Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?

OBJECTIVES: Artificial intelligence (AI) has shown promise in improving the performance of fetal ultrasound screening in detecting congenital heart disease (CHD). The effect of giving AI advice to human operators has not been studied in this context. Giving additional information about AI model workings, such as confidence scores for AI predictions, may be a way of further improving performance. Our aims were to investigate whether AI advice improved overall diagnostic accuracy (using a single CHD lesion as an exemplar), and to determine what, if any, additional information given to clinicians optimized the overall performance of the clinician-AI team. METHODS: An AI model was trained to classify a single fetal CHD lesion (atrioventricular septal defect (AVSD)), using a retrospective cohort of 121 130 cardiac four-chamber images extracted from 173 ultrasound scan videos (98 with normal hearts, 75 with AVSD); a ResNet50 model architecture was used. Temperature scaling of model prediction probability was performed on a validation set, and gradient-weighted class activation maps (grad-CAMs) produced. Ten clinicians (two consultant fetal cardiologists, three trainees in pediatric cardiology and five fetal cardiac sonographers) were recruited from a center of fetal cardiology to participate. Each participant was shown 2000 fetal four-chamber images in a random order (1000 normal and 1000 AVSD). The dataset comprised 500 images, each shown in four conditions: (1) image alone without AI output; (2) image with binary AI classification; (3) image with AI model confidence; and (4) image with grad-CAM image overlays. The clinicians were asked to classify each image as normal or AVSD. RESULTS: A total of 20 000 image classifications were recorded from 10 clinicians. The AI model alone achieved an accuracy of 0.798 (95% CI, 0.760-0.832), a sensitivity of 0.868 (95% CI, 0.834-0.902) and a specificity of 0.728 (95% CI, 0.702-0.754), and the clinicians without AI achieved an accuracy of 0.844 (95% CI, 0.834-0.854), a sensitivity of 0.827 (95% CI, 0.795-0.858) and a specificity of 0.861 (95% CI, 0.828-0.895). Showing a binary (normal or AVSD) AI model output resulted in significant improvement in accuracy to 0.865 (P < 0.001). This effect was seen in both experienced and less-experienced participants. Giving incorrect AI advice resulted in a significant deterioration in overall accuracy, from 0.761 to 0.693 (P < 0.001), which was driven by an increase in both Type-I and Type-II errors by the clinicians. This effect was worsened by showing model confidence (accuracy, 0.649; P < 0.001) or grad-CAM (accuracy, 0.644; P < 0.001). CONCLUSIONS: AI has the potential to improve performance when used in collaboration with clinicians, even if the model performance does not reach expert level. Giving additional information about model workings such as model confidence and class activation map image overlays did not improve overall performance, and actually worsened performance for images for which the AI model was incorrect. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Wideband RCS reduction due to plasma generated by radioactive nuclei for cylindrical object.

Radar cross section reduction has been one of the most important research topics in recent years. Plasma-based stealth is a method of reducing the radar cross section, which dampens the electromagnetic waves and reduces the amount of return waves. In this paper, a coating of the radioactive nucleus [Formula: see text] on the surface of the cylinder with a radius of 10 cm is considered and the range of the emitted alpha particles and the electron density generated in the air are obtained using the Geant4 code under standard temperature and pressure conditions. By finite element method solution, the radar cross section of the conductive cylindrical object has been simulated and extracted in the presence and absence of plasma created by alpha-particles. The obtained results show a reduction of 5-8 dB [Formula: see text] in the radar cross section in the frequency range of 2-12 GHz for specific activity source of 1 Ci/[Formula: see text].

Synergy in the heart: RV systolic function plays a key role in optimizing LV performance during exercise.

The right ventricle (RV) is often overlooked in the evaluation of cardiac performance and treatment of left ventricular (LV) heart diseases. However, recent evidence suggests the RV may play an important role in maintaining systemic cardiac function and delivering stroke volume (SV). We used exercise cardiac magnetic resonance and biomechanical modeling to investigate the role of the RV in LV stroke volume regulation. We studied SV augmentation during exercise by pharmacologically inducing negative chronotropy (sHRi) in healthy volunteers and investigating training-induced SV augmentation in endurance athletes. SV augmentation during exercise after sHRi is achieved differently in the two ventricles. In the RV, the larger SV is driven by increasing contraction down to lower end-systolic volume (ESV; P < 0.001). In the LV, SV augmentation is achieved through an increase in end-diastolic volume (EDV; P < 0.001), avoiding contraction to a lower ESV. The same mechanism underlies the enhanced SV response observed in athletes. Changes in atrial area during SV augmentation suggest that the improved LV EDV response is sustained by the larger RV contractions. Using our biomechanical model, we explain this behavior by showing that the RV systolic function-driven regulation of LV SV optimizes the energetic cost of LV contraction and leads to minimization of the total costs of biventricular contraction. In conclusion, this work provides mechanistic understanding of the pivotal role of the RV in optimizing LV SV during exercise. It demonstrates why optimizing RV function needs to become a key part of therapeutic strategies in patients and training for athletes.NEW & NOTEWORTHY The right ventricle appears to have an important impact on maintaining systemic cardiac function and delivering stroke volume. However, its exact role in supporting left ventricular function has so far been unclear. This study demonstrates a new mechanism of ventricular interaction that provides mechanistic understanding of the key importance of the right ventricle in driving cardiac performance.

An observational study to compare the utilisation of computed tomography colonography with optical colonoscopy as the first diagnostic imaging tool in patients with suspected colorectal cancer.

AIM: To evaluate the clinical and cost implications of using computed tomography colonography (CTC) compared to optical colonoscopy (OC) as the initial colonic investigation in patients with low-to-intermediate risk of colorectal cancer (CRC). MATERIALS AND METHODS: A non-randomised, prospective single-centre study recruited 180 participants to compare the cost implications of two clinical pathways used in the diagnosis of low-to-intermediate risk of CRC that differ in the initial diagnostic test, either CTC or OC. Costs were compared using generalised linear models (GLM) and combined with quality-adjusted life years (QALYs, based on the EQ-5D-5L) to estimate cost-effectiveness at 6 months post-recruitment. Secondary outcomes assessed access to care and patient satisfaction. RESULTS: Mean (SD, n) cost at 6 months post-recruitment per participant was £991 (£316, n=105) for the OC group and £645 (£607, n=68) for the CTC group, leading to an estimated cost difference of -£370 (95% CI: -£554, -£185, p<0.001). Assuming a £20,000 willingness-to-pay per QALY threshold, there was a 91.4% probability of CTC being cost-effective at month 6. The utilisation of CTC led to improved access to care, with a shorter mean time from referral from primary care to results (6.3 days difference, p=0.005). No differences in patient satisfaction were detected between both groups. CONCLUSION: The utilisation of CTC as the first-line investigation for patients with low-to-intermediate risk of CRC has the potential to release OC capacity, of pivotal importance for patients more likely to benefit from an invasive diagnostic approach.

SiRNA/DOX lodeded chitosan based nanoparticles: Development, Characterization and in vitro evaluation on A549 lung cancer cell line.

High-mobility group AT-hook2 (HMGA2), involved in epithelial mesenchymal transition (EMT) process, has a pivotal role in lung cancer metastasis. Lung cancer therapy with HMGA2 suppressing small interfering RNA (siRNA) has been introduced recently while doxorubicin (DOX) has been used as a frequent cancer chemotherapy agent. Both reagents have been faced with obstacles in clinic which make them ineffective. NanoParticles (NPs) provided a platform for efficient co delivery of the anticancer drugs. The aim of this study was production and in vitro characterization of different pharmacological groups (siRNA, DOX or siRNA-DOX) of carboxymethyl dextran thrimethyl chitosan nanoparticles (CMDTMChiNPs) on cytotoxicity, gene expression, apoptosis and migration of metastatic lung cancer cell line (A-549). CMDTMChiNPs were synthesized and encapsulated with siRNA, DOX or siRNA-DOX. Then the effects of HMGA2 siRNA and DOX co delivery was assessed in A549 viability and target genes (HMGA2, Ecadherin, vimentin and MMP9) by MTT and real time PCR, respectively. In addition capability of apoptosis induction and anti-migratory features of formulated NPs were analyzed by flowcytometry and wound healing assays. SiRNA-DOX-CMDTM ChiNPs approximate size were 207±5 with poly dispersity index (PDI) and zeta potential of 0.4 and 16.3±0.3, respectively. NPs loaded with DOX and siRNA were the most efficient drug formulations in A549 cell cytotoxicity, altering of EMT markers, apoptosis induction and migration inhibition. Generally our results showed that co delivery of HMGA2 siRNA and DOX by novel designed CMDTMChiNPs is a new therapeutic approach with great potential efficiency for lung cancer treatment.

A novel methodology for personalized simulations of ventricular hemodynamics from noninvasive imaging data.

Current state-of-the-art imaging techniques can provide quantitative information to characterize ventricular function within the limits of the spatiotemporal resolution achievable in a realistic acquisition time. These imaging data can be used to personalize computer models, which in turn can help treatment planning by quantifying biomarkers that cannot be directly imaged, such as flow energy, shear stress and pressure gradients. To date, computer models have typically relied on invasive pressure measurements to be made patient-specific. When these data are not available, the scope and validity of the models are limited. To address this problem, we propose a new methodology for modeling patient-specific hemodynamics based exclusively on noninvasive velocity and anatomical data from 3D+t echocardiography or Magnetic Resonance Imaging (MRI). Numerical simulations of the cardiac cycle are driven by the image-derived velocities prescribed at the model boundaries using a penalty method that recovers a physical solution by minimizing the energy imparted to the system. This numerical approach circumvents the mathematical challenges due to the poor conditioning that arises from the imposition of boundary conditions on velocity only. We demonstrate that through this technique we are able to reconstruct given flow fields using Dirichlet only conditions. We also perform a sensitivity analysis to investigate the accuracy of this approach for different images with varying spatiotemporal resolution. Finally, we examine the influence of noise on the computed result, showing robustness to unbiased noise with an average error in the simulated velocity approximately 7% for a typical voxel size of 2mm(3) and temporal resolution of 30ms. The methodology is eventually applied to a patient case to highlight the potential for a direct clinical translation.

Multidetector computed tomography sizing of bioprosthetic valves: guidelines for measurement and implications for valve-in-valve therapies.

AIM: To describe a technique for bioprosthetic multidetector computed tomography (MDCT) sizing and to compare MDCT-derived values against manufacturer-provided sizing. MATERIALS AND METHODS: Fourteen bioprosthetic stented valves commonly used in the aortic valve position were evaluated using a Philips 256 MDCT system. All valves were scanned using a dedicated cardiac CT protocol with a four-channel electrocardiography (ECG) simulator. Measurements were made of major and minor axes and the area and perimeter of the internal stent using varying reconstruction kernels and window settings. Measurements derived from MDCT (MDCT ID) were compared against the stent internal diameter (Stent ID) as provided by the valve manufacturer and the True ID (Stent ID + insertion of leaflets). All data were collected and analysed using SPSS for Mac (version 21). RESULTS: The mean difference between the MDCT ID and Stent ID was 0.6±1.9 mm (r=0.649, p=0.012) and between MDCT ID and True ID 2.1±2 mm (r=0.71, p=0.005). There was no difference in the major (p=0.90), minor (p=0.87), area (p=0.92), or perimeter (p=0.92) measurements when sharp, standard, and detailed stent kernels were used. Similarly, the measurements remained consistent across differing windowing levels. CONCLUSION: Bioprosthetic stented valves may be reliably sized using MDCT in patients requiring valve-in-valve (VIV) interventions where the valve type and size are unknown. In these cases, clinicians should be aware that MDCT has a tendency to overestimate the True ID size.

Personalization of a cardiac electromechanical model using reduced order unscented Kalman filtering from regional volumes.

Patient-specific cardiac modeling can help in understanding pathophysiology and therapy planning. However it requires to combine functional and anatomical data in order to build accurate models and to personalize the model geometry, kinematics, electrophysiology and mechanics. Personalizing the electromechanical coupling from medical images is a challenging task. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reasonable number of parameters (14 for each ventricle) compared to the available clinical data at the organ level. We propose a personalization strategy from cine MRI data in two steps. We first estimate global parameters with an automatic calibration algorithm based on the Unscented Transform which allows to initialize the parameters while matching the volume and pressure curves. In a second step we locally personalize the contractilities of all AHA (American Heart Association) zones of the left ventricle using the reduced order unscented Kalman filtering on Regional Volumes. This personalization strategy was validated synthetically and tested successfully on eight healthy and three pathological cases.

Benchmarking framework for myocardial tracking and deformation algorithms: an open access database.

In this paper we present a benchmarking framework for the validation of cardiac motion analysis algorithms. The reported methods are the response to an open challenge that was issued to the medical imaging community through a MICCAI workshop. The database included magnetic resonance (MR) and 3D ultrasound (3DUS) datasets from a dynamic phantom and 15 healthy volunteers. Participants processed 3D tagged MR datasets (3DTAG), cine steady state free precession MR datasets (SSFP) and 3DUS datasets, amounting to 1158 image volumes. Ground-truth for motion tracking was based on 12 landmarks (4 walls at 3 ventricular levels). They were manually tracked by two observers in the 3DTAG data over the whole cardiac cycle, using an in-house application with 4D visualization capabilities. The median of the inter-observer variability was computed for the phantom dataset (0.77 mm) and for the volunteer datasets (0.84 mm). The ground-truth was registered to 3DUS coordinates using a point based similarity transform. Four institutions responded to the challenge by providing motion estimates for the data: Fraunhofer MEVIS (MEVIS), Bremen, Germany; Imperial College London - University College London (IUCL), UK; Universitat Pompeu Fabra (UPF), Barcelona, Spain; Inria-Asclepios project (INRIA), France. Details on the implementation and evaluation of the four methodologies are presented in this manuscript. The manually tracked landmarks were used to evaluate tracking accuracy of all methodologies. For 3DTAG, median values were computed over all time frames for the phantom dataset (MEVIS=1.20mm, IUCL=0.73 mm, UPF=1.10mm, INRIA=1.09 mm) and for the volunteer datasets (MEVIS=1.33 mm, IUCL=1.52 mm, UPF=1.09 mm, INRIA=1.32 mm). For 3DUS, median values were computed at end diastole and end systole for the phantom dataset (MEVIS=4.40 mm, UPF=3.48 mm, INRIA=4.78 mm) and for the volunteer datasets (MEVIS=3.51 mm, UPF=3.71 mm, INRIA=4.07 mm). For SSFP, median values were computed at end diastole and end systole for the phantom dataset(UPF=6.18 mm, INRIA=3.93 mm) and for the volunteer datasets (UPF=3.09 mm, INRIA=4.78 mm). Finally, strain curves were generated and qualitatively compared. Good agreement was found between the different modalities and methodologies, except for radial strain that showed a high variability in cases of lower image quality.

Preliminary specificity study of the Bestel-Clément-Sorine electromechanical model of the heart using parameter calibration from medical images.

Patient-specific cardiac modelling can help in understanding pathophysiology and predict therapy effects. This requires the personalization of the geometry, kinematics, electrophysiology and mechanics. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reduced parameter number compared to the available clinical data at the organ level. We propose a preliminary specificity study to determine the relevant global parameters able to differentiate the pathological cases from the healthy controls. To this end, a calibration algorithm on global measurements is developed. This calibration method was tested successfully on 6 volunteers and 2 heart failure cases and enabled to tune up to 7 out of the 14 necessary parameters of the BCS model, from the volume and pressure curves. This specificity study confirmed domain-knowledge that the relaxation rate is impaired in post-myocardial infarction heart failure and the myocardial stiffness is increased in dilated cardiomyopathy heart failures.

Understanding the mechanisms amenable to CRT response: from pre-operative multimodal image data to patient-specific computational models.

This manuscript describes our recent developments towards better understanding of the mechanisms amenable to cardiac resynchronization therapy response. We report the results from a full multimodal dataset corresponding to eight patients from the euHeart project. The datasets include echocardiography, MRI and electrophysiological studies. We investigate two aspects. The first one focuses on pre-operative multimodal image data. From 2D echocardiography and 3D tagged MRI images, we compute atlas based dyssynchrony indices. We complement these indices with presence and extent of scar tissue and correlate them with CRT response. The second one focuses on computational models. We use pre-operative imaging to generate a patient-specific computational model. We show results of a fully automatic personalized electromechanical simulation. By case-per-case discussion of the results, we highlight the potential and key issues of this multimodal pipeline for the understanding of the mechanisms of CRT response and a better patient selection.

Patient specific fluid-structure ventricular modelling for integrated cardiac care.

Cardiac diseases represent one of the primary causes of mortality and result in a substantial decrease in quality of life. Optimal surgical planning and long-term treatment are crucial for a successful and cost-effective patient care. Recently developed state-of-the-art imaging techniques supply a wealth of detailed data to support diagnosis. This provides the foundations for a novel approach to clinical planning based on personalisation, which can lead to more tailored treatment plans when compared to strategies based on standard population metrics. The goal of this study is to develop and apply a methodology for creating personalised ventricular models of blood and tissue mechanics to assess patient-specific metrics. Fluid-structure interaction simulations are performed to analyse the diastolic function in hypoplastic left heart patients, who underwent the first stage of a three-step surgical palliation and whose condition must be accurately evaluated to plan further intervention. The kinetic energy changes generated by the blood propagation in early diastole are found to reflect the intraventricular pressure gradient, giving indications on the filling efficiency. This suggests good agreement between the 3D model and the Euler equation, which provides a simplified relationship between pressure and kinetic energy and could, therefore, be applied in the clinical context.

Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: a preliminary clinical validation.

Cardiac resynchronisation therapy (CRT) is an effective treatment for patients with congestive heart failure and a wide QRS complex. However, up to 30% of patients are non-responders to therapy in terms of exercise capacity or left ventricular reverse remodelling. A number of controversies still remain surrounding patient selection, targeted lead implantation and optimisation of this important treatment. The development of biophysical models to predict the response to CRT represents a potential strategy to address these issues. In this article, we present how the personalisation of an electromechanical model of the myocardium can predict the acute haemodynamic changes associated with CRT. In order to introduce such an approach as a clinical application, we needed to design models that can be individualised from images and electrophysiological mapping of the left ventricle. In this paper the personalisation of the anatomy, the electrophysiology, the kinematics and the mechanics are described. The acute effects of pacing on pressure development were predicted with the in silico model for several pacing conditions on two patients, achieving good agreement with invasive haemodynamic measurements: the mean error on dP/dt(max) is 47.5±35mmHgs(-1), less than 5% error. These promising results demonstrate the potential of physiological models personalised from images and electrophysiology signals to improve patient selection and plan CRT.

Evaluation of a real-time hybrid three-dimensional echo and X-ray imaging system for guidance of cardiac catheterisation procedures.

Minimally invasive cardiac surgery is made possible by image guidance technology. X-ray fluoroscopy provides high contrast images of catheters and devices, whereas 3D ultrasound is better for visualising cardiac anatomy. We present a system in which the two modalities are combined, with a trans-esophageal echo volume registered to and overlaid on an X-ray projection image in real-time. We evaluate the accuracy of the system in terms of both temporal synchronisation errors and overlay registration errors. The temporal synchronisation error was found to be 10% of the typical cardiac cycle length. In 11 clinical data sets, we found an average alignment error of 2.9 mm. We conclude that the accuracy result is very encouraging and sufficient for guiding many types of cardiac interventions. The combined information is clinically useful for placing the echo image in a familiar coordinate system and for more easily identifying catheters in the echo volume.

Biophysical modeling to simulate the response to multisite left ventricular stimulation using a quadripolar pacing lead.

BACKGROUND: Response to cardiac resynchronization therapy (CRT) is reduced in patients with posterolateral scar. Multipolar pacing leads offer the ability to select desirable pacing sites and/or stimulate from multiple pacing sites concurrently using a single lead position. Despite this potential, the clinical evaluation and identification of metrics for optimization of multisite CRT (MCRT) has not been performed. METHODS: The efficacy of MCRT via a quadripolar lead with two left ventricular (LV) pacing sites in conjunction with right ventricular pacing was compared with single-site LV pacing using a coupled electromechanical biophysical model of the human heart with no, mild, or severe scar in the LV posterolateral wall. RESULT: The maximum dP/dt(max) improvement from baseline was 21%, 23%, and 21% for standard CRT versus 22%, 24%, and 25% for MCRT for no, mild, and severe scar, respectively. In the presence of severe scar, there was an incremental benefit of multisite versus standard CRT (25% vs 21%, 19% relative improvement in response). Minimizing total activation time (analogous to QRS duration) or minimizing the activation time of short-axis slices of the heart did not correlate with CRT response. The peak electrical activation wave area in the LV corresponded with CRT response with an R(2) value between 0.42 and 0.75. CONCLUSION: Biophysical modeling predicts that in the presence of posterolateral scar MCRT offers an improved response over conventional CRT. Maximizing the activation wave area in the LV had the most consistent correlation with CRT response, independent of pacing protocol, scar size, or lead location.

Detection of intracoronary thrombus by magnetic resonance imaging in patients with acute myocardial infarction.

BACKGROUND: Persistent intracoronary thrombus after plaque rupture is associated with an increased risk of subsequent myocardial infarction and mortality. Coronary thrombus is usually visualized invasively by x-ray coronary angiography. Non-contrast-enhanced T1-weighted magnetic resonance (MR) imaging has been useful for direct imaging of carotid thrombus and intraplaque hemorrhage by taking advantage of the short T1 of methemoglobin present in acute thrombus and intraplaque hemorrhage. The aim of this study was to investigate the use of non-contrast-enhanced MR for direct thrombus imaging (MRDTI) in patients with acute myocardial infarction. METHODS AND RESULTS: Eighteen patients (14 men; age, 61±9 years) underwent MRDTI within 24 to 72 hours of presenting with an acute coronary syndrome before invasive x-ray coronary angiography; MRDTI was performed with a T1-weighted, 3-dimensional, inversion-recovery black-blood gradient-echo sequence without contrast administration. Ten patients were found to have intracoronary thrombus on x-ray coronary angiography (left anterior descending, 4; left circumflex, 2; right coronary artery, 4; and right coronary artery-posterior descending artery, 1), and 8 had no visible thrombus. We found that MRDTI correctly identified thrombus in 9 of 10 patients (sensitivity, 91%; posterior descending artery thrombus not detected) and correctly classified the control group in 7 of 8 patients without thrombus formation (specificity, 88%). The contrast-to-noise ratio was significantly greater in coronary segments containing thrombus (n=10) compared with those without visible thrombus (n=131; mean contrast-to-noise ratio, 15.9 versus 2.6; P<0.001). CONCLUSION: Use of MRDTI allows selective visualization of coronary thrombus in a patient population with a high probability of intracoronary thrombosis.

Whole heart segmentation of cardiac MRI using multiple path propagation strategy.

Automatic segmentation of cardiac MRI is an important but challenging task in clinical study of cardiac morphology. Recently, fusing segmentations from multiple classifiers has been shown to achieve more accurate results than a single classifier. In this work, we propose a new strategy, MUltiple Path Propagation and Segmentation (MUPPS), in contrast with the currently widely used multi-atlas propagation and segmentation (MAPS) scheme. We showed that MUPPS outperformed the standard MAPS in the experiment using twenty-one in vivo cardiac MR images. Furthermore, we studied and compared different path selection strategies for the MUPPS, to pursue an efficient implementation of the segmentation framework. We showed that the path ranking scheme using the image similarity after an affine registration converged faster and only needed eleven classifiers from the atlas repository. The fusion of eleven propagation results using the proposed path ranking scheme achieved a mean Dice score of 0.911 in the whole heart segmentation and the highest gain of accuracy was obtained from myocardium segmentation.

Coupled personalisation of electrophysiology models for simulation of induced ischemic ventricular tachycardia.

Despite recent efforts in cardiac electrophysiology modelling, there is still a strong need to make macroscopic models usable in planning and assistance of the clinical procedures. This requires model personalisation i.e. estimation of patient-specific model parameters and computations compatible with clinical constraints. Fast macroscopic models allow a quick estimation of the tissue conductivity, but are often unreliable in prediction of arrhythmias. On the other side, complex biophysical models are quite expensive for the tissue conductivity estimation, but are well suited for arrhythmia predictions. Here we present a coupled personalisation framework, which combines the benefits of the two models. A fast Eikonal (EK) model is used to estimate the conductivity parameters, which are then used to set the parameters of a biophysical model, the Mitchell-Schaeffer (MS) model. Additional parameters related to Action Potential Duration (APD) and APD restitution curves for the tissue are estimated for the MS model. This framework is applied to a clinical dataset provided with an hybrid X-Ray/MR imaging on an ischemic patient. This personalised MS Model is then used for in silico simulation of clinical Ventricular Tachycardia (VT) stimulation protocol to predict the induction of VT. This proof of concept opens up possibilities of using VT induction modelling directly in the intervention room, in order to plan the radio-frequency ablation lines.