Cardiac image computing for myocardial infarction patients

Cardiovascular diseases (CVDs), which are a prime cause of global mortality, are disorders that affect the heart and blood vessels' functioning. CVDs may cause consequent complications, due to occlusion in a blood vessel and present as impaired cardiac wall functioning (myocardium). Identifying such impairment (infarction) of the myocardium is of great clinical interest, as it can reveal the nature of altered cardiac topography (ventricular remodelling) to aid the associated intervention decisions. With recent advances in cardiac imaging, such as Magnetic Resonance (MR) imaging, the visualisation and identification of infarcted myocardium has been routinely and effectively used in clinical practice. Diagnosing infarcted myocardium is achieved clinically through the late gadolinium enhancement (LGE) test, which acquires MR images after injecting a gadolinium-based contrast agent (GBCA). Due to the increased accuracy and reproducibility, LGE has emerged as the gold-standard MR imaging test in identifying myocardial infarction. However, clinical studies have reported gadolinium deposition concerns in different body organs and adverse outcomes in patients with advanced kidney failure, over time. Such incidents have motivated researchers to look into the development of both accurate as well as safe diagnostic tools. Emerging research on identifying infarcted myocardium utilises myocardial strain to safely identify infarcted myocardium, which has been addressed in the presented study. For example, myocardial strain represents the shortening or lengthening of the myocardium. If the myocardium is infarcted, then the corresponding strain values differ compared to the healthy myocardium. This finding can be identified and utilised for clinical applications. The research presented in this thesis aims to identify infarcted myocardium accurately and safely by using myocardial strain (shortening or lengthening of the myocardium). To achieve the aforementioned aim, the research methodology is divided into six objectives. The initial objectives relate to the development of a novel myocardial tracking method. The middle objectives relate to the development of clinical application methods, and the final objectives concern the validation of the developed methods through clinical studies and associated datasets. The research presented in this thesis has addressed the following research question: Research question 1: How can a 2D myocardial tracking and strain calculation method be developed using the 2D local weighted mean function and structural deformation within the myocardium? Research question 2: How can a 3D myocardial tracking and strain calculation method be developed using the 3D local weighted mean function to calculate 3D myocardial strain? Research question 3: How can 2D circumferential strain of the myocardium be used in identifying infarcted left ventricular segments for the diagnosis of myocardial infarction patients? In literature, myocardial tracking and strain calculation methods have limited extension to 3D and dependency on tissue material properties. Moreover, additional limitations, such as limited inclusion of structural deformation details within the myocardium, are found in the literature. Therefore, methods are likely to become subjective or numerically unstable during computation. Moreover, the inclusion of myocardial details with grid-tagging MRI, for structural deformation within the myocardium, is more realistic compared to cine MRI.   The aforementioned limitations are overcome by proposing a novel Hierarchical Template Matching method, which performs non-rigid image registration among grid-tagging MR images of a cardiac cycle. This is achieved by employing a local weighted mean transformation function. The proposed non-rigid image registration method does not require the use of tissue material properties. Grid-tagging MRI is used to capture wall function within the myocardium, and the local weighted mean function is used for numerical stability. The performance of the developed methods is evaluated with multiple error measures and with a benchmark framework. This benchmark framework has provided an open-access 3D dataset, a set of validation methods, and results of four leading methods for comparison. Validation methods include qualitative and quantitative methods. The qualitative assessment of outcomes and verified ground truth for the quantitative evaluation of results are followed from the benchmark framework paper (Tobon-Gomez, Craene, Mcleod, et al., 2013). 2D HTM method has reported the root mean square error of point tracking in left ventricular slices, which are the basal slice 0.31±0.07 mm, the upper mid-ventricular slice 0.37±0.06 mm, the mid-ventricular slice 0.41±0.05 mm, and the apical slice 0.32±0.08 mm. The mid-ventricular slice has a significantly higher 4% (P=0.05) mean root mean square error compared to the other slices. However, the other slices do not have a significant difference among them. Compared to the benchmark free form deformation method, HTM has a mean error of 0.35±0.05 mm, which is 17% (P=0.07, CI:[-0.01,0.35]) reduced to the free form deformation method. Our technical method has shown the 3D extension of HTM and a method without using material properties, which is advantageous compared to the methods which are limited to 2D or dependent on material properties. Moreover, the 3D HTM has demonstrated the use of 3D local weighted mean function in 3D myocardial tracking. While comparing to the benchmark methods, it was found that the median tracking error of 3D HTM is comparable to benchmark methods and has very few outliers compared to them. The clinical results are validated with LGE imaging. The quantitative error measure is the area under the curve (AUC) of sensitivity vs 1-specificity curve of the receiver operating characteristic (ROC) test. The achieved AUC value in detecting infarcted segments in basal, mid-ventricular, and apical slices are 0.85, 0.82, and 0.87, respectively. Calculating AUC with 95% confidence level, the confidence intervals of lower and upper mean AUC values in basal, mid-ventricular and apical slices are [0.80, 0.89], [0.74, 0.85], and [0.78, 0.91], respectively. Overall, considering the detections of LGE imaging as the base, our method has an accuracy of AUC 0.73 (P=0.05) in identifying infarcted left ventricular segments. The developed methods have shown, systematically, a promising approach in identifying infarcted left ventricular segments by image processing method and without using GBCA-based LGE imaging.

Hierarchical template matching for 3D myocardial tracking and cardiac strain estimation

Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers

A novel hierarchical template matching model for cardiac motion estimation

Cardiovascular disease diagnosis and prognosis can be improved by measuring patient-specific in-vivo local myocardial strain using Magnetic Resonance Imaging. Local myocardial strain can be determined by tracking the movement of sample muscles points during cardiac cycle using cardiac motion estimation model. The tracking accuracy of the benchmark Free Form Deformation (FFD) model is greatly affected due to its dependency on tunable parameters and regularisation function. Therefore, Hierarchical Template Matching (HTM) model, which is independent of tunable parameters, regularisation function, and image-specific features, is proposed in this article. HTM has dense and uniform points correspondence that provides HTM with the ability to estimate local muscular deformation with a promising accuracy of less than half a millimetre of cardiac wall muscle. As a result, the muscles tracking accuracy has been significantly (p<0.001) improved (30%) compared to the benchmark model. Such merits of HTM provide reliably calculated clinical measures which can be incorporated into the decision-making process of cardiac disease diagnosis and prognosis

Comparative Review on Harmless Herbs with Allopathic Remedies As Anti- Hypertensive

ABSTRACT The incidence and prevalence of systemic hypertension are reaching global epidemic proportions. Hypertension is the leading cause of cardiovascular disease worldwide. Despite a diversity of pharmacological agents to treat high blood pressure, suboptimal control remains a significant problem in as many as 43% of patients and this rate has not significantly improved over the past 2 decades. There are a variety of factors contributing to this including patient&apos;s non-adherence due to complex drug regimens and medications side effects, under-treatment and treatment resistance. There, thus, remains a need to find herbal treatment to antihypertensive therapy that facilitate attainment of optimal blood pressure levels. This monograph will review a number of pharmacological targets and interventions, herbal alternatives to achieve optimum hypertensive boundaries as well as novel approaches for the same. This review mainly focuses on better herbal alternative of current allopathic remedies as well as newer herbal approaches like Hibiscus tea to treat hypertension

Magnetic resonance image-based brain tumour segmentation methods : a systematic review

Background: Image segmentation is an essential step in the analysis and subsequent characterisation of brain tumours through magnetic resonance imaging. In the literature, segmentation methods are empowered by open-access magnetic resonance imaging datasets, such as the brain tumour segmentation dataset. Moreover, with the increased use of artificial intelligence methods in medical imaging, access to larger data repositories has become vital in method development. Purpose: To determine what automated brain tumour segmentation techniques can medical imaging specialists and clinicians use to identify tumour components, compared to manual segmentation. Methods: We conducted a systematic review of 572 brain tumour segmentation studies during 2015–2020. We reviewed segmentation techniques using T1-weighted, T2-weighted, gadolinium-enhanced T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and perfusion-weighted magnetic resonance imaging sequences. Moreover, we assessed physics or mathematics-based methods, deep learning methods, and software-based or semi-automatic methods, as applied to magnetic resonance imaging techniques. Particularly, we synthesised each method as per the utilised magnetic resonance imaging sequences, study population, technical approach (such as deep learning) and performance score measures (such as Dice score). Statistical tests: We compared median Dice score in segmenting the whole tumour, tumour core and enhanced tumour. Results: We found that T1-weighted, gadolinium-enhanced T1-weighted, T2-weighted and fluid-attenuated inversion recovery magnetic resonance imaging are used the most in various segmentation algorithms. However, there is limited use of perfusion-weighted and diffusion-weighted magnetic resonance imaging. Moreover, we found that the U-Net deep learning technology is cited the most, and has high accuracy (Dice score 0.9) for magnetic resonance imaging-based brain tumour segmentation. Conclusion: U-Net is a promising deep learning technology for magnetic resonance imaging-based brain tumour segmentation. The community should be encouraged to contribute open-access datasets so training, testing and validation of deep learning algorithms can be improved, particularly for diffusion- and perfusion-weighted magnetic resonance imaging, where there are limited datasets available

Click-chemistry mediated synthesis of OTBN-1,2,3-Triazole derivatives exhibiting STK33 inhibition with diverse anti-cancer activities

There is a continuous and pressing need to establish new brain-penetrant bioactive compounds with anti-cancer properties. To this end, a new series of 4′-((4-substituted-4,5-dihydro-1H-1,2,3-triazol-1-yl)methyl)-[1,1′-biphenyl]-2-carbonitrile (OTBN-1,2,3-triazole) derivatives were synthesized by click chemistry. The series of bioactive compounds were designed and synthesized from diverse alkynes and N3-OTBN, using copper (II) acetate monohydrate in aqueous dimethylformamide at room temperature. Besides being highly cost-effective and significantly reducing synthesis, the reaction yielded 91–98 % of the target products without the need of any additional steps or chromatographic techniques. Two analogues exhibit promising anti-cancer biological activities. Analogue 4l shows highly specific cytostatic activity against lung cancer cells, while analogue 4k exhibits pan-cancer anti-growth activity. A kinase screen suggests compound 4k has single-digit micromolar activity against kinase STK33. High STK33 RNA expression correlates strongly with poorer patient outcomes in both adult and pediatric glioma. Compound 4k potently inhibits cell proliferation, invasion, and 3D neurosphere formation in primary patient-derived glioma cell lines. The observed anti-cancer activity is enhanced in combination with specific clinically relevant small molecule inhibitors. Herein we establish a novel biochemical kinase inhibitory function for click-chemistry-derived OTBN-1,2,3-triazole analogues and further report their anti-cancer activity in vitro for the first time

Click-chemistry mediated synthesis of OTBN-1,2,3-Triazole derivatives exhibiting STK33 inhibition with diverse anti-cancer activities

There is a continuous and pressing need to establish new brain-penetrant bioactive compounds with anti-cancer properties. To this end, a new series of 4′-((4-substituted-4,5-dihydro-1H-1,2,3-triazol-1-yl)methyl)-[1,1′-biphenyl]-2-carbonitrile (OTBN-1,2,3-triazole) derivatives were synthesized by click chemistry. The series of bioactive compounds were designed and synthesized from diverse alkynes and N3-OTBN, using copper (II) acetate monohydrate in aqueous dimethylformamide at room temperature. Besides being highly cost-effective and significantly reducing synthesis, the reaction yielded 91–98 % of the target products without the need of any additional steps or chromatographic techniques. Two analogues exhibit promising anti-cancer biological activities. Analogue 4l shows highly specific cytostatic activity against lung cancer cells, while analogue 4k exhibits pan-cancer anti-growth activity. A kinase screen suggests compound 4k has single-digit micromolar activity against kinase STK33. High STK33 RNA expression correlates strongly with poorer patient outcomes in both adult and pediatric glioma. Compound 4k potently inhibits cell proliferation, invasion, and 3D neurosphere formation in primary patient-derived glioma cell lines. The observed anti-cancer activity is enhanced in combination with specific clinically relevant small molecule inhibitors. Herein we establish a novel biochemical kinase inhibitory function for click-chemistry-derived OTBN-1,2,3-triazole analogues and further report their anti-cancer activity in vitro for the first time

A green bio-organic catalyst (taurine) promoted one-pot synthesis of (R/S)-2-thioxo-3,4-dihydropyrimidine(TDHPM)-5-carboxanilides: chiral investigations using circular dichroism and validation by computational approaches

Owing to the massive importance of dihydropyrimidine (DHPMs) scaffolds in the pharmaceutical industry and other areas, we developed an effective and sustainable one-pot reaction protocol for the synthesis of (R/S)-2-thioxo-DHPM-5-carboxanilides via the Biginelli-type cyclo-condensation reaction of aryl aldehydes, thiourea and various acetoacetanilide derivatives in ethanol at 100 °C. In this protocol, taurine was used as a green and reusable bio-organic catalyst. Twenty-three novel derivatives of (R/S)-TDHPM-5-carboxanilides and their structures were confirmed by various spectroscopy techniques. The aforementioned compounds were synthesized via the formation of one asymmetric centre, one new C–C bond, and two new C–N bonds in the final product. All the newly synthesized compounds were obtained in their racemic form with up to 99% yield. In addition, the separation of the racemic mixture of all the newly synthesized compounds was carried out by chiral HPLC (Prep LC), which provided up to 99.99% purity. The absolute configuration of all the enantiomerically pure isomers was determined using a circular dichroism study and validated by a computational approach. With up to 99% yield of 4d, this one-pot synthetic approach can also be useful for large-scale industrial production. One of the separated isomers (4R)-(+)-4S developed as a single crystal, and it was found that this crystal structure was orthorhombic

A green bio-organic catalyst (taurine) promoted one-pot synthesis of (R/S)-2-thioxo-3,4-dihydropyrimidine(TDHPM)-5-carboxanilides: chiral investigations using circular dichroism and validation by computational approaches

Owing to the massive importance of dihydropyrimidine (DHPMs) scaffolds in the pharmaceutical industry and other areas, we developed an effective and sustainable one-pot reaction protocol for the synthesis of (R/S)-2-thioxo-DHPM-5-carboxanilides via the Biginelli-type cyclo-condensation reaction of aryl aldehydes, thiourea and various acetoacetanilide derivatives in ethanol at 100 °C. In this protocol, taurine was used as a green and reusable bio-organic catalyst. Twenty-three novel derivatives of (R/S)-TDHPM-5-carboxanilides and their structures were confirmed by various spectroscopy techniques. The aforementioned compounds were synthesized via the formation of one asymmetric centre, one new C–C bond, and two new C–N bonds in the final product. All the newly synthesized compounds were obtained in their racemic form with up to 99% yield. In addition, the separation of the racemic mixture of all the newly synthesized compounds was carried out by chiral HPLC (Prep LC), which provided up to 99.99% purity. The absolute configuration of all the enantiomerically pure isomers was determined using a circular dichroism study and validated by a computational approach. With up to 99% yield of 4d, this one-pot synthetic approach can also be useful for large-scale industrial production. One of the separated isomers (4R)-(+)-4S developed as a single crystal, and it was found that this crystal structure was orthorhombic

Identifying myocardial infarction using hierarchical template matching–based myocardial strain : algorithm development and usability study

Background: Myocardial infarction (MI; location and extent of infarction) can be determined by late enhancement cardiac magnetic resonance (CMR) imaging, which requires the injection of a potentially harmful gadolinium-based contrast agent (GBCA). Alternatively, emerging research in the area of myocardial strain has shown potential to identify MI using strain values. Objective: This study aims to identify the location of MI by developing an applied algorithmic method of circumferential strain (CS) values, which are derived through a novel hierarchical template matching (HTM) method. Methods: HTM-based CS H-spread from end-diastole to end-systole was used to develop an applied method. Grid-tagging magnetic resonance imaging was used to calculate strain values in the left ventricular (LV) myocardium, followed by the 16-segment American Heart Association model. The data set was used with k-fold cross-validation to estimate the percentage reduction of H-spread among infarcted and noninfarcted LV segments. A total of 43 participants (38 MI and 5 healthy) who underwent CMR imaging were retrospectively selected. Infarcted segments detected by using this method were validated by comparison with late enhancement CMR, and the diagnostic performance of the applied algorithmic method was evaluated with a receiver operating characteristic curve test. Results: The H-spread of the CS was reduced in infarcted segments compared with noninfarcted segments of the LV. The reductions were 30% in basal segments, 30% in midventricular segments, and 20% in apical LV segments. The diagnostic accuracy of detection, using the reported method, was represented by area under the curve values, which were 0.85, 0.82, and 0.87 for basal, midventricular, and apical slices, respectively, demonstrating good agreement with the late-gadolinium enhancement–based detections. Conclusions: The proposed applied algorithmic method has the potential to accurately identify the location of infarcted LV segments without the administration of late-gadolinium enhancement. Such an approach adds the potential to safely identify MI, potentially reduce patient scanning time, and extend the utility of CMR in patients who are contraindicated for the use of GBCA