Three-Tesla Magnetic Resonance Imaging Characteristics of Hypertrophic Cardiomyopathy: A Comparison with Several Echocardiography Parameters.

Background: Hypertrophic cardiomyopathy (HCM) is a primary cardiac disorder characterized by myocardial hypertrophy without increased afterload. This study set out to describe the cardiac magnetic resonance (CMR) imaging characteristics of HCM and to evaluate correlations of selected CMR parameters with echocardiography. Methods: This cross-sectional study enrolled 46 patients diagnosed at the Vietnam Heart Institute with HCM and underwent CMR at the Radiology Center, Bach Mai Hospital, from July 2021 to September 2022. Results: A left ventricular outflow tract (LVOT)/aortic valve (AO) diameter ratio of ≥0.38 on CMR was consistent with an LVOT pressure gradient (PG) of <30 mmHg on echocardiography. The LVOT diameter and the LVOT/AO diameter ratio differed significantly between obstructive and non-obstructive HCM. The predominant phenotypes were diffuse asymmetric HCM (32.6%) and septal HCM (37%), followed by apical HCM (6.5%). Most late gadolinium enhancement (LGE) lesions were observed in the mid-wall of the hypertrophic segments. The mean LGE mass was significantly higher in the obstructive group than in the non-obstructive HCM group (p < 0.05). A strong negative correlation (r = -0.66) was found between the LVOT/AO diameter ratio on the CMR and the LVOT PG via echocardiography. Moreover, echocardiography detected morphologic risk factors for sudden cardiac death (SCD) in 80.4% of patients, whereas the corresponding proportion detected by CMR was 91.3%. Patients with systolic anterior motion (SAM) had a risk for a LVOT/AO diameter ratio <0.38, which was 5.7 times the risk observed in their counterparts without SAM. Conclusions: The LVOT/AO diameter ratio detected by CMR is a precise index for classifying hemodynamic HCM groups. CMR was better than echocardiography for SCD risk stratification.

The effectiveness of coronary computed tomography angiography and functional testing for the diagnosis of obstructive coronary artery disease: results from the individual patient data Collaborative Meta-Analysis of Cardiac CT (COME-CCT).

AIM: To determine the effectiveness of functional stress testing and computed tomography angiography (CTA) for diagnosis of obstructive coronary artery disease (CAD). METHODS AND RESULTS: Two-thousand nine-hundred twenty symptomatic stable chest pain patients were included in the international Collaborative Meta-Analysis of Cardiac CT consortium to compare CTA with exercise electrocardiography (exercise-ECG) and single-photon emission computed tomography (SPECT) for diagnosis of CAD defined as ≥ 50% diameter stenosis by invasive coronary angiography (ICA) as reference standard. Generalised linear mixed models were used for calculating the diagnostic accuracy of each diagnostic test including non-diagnostic results as dependent variables in a logistic regression model with random intercepts and slopes. Covariates were the reference standard ICA, the type of diagnostic method, and their interactions. CTA showed significantly better diagnostic performance (p < 0.0001) with a sensitivity of 94.6% (95% CI 92.7-96) and a specificity of 76.3% (72.2-80) compared to exercise-ECG with 54.9% (47.9-61.7) and 60.9% (53.4-66.3), SPECT with 72.9% (65-79.6) and 44.9% (36.8-53.4), respectively. The positive predictive value of CTA was ≥ 50% in patients with a clinical pretest probability of 10% or more while this was the case for ECG and SPECT at pretest probabilities of ≥ 40 and 28%. CTA reliably excluded obstructive CAD with a post-test probability of below 15% in patients with a pretest probability of up to 74%. CONCLUSION: In patients with stable chest pain, CTA is more effective than functional testing for the diagnosis as well as for reliable exclusion of obstructive CAD. CTA should become widely adopted in patients with intermediate pretest probability. SYSTEMATIC REVIEW REGISTRATION: PROSPERO Database for Systematic Reviews-CRD42012002780. CRITICAL RELEVANCE STATEMENT: In symptomatic stable chest pain patients, coronary CTA is more effective than functional testing for diagnosis and reliable exclusion of obstructive CAD in intermediate pretest probability of CAD. KEY POINTS: Coronary computed tomography angiography showed significantly better diagnostic performance (p < 0.0001) for diagnosis of coronary artery disease compared to exercise-ECG and SPECT. The positive predictive value of coronary computed tomography angiography was ≥ 50% in patients with a clinical pretest probability of at least 10%, for ECG ≥ 40%, and for SPECT 28%. Coronary computed tomography angiography reliably excluded obstructive coronary artery disease with a post-test probability of below 15% in patients with a pretest probability of up to 74%.

Incidental Findings in Lung Cancer Screening.

While low-dose computed tomography (LDCT) for lung cancer screening (LCS) has been recognized for its effectiveness in reducing lung cancer mortality, it often simultaneously leads to the detection of incidental findings (IFs) unrelated to the primary screening indication. These IFs present diagnostic and management challenges, potentially causing unnecessary anxiety and further invasive diagnostic procedures for patients. This review article provides an overview of IFs encountered in LDCT, emphasizing their clinical significance and recommended management strategies. We categorize IFs based on their anatomical locations (intrathoracic-intrapulmonary, intrathoracic-extrapulmonary, and extrathoracic) and discuss the most common findings. We highlight the importance of utilizing guidelines and standardized reporting systems by the American College of Radiology (ACR) to guide appropriate follow-ups. For each category, we present specific IF examples, their radiologic features, and the suggested management approach. This review aims to provide radiologists and clinicians with a comprehensive understanding of IFs in LCS for accurate assessment and management, ultimately enhancing patient care. Finally, we outline a few key aspects for future research and development in managing IFs.

Identification of CD5/SOX11 double-negative pleomorphic mantle cell lymphoma.

Cyclin D1 protein-positive diffuse large B cell lymphoma (DLBCL) has an immunophenotype of CD5(-) cyclin D1(+) SOX11(-), and most cases lack a CCND1 rearrangement and have a gene expression profile of DLBCL. Rarely, cyclin D1 protein-positive DLBCL harbors a CCND1 rearrangement, and some genetic copy number features typical of mantle cell lymphoma (MCL) have been detected. Since gene expression studies have not been performed, whether such CCND1-rearranged cases represent cyclin D1 protein-positive DLBCL or CD5/SOX11 double-negative pleomorphic MCL remains unclear. To date, no cases of CD5/SOX11 double-negative MCL have been reported. In this study, we collected eight cases initially diagnosed as cyclin D1 protein-positive DLBCL, including four with a CCND1 rearrangement and four without. Immunohistochemically, all four CCND1-rearranged cases had >50% of tumor cells positive for cyclin D1 protein, whereas only one (25%) non-rearranged case had >50% positive tumor cells. Analysis of genome-wide copy number, mutational, and gene expression profiles revealed that CCND1-rearranged cases were similar to MCL, whereas CCND1-non-rearranged cases resembled DLBCL. Despite the SOX11 negativity by immunohistochemistry, CCND1-rearranged cases had a notable trend (P = 0.064) of higher SOX11 mRNA levels compared to non-rearranged cases. Here, we show for the first time that CCND1 rearrangement could be useful for identifying CD5/SOX11 double-negative pleomorphic MCL in cases diagnosed as cyclin D1 protein-positive DLBCL. Cases with >50% cyclin D1 protein-positive tumor cells immunohistochemically and higher SOX11 mRNA levels are more likely to have a CCND1 rearrangement, and fluorescence in situ hybridization can be used to detect the rearrangement.

Ultrasonography of acute retroperitoneum.

The retroperitoneum is an important space in the human body that is often implicated in a range Epub ahead of print of acute medical conditions, some of which can be life-threatening. Ultrasonography may serve as a pivotal first-line imaging technique when assessing patients with suspected retroperitoneal abnormalities. Effective ultrasonography of the retroperitoneum requires a comprehensive grasp of its anatomy, adjacent structures, and potential pathologies. Being well-acquainted with the imaging characteristics of acute conditions can meaningfully assist in an accurate diagnosis and guide subsequent management. This review article summarizes and illustrates the acute conditions involving the retroperitoneum through the lens of ultrasound imaging.

Hyperpolarized Carbon-13 Magnetic Resonance Imaging: Technical Considerations and Clinical Applications.

Hyperpolarized (HP) carbon-13 (13C) MRI represents an innovative approach for noninvasive, real-time assessment of dynamic metabolic flux, with potential integration into routine clinical MRI. The use of [1-13C]pyruvate as a probe and its conversion to [1-13C]lactate constitute an extensively explored metabolic pathway. This review comprehensively outlines the establishment of HP 13C-MRI, covering multidisciplinary team collaboration, hardware prerequisites, probe preparation, hyperpolarization techniques, imaging acquisition, and data analysis. This article discusses the clinical applications of HP 13C-MRI across various anatomical domains, including the brain, heart, skeletal muscle, breast, liver, kidney, pancreas, and prostate. Each section highlights the specific applications and findings pertinent to these regions, emphasizing the potential versatility of HP 13C-MRI in diverse clinical contexts. This review serves as a comprehensive update, bridging technical aspects with clinical applications and offering insights into the ongoing advancements in HP 13C-MRI.

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.

The Role of Artificial Intelligence in Coronary Calcium Scoring in Standard Cardiac Computed Tomography and Chest Computed Tomography With Different Reconstruction Kernels.

PURPOSE: To assess the correlation of coronary calcium score (CS) obtained by artificial intelligence (AI) with those obtained by electrocardiography gated standard cardiac computed tomography (CCT) and nongated chest computed tomography (ChCT) with different reconstruction kernels. PATIENTS AND METHODS: Seventy-six patients received standard CCT and ChCT simultaneously. We compared CS obtained in 4 groups: CS CCT , by the traditional method from standard CCT, 25 cm field of view, 3 mm slice thickness, and kernel filter convolution 12 (FC12); CS AICCT , by AI from the standard CCT; CS ChCTsoft , by AI from the non-gated CCT, 40 cm field of view, 3 mm slice thickness, and a soft kernel FC02; and CS ChCTsharp , by AI from CCT image with same parameters for CS ChCTsoft except for using a sharp kernel FC56. Statistical analyses included Spearman rank correlation coefficient (ρ), intraclass correlation (ICC), Bland-Altman plots, and weighted kappa analysis (κ). RESULTS: The CS AICCT was consistent with CS CCT (ρ = 0.994 and ICC of 1.00, P < 0.001) with excellent agreement with respect to cardiovascular (CV) risk categories of the Agatston score (κ = 1.000). The correlation between CS ChCTsoft and CS ChCTsharp was good (ρ = 0.912, 0.963 and ICC = 0.929, 0.948, respectively, P < 0.001) with a tendency of underestimation (Bland-Altman mean difference and 95% upper and lower limits of agreements were 329.1 [-798.9 to 1457] and 335.3 [-651.9 to 1322], respectively). The CV risk category agreement between CS ChCTsoft and CS ChCTsharp was moderate (κ = 0.556 and 0.537, respectively). CONCLUSIONS: There was an excellent correlation between CS CCT and CS AICCT , with excellent agreement between CV risk categories. There was also a good correlation between CS CCT and CS obtained by ChCT albeit with a tendency for underestimation and moderate accuracy in terms of CV risk assessment.

Low-dose CT screening among never-smokers with or without a family history of lung cancer in Taiwan: a prospective cohort study.

BACKGROUND: In Taiwan, lung cancers occur predominantly in never-smokers, of whom nearly 60% have stage IV disease at diagnosis. We aimed to assess the efficacy of low-dose CT (LDCT) screening among never-smokers, who had other risk factors for lung cancer. METHODS: The Taiwan Lung Cancer Screening in Never-Smoker Trial (TALENT) was a nationwide, multicentre, prospective cohort study done at 17 tertiary medical centres in Taiwan. Eligible individuals had negative chest radiography, were aged 55-75 years, had never smoked or had smoked fewer than 10 pack-years and stopped smoking for more than 15 years (self-report), and had one of the following risk factors: a family history of lung cancer; passive smoke exposure; a history of pulmonary tuberculosis or chronic obstructive pulmonary disorders; a cooking index of 110 or higher; or cooking without using ventilation. Eligible participants underwent LDCT at baseline, then annually for 2 years, and then every 2 years up to 6 years thereafter, with follow-up assessments at each LDCT scan (ie, total follow-up of 8 years). A positive scan was defined as a solid or part-solid nodule larger than 6 mm in mean diameter or a pure ground-glass nodule larger than 5 mm in mean diameter. Lung cancer was diagnosed through invasive procedures, such as image-guided aspiration or biopsy or surgery. Here, we report the results of 1-year follow-up after LDCT screening at baseline. The primary outcome was lung cancer detection rate. The p value for detection rates was estimated by the χ2 test. Univariate and multivariable logistic regression analyses were used to assess the association between lung cancer incidence and each risk factor. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of LDCT screening were also assessed. This study is registered with ClinicalTrials.gov, NCT02611570, and is ongoing. FINDINGS: Between Dec 1, 2015, and July 31, 2019, 12 011 participants (8868 females) were enrolled, of whom 6009 had a family history of lung cancer. Among 12 011 LDCT scans done at baseline, 2094 (17·4%) were positive. Lung cancer was diagnosed in 318 (2·6%) of 12 011 participants (257 [2·1%] participants had invasive lung cancer and 61 [0·5%] had adenocarcinomas in situ). 317 of 318 participants had adenocarcinoma and 246 (77·4%) of 318 had stage I disease. The prevalence of invasive lung cancer was higher among participants with a family history of lung cancer (161 [2·7%] of 6009 participants) than in those without (96 [1·6%] of 6002 participants). In participants with a family history of lung cancer, the detection rate of invasive lung cancer increased significantly with age, whereas the detection rate of adenocarcinoma in situ remained stable. In multivariable analysis, female sex, a family history of lung cancer, and age older than 60 years were associated with an increased risk of lung cancer and invasive lung cancer; passive smoke exposure, cumulative exposure to cooking, cooking without ventilation, and a previous history of chronic lung diseases were not associated with lung cancer, even after stratification by family history of lung cancer. In participants with a family history of lung cancer, the higher the number of first-degree relatives affected, the higher the risk of lung cancer; participants whose mother or sibling had lung cancer were also at an increased risk. A positive LDCT scan had 92·1% sensitivity, 84·6% specificity, a PPV of 14·0%, and a NPV of 99·7% for lung cancer diagnosis. INTERPRETATION: TALENT had a high invasive lung cancer detection rate at 1 year after baseline LDCT scan. Overdiagnosis could have occurred, especially in participants diagnosed with adenocarcinoma in situ. In individuals who do not smoke, our findings suggest that a family history of lung cancer among first-degree relatives significantly increases the risk of lung cancer as well as the rate of invasive lung cancer with increasing age. Further research on risk factors for lung cancer in this population is needed, particularly for those without a family history of lung cancer. FUNDING: Ministry of Health and Welfare of Taiwan.

Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography.

PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely to benefit. We hypothesized that a deep learning model assessing the entire volumetric LDCT data could be built to predict individual risk without requiring additional demographic or clinical data. METHODS: We developed a model called Sybil using LDCTs from the National Lung Screening Trial (NLST). Sybil requires only one LDCT and does not require clinical data or radiologist annotations; it can run in real time in the background on a radiology reading station. Sybil was validated on three independent data sets: a heldout set of 6,282 LDCTs from NLST participants, 8,821 LDCTs from Massachusetts General Hospital (MGH), and 12,280 LDCTs from Chang Gung Memorial Hospital (CGMH, which included people with a range of smoking history including nonsmokers). RESULTS: Sybil achieved area under the receiver-operator curves for lung cancer prediction at 1 year of 0.92 (95% CI, 0.88 to 0.95) on NLST, 0.86 (95% CI, 0.82 to 0.90) on MGH, and 0.94 (95% CI, 0.91 to 1.00) on CGMH external validation sets. Concordance indices over 6 years were 0.75 (95% CI, 0.72 to 0.78), 0.81 (95% CI, 0.77 to 0.85), and 0.80 (95% CI, 0.75 to 0.86) for NLST, MGH, and CGMH, respectively. CONCLUSION: Sybil can accurately predict an individual's future lung cancer risk from a single LDCT scan to further enable personalized screening. Future study is required to understand Sybil's clinical applications. Our model and annotations are publicly available.[Media: see text].

Quantitative ultrasound envelope statistics imaging as a screening approach for pediatric hepatic steatosis and liver fibrosis: using biomarker and transient elastography as reference standards.

Quantitative ultrasound (QUS) envelope statistics imaging is an emerging technique for the assessment of hepatic steatosis in adults. Blood tests are currently recommended as the screening tool for pediatric hepatic steatosis, a condition that can lead to liver fibrosis in children. This study examined the utility of QUS envelope statistics imaging in grading biomarker-diagnosed hepatic steatosis and detecting liver fibrosis in a pediatric population. A total of 173 subjects was enrolled (Group A) for QUS envelope statistics imaging using two statistical distributions, Nakagami and homodyned K (HK) models, and information entropy. QUS parameter values were compared with the hepatic steatosis index (HSI) and steatosis grade (G0: HSI <30; G1: 30 ≤ HSI <36; G2: 36 ≤ HSI <41.6; G3: ≥41.6). An additional cohort of 63 subjects (Group B) was recruited to undergo both QUS envelope statistics imaging and liver stiffness measurements (LSM) obtained from the transient elastography (Fibroscan), with a cutoff value set at 5 kPa to indicate liver fibrosis. The diagnostic performances were evaluated using the area under the receiver operating characteristic curve (AUROC). QUS envelope statistics imaging generated the AUROC values for steatosis grading at levels ≥ G1, ≥ G2, and ≥ G3 ranged from 0.94 to 0.97, 0.91 to 0.93, and 0.83 to 0.87, respectively, and produced an AUROC range of between 0.82 and 0.84 for identifying liver fibrosis. QUS envelope statistics imaging integrates the benefits of both biomarkers and elastography, enabling the screening of hepatic steatosis and detection of liver fibrosis in a pediatric population.

Management of Patients with Adhesive Capsulitis via Ultrasound-Guided Hydrodilatation without Concomitant Intra-Articular Lidocaine Infusion: A Single-Center Experience.

Considering the potential chondrotoxic effects of lidocaine, this retrospective study aimed to examine whether ultrasound-guided hydrodilatation without concurrent lidocaine infusion can still provide comparable treatment benefits for patients with adhesive capsulitis (AC). Outpatient data from 104 eligible AC patients who received ultrasound-guided hydrodilatation between May 2016 and April 2021 were reviewed. A total of 59 patients received hydrodilatation with diluted corticosteroid only, while 45 patients received treatment with mixed, diluted corticosteroid and 1% lidocaine. The overall treatment outcome was documented as the percentage of clinical improvement, ranging from 0% to 100% compared to baseline, and it was ranked into poor, moderate and good treatment outcomes. The results show no significant group-wise difference in demographics, overall treatment outcome, and number of hydrodilatations, while most patients showed moderate and good treatment outcomes. Patients with lidocaine infusion did not show greater treatment benefit. Our results suggest that ultrasound-guided hydrodilatation without concurrent lidocaine infusion can still deliver good treatment benefits for AC patients, and the findings are supportive of a modified approach toward careful intra-articular local anesthetic use during management of AC in the primary care setting.

Evaluation of Hemodynamic Changes in Retrobulbar Blood Vessels Using Color Doppler Imaging in Diabetic Patients.

Background­Diabetic retinopathy is a common complication of long-standing hyperglycemia. Microangiopathy-induced retinal changes are well-visualized on ophthalmoscopic examination. However, certain hemodynamic alterations have also been documented in the diabetic population, which have not been completely understood. Aim­To study the hemodynamic changes in retrobulbar circulation in diabetic patients with and without retinopathy, and to compare these changes with non-diabetic controls. Materials and Methods­This hospital-based prospective study included 50 diabetic and 50 non-diabetic patients. The diabetic groups consisted of 25 patients without retinopathy and 25 patients with retinopathy, and were labeled as Groups I and II, respectively. All subjects underwent orbital color Doppler ultrasonography using a linear high-frequency probe. The color Doppler parameters (peak systolic velocity (PSV), end-diastolic velocity (EDV), and resistive index (RI)) were measured and recorded using the spectral waveform of the ophthalmic artery (OA), central retinal artery (CRA), and short posterior ciliary arteries (SPCA). Comparison of obtained values was carried out using appropriate tests of significance. Results­The resistive indices of the ophthalmic, central retinal, and short posterior ciliary arteries were significantly higher in diabetic patients compared to controls (p < 0.001). The difference was also significant between Group I and Group II. Comparison of PSV and EDV of CRA and SPCAs among three groups using one-way ANOVA revealed a significant difference, with the highest blood flow velocities in the control group and the lowest in diabetics with retinopathy. The ophthalmic artery showed no significant change in blood flow velocity. Analysis using the Pearson correlation coefficient provided a positive correlation between the RI values of OA, CRA, and SPCA and the presence of diabetic retinopathy (OA = r 0.417, p < 0.001; CRA = r 0.466, p < 0.001; SPCA = r 0.438; p < 0.001). Conclusions­The resistive index of OA, CRA, and SPCA is a reliable indicator to assess diabetic-associated hemodynamic changes. The use of orbital color Doppler ultrasonography in diabetic patients can help in the identification of patients who are at risk of developing retinopathy.

Transmastoid Ultrasound Detection of Middle Ear Effusion and Its Association with Clinical Audiometric Tests.

Medical history taking, otoscopy, tympanometry, and audiometry are clinical methods to diagnose middle ear effusion (MEE); however, these procedures are experience-dependent and result in misdiagnosis under unfavorable conditions of the external auditory canal in non-cooperative young children. This study aimed to explore the use of transmastoid ultrasound combined with the Nakagami parameter analysis to detect MEE in children aged 3−5 years and to compare the proposed method with clinical evaluation methods. A total of forty subjects were enrolled; for each subject, a single-element ultrasound transducer of 2.25 MHz was used to measure backscattered signals returned from the mastoid for estimating the Nakagami parameter, which is a measure of the echo amplitude distribution. Tympanogram and hearing loss were also measured for comparisons. The results showed that the Nakagami parameter in the patients with MEE was significantly larger than that of the normal group (p < 0.05). The area under the receiver operating characteristic curve (AUROC) for using the Nakagami parameter to detect MEE was 0.90, and the sensitivity, specificity, and accuracy were 82.5%, 97.5%, and 79.6%, respectively. The Nakagami parameter for tympanogram types B/C was higher than that for tympanogram type A (p < 0.05); it was also higher in the subjects with hearing loss (p < 0.05). Quantitative transmastoid ultrasound based on the Nakagami parameter analysis has the potential to detect MEE and evaluate hearing loss.

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.

Added Value of Computed Tomography Virtual Intravascular Endoscopy in the Evaluation of Coronary Arteries with Stents or Plaques.

Coronary computed tomography angiography (CCTA) is a widely used imaging modality for diagnosing coronary artery disease (CAD) but is limited by a high false positive rate when evaluating coronary arteries with stents and heavy calcifications. Virtual intravascular endoscopy (VIE) images generated from CCTA can be used to qualitatively assess the vascular lumen and might be helpful for overcoming this challenge. In this study, one hundred subjects with coronary stents underwent both CCTA and invasive coronary angiography (ICA). A total of 902 vessel segments were analyzed using CCTA and VIE. The vessel segments were first analyzed on CCTA alone. Then, using VIE, the segments were classified qualitatively as either negative or positive for in-stent restenosis (ISR) or CAD. These results were compared, using ICA as the reference, to determine the added diagnostic value of VIE. Of the 902 analyzed vessel segments, CCTA/VIE had sensitivity, specificity, accuracy, positive predictive value, and negative predictive value (shown in %) of 93.9/90.2, 96.2/98.2, 96.0/97.7, 70.0/83.1, and 99.4/99.0, respectively, in diagnosing ISR or CAD, with significantly improved specificity (p = 0.025), accuracy (p = 0.046), and positive predictive value (p = 0.047). VIE can be a helpful addition to CCTA when evaluating coronary arteries.

Update on Color Flow Imaging in Obstetrics.

Color flow imaging (CFI), being non-invasive, is commonly used in obstetrics to study the fetal and placental circulations. The conventional CFI modes include color Doppler flow imaging (CDFI) and power Doppler imaging (PDI). In recent years, there is increasing use of new modes, including high-definition flow imaging (HDFI), radiant flow, microvascular flow imaging (MVFI), and three-/four-dimensional rendering in glass-body mode. Compared to CDFI, HDFI can show a higher resolution and sensitivity and allow the detection of slower flows. MVFI increases the sensitivity to fine or low-flow vessels while producing little or no motion artifacts. Radiant flow shows the blood flow with a sense of depth and reduces blood overflow. Glass-body mode, showing both gray-scale and color-flow information, can demonstrate the heart-cycle-related flow events and the vessel spatial relationship. In this review, the characteristics and applications of the various CFI modes in obstetrics are discussed. In particular, how these new technologies are integrated in detailed diagnostic and early morphology scans is presented.

Optimizing risk-based breast cancer screening policies with reinforcement learning.

Screening programs must balance the benefit of early detection with the cost of overscreening. Here, we introduce a novel reinforcement learning-based framework for personalized screening, Tempo, and demonstrate its efficacy in the context of breast cancer. We trained our risk-based screening policies on a large screening mammography dataset from Massachusetts General Hospital (MGH; USA) and validated this dataset in held-out patients from MGH and external datasets from Emory University (Emory; USA), Karolinska Institute (Karolinska; Sweden) and Chang Gung Memorial Hospital (CGMH; Taiwan). Across all test sets, we find that the Tempo policy combined with an image-based artificial intelligence (AI) risk model is significantly more efficient than current regimens used in clinical practice in terms of simulated early detection per screen frequency. Moreover, we show that the same Tempo policy can be easily adapted to a wide range of possible screening preferences, allowing clinicians to select their desired trade-off between early detection and screening costs without training new policies. Finally, we demonstrate that Tempo policies based on AI-based risk models outperform Tempo policies based on less accurate clinical risk models. Altogether, our results show that pairing AI-based risk models with agile AI-designed screening policies has the potential to improve screening programs by advancing early detection while reducing overscreening.