bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Image Reconstruction Algorithms in Pericoronary Adipose Tissue Attenuation obtained with Coronary CT Angiography
Authors: Krebs K K , Rossi A R , Jurisic S J , Gajic M G , Albertini T A , Heiniger P S H , Galafton A G , Pazhenkottil A P P , Kaufmann P A K , Buechel R R B , Benz D C B , Giannopoulos A
Published: June 2024

Background/Introduction

Pericoronary adipose tissue (PCAT) attenuation measured at coronary CT angiography (CCTA) can detect vascular inflammation and is a useful diagnostic and prognostic marker. Modern iterative and artificial-intelligence-based CCTA reconstruction methods can affect image noise and overall image quality. We aimed to investigate the potential influence of different CCTA image reconstruction algorithms on PCAT attenuation measurements.

Methods

Patients referred for clinically indicated CCTA between March 2015 and June 2016 were retrospectively included. Datasets were reconstructed with filtered back projection (FBP), with adaptive statistical iterative reconstruction-Veo (ASiR-V) and with deep-learning image reconstruction (DLIR). In all three reconstructions, mean PCAT was evaluated in the three major epicardial coronary arteries using dedicated software (QAngio CT Research Edition version 3.2.0.13, Medis Medical Imaging Systems) and was defined as the area with an attenuation between − 30 and − 190 Hounsfield Units (HU) within a radial distance from the outer vessel wall equivalent to the diameter of the vessel. The proximal 40 mm segments of the left anterior descending artery (LAD) and left circumflex artery (LCx) and the proximal 10–50 mm segment of the right coronary artery (RCA) were analyzed. Using FBP (PCATFBP) as reference standard, correlation and agreement of PCAT estimates using ASIR-V (PCATASIR-V) and DLIR (PCATDLIHR) reconstructions were assessed.

Results

In 39 patients (mean age 57.9±11.2 years, 90% men), 117 arteries were analyzed. Mean PCATFBP attenuation of the overall population was -79.9 ±9.4 HU and did not differ significantly compared to PCATASIR-V and to PCATDLIR (-80.9±8.9 HU and -78.5±9.5 HU, respectively; pANOVA=0.123). Correlation was excellent for all comparisons [PCATFBP vs. PCATASIR-V; r=0.99, (y=4.68+1.046x, p<0.001), PCATFBP vs. PCATDLIR; r=0.99 (y=-3.57+0.973x, p<0.001)]. Intraclass correlation coefficient was excellent for all reconstructions [PCATFBP vs. PCATASIR-V; 0.99 (95% confidence interval: 0.98-0.99), PCATFBP vs. PCATDLIR; 0.98 (95% confidence interval: 0.98-0.99), all p<0.0001]. Agreement with Bland-Altman analysis was high with small mean absolute differences and relatively narrow limits of agreement [PCATFBP vs. PCATASIR-V; Bias: 1.0 HU (95% limits of agreement: -1.4 – 3.3), PCATFBP vs. PCATDLIR; Bias: -1.5HU (95% limits of agreement: -4.4 – 1.4)].

Conclusions

CCTA-derived PCAT measurements using advanced iterative image reconstruction– and deep-learning image reconstruction–algorithms have excellent correlation and high agreement compared to conventional image reconstruction algorithms and could be potentially interchangeably used.
Ultra-low dose contrast CT-angiography in TAVI candidates with severe renal failure
Authors: Babbaro M , Perillo N , Bedogni F , Spagnolo P
Published: June 2024

Introduction

computer tomography angiography (CTA) has assumed an important role in patient screening before TAVI. The high volumes of iodinated contrast media (CM) injected during the examination represents the main limitation of CTA with a dose-dependent association with contrast-induced nephropathy.

Purpose

to show the feasibility of an ultra-low-dose CM pulmonary arterial injection protocol for CTA in TAVI candidates in high risk patients with severe renal failure.

Methods

retrospective study, 77 patients with CKD on stage 3b or worse (eGFR ≤ 45/min/1.73 m2) underwent pre-procedural CTA for TAVI-planning with a pulmonary arterial administration of CM. All CTA examinations were performed using a Dual Source 256-slice CT system. All enhanced CT acquisitions were performed using our dedicated biphasic injection protocol composed of two connected phases of contrast medium injection using different amount of CM (8, 10, 15 and 20 ml) according to BMI (<22 kg/m2; 22-24 kg/m2; 24-28 kg/m2; >28 kg/m2). The CM was administered directly into the pulmonary artery in all patients. For each examination was measured Intraluminal attenuation at thoraco-abdominal aorta and along the ilio-femoral vessels using the ROI (mean SD in HU) as objective image parameters (Picture 1). Serum creatinine and the eGFR were recorded pre-TAVI CT scan and after the procedures as reference of CM to renal function.

Results

CTA was successfully performed in all patients. Mean creatinine was 2.25 ± 0,76 mg/dL and mean GFR was 26.5± 8.1 mL/min/m2. Mean vessel attenuation was 352±164 HU at the aortic annulus, 238.1 ± 141,3 HU in the aortic arch and 266±168 in the iliac arteries (Picture 2).

The mean image noise was 28.2 ± 7 HU in the aortic annulus, 24.4 ± 10,9 in the right external iliac artery, and 25. ± 12,8 HU in the left external iliac artery. After CTA examination, a total of 74 patients (96%) underwent TAVI. Mean CM dose administered during TAVI procedure was 150,6 ± 85,8. Three patients (3.9%) were abolished for TAVI.

Postprocedural settings complications were recorded. A total of 31 patients (41%) had grade 1 paravalvular regurgitation, 10 patients (14%) grade 2. No cases of valve embolization or anulus rupture occured. No major vascular complications occured. No significant differences between creatine and eGFR pre and post procedures (p<0,001).

Conclusions

the use of an ultra-low-dose CM pulmonary arterial injection protocol for CTA in TAVI candidates does not affect the renal function and procedural success rate is high and the clinical outcomes after TAVI is satisfactory according to the litterature.Intraluminal attenuation in aorta
Correlation between aortic valve calcium score and peak to peak gradient in patients with preserved or reduced ejection fraction
Authors: Benetos G , Stergianos E , Ktenopoulos N , Drakopoulou M , Synetos A , Tsalamandris S , Aznaouridis K , Tsioufis C , Toutouzas K
Published: June 2024

Introduction

During the last decade, the use of aortic valve calcium (AVC) score as measured by multidetector computed tomography (MDCT) has gained ground as a reliable, supplemental method of detecting patients with severe aortic stenosis (AS). The correlation between AVC score and peak to peak gradient during left heart catheterization is not well studied.

Purpose

We aimed to study the relationship between AVC score and peak to peak gradient in patients with AS undergoing transcatheter aortic valve implantation (TAVI), classified in reduced and preserved ejection fraction (EF).

Methods

We retrospectively reviewed the medical records of 59 patients with tricuspid, degenerative, native valve severe AS that had TAVI in our hospital. All patients included had MDCT and Doppler echocardiography prior the operation while peak to peak gradient was measured during TAVI.

Results

Patients were classified according to their EF into Group A (N=46, preserved EF ≥50%) and Group B (N=13, reduced EF <50%). Mean AVC score was higher in the preserved EF group (mean AVC group A=3670HU, mean AVC group B=2910HU) but there was not statistical significant differences between the groups (p=0.19). In group A, AVC score positively correlated with measured peak to peak gradient (r=+0.59, p<0.001), Doppler-derived AV maximum velocity (r=+0.39, p=0.02) and mean AV gradient(r=+0.53, p=0.002), while in group B we did not found any significant association between AVC score and peak to peak gradient (p=0.92), AV maximum velocity (p=0.62) and mean AV gradient (p=0.07).

Conclusion

There was a strong correlation between AVC score and peak to peak gradient in patients with normal EF, but not in patients with low EF.
Incidental CT findings from myocardial perfusion PET/CTs
Authors: Berenji G , Puente C A , Niknam K H , Packard R
Published: June 2024

Introduction

New state-of-art hybrid imaging systems provide high quality CT images along with myocardial perfusion imaging (MPI), which introduces new opportunities and challenges for interpreting and referring physicians. American and European societies recommend reporting these CT scans including non MPI related incidental findings. PET MPI studies provide CT that allows examination of the chest and upper abdomen in addition to the heart and coronary vessels. Previous studies demonstrated these incidental findings may have an important impact on detection of malignancies or other abnormalities depending on the studied population. The objective of this study was to describe the prevalence of CT incidental findings during MPI PET/CT. We hypothesized that the veteran population may have a high prevalence of incidental CT findings based on their risk factor profile.

Methods

This IRB-approved single-center retrospective study included 2756 patients, who underwent 82-rubidium-chloride PET-CT MPI between December 2018 and July 2022. Each patient received a low dose CT of the chest and upper abdomen for attenuation correction and anatomic localization. At our institution, complete CT reports are generated by board certified nuclear medicine physicians or cardiologists with special competency in CT interpretation. Data collected by reviewing the MPI reports resided in the PACS system. Incidental CT findings were identified, and percentages of each finding were calculated.

Results

In addition to abnormal PET MPI findings including ischemia and/or scar, the thoracic CT demonstrated incidental findings in aorta (14%), pulmonary artery (20%), coronary arteries (94%), lung (50%), lymph nodes (3%), and breast (12%). The upper abdominal CT findings included the liver (14%), gallbladder (10%), spleen (3%), kidneys (13%), stomach (10%), and ascites (1%). Some of these findings were deemed serious which required follow up imaging.

Conclusion

Our study again confirms the importance of reviewing and reporting CT component of MPI studies as recommended by American and European societies. These CT images frequently, demonstrate incidental thoracic and upper abdominal findings, some of which require further workup. However, these findings can be burdensome for the referring physician and may cause patient anxiety. Hence, adequate training and experience or a multispecialty approach may be necessary to accurately interpret and provide differential diagnosis and recommendation to minimize the healthcare burden and anxiety for patients while maximizing the clinical benefits.
Baseline left ventricular ejection fraction assessed by cardiac computed tomography in patients undergoing transcatheter aortic valve replacement
Authors: Lopes V , Moreira N , Fernandes R , Cunha G , Ramalho A , Teixeira R , Goncalves L
Published: June 2024

Introduction

Left ventricular systolic dysfunction has been associated with adverse outcomes after transcatheter aortic valve replacement (TAVR). Patients undergoing TAVR routinely undergo cardiac computed tomography (CCT) to plan the procedure. Left ventricular ejection fraction (LVEF) can be assessed by CCT, but its association with prognosis in patients undergoing TAVR in unclear.

Purpose

To investigate the association between LVEF assessed by CCT and clinical outcomes after TAVR.

Methods

We retrospectively assessed baseline LVEF using preprocedural CCT in patients undergoing TAVR. Two groups were identified: (1) patients with an LVEF of <50%, and (2) patients an LVEF of ≥50%. Baseline clinical characteristics, laboratory data, and clinical outcomes were analyzed. The primary endpoint was major adverse cardiac events (MACE) at 1 year, defined as a composite of all-cause mortality, heart failure hospitalization, and stroke.

Results

A total of 157 consecutive TAVR patients were included in the analysis: median age was 82 (IQR 8) years, and 55% (n=86) of patients were male. Mean LVEF assessed by CCT was 56.3 ±15.1%, and 29% (n=45) of patients had an LVEF <50%.

Groups were comparable regarding age and sex. Compared with patients with normal LVEF, patients with low LVEF were more likely to have a history of myocardial infarction (4.5% vs. 17.8%, p=0.01). There were no significant differences regarding other baseline comorbidities and laboratory analysis between groups.

Regarding CCT findings, patients with left ventricular dysfunction had a larger LV [indexed LV end-diastolic volume 82 (IQR 26) vs. 108 (IQR 39) ml/m2, p<0.001], and a lower right ventricular ejection fraction [43 (IQR 9) vs. 35 (IQR 13) %, p <0.001].

Regarding prognosis, after 1 year post-TAVR, 13.5% (n=24) of patients experienced the primary endpoint. Rates of MACE did not differ between groups (12.6% vs 15.6%, p=0.63; HR 1.27, 95% CI 0.51-3.15, p=0.61), although patients with an LVEF <50% were numerically at higher risk. When LVEF was treated as continuous variable, it was also not found to be associated with increased 1-year risk of MACE (HR 0.98, 95% CI 0.96–1.01; p=0.16) or all-cause mortality (HR, 0.97; 95% CI 0.93–1.00; p=0.07). Main results are presented in Table 1. Kaplan-Meier survival curves can be seen in Figure 1.

Conclusion

The assessment of LVEF using preprocedural CCT in patients undergoing TAVR is possible. Baseline LVEF assessed by CCT was not found to be an independent predictor of 1-year MACE after TAVR.Table 1  Figure 1
Left ventricular ejection fraction by computed tomography in severe aortic stenosis patients - real world experience
Authors: Costa G , Silva A L , Ramalho R , Vieira M J , Goncalves L , Teixeira R
Published: June 2024

Introduction

The left ventricular ejection fraction (LVEF) is pivotal for predicting cardiac outcomes and treatment decisions, with multiple imaging methods available for its assessment. While cardiac computed tomography (CCT) serves as a standard test to evaluate the aortic valve structure prior to transcatheter aortic valve implantation (TAVI), it typically focuses on assessing the aortic valve rather than routinely providing quantitative information about LVEF despite its capability to offer insights into other cardiac structures.

Purpose

The aim of this study is to assess the correlation and agreement between LVEF measured by two-dimensional transthoracic echocardiography (TTE) and CCT in severe aortic stenosis patients.

Methods

Single-center, retrospective study. Patients undergoing CCT preceding TAVI for severe aortic stenosis from June until December 2023 were selected. Patients without measurements for both TTE and CCT LVEF were excluded from the analysis. The paired-sample T-test and Pearson's coefficient of correlation (r) were calculated, and the Bland-Altman plot was inspected to assess the between-agreement measurements of the two modalities, using SPSS 28.0.1.1 software.

Results

Of the 113 patients with severe aortic stenosis identified, only 42 (37.2%) had measurements of both TTE and CCT LVEF and were enrolled in the analysis. The mean age of the population was 82.3 (±6.8) years, 64.3% female. Cardiovascular risk factors were significantly prevalent: 90.0% had arterial hypertension, 75.0% had dyslipidemia, and 47.5% had diabetes. The prevalence of coronary artery disease was considerable (28.2%). Based on the LVEF-TTE assessment, 21.4% of patients had LVEF inferior to 50%.

Despite a statistically significant difference between TTE and CCT LVEF means (55.5±10.6% vs. 61.9±15.4%, p<0.001), a positive moderate correlation was observed between the measurements (r=0.606; p<0.001). In the subgroup analysis, the correlation was stronger in patients with LVEF lower than 50% (r=0.759, p=0.018) when compared with the higher LVEF group (r=0.427; p=0.013).

Analyzing the Bland-Altman plot of LVEF from the comparison between the two imaging modalities, CCT showed an overall tendency to overestimate LVEF (mean difference=-6.43±10.56%), particularly with LVEF increasing.

Conclusion

Despite a moderate correlation, CCT gives considerably different LVEF measurements than TTE in severe aortic stenosis patients undergoing CCT prior to TAVI. CCT showed a tendency to systematically overestimate LVEF, highlighting the importance of careful interpretation when comparing these imaging findings.
Assessing the efficacy and safety of propranolol for cardiac computed tomography in severe aortic stenosis - defying the norm
Authors: Costa G , Silva A L , Cunha G , Guimaraes J , Fernandes D , Monteiro E , Ramalho A R , Vieira M J , Goncalves L , Teixeira R
Published: June 2024

Introduction

Cardiac computed tomography angiography (CCTA) is a crucialexamination in the planning of percutaneous aortic valve implantation (TAVI) for patients with severe aortic stenosis. However, proper heart rate control is essential for obtaining high-quality images through cardiac CCTA, reducing the occurrence of motion artifacts. Intravenous beta-Blockers (BB) are usually used to induce bradycardia during CCTA but are contra-indicated in patients with aortic stenosis. Oral propranolol is a non-selective BB that pharmacodynamics may be favorable for this subset of patients.

Methods

This is a single-center prospective observational study that included patients with severe aortic stenosis admitted for CCTA for TAVI planning. Patients with pacemakers were excluded. Patients with HR 55-64 bpm and systolic blood pressure (BP) > 105 mmHg were administered 5 mg oral propranolol and patients with HR >65 bpm and systolic BP were administered 10 mg. HR, symptomatic bradycardia and hypotension were assessed.

Results

We included 92 patients between July and November 2023. 48 patients were male (52%). Mean age was 76 ± 6,3 years. Atrial fibrillation was presented 32 patients (34,7%). In patients that oral propranolol was administered a mean HR difference was –7,86 ± 10,64 bpm versus 1,75 ± 7,41 bpm in patients without BB prior to CCTA. Mann-Whitney test yield a statistically significant result (P < 0.01) between the 2 groups. No symptomatic bradycardia or hypotension was reported,and all patients were safely discharged.

Conclusion

Our study suggests that oral propranol proved a safe and usefulagent for lowering HR in patients with severe aortic stenosis undergoing CCTA pre-TAVI.
Calcium hides the clue: unraveling the diagnostic value of early coronary calcium scoring in cardiac arrest survivors
Authors: Martins A , Rigueira J , Alves Da Silva P , Garcia A B , Oliveira C , Valente Silva B , Placido R , Silva D , Pinto F J , Almeida A G
Published: June 2024

Aim

To find if CAC in non-gated CT scans performed in OHCA survivors could be a good predictor of coronary artery disease and help select those who effectively require CA. Assess the rate of CAC reporting.

Methods

Single-center, retrospective study of OHCA survivors without STEMI. We selected those who performed a non-gated chest CT as a part of an etiological study and underwent CAG due to clinical, ECG or echo suspicion of ACS. An investigator blinded to the CAG report, evaluated CAC quantitatively (with Agatston score) and qualitatively (absent, mild, moderate or severe).

Results

45 pts were included, 71% male, mean age of 5710 years old. 88,9% of the OHCA were witnessed, with mean no-flow time of 4±7min and low-flow time of 18,3±13,6min. Most pts presented with ventricular fibrillation or non-specified shockable rhythm (22,4% each). CT scans were performed with a mean of 3,7h after first medical contact. CAC was identified in 57,8% pts and classified as mild, moderate and severe in 11,1%, 24,4% and 22,2%, respectively. Mean Agatston score: 387 322UA. 16pts (33,3%) had significant coronary lesions, of which 80% had angioplasty and 2,2% CABG.

Quantitative CAC assessment accurately predicted significant lesions (AUC=0,873; 95%CI 0,773-0,974, p<0,001). In fact, of the 19 pts without calcification, none showed significant lesions on CAG. Moderate or severe CAC also predicted significant lesions (OR=13,4,95%CI 1,755- 103,68, p=0,012). There was also a good and significant correlation between the vessel with moderate calcification in CT-scan (Agatston score >100] ) and the vessel identified as culprit in CAG (kappa=0,615, p<0,001). The CAC was reported in only 7,7% CT exams, all with severe calcification.

Conclusion

Assessment of CAC in chest CT scans proved to be feasible and had a strong correlation with the presence, severity and location of CAD. Its routine use upfront showed to be an important complement to CT scans report to guide patient care – avoiding time consuming invasive procedure and focusing on neuro-protection.
Simplified, non invasive CCTA based identification of high risk coronary artery disease - long term prognostic implications
Authors: Giannopoulos A , Rossi A R , Steffek Z S , Jurisic S J , Heiniger P S H , Gajic M G , Albertini T A , Benz D C B , Buechel R R B , Kaufmann P A K , Pazhenkottil A P P
Published: June 2024

Background/Introduction

The CT-BCIS-Jeopardy score is a simple angiographic scoring system, enabling quantification of the extent of jeopardized myocardium related to clinically significant coronary artery disease (CAD), using coronary CT angiography (CCTA). Grading only lesions with ≥70% diameter stenosis and ranging from zero (non-significant CAD) to twelve (very extensive CAD), it allows accurate and fast identification of high-risk CAD. We aimed to assess the long-term prognostic value of the CT-BCIS-Jeopardy score.

Methods

Retrospectively, 337 patients with known or suspected CAD referred for CCTA between 2005 and December 2008 were included. The CT-BCIS-Jeopardy score was estimated for all patients using a purpose-developed online calculator, with a score of ≥6 indicating high-risk CAD. Endpoints were all-cause death or myocardial infarction ("hard events") and a composite of major adverse cardiovascular events (MACE). The Kaplan-Meier method was used to identify survival free of MACE, and Cox proportional hazard regression analysis was used to determine independent predictors for MACE.

Results

Mean patients’ age was 61.7±11 years and 216 (64%) were male. High-risk CAD was detected in 88 (26.1%) patients. During a median follow-up of 6.8 (IQR: 5.7-8.5) years, 47 (14%) patients had a hard event and 97 (29%) patients experienced any MACE. Compared to non-high-risk CAD, patients with high-risk CAD had 9.6-fold higher event rate for hard events [9 (19%) vs. 38 (81%); p<0.001] and 22-fold higher annual event rate for any MACE [19 (5.6%) vs. 78 (23%); p<0.001]. When adjusted for age, sex, BMI, and traditional CAD risk factors, a CT-BCIS-Jeopardy score of ≥6 was an independent strong predictor of both, all MACE and hard events.

Conclusions

The CT-BCIS-Jeopardy score is an excellent non-invasive long-term predictor of adverse cardiac events. High-risk CAD identified using the score is associated with significantly higher annual cardiac event rate.Figure 1  Figure 2
Incremental value of a novel AI-based CCTA derived ischemia algorithm over standard CCTA interpretation for predicting myocardial ischemia in suspected coronary artery disease
Authors: Nabeta T , Bar S , Maanniitty T , Min J K , Earls J P , Bax J J , Saraste A , Knuuti J
Published: June 2024

Background

Coronary computed tomography angiography (CCTA) is a widely used non-invasive test to diagnose coronary artery stenosis in patients with suspected coronary artery disease (CAD); however, it does not provide information of the functional ischemia. A novel artificial intelligence -guided quantitative CT ischemia algorithm (AI-QCTischemia) has been established, which comprises a machine-learned method using features of atherosclerosis and vascular morphology from CCTA images to identify the likelihood of myocardial ischemia.

Purpose

The aim of this study is to investigate the diagnostic performance of AI-QCTischemia over standard CCTA interpretation in detecting myocardial ischemia using positron emission tomography (PET) perfusion imaging as a reference standard.

Methods

Patients with suspected CAD referred for CCTA at our University Hospital from February 2007 to December 2016 were analysed. The AI-QCTischemia algorithm was applied by analysts blinded for patient characteristics and clinical outcomes using the CCTA images to detect probability of myocardial ischemia per patient level. In diagnostic reading significant stenosis was defined as 50% on CCTA. The reference standard was ischemia detected by stress 15O-H2O PET.

Results

A total of 1746 patients (mean age 62 ± 10 years, 44% male) were included. Myocardial ischemia by PET was detected in 325 (19%) patients while the other patients had either normal PET or had non-obstructive CAD by CCTA. AI-QCTischemia was found positive in 430 (25%) patients. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the AI-QCTischemia algorithm for the assessment of myocardial ischemia were 87%, 81%, 88%, 61%, and 95%, respectively. Compared with the clinical visual reading of CCTA, AI-QCTischemia demonstrated higher specificity and positive predictive value but somewhat lower sensitivity and negative predictive value. The accuracy of AI-QCTischemia was 87% while it was 86% with visual reading of CCTA. (Figure 1) Compared with diagnostic reading of CCTA (area under the receiver operating characteristic curve [AUC], 0.868), the model including clinical reading and AI-QCTischemia algorithm demonstrated superior discrimination of myocardial ischemia (AUC 0.899, p-value <0.001). (Figure 2)

Conclusions

A novel AI-based ischemia algorithm derived from CCTA has a high diagnostic accuracy for predicting myocardial ischemia defined by PET perfusion imaging in symptomatic patients with suspected CAD. Moreover, combination of novel AI-based ischemia algorithm and clinical reading of CCTA demonstrated that incremental diagnostic accuracy for predicting diagnostic accuracy.Diagnostic accuracy of CCTA and AI-QCT  AUC for myocardial ischemia on PET
Cardiovascular risk assessment and atherosclerosis phenotype by coronary computed tomography angiography in a cohort of Italian patients with type 1 diabetes mellitus
Authors: Mushtaq S , Genovese S , Licastro M , Rondinelli M , Gallotta A , Bonomi A , Baggiano A , Fazzari F , Tassetti L , Volpe A , Fusini L , Maragna R , Junod D , Andreini D , Pontone G
Published: June 2024

Objective

Mortality rates are 2- to 4-fold higher in people with type 1 diabetes mellitus (T1DM) than in the general population. Cardiovascular disease (CVD) is the main cause of such excess mortality, with CVD events occurring over a decade earlier than expected. However, while epidemiological studies on CVD and type 2 diabetes mellitus are numerous, less information is available on the prevalence of CVD in patients with T1DM. The primary aim of the study was to evaluate the prevalence of CAD at coronary CT angiography (CCTA) in consecutive T1DM patients referred to our diabetic center and to assess the characteristics of coronary plaques in this population.

Materials and Methods

We prospectively enrolled 109 consecutive T1DM patients referred to our diabetic unit center in CARDT1 study.

Patients underwent a non-contrast CT for calculation of Calcium Score and a CCTA.

Patients were stratified into three risk groups according to the STENO T1 RISK ENGINE and the ESC score. After the finding of CCTA patients were also divided into three groups: normal (no coronary plaques), non-obstructive CAD (lesions ,50%), and obstructive CAD (lesions >50%). The number of segments with any obstructive plaque also was recorded. Each coronary segment was evaluated for the presence of calcified and mixed plaques.

Results

The analytic study population consisted of 88 patients. Fourty-seven were male (53%) and the mean age was 46.42±13.09 years old with a mean duration of diabetes of 24 years.

According to the Steno Type 1 Risk Engine, the mean estimated risk of CVD events over 5 years was 5.1% and 10% over 10 years. Thirty-five patients (48%) and 15 (20%) were classified as low and high Steno Risk, respectively. Moreover 45 (51%) patients have completely normal coronary arteries, 32 (36%) non obstructive CAD and 11 (12%) obstructive CAD.

In patients with obstructive CAD the duration of diabetes was significantly higher than in those with no CAD and not obstructive CAD (40 years vs 17 years and 27 years, respectively, p<0.0001).

Eighty-three% of low risk Steno Score T1DM have normal coronary arteries while 21% of high risk Steno score patients had obstructive CAD and 14% of high Steno risk have no plaque at CTCA. The number of coronary segments diseased was 1.5 (median) in non-obstructive CAD patients and 4 in obstructive CAD patients (p<0.0001).

Among 118 coronary segments diseased, in 51 segments there was a calcified disease and in 65 there was a non prevalent calcified atherosclerotic disease

Conclusions

CCTA is able to restratify the risk of CAD in T1DM according to the presence or absence of CAD.

In contrast with T2 diabetic patients who have a prevalent calcified and diffuse disease, T1DM patients have a more focal and fibrolipidic pattern of CAD.
Incremental prognostic value of artificial intelligence-based automated plaque characterisation on top of ischemia evaluation by CCTA and CCTA/PET
Authors: Bar S , Maaniitty T , Kiatkittikul P , Nabeta T , Bax J J , Min J K , Earls J P , Saraste A , Knuuti J
Published: June 2024

Background

Artificial intelligence (AI)-based quantitative computed tomography (AI-QCT) is a novel tool for automated plaque characterisation and quantitation from coronary computed tomography angiography (CCTA). The prognostic value of various AI-QCT plaque types on top of the presence of ischemic coronary artery disease (CAD) is unknown to date.

Purpose

We aimed to investigate the added prognostic value of the AI-QCT plaque characteristics percent atheroma volume (PAV) %, non-calcified plaque burden (NCPB) %, and calcified plaque burden (CPB) % on top of: 1) A novel AI-based CCTA-derived ischemia algorithm (AI-QCTischemia) which predicts the presence of invasive FFR ≤0.80 using 38 morphological features from CCTA; and 2) ischemic CAD based on hybrid CCTA/15O-H2O positron emission tomography (PET) for the composite of all-cause death, myocardial infarction (MI), or unstable angina pectoris (uAP).

Methods

This was a cohort of 1772 symptomatic patients having undergone hybrid CCTA/15O-H2O PET perfusion imaging to assess the presence of ischemic CAD. Multivariable Cox regressions adjusted for clinical confounders (age, sex, hypertension, diabetes, smoking, typical angina) were performed and compared with the C-index. AI-QCTischemia models were: 1) AI-QCTischemia, 2) AI-QCTischemia+PAV, 3) AI-QCTischemia+NCPB, 4) AI-QCTischemia+CPB. Hybrid CCTA/PET models were: 5) hybrid CCTA/PET, 6) hybrid CCTA/PET+PAV, 7) hybrid CCTA/PET+NCPB, and 8) hybrid CCTA/PET+CPB.

Results

Throughout a median follow-up of 7 years, 177/1772 (10%) patients experienced the composite endpoint. The C-indexes (p-value vs. model 1) of the AI-QCTischemia models were 1) 0.729, 2) 0.748 (p=0.008), 3) 0.743 (p=0.012), and 4) 0.739 (p=0.067). The C-indexes (p-value vs. model 5) of the hybrid CCTA/PET models were: 5) 0.733, 6) 0.751 (p=0.014), 7) 0.746 (p=0.018), 8) 0.745 (p=0.058). AI-QCTischemia and hybrid CCTA/PET imaging performed similarly by means of C-statistics.

Conclusions

PAV and NCPB, but not CPB by AI-QCT plaque analysis improved the prediction of 7-year death, MI, or uAP when added on top of the presence of ischemic CAD, determined either by AI-QCTischemia or hybrid CCTA/PET imaging. Overall, the risk stratification based on AI-QCTischemia performed similarly as hybrid CCTA/PET imaging.C-indexes for death, MI, or uAP
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

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<0.001; model 3 vs. model 2: p<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

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 <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

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 <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

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

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

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] > 18.4º, bandwidth [BD] > 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 > 18.4º and/or BD > 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<18) and/or abnormal ventricular motility (STS >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.