The pericoronary adipose tissue attenuation in CT strongly depends on kernels and iterative reconstructions.

OBJECTIVES: To investigate the influence of kernels and iterative reconstructions on pericoronary adipose tissue (PCAT) attenuation in coronary CT angiography (CCTA). MATERIALS AND METHODS: Twenty otherwise healthy subjects (16 females; median age 52 years) with atypical chest pain, low risk of coronary artery disease (CAD), and without CAD in photon-counting detector CCTA were included. Images were reconstructed with a quantitative smooth (Qr36) and three vascular kernels of increasing sharpness levels (Bv36, Bv44, Bv56). Quantum iterative reconstruction (QIR) was either switched-off (QIRoff) or was used with strength levels 2 and 4. The fat-attenuation-index (FAI) of the PCAT surrounding the right coronary artery was calculated in each dataset. Histograms of FAI measurements were created. Intra- and inter-reader agreements were determined. A CT edge phantom was used to determine the edge spread function (ESF) for the same datasets. RESULTS: Intra- and inter-reader agreement of FAI was excellent (intra-class correlation coefficient = 0.99 and 0.98, respectively). Significant differences in FAI were observed depending on the kernel and iterative reconstruction strength level (each, p < 0.001), with considerable inter-individual variation up to 34 HU and intra-individual variation up to 33 HU, depending on kernels and iterative reconstruction levels. The ESFs showed a reduced range of edge-smoothing with increasing kernel sharpness, causing an FAI decrease. Histogram analyses revealed a narrower peak of PCAT values with increasing iterative reconstruction levels, causing a FAI increase. CONCLUSIONS: PCAT attenuation determined with CCTA heavily depends on kernels and iterative reconstruction levels both within and across subjects. Standardization of CT reconstruction parameters is mandatory for FAI studies to enable meaningful interpretations. KEY POINTS: Question Do kernels and iterative reconstructions influence pericoronary adipose tissue (PCAT) attenuation in coronary CT angiography (CCTA)? Findings Significant differences in fat-attenuation-index (FAI) were observed depending on the kernel and iterative reconstruction strength level with considerable inter- and intra-individual variation. Clinical relevance PCAT attenuation heavily depends on kernels and iterative reconstructions requiring CT reconstruction parameter standardization to enable meaningful interpretations of fat-attenuation differences across subjects.

Synthetic hematocrit from virtual non-contrast images for myocardial extracellular volume evaluation with photon-counting detector CT.

OBJECTIVES: To assess the accuracy of a synthetic hematocrit derived from virtual non-contrast (VNC) and virtual non-iodine images (VNI) for myocardial extracellular volume (ECV) computation with photon-counting detector computed tomography (PCD-CT). MATERIALS AND METHODS: Consecutive patients undergoing PCD-CT including a coronary CT angiography (CCTA) and a late enhancement (LE) scan and having a blood hematocrit were retrospectively included. In the first 75 patients (derivation cohort), CCTA and LE scans were reconstructed as VNI at 60, 70, and 80 keV and as VNC with quantum iterative reconstruction (QIR) strengths 2, 3, and 4. Blood pool attenuation (BPmean) was correlated to blood hematocrit. In the next 50 patients (validation cohort), synthetic hematocrit was calculated using BPmean. Myocardial ECV was computed using the synthetic hematocrit and compared with the ECV using the blood hematocrit as a reference. RESULTS: In the derivation cohort (49 men, mean age 79 ± 8 years), a correlation between BPmean and blood hematocrit ranged from poor for VNI of CCTA at 80 keV, QIR2 (R2 = 0.12) to moderate for VNI of LE at 60 keV, QIR4; 70 keV, QIR3 and 4; and VNC of LE, QIR3 and 4 (all, R2 = 0.58). In the validation cohort (29 men, age 75 ± 14 years), synthetic hematocrit was calculated from VNC of the LE scan, QIR3. Median ECV was 26.9% (interquartile range (IQR), 25.5%, 28.8%) using the blood hematocrit and 26.8% (IQR, 25.4%, 29.7%) using synthetic hematocrit (VNC, QIR3; mean difference, -0.2%; limits of agreement, -2.4%, 2.0%; p = 0.33). CONCLUSION: Synthetic hematocrit calculated from VNC images enables an accurate computation of myocardial ECV with PCD-CT. CLINICAL RELEVANCE STATEMENT: Virtual non-contrast images from cardiac late enhancement scans with photon-counting detector CT allow the calculation of a synthetic hematocrit, which enables accurate computation of myocardial extracellular volume. KEY POINTS: Blood hematocrit is mandatory for conventional myocardial extracellular volume computation. Synthetic hematocrit can be calculated from virtual non-iodine and non-contrast photon-counting detector CT images. Synthetic hematocrit from virtual non-contrast images enables computation of the myocardial extracellular volume.

Effect of Vessel Attenuation, VMI Level, and Reconstruction Kernel on Pericoronary Adipose Tissue Attenuation for EID CT and PCD CT: An Ex Vivo Porcine Heart Study.

Background: Pericoronary adipose tissue (PCAT) attenuation and fat attenuation index (FAI) may serve as markers of inflammation and risk of adverse cardiac events. However, standardization of relevant CT acquisition and reconstruction parameters is lacking. Objective: To investigate the influence of vessel attenuation, virtual monoenergetic image (VMI) level, and reconstruction kernel on PCAT attenuation and FAI using energy-integrating detector (EID) and photon-counting detector (PCD) CT systems in an ex-vivo porcine heart model. Methods: A porcine heart's right coronary artery (RCA) was injected with saline or varying contrast media dilutions to achieve vessel attenuations ranging from 0 to 1000 HU. After each injection, the heart was scanned with EID CT at 120 kVp and PCD CT at 140 kVp, at constant CTDIvol (10 mGy). For EID CT, polychromatic images were reconstructed with Qr40 kernel. For PCD CT, VMI (40-80 keV at 10-keV increments) were reconstructed with Qr40, Bv40, and Bv56 kernels. ROIs were placed to measure RCA and PCAT attenuation. FAI was determined using software; histogram analysis was performed of voxel attenuations in the volumes of interest for FAI calculation. Results: Correlations were observed between attenuation in the RCA and adjacent PCAT (r=0.3-1.0), and between vessel attenuation and FAI (r=-0.9-1.0). For PCAT attenuation and FAI, these associations became progressively weaker for progressively sharper kernels. For increasing vessel attenuation for EID CT and for increasing VMI level for PCD CT, FAI histograms showed right shifts of the peak attenuation; the percentage of histogram voxels meeting the threshold range for inclusion in FAI calculation for EID CT was 8-29% and for PCD CT at VMI levels of 70-80 keV was 5-42%. For PCD CT, sharper kernels were associated with left shifts in peak attenuations and greater percentages of voxels within the threshold range for inclusion in FAI calculations. Conclusion: PCAT attenuation and FAI are influenced by vessel lumen attenuation, VMI level, and reconstruction kernel. A minority of pericoronary voxels contribute to FAI measurements for polychromatic EID CT and for PCD CT at high VMI levels. Clinical Impact: These findings may help standardize acquisition and reconstruction parameters for PCAT attenuation and FAI measurements.

Mammographic calcifications undergoing percutaneous biopsy: outcome in women with and without a personal history of breast cancer.

PURPOSE: To compare the positive predictive values (PPVs) of BI-RADS categories used to assess pure mammographic calcifications in women with and without a previous history of breast cancer (PHBC). MATERIALS AND METHODS: In this retrospective study, all consecutive pure mammographic calcifications (n = 320) undergoing a stereotactic biopsy between 2016 and 2018 were identified. Mammograms were evaluated in consensus by two radiologists according to BI-RADS and blinded to patient history and pathology results. Final pathologic results were used as the standard of reference. PPV of BI-RADS categories were compared between the two groups. Data were evaluated using standard statistics, Mann-Whitney U tests and Chi-square tests. RESULTS: Two hundred sixty-eight patients (274 lesions, median age 54 years, inter-quartile range, 50-65 years) with a PHBC (n = 46) and without a PHBC (n = 222) were included. Overall PPVs were the following: BI-RADS 2, 0% (0 of 56); BI-RADS 3, 9.1% (1 of 11); BI-RADS 4a, 16.2% (6 of 37); BI-RADS 4b, 37.5% (48 of 128); BI-RADS 4c, 47.3% (18 of 38) and BI-RADS 5, 100% (4 of 4). The PPV of BI-RADS categories was similar in patients with and without a PHBC (P = .715). Calcifications were more often malignant in patients with a PHBC older than 10 years (47.3%, 9 of 19) compared to 1-2 years (25%, 1 of 4), 2-5 years (20%, 2 of 10) and 5-10 years (0%, of 13) from the first breast cancer (P = .005). CONCLUSION: PPV of mammographic calcifications is similar in women with or without PHBC when BI-RADS classification is strictly applied. A higher risk of malignancy was observed in patients with a PHBC longer than 10 years.

Quantum Iterative Reconstruction for Abdominal Photon-counting Detector CT Improves Image Quality.

Background An iterative reconstruction (IR) algorithm was introduced for clinical photon-counting detector (PCD) CT. Purpose To investigate the image quality and the optimal strength level of a quantum IR algorithm (QIR; Siemens Healthcare) for virtual monoenergetic images and polychromatic images (T3D) in a phantom and in patients undergoing portal venous abdominal PCD CT. Materials and Methods In this retrospective study, noise power spectrum (NPS) was measured in a water-filled phantom. Consecutive oncologic patients who underwent portal venous abdominal PCD CT between March and April 2021 were included. Virtual monoenergetic images at 60 keV and T3D were reconstructed without QIR (QIR-off; reference standard) and with QIR at four levels (QIR 1-4; index tests). Global noise index, contrast-to-noise ratio (CNR), and voxel-wise CT attenuation differences were measured. Noise and texture, artifacts, diagnostic confidence, and overall quality were assessed qualitatively. Conspicuity of hypodense liver lesions was rated by four readers. Parametric (analyses of variance, paired t tests) and nonparametric tests (Friedman, post hoc Wilcoxon signed-rank tests) were used to compare quantitative and qualitative image quality among reconstructions. Results In the phantom, NPS showed unchanged noise texture across reconstructions with maximum spatial frequency differences of 0.01 per millimeter. Fifty patients (mean age, 59 years ± 16 [standard deviation]; 31 women) were included. Global noise index was reduced from QIR-off to QIR-4 by 45% for 60 keV and by 44% for T3D (both, P < .001). CNR of the liver improved from QIR-off to QIR-4 by 74% for 60 keV and by 69% for T3D (both, P < .001). No evidence of difference was found in mean attenuation of fat and liver (P = .79-.84) and on a voxel-wise basis among reconstructions. Qualitatively, QIR-4 outperformed all reconstructions in every category for 60 keV and T3D (P value range, <.001 to .01). All four readers rated QIR-4 superior to other strengths for lesion conspicuity (P value range, <.001 to .04). Conclusion In portal venous abdominal photon-counting detector CT, an iterative reconstruction algorithm (QIR; Siemens Healthcare) at high strength levels improved image quality by reducing noise and improving contrast-to-noise ratio and lesion conspicuity without compromising image texture or CT attenuation values. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Sinitsyn in this issue.

Diagnosis of acute heart failure in CT pulmonary angiography: feasibility and accuracy.

OBJECTIVES: To evaluate the feasibility and accuracy of diagnosing acute heart failure (HF) with CT pulmonary angiography (CTPA) in emergency department patients. METHODS: In this retrospective single-center study, we evaluated 150 emergency department patients (mean age 65 ± 17 years) undergoing CTPA with a fixed scan (100 kVp) and contrast media protocol (60 mL, 4 mL/s) who had no pulmonary embolism (PE). Patients were subdivided into training cohort (n = 100) and test cohort (n = 50). Three independent, blinded readers measured the attenuation in the right ventricle (RV) and left ventricle (LV) on axial images. The ratio (HUratio) and difference (HUdiff) between RV and LV attenuation were calculated. Diagnosis of acute HF was made on the basis of clinical, laboratory, and echocardiography data. Optimal thresholds, sensitivity, and specificity were calculated using the area under the curve (AUC) from receiver operating characteristics analysis. RESULTS: Fifty-nine of the 150 patients (40%) were diagnosed with acute HF. Attenuation measurements showed an almost perfect interobserver agreement (intraclass correlation coefficient: 0.986, 95%CI: 0.980-0.991). NT-pro BNP exhibited moderate correlations with HUratio (r = 0.50, p < 0.001) and HUdiff (r = 0.50, p < 0.001). In the training cohort, HUratio (AUC: 0.89, 95%CI: 0.82-0.95) and HUdiff (AUC: 0.88, 95%CI: 0.81-0.95) showed a very good performance to diagnose HF. Optimal cutoff values were 1.42 for HUratio (sensitivity 93%; specificity 75%) and 113 for HUdiff (sensitivity 93%; specificity 73%). Applying these thresholds to the test cohort yielded a sensitivity of 89% and 89% and a specificity of 69% and 63% for HUratio and HUdiff, respectively. CONCLUSION: In emergency department patients undergoing CTPA and showing no PE, both HUratio and HUdiff have a high sensitivity for diagnosing acute HF. KEY POINTS: • Heart failure is a common differential diagnosis in patients undergoing CT pulmonary angiography. • In emergency department patients undergoing CT pulmonary angiography and showing no pulmonary embolism, attenuation differences of the left and right ventricle have a high sensitivity for diagnosing acute heart failure.

Comparison of detection of trauma-related injuries using combined "all-in-one" fused images and conventionally reconstructed images in acute trauma CT.

OBJECTIVES: To compare the accuracy of lesion detection of trauma-related injuries using combined "all-in-one" fused (AIO) and conventionally reconstructed images (CR) in acute trauma CT. METHODS: In this retrospective study, trauma CT of 66 patients (median age 47 years, range 18-96 years; 20 female (30.3%)) were read using AIO and CR. Images were independently reviewed by 4 blinded radiologists (two residents and two consultants) for trauma-related injuries in 22 regions. Sub-analyses were performed to analyze the influence of experience (residents vs. consultants) and body region (chest, abdomen, skeletal structures) on lesion detection. Paired t-test was used to compare the accuracy of lesion detection. The effect size was calculated (Cohen's d). Linear mixed-effects model with patients as the fixed effect and random forest models were used to investigate the effect of experience, reconstruction/image processing, and body region on lesion detection. RESULTS: Reading time of residents was significantly faster using AIO (AIO: 266 ± 72 s, CR: 318 ± 113 s; p < 0.001; d = 0.46) while no significant difference was observed in the accuracy of lesion detection (AIO: 93.5 ± 6.0%, CR: 94.6 ± 6.0% p = 0.092; d = - 0.21). Reading time of consultants showed no significant difference (AIO: 283 ± 82 s, CR: 274 ± 95 s; p = 0.067; d = 0.16). Accuracy was significantly higher using CR; however, the difference and effect size were very small (AIO 95.1 ± 4.9%, CR: 97.3 ± 3.7%, p = 0.002; d = - 0.39). The linear mixed-effects model showed only minor effect of image processing/reconstruction for lesion detection. CONCLUSIONS: Residents at the emergency department might benefit from faster reading time without sacrificing lesion detection rate using AIO for trauma CT. KEY POINTS: • Image fusion techniques decrease the reading time of acute trauma CT without sacrificing diagnostic accuracy.

Epicardial Adipose Tissue Attenuation and Fat Attenuation Index: Phantom Study and In Vivo Measurements With Photon-Counting Detector CT.

BACKGROUND. Epicardial adipose tissue (EAT) attenuation is a vascular inflammation marker predictive of adverse cardiac events. The fat attenuation index (FAI) assesses fat attenuation for predefined coronary segments. Photon-counting detector (PCD) CT uses routine virtual monoenergetic image (VMI) reconstructions. VMI energy level may affect EAT attenuation and FAI measurements. OBJECTIVE. The purpose of this article was to assess EAT attenuation and FAI measurements at different monoenergetic energy levels in patients undergoing coronary CTA using a first-generation whole-body dual-source PCD CT scanner. METHODS. An anthropomorphic phantom at two sizes with a fat insert was imaged on a first-generation dual-source PCD CT scanner and, as a reference, on a conventional energy-integrating detector (EID) CT scanner at 120 kV. Thirty patients (11 women, 19 men; mean age, 48 ± 10 years; Agatston score < 60) who underwent an ECG-gated unenhanced calcium-scoring scan and contrast-enhanced coronary CTA by PCD CT were retrospectively evaluated. VMIs from 55 to 80 keV at 5-keV increments were reconstructed. EAT attenuation was manually measured on unenhanced and contrast-enhanced images. FAI was calculated using semiautomated software. RESULTS. The attenuation of the phantom fat insert was -69 HU for the reference EID CT; the closest attenuation for PCD CT was observed at 70 keV for the small (-69 HU) and large (-70 HU) phantoms. In patients, EAT attenuation increased for unenhanced acquisition from -111 ± 11 HU at 55 keV to -82 ± 9 HU at 80 keV and for contrast-enhanced acquisition from -104 ± 11 HU at 55 keV to -81 ± 9 HU at 80 keV. The mean attenuation difference between unenhanced and contrast-enhanced scans decreased with increasing energy level (from 7 ± 12 HU to 1 ± 10 HU). The FAI increased from -89 ± 8 HU at 55 keV to -77 ± 12 HU at 80 keV for the right coronary artery, -95 ± 11 HU at 55 keV to -85 ± 11 HU at 80 keV for the left anterior descending artery, and -87 ± 10 HU at 55 keV to -80 ± 12 HU at 80 keV for the circumflex artery. CONCLUSION. EAT attenuation and FAI measurements using PCD CT are impacted by VMI energy level and contrast enhancement. Use of VMI reconstruction at 70 keV provides fat attenuation approximating conventional polychromatic measurements. CLINICAL IMPACT. The findings may help standardize evaluation of pericoronary inflammation by PCD CT as a measure of patients' cardiac risk.

Segmental strain for scar detection in acute myocardial infarcts and in follow-up exams using non-contrast CMR cine sequences.

BACKGROUND: The purpose of the study was to investigate feasibility of infarct detection in segmental strain derived from non-contrast cardiac magnetic resonance (CMR) cine sequences in patients with acute myocardial infarction (AMI) and in follow-up (FU) exams. METHODS: 57 patients with AMI (mean age 61 ± 12 years, CMR 2.8 ± 2 days after infarction) were retrospectively included, FU exams were available in 32 patients (35 ± 14 days after first CMR). 43 patients with normal CMR (54 ± 11 years) served as controls. Dedicated software (Segment CMR, Medviso) was used to calculate global and segmental strain derived from cine sequences. Cine short axis stacks and segmental circumferential strain calculations of every patient and control were presented to two blinded readers in random order, who were advised to identify potentially infarcted segments, blinded to LGE and clinical information. RESULTS: Impaired global strain was measured in AMI patients compared to controls (global peak circumferential strain [GPCS] p = 0.01; global peak longitudinal strain [GPLS] p = 0.04; global peak radial strain [GPRS] p = 0.01). In both imaging time points, mean segmental peak circumferential strain [SPCS] was impaired in infarcted tissue compared to remote segments (AMI: p = 0.03, FU: p = 0.02). SPCS values in infarcted segments were similar between AMI and FU (p = 0.8). In SPCS calculations, 141 from 189 acutely infarcted segments were accurately detected (74.6%), visual evaluation of correlating cine images detected 43.4% infarcts. In FU, 80% infarcted segments (91/114 segments) were detected in SPCS and 51.8% by visual evaluation of correlating short axis cine images (p = 0.01). CONCLUSION: Segmental circumferential strain derived from routinely acquired native cine sequences detects nearly 75% of acute infarcts and 80% of infarcts in subacute follow-up CMR, significantly more than visual evaluation of correlating cine images alone. Acute infarcts may display only subtle impairment of wall motion and no obvious wall thinning, thus SPCS calculation might be helpful for scar detection in patients with acute infarcts, when LGE images are not available.

Bone Mineral Density Quantification from Localizer Radiographs: Accuracy and Precision of Energy-integrating Detector CT and Photon-counting Detector CT.

Background Bone mineral density (BMD) could be derived from CT localizer radiographs and could potentially enable opportunistic osteoporosis screening. Purpose To assess the accuracy and precision of BMD measurement using two localizer radiographs obtained with energy-integrating detector CT and a single localizer radiograph obtained with photon-counting detector CT. Materials and Methods A calibration phantom and a porcine phantom with lumbar vertebrae were imaged with a dual-energy x-ray absorptiometry (DXA) scanner, a clinical energy-integrating detector CT scanner, and a prototype photon-counting detector CT scanner. Two localizer radiographs at different combinations of tube voltages were obtained with energy-integrating detector CT, and one localizer radiograph was obtained with photon-counting detector CT using different energy thresholds. BMD was calculated for all three approaches and compared with the known specifications in the calibration phantom. In the animal phantom, BMDs from both CT systems were compared with those from the DXA scanner (the reference standard). Accuracy was defined as the measurement error of BMD (ΔBMD), and precision was defined as the coefficient of variation (in percentage). Radiation doses were estimated. Nonparametric tests were applied. Results In the calibration phantom, ΔBMD was smaller with both CT systems compared with the DXA scanner (both P < .05). ΔBMD ranged from -5% to -1.8% for DXA, from -2.3% to -1.7% for energy-integrating detector CT, and from -1.6% to 1.6% for photon-counting detector CT. Precision (range, 0.3%-2.8%) was high for both CT systems. In the animal phantom, ΔBMD ranged from -0.6% to 0.1% for energy-integrating detector CT and from -0.1% to 0.6% for photon-counting detector CT, with no significant differences between CT systems (P = .65). The dose-area product in the animal phantom was 4.6 cGy ∙ cm2 for DXA, 3.5-11.5 cGy ∙ cm2 for energy-integrating detector CT, and 7.2-11.2 cGy ∙ cm2 for photon-counting detector CT, depending on tube voltage and energy threshold combination. Conclusion Experimental evidence suggests that bone mineral density measurements are accurate and precise using two localizer radiographs at different tube voltages from energy-integrating detector CT and a single localizer radiograph with different energy thresholds from photon-counting detector CT. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Pourmorteza in this issue.

Incremental Prognostic Value of Coronary Artery Calcium Score for Predicting All-Cause Mortality after Transcatheter Aortic Valve Replacement.

Background Current risk models show limited performances for predicting all-cause mortality after transcatheter aortic valve replacement (TAVR). Purpose To determine the prognostic value of coronary artery calcium (CAC) scoring for predicting 30-day and 1-year mortality in patients undergoing TAVR. Materials and Methods In this single-center institutional review board-approved secondary analysis of prospectively collected data (SwissTAVI Registry), the authors evaluated participants who, before TAVR, underwent CT that included a nonenhanced electrocardiography-gated cardiac scan between May 2008 and September 2019 and who had not undergone previous coronary revascularization. Clinical data, including the European System for Cardiac Operative Risk Evaluation (EuroSCORE II), were recorded. The CAC score was determined, and 30-day and 1-year all-cause mortality were assessed by using Cox regression analyses. Results In total, 309 participants (mean age ± standard deviation, 81 years ± 7; 175 women) were included, with a median CAC score of 334 (interquartile range, 104-987). Seventy-seven of the 309 participants (25%) had a CAC score greater than or equal to 1000. A CAC score of 1000 or greater served as an independent predictor of 30-day (hazard ratio [HR], 4.5 [95% CI: 1.5, 13.6] compared with a CAC score <1000; P = .007) and 1-year (HR, 4.3 [95% CI: 1.5, 12.7] compared with a CAC score of 0-99; P = .008) mortality after TAVR. Similar trends were observed for each point increase of the EuroSCORE II as an independent predictor of 30-day (HR, 1.22 [95% CI: 1.10, 1.36]; P < .001) and 1-year (HR, 1.16 [95% CI: 1.08, 1.25]; P < .001) mortality. Adding the CAC score to the EuroSCORE II provided incremental prognostic value for 1-year mortality after TAVR over the EuroSCORE II alone (concordance index, 0.76 vs 0.69; P = .04). Conclusion In participants without prior coronary revascularization, the coronary artery calcium score represented an independent predictor of 30-day and 1-year mortality after transcatheter aortic valve replacement. ClinicalTrials.gov identifier, NCT01368250 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Almeida in this issue.

Artificial Intelligence and Texture Analysis in Cardiac Imaging.

PURPOSE OF REVIEW: The aim of this structured review is to summarize the current research applications and opportunities arising from artificial intelligence (AI) and texture analysis with regard to cardiac imaging. RECENT FINDINGS: Current research findings suggest tremendous potential for AI in cardiac imaging, especially with regard to objective image analyses, overcoming the limitations of an observer-dependent subjective image interpretation. Researchers have used this technique across multiple imaging modalities, for instance to detect myocardial scars in cardiac MR imaging, to predict contrast enhancement in non-contrast studies, and to improve image acquisition and reconstruction. AI in medical imaging has the potential to provide novel, much-needed applications for improving patient care pertaining to the cardiovascular system. While several shortcomings are still present in the current methodology, AI may serve as a resourceful assistant to radiologists and clinicians alike.

[Pulmonary nodules - an overview]. / Lungenrundherde ­ Ein Überblick.

Pulmonary nodules - an overview Abstract. Computed tomography (CT) offers fast temporal and high spatial resolution and is increasingly employed for various investigations. Since the 1990s, when multislice computed tomography (CT) technique became commonly available, the detection rate of incidentally detected pulmonary nodules has increased. The aetiology of pulmonary nodules can range from infectious over interstitial lung disease to malignant entities and pose a diagnostic dilemma: Should the incidental finding be dismissed or further investigated? If further investigated which modality and which time frame should be used? Due to the multidisciplinary nature of data required for the complex assessment of an incidental pulmonary nodule, management guidelines are needed in the diagnostic process such as those proposed by the Fleischner Society. The aim of this review is to discuss the different aetiologies pf pulmonary nodules and their potential work-up. Finally, we will also discuss the utility of lung cancer screening.

[Non-invasive Imaging of Chronic Coronary Syndromes - CT Coronary Angiography and Stress Perfusion Cardiac MRI]. / Nicht-invasive Diagnostik der chronischen koronaren Herzkrankheit ­ CT-Koronarangio­graphie und Stress-MRT.

Non-invasive Imaging of Chronic Coronary Syndromes - CT Coronary Angiography and Stress Perfusion Cardiac MRI Abstract. Coronary artery disease (CAD) is amongst the leading causes of death worldwide. The European Society of Cardiology (ESC) has recently published new guidelines on diagnosis and management of chronic coronary syndromes. These guidelines emphasize the use of non-invasive imaging tests to assess CAD. Compared to previous versions of these guidelines, the pre-test probabilities of CAD based on age, sex and symptoms have been adjusted downward. Unless obstructive CAD can be excluded by clinical assessment alone, various strategies to diagnose CAD in symptomatic patients may be used: coronary CT angiography, non-invasive functional imaging for myocardial ischaemia, or invasive coronary angiography combined with functional evaluation. This review summarizes strengths and weaknesses of non-invasive cardiac imaging modalities with emphasize on coronary CT angiography and stress perfusion cardiac magnetic resonance (CMR) imaging.

CT Angiography of the Aorta: Contrast Timing by Using a Fixed versus a Patient-specific Trigger Delay.

Background Optimal timing of the CT scan relative to the contrast media bolus remains a challenging task given the shorter scan durations of modern CT scanners, as well as interpatient variability. Purpose To compare contrast opacification in CT angiography of the aorta between a cohort with fixed trigger delay and a cohort with patient-specific individualized trigger delay for contrast media timing with bolus tracking. Materials and Methods In this prospective study (January-August 2018), CT angiography of the thoracoabdominal aorta with bolus tracking was performed in two different study cohorts: one with a fixed trigger delay of 4 seconds (fixed cohort) and one with a patient-specific trigger delay (individualized cohort). All CT and contrast media protocol parameters were kept identical among cohorts. Objective image quality was evaluated by one reader; two readers assessed subjective image quality. Student t test was used to test for differences in mean attenuation; the Wilcoxon-Mann-Whitney test was used to test for differences in noise, contrast-to-noise ratio, and subjective image quality. Results The fixed cohort had 108 study participants (16 women; mean age ± standard deviation, 72 years ± 10); the individualized cohort had 108 participants (16 women; mean age, 72 years ± 12). The trigger delay in the individualized cohort ranged from 6.4-11.3 seconds (mean, 9.2 seconds). There was higher overall attenuation in the individualized cohort than in the fixed cohort (486 HU ± 92 for individualized vs 438 HU ± 99 for fixed; P < .001), with increasing differences from the aortic arch (8 HU) to the iliac arteries (95 HU). The regression model indicated uniform attenuation in the individualized cohort and decreasing attenuation in the fixed cohort (decrease of 87 HU by the iliac arteries; P < .001). There was no difference between cohorts for image noise (20 vs 19; P = .41), but contrast-to-noise ratio (21 vs 19; P = .04) and subjective image quality were higher in the individualized cohort than in the fixed cohort (excellent or good image quality, 100% vs 67%; P < .001). Conclusion Compared with a fixed delay time after bolus tracking, a patient-specific individualized trigger delay improves image quality and provides uniform contrast attenuation for CT angiography of the aorta. ©RSNA, 2019.

Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making.

OBJECTIVES: To evaluate a deep convolutional neural network (dCNN) for detection, highlighting, and classification of ultrasound (US) breast lesions mimicking human decision-making according to the Breast Imaging Reporting and Data System (BI-RADS). METHODS AND MATERIALS: One thousand nineteen breast ultrasound images from 582 patients (age 56.3 ± 11.5 years) were linked to the corresponding radiological report. Lesions were categorized into the following classes: no tissue, normal breast tissue, BI-RADS 2 (cysts, lymph nodes), BI-RADS 3 (non-cystic mass), and BI-RADS 4-5 (suspicious). To test the accuracy of the dCNN, one internal dataset (101 images) and one external test dataset (43 images) were evaluated by the dCNN and two independent readers. Radiological reports, histopathological results, and follow-up examinations served as reference. The performances of the dCNN and the humans were quantified in terms of classification accuracies and receiver operating characteristic (ROC) curves. RESULTS: In the internal test dataset, the classification accuracy of the dCNN differentiating BI-RADS 2 from BI-RADS 3-5 lesions was 87.1% (external 93.0%) compared with that of human readers with 79.2 ± 1.9% (external 95.3 ± 2.3%). For the classification of BI-RADS 2-3 versus BI-RADS 4-5, the dCNN reached a classification accuracy of 93.1% (external 95.3%), whereas the classification accuracy of humans yielded 91.6 ± 5.4% (external 94.1 ± 1.2%). The AUC on the internal dataset was 83.8 (external 96.7) for the dCNN and 84.6 ± 2.3 (external 90.9 ± 2.9) for the humans. CONCLUSION: dCNNs may be used to mimic human decision-making in the evaluation of single US images of breast lesion according to the BI-RADS catalog. The technique reaches high accuracies and may serve for standardization of highly observer-dependent US assessment. KEY POINTS: • Deep convolutional neural networks could be used to classify US breast lesions. • The implemented dCNN with its sliding window approach reaches high accuracies in the classification of US breast lesions. • Deep convolutional neural networks may serve for standardization in US BI-RADS classification.

Pre-procedural CT angiography inferior vena cava measurements: a predictor of mortality in patients undergoing transcatheter aortic valve implantation.

OBJECTIVES: To assess the value of pre-procedural computed tomography angiography (CTA) measurements of the suprahepatic inferior vena cava (IVC) to detect elevated central venous pressure (CVP) assessed by right heart catheterisation (RHC), and to predict post-procedural 1-year mortality in a cohort of patients undergoing transcatheter aortic valve implantation (TAVI). METHODS: We retrospectively evaluated 408 consecutive patients undergoing CTA before TAVI between January 2011 and December 2014. Two hundred and five patients were included in the RHC cohort, who underwent RHC and CTA within ≤1 day prior to TAVI. Two hundred and three patients not fulfilling this requirement were included in the validation cohort. Measurements of the IVC were performed between diaphragm and right atrium on axial slices. Receiver operating characteristic (ROC) analyses, Kaplan-Meier analyses and Cox regression analyses were performed. RESULTS: In the RHC cohort, ROC curve analyses for IVC area measurements indicated an AUC of 0.77 (p < 0.001) to detect CVP ≥10mmHg and an area under the ROC curve (AUC) of 0.72 (p < 0.001) to predict 1-year mortality. An IVC area cut-off of ≥665 mm2 predicted 1-year mortality with a specificity of 84% and a sensitivity of 63%. Kaplan-Meier analysis showed that patients with an IVC area ≥665 mm2 had a significantly higher post-procedural 1-year mortality (38% versus 7%, log-rank p < 0.001) with a hazard ratio of 5.5 (95% CI, 2.2-13.6; p < 0.001). Applying this cut-off value to the validation cohort confirmed a significantly higher 1-year mortality after TAVI (34% versus 11%; log-rank p = 0.004) for patients with an IVC area ≥665 mm2. CONCLUSIONS: Pre-procedural enlargement of the suprahepatic IVC is a predictor of post-procedural 1-year mortality in patients evaluated for TAVI. KEY POINTS: • IVC measurements are moderate predictors of an elevated CVP in TAVI patients. • Pre-procedural IVC enlargement is a predictor of 1-year mortality after TAVI. • IVC enlargement is associated with right heart dysfunction in TAVI patients.