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31


Three's Company: A Rare Case of a Myocardial Bridge With Concomitant SCAD and Takotsubo Cardiomyopathy [Editorial]

Gianos, Eugenia; Dwivedi, Aeshita
PMCID:8310970
PMID: 34317513
ISSN: 2666-0849
CID: 4949492

Age- and sex-related features of atherosclerosis from coronary computed tomography angiography in patients prior to acute coronary syndrome: results from the ICONIC study

Conte, Edoardo; Dwivedi, Aeshita; Mushtaq, Saima; Pontone, Gianluca; Lin, Fay Y; Hollenberg, Emma J; Lee, Sang-Eun; Bax, Jeroen; Cademartiri, Filippo; Chinnaiyan, Kavitha; Chow, Benjamin J W; Cury, Ricardo C; Feuchtner, Gudrun; Hadamitzky, Martin; Kim, Yong-Jin; Baggiano, Andrea; Leipsic, Jonathon; Maffei, Erica; Marques, Hugo; Plank, Fabian; Raff, Gilbert L; van Rosendael, Alexander R; Villines, Todd C; Weirich, Harald G; Al'Aref, Subhi J; Baskaran, Lohendran; Cho, Iksung; Danad, Ibrahim; Han, Donghee; Heo, Ran; Lee, Ji Hyun; Stuijfzand, Wijnand J; Gransar, Heidi; Lu, Yao; Sung, Ji Min; Park, Hyung-Bok; Al-Mallah, Mouaz H; de Araújo Gonçalves, Pedro; Berman, Daniel S; Budoff, Matthew J; Samady, Habib; Shaw, Leslee J; Stone, Peter H; Virmani, Renu; Narula, Jagat; Min, James K; Chang, Hyuk-Jae; Andreini, Daniele
AIMS/OBJECTIVE:Although there is increasing evidence supporting coronary atherosclerosis evaluation by coronary computed tomography angiography (CCTA), no data are available on age and sex differences for quantitative plaque features. The aim of this study was to investigate sex and age differences in both qualitative and quantitative atherosclerotic features from CCTA prior to acute coronary syndrome (ACS). METHODS AND RESULTS/RESULTS:Within the ICONIC study, in which 234 patients with subsequent ACS were propensity matched 1:1 with 234 non-event controls, our current subanalysis included only the ACS cases. Both qualitative and quantitative advance plaque analysis by CCTA were performed by a core laboratory. In 129 cases, culprit lesions identified by invasive coronary angiography at the time of ACS were co-registered to baseline CCTA precursor lesions. The study population was then divided into subgroups according to sex and age (<65 vs. ≥ 65 years old) for analysis. Older patients had higher total plaque volume than younger patients. Within specific subtypes of plaque volume, however, only calcified plaque volume was higher in older patients (135.9 ± 163.7 vs. 63.8 ± 94.2 mm3, P < 0.0001, respectively). Although no sex-related differences were recorded for calcified plaque volume, females had lower fibrous and fibrofatty plaque volume than males (Fibrofatty volume 29.6 ± 44.1 vs. 75.3 ± 98.6 mm3, P = 0.0001, respectively). No sex-related differences in the prevalence of qualitative high-risk plaque features were found, even after separate analyses considering age were performed. CONCLUSION/CONCLUSIONS:Our data underline the importance of age- and sex-related differences in coronary atherosclerosis presentation, which should be considered during CCTA-based atherosclerosis quantification.
PMID: 32793985
ISSN: 2047-2412
CID: 4556762

Unusual Cause of Severe Tricuspid Regurgitation: Tricuspid Leaflet Annular Tear Following Remote Motor Vehicle Accident [Case Report]

Bamira, Daniel G; Dwivedi, Aeshita; Bhatla, Puneet; Halpern, Dan; Vainrib, Alan F; Kim, Eugene; Zias, Elias; Saric, Muhamed
Tricuspid regurgitation (TR) is an uncommon and underdiagnosed complication of blunt chest trauma. Typical mechanisms include torn chordae, papillary muscle rupture, and radial leaflet tear. We describe an unusual case of traumatic TR due to circumferential avulsion of the anterior tricuspid leaflet from the tricuspid annulus and the crucial role of multimodality imaging in its diagnosis and treatment. (Level of Difficulty: Intermediate.).
PMCID:8299867
PMID: 34317128
ISSN: 2666-0849
CID: 4949442

Constrictive Pericarditis Caused by IgG4-Related Disease Requiring Pericardiectomy After Partial Response to Corticosteroids [Case Report]

Yuriditsky, Eugene; Dwivedi, Aeshita; Narula, Navneet; Axel, Leon; Horowitz, James M; Vaynblat, Mikhail
Immunoglobulin G4-related disease is a systemic fibroinflammatory disease; pericardial involvement has occasionally been reported in publications. A 79-year-old man with biopsy-proven immunoglobulin G4-related disease with pleural involvement was admitted in acute heart failure, with imaging and hemodynamic studies consistent with constrictive pericarditis. He was treated with corticosteroids for 2 months with partial response manifest by decreases in pericardial thickening and immunoglobulin G4 levels. However, persistent constriction required pericardiectomy, leading to significant symptomatic improvement. (Level of Difficulty: Intermediate.).
PMCID:8302180
PMID: 34317017
ISSN: 2666-0849
CID: 4949402

A Rare Case of Sarcoidosis-Induced Polyserositis and Steroid-Induced Mediastinal Lipomatosis Masquerading as an Epicardial Tumor [Case Report]

Qiu, Jessica K; Dwivedi, Aeshita; Alter, Eric; Halpern, Dan; Katz, Edward S; Donnino, Robert; Saric, Muhamed
PMCID:7303243
PMID: 32577599
ISSN: 2468-6441
CID: 4493172

Body mass index and peripheral artery disease

Heffron, Sean P; Dwivedi, Aeshita; Rockman, Caron B; Xia, Yuhe; Guo, Yu; Zhong, Judy; Berger, Jeffrey S
BACKGROUND AND AIMS/OBJECTIVE:An independent association of body mass index (BMI) with atherosclerotic cardiovascular disease is somewhat controversial and may differ by vascular bed. Sex-specific risk factors for atherosclerosis may further modify these associations. Obesity and peripheral artery disease (PAD) are both more prevalent in women. We sought to determine the association between PAD and BMI using a very large population-based study. METHODS:Self-referred individuals at >20,000 US sites completed medical questionnaires including height and weight, and were evaluated by screening ankle brachial indices (ABI) for PAD (ABI<0.9). RESULTS:). CONCLUSIONS:Our study suggests that increasing BMI is a robust independent risk factor for PAD only in women. This observation requires validation, but highlights the need for further research on sex-specific risk and mechanisms of atherosclerosis.
PMID: 31739257
ISSN: 1879-1484
CID: 4208652

Quantitative Evaluation of High-Risk Coronary Plaque by Coronary CTA and Subsequent Acute Coronary Events

van Rosendael, Alexander R; Al'Aref, Subhi J; Dwivedi, Aeshita; Kim, Timothy S; Peña, Jessica M; Dunham, Patricia C; Kim, Yong-Jin; Chinnaiyan, Kavitha; Feuchtner, Gudrun; Plank, Fabian; Berman, Daniel S; Shaw, Leslee J; Chang, Hyuk-Jae; Lin, Fay Y; Bax, Jeroen J; Narula, Jagat; Min, James K
PMID: 30660535
ISSN: 1876-7591
CID: 3682712

Implantable Loop Recorder in Inherited Arrhythmia Diseases: A Critical Tool for Symptom Diagnosis and Advanced Risk Stratification [Letter]

Dwivedi, Aeshita; Joza, Jacqueline; Malkani, Kabir; Mendelson, Todd B; Priori, Silvia G; Chinitz, Larry A; Fowler, Steven J; Cerrone, Marina
PMID: 30336885
ISSN: 2405-5018
CID: 3368792

Machine learning in cardiac CT: Basic concepts and contemporary data

Singh, Gurpreet; Al'Aref, Subhi J; Van Assen, Marly; Kim, Timothy Suyong; van Rosendael, Alexander; Kolli, Kranthi K; Dwivedi, Aeshita; Maliakal, Gabriel; Pandey, Mohit; Wang, Jing; Do, Virginie; Gummalla, Manasa; De Cecco, Carlo N; Min, James K
Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular medicine. Owing to the growing body of literature validating both the diagnostic performance as well as the prognostic implications of anatomic and physiologic findings, coronary computed tomography angiography (CCTA) is now a well-established non-invasive modality for the assessment of cardiovascular disease. ML has been increasingly utilized to optimize performance as well as extract data from CCTA as well as non-contrast enhanced cardiac CT scans. The purpose of this review is to describe the contemporary state of ML based algorithms applied to cardiac CT, as well as to provide clinicians with an understanding of its benefits and associated limitations.
PMID: 29754806
ISSN: 1876-861x
CID: 3130032

Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry

van Rosendael, Alexander R; Maliakal, Gabriel; Kolli, Kranthi K; Beecy, Ashley; Al'Aref, Subhi J; Dwivedi, Aeshita; Singh, Gurpreet; Panday, Mohit; Kumar, Amit; Ma, Xiaoyue; Achenbach, Stephan; Al-Mallah, Mouaz H; Andreini, Daniele; Bax, Jeroen J; Berman, Daniel S; Budoff, Matthew J; Cademartiri, Filippo; Callister, Tracy Q; Chang, Hyuk-Jae; Chinnaiyan, Kavitha; Chow, Benjamin J W; Cury, Ricardo C; DeLago, Augustin; Feuchtner, Gudrun; Hadamitzky, Martin; Hausleiter, Joerg; Kaufmann, Philipp A; Kim, Yong-Jin; Leipsic, Jonathon A; Maffei, Erica; Marques, Hugo; Pontone, Gianluca; Raff, Gilbert L; Rubinshtein, Ronen; Shaw, Leslee J; Villines, Todd C; Gransar, Heidi; Lu, Yao; Jones, Erica C; Peña, Jessica M; Lin, Fay Y; Min, James K
INTRODUCTION/BACKGROUND:Machine learning (ML) is a field in computer science that demonstrated to effectively integrate clinical and imaging data for the creation of prognostic scores. The current study investigated whether a ML score, incorporating only the 16 segment coronary tree information derived from coronary computed tomography angiography (CCTA), provides enhanced risk stratification compared with current CCTA based risk scores. METHODS:From the multi-center CONFIRM registry, patients were included with complete CCTA risk score information and ≥3 year follow-up for myocardial infarction and death (primary endpoint). Patients with prior coronary artery disease were excluded. Conventional CCTA risk scores (conventional CCTA approach, segment involvement score, duke prognostic index, segment stenosis score, and the Leaman risk score) and a score created using ML were compared with the C-statistic. Only 16 segment based coronary stenosis (0%, 1-24%, 25-49%, 50-69%, 70-99% and 100%) and composition (calcified, mixed and non-calcified plaque) were provided to the ML model. A boosted ensemble algorithm (extreme gradient boosting; XGBoost) was used and the entire data was randomly split into a training set (80%) on which 5-fold internal cross validation was done to tune the model. The performance of this model was independently tested using the test set (20%). RESULTS:In total, 8844 patients (mean age 58.0 ± 11.5 years, 57.7% male) were included. During a mean follow-up time of 4.6 ± 1.5 years, 609 events occurred (6.9%). No CAD was observed in 48.7% (3.5% event), non-obstructive CAD in 31.8% (6.8% event), and obstructive CAD in 19.5% (15.6% event). Discrimination of events as expressed by C-statistic was significantly better for the ML based approach (0.771) vs the other scores (ranging from 0.685 to 0.701), P < 0.001. Net reclassification improvement analysis showed that the improved risk stratification was the result of down-classification of risk among patients that did not experience events (non-events). CONCLUSION/CONCLUSIONS:A risk score created by a ML based algorithm, that utilizes standard 16 coronary segment stenosis and composition information derived from detailed CCTA reading, has greater prognostic accuracy than current CCTA integrated risk scores. These findings indicate that a ML based algorithm can improve the integration of CCTA derived plaque information to improve risk stratification.
PMID: 29753765
ISSN: 1876-861x
CID: 3130022