, with 46 male subjects (58,2 %) and 33 female subjects (41,8 %). From the clinical spectrum of illness, as many as 0% of patients were asymptomatic, 30.4% with mild symptoms, 25.3% with moderate symptoms, 17.7% with severe symptoms/severe pneumonia, and 26.6% with critical symptoms. Of the 79 samples, 93.7% had pulmonary abnormalities. The most abnormalities that were found were fibrosis at 88.6% and ground glass opacity (GGO) at 78.5%. Conclusion: Even though the patient has been declared cured of COVID-19 with a negative RT-PCR result, there are still abnormalities in the patients lungs. A significant correlation between clinical spectrum with pulmonary severity was found

Proposing a novel deep network for detecting COVID-19 based on chest images

The rapid outbreak of coronavirus threatens humans’ life all around the world. Due to the insufficient diagnostic infrastructures, developing an accurate, efficient, inexpensive, and quick diagnostic tool is of great importance. To date, researchers have proposed several detection models based on chest imaging analysis, primarily based on deep neural networks; however, none of which could achieve a reliable and highly sensitive performance yet. Therefore, the nature of this study is primary epidemiological research that aims to overcome the limitations mentioned above by proposing a large-scale publicly available dataset of chest computed tomography scan (CT-scan) images consisting of more than 13k samples. Secondly, we propose a more sensitive deep neural networks model for CT-scan images of the lungs, providing a pixel-wise attention layer on top of the high-level features extracted from the network. Moreover, the proposed model is extended through a transfer learning approach for being applicable in the case of chest X-Ray (CXR) images. The proposed model and its extension have been trained and evaluated through several experiments. The inclusion criteria were patients with suspected PE and positive real-time reverse-transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2. The exclusion criteria were negative or inconclusive RT-PCR and other chest CT indications. Our model achieves an AUC score of 0.886, significantly better than its closest competitor, whose AUC is 0.843. Moreover, the obtained results on another commonly-used benchmark show an AUC of 0.899, outperforming related models. Additionally, the sensitivity of our model is 0.858, while that of its closest competitor is 0.81, explaining the efficiency of pixel-wise attention strategy in detecting coronavirus. Our promising results and the efficiency of the models imply that the proposed models can be considered reliable tools for assisting doctors in detecting coronavirus.

Value of a chest X-ray and CT to diagnose acute heart failure in acute patients with dyspnoea: a prospective comparative diagnostic study in the emergency department

Abstract Background and purpose Diagnosing heart failure (HF) remains difficult in the acute setting where multiple diagnoses are in play. Objective evidence of pulmonary congestion by chest X-ray (CXR) is one criteria for the recent universal definition of heart failure (UniHF). But, since CXR is known to have a low diagnostic value, we hypothesized that a chest CT (CT) would outdo the CXR to diagnose decompensated HF in acute breathless patients. This study's primary objective was to examine if the CT has higher accuracy than the CXR to diagnose HF in the acute setting; and, secondly, to identify what pre-test characteristics would predict a false negative CXR or CT. Methods We performed a single-centre, prospective observational study and included consecutive adult patients with dyspnoea in the emergency department. Patients underwent immediate clinical examination, blood tests, CXR, CT and an echocardiogram. Congestion on CXR and CT was defined as the congruent verdict by two expert thorax radiologists, blinded to each others reading and all other clinical data. The absence of congestion was defined as the congruent verdict of “no congestion”. Congestion of CXR and CT was held up against UniHF ascertained by an expert panel of cardiologists where the pulmonary congestion component primarily was based on elevated filling pressures from the simultaneous comprehensive echocardiogram. Univariate- and multivariate logistic analyses identified factors associated with a false negative chest x-ray and CT. Results Of 228 patients with a mean age of 74,5 years, 129 (56,5%) were male, 98 (43%) had UniHF, and 139 (61.0%) had pulmonary disease. Congestion on the CXR diagnosed UniHF with a 54% sensitivity and 95% specificity, with almost similar figures for the CT with 54% and 99% respectively. A marginally better performance of the CT was shown by a significantly lower Akaike Information Criterion for pulmonary congestion by CT than for CXR. However, the net reclassification improvement by CT was 4% (p:0.5586). The CXR and CT were false negative for UniHF in 46% (45/98) for both modalities (Table 1). The only independent pre-test predictor of a false negative radiology examination in multivariable logistic regression analysis was NT-proBNP (CXR: OR 1.670 per log(BNP), p: &amp;lt;0.001) and CT: OR 1.693 per log(BNP), p: &amp;lt;0.001). Conclusions For the first time, CT has been directly compared with CXR to diagnose HF in consecutive breathless patients from the emergency department. The chest CT was marginally more specific than the CXR to diagnose HF, but with a similar sensitivity. Approximately half the patients obeying the universal definition of HF have no definite congestion on CXR nor CT, and these can only be identified by a high proBNP. Funding Acknowledgement Type of funding sources: None. Table 1

Efficacy of chest CT scan for COVID-19 diagnosis in a low prevalence and incidence region.

ObjectivesValue of chest CT was mainly studied in area of high COVID-19 incidence. The aim of this study was therefore to evaluate chest CT performances to diagnose COVID-19 pneumonia with regard to RT-PCR as reference standard in a low incidence area.MethodsA survey was sent to radiology department in 4 hospitals in an administrative French region of weak disease prevalence (3.4%). Study design was approved by the local institutional review board and recorded on the clinicaltrial.gov website (NCT04339686). Written informed consent was waived due to retrospective anonymized data collection. Patients who underwent a RT-PCR and a chest CT scan within 48 h for COVID-19 pneumonia suspicion were consecutively included. Diagnostic accuracy including the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of chest CT regarding RT-PCR as reference standard were calculated.ResultsOne hundred twenty-nine patients had abnormal chest CT findings compatible with a COVID-19 pneumonia (26%, 129/487). Among the 358 negative chest CT findings, 3% (10/358) were RT-PCR positive. Chest CT sensitivity, specificity, positive, and negative predictive value were respectively 87% (IC95: 85, 89; 69/79), 85% (IC95: 83, 87; 348/408), 53% (IC95: 50, 56; 69/129), and 97% (IC95: 95, 99; 348/358).ConclusionsIn a low prevalence area, chest CT scan is a good diagnostic tool to rule out COVID-19 infection among symptomatic suspected patients.Key Points • In a low prevalence area (3.4% in the administrative area and 5.8% at mean in the study) chest CT sensitivity and specificity for diagnosing COVID-19 pneumonia were 87% and 85% respectively. • In patients with negative chest CT for COVID-19 pneumonia, the negative predictive value of COVID-19 infection was 97% (348/358 subjects). • Performance of CT was equivalent between the 4 centers participating to this study. Supplementary InformationThe online version contains supplementary material available at 10.1007/s00330-021-07863-4.

CT Esophagography for Evaluation of Esophageal Perforation

Esophageal emergencies such as rupture or postoperative leak are uncommon but may be life threatening when they occur. Delay in their diagnosis and treatment may significantly increase morbidity and mortality. Causes of esophageal injury include iatrogenic (including esophagogastroduodenoscopy and stent placement), foreign body ingestion, blunt or penetrating trauma to the chest or abdomen, and forceful retching, also called Boerhaave syndrome. Although fluoroscopic esophagography remains the imaging study of choice according the American College of Radiology appropriateness criteria, CT esophagography has been shown to be at least equal to if not superior to fluoroscopic evaluation for esophageal injury. In addition, CT esophagography allows diagnosis of extraesophageal abnormalities, both as the cause of the patient's symptoms as well as incidental findings. CT esophagography also allows rapid diagnosis since the examination can be readily performed in most clinical settings and requires no direct radiologist supervision, requiring only properly trained technologists and a CT scanner. Multiple prior studies have shown the limited utility of fluoroscopic esophagography after a negative chest CT scan and the increase in accuracy after adding oral contrast agent to CT examinations, although there is considerable variability of CT esophagography protocols among institutions. Development of a CT esophagography program, utilizing a well-defined protocol with input from staff from the radiology, gastroenterology, emergency, and general surgery departments, can facilitate more rapid diagnosis and patient care, especially in overnight and emergency settings. The purpose of this article is to familiarize radiologists with CT esophagography techniques and imaging findings of emergent esophageal conditions. Online supplemental material is available for this article. ©RSNA, 2021.

The role of CT imaging for management of COVID-19 in epidemic area: early experience from a University Hospital

BackgroundTo evaluate the clinical value of the chest CT scan compared to the reference standard real-time polymerase chain reaction (RT-PCR) in COVID-19 patients.MethodsFrom March 29th to April 15th of 2020, a total of 240 patients with respiratory distress underwent both a low-dose chest CT scan and RT-PCR tests. The performance of chest CT in diagnosing COVID-19 was assessed with reference to the RT-PCR result. Two board-certified radiologists (mean 24 years of experience chest CT), blinded for the RT-PCR result, reviewed all scans and decided positive or negative chest CT findings by consensus.ResultsOut of 240 patients, 60% (144/240) had positive RT-PCR results and 89% (213/240) had a positive chest CT scans. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of chest CT in suggesting COVID-19 were 100% (95% CI: 97–100%, 144/240), 28% (95% CI: 19–38%, 27/240), 68% (95% CI: 65–70%) and 100%, respectively. The diagnostic accuracy of the chest CT suggesting COVID-19 was 71% (95% CI: 65–77%). Thirty-three patients with positive chest CT scan and negative RT-PCR test at baseline underwent repeat RT-PCR assay. In this subgroup, 21.2% (7/33) cases became RT-PCR positive.ConclusionChest CT imaging has high sensitivity and high NPV for diagnosing COVID-19 and can be considered as an alternative primary screening tool for COVID-19 in epidemic areas. In addition, a negative RT-PCR test, but positive CT findings can still be suggestive of COVID-19 infection.

Lung Ultrasound Findings in a Covid-19 Patient with Negative Chest CT.

On March 11, 2020, the World Health Organization declared a pandemic caused by Severe Acute Respiratory Syndrome due to Coronavirus 2 (SARS-CoV-2) with spread to more than 180 countries, 18 566 769 confirmed cases and 701 278 deaths (Johns Hopkins Coronavirus Resource Center, accesed on August 5, 2020).

Follow-Up CT Results of COVID-19 Patients with Initial Negative Chest CT.

PurposeTo determine whether new pulmonary lesions will develop in COVID-19 patients with negative initial chest CT findings and to investigate their CT features and outcome during treatment.Patients and MethodsData were collected retrospectively from 29 patients who had tested positive for COVID-19 by reverse-transcription polymerase chain reaction testing but negative by initial chest CT from January 22 to February 17, 2020. Clinical manifestations, laboratory indicators, and follow-up CT data were evaluated.ResultsAmong 317 confirmed COVID-19 patients, 29 (9.1%) (mean ± SD, 38.5 ± 20.5 years; 12 women) with negative initial chest CT findings were evaluated. New pulmonary lesions developed in 10 (34.5%) patients on follow-up CT. Mean time from onset of new lesions to initial CT was 5.8 ± 3.0 days (range: 2–12 days). New lesions (mean involved lobes and segments: 2.5 ± 1.6 [range: 1–5] and 4.5 ± 4.5 [range: 1–13]) were mainly spherical/patchy ground-glass opacities frequently located in the left lower lobe (9, 90.0%). Among the 10 patients, lesions in 6 (60.0%) indicated progression after occurrence, and those in 10 (100.0%) indicated significant absorption on latest CT. When new lesions developed, 6 (60.0%) patients developed new symptoms or had aggravated symptoms and 3 (30.0%) had decreased lymphocyte count. Patients with worsening symptoms had higher involvement of lung segments (mean: 6.5 ± 5.0, range: 1–13) than asymptomatic patients (mean: 1.5 ± 0.6, range: 1–2) (P = 0.057).ConclusionIn COVID-19 patients with negative initial chest CT findings, new pulmonary lesions may develop during treatment. Repeat CT is necessary for monitoring the disease, especially when patients have worsening symptoms or laboratory indicators.

Diagnostic performance of chest CT in screening patients with suspected COVID-19 infection in a Western population.

Objective:To investigate the diagnostic performance of chest CT in screening patients suspected of Coronavirus disease 2019 (COVID-19) in a Western population.Methods:Consecutive patients who underwent chest CT because of clinical suspicion of COVID-19 were included. CT scans were prospectively evaluated by frontline general radiologists who were on duty at the time when the CT scan was performed and retrospectively assessed by a chest radiologist in an independent and blinded manner. Real-time reverse transcriptase–polymerase chain reaction was used as reference standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Sensitivity and specificity of the frontline general radiologists were compared to those of the chest radiologist using the McNemar test.Results:56 patients were included. Sensitivity, specificity, PPV, and NPV for the frontline general radiologists were 89.3% [95% confidence interval (CI): 71.8%, 97.7%], 32.1% (95% CI: 15.9%, 52.4%), 56.8% (95% CI: 41.0%, 71.7%), and 75.0% (95% CI: 42.8%, 94.5%), respectively. Sensitivity, specificity, PPV, and NPV for the chest radiologist were 89.3% (95% CI: 71.8%, 97.7%), 75.0% (95% CI: 55.1%, 89.3%), 78.1% (95% CI: 60.0%, 90.7%), and 87.5% (95% CI: 67.6%, 97.3%), respectively. Sensitivity was not significantly different (p = 1.000), but specificity was significantly higher for the chest radiologist (p = 0.001).Conclusion:Chest CT interpreted by frontline general radiologists achieves insufficient screening performance. Although specificity of a chest radiologist appears to be significantly higher, sensitivity did not improve. A negative chest CT result does not exclude COVID-19.Advances in knowledge:Our study shows that chest CT interpreted by frontline general radiologists achieves insufficient diagnostic performance to use it as an independent screening tool for COVID-19. Although specificity of a chest radiologist appears to be significantly higher, sensitivity is still insufficiently high.

Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia.

BackgroundComputed tomography (CT) of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease depicts the extent of lung involvement in COVID-19 pneumonia.PurposeThe aim of the study was to determine the value of quantification of the well-aerated lung obtained at baseline chest CT for determining prognosis in patients with COVID-19 pneumonia.Materials and MethodsPatients who underwent chest CT suspected for COVID-19 pneumonia at the emergency department admission between February 17 to March 10, 2020 were retrospectively analyzed. Patients with negative reverse-transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2 in nasal-pharyngeal swabs, negative chest CT, and incomplete clinical data were excluded. CT was analyzed for quantification of well aerated lung visually (%V-WAL) and by open-source software (%S-WAL and absolute volume, VOL-WAL). Clinical parameters included demographics, comorbidities, symptoms and symptom duration, oxygen saturation and laboratory values. Logistic regression was used to evaluate relationship between clinical parameters and CT metrics versus patient outcome (ICU admission/death vs. no ICU admission/ death). The area under the receiver operating characteristic curve (AUC) was calculated to determine model performance.ResultsThe study included 236 patients (females 59/123, 25%; median age, 68 years). A %V-WAL<73% (OR, 5.4; 95% CI, 2.7-10.8; P<0.001), %S-WAL<71% (OR, 3.8; 95% CI, 1.9-7.5; P<0.001), and VOL-WAL<2.9 L (OR, 2.6; 95% CI, 1.2-5.8; P<0.01) were predictors of ICU admission/death. In comparison with clinical model containing only clinical parameters (AUC, 0.83), all three quantitative models showed higher diagnostic performance (AUC 0.86 for all models). The models containing %V-WAL<73% and VOL-WAL<2.9L were superior in terms of performance as compared to the models containing only clinical parameters (P=0.04 for both models).ConclusionIn patients with confirmed COVID-19 pneumonia, visual or software quantification the extent of CT lung abnormality were predictors of ICU admission or death.

Impact on clinical practice of the preoperative screening of Covid-19 infection in surgical oncological patients. Prospective cohort study

BackgroundIn the oncological patient, an COVID-19-Infection, whether symptomatic or asymptomatic, a surgical procedure may carry a higher postoperative morbidity and mortality. The aim of this study was to describe the impact on clinical practice of sequential preoperative screening for COVID-19-infection in deciding whether to proceed or postpone surgery. MethodsProspective, cohort study, based on consecutive patients’ candidates for an oncological surgical intervention. Sequential preoperative screening for COVID-19-infection: two-time medical history (telematic and face-to-face), PCR and chest CT, 48 h before of surgical intervention. COVID-19-infection was considered positive if the patient had a suggestive medical history and/or PCR-positive and/or CT of pneumonia. ResultsBetween April 15th and May 4th, 2020, 179 patients were studied, 97 were male (54%), mean (sd) age 66.7 (13,6). Sequential preoperative screening was performed within 48 h before to surgical intervention. The prevalence of preoperative COVID-19-infection was 4.5%, 95%CI:2.3–8.6% (8 patients). Of the operated patients (171), all had a negative medical history, PCR and chest CT. The complications was 14.8% (I-II) and 2.5% (III-IV). There was no mortality. The hospital stay was 3.1 (sd 2.7) days.In the 8 patients with COVID-19-infection, the medical history was suggestive in all of them, 7 presented PCR-positive and 5 had a chest CT suggestive of pneumonia. The surgical intervention was postponed between 15 and 21 days. ConclusionPreoperative screening for COVID-19-infection using medical history and PCR helped the surgeon to decide whether to go ahead or postpone surgery in oncological patients. The chest CT may be useful in unclear cases.

A liquid biopsy-based method for the detection and quantification of circulating tumor cells in surgical osteosarcoma patients.

A method for the enumeration and quantification of osteosarcoma (OS) circulating tumor cells (CTCs) is currently not available. A correlation between the number of CTCs and progression-free survival (PFS) has been established for other cancers, but not for OS CTCs. A method was therefore developed for CTC quantification in OS and validated in a prospective cohort of surgical patients with primary and recurrent/metastatic OS (N=23). Human OS cells, acting as CTCs, were enumerated from spiked human peripheral blood (PB) following erythrocyte and leukocyte depletion. The OS cells were quantified microscopically based on aneuploidy and a CK18−/CD45− phenotype. Aneuploidy was assayed by fluorescence in situ hybridization (FISH) using fluorescence-labeled alpha-satellite probes for the centromeres of chromosome (CEP 8). CK18 and CD45 phenotyping was performed with immunocytochemistry. HOS cells in spiked PB could be effectively retrieved with the FISH-based enumeration method, which was subsequently employed in an OS patient cohort. PB of recurrent/metastatic OS patients contained more CTCs than the PB of primary OS patients. OS patients with ≥2 CTCs per 7.5 ml of PB had worse PFS than patients whose PB contained <2 CTCs. In 2 cases, CTCs were present in PB of OS patients with negative X-ray and chest CT scans. In conclusion, our method was able to quantitate CTCs in liquid biopsies of OS patients. The number of CTCs has diagnostic and prognostic value.

Assessing the use of routine abdominal CT in staging evaluation of patients with primary breast cancer.

3 Background: The purpose of this study was to determine the utility of routine abdominal CT in the staging evaluation of women with newly diagnosed primary breast cancer given no detectable disease beyond the ipsilateral axillary nodes on chest CT. Methods: The chest and abdominal CT scans from 440 patients over a 10-year period were reviewed. The presence of definite or possible metastatic disease in the axillary nodes, chest wall, internal mammary nodes, mediastinal nodes, lungs, liver and adrenals were recorded for each patient. Cross tabulation bivariate analysis as well as a chi-square test were performed to characterize the relationship between detection of disease in the chest and disease in the abdomen. Results: Of the 440 patients reviewed, the following were found to have detectable metastatic disease by CT scan: axillary nodes 258 of 440 (56.46%), chest wall 40 of 440 (9.10%), internalmammary nodes 8 of 440 (1.82%), mediastinal nodes 29 of 440 (6.59%), lung 25 of 440 (5.68%), liver 12 of 437 (2.73%), and adrenals 8 of 440 (1.82%). In total, 81 patients had disease detectable in the chest beyond the ipsilateral axillary nodes, and only 12 patients had detectable disease spread in the abdomen. Of the 359 patients who had a negative chest CT, only 1 patient had detectable or possible metastatic disease spread on abdominal CT, resulting in a 99.70% negative predictive value (p &lt; 0.001). Conclusions: The routine use of abdominal CT in women with newly diagnosed primary breast cancer and no detectable disease beyond the ipsilateral axillary nodes on staging chest CT scan has little value with a 99.70% negative predictive value. We recommend that if a negative CT scan of the patient’s chest yields no detectable disease beyond the axillary nodes, then further CT imaging of the abdomen is of no additional benefit to the patient. [Table: see text]

Phase II study of neoadjuvant gemcitabine (GC), pegylated liposomal doxorubicin (DX) and docetaxel (TT) in locally advanced breast cancer

606 Background: Neoadjuvant chemotherapy is currently the standard of care for the management of locally advanced breast cancer, as it improves both disease-free and overall survival. Methods: Patients with histologic confirmation of locally advanced breast cancer, age >18 years, left ventricular ejection fraction >50%, good performance status and adequate bone marrow, negative chest and abdominal CT scan, renal and hepatic function were included in the study. Prior systemic therapy and radiotherapy and the presence of metastases were not allowed. The treatment schedule was as follows: GC: 1,250 mg/m2 (day 1); GC 1,000 mg/m2 plus TT 75 mg/m2 plus DX 30 mg/m2 (day 8). Pegfilgrastim was routinely administered as primary prophylaxis against febrile neutropenia. Courses were repeated each 21 days for 4–6 cycles. This study was aimed to assess the activity of GC, DX and TT in locally advanced breast cancer. Results: Fifty patients were enrolled and treated. Median age was 51 years (range: 34–73), 27 (54%) being postmenopausal patients. Infiltrating ductal carcinoma was diagnosed in 84% of cases. Tumor size was as follows: T1 (n=2, 4%), T2 (n= 31, 62%), T3 (n=14, 28%), T4 (n=2, 4%). G3 grading was found in 28% of cases. Median tumor size was 4 cm (range: 2–10). Tumors were ER+, PR+ and c-Erb-B2+ in 34 (68%), 31(62%) and 27 (54%) cases, respectively. Surgery was performed in 47 (94%) patients: 12 (26%) pathologic complete response, 24 (51%) partial response and 9 (19%) stable disease were observed resulting in a pathologic overall response rate of 77%. Logistic regression analysis revealed that larger tumor size, Mib1 higher expression and higher number of cycles were independently associated with better tumor response rates. Conclusions: This combination chemotherapy can yield a high tumor response rate. Correlation analysis suggests that this neoadjuvant regimen might be more effective in patients with larger tumors expressing Mib1, particularly if full treatment can be administered. No significant financial relationships to disclose.

Detection of lung cancer using weighted digital analysis of breath biomarkers

Background A combination of biomarkers in a multivariate model may predict disease with greater accuracy than a single biomarker employed alone. We developed a non-linear method of multivariate analysis, weighted digital analysis (WDA), and evaluated its ability to predict lung cancer employing volatile biomarkers in the breath. Methods WDA generates a discriminant function to predict membership in disease vs no disease groups by determining weight, a cutoff value, and a sign for each predictor variable employed in the model. The weight of each predictor variable was the area under the curve (AUC) of the receiver operating characteristic (ROC) curve minus a fixed offset of 0.55, where the AUC was obtained by employing that predictor variable alone, as the sole marker of disease. The sign (±) was used to invert the predictor variable if a lower value indicated a higher probability of disease. When employed to predict the presence of a disease in a particular patient, the discriminant function was determined as the sum of the weights of all predictor variables that exceeded their cutoff values. The algorithm that generates the discriminant function is deterministic because parameters are calculated from each individual predictor variable without any optimization or adjustment. We employed WDA to re-evaluate data from a recent study of breath biomarkers of lung cancer, comprising the volatile organic compounds (VOCs) in the alveolar breath of 193 subjects with primary lung cancer and 211 controls with a negative chest CT. Results The WDA discriminant function accurately identified patients with lung cancer in a model employing 30 breath VOCs (ROC curve AUC = 0.90; sensitivity = 84.5%, specificity = 81.0%). These results were superior to multilinear regression analysis of the same data set (AUC = 0.74, sensitivity = 68.4, specificity = 73.5%). WDA test accuracy did not vary appreciably with TNM (tumor, node, metastasis) stage of disease, and results were not affected by tobacco smoking (ROC curve AUC = 0.92 in current smokers, 0.90 in former smokers). WDA was a robust predictor of lung cancer: random removal of 1/3 of the VOCs did not reduce the AUC of the ROC curve by > 10% (99.7% CI). Conclusions A test employing WDA of breath VOCs predicted lung cancer with accuracy similar to chest computed tomography . The algorithm identified dependencies that were not apparent with traditional linear methods. WDA appears to provide a useful new technique for non-linear multivariate analysis of data.

Prediction of lung cancer using volatile biomarkers in breath1

Normal metabolism generates several volatile organic compounds (VOCs) that are excreted in the breath (e.g. alkanes). In patients with lung cancer, induction of high-risk cytochrome p450 genotypes may accelerate catabolism of these VOCs, so that their altered abundance in breath may provide biomarkers of lung cancer. VOCs in 1.0 L alveolar breath were analyzed in 193 subjects with primary lung cancer and 211 controls with a negative chest CT. Subjects were randomly assigned to a training set or to a prediction set in a 2:1 split. A fuzzy logic model of breath biomarkers of lung cancer was constructed in the training set and then tested in subjects in the prediction set by generating their typicality scores for lung cancer. Mean typicality scores employing a 16 VOC model were significantly higher in lung cancer patients than in the control group (p<0.0001 in all TNM stages). The model predicted primary lung cancer with 84.6% sensitivity, 80.0% specificity, and 0.88 area under curve (AUC) of the receiver operating characteristic (ROC) curve. Predictive accuracy was similar in TNM stages 1 through 4, and was not affected by current or former tobacco smoking. The predictive model achieved near-maximal performance with six breath VOCs, and was progressively degraded by random classifiers. Predictions with fuzzy logic were consistently superior to multilinear analysis. If applied to a population with 2% prevalence of lung cancer, a screening breath test would have a negative predictive value of 0.985 and a positive predictive value of 0.163 (true positive rate =0.277, false positive rate =0.029). A two-minute breath test predicted lung cancer with accuracy comparable to screening CT of chest. The accuracy of the test was not affected by TNM stage of disease or tobacco smoking. Alterations in breath VOCs in lung cancer were consistent with a non-linear pathophysiologic process, such as an off-on switch controlling high-risk cytochrome p450 activity. Further research is needed to determine if detection of lung cancer with this test will reduce mortality.