Baseline Computed Tomography Research Articles

Post-COVID-19 pulmonary fibrosis with prognostic risk factors: A study in the hilly state of North India

Context: Coronavirus disease 19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). As it is a novel coronavirus infection, its acute as well as long-term pulmonary alterations in terms of radiological imaging and pathology need to be explored. Aim: To analyze the risk factors associated with the development of pulmonary fibrosis in post-COVID-19 patients. Settings and Design: A retrospective study in a tertiary center in a hilly state of North India. Methods and Material: A retrospective study was carried out in a hilly state of North India during the second wave of the COVID-19 pandemic. A baseline computed tomography (CT) within 1 month and a follow-up CT within 3–6 months of the onset of patients’ symptoms was done. The patients were assigned two groups based on the presence of fibrosis [reticular pattern (inter/intralobular septal thickening), parenchymal bands, bronchiectasis, and/ or honeycombing] on follow-up CT. The patients’ demographic profiles, clinical records, blood laboratory findings, treatment given, baseline CT, and follow-up CT findings were compared between the fibrosis and non-fibrosis groups. Statistical analysis used: The data entry was done in the Microsoft EXCEL spreadsheet, and the final analysis was done with the use of Statistical Package for Social Sciences (SPSS) software, IBM manufacturer, Chicago, USA, ver 25.0. Results: Of the total 72 patients, two had no abnormality on baseline CT. Forty (57.14%) out of 70 patients already had fibrosis on baseline CT, which increased to involve 47 (67.14%) patients on follow-up CT. It was analyzed that old age, smoking, comorbid status, low SpO2, longer hospitalization, lymphopenia, and increased severity of COVID-19 disease were independent risk factors for the development of pulmonary fibrosis in post-COVID-19 pneumonia. Conclusions: A better understanding of the underlying mechanism and pathogenesis can help in filling up of gaps in risk stratification of COVID-19.

Predicting response to immunotherapy in non-small cell lung cancer- from bench to bedside.

Immune checkpoint inhibitor (ICI) therapy is first-line treatment for many advanced non-small cell lung cancer (aNSCLC) patients. Predicting response could help guide selection of intensified or alternative anti-cancer regimens. We hypothesized that radiomics and laboratory variables predictive of ICI response in a murine model would also predict response in aNSCLC patients. Fifteen mice with lung carcinoma tumors implanted in bilateral flanks received ICI. Pre-ICI laboratory and computed tomography (CT) data were evaluated for association with systemic ICI response. Baseline clinical and CT data for 117 aNSCLC patients treated with nivolumab were correlated with overall survival (OS). Models for predicting treatment response were created and subjected to internal cross-validation, with the human model further tested on 42 aNSCLC patients who received pembrolizumab. Models incorporating baseline NLR and identical radiomics (surface-to-mass ratio, average Gray, and 2D kurtosis) predicted ICI response in mice and OS in humans with AUCs of 0.91 and 0.75, respectively. The human model successfully sorted pembrolizumab patients by longer vs. shorter predicted OS (median 35 months vs. 6 months, p=0.026 by log-rank). This study advances precision oncology by non-invasively classifying aNSCLC patients according to ICI response using pre-treatment data only. Interestingly, identical radiomics features and NLR correlated with outcomes in the preclinical study and with ICI response in 2 independent patient cohorts, suggesting translatability of the findings. Future directions include using a radiogenomic approach to optimize modeling of ICI response.

Abstract 11959: The Relationship of Matrix Gla Protein With Coronary and Extracoronary Calcification in the Multi-Ethnic Study of Atherosclerosis

Introduction: Vascular calcification regulators are understudied. Matrix Gla protein (MGP) is a calcification inhibitor, and its inactive dephosphorylated-uncarboxylated (dp-ucMGP) form has been linked to calcification. The longitudinal relationship of dp-ucMGP with coronary and extracoronary artery calcification in large populations is unknown. Hypothesis: Higher levels of dp-ucMGP may be associated with greater coronary artery, ascending thoracic aortic, and descending thoracic aortic calcification (CAC, ATAC, DTAC). Aim: To determine the association of dp-ucMGP with CAC, ATAC, and DTAC. Methods: Calcification was measured on serial thoracic computed tomography (CT) scans in the Multi-Ethnic Study of Atherosclerosis (MESA, n=6814). Dp-ucMGP was measured at baseline in a random subset of available serum samples (n=2663), 2539 included in the fully adjusted models) in participants with a baseline (2000-02) and follow-up CTs at Exam 5 (2010-12) ( InaKtif MGP ELISA, Perkin Elmer, Waltham, MA). Linear mixed effect models were used to determine the association of baseline dp-uc MGP levels with long-term CAC, ATAC, and DTAC incidence and progression. Results: Participants were on average 61 + 9 years, 51.3% women, and 37.7% white. For each one standard deviation (178 pmol/L) increase in dp-ucMGP, CAC increased by 3.44 ([95% CI = 1.68, 5.21], p<0.001) Agatston units/year (AU/year), ATAC increased by 0.63 ([95% CI = 0.27, 0.98], p=0.001) AU/year, and DTAC increased by 8.61 ([95% CI = 4.55, 12.67], p<0.001) AU/year, in fully adjusted models. Conclusion: We found an association of the inactive form of matrix Gla protein, dp-ucMGP, with long-term incidence/progression of CAC, ATAC, and DTAC. Future studies should investigate MGP as a calcification regulator and possible therapeutic target.

Validation of Biomechanical Computed Tomography for Fracture Risk Classification in Metastatic Hormone-sensitive Prostate Cancer

BackgroundGuidelines recommend dual-energy x-ray absorptiometry (DXA) screening to assess fracture risk and benefit from antiresorptive therapy in men with metastatic hormone-sensitive prostate cancer (mHSPC) on androgen deprivation therapy (ADT). However, <30% of eligible patients undergo DXA screening. Biomechanical computed tomography (BCT) is a radiomic technique that measures bone mineral density (BMD) and bone strength from computed tomography (CT) scans. ObjectiveTo evaluate the (1) correlations between BCT- and DXA-assessed BMD, and (2) associations between BCT-assessed metrics and subsequent fracture. Design, setting, and participantsA multicenter retrospective cohort study was conducted among patients with mHSPC between 2013 and 2020 who received CT abdomen/pelvis or positron emission tomography/CT within 48 wk before ADT initiation and during follow-up (48–96 wk after ADT initiation). Outcome measurements and statistical analysisWe used univariate logistic regression to assess the associations between BCT measurements and the primary outcomes of subsequent pathologic and nonpathologic fractures. Results and limitationsAmong 91 eligible patients, the median ([interquartile range) age was 67 yr (62–75), 44 (48.4%) were White, and 41 (45.1%) were Black. During the median follow-up of 82 wk, 17 men (18.6%) developed a pathologic and 15 (16.5%) a nonpathologic fracture. BCT- and DXA-assessed femoral-neck BMD T scores were strongly correlated (R2 = 0.93). On baseline CT, lower BCT-assessed BMD (odds ratio [OR] 1.80, 95% confidence interval or CI [1.10, 3.25], p = 0.03) was associated with an increased risk of a pathologic fracture. Lower femoral strength (OR 1.63, 95% CI [0.99, 2.71], p = 0.06) was marginally associated with an increased risk of a pathologic fracture. Neither BMD (OR 1.52, 95% CI [0.95, 2.63], p = 0.11) nor strength (OR 1.14, 95% CI [0.75, 1.80], p = 0.57) was associated with a nonpathologic fracture. BCT identified nine (9.9%) men eligible for antiresorptive therapy, of whom four (44%) were not treated. Limitations include low fracture numbers resulting in lower power to detect fracture associations. ConclusionsAmong men diagnosed with mHSPC, BCT assessments were strongly correlated with DXA, predicted subsequent pathologic fracture, and identified additional men indicated for antiresorptive therapy. Patient summaryWe assess whether biomechanical computer tomography (BCT) from routine computer tomography (CT) scans can identify fracture risk among patients recently diagnosed with metastatic prostate cancer. We find that BCT and dual-energy x-ray absorptiometry–derived bone mineral density are strongly correlated and that BCT accurately identifies the risk for future fracture. BCT may enable broader fracture risk assessment and facilitate timely interventions to reduce fracture risk in metastatic prostate cancer patients.

Reference Range of CT Value in NC-CBBCT Based on Female Breast Structure.

As a new high-resolution three-dimensional CT imaging technology, the essential reference range of CT values in Cone-beam breast computed tomography (CBBCT) has not been established to date. To determine the reference range of computed tomography (CT) values in CBBCT for clinical breast examination. In total, 913 cases (1167 lateral) were subject to CBBCT. CT values of the glandular tissue, fat and different quadrants and different distances of CBBCT images were analyzed. The nipple and muscle were also evaluated. A total of 672 lateral breasts were included in the normal group for investigation. The reference range of the absolute CT value of the chest wall muscle is -136.68~43.36 HU. The reference range of the absolute CT value of the nipple is 176.39~334.02 HU. The reference range of the absolute CT value of fat is -190.4~-63.67HU, and of glandular tissue is -12.2~199.07HU. Our results firstly established the baseline CT values of Non-contrast CBBCT in female breasts, which will benefit cancer screening and lesion locating. The closer the normal breast fat and glandular tissue is to the nipple, the greater the CT value. The older the age, the lower the density. The CT values of fat are unstable in a distance of less than 5 cm, and the CT values of glandular tissues are relatively stable. The difference between the upper and lower quadrants is significant in the same lateral breast and the same section.

Radiologic Progression of Interstitial Lung Abnormalities following Surgical Resection in Patients with Lung Cancer.

In this study, we aimed to assess the prevalence of interstitial lung abnormalities (ILAs) and investigate the rates and risk factors associated with radiologic ILA progression among patients with lung cancer following surgical resection. Patients who underwent surgical resection for lung cancer at our institution from January 2015 to December 2020 were retrospectively evaluated and grouped according to their ILA status as having no ILAs, equivocal ILAs, or ILAs. Progression was determined by simultaneously reviewing the baseline and corresponding follow-up computed tomography (CT) scans. Among 346 patients (median age: 67 (interquartile range: 60-74) years, 204 (59.0%) men), 22 (6.4%) had equivocal ILAs, and 33 (9.5%) had ILAs detected upon baseline CT. Notably, six patients (6/291; 2.1%) without ILAs upon baseline CT later developed ILAs, and 50% (11/22) of those with equivocal ILAs exhibited progression. Furthermore, 75.8% (25/33) of patients with ILAs upon baseline CT exhibited ILA progression (76.9% and 71.4% with fibrotic and non-fibrotic ILAs, respectively). Multivariate analysis revealed that ILA status was a significant risk factor for ILA progression. ILAs and equivocal ILAs were associated with radiologic ILA progression after surgical resection in patients with lung cancer. Hence, early ILA detection can significantly affect clinical outcomes.

Prognostic utility of body composition parameters based on computed tomography analysis of advanced non-small cell lung cancer treated with immune checkpoint inhibitors

ObjectiveThe purpose of this study was to evaluate the prognostic impact of body composition parameters based on computed tomography (CT) in patients with non-small cell lung cancer (NSCLC) who received ICI treatment.MethodsThis retrospective study analyzed the data from advanced NSCLC patients treated with ICI therapy between 2013 and 2019. We included patients with NSCLC who underwent baseline CT scans. The exclusion criteria included patients who received three or more lines of chemotherapy, those with insufficient clinical information, or those without treatment response evaluation.ResultsA total of 136 patients were enrolled. Among the volumetric body composition parameters, patients in the highest quartiles (Q2–4) of the visceral fat index (VFI) exhibited a higher response rate to ICI therapy than those in the lowest quartile (Q1) of VFI (Q1 vs. Q2–4: 18.2% vs. 43.1%, p = 0.012). Patients with a VFI in Q2–4 had significantly prolonged progression-free survival (PFS) and overall survival (OS) (PFS, Q1 vs. Q2–4: 3.0 months vs. 6.4 months, p = 0.043; OS, Q1 vs. Q2–4: 5.6 months vs. 16.3 months, p = 0.004). Kaplan–Meier analysis based on the VFI and visceral fat Hounsfield unit (HU) revealed that patients with VFI in Q1 and HU in Q2–4 had the worst prognosis.ConclusionsVisceral fat volume is significantly associated with treatment outcomes in ICI-treated patients with NSCLC. Moreover, fat quality may impact the treatment outcomes. This finding underscores the potential significance of both fat compartments and fat quality as prognostic indicators.Critical relevance statementVisceral fat volume is significantly associated with treatment outcomes in ICI-treated patients with non-small cell lung cancer. Moreover, fat quality may impact the treatment outcomes. This finding underscores the potential significance of both fat compartments and fat quality as prognostic indicators.Graphical Key points• We found that visceral fat volume positively correlated with treatment response and survival in patients with non-small cell lung cancer receiving immune checkpoint inhibitors.• Additionally, a trend toward a negative correlation between visceral fat attenuation and survival was observed.• The findings highlight the prognostic utility of fat compartments and fat quality.

COVID-19 impact on liver attenuation by computed tomography: a retrospective cohort study

Introduction. A high prevalence of decreased liver attenuation has been shown in patients with COVID-19, but there is no unequivocal estimate of the effect of disease severity on it. There has been no evaluation of the liver status both before and after COVID-19.Aim: To study the impact of COVID-19 on liver attenuation by two computed tomography (CT) scans: before and after the onset of pneumonia.Material and Methods. Retrospective cohort study was performed. Data of COVID-19 outpatients were analyzed. Inclusion criteria: two chest CT scans, alanine aminotransferase (ALT), aspartate aminotransferase (AST) blood values, polymerase chain reaction to verify SARS-CoV-2. A PCR positive result was a criterion for the COVID-19 presence. The criteria for absence were a negative PCR result on an oropharyngeal swab for SARS-CoV-2, and absence of a lung lesion on both CT scans. The endpoint was a decrease in liver density of more than 10 HU. Two comparison groups have been identified following the achievement of the endpoint. Liver attemuation was analyzed by automatic segmentation, with values less than 40 HU being considered pathologic.Results. Data from 499 patients were selected and two comparison groups were formed: group 1 – liver attenuation decreased by more than 10 HU in the dynamics and group 2 – control group. Liver attenuation on baseline CT was 8.4 HU higher (95% confidence interval (CI) 5.5-11.2; p-value &lt; 0.001) in group 1 versus group 2. Regression analysis showed an association between a decrease in liver attenuation 10 HU or more on follow-up and low liver attenuation on primary CT (odds ratio 0.26 (95% CI 0.1-0.69), p-value = 0.002). Other factors had no significant effect on the liver attenuation change.Conclusion. COVID-19 has no effect on liver attenuation, which may indicate that there is no significant effect of the virus on liver status.

Drug-induced interstitial lung disease after chemoimmunotherapy for extensive-stage small cell lung cancer

ObjectivesThe combination of chemotherapy and immune checkpoint inhibitors (chemo-ICI) has become the new standard of treatment for extensive-stage small cell lung cancer (ES-SCLC). Recently, slight changes in interstitial shadows, defined as interstitial lung abnormalities (ILA), have been identified. In patients with ES-SCLC who received chemo-ICI, there are limited data on the incidence of drug-induced interstitial lung disease (D-ILD) in daily practice and the association between the development of D-ILD and ILA in the baseline computed tomography (CT). Materials and methodsA multicenter, retrospective study was conducted to investigate the incidence of D-ILD, the risk factors for developing D-ILD, progression-free survival (PFS), and overall survival (OS) in patients with ES-SCLC who received chemo-ICI between August 2019 and November 2021. ResultsThis study enrolled 70 patients (median age, 71 years; including 58 men) from nine institutions in Japan. There were 62 patients (89%) treated with carboplatin/etoposide/atezolizumab and 8 patients treated with carboplatin or cisplatin/etoposide/durvalumab. Twenty-nine patients (41.4%) were found to have ILA at baseline CT. Eleven patients (15.7%) developed D-ILD. The proportion of patients with ILA was significantly higher in the group who developed D-ILD than in the group who did not (9/11 (81.8%) vs. 20/59 (33.9%), respectively, P = 0.0057). In addition, the frequency of ground glass attenuation (GGA) and reticulation was higher in patients who developed D-ILD. There was no significant difference in PFS and OS between patients who developed D-ILD and those who did not (median PFS, 8.0 (95% confidence interval (CI), 5.5–9.5) months vs. 5.0 (95% CI, 4.5–5.6) months, respectively, P = 0.11 and median OS, not reached (NR) (95% CI, 8.7–NR) vs. 18.2 (95% CI, 13.2–NR) months, respectively, P = 0.20). ConclusionThe incidence of D-ILD in patients with ES-SCLC who received chemo-ICI in clinical practice was higher than that in clinical trials. Patients with pre-existing ILA were more likely to develop D-ILD.

Chest MRI and CT Predictors of 10-Year All-Cause Mortality in COPD

Pulmonary imaging measurements using magnetic resonance imaging (MRI) and computed tomography (CT) have the potential to deepen our understanding of chronic obstructive pulmonary disease (COPD) by measuring airway and parenchymal pathologic information that cannot be provided by spirometry. Currently, MRI and CT measurements are not included in mortality risk predictions, diagnosis, or COPD staging. We evaluated baseline pulmonary function, MRI and CT measurements alongside imaging texture-features to predict 10-year all-cause mortality in ex-smokers with (n = 93; 31 females; 70 ± 9years) and without (n = 69; 29 females, 69 ± 9years) COPD. CT airway and vessel measurements, helium-3 (3He) MRI ventilation defect percent (VDP) and apparent diffusion coefficients (ADC) were quantified. MRI and CT texture-features were extracted using PyRadiomics (version2.2.0). Associations between 10-year all-cause mortality and all clinical and imaging measurements were evaluated using multivariable regression model odds-ratios. Machine-learning predictive models for 10-year all-cause mortality were evaluated using area-under-receiver-operator-characteristic-curve (AUC), sensitivity and specificity analyses. DLCO (%pred) (HR = 0.955, 95%CI: 0.934-0.976, p < 0.001), MRI ADC (HR = 1.843, 95%CI: 1.260-2.871, p < 0.001), and CT informational-measure-of-correlation (HR = 3.546, 95% CI: 1.660-7.573, p = 0.001) were the strongest predictors of 10-year mortality. A machine-learning model trained on clinical, imaging, and imaging textures was the best predictive model (AUC = 0.82, sensitivity = 83%, specificity = 84%) and outperformed the solely clinical model (AUC = 0.76, sensitivity = 77%, specificity = 79%). In ex-smokers, regardless of COPD status, addition of CT and MR imaging texture measurements to clinical models provided unique prognostic information of mortality risk that can allow for better clinical management.Clinical Trial Registration: www.clinicaltrials.gov NCT02279329

Multi-organ Radiomics-Based Prediction of Future Remnant Liver Hypertrophy Following Portal Vein Embolization

BackgroundPortal vein embolization (PVE) is used to induce remnant liver hypertrophy prior to major hepatectomy. The purpose of this study was to evaluate the predictive value of baseline computed tomography (CT) data for future remnant liver (FRL) hypertrophy after PVE.MethodsIn this retrospective study, all consecutive patients undergoing right-sided PVE with or without hepatic vein embolization between 2018 and 2021 were included. CT volumetry was performed before and after PVE to assess standardized FRL volume (sFRLV). Radiomic features were extracted from baseline CT after segmenting liver (without tumor), spleen and bone marrow. For selecting features that allow classification of response (hypertrophy ≥ 1.33), a stepwise dimension reduction was performed. Logistic regression models were fitted and selected features were tested for their predictive value. Decision curve analysis was performed on the test dataset.ResultsA total of 53 patients with liver tumor were included in this study. sFRLV increased significantly after PVE, with a mean hypertrophy of FRL of 1.5 ± 0.3-fold. sFRLV hypertrophy ≥ 1.33 was reached in 35 (66%) patients. Three independent radiomic features, i.e. liver-, spleen- and bone marrow-associated, differentiated well between responders and non-responders. A logistic regression model revealed the highest accuracy (area under the curve 0.875) for the prediction of response, with sensitivity of 1.0 and specificity of 0.5. Decision curve analysis revealed a positive net benefit when applying the model.ConclusionsThis proof-of-concept study provides first evidence of a potential predictive value of baseline multi-organ radiomics CT data for FRL hypertrophy after PVE.

Investigating the impact of non-gated thoracic CT prior to CTCA to reduce layered testing

To determine the proportion of computed tomography (CT) coronary angiography (CTCA) referrals with coronary artery calcification (CAC) evident on previous non-cardiac CT imaging and how this impacted the diagnostic yield for CTCA, the requirement for additional diagnostic testing, and the associated costs to confirm or refute obstructive coronary artery disease (CAD). A retrospective review of CTCA examinations was undertaken between 01/05/2018 and 31/05/2020 in which the examinations were cross referenced for previous non-gated thoracic CT at Royal United Hospitals Bath. Major epicardial vessel CAC on baseline CT was re-evaluated by published semi-quantitative methods, giving a per-patient CAC score (mild=1-3, moderate=4-6, severe >6). Subsequent incomplete CTCA diagnostic yield, further testing, and cost implications were examined. Of the 2140 CTCA examinations identified, 13% (280/2140) had a preceding non-gated thoracic CT (53% female, age 63±11 years). The incomplete diagnostic rate increased with CAC grade, mild 32%, (RR 12; 95% CI 4-40), moderate 64% (RR 25; 95% CI 8-80), severe 75%, (RR 29; 95% CI 9-94). Additional diagnostic testing occurred in 4% for the mild CAC category, and 14% and 42% for moderate and severe, respectively. When severe CAC was identified on a non-gated thoracic CT a cost saving of £171/patient (dobutamine stress echo [DSE]) and £61/patient (myocardial perfusion scintigraphy [MPS]) was established with a direct to functional testing pathway. In patients referred for CTCA where severe CAC was identified on a preceding non-gated thoracic CT a direct to functional testing altered management in 42% of cases and was cost-effective.

Development of machine learning models for predicting outcome in patients with distal medium vessel occlusions: a retrospective study.

While numerous prognostic factors have been reported for large vessel occlusion (LVO)-acute ischemic stroke (AIS) patients, the same cannot be said for distal medium vessel occlusions (DMVOs). We used machine learning (ML) algorithms to develop a model predicting the short-term outcome of AIS patients with DMVOs using demographic, clinical, and laboratory variables and baseline computed tomography (CT) perfusion (CTP) postprocessing quantitative parameters. In this retrospective cohort study, consecutive patients with AIS admitted to two comprehensive stroke centers between January 1, 2017, and September 1, 2022, were screened. Demographic, clinical, and radiological data were extracted from electronic medical records. The clinical outcome was divided into two categories, with a cut-off defined by the median National Institutes of Health Stroke Scale (NIHSS) shift score. Data preprocessing involved addressing missing values through imputation, scaling with a robust scaler, normalization using min-max normalization, and encoding of categorical variables. The data were split into training and test sets (70:30), and recursive feature elimination (RFE) was employed for feature selection. For ML analyses, XGBoost, LightGBM, CatBoost, multi-layer perceptron, random forest, and logistic regression algorithms were utilized. Performance evaluation involved the receiver operating characteristic (ROC) curve, precision-recall curve (PRC), the area under these curves, accuracy, precision, recall, and Matthews correlation coefficient (MCC). The relative weights of predictor variables were examined using Shapley additive explanations (SHAP). Sixty-nine patients were included and divided into two groups: 35 patients with favorable outcomes and 34 patients with unfavorable outcomes. Utilizing ten selected features, the XGBoost algorithm achieved the best performance in predicting unfavorable outcomes, with an area under the ROC curve (AUROC) of 0.894 and an area under the PRC curve (AUPRC) of 0.756. The SHAP analysis ranked the following features in order of importance for the XGBoost model: mismatch volume, time-to-maximum of the tissue residue function (Tmax) >6 s, diffusion-weighted imaging (DWI) volume, neutrophil-to-platelet ratio (NPR), mean corpuscular volume (MCV), Tmax >10 s, hemoglobin, potassium, hypoperfusion index (HI), and Tmax >8 s. Our ML models, trained on baseline quantitative laboratory and CT parameters, accurately predicted the short-term outcome in patients with DMVOs. These findings may aid clinicians in predicting prognosis and may be helpful for future research.

Computed Tomography Utilization in the Management of Children with Mild Head Trauma.

This study demonstrates the trend of computed tomography (CT) usage for children with mild traumatic brain injury (mTBI) in the context of the initiation of the Safe CT Imaging Collaborative Initiative to promote the Pediatric Emergency Care Applied Research Network (PECARN) rules at the acute care hospitals in New Jersey. We used administrative databases of 10 children's and 59 general hospitals to compare CT rates before 2014-2015, during 2016, and after the initiation of the program (2017-2019). The CT usage rates at baseline and the end of surveillance in children's hospitals (19.2% and 14.2%) were lower than in general hospitals (36.7% and 21.0%), p < 0.0001. The absolute mean difference from baseline to the end of surveillance in children's hospitals was 5.1% compared to a high of 9.7% in general hospitals, medium-high with 13.2%, and 14.0% in a medium volume of pediatric patients (p < 0.001-0.0001). The time-series model demonstrates a positive trend of CT reduction in pediatric patients with mTBI within four years of the program's implementation (p < 0.03-0.001). The primary CT reduction was recorded during the year of program implementation. Regression analysis revealed the significant role of a baseline CT usage rate in predicting the level of CT reduction independent of the volume of pediatric patients and type of hospital.

Early Signs of Elevated Intracranial Pressure on Computed Tomography Correlate With Measured Intracranial Pressure in the Intensive Care Unit and Six-Month Outcome After Moderate to Severe Traumatic Brain Injury.

Traumatic brain injury (TBI) is a leading cause of death and disability in the United States. Early triage and treatment after TBI have been shown to improve outcome. Identifying patients at risk for increased intracranial pressure (ICP) via baseline computed tomography (CT) , however, has not been validated previously in a prospective dataset. We hypothesized that acute CT findings of elevated ICP, combined with direct ICP measurement, hold prognostic value in terms of six-month patient outcome after TBI. Data were obtained from the Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment (ProTECTIII) multi-center clinical trial. Baseline CT scans for 881 participants were individually reviewed by a blinded central neuroradiologist. Five signs of elevated ICP were measured (sulcal obliteration, lateral ventricle compression, third ventricle compression, midline shift, and herniation). Associations between signs of increased ICP and outcomes (six-month functional outcome and death) were assessed. Secondary analyses of 354 patients with recorded ICP monitoring data available explored the relationships between hemorrhage phenotype/anatomic location, sustained ICP ≥20 mm Hg, and surgical intervention(s). Univariate and multi-variate logistic/linear regressions were performed; p < 0.05 is defined as statistically significant. Imaging characteristics associated with ICP in this cohort include sulcal obliteration (p = 0.029) and third ventricular compression (p = 0.039). Univariate regression analyses indicated that increasing combinations of the five defined signs of elevated ICP were associated with death, poor functional outcome, and time to death. There was also an increased likelihood of death if patients required craniotomy (odds ratio [OR] = 4.318, 95% confidence interval [1.330-16.030]) or hemicraniectomy (OR = 2.993 [1.109-8.482]). On multi-variate regression analyses, hemorrhage location was associated with death (posterior fossa, OR = 3.208 [1.120-9.188] and basal ganglia, OR = 3.079 [1.178-8.077]). Volume of hemorrhage >30 cc was also associated with increased death, OR = 3.702 [1.575-8.956]). The proportion of patient hours with sustained ICP ≥20 mm Hg, and maximum ICP ≥20 mm Hg were also directly correlated with increased death (OR = 6 4.99 [7.731-635.51]; and OR = 1.025 [1.004-1.047]), but not with functional outcome. Poor functional outcome was predicted by concurrent presence of all five radiographic signs of elevated ICP (OR = 4.44 [1.514-14.183]) and presence of frontal lobe (OR = 2.951 [1.265-7.067]), subarachnoid (OR = 2.231 [1.067-4.717]), or intraventricular (OR = 2.249 [1.159-4.508]) hemorrhage. Time to death was modulated by total patient days of elevated ICP ≥20 mm Hg (effect size = 3.424 [1.500, 5.439]) in the first two weeks of hospitalization. Sulcal obliteration and third ventricular compression, radiographic signs of elevated ICP, were significantly associated with measurements of ICP ≥20 mm Hg. These radiographic biomarkers were significantly associated with patient outcome. There is potential utility of ICP-related imaging variables in triage and prognostication for patients after moderate-severe TBI.

Proposal of early CT morphological criteria for response of liver metastases to systemic treatments in gastroenteropancreatic neuroendocrine tumors: Alternatives to RECIST.

RECIST 1.1 criteria are commonly used with computed tomography (CT) to evaluate the efficacy of systemic treatments in patients with neuroendocrine tumors (NETs) and liver metastases (LMs), but their relevance is questioned in this setting. We aimed to explore alternative criteria using different numbers of measured LMs and thresholds of size and density variation. We retrospectively studied patients with advanced pancreatic or small intestine NETs with LMs, treated with systemic treatment in the first-and/or second-line, without early progression, in 14 European expert centers. We compared time to treatment failure (TTF) between responders and non-responders according to various criteria defined by 0%, 10%, 20% or 30% decrease in the sum of LM size, and/or by 10%, 15% or 20% decrease in LM density, measured on two, three or five LMs, on baseline (≤1 month before treatment initiation) and first revaluation (≤6 months) contrast-enhanced CT scans. Multivariable Cox proportional hazard models were performed to adjust the association between response criteria and TTF on prognostic factors. We included 129 systemic treatments (long-acting somatostatin analogs 41.9%, chemotherapy 26.4%, targeted therapies 31.8%), administered as first-line (53.5%) or second-line therapies (46.5%) in 91 patients. A decrease ≥10% in the size of three LMs was the response criterion that best predicted prolonged TTF, with significance at multivariable analysis (HR 1.90; 95% CI: 1.06-3.40; p = .03). Conversely, response defined by RECIST 1.1 did not predict prolonged TTF (p = .91), and neither did criteria based on changes in LM density. A ≥10% decrease in size of three LMs could be a more clinically relevant criterion than the current 30% threshold utilized by RECIST 1.1 for the evaluation of treatment efficacy in patients with advanced NETs. Its implementation in clinical trials is mandatory for prospective validation. Criteria based on changes in LM density were not predictive of treatment efficacy. CLINICAL TRIAL REGISTRATION: Registered at CNIL-CERB, Assistance publique hopitaux de Paris as "E-NETNET-L-E-CT" July 2018. No number was assigned. Approved by the Medical Ethics Review Board of University Medical Center Groningen.

Software-based quantitative CT analysis to predict the growth trend of persistent nonsolid pulmonary nodules: a retrospective study

PurposePersistent nonsolid nodules (NSNs) usually exhibit an indolent course and may remain stable for several years; however, some NSNs grow quickly and require surgical excision. Therefore, identifying quantitative features capable of early discrimination between growing and nongrowing NSNs is becoming a crucial aspect of radiological analysis. The main purpose of this study was to evaluate the performance of an open-source software (ImageJ) to predict the future growth of NSNs detected in a Caucasian (Italian) population.Material and methodsWe retrospectively selected 60 NSNs with an axial diameter of 6–30 mm scanned with the same acquisition-reconstruction parameters and the same computed tomography (CT) scanner. Software-based analysis was performed on thin-section CT images using ImageJ. For each NSNs, several quantitative features were extracted from the baseline CT images. The relationships of NSN growth with quantitative CT features and other categorical variables were analyzed using univariate and multivariable logistic regression analyses.ResultsIn multivariable analysis, only the skewness and linear mass density (LMD) were significantly associated with NSN growth, and the skewness was the strongest predictor of growth. In receiver operating characteristic curve analyses, the optimal cutoff values of skewness and LMD were 0.90 and 19.16 mg/mm, respectively. The two predictive models that included the skewness, with or without LMD, exhibited an excellent power for predicting NSN growth.ConclusionAccording to our results, NSNs with a skewness value > 0.90, specifically those with a LMD > 19.16 mg/mm, should require closer follow-up due to their higher growth potential, and higher risk of becoming an active cancer.

Relationship Between Pretreatment Body Composition and Clinical Outcomes in Patients With Metastatic Renal Cell Carcinoma Receiving First-Line Ipilimumab Plus Nivolumab

IntroductionBiomarkers are needed to identify patients with metastatic renal cell carcinoma (mRCC) most likely to benefit from immune checkpoint inhibitors. We examined associations between radiographically assessed body composition (BC) variables and body mass index (BMI) with clinical outcomes for patients with mRCC receiving first-line ipilimumab + nivolumab (ipi/nivo). Patients and MethodsWe retrospectively reviewed all patients with mRCC treated with first-line ipi/nivo at one institution before June 1, 2021 with an analyzable baseline computed tomography (CT) scan. BC variables (skeletal muscle index [SMI], subcutaneous adipose tissue index [SATI], and visceral adipose tissue index [VATI]) were measured using baseline CT scans. Relationships between BC variables and clinical outcomes were examined using Cox proportional hazard regression models. ResultsNinety-nine patients were analyzed (74% male, 64% overweight/obese, 75% low SMI). Controlling for age, IMDC risk, and sex (for BMI analyses), high vs. low SMI (HR=2.433, CI: 1.397-4.238, P=.0017), high vs. low SATI (HR=1.641, CI: 1.023-2.632, P=.0398), and obese BMI (≥ 30 kg/m2) vs. normal/overweight BMI (<30 kg/m2) (HR=1.859, CI: 1.156-2.989, P=.0105) were significantly associated with progression-free survival (PFS). Median overall survival (OS) for low SMI patients was higher (42.74 months, CI: 26.84, NR) than median OS for high SMI patients (27.01 months, CI: 15.28, NR) (adjusted HR=1.728, CI: 0.909-3.285, P=.0952). No BC variables were significantly associated with OS or objective response rate. ConclusionsLow SMI and low SATI were associated with significantly better PFS for patients with mRCC receiving first-line ipi/nivo. Radiographic BC variables may be useful prognostic biomarkers in this setting.

Early Natural Menopause Is Associated With Poor Lung Health and Increased Mortality Among Female Smokers

ABSTRACT Menopause results from the decline of estrogen levels and is driven by ovarian aging. Some tissues, including the lung, may contribute to local estrogen synthesis in the postmenopausal state. Cigarette smoking is the most established factor for early menopause, and previous studies have shown that the menopause transition accelerated age-related decline of lung function following a restrictive disease pattern. In addition, studies have supported a potential synergistic effect of cigarette smoking and menopause on lung function. Delineating the effect of menopause timing and estrogen exposure on subsequent disease development may have important benefits for health maintenance and disease prevention in older women. This study aimed to assess the associations between early menopause and lung biomarkers, lung cancer risk, and cause-specific mortality. Data were obtained from the Pittsburg Lung Screening Study, a community-based research cohort of current and former smokers screened with low-dose computed tomography (CT) at baseline and 1 year later. Menstrual and reproductive history and data on respiratory symptoms were collected through questionnaires. Radiographic emphysema score was calculated from the baseline CT scan. Early menopause was defined as age at menopause of &lt;45 years. The study cohort included female Pittsburg Lung Screening Study participants who reported natural (n = 1038) or surgical (n = 628) menopause at study entry. A total of 1064 participants (63.9%) were current smokers with an average pack-years of 46.1 ± 19.8 at baseline. Early menopause was associated with several pathologies including self-reported wheezing (odds ratio [OR], 1.65; 95% confidence interval [CI], 1.18–2.30; P &lt; 0.01), chronic bronchitis (OR, 1.73; 95% CI, 1.19–2.53; P &lt; 0.01), cardiovascular diseases (OR, 1.87; 95% CI, 1.13–3.11; P = 0.02), radiographic emphysema (OR, 1.70; 95% CI, 1.25–2.31; P &lt; 0.001), and incident airway obstruction (OR, 2.02; 95% CI, 1.03–3.96; P = 0.04) in women with natural menopause, but not surgical menopause except for physician-diagnosed cardiovascular diseases (OR, 4.03; 95% CI, 1.78–9.14; P &lt; 0.001). Trend tests for each of these outcomes in women with natural menopause identified monotonically increasing risk associated with younger age at menopause. Early menopause was associated with lower measurements of the lung function measurements forced expiratory volume in 1 second (FEV1; −104.8 ± 36.7 mL/s; P &lt; 0.01), forced vital capacity (FVC; −78.6 ± 38.2 mL; P = 0.04), and FEV1-to-FVC ratio (−2.1% ± 0.8%; P = 0.01) at baseline in women with natural menopause but not surgical menopause. The use of hormone therapy at any point was associated with higher baseline FEV1 levels and higher FEV1-to-FVC ratio at baseline among women with natural menopause. Early natural menopause was associated with a 40% increased risk of all-cause death with respiratory diseases (hazard ratio [HR], 2.32; 95% CI, 1.52–3.52; P &lt; 0.001), and early menopause was associated with twice the risk of lung cancer-specific mortality (HR, 1.94; 95% CI, 1.05–3.58; P = 0.03). This association was exacerbated by continuous cigarette smoking, with HRs of 4.65 (95% CI, 2.55–8.49; P &lt; 0.001) and 4.61 (95% CI, 2.63–8.07; P &lt; 0.001) for lung cancer and cancer mortality, respectively, among continuous smokers with early menopause compared with women with noncontinuous smoking and nonearly menopause. The results of this study demonstrate that among a postmenopausal cohort of middle-aged and older smokers, natural early menopause is associated with worse lung health and accelerated lung aging.

Growth Regularity of Pulmonary Ground Glass Nodules Based on 3D Reconstruction Technology

Since the popularization of computed tomography (CT) technology, the detection rate of pulmonary ground glass nodules (GGNs) with imaging follow-up as the main management method has increased significantly. The purpose of this study is to quantitatively analyze the changes of pulmonary GGNs during the follow-up process with three-dimensional reconstruction technology, explore the natural progression of pulmonary GGNs, and provide effective basis for clinical guidance for patients to conduct reasonable management of nodules. A total of 115 cases of pulmonary GGNs with regular follow-up in the Combined Outpatient Department of Zhoushan Hospital from March 2015 to November 2022 were enrolled. Quantitative imaging features of nodules were extracted by semi-automatic segmentation of 3D Slicer software to evaluate the growth of nodules and clinical intervention during follow-up. The average baseline age of the patients was (56.9±10.1) yr. The mean follow-up time was (48.8±18.9) months. The two-dimensional diameter of baseline CT scan was (7.9±2.9) mm, and the maximum three-dimensional diameter was (10.1±3.4) mm. The two-dimensional diameter of the last CT scan was (9.9±4.7) mm, and the maximum three-dimensional diameter was (11.4±5.1) mm. A total of 27 cases (23.5%) showed an increase during follow-up, with a median volume doubling time of 822 days and a median mass doubling time of 1,007 days. 32 cases were surgically resected, including 6 cases of invasive adenocarcinoma (IAC), 16 cases of minimally invasive adenocarcinoma (MIA), 8 cases of adenocarcinoma in situ (AIS) and 2 cases of atypical adenomatous hyperplasia (AAH). Five nodules underwent surgical intervention due to the progression of two-dimensional diameter, which was pathologically confirmed as pre-invasive lesions, but their three-dimensional maximum diameter showed no significant change. Nodular morphology, lobulated sign, spiculated sign and vacuole signs all promoted the growth of nodules in univariate analysis. There were significant differences in age, baseline diameter, mean CT value, median CT value, 10% and 90% percentile CT number between the growth group and the stable group (P<0.05). Multivariate Logistic regression analysis showed that age and average CT value were risk factors for nodule growth (P<0.05). Receiver-operating characteristic (ROC) curve analysis results indicated that the age ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU were more likely to accelerate the growth of GGNs. The maximum three-dimensional diameter ≥14.4 mm and the average CT value ≥-495.7 HU may be a higher malignant probability. GGNs show an inert growth process, and the use of three-dimensional measurements during follow-up is of greater significance. For persistent glass grinding nodules ≥63 years old, the baseline three-dimensional maximum diameter ≥9.2 mm, and the average CT value ≥-507.8 HU are more likely to increase. However, most nodules still have good prognosis after progression, and long-term follow-up is safe.