scholarly journals Lung Nodules in Cancer Patients: Chest CT Scan Misses Up to 66% of Malignant Nodules

2017 ◽  
Vol 65 (S 01) ◽  
pp. S1-S110
Author(s):  
S. Macherey ◽  
F. Doerr ◽  
A. Gassa ◽  
J.Y. Seo ◽  
M. Heldwein ◽  
...  
2020 ◽  
Vol 93 (1113) ◽  
pp. 20190693
Author(s):  
Alessio Casutt ◽  
Jade Couchepin ◽  
Anne-Sophie Brunel ◽  
Alban Lovis ◽  
Pierre-Yves Bochud ◽  
...  

Objective: The aim of this study is to characterize chest CT findings of neutropenic patients with proven/probable invasive pulmonary aspergillosis (IPA). Methods: Hematological cancer patients admitted to our institution (2007–2017) were retrospectively enrolled if the diagnostic criteria of proven/probable IPA during the neutropenia were met (EORTC/MSG). Galactomannan (GM) was routinely measured in serum and chest CT-scan was routinely performed in case of recurrent/persistent fever. Bronchoscopy was performed in case of chest CT-scan abnormalities. Chest CT-scan and GM dosage were analyzed at the time of IPA suspicion. Chest lesions were classified using a clinical report form by two expert radiologists. Results: 35 patients were identified. Peribronchial focal lesions were observed in 29 IPA (82.9%) by the first radiologist and in 31 (88.5%) by the second (k = 0.768). 12 weeks mortality was 20%. Conclusion: Peribronchial focal lesions are a common finding in early-IPA whatever the GM value during neutropenia and our findings reinforce the efficiency of a preemptive approach. Advances in knowledge; Peribronchial focal lesions, which are classically described in airway invasive aspergillosis, are a common finding in early-IPA in hematological cancer patients with prolonged neutropenia regardless of the GM value, and such peribronchial lesions should reinforce the possibility of IPA.


2021 ◽  
Vol 41 (2) ◽  
pp. 94-101
Author(s):  
Luths Maharina ◽  
Yusup Subagio Sutanto ◽  
Widiastuti Widiastuti ◽  
Sulistyani Kusumaningrum ◽  
Adam Prabata ◽  
...  

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Priyanka Yadlapalli ◽  
D. Bhavana ◽  
Suryanarayana Gunnam

PurposeComputed tomography (CT) scan can provide valuable information in the diagnosis of lung diseases. To detect the location of the cancerous lung nodules, this work uses novel deep learning methods. The majority of the early investigations used CT, magnetic resonance and mammography imaging. Using appropriate procedures, the professional doctor in this sector analyses these images to discover and diagnose the various degrees of lung cancer. All of the methods used to discover and detect cancer illnesses are time-consuming, expensive and stressful for the patients. To address all of these issues, appropriate deep learning approaches for analyzing these medical images, which included CT scan images, were utilized.Design/methodology/approachRadiologists currently employ chest CT scans to detect lung cancer at an early stage. In certain situations, radiologists' perception plays a critical role in identifying lung melanoma which is incorrectly detected. Deep learning is a new, capable and influential approach for predicting medical images. In this paper, the authors employed deep transfer learning algorithms for intelligent classification of lung nodules. Convolutional neural networks (VGG16, VGG19, MobileNet and DenseNet169) are used to constrain the input and output layers of a chest CT scan image dataset.FindingsThe collection includes normal chest CT scan pictures as well as images from two kinds of lung cancer, squamous and adenocarcinoma impacted chest CT scan images. According to the confusion matrix results, the VGG16 transfer learning technique has the highest accuracy in lung cancer classification with 91.28% accuracy, followed by VGG19 with 89.39%, MobileNet with 85.60% and DenseNet169 with 83.71% accuracy, which is analyzed using Google Collaborator.Originality/valueThe proposed approach using VGG16 maximizes the classification accuracy when compared to VGG19, MobileNet and DenseNet169. The results are validated by computing the confusion matrix for each network type.


2020 ◽  
Author(s):  
seied Asadollah Mousavi ◽  
Tahereh Rostami ◽  
Azadeh kiumarsi ◽  
soroush Rad ◽  
mohammadreza Rostami ◽  
...  

Abstract BackgroundCancer patients, with an incidence of more than 18 million new cases per year, may constitute a significant portion of the COVID-19 infected population. In the pandemic situation, these patients are considered highly vulnerable to infectious complications due to their immunocompromised state.Material & MethodsIn this retrospective case series, the documents of solid cancer patients infected by SARS-CoV-2, hospitalized in Shariati hospital (a tertiary care referral center designated for COVID-19 patients, affiliated by Tehran University of Medical Sciences) between 20 February and 20 April 2020, were evaluated. The diagnosis of COVID-19 was based on a positive real-time fluorescence reverse transcription-polymerase chain reaction (RT-PCR) for SARS-CoV-2 nucleic acids from nasal and/or pharyngeal specimens and/or features of chest CT scan highly suggestive for SARS-CoV-2.ResultsAmong 33 patients with solid cancer, 11 patients had a positive RT-PCR for SARS-CoV-2 and 22 patients had highly suggestive chest CT scan findings in favor of SARS-CoV-2 but negative RT-PCR . The mean age of the patients was 63.9 years, and 54.5% of the patients were males. Age and sex of the patients did not correlate with mortality. There was no difference in COVID-19 symptoms, lymphocytopenia, thrombocytopenia between survived and un-survived cancer patients. However, LDH level was significantly higher (7170±2077 vs. 932.3±324.7, P-value=0.016) and also serum albumin was significantly lower in un-survived group (3.6±0.5 vs. 2.9±0.6 p-value=0.03). Among 16 patients with stage IV cancer, thirteen patients died, which was significantly higher compared to stage I-III cancer patients (81.3% vs. 18.8% P-value= <0.001). In terms of developing complications, sepsis, invasive ventilation and mortality was significantly higher in patients who received cytotoxic chemotherapy within the last 14 days. There was no significant difference between the two groups of positive and negative SARS-CoV-2 RT-PCR regarding their sex, age, cancer type, mean Hemoglobin concentration, Platelet count, lymphocyte count, serum albumin level, ESR and CRP titer or other laboratory findings and also in terms of clinical symptoms and coexisting.ConclusionIn this study, we showed that the mortality rate among cancer patients affected by COVID-19 was higher than general population and this rate has a significant correlation with factors such as the stage of the disease, the type of cancer, the activity of cancer and finally receiving cytotoxic chemotherapy within 14 days before diagnosis of COVID-19. We also showed that the outcome of cancer patients with positive RT-PCR for COVID-19 similar to those with negative RT-PCR with highly suggestive chest CT scan findings.


Author(s):  
Brett Norman ◽  
S. Pipavath ◽  
Kieth Sigel ◽  
Shahida Shahrir ◽  
Kathleen Akgun ◽  
...  

2021 ◽  
Vol 123 (4) ◽  
pp. 815-822
Author(s):  
Joanne Guerlain ◽  
Fabienne Haroun ◽  
Alexandra Voicu ◽  
Charles Honoré ◽  
Franck Griscelli ◽  
...  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fatemeh Khatami ◽  
Mohammad Saatchi ◽  
Seyed Saeed Tamehri Zadeh ◽  
Zahra Sadat Aghamir ◽  
Alireza Namazi Shabestari ◽  
...  

AbstractNowadays there is an ongoing acute respiratory outbreak caused by the novel highly contagious coronavirus (COVID-19). The diagnostic protocol is based on quantitative reverse-transcription polymerase chain reaction (RT-PCR) and chests CT scan, with uncertain accuracy. This meta-analysis study determines the diagnostic value of an initial chest CT scan in patients with COVID-19 infection in comparison with RT-PCR. Three main databases; PubMed (MEDLINE), Scopus, and EMBASE were systematically searched for all published literature from January 1st, 2019, to the 21st May 2020 with the keywords "COVID19 virus", "2019 novel coronavirus", "Wuhan coronavirus", "2019-nCoV", "X-Ray Computed Tomography", "Polymerase Chain Reaction", "Reverse Transcriptase PCR", and "PCR Reverse Transcriptase". All relevant case-series, cross-sectional, and cohort studies were selected. Data extraction and analysis were performed using STATA v.14.0SE (College Station, TX, USA) and RevMan 5. Among 1022 articles, 60 studies were eligible for totalizing 5744 patients. The overall sensitivity, specificity, positive predictive value, and negative predictive value of chest CT scan compared to RT-PCR were 87% (95% CI 85–90%), 46% (95% CI 29–63%), 69% (95% CI 56–72%), and 89% (95% CI 82–96%), respectively. It is important to rely on the repeated RT-PCR three times to give 99% accuracy, especially in negative samples. Regarding the overall diagnostic sensitivity of 87% for chest CT, the RT-PCR testing is essential and should be repeated to escape misdiagnosis.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Vikram rao Bollineni ◽  
Koenraad Hans Nieboer ◽  
Seema Döring ◽  
Nico Buls ◽  
Johan de Mey

Abstract Background To 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. Methods From 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. Results Out 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. Conclusion Chest 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.


CHEST Journal ◽  
2013 ◽  
Vol 144 (2) ◽  
pp. 700-703 ◽  
Author(s):  
Sarah Bastawrous ◽  
Jan V. Hirschmann

Sign in / Sign up

Export Citation Format

Share Document