Artificial Intelligence in Cardiac Imaging

Machine learning (ML), a subset of artificial intelligence, is showing promising results in cardiology, especially in cardiac imaging. ML algorithms are allowing cardiologists to explore new opportunities and make discoveries not seen with conventional approaches. This offers new opportunities to enhance patient care and open new gateways in medical decision-making. This review highlights the role of ML in cardiac imaging for precision phenotyping and prognostication of cardiac disorders

Cardiovascular Imaging and Intervention Through the Lens of Artificial Intelligence

Artificial Intelligence (AI) is the simulation of human intelligence in machines so they can perform various actions and execute decision-making. Machine learning (ML), a branch of AI, can analyse information from data and discover novel patterns. AI and ML are rapidly gaining prominence in healthcare as data become increasingly complex. These algorithms can enhance the role of cardiovascular imaging by automating many tasks or calculations, find new patterns or phenotypes in data and provide alternative diagnoses. In interventional cardiology, AI can assist in intraprocedural guidance, intravascular imaging and provide additional information to the operator. AI is slowly expanding its boundaries into interventional cardiology and can fundamentally alter the field. In this review, the authors discuss how AI can enhance the role of cardiovascular imaging and imaging in interventional cardiology

Optical imaging of the peri-tumoral inflammatory response in breast cancer

<p>Abstract</p> <p>Purpose</p> <p>Peri-tumoral inflammation is a common tumor response that plays a central role in tumor invasion and metastasis, and inflammatory cell recruitment is essential to this process. The purpose of this study was to determine whether injected fluorescently-labeled monocytes accumulate within murine breast tumors and are visible with optical imaging.</p> <p>Materials and methods</p> <p>Murine monocytes were labeled with the fluorescent dye DiD and subsequently injected intravenously into 6 transgenic MMTV-PymT tumor-bearing mice and 6 FVB/n control mice without tumors. Optical imaging (OI) was performed before and after cell injection. Ratios of post-injection to pre-injection fluorescent signal intensity of the tumors (MMTV-PymT mice) and mammary tissue (FVB/n controls) were calculated and statistically compared.</p> <p>Results</p> <p>MMTV-PymT breast tumors had an average post/pre signal intensity ratio of 1.8+/- 0.2 (range 1.1-2.7). Control mammary tissue had an average post/pre signal intensity ratio of 1.1 +/- 0.1 (range, 0.4 to 1.4). The p-value for the difference between the ratios was less than 0.05. Confocal fluorescence microscopy confirmed the presence of DiD-labeled cells within the breast tumors.</p> <p>Conclusion</p> <p>Murine monocytes accumulate at the site of breast cancer development in this transgenic model, providing evidence that peri-tumoral inflammatory cell recruitment can be evaluated non-invasively using optical imaging.</p

Role of extended Vs conventional echocardiographic parameters to quantify severity of aortic stenosis

AIMS : The objective of the study was to evaluate left ventricular (LV) strain by speckle tracking imaging and plasma NT-ProBNP in patients with moderate to severe aortic valve stenosis (AS). METHODS : Thirty-three patients with isolated AS with preserved ejection fraction (EF) and ten controls underwent assessment of symptoms, transthoracic echocardiography and measurement of plasma levels of NT-ProBNP.LV Strain and plasma NT-ProBNP were analysed to find differences and correlation with conventional echocardiographic parameters and clinical variables. These parameters were also studied for their strength to predict symptomatic status in these patients. RESULTS : Global longitudinal (GLS), global area (GAS) and global radial (GRS) strains were lower in patients with aortic stenosis (n=33; Median -13.0,-26.0 and 40.0 ,respectively) compared to controls (n=10; Median -20.4 ,-31.5 and 49.5,respectively;p <0.001 ,0.02 and 0.01 respectively).GLS,GAS and GRS were also lower in severe AS patients (n=27 ;Median -12.6,-25.0 and – 38.0,respectively) compared to moderate AS patients (n=6;Medain -19.8,-32.5 and 52.5 respectively; p=0.02,0.01 and0.03 respectively).GLS,GAS and GCS were lower in symptomatic (n=21;Median -11.6,-25.0 and 38.0 ) compared to asymptomatic (n=12;Median -16.45,-29.5 and 47.0 respectively; p=0.001,0.005 and 0.018 respectively) patients. Global circumferential strain (GCS) did not differ significantly between controls and AS patients or between subgroups of AS. There was a regional difference in strain with longitudinal strain in basal segments being decreased with preserved apical segmental longitudinal strain. Plasma NT-ProBNP was higher in AS patients (Median 628.00 pg/ml) compared to controls (80.82 pg/ml; p<0.001). NT-ProBNP was higher in severe AS (Median 614.0 pg/ml) patients compared to moderate AS patients (Median 118.9 pg/ml) and symptomatic (Median 1191.0 pg/ml ) compared to asymptomatic (Median 118.9 pg/ml) patients. Absolute value of GLS correlated strongly with LV mass index (r= -0.70; p<0.001) and NT-ProBNP correlated strongly with LA volume index (r= 0.74; p<0.001). Log-transformed NT-ProBNP correlated well with GLS (r= -0.63; p<0.001).Of all the variables NT-ProBNP was the best predictor of symptomatic status ; cut-off of 190.95 pg/ml has sensitivity of 90.5% and specificity of 91.7%.NT-ProBNP cut-off for predicting severe AS was 141.50 pg/ml with a sensitivity of 88.9% and specificity of 83.3%. CONCLUSIONS : LV strain, especially GLS and plasma NT-ProBNP are affected early in patients with AS before the onset of symptoms and deterioration of LV function. Measurement of these variables to assess aortic stenosis patients may complement clinical and echocardiographic evaluation of these patients

MicroRNA profiling predicts a variance in the proliferative potential of cardiac progenitor cells derived from neonatal and adult murine hearts

Cardiac progenitor cells (CPCs) are multipotent cells that may offer tremendous potentials for the regeneration of injured myocardium. To expand the limited number of CPCs for effective clinical regeneration of myocardium, it is important to understand their proliferative potentials. Single-cell based assays were utilized to purify c-kit pos CPCs from human and mouse hearts. MicroRNA profiling identified eight differentially expressed microRNAs in CPCs from neonatal and adult hearts. Notably, the predicted protein targets were predominantly involved in cellular proliferation-related pathways. To directly test this phenotypic prediction, the developmental variance in the proliferation of CPCs was tested. Ki67 protein expression and DNA kinetics were tested in human and mouse in vivo CPCs, and doubling times were tested in primary culture of mouse CPCs. The human embryonic and mouse neonatal CPCs showed a six-fold increase in Ki67 expressing cells, a two-fold increase in the number of cells in S/G2-M phases of cell cycle, and a seven-fold increase in the doubling time in culture when compared to the corresponding adult CPCs. The over-expression of miR-17-92 increased the proliferation in adult CPCs in vivo by two-fold. In addition, the level of retinoblastoma-like 2 (Rbl2/p130) protein was two-fold higher in adult compared to neonatal-mouse CPCs. In conclusion, we demonstrate a differentially regulated cohort of microRNAs that predicts differences in cellular proliferation in CPCs during postnatal development and target microRNAs that are involved in this transition. Our study provides new insights that may enhance the utilization of adult CPCs for regenerative therapy of the injured myocardium. © 2011 Elsevier Ltd.link_to_OA_fulltex