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Low-dose computed tomography for the diagnosis of pneumonia in elderly patients: a prospective, interventional cohort study.

ABSTRACT: The diagnosis of pneumonia is challenging. Our objective was to assess whether low-dose computed tomography (LDCT) modified the probability of diagnosing pneumonia in elderly patients.We prospectively included patients aged over 65?years with a suspicion of pneumonia treated with antimicrobial therapy (AT). All patients had a chest radiograph and LDCT within 72?h of inclusion. The treating clinician assessed the probability of pneumonia before and after the LDCT scan using a Likert scale. An adjudication committee retrospectively rated the probability of pneumonia and was considered as the reference for diagnosis. The main outcome was the difference in the clinician's pneumonia probability estimates before and after LDCT and the proportion of modified diagnoses which matched the reference diagnosis (the net reclassification improvement (NRI)).A total of 200 patients with a median age of 84?years were included. After LDCT, the estimated probability of pneumonia changed in 90 patients (45%), of which 60 (30%) were downgraded and 30 (15%) were upgraded. The NRI was 8% (NRI event (-6%) + NRI non-event (14%)).LDCT modified the estimated probability of pneumonia in a substantial proportion of patients. It mostly helped to exclude a diagnosis of pneumonia and hence to reduce unnecessary AT.

SUBMITTER: Prendki V

PROVIDER: S-EPMC5978575 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Low-dose computed tomography for the diagnosis of pneumonia in elderly patients: a prospective, interventional cohort study.

Prendki Virginie V Scheffler Max M Huttner Benedikt B Garin Nicolas N Herrmann François F Janssens Jean-Paul JP Marti Christophe C Carballo Sebastian S Roux Xavier X Serratrice Christine C Serratrice Jacques J Agoritsas Thomas T Becker Christoph D CD Kaiser Laurent L Rosset-Zufferey Sarah S Soulier Valérie V Perrier Arnaud A Reny Jean-Luc JL Montet Xavier X Stirnemann Jérôme J

The European respiratory journal 20180530 5

The diagnosis of pneumonia is challenging. Our objective was to assess whether low-dose computed tomography (LDCT) modified the probability of diagnosing pneumonia in elderly patients.We prospectively included patients aged over 65 years with a suspicion of pneumonia treated with antimicrobial therapy (AT). All patients had a chest radiograph and LDCT within 72 h of inclusion. The treating clinician assessed the probability of pneumonia before and after the LDCT scan using a Likert scale. An adj ...[more]

PMID: 29650558

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Project description:ObjectiveTo determine patient, institution, and machine characteristics that contribute to variation in radiation doses used for computed tomography (CT).DesignProspective cohort study.SettingData were assembled and analyzed from the University of California San Francisco CT International Dose Registry.ParticipantsStandardized data from over 2.0 million CT examinations of adults who underwent CT between November 2015 and August 2017 from 151 institutions, across seven countries (Switzerland, Netherlands, Germany, United Kingdom, United States, Israel, and Japan).Main outcome measuresMean effective doses and proportions of high dose examinations for abdomen, chest, combined chest and abdomen, and head CT were determined by patient characteristics (sex, age, and size), type of institution (trauma center, care provision 24 hours per day and seven days per week, academic, private), institutional practice volume, machine factors (manufacturer, model), country, and how scanners were used, before and after adjustment for patient characteristics, using hierarchical linear and logistic regression. High dose examinations were defined as CT scans with doses above the 75th percentile defined during a baseline period.ResultsThe mean effective dose and proportion of high dose examinations varied substantially across institutions. The doses varied modestly (10-30%) by type of institution and machine characteristics after adjusting for patient characteristics. By contrast, even after adjusting for patient characteristics, wide variations in radiation doses across countries persisted, with a fourfold range in mean effective dose for abdomen CT examinations (7.0-25.7 mSv) and a 17-fold range in proportion of high dose examinations (4-69%). Similar variation across countries was observed for chest (mean effective dose 1.7-6.4 mSv, proportion of high dose examinations 1-26%) and combined chest and abdomen CT (10.0-37.9 mSv, 2-78%). Doses for head CT varied less (1.4-1.9 mSv, 8-27%). In multivariable models, the dose variation across countries was primarily attributable to institutional decisions regarding technical parameters (that is, how the scanners were used).ConclusionsCT protocols and radiation doses vary greatly across countries and are primarily attributable to local choices regarding technical parameters, rather than patient, institution, or machine characteristics. These findings suggest that the optimization of doses to a consistent standard should be possible.Study registrationClinicaltrials.gov NCT03000751.

Project description:BackgroundIt is unclear whether local pathological pulmonary changes truly reflect the severity of childhood Mycoplasma pneumoniae infection, which is characterized by rapid progress and potential mortality. This study multi-dimensionally analyzed low-dose computed tomography findings to assess the severity of Mycoplasma pneumoniae infection and predict its progress in such patients.MethodsIn all, 752 children with Mycoplasma pneumoniae pneumonia (MPP) who underwent low-dose computed tomography examinations from February 2016 to July 2020 were retrospectively enrolled to conduct a cohort study. Clinical and radiological variables were analyzed using univariate analysis, and radiological variables were further analyzed using multivariable logistic regression in severe cases. Then, the correlation between the key computed tomography features and clinical symptoms, laboratory indicators, and medical costs were assessed using the chi-squared and Kruskal-Wallis H tests. Kaplan-Meier curves and Cox regression models were created to evaluate the correlations between the key computed tomography features, fever duration, and the length of hospital stay.ResultsOf the 752 included patients, 16.2% (122/752) developed severe MPP. Atelectasis, pleural effusion, and lung consolidation occurred in 9.7% (73/752), 15.8% (119/752), and 90.3% (679/752) of patients, respectively. In addition to pleural effusion, the number of lobes of lung consolidation was the highest risk feature of severe MPP. Patients with consolidation in 2, 3, and 4 lobes had a 1.0-, 3.1-, and 7.5-fold increased risk of severe MPP, compared with patients with consolidation in fewer than 1 lobe. The duration of fever prior to admission had no effect on the proportions of the lobar consolidation (P=0.14) but did have significant effect on the incidence of pleural effusion (P=0.004). Levels of inflammatory markers and medical costs rose consistently with the increase in the number of lobar consolidations (P<0.001). After adjustments for pleural effusion, 1, 2, 3, and 4 lobes of consolidation remained positively associated with fever duration [1 lobe: hazard ratio (HR) =1.55, 95% CI: 1.10-2.18; 2 lobes: HR =1.65, 95% CI: 1.13-2.42l; 3 lobes: HR =1.82, 95% CI: 1.11-2.98; 4 lobes: HR =2.87, 95% CI: 1.25-6.61] compared to 0 lobes of consolidation. Compared to 0 lobes of consolidation, 1, 2, 3, and 4 lobes of consolidation were also positively correlated with the length of hospital stay (1 lobe: HR =2.24, 95% CI: 1.73-2.89; 2 lobes: HR =2.56, 95% CI: 1.91-3.43; 3 lobes: HR =2.87, 95% CI: 1.90-4.32; 4 lobes: HR =4.12, 95% CI: 2.01-8.46).ConclusionsLobar consolidation is a stable and reliable computed tomography feature that can be used to assess the severity of MPP in children. Quantitative analysis of lobar consolidation can comprehensively and accurately predict the progression of Mycoplasma pneumoniae. Low-dose computed tomography is recommended for children with severe MPP with complicated courses.

Project description:ImportanceScreening for lung cancer has the potential to reduce mortality, but in addition to detecting aggressive tumors, screening will also detect indolent tumors that otherwise may not cause clinical symptoms. These overdiagnosis cases represent an important potential harm of screening because they incur additional cost, anxiety, and morbidity associated with cancer treatment.ObjectiveTo estimate overdiagnosis in the National Lung Screening Trial (NLST).Design, setting, and participantsWe used data from the NLST, a randomized trial comparing screening using low-dose computed tomography (LDCT) vs chest radiography (CXR) among 53 452 persons at high risk for lung cancer observed for 6.4 years, to estimate the excess number of lung cancers in the LDCT arm of the NLST compared with the CXR arm.Main outcomes and measuresWe calculated 2 measures of overdiagnosis: the probability that a lung cancer detected by screening with LDCT is an overdiagnosis (PS), defined as the excess lung cancers detected by LDCT divided by all lung cancers detected by screening in the LDCT arm; and the number of cases that were considered overdiagnosis relative to the number of persons needed to screen to prevent 1 death from lung cancer.ResultsDuring follow-up, 1089 lung cancers were reported in the LDCT arm and 969 in the CXR arm of the NLST. The probability is 18.5% (95% CI, 5.4%-30.6%) that any lung cancer detected by screening with LDCT was an overdiagnosis, 22.5% (95% CI, 9.7%-34.3%) that a non-small cell lung cancer detected by LDCT was an overdiagnosis, and 78.9% (95% CI, 62.2%-93.5%) that a bronchioalveolar lung cancer detected by LDCT was an overdiagnosis. The number of cases of overdiagnosis found among the 320 participants who would need to be screened in the NLST to prevent 1 death from lung cancer was 1.38.Conclusions and relevanceMore than 18% of all lung cancers detected by LDCT in the NLST seem to be indolent, and overdiagnosis should be considered when describing the risks of LDCT screening for lung cancer.

Project description:In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series.Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols.Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use of the previous normal-dose scan via the presented ndiNLM algorithm is noticeable as compared to a similar approach without using the previous normal-dose scan.For low-dose CT image restoration, the presented ndiNLM method is robust in preserving the spatial resolution and identifying the low-contrast structure. The authors can draw the conclusion that the presented ndiNLM algorithm may be useful for some clinical applications such as in perfusion imaging, radiotherapy, tumor surveillance, etc.

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Low-dose computed tomography for the diagnosis of pneumonia in elderly patients: a prospective, interventional cohort study.

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Low-dose computed tomography for the diagnosis of pneumonia in elderly patients: a prospective, interventional cohort study.

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