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Suspected coronary artery disease (CAD) is one of the most common, potentially life-threatening diagnostic problems clinicians encounter. However, no large outcome-based randomized trials have been performed to guide the selection of diagnostic strategies for these patients. The PROMISE study is a prospective, randomized trial comparing the effectiveness of 2 initial diagnostic strategies in patients with symptoms suspicious for CAD. Patients are randomized to either (1) functional testing (exercise electrocardiogram, stress nuclear imaging, or stress echocardiogram) or (2) anatomical testing with ≥64-slice multidetector coronary computed tomographic angiography. Tests are interpreted locally in real time by subspecialty certified physicians, and all subsequent care decisions are made by the clinical care team. Sites are provided results of central core laboratory quality and completeness assessment. All subjects are followed up for ≥1 year. The primary end point is the time to occurrence of the composite of death, myocardial infarction, major procedural complications (stroke, major bleeding, anaphylaxis, and renal failure), or hospitalization for unstable angina. More than 10,000 symptomatic subjects were randomized in 3.2 years at 193 US and Canadian cardiology, radiology, primary care, urgent care, and anesthesiology sites. Multispecialty community practice enrollment into a large pragmatic trial of diagnostic testing strategies is both feasible and efficient. The PROMISE trial will compare the clinical effectiveness of an initial strategy of functional testing against an initial strategy of anatomical testing in symptomatic patients with suspected CAD. Quality of life, resource use, cost-effectiveness, and radiation exposure will be assessed.

Tirzepatide is a novel once-week dual GIP/GLP-1 RA agonist approved for T2DM and its role to reduce cardiovascular events remains to be elucidated. The goal of this trial is to assess how tirzepatide affects the progression of atherosclerotic plaque as determined by multidetector computed tomography angiography (MDCTA). This trial is a double blind, randomized, prospective, placebo-controlled multicenter phase IV trial. Participant eligible for the study will be adults with T2DM between 40 and 80 years of age who have HbA1c ≥ 7.0% to ≤ 10.5% and at least 20% stenosis in major epicardial vessel on CCTA. Baseline examination will include the results of their demographics, lab tests, coronary calcium, as well as coronary plaque volume/composition. Following randomization, tirzepatide or placebo will be given at a weekly dose of 2.5 mg, and a fixed dose-escalation strategy will be followed. Patients will undergo quarterly visits for safety assessments and labs, and follow up with repeat CCTA at 1 year. This study evaluates the antiatherogenic potential of tirzepatide, providing a mechanism of potential CV benefit. This is crucial to our understanding of T2DM treatment and CVD since plaque progression portends worse outcomes in these populations. MDCTA is a noninvasive method that assesses the volume, composition, and degree of coronary vessel stenosis. This study will be the first study to assess the effects of tirzepatide on atherosclerotic plaque progression measured by MDCTA in participants with T2DM.

ObjectivesThis study was conducted in order to evaluate a novel risk stratification model using dual-energy CT (DECT) texture analysis of head and neck squamous cell carcinoma (HNSCC) with machine learning to (1) predict associated cervical lymphadenopathy and (2) compare the accuracy of spectral versus single-energy (65 keV) texture evaluation for endpoint prediction.MethodsEighty-seven patients with HNSCC were evaluated. Texture feature extraction was performed on virtual monochromatic images (VMIs) at 65 keV alone or different sets of multi-energy VMIs ranging from 40 to 140 keV, in addition to iodine material decomposition maps and other clinical information. Random forests (RF) models were constructed for outcome prediction with internal cross-validation in addition to the use of separate randomly selected training (70%) and testing (30%) sets. Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined for predicting positive versus negative nodal status in the neck.ResultsDepending on the model used and subset of patients evaluated, an accuracy, sensitivity, specificity, PPV, and NPV of up to 88, 100, 67, 83, and 100%, respectively, could be achieved using multi-energy texture analysis. Texture evaluation of VMIs at 65 keV alone or in combination with only iodine maps had a much lower accuracy.ConclusionsMulti-energy DECT texture analysis of HNSCC is superior to texture analysis of 65 keV VMIs and iodine maps alone and can be used to predict cervical nodal metastases with relatively high accuracy, providing information not currently available by expert evaluation of the primary tumor alone.Key Points• Texture features of HNSCC tumor are predictive of nodal status.• Multi-energy texture analysis is superior to analysis of datasets at a single energy.• Dual-energy CT texture analysis with machine learning can enhance noninvasive diagnostic tumor evaluation.

ObjectivesTo assess the diagnostic accuracy (ACC) of post-mortem computed tomography (PMCT) for fractures of the isolated larynx-hyoid complex (LHC) in comparison to post-mortem fine preparation (PMFP).MethodsThis monocentric prospective study enclosed 54 LHCs that were extracted during autopsy, fixed in formalin, and underwent a PMCT scan (64-row multidetector CT, helical pitch). Two radiologists independently analyzed the LHC scans for image quality (IQ) and fractures (4-point Likert scales). A specialized forensic preparator dissected the specimens under the stereomicroscope. The PMFP results were standardized documented, and used as the standard of reference for the comparison to PMCT.ResultsThe PMCT-IQ of 95% of the LHC images was rated as good or excellent. IQ was decreased by decay, incisions during autopsy, and separation of the hyoid from the cartilaginous components in 7, 3, and 12 specimens, respectively. PMFP detected 119 fractures in 34 LHCs (63.0%). PMCT identified 91 fractures in 32 specimens (59.3%). PMFP and PMCT significantly agreed concerning the location (Cohen’s κ = 0.762; p < 0.001) and the degree of dislocation (κ = 0.689; p < 0.001) of the fractures. Comparing PMCT to PMFP resulted in a sensitivity of 88.2%, a specificity of 90.0%, and an ACC of 88.9% for the LHC. The ACCs for the hyoid, thyroid, and cricoid were 94.4%, 87.0%, and 81.5%, respectively. PMCT procedure was significantly faster than PMFP (28.9 ± 4.1 min vs. 208.2 ± 32.5 min; p < 0,001).ConclusionsPMCT can detect distinct injuries of the isolated LHC and may promptly confirm violence against the neck as cause of death. PMFP outmatches PMCT in the detection of decent injuries like tears of the cricoid cartilage.Key Points• Post-mortem computed tomography is able to assess fractures of the larynx-hyoid complex.• Prospective monocentric in vitro study showed that post-mortem computed tomography of the larynx-hyoid complex is faster than post-mortem fine preparation.• Post-mortem computed tomography can confirm violence against the neck as cause of death.

Coronary computed tomography angiography (CTA) is the preferred primary diagnostic modality when examining patients with low to intermediate pre-test probability of coronary artery disease (CAD). Only 20-30% of these have potentially obstructive CAD. Because of the relatively poor positive predictive value of coronary CTA, unnecessary invasive coronary angiographies (ICAs) are conducted with the costs and risks associated with the procedure. Hence, an optimized diagnostic CAD algorithm may reduce the numbers of ICAs not followed by revascularization. The Dan-NICAD 2 study has 3 equivalent main aims: (1) To examine the diagnostic precision of a sound-based diagnostic algorithm, The CADScor®System (Acarix A/S, Denmark), in patients with a low to intermediate pre-test risk of CAD referred to a primary examination by coronary CTA. We hypothesize that the CADScor®System provides better stratification prior to coronary CTA than clinical risk stratification scores alone. (2) To compare the diagnostic accuracy of 3T cardiac magnetic resonance imaging (3T CMRI), 82rubidium positron emission tomography (82Rb-PET), and CT-derived fractional flow reserve (FFRCT) in patients where obstructive CAD cannot be ruled out by coronary CTA using ICA fractional flow reserve (FFR) as reference standard. (3) To compare the diagnostic performance of quantitative flow ratio (QFR) and ICA-FFR in patients with low to intermediate pre-test probability of CAD using 82Rb-PET as reference standard. Dan-NICAD 2 is a prospective, multicenter, cross-sectional study including approximately 2,000 patients with low to intermediate pre-test probability of CAD and without previous history of CAD. Patients are referred to coronary CTA because of symptoms suggestive of CAD, as evaluated by a cardiologist. Patient interviews, sound recordings, and blood samples are obtained in connection with the coronary CTA. If coronary CTA does not rule out obstructive CAD, patients will be examined by 3T CMRI 82Rb-PET, FFRCT, ICA, and FFR. Reference standard is ICA-FFR. Obstructive CAD is defined as an FFR ≤0.80 or as high-grade stenosis (>90% diameter stenosis) by visual assessment. Diagnostic performance will be evaluated as sensitivity, specificity, predictive values, likelihood ratios, calibration, and discrimination. Enrolment started January 2018 and is expected to be completed by June 2020. Patients are followed for 10 years after inclusion. The results of the Dan-NICAD 2 study are expected to contribute to the improvement of diagnostic strategies for patients suspected of CAD in 3 different steps: risk stratification prior to coronary CTA, diagnostic strategy after coronary CTA, and invasive wireless QFR analysis as an alternative to ICA-FFR.

ObjectiveThere is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm.MethodsForty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set.ResultsUsing multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis.ConclusionsMulti-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours.Key Points• We present and validate a paradigm for texture analysis of DECT scans.• Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis.• DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours.• DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

Objectives To compare and evaluate the usefulness of magnetic resonance imaging (MRI) with computed tomography (CT) in bronchiectasis; to compare MRI and CT scores with pulmonary function tests (PFT) and to evaluate the role of Diffusion-weighted imaging (DWI) in bronchiectasis. Methods In this prospective study, 25 patients between 7–21 y of age with a clinical/radiological diagnosis of bronchiectasis underwent MDCT and MRI chest. MRI and CT scoring was performed using modified Bhalla-Helbich’s score by two independent radiologists for all parameters. A final consensus score was recorded. The overall image quality of different MRI sequences to identify pathologies was also assessed. Appropriate statistical tests were used for inter-observer agreements, and correlation amongst CT and MRI; as well as CT, MRI and PFT. Results Strong agreement (ICC 0.80–0.95) between CT and MRI was seen for extent and severity of bronchiectasis, number of bullae, sacculation/abscess, emphysema, collapse/ consolidation, mucus plugging, and mosaic perfusion. Overall CT and MRI scores had perfect concordance (ICC 0.978). Statistically significant ( p -value <0.01) intra-observer and inter-observer agreement for all CT and MRI score parameters were seen. A strong negative correlation was seen between total CT and MRI severity scores and forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), forced expiratory flow (FEF) 25–75%. DWI MR, with an apparent diffusion coefficient (ADC) cut-off of 1.62 × 10 –3 mm 3 /s had a sensitivity of 70% and specificity of 75% in detecting true mucus plugs. Conclusions MRI with DWI can be considered as a radiation-free alternative in the diagnostic algorithm for assessment of lung changes in bronchiectasis, especially in follow-up.

Objectives This study introduces a method to calculate myocardium blood flow (MBF) and coronary flow reserve (CFR) using the relatively low-dose dynamic 320-row multi-detector computed tomography (MDCT), validates the method against 15 O-H 2 O positron-emission tomography (PET) and assesses the CFRs of coronary artery disease (CAD) patients. Methods Thirty-two subjects underwent both dynamic CT perfusion (CTP) and PET perfusion imaging at rest and during pharmacological stress. In 12 normal subjects (pilot group), the calculation method for MBF and CFR was established. In the other 13 normal subjects (validation group), MBF and CFR obtained by dynamic CTP and PET were compared. Finally, the CFRs obtained by dynamic CTP and PET were compared between the validation group and CAD patients ( n  = 7). Results Correlation between MBF of MDCT and PET was strong ( r  = 0.95, P  < 0.0001). CFR showed good correlation between dynamic CTP and PET ( r  = 0.67, P  = 0.0126). CFR CT in the CAD group (2.3 ± 0.8) was significantly lower than that in the validation group (5.2 ± 1.8) ( P  = 0.0011). Conclusions We established a method for measuring MBF and CFR with the relatively low-dose dynamic MDCT. Lower CFR was well demonstrated in CAD patients by dynamic CTP. Key Points • MBF and CFR can be calculated using dynamic CTP with 320-row MDCT. • MBF and CFR showed good correlation between dynamic CTP and PET. • Lower CFR was well demonstrated in CAD patients by dynamic CTP.

Background Different imaging techniques, such as multi-detector computed tomography (MDCT) scan and cone beam computed tomography(CBCT), are used to check the structure of the nose before rhinoplasty. This study aimed to evaluate the accuracy of two imaging techniques, MDCT scan, and CBCT, in diagnosing structural Variations in rhinoplasty for the first time. Methods This diagnostic accuracy study was conducted on 64 rhinoplasty candidates who complained of snoring and sleep apnea or had a positive result in the examination with Cottle’s maneuver or modified Cottle technique between February 2021 and October 2022 at 15- Khordad Hospital affiliated to Beheshti University of Medical Sciences. Before rhinoplasty, patients were randomly assigned to one of the CT and CBCT techniques with an equal ratio. Scans were assessed for the presence of Nasal septum deviation (NSD), Mucocele, Concha bullosa, and nasal septal spur by two independent radiologists. The findings of the two methods were evaluated with the results during rhinoplasty as the gold standard. Results NSD was the most common anatomical variation based on both imaging techniques. The accuracy of CBCT for diagnosing Nasal Septum Deviation and Mucocele was 80% and 75%, respectively. The sensitivity, specificity, and accuracy of CBCT in detecting Concha bullosa were 81.3% and 83.3%, respectively. The Kappa coefficient between CBCT and intraoperative findings for diagnosing NSD and Concha Bullosa was 0.76 and 0.73, respectively (p < 0.05). Conclusion CBCT can be considered a suitable method with high accuracy and quality to evaluate the anatomical variations before rhinoplasty.

Objectives Shaping the energy spectrum of the X-ray beam has been shown to be beneficial in low-dose CT. This study’s aim was to investigate dose and image quality of tin filtration at 100 kV for pre-operative planning in low-dose paranasal CT imaging in a large patient cohort. Methods In a prospective trial, 129 patients were included. 64 patients were randomly assigned to the study protocol (100 kV with additional tin filtration, 150mAs, 192x0.6-mm slice collimation) and 65 patients to the standard low-dose protocol (100 kV, 50mAs, 128 × 0.6-mm slice collimation). To assess the image quality, subjective parameters were evaluated using a five-point scale. This scale was applied on overall image quality and contour delineation of critical anatomical structures. Results All scans were of diagnostic image quality. Bony structures were of good diagnostic image quality in both groups, soft tissues were of sufficient diagnostic image quality in the study group because of a high level of noise. Radiation exposure was very low in both groups, but significantly lower in the study group (CTDI vol 1.2 mGy vs. 4.4 mGy, p  < 0.001). Conclusions Spectral optimization (tin filtration at 100 kV) allows for visualization of the paranasal sinus with sufficient image quality at a very low radiation exposure. Key Points • Spectral optimization (tin filtration) is beneficial to low-dose parasinus CT • Tin filtration at 100 kV yields sufficient image quality for pre-operative planning • Diagnostic parasinus CT can be performed with an effective dose <0.05 mSv