Routine Chest CT Scan Research Articles

COVID-19 Vaccination Effectively Reduces Pneumonia Severity as Assessed by Routine Chest Computed Tomography

Background: In China, the COVID-19 outbreak infected more than 80% of the population. Few trials have been conducted to assess the effectiveness of the China-manufactured vaccine against COVID-19. Purpose: The purpose of this study was to evaluate the severity of pneumonia in individuals with COVID-19 who were fully vaccinated, partially vaccinated, and unvaccinated, using routine chest computed tomography. Materials and Methods: We analyzed data from patients (aged >18 years) who were hospitalized due to COVID-19 pneumonia between December 2022 and January 2023. Patients who underwent routine chest CT scans were divided into three groups based on their vaccination status. The lobar involvement grading system (0-25) was used to assess the extent of lung injury. The primary outcome was either survival or death. The Pearson chi-square test, Fisher's exact test, and one-way ANOVA were used to compare clinical and imaging features. The receiver operating characteristic (ROC) curve analysis was used to calculate the area under the curve (AUC), sensitivity, and specificity of the CT severity score (CT-SS) in relation to the outcome. Results: Of the 94 patients with COVID-19 pneumonia, 39 patients (41%) were fully vaccinated, 14 (15%) were partially vaccinated, and 41 (44%) were unvaccinated. Among patients with COVID-19 pneumonia, the mean CT severity scores (CT-SS) were 5.9 ± 4.0, 6.5 ± 4.9, and 8.9 ± 4.5 for fully vaccinated individuals, partially vaccinated individuals, and unvaccinated individuals, respectively. The difference was statistically significant (p<0.05). CT-SS of 10.5 or higher was associated with severe pneumonia (100% sensitivity, 81.1% specificity, and an area under the curve of 0.92). Conclusion: COVID-19 vaccination leads to less severe pneumonia based on CT. Fully and partially vaccinated patients with COVID-19 pneumonia have less lung involvement compared to unvaccinated patients. Visual observation by CT imaging provides additional evidence to support the clinical effectiveness of vaccination.

Artificial Intelligence Tool for Detection and Worklist Prioritization Reduces Time to Diagnosis of Incidental Pulmonary Embolism at CT

To evaluate the diagnostic efficacy of artificial intelligence (AI) software in detecting incidental pulmonary embolism (IPE) at CT and shorten the time to diagnosis with use of radiologist reading worklist prioritization. In this study with historical controls and prospective evaluation, regulatory-cleared AI software was evaluated to prioritize IPE on routine chest CT scans with intravenous contrast agent in adult oncology patients. Diagnostic accuracy metrics were calculated, and temporal end points, including detection and notification times (DNTs), were assessed during three time periods (April 2019 to September 2020): routine workflow without AI, human triage without AI, and worklist prioritization with AI. In total, 11 736 CT scans in 6447 oncology patients (mean age, 63 years ± 12 [SD]; 3367 men) were included. Prevalence of IPE was 1.3% (51 of 3837 scans), 1.4% (54 of 3920 scans), and 1.0% (38 of 3979 scans) for the respective time periods. The AI software detected 131 true-positive, 12 false-negative, 31 false-positive, and 11 559 true-negative results, achieving 91.6% sensitivity, 99.7% specificity, 99.9% negative predictive value, and 80.9% positive predictive value. During prospective evaluation, AI-based worklist prioritization reduced the median DNT for IPE-positive examinations to 87 minutes (vs routine workflow of 7714 minutes and human triage of 4973 minutes). Radiologists' missed rate of IPE was significantly reduced from 44.8% (47 of 105 scans) without AI to 2.6% (one of 38 scans) when assisted by the AI tool (P < .001). AI-assisted workflow prioritization of IPE on routine CT scans in oncology patients showed high diagnostic accuracy and significantly shortened the time to diagnosis in a setting with a backlog of examinations.Keywords: CT, Computer Applications, Detection, Diagnosis, Embolism, Thorax, ThrombosisSupplemental material is available for this article.© RSNA, 2023See also the commentary by Elicker in this issue.

CT Scan-Derived Muscle, But Not Fat, Area Independently Predicts Mortality in COVID-19

COVID-19 has demonstrated a highly variable disease course, from asymptomatic to severe illness and eventually death. Clinical parameters, as included in the 4C Mortality Score, can predict mortality accurately in COVID-19. Additionally, CT scan-derived low muscle and high adipose tissue cross-sectional areas (CSAs) have been associated with adverse outcomes in COVID-19. Are CT scan-derived muscle and adipose tissue CSAs associated with 30-day in-hospital mortality in COVID-19, independent of 4C Mortality Score? This was a retrospective cohort analysis of patients with COVID-19 seeking treatment at the ED of two participating hospitals during the first wave of the pandemic. Skeletal muscle and adipose tissue CSAs were collected from routine chest CT-scans at admission. Pectoralis muscle CSA was demarcated manually at the fourth thoracic vertebra, and skeletal muscle and adipose tissue CSA was demarcated at the first lumbar vertebra level. Outcome measures and 4C Mortality Score items were retrieved from medical records. Data from 578 patients were analyzed (64.6%men; mean age, 67.7 ± 13.5 years; 18.2%30-day in-hospital mortality). Patients who died within 30days demonstrated lower pectoralis CSA (median, 32.6 [interquartile range (IQR), 24.3-38.8] vs35.4 [IQR, 27.2-44.2]; P= .002) than survivors, whereas visceral adipose tissue CSA was higher (median, 151.1 [IQR, 93.6-219.7] vs112.9 [IQR, 63.7-174.1]; P= .013). In multivariate analyses, low pectoralis muscle CSA remained associated with 30-day in-hospital mortality when adjusted for 4C Mortality Score (hazard ratio, 0.98; 95%CI, 0.96-1.00; P= .038). CT scan-derived low pectoralis muscle CSA is associated significantly with higher 30-day in-hospital mortality in patients with COVID-19 independently of the 4C Mortality Score.

Individual Trajectories of Bone Mineral Density Reveal Persistent Bone Loss in Bone Sarcoma Patients: A Retrospective Study.

Multiagent chemotherapy offers an undoubted therapeutic benefit to cancer patients, but is also associated with chronic complications in survivors. Osteoporosis affects the quality of life of oncologic patients, especially at the paediatric age. However, very few studies have described the extent of loss of bone mineral density (BMD) in bone sarcoma patients. We analysed a retrospective series of children and adolescents with primary malignant bone tumours (52 osteosarcoma and 31 Ewing sarcoma) and retrieved their BMD at diagnosis and follow-up as Hounsfield units (HU). We studied their individual BMD trajectories before and after chemotherapy up to 5 years, using routine chest CT scan and attenuation thresholds on T12 vertebrae ROI. At one year, bone sarcoma patients showed significant bone loss compared to diagnosis: 17.6% and 17.1% less for OS and EW, respectively. Furthermore, a bone loss of more than 49.2 HU at one-year follow-up was predictive of the persistence of a reduced bone mass over the following 4 years, especially in patients with EW. At 4 years, only 26% and 12.5% of OS and EW, respectively, had recovered or improved their BMD with respect to the onset, suggesting a risk of developing morbidities related to a low BMD in those subjects.

A Fully Automated Deep Learning Pipeline for Multi-Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans.

Body composition on chest CT scans encompasses a set of important imaging biomarkers. This study developed and validated a fully automated analysis pipeline for multi-vertebral level assessment of muscle and adipose tissue on routine chest CT scans. This study retrospectively trained two convolutional neural networks on 629 chest CT scans from 629 patients (55% women; mean age, 67 years ± 10 [standard deviation]) obtained between 2014 and 2017 prior to lobectomy for primary lung cancer at three institutions. A slice-selection network was developed to identify an axial image at the level of the fifth, eighth, and 10th thoracic vertebral bodies. A segmentation network (U-Net) was trained to segment muscle and adipose tissue on an axial image. Radiologist-guided manual-level selection and segmentation generated ground truth. The authors then assessed the predictive performance of their approach for cross-sectional area (CSA) (in centimeters squared) and attenuation (in Hounsfield units) on an independent test set. For the pipeline, median absolute error and intraclass correlation coefficients for both tissues were 3.6% (interquartile range, 1.3%-7.0%) and 0.959-0.998 for the CSA and 1.0 HU (interquartile range, 0.0-2.0 HU) and 0.95-0.99 for median attenuation. This study demonstrates accurate and reliable fully automated multi-vertebral level quantification and characterization of muscle and adipose tissue on routine chest CT scans. Keywords: Skeletal Muscle, Adipose Tissue, CT, Chest, Body Composition Analysis, Convolutional Neural Network (CNN), Supervised Learning Supplemental material is available for this article. © RSNA, 2022.

Prospects and Challenges of Radiomics by Using Nononcologic Routine Chest CT.

Chest CT scans are one of the most common medical imaging procedures. The automatic extraction and quantification of imaging features may help in diagnosis, prognosis of, or treatment decision in cardiovascular, pulmonary, and metabolic diseases. However, an adequate sample size as a statistical necessity for radiomics studies is often difficult to achieve in prospective trials. By exploiting imaging data from clinical routine, a much larger amount of data could be used than in clinical trials. Still, there is only little literature on the implementation of radiomics in clinical routine chest CT scans. Reasons are heterogeneous CT scanning protocols and the resulting technical variability (eg, different slice thicknesses, reconstruction kernels or timings after contrast material administration) in routine CT imaging data. This review summarizes the recent state of the art of studies aiming to develop quantifiable imaging biomarkers at chest CT, such as for osteoporosis, chronic obstructive pulmonary disease, interstitial lung disease, and coronary artery disease. This review explains solutions to overcome heterogeneity in routine data such as the use of imaging repositories, the standardization of radiomic features, algorithmic approaches to improve feature stability, test-retest studies, and the evolution of deep learning for modeling radiomics features. Supplemental material is available for this article. © RSNA, 2020 See also the commentary by Kay in this issue.

Reporting of coronary artery calcification on chest CT studies in breast cancer patients at high risk of cancer therapy related cardiac events

BackgroundThe identification of coronary artery calcification (CAC) detected coincidentally on chest CT exams could assist in cardiovascular risk assessment but may not be reported consistently on clinical studies. Cardiovascular risk factor stratification is important to predict short term cardiac events during cancer therapy and long term cardiac event free survival in cancer patients. We sought to determine the prevalence of CAC and clinical reporting rates in a cohort of cancer patients at high risk of cancer therapy related cardiac events. Methods408 Breast cancer patients who were referred to a cardiac oncology clinic were screened. Inclusion criteria included having had a CT chest and the absence of known coronary disease. Among those screened 263 patients were included in the study. ResultsCAC was identified in 70 patients (26%). CAC was reported in 18% of studies. The reporting rates of CAC increased with the extent of coronary calcification (p < 0.01) and increased during the period of the study (p < 0.05). ConclusionsCAC was commonly detected on chest CT studies in this observational study of breast cancer patients at high risk of cardiac oncology events. The presence of CAC was often not reported clinically but reporting rates have increased over time. Recent SCCT/STR guidelines recommend reporting the presence of CAC on routine chest CT scans in recognition of the importance of CAC as a predictor of cardiovascular events. Reporting of CAC on chest CTs may help to further risk stratify breast cancer patients and improve cardiovascular outcomes in this vulnerable population.

Thoracic CT after peroral endoscopic myotomy for the treatment of achalasia

Peroral endoscopic myotomy (POEM) is a promising new endoscopic method for the treatment of achalasia. The aim of this study was to analyze the value of routine postoperative CT of the chest to detect POEM-associated adverse events. Single-center, retrospective study. Tertiary care center. Between August 2010 and July 2012, 428 patients underwent POEM. Three hundred postprocedure CT POEM patients were retrospectively analyzed and findings correlated with clinical outcome and management. The frequency of postoperative pathological CT scan findings after POEM and the rate of interventions required for adverse event management. The main CT findings could be divided into frequent and reversible sequelae of POEM, pneumomediastinum (48%), pneumoperitoneum (37%), and subcutaneous emphysema (28%), and into potential adverse events such as pneumothorax (17%), pleural effusion (66%), pneumonitis (52%), and focal atelectasis (21%). Only 17 of 50 patients with pneumothorax (5.6% of all patients) and 2 of 200 patients with pleural effusion (0.7% of all patients) required interventional treatment based on clinical symptoms. In 1 patient, a hematoma was observed on a CT scan before any clinical manifestation occurred. Increasing age and the use of air instead of CO2 were associated with an increased rate of pneumothorax (P = .031; 95% confidence interval, 1.002-1.049 and P < .001; 95% confidence interval, 0.012-0.157, respectively). Single-center, retrospective study. Routine chest CT scan for achalasia patients undergoing POEM is probably not warranted because of the high rate of minor and clinically irrelevant findings. The use of CO2 is obligatory to reduce related adverse events.

Acute vascular rejection during antituberculosis therapy in a kidney transplant patient

We report a case of acute vascular rejection occurring during antituberculosis therapy in a patient who had received a kidney transplant. A 29 year-old man was admitted for a protocol biopsy; he had a serum creatinine (S-Cr) level of 1.5 mg/dL 1 year after primary kidney transplantation. Histological examination yielded no evidence of rejection but a routine chest CT scan revealed typical lung tuberculosis and his serum was positive for QFT. We commenced antituberculosis therapy, including rifampicin, on June 29 2012. We paid close attention to the weekly trough tacrolimus (TAC) level but the S-Cr concentration increased to 3.7 mg/dL on October 16 2012, and he was admitted for biopsy. Histological examination revealed, first, a diffuse aggressive infiltration of tubulointerstitial inflammatory cells accompanied by severe tubulitis and mild intimal arteritis and, second, peritubular capillary infiltration by inflammatory cells (including neutrophils). Laboratory data revealed that our patient did not express donor-specific antibody and the peritubular capillaries did not exhibit C4d immunoreactivity. Upon consideration of both histological and laboratory findings, we diagnosed acute vascular rejection of Banff 2007 class ACR IIA. We commenced 3-day sessions of intravenous steroid pulse therapy twice weekly and adjusted the trough TAC level to 5-8 ng/mL by varying the TAC dose. We next performed an allograft biopsy and found no evidence of rejection (the S-Cr level was 2.7 mg/dL on April 1 2013). The present case report demonstrates the difficulties associated with management of TAC-based regimens in kidney transplant patients undergoing antituberculosis therapy. We also review the relevant literature.

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Introduction: ATLS® does not recommend routine chest CT in stable trauma patients. Many centers use routine Chest CT. We assessed the utility of routine Chest CT. Methods: we retrospectively assessed 458 stable trauma patients at our level 1 trauma center that had both a chest x-ray[cx-ray] and Chest CT as part of initial work-up. Assessment of whether CT findings were different from cx-ray findings and if they led to a change in management was noted for each patient. The patients were separated into 2 groups; data correlated group [chest x-ray and Chest CT data] and data non-correlated group. The groups were compared with one-way analysis of variance [ANOVA]. Results: The findings between the chest CT and cx-ray correlated in 273 patients [59.5%] and non-correlated in 186 patients [40.5 %] with CT providing more data. The non-correlated group data analysis showed that there was a change in management related to CT findings in 44 patients [24 % within group and 9.6% overall]. The average revised trauma score[RTS] for the 2 groups was equivalent. The injury severity score was significantly higher for the non-correlated group as compared to the correlated group [14.2 + 0.7 versus 7.6 + 0.6 respectively, p<0.006]. The non-correlated group had a lower calculated probability of survival [92% versus 97% for the correlated group, p<0.006]. Conclusions: The routine Chest CT scan is efficacious in the management of the stable trauma patient. The non-correlation between CT and cx-ray in this population is a better marker for the identification of higher risk trauma patients than RTS.

SU-D-217BCD-04: How Do We Know How Low Can We Go in Lung Cancer Screening CT?

To demonstrate a technique for determining the acceptable radiation dose level for lung cancer screening CT. 20 patients who underwent a clinically indicated routine chest CT scan with 120 kV and 180 quality reference mAs were enrolled in this IRB approved study. Automatic exposure control was used to adjust for patient size. Scanner output, as expressed in CTDIvol, varied accordingly (mean=16.8 mGy, range=7.6 to 26.6 mGy). A previously validated noise insertion software tool developed in our lab was used to simulate scans acquired with reduced dose levels (12.5%, 25%, 50% of the original dose level). Images reconstructed from the same raw data but at the original and simulated, reduced dose levels were randomized and blindly reviewed by three thoracic radiologists. Lung and soft tissue regions were graded for two different imaging tasks: 1) routine diagnostic CT exam of the chest and 2) screening exam of the chest for lung cancer. A 5 point scale was used to rate each exam for each task (1=too noisy, significantly impacted confidence to 5=excellent quality, excellent confidence). Exams were considered acceptable when at least two of the three radiologists gave a score of 3 or higher. The percentage of patients meeting this definition of acceptable was calculated for each imaging task, dose level, and tissue type (lung or soft tissue). The percentages of exams considered acceptable for the purpose of lung cancer screening were 90%, 100%, 100%, 100% (lung tissue) and 85%, 100%, 100%, 100% (soft tissue) at 12.5%, 25%, 50% and 100% of original dose level. For the purpose of routine diagnostic chest CT, the percentage of acceptable exams were 75%, 95%, 100%, 100% (lung tissue) and 35%, 85%, 90%, 100% (soft tissue) at 12.5%, 25%, 50% and 100% of original dose level. At 25% of the dose used for routine diagnostic chest CT at our institution, acceptable image quality for the purpose of CT screening for lung cancer was achieved in 100% of the evaluated cases. This factor of 4 in dose reduction relative to routine chest exams is similar to what was used in the NLST trial.

Determination of Optimal Timing Window for Pulmonary Artery MDCT Angiography

The purpose of our study was to determine the optimal timing window for pulmonary artery MDCT angiography. We prospectively studied 150 patients. Routine chest CT scans were acquired using 1.3 mL/kg of contrast medium (370 mg I/mL) that was injected at a fixed injection duration of 30 seconds, followed by a 10-second saline chase. To measure early contrast enhancement, sequential monitoring scans were obtained every 2 seconds over a fixed level of the main pulmonary artery 5 seconds after the start of the injection. Then helical diagnostic scans were obtained at three different predetermined scanning delays (group A, 25 seconds; group B, 35 seconds; and group C, 45 seconds after the start of the injection). Time-enhancement curves; time to reach 100 H, 200 H, and peak enhancement; and enhancement duration greater than 200 H of the pulmonary artery were measured from the monitoring scan. Contrast enhancements of the pulmonary artery and descending aorta and vascular artifacts were assessed from the diagnostic scan. Times to reach 100 H and 200 H at the pulmonary artery were mean 11 +/- 2.5 (SD) seconds and 16 +/- 3.0 seconds, respectively. Pulmonary artery enhancement duration of greater than 200 H was 25 +/- 2.7 seconds (only obtained in group C). Mean time to peak enhancement (335 +/- 62 H) at the pulmonary artery was 37 seconds. Mean enhancement measured on the diagnostic scan was 294 +/- 43 H, group A; 208 +/- 48 H, group B; and 157 +/- 15 H, group C for the pulmonary artery, and 240 +/- 42 H, group A; 277 +/- 49 H, group B; and 172 +/- 29 H, group C for the aorta (p < 0.01). Artifacts were noted in the superior vena cava (group A, 96.7%; group B, 18.3%; and group C, 0%) and in the subclavian vein (group A, 93.5%; group B, 38.7%; and group C, 0%), (p < 0.05). With our study protocol of a 30-second injection and 10-second saline flush, the optimal temporal window to achieve pulmonary artery enhancement greater than 200 H was from 16 seconds to 41 seconds after the start of the injection.

Persistent left superior vena cava with absent right superior vena cava: Morphological CT features and clinical implications

Here we report a rare case of the persisting left superior vena cava with simultaneous absence of the right superior vena cava. This central venous variation has been identified during a routine chest CT scan as follow-up after colonic cancer in an asymptomatic patient with no previous history of heart diseases. Morphological features of this variation are illustrated on axial CT images and 3D image reconstructions. This anomaly occurs in 0.1% of the general population. In presence with the right superior vena cava it is the most common anatomical variation in the central venous system with a reported occurrence of 0.2–8%. Such condition can be associated with additional congenital cardiovascular malformations and heart diseases or rhythm abnormalities. Diagnosis can be difficult and is often achieved incidentally since hemodynamics in these patients can be normal and clinical symptoms are mostly absent. Important clinical implications include difficulties in central venous access or cardiac pacemaker placement as well as management consequences in cardiothoracic surgery. In conclusion clinicians should be aware of this anomaly and their clinical relevance to avoid possible complications.

Normal cross-sectional dimensions of the thyroid gland on routine chest CT scans.

The purpose of this work was to determine the range of normal measurements for the thyroid gland on chest CT scans and relate it to the dimensions of the trachea. Chest CT scans in 118 patients were examined prospectively for visibility of the thyroid gland and its relationship to the trachea. The greatest transverse dimensions of the lobes and the transverse tracheal diameter were measured. A thyroid/trachea ratio was determined. The mean value for the transverse diameter of the thyroid gland was 28.79 mm (SD 6.57 mm). The right lobe averaged 15.05 mm (SD 3.51 mm). The left lobe averaged 13.74 mm (SD 3.91 mm). Measurements for the trachea showed a mean value of 19.97 mm (SD 2.37 mm). A thyroid/trachea index was calculated with a mean value of 1.46 (SD 0.39). Our investigation provides initial values for assessing the thyroid gland on CT scans, defining the limits of normal and the border zones of abnormal size.