Patient satisfaction with coronary CT angiography versus invasive coronary angiography: results of a single-center randomized trial.

OBJECTIVE: Because there is evidence for a clinical benefit of using coronary computed tomography (CT) angiography instead of invasive coronary angiography (ICA) in patients with suspected coronary artery disease (CAD), we ascertained if patient satisfaction could represent an important barrier to implementation of coronary CT in clinical practice. MATERIALS AND METHODS: A total of 329 patients with suspected CAD and clinical indication for ICA were randomly assigned to undergo either CT or ICA for guiding treatment. Satisfaction for both groups was assessed by patient questionnaire completed twice, ≥24 h after CT or ICA, and at follow-up after a median of 3.7 years. Assessment included preparation, concern, comfort, helplessness, pain, willingness to undergo tests again, overall satisfaction, and preference. Pearson's chi-square test and Wilcoxon rank-sum test were used. RESULTS: Overall, 91% of patients undergoing CT (152/167) and 86% undergoing ICA completed assessment (140/162, p = 0.19). Patients reported being significantly better prepared for CT, less concerned about the test, and felt less helpless than during ICA (all: p < 0.001). Subjective pain (horizontal nonmarked visual analogue scale) was significantly lower for CT (6.9 ± 14.7) than for ICA (17.1 ± 22.7; p < 0.001). At follow-up, significantly more patients in the CT group reported very good satisfaction with communication of findings compared with the ICA group (p < 0.001) and 92% would recommend the institution to someone referred for the same examination. CONCLUSIONS: Results from our single-center randomized study show very good satisfaction with coronary CT compared to ICA. Thus, superior acceptance of CT should be considered in shared decision-making. CLINICAL RELEVANCE STATEMENT: This evaluation of patient satisfaction in a randomized study shows that patients' preference is in line with the clinical benefit provided by CT and also suggests to prefer a CT-first strategy in suspected coronary artery disease. KEY POINTS: • Subjective pain was significantly lower for coronary CT angiography than for invasive coronary angiography and patients felt better prepared and less concerned about CT. • Patients were overall more satisfied with coronary CT angiography than invasive coronary angiography in a randomized controlled trial. • After a median follow-up of 3.7 years, more patients in the CT group indicated very good satisfaction with the communication of findings and with the examination itself.

Computed tomography in patients with sepsis presenting to the emergency department: exploring its role in light of patient outcomes.

OBJECTIVES: This study aimed to explore the role of CT in septic patients presenting to the emergency department (ED). MATERIALS AND METHODS: We performed a retrospective secondary analysis of 192 septic patients from a prospective observational study, i.e., the "LIFE POC" study. Sepsis was diagnosed in accordance with the Sepsis-3 definition. Clinical and radiological data were collected from the hospital administration and radiological systems. Information on mortality and morbidity was collected. Time-to-CT between CT scan and sepsis diagnosis (ttCTsd) was calculated. Diagnostic accuracy was assessed with the final sepsis source as reference standard. The reference standard was established through the treating team of the patient based on all available clinical, imaging, and microbiological data. RESULTS: Sixty-two of 192 patients underwent a CT examination for sepsis focus detection. The final septic source was identified by CT in 69.4% (n = 43). CT detected septic foci with 81.1% sensitivity (95% CI, 68.0-90.6%) and 55.6% specificity (95% CI, 21.2-86.3%). Patients with short versus long ttCTsd did not differ in terms of mortality (16.1%, n = 5 vs 9.7, n = 3; p = 0.449), length of hospital stay (median 16 d, IQR 9 d 12 h-23 d 18 h vs median 13 d, IQR 10 d 00 h-24 d 00 h; p = 0.863), or duration of intensive care (median 3d 12 h, IQR 2 d 6 h-7 d 18 h vs median 5d, IQR 2 d-11 d; p = 0.800). CONCLUSIONS: Our findings show a high sensitivity of CT in ED patients with sepsis, confirming its relevance in guiding treatment decisions. The low specificity suggests that a negative CT requires further ancillary diagnostic tests for focus detection. The timing of CT did not affect morbidity or mortality outcomes. CLINICAL RELEVANCE STATEMENT: In patients with sepsis who present to the ED, CT can be used to identify infectious foci on the basis of clinical suspicion, but should not be used as a rule-out test. Scientific evidence for the optimal timing of CT beyond clinical decision-making is currently missing, as potential mortality benefits are clouded by differences in clinical severity at the time of ED presentation. KEY POINTS: • In patients with sepsis who present to the ED, CT for focus identification has a high sensitivity and can thereby be valuable for patient management. • As the specificity is considerably lower, a thorough microbiological assessment is important in these cases. • The timing of CT did not affect morbidity and mortality outcomes in this study, which might be due to variability in clinical severity at the time of ED presentation.

Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning.

BACKGROUND: Accurate mortality risk quantification is crucial for the management of hepatocellular carcinoma (HCC); however, most scoring systems are subjective. PURPOSE: To develop and independently validate a machine learning mortality risk quantification method for HCC patients using standard-of-care clinical data and liver radiomics on baseline magnetic resonance imaging (MRI). METHODS: This retrospective study included all patients with multiphasic contrast-enhanced MRI at the time of diagnosis treated at our institution. Patients were censored at their last date of follow-up, end-of-observation, or liver transplantation date. The data were randomly sampled into independent cohorts, with 85% for development and 15% for independent validation. An automated liver segmentation framework was adopted for radiomic feature extraction. A random survival forest combined clinical and radiomic variables to predict overall survival (OS), and performance was evaluated using Harrell's C-index. RESULTS: A total of 555 treatment-naïve HCC patients (mean age, 63.8 years ± 8.9 [standard deviation]; 118 females) with MRI at the time of diagnosis were included, of which 287 (51.7%) died after a median time of 14.40 (interquartile range, 22.23) months, and had median followed up of 32.47 (interquartile range, 61.5) months. The developed risk prediction framework required 1.11 min on average and yielded C-indices of 0.8503 and 0.8234 in the development and independent validation cohorts, respectively, outperforming conventional clinical staging systems. Predicted risk scores were significantly associated with OS (p < .00001 in both cohorts). CONCLUSIONS: Machine learning reliably, rapidly, and reproducibly predicts mortality risk in patients with hepatocellular carcinoma from data routinely acquired in clinical practice. CLINICAL RELEVANCE STATEMENT: Precision mortality risk prediction using routinely available standard-of-care clinical data and automated MRI radiomic features could enable personalized follow-up strategies, guide management decisions, and improve clinical workflow efficiency in tumor boards. KEY POINTS: • Machine learning enables hepatocellular carcinoma mortality risk prediction using standard-of-care clinical data and automated radiomic features from multiphasic contrast-enhanced MRI. • Automated mortality risk prediction achieved state-of-the-art performances for mortality risk quantification and outperformed conventional clinical staging systems. • Patients were stratified into low, intermediate, and high-risk groups with significantly different survival times, generalizable to an independent evaluation cohort.

Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics.

OBJECTIVES: To develop and evaluate a deep convolutional neural network (DCNN) for automated liver segmentation, volumetry, and radiomic feature extraction on contrast-enhanced portal venous phase magnetic resonance imaging (MRI). MATERIALS AND METHODS: This retrospective study included hepatocellular carcinoma patients from an institutional database with portal venous MRI. After manual segmentation, the data was randomly split into independent training, validation, and internal testing sets. From a collaborating institution, de-identified scans were used for external testing. The public LiverHccSeg dataset was used for further external validation. A 3D DCNN was trained to automatically segment the liver. Segmentation accuracy was quantified by the Dice similarity coefficient (DSC) with respect to manual segmentation. A Mann-Whitney U test was used to compare the internal and external test sets. Agreement of volumetry and radiomic features was assessed using the intraclass correlation coefficient (ICC). RESULTS: In total, 470 patients met the inclusion criteria (63.9±8.2 years; 376 males) and 20 patients were used for external validation (41±12 years; 13 males). DSC segmentation accuracy of the DCNN was similarly high between the internal (0.97±0.01) and external (0.96±0.03) test sets (p=0.28) and demonstrated robust segmentation performance on public testing (0.93±0.03). Agreement of liver volumetry was satisfactory in the internal (ICC, 0.99), external (ICC, 0.97), and public (ICC, 0.85) test sets. Radiomic features demonstrated excellent agreement in the internal (mean ICC, 0.98±0.04), external (mean ICC, 0.94±0.10), and public (mean ICC, 0.91±0.09) datasets. CONCLUSION: Automated liver segmentation yields robust and generalizable segmentation performance on MRI data and can be used for volumetry and radiomic feature extraction. CLINICAL RELEVANCE STATEMENT: Liver volumetry, anatomic localization, and extraction of quantitative imaging biomarkers require accurate segmentation, but manual segmentation is time-consuming. A deep convolutional neural network demonstrates fast and accurate segmentation performance on T1-weighted portal venous MRI. KEY POINTS: • This deep convolutional neural network yields robust and generalizable liver segmentation performance on internal, external, and public testing data. • Automated liver volumetry demonstrated excellent agreement with manual volumetry. • Automated liver segmentations can be used for robust and reproducible radiomic feature extraction.

Combination of computed tomography angiography with coronary artery calcium score for improved diagnosis of coronary artery disease: a collaborative meta-analysis of stable chest pain patients referred for invasive coronary angiography.

OBJECTIVES: Coronary computed tomography angiography (CCTA) has higher diagnostic accuracy than coronary artery calcium (CAC) score for detecting obstructive coronary artery disease (CAD) in patients with stable chest pain, while the added diagnostic value of combining CCTA with CAC is unknown. We investigated whether combining coronary CCTA with CAC score can improve the diagnosis of obstructive CAD compared with CCTA alone. METHODS: A total of 2315 patients (858 women, 37%) aged 61.1 ± 10.2 from 29 original studies were included to build two CAD prediction models based on either CCTA alone or CCTA combined with the CAC score. CAD was defined as at least 50% coronary diameter stenosis on invasive coronary angiography. Models were built by using generalized linear mixed-effects models with a random intercept set for the original study. The two CAD prediction models were compared by the likelihood ratio test, while their diagnostic performance was compared using the area under the receiver-operating-characteristic curve (AUC). Net benefit (benefit of true positive versus harm of false positive) was assessed by decision curve analysis. RESULTS: CAD prevalence was 43.5% (1007/2315). Combining CCTA with CAC improved CAD diagnosis compared with CCTA alone (AUC: 87% [95% CI: 86 to 89%] vs. 80% [95% CI: 78 to 82%]; p < 0.001), likelihood ratio test 236.3, df: 1, p < 0.001, showing a higher net benefit across almost all threshold probabilities. CONCLUSION: Adding the CAC score to CCTA findings in patients with stable chest pain improves the diagnostic performance in detecting CAD and the net benefit compared with CCTA alone. CLINICAL RELEVANCE STATEMENT: CAC scoring CT performed before coronary CTA and included in the diagnostic model can improve obstructive CAD diagnosis, especially when CCTA is non-diagnostic. KEY POINTS: • The combination of coronary artery calcium with coronary computed tomography angiography showed significantly higher AUC (87%, 95% confidence interval [CI]: 86 to 89%) for diagnosis of coronary artery disease compared to coronary computed tomography angiography alone (80%, 95% CI: 78 to 82%, p < 0.001). • Diagnostic improvement was mostly seen in patients with non-diagnostic C. • The improvement in diagnostic performance and the net benefit was consistent across age groups, chest pain types, and genders.

Has the STARD statement improved the quality of reporting of diagnostic accuracy studies published in European Radiology?

OBJECTIVES: To investigate whether encouraging authors to follow the Standards for Reporting Diagnostic Accuracy (STARD) guidelines improves the quality of reporting of diagnostic accuracy studies. METHODS: In mid-2017, European Radiology started encouraging its authors to follow the STARD guidelines. Our MEDLINE search identified 114 diagnostic accuracy studies published in European Radiology in 2015 and 2019. The quality of reporting was evaluated by two independent reviewers using the revised STARD statement. Item 11 was excluded because a meaningful decision about adherence was not possible. Student's t test for independent samples was used to analyze differences in the mean number of reported STARD items between studies published in 2015 and in 2019. In addition, we calculated differences related to the study design, data collection, and citation rate. RESULTS: The mean total number of reported STARD items for all 114 diagnostic accuracy studies analyzed was 15.9 ± 2.6 (54.8%) of 29 items (range 9.5-22.5). The quality of reporting of diagnostic accuracy studies was significantly better in 2019 (mean ± standard deviation (SD), 16.3 ± 2.7) than in 2015 (mean ± SD, 15.1 ± 2.3; p < 0.02). No significant differences in the reported STARD items were identified in relation to study design (p = 0.13), data collection (p = 0.87), and citation rate (p = 0.09). CONCLUSION: The quality of reporting of diagnostic accuracy studies according to the STARD statement was moderate with a slight improvement since European Radiology started to recommend its authors to follow the STARD guidelines. KEY POINTS: • The quality of reporting of diagnostic accuracy studies was moderate with a mean total number of reported STARD items of 15.9 ± 2.6. • The adherence to STARD was significantly better in 2019 than in 2015 (16.3 ± 2.7 vs. 15.1 ± 2.3; p = 0.016). • No significant differences in the reported STARD items were identified in relation to study design (p = 0.13), data collection (p = 0.87), and citation rate (p = 0.09).

State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting-a consensus document by the European Society of Cardiovascular Radiology (ESCR).

The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society's highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. The purpose of this second document is to discuss suggestions for standardized reporting based on the accompanying consensus document part I. KEY POINTS: • CT and MR imaging-based evaluation of carotid artery disease provides essential information for risk stratification and prediction of stroke. • The information in the report must cover vessel morphology, description of stenosis, and plaque imaging features. • A structured approach to reporting ensures that all essential information is delivered in a standardized and consistent way to the referring clinician.

State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements-a consensus document by the European Society of Cardiovascular Radiology (ESCR).

The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society's highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. We have produced a twin-papers consensus, indicated through the documents as respectively "Part I" and "Part II." The first document (Part I) begins with a discussion of features, role, indications, and evidence for CT and MR imaging-based diagnosis of carotid artery disease for risk stratification and prediction of stroke (Section I). It then provides an extensive overview and insight into imaging-derived biomarkers and their potential use in risk stratification (Section II). Finally, detailed recommendations about optimized imaging technique and imaging strategies are summarized (Section III). The second part of this consensus paper (Part II) is focused on structured reporting of carotid imaging studies with CT/MR. KEY POINTS: • CT and MR imaging-based evaluation of carotid artery disease provides essential information for risk stratification and prediction of stroke. • Imaging-derived biomarkers and their potential use in risk stratification are evolving; their correct interpretation and use in clinical practice must be well-understood. • A correct imaging strategy and scan protocol will produce the best possible results for disease evaluation.

Interdisciplinary perspectives on computed tomography in sepsis: survey among medical doctors at a large university medical center.

OBJECTIVES: This study aims to describe physicians' perspectives on the use of computed tomography (CT) in patients with sepsis. METHODS: In January 2022, physicians of a large European university medical center were surveyed using a web-based questionnaire asking about their views on the role of CT in sepsis. A total of 371 questionnaires met the inclusion criteria and were analyzed using work experience, workplace, and medical specialty of physicians as variables. Chi-square tests were performed. RESULTS: Physicians considered the ability to detect an unknown focus as the greatest benefit of CT scans in sepsis (70.9%, n = 263/371). Two clinical criteria - "signs of decreased vigilance" (89.2%, n = 331/371) and "increased catecholamine demand" (84.7%, n = 314/371) - were considered highly relevant for a CT request. Elevated procalcitonin (82.7%, n = 307/371) and lactate levels (83.6%, n = 310/371) were consistently found to be critical laboratory values to request a CT. As long as there is evidence of infection in one organ region, most physicians (42.6%, n = 158/371) would order a CT scan based on clinical assessment. Combined examination of the chest, abdomen, and pelvis was favored (34.8%, n = 129/371) in cases without clinical clues of an infection source. A time window of ≥ 1-6 h was preferred for both CT examinations (53.9%, n = 200/371) and CT-guided interventions (59.3%, n = 220/371) in patients with sepsis. CONCLUSION: Despite much consensus, there are significant differences in attitudes towards the use of CT in septic patients among physicians from different workplaces and medical specialties. Knowledge of these perspectives may improve patient management and interprofessional communication. KEY POINTS: Despite interdisciplinary consensus on the use of CT in sepsis, statistically significant differences in the responses are apparent among physicians from different workplaces and medical specialties. The detection of a previously unknown source of infection and the ability to plan interventions and/or surgery based on CT findings are considered key advantages of CT in septic patients. Timing of CT reflects the requirements of specific disciplines.

Prediction of prostate cancer grade using fractal analysis of perfusion MRI: retrospective proof-of-principle study.

OBJECTIVES: Multiparametric MRI has high diagnostic accuracy for detecting prostate cancer, but non-invasive prediction of tumor grade remains challenging. Characterizing tumor perfusion by exploiting the fractal nature of vascular anatomy might elucidate the aggressive potential of a tumor. This study introduces the concept of fractal analysis for characterizing prostate cancer perfusion and reports about its usefulness for non-invasive prediction of tumor grade. METHODS: We retrospectively analyzed the openly available PROSTATEx dataset with 112 cancer foci in 99 patients. In all patients, histological grading groups specified by the International Society of Urological Pathology (ISUP) were obtained from in-bore MRI-guided biopsy. Fractal analysis of dynamic contrast-enhanced perfusion MRI sequences was performed, yielding fractal dimension (FD) as quantitative descriptor. Two-class and multiclass diagnostic accuracy was analyzed using area under the curve (AUC) receiver operating characteristic analysis, and optimal FD cutoffs were established. Additionally, we compared fractal analysis to conventional apparent diffusion coefficient (ADC) measurements. RESULTS: Fractal analysis of perfusion allowed accurate differentiation of non-significant (group 1) and clinically significant (groups 2-5) cancer with a sensitivity of 91% (confidence interval [CI]: 83-96%) and a specificity of 86% (CI: 73-94%). FD correlated linearly with ISUP groups (r2 = 0.874, p < 0.001). Significant groupwise differences were obtained between low, intermediate, and high ISUP group 1-4 (p ≤ 0.001) but not group 5 tumors. Fractal analysis of perfusion was significantly more reliable than ADC in predicting non-significant and clinically significant cancer (AUCFD = 0.97 versus AUCADC = 0.77, p < 0.001). CONCLUSION: Fractal analysis of perfusion MRI accurately predicts prostate cancer grading in low-, intermediate-, and high-, but not highest-grade, tumors. KEY POINTS: • In 112 prostate carcinomas, fractal analysis of MR perfusion imaging accurately differentiated low-, intermediate-, and high-grade cancer (ISUP grade groups 1-4). • Fractal analysis detected clinically significant prostate cancer with a sensitivity of 91% (83-96%) and a specificity of 86% (73-94%). • Fractal dimension of perfusion at the tumor margin may provide an imaging biomarker to predict prostate cancer grading.

Accuracy of fractal analysis and PI-RADS assessment of prostate magnetic resonance imaging for prediction of cancer grade groups: a clinical validation study.

OBJECTIVES: Multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) assessment is sensitive but not specific for detecting clinically significant prostate cancer. This study validates the diagnostic accuracy of the recently suggested fractal dimension (FD) of perfusion for detecting clinically significant cancer. MATERIALS AND METHODS: Routine clinical MR imaging data, acquired at 3 T without an endorectal coil including dynamic contrast-enhanced sequences, of 72 prostate cancer foci in 64 patients were analyzed. In-bore MRI-guided biopsy with International Society of Urological Pathology (ISUP) grading served as reference standard. Previously established FD cutoffs for predicting tumor grade were compared to measurements of the apparent diffusion coefficient (25th percentile, ADC25) and PI-RADS assessment with and without inclusion of the FD as separate criterion. RESULTS: Fractal analysis allowed prediction of ISUP grade groups 1 to 4 but not 5, with high agreement to the reference standard (κFD = 0.88 [CI: 0.79-0.98]). Integrating fractal analysis into PI-RADS allowed a strong improvement in specificity and overall accuracy while maintaining high sensitivity for significant cancer detection (ISUP > 1; PI-RADS alone: sensitivity = 96%, specificity = 20%, area under the receiver operating curve [AUC] = 0.65; versus PI-RADS with fractal analysis: sensitivity = 95%, specificity = 88%, AUC = 0.92, p < 0.001). ADC25 only differentiated low-grade group 1 from pooled higher-grade groups 2-5 (κADC = 0.36 [CI: 0.12-0.59]). Importantly, fractal analysis was significantly more reliable than ADC25 in predicting non-significant and clinically significant cancer (AUCFD = 0.96 versus AUCADC = 0.75, p < 0.001). Diagnostic accuracy was not significantly affected by zone location. CONCLUSIONS: Fractal analysis is accurate in noninvasively predicting tumor grades in prostate cancer and adds independent information when implemented into PI-RADS assessment. This opens the opportunity to individually adjust biopsy priority and method in individual patients. KEY POINTS: • Fractal analysis of perfusion is accurate in noninvasively predicting tumor grades in prostate cancer using dynamic contrast-enhanced sequences (κFD = 0.88). • Including the fractal dimension into PI-RADS as a separate criterion improved specificity (from 20 to 88%) and overall accuracy (AUC from 0.86 to 0.96) while maintaining high sensitivity (96% versus 95%) for predicting clinically significant cancer. • Fractal analysis was significantly more reliable than ADC25 in predicting clinically significant cancer (AUCFD = 0.96 versus AUCADC = 0.75).

Fractal analysis improves tumour size measurement on computed tomography in pancreatic ductal adenocarcinoma: comparison with gross pathology and multi-parametric MRI.

OBJECTIVES: Tumour size measurement is pivotal for staging and stratifying patients with pancreatic ductal adenocarcinoma (PDA). However, computed tomography (CT) frequently underestimates tumour size due to insufficient depiction of the tumour rim. CT-derived fractal dimension (FD) maps might help to visualise perfusion chaos, thus allowing more realistic size measurement. METHODS: In 46 patients with histology-proven PDA, we compared tumour size measurements in routine multiphasic CT scans, CT-derived FD maps, multi-parametric magnetic resonance imaging (mpMRI), and, where available, gross pathology of resected specimens. Gross pathology was available as reference for diameter measurement in a discovery cohort of 10 patients. The remaining 36 patients constituted a separate validation cohort with mpMRI as reference for diameter and volume. RESULTS: Median RECIST diameter of all included tumours was 40 mm (range: 18-82 mm). In the discovery cohort, we found significant (p = 0.03) underestimation of tumour diameter on CT compared with gross pathology (Δdiameter3D = -5.7 mm), while realistic diameter measurements were obtained from FD maps (Δdiameter3D = 0.6 mm) and mpMRI (Δdiameter3D = -0.9 mm), with excellent correlation between the two (R2 = 0.88). In the validation cohort, CT also systematically underestimated tumour size in comparison to mpMRI (Δdiameter3D = -10.6 mm, Δvolume = -10.2 mL), especially in larger tumours. In contrast, FD map measurements agreed excellently with mpMRI (Δdiameter3D = +1.5 mm, Δvolume = -0.6 mL). Quantitative perfusion chaos was significantly (p = 0.001) higher in the tumour rim (FDrim = 4.43) compared to the core (FDcore = 4.37) and remote pancreas (FDpancreas = 4.28). CONCLUSIONS: In PDA, fractal analysis visualises perfusion chaos in the tumour rim and improves size measurement on CT in comparison to gross pathology and mpMRI, thus compensating for size underestimation from routine CT. KEY POINTS: • CT-based measurement of tumour size in pancreatic adenocarcinoma systematically underestimates both tumour diameter (Δdiameter = -10.6 mm) and volume (Δvolume = -10.2 mL), especially in larger tumours. • Fractal analysis provides maps of the fractal dimension (FD), which enable a more reliable and size-independent measurement using gross pathology or multi-parametric MRI as reference standards. • FD quantifies perfusion chaos-the underlying pathophysiological principle-and can separate the more chaotic tumour rim from the tumour core and adjacent non-tumourous pancreas tissue.

Detection of relevant extracardiac findings on coronary computed tomography angiography vs. invasive coronary angiography.

OBJECTIVES: To compare the detection of relevant extracardiac findings (ECFs) on coronary computed tomography angiography (CTA) and invasive coronary angiography (ICA) and evaluate the potential clinical benefit of their detection. METHODS: This is the prespecified subanalysis of ECFs in patients presenting with a clinical indication for ICA based on atypical angina and suspected coronary artery disease (CAD) included in the prospective single-center randomized controlled Coronary Artery Disease Management (CAD-Man) study. ECFs requiring immediate therapy and/or further workup including additional imaging were defined as clinically relevant. We evaluated the scope of ECFs in 329 patients and analyzed the potential clinical benefit of their detection. RESULTS: ECFs were detected in 107 of 329 patients (32.5%; CTA: 101/167, 60.5%; ICA: 6/162, 3.7%; p < .001). Fifty-nine patients had clinically relevant ECFs (17.9%; CTA: 55/167, 32.9%; ICA: 4/162, 2.5%; p < .001). In the CTA group, ECFs potentially explained atypical chest pain in 13 of 101 patients with ECFs (12.9%). After initiation of therapy, chest pain improved in 4 (4.0%) and resolved in 7 patients (6.9%). Follow-up imaging was recommended in 33 (10.0%; CTA: 30/167, 18.0%; ICA: 3/162, 1.9%) and additional clinic consultation in 26 patients (7.9%; CTA: 25/167, 15.0%; ICA: 1/162, 0.6%). Malignancy was newly diagnosed in one patient (0.3%; CTA: 1/167, 0.6%; ICA: 0). CONCLUSIONS: In this randomized study, CTA but not ICA detected clinically relevant ECFs that may point to possible other causes of chest pain in patients without CAD. Thus, CTA might preclude the need for ICA in those patients. TRIAL REGISTRATION: NCT Unique ID: 00844220 KEY POINTS: • CTA detects ten times more clinically relevant ECFs than ICA. • Actionable clinically relevant ECFs affect patient management and therapy and may thus improve chest pain. • Detection of ECFs explaining chest pain on CTA might preclude the need for performing ICA.

Computed tomography angiography versus Agatston score for diagnosis of coronary artery disease in patients with stable chest pain: individual patient data meta-analysis of the international COME-CCT Consortium.

OBJECTIVES: There is conflicting evidence about the comparative diagnostic accuracy of the Agatston score versus computed tomography angiography (CTA) in patients with suspected obstructive coronary artery disease (CAD). PURPOSE: To determine whether CTA is superior to the Agatston score in the diagnosis of CAD. METHODS: In total 2452 patients with stable chest pain and a clinical indication for invasive coronary angiography (ICA) for suspected CAD were included by the Collaborative Meta-analysis of Cardiac CT (COME-CCT) Consortium. An Agatston score of > 400 was considered positive, and obstructive CAD defined as at least 50% coronary diameter stenosis on ICA was used as the reference standard. RESULTS: Obstructive CAD was diagnosed in 44.9% of patients (1100/2452). The median Agatston score was 74. Diagnostic accuracy of CTA for the detection of obstructive CAD (81.1%, 95% confidence interval [CI]: 77.5 to 84.1%) was significantly higher than that of the Agatston score (68.8%, 95% CI: 64.2 to 73.1%, p < 0.001). Among patients with an Agatston score of zero, 17% (101/600) had obstructive CAD. Diagnostic accuracy of CTA was not significantly different in patients with low to intermediate (1 to < 100, 100-400) versus moderate to high Agatston scores (401-1000, > 1000). CONCLUSIONS: Results in our international cohort show CTA to have significantly higher diagnostic accuracy than the Agatston score in patients with stable chest pain, suspected CAD, and a clinical indication for ICA. Diagnostic performance of CTA is not affected by a higher Agatston score while an Agatston score of zero does not reliably exclude obstructive CAD. KEY POINTS: • CTA showed significantly higher diagnostic accuracy (81.1%, 95% confidence interval [CI]: 77.5 to 84.1%) for diagnosis of coronary artery disease when compared to the Agatston score (68.8%, 95% CI: 64.2 to 73.1%, p < 0.001). • Diagnostic performance of CTA was not affected by increased amount of calcium and was not significantly different in patients with low to intermediate (1 to <100, 100-400) versus moderate to high Agatston scores (401-1000, > 1000). • Seventeen percent of patients with an Agatston score of zero showed obstructive coronary artery disease by invasive angiography showing absence of coronary artery calcium cannot reliably exclude coronary artery disease.

Body computed tomography in sepsis: predictors of CT findings and patient outcomes in a retrospective medical ICU cohort study.

BACKGROUND: Sepsis is a life-threatening condition that requires immediate focus identification and control. However, international sepsis guidelines do not provide information on imaging choice. PURPOSE: To identify predictors of CT findings and patient outcomes in a population of septic patients from a medical ICU. MATERIAL AND METHODS: A full-text search in the radiological information system (RIS) retrieved 227 body CT examinations conducted to identify infectious sources in 2018. CT reports were categorized according to identified foci and their diagnostic certainty. Diagnostic accuracy of CT was compared to microbiological results. Clinical and laboratory information was gathered. Statistical analysis was performed using nonparametric tests and logistic regression analysis. RESULTS: CT revealed more positive infectious foci 52.4% (n = 191/227) than microbiological tests 39.3% (n = 79/201). There were no significant differences between focus-positive CT scans with regard to positive microbiological testing (p = 0.32). Sequential organ failure assessment (SOFA) scores were slightly but nonsignificantly higher in patients with a focus-positive CT, odds ratio (OR) = 0.999 (95% CI 0.997-1.001) with p = 0.52. Among C-reactive protein (CRP), procalcitonin (PCT), and leukocytes, in focus-positive versus focus-negative CT scans, CRP showed a minor but statistically significant elevation in the group with focus-positive CT scans (OR = 1.004, 95% CI = 1.000-1.007, p = 0.04). No significant association was found for PCT (OR = 1.007, 95% CI = 0.991-1.023; p = 0.40) or leukocytes (OR = 1.003, 95% CI = 0.970-1.038; p = 0.85). In 33.5% (n = 76/227) of cases, the CT findings had at least one therapeutic consequence. In 81.6% (n = 62/76), the CT findings resulted in one consequence, in 14.5% (n = 11/76) in two consequences, and in 3.9% (n = 3/76) in three consequences. There was no significant association between focus-positive CT scans and mortality (p = 0.81). CONCLUSION: In this population of septic patients in medical intensive care, microbiological analysis complemented CT findings. Both clinical and laboratory parameters were not predictive of CT findings. While therapeutic consequences of CT findings in this study population underline the role of CT for decision making in septic patients, CT findings do not predict patient outcomes in this retrospective analysis.

Patient preferences for development in MRI scanner design: a survey of claustrophobic patients in a randomized study.

OBJECTIVE: To investigate which magnetic resonance imaging (MRI) scanner designs claustrophobic patients prefer. MATERIAL/METHODS: We analyzed questionnaires completed by 160 patients at high risk for claustrophobia directly after a scan in either a short-bore or open panoramic scanner as part of a prospective randomized trial Enders et al (BMC Med Imaging 11:4, 2011). Scanner preferences were judged based on schematic drawings of four scanners. Information on the diagnostic performance of the depicted scanners was provided, too. RESULTS: A majority of patients suggested upright open (59/160, 36.9%) and open panoramic (53/160, 33.1%) before short-bore designs (26/160, 16.3%, for all p < 0.001) for future development. When asked about patients' preferred scanner choice for an upcoming examination, information about a better diagnostic performance of a short-bore scanner significantly improved its preference rates (from 6/160 to 49/160 or 3.8 to 30.5%, p < 0.001). Patients with a claustrophobic event preferred open designs significantly more often than patients without a claustrophobic event (p = 0.047). Patients scanned in a short-bore scanner in our trial preferred this design significantly more often (p = 0.003). Noise reduction (51/160, 31.9%), more space over the head (44/160, 27.5%), and overall more space (33/160, 20.6%) were the commonest suggested areas of improvement. CONCLUSION: Patients at high risk for claustrophobia visually prefer open- over short-bore MRI designs for further development. Education about a better diagnostic performance of a visually less-attractive scanner can increase its acceptance. Noise and space were of most concern for claustrophobic patients. This information can guide individual referral of claustrophobic patients to scanners and future scanner development. KEY POINTS: • Patients at high risk for claustrophobia visually favor the further development of open scanners as opposed to short- and closed-bore scanner designs. • Educating claustrophobic patients about a higher diagnostic performance of a short-bore scanner can significantly increase their acceptance of this otherwise visually less-attractive design. • A medical history of earlier claustrophobic events in a given MRI scanner type and focusing on the features "more space" and "noise reduction" can help to guide referral of patients who are at high risk for claustrophobia.

Audio-guided self-hypnosis for reduction of claustrophobia during MR imaging: results of an observational 2-group study.

OBJECTIVES: To evaluate the influence of audio-guided self-hypnosis on claustrophobia in a high-risk cohort undergoing magnetic resonance (MR) imaging. METHODS: In this prospective observational 2-group study, 55 patients (69% female, mean age 53.6 ± 13.9) used self-hypnosis directly before imaging. Claustrophobia included premature termination, sedation, and coping actions. The claustrophobia questionnaire (CLQ) was completed before self-hypnosis and after MR imaging. Results were compared to a control cohort of 89 patients examined on the same open MR scanner using logistic regression for multivariate analysis. Furthermore, patients were asked about their preferences for future imaging. RESULTS: There was significantly fewer claustrophobia in the self-hypnosis group (16%; 9/55), compared with the control group (43%; 38/89; odds ratio .14; p = .001). Self-hypnosis patients also needed less sedation (2% vs 16%; 1/55 vs 14/89; odds ratio .1; p = .008) and non-sedation coping actions (13% vs 28%; 7/55 vs 25/89; odds ratio .3; p = .02). Self-hypnosis did not influence the CLQ results measured before and after MR imaging (p = .79). Self-hypnosis reduced the frequency of claustrophobia in the subgroup of patients above an established CLQ cut-off of .33 from 47% (37/78) to 18% (9/49; p = .002). In the subgroup below the CLQ cut-off of 0.33, there were no significant differences (0% vs 9%, 0/6 vs 1/11; p = 1.0). Most patients (67%; 35/52) preferred self-hypnosis for future MR examinations. CONCLUSIONS: Self-hypnosis reduced claustrophobia in high-risk patients undergoing imaging in an open MR scanner and might reduce the need for sedation and non-sedation coping actions. KEY POINTS: • Forty percent of the patients at high risk for claustrophobia may also experience a claustrophobic event in an open MR scanner. • Self-hypnosis while listening to an audio in the waiting room before the examination may reduce claustrophobic events in over 50% of patients with high risk for claustrophobia. • Self-hypnosis may also reduce the need for sedation and other time-consuming non-sedation coping actions and is preferred by high-risk patients for future examinations.

Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers.

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.

Clinical pre-test probability for obstructive coronary artery disease: insights from the European DISCHARGE pilot study.

OBJECTIVES: To test the accuracy of clinical pre-test probability (PTP) for prediction of obstructive coronary artery disease (CAD) in a pan-European setting. METHODS: Patients with suspected CAD and stable chest pain who were clinically referred for invasive coronary angiography (ICA) or computed tomography (CT) were included by clinical sites participating in the pilot study of the European multi-centre DISCHARGE trial. PTP of CAD was determined using the Diamond-Forrester (D+F) prediction model initially introduced in 1979 and the updated D+F model from 2011. Obstructive coronary artery disease (CAD) was defined by one at least 50% diameter coronary stenosis by both CT and ICA. RESULTS: In total, 1440 patients (654 female, 786 male) were included at 25 clinical sites from May 2014 until July 2017. Of these patients, 725 underwent CT, while 715 underwent ICA. Both prediction models overestimated the prevalence of obstructive CAD (31.7%, 456 of 1440 patients, PTP: initial D+F 58.9% (28.1-90.6%), updated D+F 47.3% (34.2-59.9%), both p < 0.001), but overestimation of disease prevalence was higher for the initial D+F (p < 0.001). The discriminative ability was higher for the updated D+F 2011 (AUC of 0.73 95% confidence interval [CI] 0.70-0.76 versus AUC of 0.70 CI 0.67-0.73 for the initial D+F; p < 0.001; odds ratio (or) 1.55 CI 1.29-1.86, net reclassification index 0.11 CI 0.05-0.16, p < 0.001). CONCLUSIONS: Clinical PTP calculation using the initial and updated D+F prediction models relevantly overestimates the actual prevalence of obstructive CAD in patients with stable chest pain clinically referred for ICA and CT suggesting that further refinements to improve clinical decision-making are needed. TRIAL REGISTRATION: https://www.clinicaltrials.gov/ct2/show/NCT02400229 KEY POINTS: • Clinical pre-test probability calculation using the initial and updated D+F model overestimates the prevalence of obstructive CAD identified by ICA and CT. • Overestimation of disease prevalence is higher for the initial D+F compared with the updated D+F. • Diagnostic accuracy of PTP assessment varies strongly between different clinical sites throughout Europe.