Influenza season influence on outcome of new nodules in the NELSON study

We evaluated the impact of the influenza season on outcome of new lung nodules in a LDCT lung cancer screening trial population. NELSON-trial participants with ≥ 1 new nodule detected in screening rounds two and three were included. Outcome (resolution or persistence) of new nodules detected per season was calculated and compared. Winter (influenza season) was defined as 1st October to 31st March, and compared to the summer (hay-fever season), 1st April to 30th September. Overall, 820 new nodules were reported in 529 participants. Of the total new nodules, 482 (59%) were reported during winter. When considering the outcome of all new nodules, there was no statistically significant association between summer and resolving nodules (OR 1.07 [CI 1.00-1.15], p = 0.066), also when looking at the largest nodule per participant (OR 1.37 [CI 0.95-1.98], p = 0.094). Similarly, there was no statistically significant association between season and screen detected cancers (OR 0.47 [CI 0.18-1.23], p = 0.123). To conclude, in this lung cancer screening population, there was no statistically significant association between influenza season and outcome of new lung nodules. Hence, we recommend new nodule management strategy is not influenced by the season in which the nodule is detected.

Qualitative Evaluation of Common Quantitative Metrics for Clinical Acceptance of Automatic Segmentation: a Case Study on Heart Contouring from CT Images by Deep Learning Algorithms

Organs-at-risk contouring is time consuming and labour intensive. Automation by deep learning algorithms would decrease the workload of radiotherapists and technicians considerably. However, the variety of metrics used for the evaluation of deep learning algorithms make the results of many papers difficult to interpret and compare. In this paper, a qualitative evaluation is done on five established metrics to assess whether their values correlate with clinical usability. A total of 377 CT volumes with heart delineations were randomly selected for training and evaluation. A deep learning algorithm was used to predict the contours of the heart. A total of 101 CT slices from the validation set with the predicted contours were shown to three experienced radiologists. They examined each slice independently whether they would accept or adjust the prediction and if there were (small) mistakes. For each slice, the scores of this qualitative evaluation were then compared with the Sørensen-Dice coefficient (DC), the Hausdorff distance (HD), pixel-wise accuracy, sensitivity and precision. The statistical analysis of the qualitative evaluation and metrics showed a significant correlation. Of the slices with a DC over 0.96 (N = 20) or a 95% HD under 5 voxels (N = 25), no slices were rejected by the readers. Contours with lower DC or higher HD were seen in both rejected and accepted contours. Qualitative evaluation shows that it is difficult to use common quantification metrics as indicator for use in clinic. We might need to change the reporting of quantitative metrics to better reflect clinical acceptance.

Deep learning for automatic calcium scoring in population based cardiovascular screening

Background

High volumes of standardized coronary artery calcium (CAC) scans are generated in screening that need to be scored accurately and efficiently to risk stratify individuals.

Purpose

To evaluate the performance of deep learning based software for automatic coronary calcium scoring in a screening setting.

Methods

Participants from the Robinsca trial that underwent low-dose ECG-triggered cardiac CT for calcium scoring were included. CAC was measured with fully automated deep learning prototype and compared to the original manual assessment of the Robinsca trial. Detection rate, positive Agatston score and risk categorization (0–99, 100–399, ≥400) were compared using McNemar test, ICC, and Cohen's kappa. False negative (FN), false positive (FP) rate and diagnostic accuracy were determined for preventive treatment initiation (cut-off ≥100 AU).

Results

In total, 997 participants were included between December 2015 and June 2016. Median age was 61.0 y (IQR: 11.0) and 54.4% was male. A high agreement for detection was found between deep learning based and manual scoring, κ=0.87 (95% CI 0.85–0.89). Median Agatston score was 58.4 (IQR: 12.3–200.2) and 61.2 (IQR: 13.9–212.9) for deep learning based and manual assessment respectively, ICC was 0.958 (95% CI 0.951–0.964). Reclassification rate was 2.0%, with a very high agreement with κ=0.960 (95% CI: 0.943–0.997), p<0.001. FN rate was 0.7% and FP rate was 0.1% and diagnostic accuracy was 99.2% for initiation of preventive treatment.

Conclusion

Deep learning based software for automatic CAC scoring can be used in a cardiovascular CT screening setting with high accuracy for risk categorization and initiation of preventive treatment.

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Robinsca trial was supported by advanced grant of European Research Council

Diffusion weighted imaging of the breast: Performance of standardized breast tumor tissue selection methods in clinical decision making

Objectives

In breast diffusion weighted imaging (DWI) protocol standardization, it is recently shown that no breast tumor tissue selection (BTTS) method outperformed the others. The purpose of this study is to analyze the feasibility of three fixed-size breast tumor tissue selection (BTTS) methods based on the reproducibility, accuracy and time-measurement in comparison to the largest oval and manual delineation in breast diffusion weighted imaging data.

Methods

This study is performed with a consecutive dataset of 116 breast lesions (98 malignant) of at least 1.0 cm, scanned in accordance with the EUSOBI breast DWI working group recommendations. Reproducibility of the maximum size manual (BTTS1) and of the maximal size round/oval (BTTS2) methods were compared with three smaller fixed-size circular BTTS methods in the middle of each lesion (BTTS3, 0.12 cm³ volume) and at lowest apparent diffusion coefficient (ADC) (BTTS4, 0.12 cm³; BTTS5, 0.24 cm³). Mean ADC values, intraclass-correlation-coefficients (ICCs), area under the curve (AUC) and measurement times (sec) of the 5 BTTS methods were assessed by two observers.

Results

Excellent inter- and intra-observer agreement was found for any BTTS (with ICC 0.88–0.92 and 0.92–0.94, respectively). Significant difference in ADCmean between any pair of BTTS methods was shown (p = <0.001–0.009), except for BTTS2 vs. BTTS3 for observer 1 (p = 0.10). AUCs were comparable between BTTS methods, with highest AUC for BTTS2 (0.89–0.91) and lowest for BTTS4 (0.76–0.85). However, as an indicator of clinical feasibility, BTTS2-3 showed shortest measurement times (10–15 sec) compared to BTTS1, 4–5 (19–39 sec).

Conclusion

The performance of fixed-size BTTS methods, as a potential tool for clinical decision making, shows equal AUC but shorter ADC measurement time compared to manual or oval whole lesion measurements. The advantage of a fixed size BTTS method is the excellent reproducibility. A central fixed breast tumor tissue volume of 0.12 cm³ is the most feasible method for use in clinical practice.

Risk results from screening for a high cardiovascular disease risk by means of traditional risk factor measurement or coronary artery calcium scoring in the ROBINSCA trial

Aims

Screening for a high cardiovascular disease (CVD) risk followed by preventive treatment can potentially reduce coronary heart disease (CHD)-related morbidity and mortality. ROBINSCA (Risk Or Benefit IN Screening for CArdiovascular disease) is a population-based randomized controlled screening trial that investigates the effectiveness of CVD screening in asymptomatic participants using the Systematic COronary Risk Evaluation (SCORE) model or Coronary Artery Calcium (CAC) scoring. This study describes the distributions in risk and treatment in the ROBINSCA trial.

Methods and results

Individuals at expected elevated CVD risk were randomized (1:1:1) into the control arm (n=14,519; usual care); screening arm A (n=14,478; SCORE, 10-year fatal and non-fatal risk); or screening arm B (n=14,450; CAC scoring). Preventive treatment was largely advised according to current Dutch guidelines. Risk and treatment differences between the screening arms were analysed. 12,185 participants (84.2%) in arm A and 12,950 (89.6%) in arm B were screened. 48.7% were women, and median age was 62 (InterQuartile Range 10) years. SCORE screening identified 45.1% at low risk (SCORE&lt;10%), 26.5% at intermediate risk (SCORE 10–20%), and 28.4% at high risk (SCORE≥20%). According to CAC screening, 76.0% were at low risk (Agatston&lt;100), 15.1% at high risk (Agatston 100–399), and 8.9% at very high risk (Agatston≥400). CAC scoring significantly reduced the number of individuals indicated for preventive treatment compared to SCORE (relative reduction women: 37.2%; men: 28.8%).

Conclusion

We showed that compared to risk stratification based on SCORE, CAC scoring classified significantly fewer men and women at increased risk, and less preventive treatment was indicated.

ROBINSCA flowchart

Funding Acknowledgement

Type of funding source: Public grant(s) – EU funding. Main funding source(s): Advanced Research Grant

Relationship between cardiovascular risk factors and coronary calcification in a middle-aged Dutch population: the Imalife study

Background

Systematic COronary Risk Evaluation (SCORE) has been proposed to assess the 10-year risk of fatal cardiovascular diseases, with distinction between low-risk and high-risk countries. Risk modifiers are recommended to further improve risk reclassification, for example the coronary artery calcium (CAC) score. CAC scoring can significantly improve risk prediction for coronary events based on outcome studies. The impact of CAC scoring on risk classification in a middle-aged cohort from a low-risk country in comparison to SCORE is unknown.

Purpose

To assess presence of coronary calcification and association with cardiovascular risk factors and related SCORE risk in a middle-aged population from a low risk country.

Methods

Coronary calcification and classical cardiovascular risk factors were analyzed in 4,083 Dutch participants aged 45–60 years (57.9% women) without a known history of coronary artery disease in the population-based ImaLife (Imaging in Lifelines) study. Individuals underwent non-contrast cardiac CT using third generation dual-source CT. Coronary artery calcium (CAC) scores were quantified using Agatston's method. Age- and sex- specific distributions of CAC categories (0, 1–99, 100–299, ≥300) and percentiles were assessed. Distribution of CAC categories was compared to SCORE risk categories (&lt;1%, ≥1% to 5%, and ≥5%) for low risk countries. Relationship between risk factors and CAC presence was evaluated by logistic regression models. Population attributable fractions (PAFs) of classical risk factors for CAC presence were estimated to investigate potential prevention strategy.

Results

CAC was present in 54.5% of men and in 26.5% of women. With increasing age, an increasing percentage had a positive CAC score, from 38.1% of men and 15.2% of women at age 45–49 years, to 66.9% of men and 36.6% of women at age 55–60. Mean SCORE was 1.3% (2.0% in men, 0.7% in women). In SCORE risk &lt;1%, 32.7% of men and 17.1% of women had CAC. In men with SCORE risk ≥5% (0.1% of women), 26.9% had no CAC. Overall PAF for presence of CAC of the classical risk factors was 18.5% in men and 31.4% in women. PAF was highest for hypertension (in men 8.0%, 95% CI 4.2–11.8%; in women 13.1%, 95% CI 7.9–18.2%) followed by hypercholesterolemia and obesity.

Conclusion

In this middle-aged Dutch cohort, slightly over half of men and a quarter of women had any CAC. With age there was an increase in CAC presence for both sexes. Only a minor proportion of CAC presence was attributable to classical risk factors. This provides further support that CAC scoring can impact risk classification in a middle-aged population of a low-risk country.

Funding Acknowledgement

Type of funding source: Other. Main funding source(s): The ImaLife study is supported by an institutional research grant from Siemens Healthineers and by the Ministry of Economic Affairs and Climate Policy by means of the PPP Allowance made available by the Top Sector Life Sciences & Health to stimulate public-private partnerships.

Implementation study of CT calcium score in patients with atypical angina pectoris and non-specific thoracic complaints in primary care: rationale, objectives, and design of the CONCRETE study

Background

Identifying and excluding coronary artery diseases (CAD) in patients with atypical angina pectoris (AP) and non-specific thoracic complaints is a challenge for general practitioners (GPs). It is unclear what the best diagnostic and prognostic strategy is for these patients in primary care. Computed Tomography coronary calcium scoring (CT CCS) has a high sensitivity for early diagnosis and exclusion of CAD. However, CT CCS has not been tested in a primary care setting. In the CONCRETE study, the impact of direct access of GPs to CT CCS on management and diagnosis will be investigated. CONCRETE is the abbreviation for “COroNary Calcium scoring as fiRst-linE Test to dEtect and exclude coronary artery disease in GPs patients with stable chest pain.” Currently, we present the rationale, objectives and design of this study.

Purpose

The purpose of CONCRETE is to study the implementation of CT CCS in primary care, and determine the effects on GP office level. The primary objective is to determine the increase in detection/treatment rate of CAD in GP offices with CT CCS, compared to GP offices with standard of care.

Methods

CONCRETE is an implementation study with a cluster randomized design, in which direct access to CT CCS in a group of 40 GP offices is compared to the standard of care in a control group of 40 GP offices. In both arms, inclusion of 800 patients with atypical angina pectoris and non-specific thoracic complaints is intended.

Results

Recruitment of GP offices and participants started in January 2019. First results will be presented.

Conclusion

CONCRETE will determine whether access to CT CCS will lead to earlier and more effective detection or exclusion of CAD in GP patients with atypical angina pectoris and non-specific thoracic complaints, in comparison to the standard of care. Implementation of the study findings could initiate a change in the (Dutch) GP healthcare policy, for these patients in primary care.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): Dutch Heart Foundation

Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis

Background

Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC).

Methods and findings

In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ≥ 800 s/mm² were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I²) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72–0.89), 0.79 (0.65–0.89), 0.88 (0.85–0.90) for BTTS1; 0.91 (0.89–0.93), 0.84 (0.80–0.87), 0.94 (0.91–0.96) for BTTS2; 0.89 (0.86–0.92), 0.90 (0.85–0.93), 0.95 (0.93–0.96) for BTTS3 and 0.90 (0.86–0.93), 0.84 (0.81–0.87), 0.86 (0.82–0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I² = 95).

Conclusions

None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.

P3397Risk Or Benefit IN Screening for CArdiovascular disease (ROBINSCA): results from screening for a high cardiovascular disease risk by using a risk prediction model or coronary artery calcium scoring

Introduction

The ROBINSCA (Risk Or Benefit IN Screening for CArdiovascular disease) trial is a large-scale population-based randomized controlled screening trial with the aim to investigate whether screening for a high risk of cardiovascular disease (CVD) by means of either the Systematic COronary Risk Evaluation (SCORE) model or coronary artery calcium (CAC) scoring followed by preventive treatment is effective in reducing morbidity and mortality from coronary heart disease (CHD). This study shows the results of the CVD risks as assessed by the two screening tools.

Methods

Based on the Dutch population registry, 394,058 men aged 45–74 years and women aged 55–74 years received an information brochure, an invitation to participate in the trial, a baseline questionnaire with waist circumference tape and an informed consent form. Eligible individuals with an expected high CVD risk were randomized (1:1:1) into a control arm (n=14,519), intervention arm A (n=14,478) or intervention arm B (n=14,450). In the control arm, usual care was continued. In intervention arm A, participants were screened for a high risk of CVD using the SCORE model based on traditional risk factors. In intervention arm B, CAC scoring after computed tomography scanning was used for screening. After screening en risk communication, preventive treatment according to the Dutch guidelines is advised for high risk persons.

Results

Screening uptake was 84.2% in intervention arm A and 89.6% in intervention arm B. Of the screened participants, 48.7% was female, median age at screening was 62 (Interquartile Range 10), 35.2% was high educated, 19.6% was baseline smoker and 41.4% had a positive family history of myocardial infarction. The assessed CVD risk status according to SCORE screening was stratified into three risk categories; 45.1% was at low risk (SCORE<10%), 26.5% was at intermediate risk (SCORE 10–20%), and 28.4% was at high risk (SCORE ≥20%). According to CAC screening, 76.0% was at low risk (Agatston <100), 15.1% was at high risk (Agatston 100–399), and 8.9% was at very high risk (Agatston ≥400). Associations between baseline variables and increased CVD risk will be analyzed soon and will be available in summer 2019.

Conclusions

Using different screening tools resulted in reclassification of the CVD risk. CAC screening caused a substantial shift to more low risk individuals. This might, when screening is found to be effective, lead to less overtreatment in prevention of CVD events. Future 5-year follow-up data should provide evidence about whether population-based screening with subsequent preventive treatment is (cost-)effective in reducing CHD-related morbidity and mortality.

P5309Age and gender distributions of coronary artery calcium in the Dutch adult population: preliminary results of the ImaLife study

Background

Coronary artery calcium (CAC) scoring is a promising tool for cardiovascular risk classification. Population-based reference values are important for the clinical interpretation of CAC scores.

Purpose

To establish standards of CAC distributions by age and gender in an unselected Dutch population, which can be used to determine reference values.

Methods

ImaLife (Imaging in Lifelines) is a computed tomography (CT) based substudy of the Lifelines cohort, with a primary aim to establish reference values of imaging biomarkers for early stages of coronary artery disease in adults (above 45 years old). In total, 12,000 participants will be enrolled from an unselected adult population in the northern Netherlands for CAC scoring with third generation dual-source CT. CAC is quantified with dedicated commercial software using the Agatston method.

Results

Included so far were 3,702 participants (57.5% females, mean age 54 years, range 45–82 years). CAC was present in 39.2% of participants, with a higher prevalence of CAC in men (55.3%) than in women (27.3%). CAC scores increased with increasing age in both genders. The percentiles of CAC scores by age and gender groups are summarized in the table.

Agatston CAC score percentiles by age and gender Percentiles Women – Age, years Men – Age, years 45–49 50–54 55–59 60–64 65∼ 45–49 50–54 55–59 60–64 65∼ N 505 634 719 260 10 355 473 543 185 18 25th 0 0 0 0 0 0 0 0 1 75 50th 0 0 0 0 4 0 1 6 22 556 75th 0 0 6 33 386 6 21 72 129 751 90th 4 26 77 120 1037 49 154 242 500 1803

Conclusion

This preliminary result presents CAC distribution by age and gender in a middle-aged unselected Dutch population. Compared with the Heinz Nixdorf Recall study, CAC scores in our cohort for both genders were lower in the 5-year age groups between 45 and 64 years. Based on the overall data, expected within 2 years, reference values of CAC for the Dutch population can be established.

P1555Agreement of coronary calcium scoring on chest CT and ECG triggered cardiac CT: a population-based study

Background

Low-dose chest computed tomography (CT) is increasingly used in lung cancer screening. The heart is inherently visualized on chest CT. Coronary artery calcium (CAC) identified on chest scans has predictive value for risk of cardiovascular disease. There is discussion whether non-ECG-triggered chest CT is reliable for CAC scoring.

Purpose

To investigate the agreement between chest CT and ECG-triggered cardiac CT in CAC identification and risk classification.

Methods

We included 1000 ImaLife participants who underwent a cardiac scan immediately followed by a non-ECG triggered chest scan. Third-generation dual-source CT and dedicated software were used for scan acquisition and CAC measurement. Chest scans were analyzed after cardiac scans with an interval of at least a month and in a different order. To ensure a comparable prevalence of CAC with previous studies and adequate samples in CAC strata, after the inclusion of the 500th consecutive participants with zero CAC, only participants with >0 CAC based on dedicated cardiac CT were included. CAC scores were divided into four risk strata: 0, 1–99, 100–399, 400. Kappa was used to assess agreement in CAC identification (0 versus >0) and risk classification.

Results

The mean age was 54 years (range 45–77), 42.5% were women, average body mass index (BMI) was 26.1kg/m2. Compared with dedicated cardiac CT, non-ECG triggered chest CT had an accuracy of 0.97, sensitivity of 0.96 and specificity of 0.99 for identifying CAC, and agreement between scans was very high (kappa 0.95) for CAC presence. In terms of CAC risk strata, chest CT had a very high agreement with cardiac CT (kappa 0.95). Total misclassification rate of CAC strata was 6.5%, with most misclassified cases shifting one risk category downward (55/65, 85%). BMI of discordant pairs was significantly higher than concordant pairs, while no difference in heart rate was found.

Conclusion

Non-ECG triggered chest CT may be reliably used for CAC identification and risk classification since chest CT has very high agreement with dedicated cardiac CT results.

Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease

OBJECTIVES

The purpose of this study was to analyze the prognostic value of dynamic CT perfusion imaging (CTP) and CT derived fractional flow reserve (CT-FFR) for major adverse cardiac events (MACE).

METHODS

81 patients from 4 institutions underwent coronary computed tomography angiography (CCTA) with dynamic CTP imaging and CT-FFR analysis. Patients were followed-up at 6, 12, and 18 months after imaging. MACE were defined as cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, or revascularization. CT-FFR was computed for each major coronary artery using an artificial intelligence-based application. CTP studies were analyzed per vessel territory using an index myocardial blood flow, the ratio between territory and global MBF. The prognostic value of CCTA, CT-FFR, and CTP was investigated with a univariate and multivariate Cox proportional hazards regression model.

RESULTS

243 vessels in 81 patients were interrogated by CCTA with CT-FFR and 243 vessel territories (1296 segments) were evaluated with dynamic CTP imaging. Of the 81 patients, 25 (31%) experienced MACE during follow-up. In univariate analysis, a positive index-MBF resulted in the largest risk for MACE (HR 11.4) compared to CCTA (HR 2.6) and CT-FFR (HR 4.6). In multivariate analysis, including clinical factors, CCTA, CT-FFR, and index-MBF, only index-MBF significantly contributed to the risk of MACE (HR 10.1), unlike CCTA (HR 1.2) and CT-FFR (HR 2.2).

CONCLUSION

Our study provides initial evidence that dynamic CTP alone has the highest prognostic value for MACE compared to CCTA and CT-FFR individually or a combination of the three, independent of clinical risk factors.

Respiratory level tracking with visual biofeedback for consistent breath-hold level with potential application in image-guided interventions

BACKGROUND

To present and evaluate a new respiratory level biofeedback system that aids the patient to return to a consistent breath-hold level with potential application in image-guided interventions.

METHODS

The study was approved by the local ethics committee and written informed consent was waived. Respiratory motion was recorded in eight healthy volunteers in the supine and prone positions, using a depth camera that measures the mean distance to thorax, abdomen and back. Volunteers were provided with real-time visual biofeedback on a screen, as a ball moving up and down with respiratory motion. For validation purposes, a conversion factor from mean distance (in mm) to relative lung volume (in mL) was determined using spirometry. Subsequently, without spirometry, volunteers were given breathing instructions and were asked to return to their initial breath-hold level at expiration ten times, in both positions, with and without visual biofeedback. For both positions, the median and interquartile range (IQR) of the absolute error in lung volume from initial breath-hold were determined with and without biofeedback and compared using Wilcoxon signed rank tests.

RESULTS

Without visual biofeedback, the median difference from initial breath-hold was 124.6 mL (IQR 55.7-259.7 mL) for the supine position and 156.3 mL (IQR 90.9-334.7 mL) for the prone position. With the biofeedback, the difference was significantly decreased to 32.7 mL (IQR 12.8-59.6 mL) (p < 0.001) and 22.3 mL (IQR 7.7-47.0 mL) (p < 0.001), respectively.

CONCLUSIONS

The use of a depth camera to provide visual biofeedback increased the reproducibility of breath-hold expiration level in healthy volunteers, with a potential to eliminate targeting errors caused by respiratory movement during lung image-guided procedures.

Non-invasive assessment of coronary artery geometry using coronary CTA

AIM

To assess the association of coronary artery geometry with the severity of coronary artery disease (CAD).

METHODS

73 asymptomatic individuals at increased risk of CAD due to peripheral vascular disease (18 women, mean age 63.5 ± 8.2 years) underwent coronary computed tomography angiography (coronary CTA) using first generation dual-source CT. Curvature and tortuosity of the coronary arteries were quantified using semi-automatically generated centerlines. Measurements were performed for individual segments and for the entire artery. Coronary segments were labeled according to the presence of significant stenosis, defined as >70% luminal narrowing, and the presence of plaque. Comparisons were made by segment and by artery, using linear mixed models.

RESULTS

Overall, median curvature and tortuosity were, respectively, 0.094 [0.071; 0.120] and 1.080 [1.040; 1.120] on a per-segment level, and 0.096 [0.078; 0.118] and 1.175 [1.090; 1.420] on a per-artery level. Curvature was associated with significant stenosis at a per-segment (p < 0.001) and per-artery level (p = 0.002). Curvature was 16.7% higher for segments with stenosis, and 13.8% higher for arteries with stenosis. Tortuosity was associated with significant stenosis only at the per-segment level (p = 0.002). Curvature was related to the presence of plaque at the per-segment (p < 0.001) and per-artery level (p < 0.001), tortuosity was only related to plaque at the per-segment level (p < 0.001).

CONCLUSION

Coronary artery geometry as derived from coronary CTA is related to the presence of plaque and significant stenosis.

Diagnostic performance of semi-quantitative and quantitative stress CMR perfusion analysis: a meta-analysis

BACKGROUND

Stress cardiovascular magnetic resonance (CMR) perfusion imaging is a promising modality for the evaluation of coronary artery disease (CAD) due to high spatial resolution and absence of radiation. Semi-quantitative and quantitative analysis of CMR perfusion are based on signal-intensity curves produced during the first-pass of gadolinium contrast. Multiple semi-quantitative and quantitative parameters have been introduced. Diagnostic performance of these parameters varies extensively among studies and standardized protocols are lacking. This study aims to determine the diagnostic accuracy of semi- quantitative and quantitative CMR perfusion parameters, compared to multiple reference standards.

METHOD

Pubmed, WebOfScience, and Embase were systematically searched using predefined criteria (3272 articles). A check for duplicates was performed (1967 articles). Eligibility and relevance of the articles was determined by two reviewers using pre-defined criteria. The primary data extraction was performed independently by two researchers with the use of a predefined template. Differences in extracted data were resolved by discussion between the two researchers. The quality of the included studies was assessed using the 'Quality Assessment of Diagnostic Accuracy Studies Tool' (QUADAS-2). True positives, false positives, true negatives, and false negatives were subtracted/calculated from the articles. The principal summary measures used to assess diagnostic accuracy were sensitivity, specificity, andarea under the receiver operating curve (AUC). Data was pooled according to analysis territory, reference standard and perfusion parameter.

RESULTS

Twenty-two articles were eligible based on the predefined study eligibility criteria. The pooled diagnostic accuracy for segment-, territory- and patient-based analyses showed good diagnostic performance with sensitivity of 0.88, 0.82, and 0.83, specificity of 0.72, 0.83, and 0.76 and AUC of 0.90, 0.84, and 0.87, respectively. In per territory analysis our results show similar diagnostic accuracy comparing anatomical (AUC 0.86(0.83-0.89)) and functional reference standards (AUC 0.88(0.84-0.90)). Only the per territory analysis sensitivity did not show significant heterogeneity. None of the groups showed signs of publication bias.

CONCLUSIONS

The clinical value of semi-quantitative and quantitative CMR perfusion analysis remains uncertain due to extensive inter-study heterogeneity and large differences in CMR perfusion acquisition protocols, reference standards, and methods of assessment of myocardial perfusion parameters. For wide spread implementation, standardization of CMR perfusion techniques is essential.

TRIAL REGISTRATION

CRD42016040176 .

Bone density loss on computed tomography at 3-year follow-up in current compared to former male smokers

OBJECTIVES

Cigarette smoking negatively affects bone quality and increases fracture risk. Little is known on the effect of smoking cessation and computed tomography (CT)-derived bone mineral density (BMD) decline in the spine. We evaluated the association of current and former smoking with BMD decline after 3-year follow-up.

METHODS

Male current and former smokers participating in a lung cancer screening trial who underwent baseline and 3-year follow-up CT were included. BMD was measured by manual placement of a region of interest in the first lumbar vertebra and expressed in Hounsfield Unit (HU). Multiple linear regression analysis was used to evaluate the association between pack years smoked and smoking status with BMD decline.

RESULTS

408 participants were included with median (25th-75th percentile) age of 59.4 (55.9-63.5) years. At the start of the study, 197 (48.3%) participants were current smokers and 211 (51.7%) were former smokers and had a similar amount of pack years. Current smokers had quit smoking for 6 (4-8) years prior to inclusion. There was no difference in BMD between current and former smokers at baseline (109±34 HU vs. 108±32 HU, p=0.96). At 3-year follow-up, current smokers had a mean BMD decline of -3±13 HU (p=0.001), while BMD in former smokers did not change as compared to baseline (1±13 HU, p=0.34). After adjustment for BMD at baseline and body mass index, current smoking was independently associated with BMD decline (-3.8 HU, p=0.003). Age, pack years, and the presence of a fracture at baseline did not associate with BMD decline.

CONCLUSIONS

Current smokers showed a more rapid BMD decline over a 3-year period compared to former smokers. This information might be important to identify subjects at risk for osteoporosis and emphasizes the importance of smoking cessation in light of BMD decline.

Free DICOM de-identification tools in clinical research: functioning and safety of patient privacy

Purpose

To compare non-commercial DICOM toolkits for their de-identification ability in removing a patient's personal health information (PHI) from a DICOM header.

Materials and Methods

Ten DICOM toolkits were selected for de-identification tests. Tests were performed by using the system’s default de-identification profile and, subsequently, the tools' best adjusted settings. We aimed to eliminate fifty elements considered to contain identifying patient information. The tools were also examined for their respective methods of customization.

Results

Only one tool was able to de-identify all required elements with the default setting. Not all of the toolkits provide a customizable de-identification profile. Six tools allowed changes by selecting the provided profiles, giving input through a graphical user interface (GUI) or configuration text file, or providing the appropriate command-line arguments. Using adjusted settings, four of those six toolkits were able to perform full de-identification.

Conclusion

Only five tools could properly de-identify the defined DICOM elements, and in four cases, only after careful customization. Therefore, free DICOM toolkits should be used with extreme care to prevent the risk of disclosing PHI, especially when using the default configuration. In case optimal security is required, one of the five toolkits is proposed.

Key Points

• Free DICOM toolkits should be carefully used to prevent patient identity disclosure.

• Each DICOM tool produces its own specific outcomes from the de-identification process.

• In case optimal security is required, using one DICOM toolkit is proposed.

A web-based institutional DICOM distribution system with the integration of the Clinical Trial Processor (CTP)

To develop and test a fast and easy rule-based web-environment with optional de-identification of imaging data to facilitate data distribution within a hospital environment. A web interface was built using Hypertext Preprocessor (PHP), an open source scripting language for web development, and Java with SQL Server to handle the database. The system allows for the selection of patient data and for de-identifying these when necessary. Using the services provided by the RSNA Clinical Trial Processor (CTP), the selected images were pushed to the appropriate services using a protocol based on the module created for the associated task. Five pipelines, each performing a different task, were set up in the server. In a 75 month period, more than 2,000,000 images are transferred and de-identified in a proper manner while 20,000,000 images are moved from one node to another without de-identification. While maintaining a high level of security and stability, the proposed system is easy to setup, it integrate well with our clinical and research practice and it provides a fast and accurate vendor-neutral process of transferring, de-identifying, and storing DICOM images. Its ability to run different de-identification processes in parallel pipelines is a major advantage in both clinical and research setting.

Relationship between epicardial adipose tissue and subclinical coronary artery disease in patients with extra-cardiac arterial disease

OBJECTIVE

Epicardial adipose tissue (EAT) and mediastinal adipose tissue (MAT) are linked to coronary artery disease (CAD). The association between EAT, MAT, and severity of CAD in known extra-cardiac arterial disease was investigated.

DESIGN AND METHODS

Sixty-five cardiac asymptomatic patients (mean age 65 ± 8 years, 69% male) with peripheral arterial disease, carotid stenosis, or aortic aneurysm underwent coronary computed tomography angiography. Patients were divided into non-significant (<50% stenosis, N = 35), single vessel (N = 15) and multi-vessel CAD (N = 15). EAT and MAT were quantified on computed tomography images using volumetric software.

RESULTS

Subgroups did not significantly differ by age, gender, or cardiovascular risk factors. Median EAT was 99.5, 98.0, and 112.0 cm(3) (P = 0.38) and median MAT was 66.0, 90.0, and 81.0 cm(3) (P = 0.53) for non-significant, single vessel, and multi-vessel CAD, respectively. In age- and gender-adjusted analysis, only EAT was significantly associated with CAD (odds ratio [OR] 1.12 [95% confidence interval, 1.01-1.25] per 10 cm(3) increase in EAT; P = 0.04). This remained in multivariate-adjusted analysis (OR 1.21 [1.04-1.39]; P = 0.01).

CONCLUSIONS

In patients with known extra-cardiac arterial disease, CAD is correlated with EAT, but not with MAT. These results suggest that EAT has a local effect on coronary atherosclerosis, apart from the endocrine effect of visceral fat.

Impact of cross-enterprise data sharing on portable media with decentralised upload of DICOM data into PACS

Objectives

To evaluate portable media utilisation for image data sharing between enterprises. To predict the costs required to keep up with the trend. To identify related problems.

Methods

A software package was developed to include patient image data from CD into our normal workflow. The trend in the workload of CDs that were uploaded into a Picture Archiving and Communication System (PACS) over 89 months was analysed. The average number of images per month (and per investigation) was calculated to provide the estimation of storage and cost required in the whole process.

Results

All Digital Imaging and Communications in Medicine (DICOM) files can be read from compact disc (CD) on any workstation in the hospital, processed quickly to the central server and checked after storage using the software tool. A total of 33,982,404 images from 88,952 CDs have been stored into the PACS system. In recent years, the stored images have reached an average of 4.2 terabytes (TB) uncompressed annually.

Conclusion

Integrated information about patients is clearly needed to provide easy and timely access to these data. The steadily growing storage can be solved by a more automated approach to portable media handling or the installation and acceptance of network-based transfer using cross-enterprise document sharing (XDS).

Key points

• Rapid assimilation of external imaging into a PACS system is essential.

• But data distribution using portable media also carries some disadvantages.

• A DICOM data uploader incorporates studies from portable media to hospital workflow.

• Automated media handling or XDS should solve the steadily growing storage problem.

• Software improvements will facilitate the steady increase in the amount of CDs processed.

Inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-row CT: an anthropomorphic phantom study

OBJECTIVE

To assess inter- and intrascanner variability in volumetry of solid pulmonary nodules in an anthropomorphic thoracic phantom using low-dose CT.

METHODS

Five spherical solid artificial nodules [diameters 3, 5, 8, 10 and 12 mm; CT density +100 Hounsfield units (HU)] were randomly placed inside an anthropomorphic thoracic phantom in different combinations. The phantom was examined on two 64-row multidetector CT (64-MDCT) systems (CT-A and CT-B) from different vendors with a low-dose protocol. Each CT examination was performed three times. The CT examinations were evaluated twice by independent blinded observers. Nodule volume was semi-automatically measured by dedicated software. Interscanner variability was evaluated by Bland-Altman analysis and expressed as 95% confidence interval (CI) of relative differences. Intrascanner variability was expressed as 95% CI of relative variation from the mean.

RESULTS

No significant difference in CT-derived volume was found between CT-A and CT-B, except for the 3-mm nodules (p<0.05). The 95% CI of interscanner variability was within ±41.6%, ±18.2% and ±4.9% for 3, 5 and ≥8 mm nodules, respectively. The 95% CI of intrascanner variability was within ±28.6%, ±13.4% and ±2.6% for 3, 5 and ≥8 mm nodules, respectively.

CONCLUSION

Different 64-MDCT scanners in low-dose settings yield good agreement in volumetry of artificial pulmonary nodules between 5 mm and 12 mm in diameter. Inter- and intrascanner variability decreases at a larger nodule size to a maximum of 4.9% for ≥8 mm nodules.

ADVANCES IN KNOWLEDGE

The commonly accepted cut-off of 25% to determine nodule growth has the potential to be reduced for ≥8 mm nodules. This offers the possibility of reducing the interval for repeated CT scans in lung cancer screenings.

Assessment of thermal sensitivity of CT during heating of liver: an ex vivo study

OBJECTIVES

The purpose of this study was to assess the thermal sensitivity of CT during heating of ex-vivo animal liver.

METHODS

Pig liver was indirectly heated from 20 to 90 °C by passage of hot air through a plastic tube. The temperature in the heated liver was measured using calibrated thermocouples. In addition, image acquisition was performed with a multislice CT scanner before and during heating of the liver sample. The reconstructed CT images were then analysed to assess the change of CT number as a function of temperature.

RESULTS

During heating, a decrease in CT numbers was observed as a hypodense area on the CT images. In addition, the hypodense area extended outward from the heat source during heating. The analysis showed a linear decrease of CT number as a function of temperature. From this relationship, we derived a thermal sensitivity of CT for pig liver tissue of -0.54±0.03 HU °C(-1) with an r(2) value of 0.91.

CONCLUSIONS

The assessment of the thermal sensitivity of CT in ex-vivo pig liver tissue showed a linear dependency on temperature ≤90 °C. This result may be beneficial for the application of isotherms or thermal maps in CT images of liver tissue.

Generalisability of the results of the Dutch-Belgian randomised controlled lung cancer CT screening trial (NELSON): does self-selection play a role?

The degree of self-selection in the Dutch-Belgian randomised controlled lung cancer screening trial (NELSON) was determined to assess the generalisability of the study results. 335,441 (mainly) men born in 1928-1953 received a questionnaire. Of the respondents (32%), eligible subjects were invited to participate (19%). Fifty-five percent gave informed consent and was randomised. Background characteristics were compared between male respondents on the first questionnaire (n = 92,802), eligible subjects among them (n = 18,570) and those randomised (n = 10,627) and Statistics Netherlands 2002-2005 (SN) (n = 5289) or GLOBE study-data (Dutch cohort) (n = 696). Initial respondents were less likely to be highly educated (OR(adj) = 0.84; 95% CI: 0.74-0.96) and comprised of significantly less current smokers (OR(adj) = 0.65; 95% CI: 0.61-0.69) compared to the general population. These current smokers smoked more heavily (OR(adj) = 1.23; 95% CI: 1.10-1.37), but for a shorter time-period (respondents: 31, SN: 42 years, p < 0.001). Age, general health, BMI, alcohol use and cancer prevalence were comparable. The randomised population was younger (Age 50-65) (randomised subjects: 85.3%, SN: 72% (p < 0.01)) comprised of more heavy current smokers (OR = 2.08; 95% CI: 1.75-2.44), that smoked for a shorter period of time (randomised subjects: 37, SN_selection: 42 years (p < 0.001)). Both the respondents (32%) of the first questionnaire as well as the randomised population of the NELSON trial appeared to differ slightly on smoking characteristics, but the differences were limited and probably balance each other. Results of the NELSON trial will be roughly applicable to the Dutch and probably other populations that fulfil our selection criteria.

Brain Metastases from Different Primary Carcinomas: an Evaluation of DSC MRI Measurements

This study evaluated the roles of different dynamic susceptibility contrast magnetic imaging (DSC MRI) measurements in discriminating between brain metastases derived from four common primary carcinomas. Thirty-seven patients with brain metastases were enrolled. Relative cerebral blood volume (rCBV), cerebral blood flow (rCBF) and relative mean transit time (rMTT) in both tumor and peritumoral edema were measured. Metastases were grouped by their primary tumor (lung, gastrointestinal, breast and renal cell carcinoma). DSC MRI measurements were compared between groups. Mean rCBV, rCBF, rMTT in tumor and peritumoral edema of all brain metastases (n=37) were 2.79 ± 1.73, 2.56 ± 2.11, 1.21 ± 0.48 and 1.05 ± 0.53, 0.86 ± 0.40, 1.99 ± 0.41, respectively. The tumoral rCBV (5.26 ± 1.89) and rCBF (5.32 ± 3.28) of renal metastases were greater than those of the other three metastases (P<0.05). The tumoral rMTT (1.58 ± 0.77) of breast metastases was statistically greater than that (0.96 ± 0.31) of gastrointestinal metastases (P=0.013). No statistical difference was found between peritumoral rCBV, rCBF and rMTT (P>0.05). Evaluating various DSC MRI measurements can provide complementary hemodynamic information on brain metastases. The tumoral rCBV, rCBF and likely rMTT can help discriminate between brain metastases originating from different primary carcinomas. The peritumoral DSC MRI measurements had limited value in discriminating between brain metastases.