Incidental findings are frequent in shoulder CT and MRI scans and increase with age.

Objectives: CT and MRI scans of the shoulder can lead to the identification of incidental findings (IF), which can have a major impact on the further treatment of the patient. The aim of this retrospective study was to record the prevalence of IF, incidentalomas (IT) and malignant IT for CT and MRI examinations of the shoulder and to investigate the effect of patient characteristics on the statistical occurrence of IF, IT and malignant IT. Materials and methods: A total of 903 shoulder examinations (415 CT, 488 MRI) were retrospectively analyzed for the presence of IF, subsequently categorized (harmless IF, IT requiring clarification, malignant IT) and analyzed regarding patient characteristics. The statistical analysis was carried out using independent t- and chi-square tests. A significance level of p < 0.05 was set. Results: Among the 903 patients evaluated (436 female, 467 male), 153 (16.9%) patients experienced IF (harmless IF: 101 (11.2%) patients, IT: 94 (10.4%), malignant IT: 4 (0.4%). The average age of the patients without IF and IT was significantly lower compared to the patients with IF and IT (p < 0.001). While IF occurred in 31.1% of the CT, IF was only detected in 4.9% of the MRI (p < 0.001). Conclusion: IF have a high prevalence (16.9%), especially in CT examinations of the shoulder, which increases with age. The exact detection and initiation of appropriate therapy is of great clinical importance, as early detection of life-threatening diseases enables more effective treatment and a potential gain in health and lifespan.

Intra- and inter-reader reproducibility in quantitative coronary plaque analysis on coronary computed tomography angiography.

PURPOSE: Coronary artery plaque burden, low attenuation non-calcified plaque (LAP), and pericoronary adipose tissue (PCAT) on coronary CT angiography (CCTA), have been linked to future cardiac events. The purpose of this study was to evaluate intra- and inter reader reproducibility in the quantification of coronary plaque burden and its characteristics using an artificial intelligence-enhanced semi-automated software. MATERIALS AND METHODS: A total of 10 women and 6 men, aged 52 (IQR 49-58) underwent CCTA using a Siemens Somatom Force, Somatom Definition AS and Somatom Definition Flash scanners. Two expert readers utilized dedicated semi-automatic software (vascuCAP, Elucid Bioimaging, Wenham, MA) to assess calcified plaque, low attenuation plaque and PCAT. Readers were blinded to all clinical information and repeated their analysis at 6 weeks in random order to minimize recall bias. Data analysis was performed on the right and left coronary arteries. Intra- and inter-reader reproducibility was compared using Pearson correlation coefficient, while absolute values between analyses and readers were compared with paired non-parametric tests. This is a sub-study of the Specialized Center of Research Excellence (SCORE) clinical trial (5U54AG062334). RESULTS: A total of 64 vessels from 16 patients were analyzed. Intra-reader Pearson correlation coefficients for calcified plaque volume, LAP volume and PCAT volumes were 0.96, 0.99 and 0.92 for reader 1 and 0.94, 0.94 and 0.95 for reader 2, respectively, (all p < 0.0001). Inter-reader Pearson correlation coefficients for calcified plaque volume, LAP and PCAT volumes were 0.92, 0.96 and 0.78, and 0.99, 0.99 and 0.93 on the second analyses, all had a p value <0.0001. There was no significant bias on the corresponding Bland-Altman analyses. CONCLUSION: Volume measurement of coronary plaque burden and PCAT volume can be performed with high intra- and inter-reader agreement.

Artificial intelligence for advanced analysis of coronary plaque.

The field of coronary plaque analysis is advancing including more quantitative analysis of coronary artery diseases such as plaque burden, high-risk plaque features, computed tomography-derived fractional flow reserve, and radiomics. Although these biomarkers have shown great promise for the diagnosis and prognosis of cardiac patients in a research setting, many of these advanced analyses are labour and time intensive and therefore hard to implement in daily clinical practice. Artificial intelligence (AI) is playing an increasing role in supporting the quantification of these new biomarkers. AI offers the opportunity to increase efficiency, reduce human error and reader variability and to increase the accuracy of diagnosis and prognosis by automating many processing and supporting clinicians in their decision-making. With the use of AI these novel analysis approaches for coronary artery disease can be made feasible for clinical practice without increasing cost and workload and potentially improve patient care.

Additive value of epicardial adipose tissue quantification to coronary CT angiography-derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia.

OBJECTIVES: Epicardial adipose tissue (EAT) from coronary CT angiography (CCTA) is strongly associated with coronary artery disease (CAD). We investigated the additive value of EAT volume to coronary plaque quantification and CT-derived fractional flow reserve (CT-FFR) to predict lesion-specific ischemia. METHODS: Patients (n = 128, 60.6 ± 10.5 years, 61% male) with suspected CAD who had undergone invasive coronary angiography (ICA) and CCTA were retrospectively analyzed. EAT volume and plaque measures were derived from CCTA using a semi-automatic software approach, while CT-FFR was calculated using a machine learning algorithm. The predictive value and discriminatory power of EAT volume, plaque measures, and CT-FFR to identify ischemic CAD were assessed using invasive FFR as the reference standard. RESULTS: Fifty-five of 152 lesions showed ischemic CAD by invasive FFR. EAT volume, CCTA ≥ 50% stenosis, and CT-FFR were significantly different in lesions with and without hemodynamic significance (all p < 0.05). Multivariate analysis revealed predictive value for lesion-specific ischemia of these parameters: EAT volume (OR 2.93, p = 0.021), CCTA ≥ 50% (OR 4.56, p = 0.002), and CT-FFR (OR 6.74, p < 0.001). ROC analysis demonstrated incremental discriminatory value with the addition of EAT volume to plaque measures alone (AUC 0.84 vs. 0.62, p < 0.05). CT-FFR (AUC 0.89) showed slightly superior performance over EAT volume with plaque measures (AUC 0.84), however without significant difference (p > 0.05). CONCLUSIONS: EAT volume is significantly associated with ischemic CAD. The combination of EAT volume with plaque quantification demonstrates a predictive value for lesion-specific ischemia similar to that of CT-FFR. Thus, EAT may aid in the identification of hemodynamically significant coronary stenosis. KEY POINTS: • CT-derived EAT volume quantification demonstrates high discriminatory power to identify lesion-specific ischemia. • EAT volume shows incremental diagnostic performance over CCTA-derived plaque measures in detecting lesion-specific ischemia. • A combination of plaque measures with EAT volume provides a similar discriminatory value for detecting lesion-specific ischemia compared to CT-FFR.

Value of Latest-generation Cone-beam Computed Tomography for Post Lipiodol-embolization Imaging in Hepatic Transarterial Chemoembolization in Comparison with Multi-detector Computed Tomography.

RATIONALE AND OBJECTIVES: To evaluate image quality, radiation dose (phantom study) and tumor volumetry of intraprocedural cone-beam computed tomography (CBCT) compared to postprocedural multidetector computed tomography (MDCT) in patients undergoing hepatic conventional transarterial chemoembolization (cTACE). MATERIALS AND METHODS: One hundred fourteen patients (64/50 female/male; mean age, 57 ± 14 years) who had undergone cTACE including intraprocedural-CBCT and postprocedural-MDCT were retrospectively enrolled. Subjective image quality (IQ) and suitability for assessing Lipiodol distribution were compared using 4-point Likert scales; additionally, lesion to liver contrast (LLC) and contrast-to-noise-ratio (CNR) were compared. Tumor volumes were measured semi-automatically and compared to magnetic resonance imaging (MRI). Effective doses were measured using an anthropomorphic phantom. RESULTS: The suitability of CBCT for assessing Lipiodol distribution during cTACE was comparable to MDCT (mean score, 3.2 ± 0.6) and CBCT (3.4 ± 1.0, p = 0.29). Subjective overall IQ was rated with a mean score of 3.2 ± 0.7 (κ = 0.66) in CBCT and 3.1 ± 0.4 (κ = 0.57, p = 0.15) in MDCT. Evaluation of LLC showed significant differences between CBCT and MDCT (mean scores 3.6 ± 1.2 and 2.6 ± 1.5, respectively). CNR analysis demonstrated comparable mean values for CBCT and MDCT (3.5 ± 1.3 vs. 3.4 ± 1.8, p = 0.31). No significant differences were found regarding tumor volumetry (mean volumes: CBCT, 27.0 ± 17.4 mm3; MDCT: 26.8 ± 16.0 mm3; p = 0.66) in comparison to T2-weighted MRI (25.9 ± 17.6 mm3). Effective doses were 3.2 ± 0.6 mSv (CBCT) and 2.5 ± 0.3 mSv (MDCT) (p < 0.001). No cTACE-related complications (bleeding, non-target embolization) were missed on intraprocedural CBCT in comparison to postprocedural MDCT. CONCLUSION: Latest-generation intraprocedural CBCT provides suitable assessment of Lipiodol distribution and similar image quality compared to MDCT while allowing for robust volumetric tumor measurements and immediate complication control by visualizing non-target embolization and hematoma. Therefore, it may improve patient safety and outcome as well as clinical workflow compared to postprocedural MDCT in hepatic cTACE in certain cases.

Long-term evaluation of pain reduction after vertebroplasty and kyphoplasty.

BACKGROUND: Various studies have been made about the most effective and safest type of treatment for vertebral compression fractures (VCFs). Long-term results are needed for qualitative evaluation. PURPOSE: The purpose of the study is to evaluate the effectiveness of percutaneous vertebroplasty (PVP) and percutaneous kyphoplasty (PKP) procedures for VCFs. MATERIALS AND METHODS: Forty-nine patients who received either PVP or PKP between 2002 and 2015 returned a specially developed questionnaire and were included in a cross-sectional outcome analysis. The questionnaire assessed pain development by use of a visual analog scale (VAS). Imaging data (CT scans) were retrospectively analyzed for identification of cement leakage. RESULTS: Patients' VAS scores significantly decreased after treatment (7.0 ± 3.4 => 3.7 ± 3.4), (p < 0.001). The average pain reduction in patients treated with PVP was -3.3 ± 3.8 (p < 0.001) (median -3.5) and -4.0 ± 3.9 (p < 0.001) (median -4.5) in patients treated with PKP. Fifteen Patients (41.7%) receiving PVP and four patients (30.7%) receiving PKP experienced recurrence of pain. Cement leakage occurred in 10 patients (22.73%). Patients with cement leakage showed comparable VAS scores after treatment (6.8 ± 3.5 => 1.4 ± 1.6), (p = 0.008). Thirty-nine patients reported an increase in mobility (79.6%) and 41 patients an improvement in quality of life (83.7%). CONCLUSION: Pain reduction by means of PVP or PKP in patients with VCFs was discernible over the period of observation. Percutaneous vertebroplasty and PKP contribute to the desired treatment results. However, the level of low pain may not remain constant.

Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome.

This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 ± 11 years, 62% men) who underwent cCTA and invasive coronary angiography (ICA) were analyzed in this single-center retrospective, institutional review board-approved, HIPAA-compliant study. Follow-up was performed to record major adverse cardiac events (MACE). Plaque quantification of lesions responsible for MACE and control lesions was retrospectively performed semiautomatically from cCTA together with machine-learning based CT-FFR. The discriminatory value of plaque markers and CT-FFR to predict MACE was evaluated. After a median follow-up of 18.5 months (interquartile range 11.5 to 26.6 months), MACE was observed in 18 patients (21%). In a multivariate analysis the following markers were predictors of MACE (odds ratio [OR]): lesion length (OR 1.16, p = 0.018), low-attenuation plaque (<30 HU) (OR 4.59, p = 0.003), Napkin ring sign (OR 2.71, p = 0.034), stenosis ≥50% (OR 3.83, p 0.042), and CT-FFR ≤0.80 (OR 7.78, p = 0.001). Receiver operating characteristics analysis including stenosis ≥50%, plaque markers and CT-FFR ≤0.80 (Area under the curve 0.94) showed incremental discriminatory power over stenosis ≥50% alone (Area under the curve 0.60, p <0.0001) for the prediction of MACE. cCTA-derived plaque markers and machine-learning CT-FFR demonstrate predictive value to identify MACE. In conclusion, combining plaque markers with machine-learning CT-FFR shows incremental discriminatory power over cCTA stenosis grading alone.

Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia.

OBJECTIVES: We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FFR as the reference standard. METHODS: Eighty-four patients (61 ± 10 years, 65% male) who had undergone cCTA followed by invasive FFR were included in this single-center retrospective, IRB-approved, HIPAA-compliant study. Various plaque markers were derived from cCTA using a semi-automatic software prototype and deep machine learning-based CT-FFR. The discriminatory value of plaque markers and CT-FFR to identify lesion-specific ischemia on a per-vessel basis was evaluated using invasive FFR as the reference standard. RESULTS: One hundred three lesion-containing vessels were investigated. 32/103 lesions were hemodynamically significant by invasive FFR. In a multivariate analysis (adjusted for Framingham risk score), the following markers showed predictive value for lesion-specific ischemia (odds ratio [OR]): lesion length (OR 1.15, p = 0.037), non-calcified plaque volume (OR 1.02, p = 0.007), napkin-ring sign (OR 5.97, p = 0.014), and CT-FFR (OR 0.81, p < 0.0001). A receiver operating characteristics analysis showed the benefit of identifying plaque markers over cCTA stenosis grading alone, with AUCs increasing from 0.61 with ≥ 50% stenosis to 0.83 with addition of plaque markers to detect lesion-specific ischemia. Further incremental benefit was realized with the addition of CT-FFR (AUC 0.93). CONCLUSION: Coronary CTA-derived plaque markers portend predictive value to identify lesion-specific ischemia when compared to cCTA stenosis grading alone. The addition of CT-FFR to plaque markers shows incremental discriminatory power. KEY POINTS: • Coronary CT angiography (cCTA)-derived quantitative plaque markers of atherosclerosis portend high discriminatory power to identify lesion-specific ischemia. • Coronary CT angiography-derived fractional flow reserve (CT-FFR) shows superior diagnostic performance over cCTA alone in detecting lesion-specific ischemia. • A combination of plaque markers with CT-FFR provides incremental discriminatory value for detecting flow-limiting stenosis.

Dual-energy CT of the heart current and future status.

Several applications utilizing dual-energy cardiac CT (DECT) have recently transitioned from the realm of research into clinical workflows. DECT acquisition techniques and subsequent post-processing can provide improved qualitative analysis, allow quantitative imaging, and have the potential to decrease requisite radiation and contrast material doses. Additionally, several experimental DECT techniques are pending further investigation and may improve the diagnostic accuracy of cardiac CT and/or provide evaluation of emerging imaging biomarkers in the future. This review article will summarize the major applications utilizing DECT in diagnosis of cardiovascular disease, including both the clinically used and investigational techniques examined to date.