bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incremental diagnostic value of a novel artificial intelligence-based ischemia algorithm to predict myocardial ischemia from CCTA
Authors: Bar S , Maaniitty T , Kiatkittikul P , Nabeta T , Bax J J , Earls J P , Min J K , Saraste A , Knuuti J 
Published: June 2024

Abstract

Background
Coronary computed tomography angiography (CCTA) is known to be limited in assessing the hemodynamic significance of a coronary artery stenosis. A novel artificial intelligence (AI)-based CCTA-derived algorithm (AI-QCTischemia) aims to identify ischemic coronary artery disease (CAD) directly from CCTA images. Its incremental diagnostic value on top of clinical risk factors, coronary calcium score (CACS), and obstructive diameter stenosis (DS) for the prediction of myocardial ischemia remains unknown.

Purpose
To assess the incremental value of AI-QCTischemia for the prediction of ischemic CAD using a reference standard of hybrid CCTA/positron emission tomography (PET) perfusion imaging.

Methods
This was a cohort of 1448 symptomatic patients with suspected CAD having undergone hybrid CCTA/PET perfusion imaging (15O-H2O) to assess the presence of ischemic CAD. Four logistic regression models for the prediction of ischemia according to hybrid CCTA/PET perfusion imaging were assessed: 1) clinical: age, sex, hypertension, diabetes mellitus, smoking, typical angina pectoris; 2) clinical+CACS; 3) clinical+CACS+DS (i.e. visual DS ≥50%); 4) clinical+CACS+DS+AI-QCTischemia. Model performance was evaluated using area under the receiver-operating characteristic curves (AUC), and Delong’s method to compare AUCs between the models.

Results
277/1448 (19.1%) patients had ischemic CAD according to hybrid CCTA/PET perfusion imaging. AUC (95% CI) for the clinical model was 0.75 (0.72-0.78), for the clinical+CACS model 0.86 (0.83-0.88), for the clinical+CACS+DS model 0.93 (0.91-0.95), and for the clinical+CACS+DS+AI-QCTischemia model 0.94 (0.92-0.95). Discriminatory ability improved significantly with each model from 1 to 4 with the model including AI-QCTischemia showing the overall highest performance (model 2 vs. model 1: p&lt;0.001; model 3 vs. model 2: p&lt;0.001; model 4 vs. model 3: p=0.011).

Conclusion
A novel AI-based CCTA-derived ischemia algorithm showed incremental diagnostic value on top of clinical risk factors, CACS, and obstructive stenosis on CCTA to predict to presence of ischemic CAD defined by the reference standard hybrid CCTA/PET perfusion imaging.AUCs for ischemic CAD
The potential of artificial intelligence in the assessment of coronary artery stenosis in follow-up CT examinations
Authors: Nagy K , Jatsch A K , Fortner P , Aurich M , Seitz S , Sommer A , Gorich J , Schobinger M , Andre F , Buss S 
Published: June 2024

Abstract

Background
Coronary CT angiography (CCTA) has become one of the main modalities for detecting coronary artery disease (CAD) and is now the first diagnostic choice in many patients. As a result, an increasing number of patients are being identified at an early stage of CAD, allowing effective early medical therapy to be initiated. In addition, CCTA offers the possibility of assessing disease progression and the effectiveness of therapy through follow-up examinations. However, the comparison of different CCTA studies is time-consuming and reader-dependent. The aim of this study was to evaluate the potential of artificial intelligence (AI) for assessing CAD progression in follow-up CCTA examinations.

Methods
41 (30 men, 11 women, age: 62.8±7.2 years) patients who were referred for follow-up examinations by their attending physicians were included in this study. Image acquisition was performed on a third–generation dual-source CT scanner using an institutional standard protocol. A series with good image quality was chosen from the CCTA study, transferred to the on-site AI prototype and processed fully automatically. A consensus reading by two experienced readers was used as a reference. Coronary arteries with a diameter &lt;2 mm were excluded from the analysis.

Results
The median baseline Coronary Artery Disease Reporting and Data System (CAD-RADS) category was 3 (2.0–3.0). The general agreement between AI and reference readers was good (ICC 0.88 (95% CI 0.82-0.92); n=82), with a maximum CAD-RADS difference of 1. After a follow-up period of 2.2±0.7 years, the CAD-RADS category was stable in 36 patients and increased in 5 patients. The agreement between the AI and reference readers regarding the assessment of disease progression was moderate (ICC 0.71 (95% CI 0.45-0.84)), with a maximum category difference of 1.

Conclusion
AI has great potential for assessing CAD progression in follow-up CCTA examinations. Further developments such as an improvement in artefact detection are required before it can be used in routine clinical practice. AI generated unfolded view
Potential of artificial intelligence to differentiate between non-obstructive and obstructive coronary artery disease on coronary CT angiography
Authors: Nagy K , Fortner P , Aurich M , Seitz S , Sommer A , Gorich J , Schobinger M , Andre F , Buss S 
Published: June 2024

Abstract

Background
Coronary computed tomography angiography (CCTA) plays an important role in the modern assessment of coronary artery disease (CAD). With the increasing number of CCTA examinations, technologies such as Artificial Intelligence (AI) that reduce reader workload and improve inter-reader agreement are of great interest. The Coronary Artery Disease Reporting and Data System (CAD-RADS) is a structured reporting system to categorise the severity of CAD and guide patient management. Patients with low CAD-RADS categories (1-2) usually need preventive medical therapies but no downstream testing. However, patients in more severe categories (CAD-RADS 3-5) may require further testing, such as stress tests or invasive coronary angiography. The aim of this study was to assess the potential of an on-site AI to differentiate between non-obstructive and potentially obstructive CAD.

Methods
In this study, 395 patients (65.3% male, 64.9 ± 10.0 years) who underwent a clinically indicated CCTA examination were retrospectively included. Cases with significant artefacts and coronary artery segments &lt;2 mm in diameter were not included into the analysis. The severity of CAD was graded as non-obstructive (CAD-RADS ≤2) or potentially obstructive (CAD-RADS ≥3) by consensus of two highly experienced readers. The final study population consisted of 50.6% non-obstructive and 49.4% obstructive CAD patients. The CCTA reconstruction with the best image quality was selected, transferred to the on-site AI prototype and fully automatically processed to yield the CAD-RADS category. Cohen's kappa and intraclass correlation were used to compare the results of the readers and the AI prototype.

Results
In the subgroup with non-obstructive CAD (n=200, 58.0% male), there was high agreement between the AI and the readers, with 96.0% of patients being correctly classified by the AI. Accordingly, 92.8% of patients with obstructive CAD (n=195, 72.8% male) were correctly classified by the AI. The results showed very good agreement between human and AI results in the overall population, with a kappa of 0.89 (95% CI 0.84-0.94) and an overall ICC of 0.89 (95% CI 0.84-0.93).

Conclusions
AI can reliably differentiate between non-obstructive and obstructive CAD in cases with good image quality. This could help readers to identify low-risk patients and expedite CCTA analysis. However, AI still has some limitations, such as the identification of artefacts in cases with impaired image quality or the detection of totally occluded coronary arteries. Further development is needed to improve its diagnostic accuracy.
Reproducibility for quantification of myocardial Tc-99m PYP amyloid uptake in grade 1 patients
Authors: Sandoval V M , Goyal D , Miller E J , Liu Y H 
Published: June 2024

Abstract

Background
Untreated Transthyretin (TTR) cardiac amyloidosis (CA) progresses to intractable heart failure and death to systolic heart failure or dysrhythmia. The recent introduction of therapy with tafamidis could hinder this disease progression. Presently, quantification of CA mainly relies on the heart to contralateral ratio (H/CL) of Tc-99m Pyrophosphate (PYP) uptake in the heart from radionuclide planar imaging. The H/CL assessment may be susceptible to false positive of CA caused by Tc-99m PYP uptake in the blood pool which is particularly pronounced in Grade 1 (equivocal cardiac uptake less than rib uptake) patients. Quantification of CA from SPECT imaging may be a preferred alternative. We have developed a method to quantify CA uptake of Heart to Mediastinum ratio (H/M) and standard uptake value (SUV) from Tc-99m PYP SPECT/CT imaging.

Purpose
This study aimed to evaluate the reproducibility of SPECT quantitative measures compared to conventional planar H/CL.

Methods
Twenty-three (N= 23) Grade 1 TTR Amyloid patients injected with Tc-99m PYP radiotracer (11.95 ± 3.03 mCi) and imaged one-hour post injection via planar followed by SPECT/CT with attenuation correction were randomly selected for this study. Planar images were quantified using a region growing method previously developed to calculate H/CL ratio, and SPECT images were quantified via a new approach to assessing H/M ratio and mean SUV of myocardial Tc-99m PYP uptake. Data were decay corrected and calibrated with a point source for SUV calculation. Quantitative analyses were performed by two different operators to assess intra- and inter-reproducibility of H/CL, H/M, and SUV assessments via linear regression analysis and coefficient of variation (COV).

Results
Planar H/CL, SPECT H/M and SPECT SUV quantified by same operator (Intra) were 1.17±0.17, 2.25±1.97, and 5.11+1.62, respectively; and those quantified by two different operators (Inter) were 1.19±0.16, 2.18±1.73 and 5.15+1.45, respectively. Reproducibility of the quantitative assessments are shown in Table 1 for intra and Table 2 for inter. The reproducibilities were excellent and COVs were small for H/CL and SUV quantification, while were relatively poor and large for H/M.

Conclusions
The mean SUV assessment of myocardial PYP uptake via Tc-99m SPECT imaging using the method we developed is extremely reproducible and may be a good alternative for planar H/CL measurement especially for Grade 1 PYP patients.
Interpretable deep generative model in myocardial perfusion SPECT images based on the creation of patient-matched normal maps
Authors: Okuda K , Nakajima K , Hara T , Yoneyama H , Kinuya S 
Published: June 2024

Abstract

Background
Although conventional quantitative method have used statistical normal databases for myocardial perfusion imaging, the potential role of generative deep learning has not been investigated.

Purpose
We sought to interpret training and generative processes of myocardial perfusion SPECT images in a variational autoencoder (VAE) (1) by comparing conventional quantitative analysis using normal maps.

Methods
A total of 3,432 polar map images without known coronary artery disease (CAD) were used as a training dataset, and 111 polar map images (43% obstructive CAD) were also used as a validation dataset. The VAE was trained to detect perfusion abnormalities using normal images, and consisted of an encoder, latent space, and a decoder (Fig.1). During the training process using the training dataset, the features of input normal images were characterized by the encoder in the latent space, where the probability of data points was represented as the Gaussian distribution. In the generative process, whatever perfusion distribution a patient had, the decoder sampled the patient’s matched perfusion distribution from the latent space, and generated a "normal" polar map image fitted for individual patients. Perfusion abnormality was detected by computing a cosine similarity (2) between the input and generated images.

Results
Distributions of normal myocardial perfusion for males and females were represented in the latent space (Fig.2a). Although male and female data points were overlapped, the distance between centroids of the points was 0.57. When normal polar maps were generated from the latent space, uniform myocardial perfusion was exhibited in the upper left corner, and decreased myocardial perfusion at the inferior was exhibited in the lower right corner (Fig. 2b). Uniform and decreased myocardial perfusion agreed with the characteristics of male and female myocardial perfusion, respectively. Trained VAE model was able to generate a normal polar map image from abnormal perfusion in the patient with CAD (Fig.2c). The areas under the receiver-operating characteristic curve for CAD detection were 0.89 ± 0.041 for cosine similarity and 0.81 ± 0.030 for summed stress score (p = 0.047).

Conclusions
The VAE automatically learned the characteristics of normal male and female myocardial perfusion distributions in the latent space, and estimated sex-specific normal perfusion distributions in generative polar map images. The VAE model has the potential to improve the detection of CAD in myocardial perfusion SPECT images.Fig 1.Structure of VAE model Fig 2.Training and generative processes
Analysis of mechanical ventricular synchrony of patients with systemic sclerosis
Authors: Aguirre E , Aguade-Bruix S , Guillen Del Castillo A , Palomar Munoz A , Cardozo-Saavedra A , Cuellar-Calabria H , Pizzi M N , Roque A , Simeon Aznar C P , Romero-Farina G 
Published: June 2024

Abstract

Background
The analysis of ventricular synchrony is important and complex in different cardiac diseases because it provides additional prognostic and diagnostic information. Insufficient information is available regarding the analysis of ventricular synchrony in patients diagnosed with systemic sclerosis (SSc) at a Nuclear Cardiology Unit.

Purpose
To assess the mechanical ventricular synchrony of patients with SSc.

Methods
Prospective cohort study of sixty-two patients (age 56.8 ± 12.9 years, men 12.9%) with SSc. All patients were studied with gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging (gSPECT-MPI) and Emory Cardiac ToolboxTM program during rest, exercise and cold test. The normal cut-off value for the dyssynchrony parameters (standard deviation [SD] &gt; 18.4º, bandwidth [BD] &gt; 51º, skewness [S] ≤ 3.2 and kurtosis [K] ≤ 9.3) were previously published and validated as well as its degrees. Statistical analyses were performed using ANOVA with Bonferroni correction and logistic regression analysis (STATA 18. StataCorp, College Station, TX, USA).

Results
The prevalence of ventricular mechanical dyssynchrony (VMD) (SD &gt; 18.4º and/or BD &gt; 51ª) at rest was high (n=40, 64.5%) and a normal ventricular mechanical synchronization was detected in 22 (35.5%) patients. Of the patients with VMD (n=40), 3 (3/40: 7.5%) had slight VMD (degree 1) and 37 (37/40: 92.5%) had moderate-severe (degrees 2-4) VMD.
There was no significant difference in BD (64.2 30, 62.3 36, 52.7 23) and SD (21.8 ± 12.6, 20.8 ± 9.6, 18.5 ± 7.6) between rest, exercise and cold test, respectively (ANOVA with Bonferroni correction). Only S (3.6 ± 0.8 vs 4 ± 0.9, p = 0.027) and K (14.8 ± 8 vs 18.7 ± 8.4, p = 0.033) were lower during exercise in comparison to rest, and the remainder combination without any significant difference.
Patients with VMD at rest had lower peak filling rate (PFR) (1.8 ± 0.5 vs 2.2 ± 0.46, p = 0.025) and a higher summed thickening score (STS) at rest (4.6 ± 10 vs 1.7 ± 6, p = 0.045) compared with patients with normal mechanical synchronization. We have defined probable VMD when a patient had diastolic dysfunction (PFR&lt;18) and/or abnormal ventricular motility (STS &gt;0). By mean of logistic regression analysis we have created a model adjusted by age, gender and previous cardiac event (CE) with a good prediction for VMD (AUC ROC: 0.76 (95% CI: 0.62 to 0.88), standard error: 0.065). (Results Table).

Conclusions
VMD has an elevated prevalence in patients with SSc. No significant differences are observed in BD and SD parameters between rest, exercise and cold tests. Furthermore, this study explains how we can calculate the pretest probability of VMD in patients with SSc.
How international atomic energy agency can support the management of ischemic heart disease in women
Authors: Peix A , Mesquita C T , Massardo T , Gutierrez-Villamil C , Berrocal I , Puente A , Astesiano A , Aguero R , Sanchez M , Gomez V V , Herrera Y , Mendoza A , Kapitan M , Estrada-Lobato E , Paez D 
Published: June 2024

Abstract

Background/Introduction
Cardiovascular diseases constitute the main cause of death in Latin America and the Caribbean (LAC), with ischemic heart disease (IHD) as the principal cause in most countries. This is particularly complex in women due to the peculiarities of the clinical picture and their specific risk factors. International Atomic Energy Agency (IAEA) supports regional projects with the aim of spreading the adequate use of medical imaging modalities and contributing to capacity building.

Purpose
To contribute to achieve an early diagnosis and an adequate risk stratification of IHD in Latin American women.

Methods
IAEA supported a regional project (2022-2023, 15 countries) in LAC. Regional courses were implemented and diagnostic units using imaging multimodality were established.

Results
Human resources capacities strengthened on the use of nuclear techniques, imaging multimodality, and their benefits in the management of IHD in LAC women. Three regional courses were implemented, with 144 professionals trained on. In addition, two courses (on multimodality and cardiac PET) will be presented in the IAEA Human Health Campus for free access, as well as 5 expert missions to help developing cardiac medical imaging.
Multimodality imaging techniques available in Cardiology (with emphasis on Nuclear Cardiology and hybrid imaging) applied in the management of IHD in LAC women. At the end of the project, two centres of diagnosis of IHD in women with the utilization of nuclear techniques in a multimodality imaging approach were established in each country. In addition, the regional network for dissemination of results, exchange of experiences, discussion of clinical cases, and virtual short courses on multimodality was implemented and is running.
Three publications on the epidemiological situation, technical and human resources available in LAC, and a consensus document adapted to the region on the utilization of multimodality in the management of IHD in women were completed.

Conclusion
The support of international organizations as IAEA contributes to the capacity building and a better management of cardiovascular disease in LAC.
Combination of CZT SPECT stress myocardial blood flow (MBF) and coronary artery calcium (CAC) scoring - opportunity for stress-first/stress-only protocol
Authors: Kaminek M , Havel M , Kincl V , Henzlova L , Dolezilek M , Hudson L 
Published: June 2024

Abstract

Introduction
Typical dynamic CZT SPECT protocol (rest – stress) enables absolute quantification of MBF and coronary flow reserve (CFR = stress MBF/rest MBF). However, its great disadvantage is a complexity. Stress-first protocol enabling stress-only MBF can significantly reduce time, cost and a radiation dose.

Purpose
To assess the prognostic significance of stress MBF, CFR, and CAC scoring.

Methods
Retrospective analysis of 73 patients (26 men, 66±9 years) examined with rest-stress dynamic myocardial SPECT and CAC scoring. The adverse cardiac event (CE) defined as sudden cardiac death, myocardial infarction, situations requiring coronary revascularization, and hospitalization for heart failure with reduced ejection fraction, were recorded.

Results
We observed 12 CE during a mean follow-up of 13±8 months. Patients with CE had higher CAC score (1035±1121 vs 205±445), comparable rest MBF (1.27±0.44 vs 1.23±0.47 ml/min/g) but significantly lower stress MBF (2.01±1.11 vs 2.83±0.98 ml/min/g) and a lower CFR (1.58±0.61 vs 2.47±0.88). A cut-off value for the prediction of CE were: CAC score 230,2 (sensitivity of 91 % and a specificity of 82 %), stress MBF 2.29 ml/min/g (sensitivity of 83 % and a specificity of 70 %), and CFR 1.94 (sensitivity of 75 % and a specificity of 77 %), respectively. There was no superiority of CFR over stress MBF in the identification of CE (P = NS). No CE occurred in patients with the combination of stress MBF ≥ 2.29 ml/min/g and CAC score &lt; 230.2.

Conclusion
We can predict CE by a combination of stress MBF and CAC scoring. A simplification of dynamic SPECT protocol (stress-first/stress-only) enables expansion of the MBF quantification for a larger number of patients.
Predictors of moderate to severe ischemia among patients referred to stress myocardial perfusion scintigraphy
Authors: Stalc M , Boncelj Svetek M , Guzic Salobir B 
Published: June 2024

Abstract

Introduction
Patients with moderate to severe ischemia on stress myocardial perfusion scintigraphy are at highest risk for cardiovascular adverse events and death. The presence, extent and severity of ischemia detected on myocardial perfusion scintigraphy have all decreased over the past few years. Therefore, there is an increasing need to identify patient cohorts where the results of myocardial perfusion scintigraphy will have the greatest impact on clinical management. The data on predictors of moderate to severe ischemia within contemporary population of patients are scarce.
Purpose of our study was to evaluate the predictors of moderate to severe ischemia across all potentially relevant clinical parameters in a cohort of patients referred to stress myocardial perfusion scintigraphy.

Methods
The clinical data and myocardial perfusion scintigraphy results of 4620 consecutive patients admitted to our department from January 2020 to December 2023 were prospectively collected. All patients underwent a 2-day stress/rest 99mTc tetrofosmin (Myoview, GE Healthcare) myocardial perfusion scintigraphy. Patients were imaged in the sitting position using a Cardius® X-ACT camera (Digirad, California, USA). The magnitude of myocardial ischemia was determined semi quantitatively in a 17-segment model according to the European Association of Nuclear Medicine guidelines. Patients were categorized in moderate to severe ischemia (&gt;10% ischemia) and &lt;10% of ischemia groups.

Results
The baseline clinical characteristics of the study population according to the degree of ischemia are shown in Table 1. Of the 4620 patients, 1695 (36.7%) had ischemia, 191 (4.1% of all patients, 11% of patients with ischemia) had moderate to severe ischemia. The proportion of male gender and the frequency of diabetes, dyslipidemia and prior coronary artery disease were higher in patients with moderate to severe ischemia (all p &lt;0.001, Table 1). Patients with moderate to severe ischemia had more often typical chest pain, were inpatients and had a higher frequency of myocardial scar (all p &lt;0.001, Table 1). In multivariable analysis male gender, diabetes, typical chest pain, known coronary artery disease and inpatient status turned out as predictors of moderate to severe ischemia (Table 2). Dyslipidemia and myocardial scar were not significant predictors (Table 2).

Conclusion
The prevalence of moderate to severe ischemia is particularly high among diabetic male patients with typical chest pain and known coronary artery disease. These observations may be used in clinical practice to identify patients who are most likely to benefit from referral to stress myocardial perfusion scintigraphy.